1. Computational and Systems Biology
  2. Developmental Biology

Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity

  1. Tarun Kumar
  2. Leo Blondel
  3. Cassandra G Extavour  Is a corresponding author
  1. Department of Organismic and Evolutionary Biology, Harvard University, United States
  2. Department of Molecular and Cellular Biology, Harvard University, United States
https://doi.org/10.7554/eLife.54082
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  1. Tarun Kumar
  2. Leo Blondel
  3. Cassandra G Extavour
(2020)
Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity
eLife 9:e54082.
https://doi.org/10.7554/eLife.54082
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Abstract

Understanding the genetic regulation of organ structure is a fundamental problem in developmental biology. Here, we use egg-producing structures of insect ovaries, called ovarioles, to deduce systems-level gene regulatory relationships from quantitative functional genetic analysis. We previously showed that Hippo signalling, a conserved regulator of animal organ size, regulates ovariole number in Drosophila melanogaster. To comprehensively determine how Hippo signalling interacts with other pathways in this regulation, we screened all known signalling pathway genes, and identified Hpo-dependent and Hpo-independent signalling requirements. Network analysis of known protein-protein interactions among screen results identified independent gene regulatory sub-networks regulating one or both of ovariole number and egg laying. These sub-networks predict involvement of previously uncharacterised genes with higher accuracy than the original candidate screen. This shows that network analysis combining functional genetic and large-scale interaction data can predict function of novel genes regulating development.

Introduction

The final shape and size of an organ is critical to organismal function and viability. Defects in human organ morphology cause a multitude of pathologies, including cancers, organ hypertrophies and atrophies (e.g. Yang and Xu, 2011). It is thus critical to understand the regulatory mechanisms underlying the stereotypic shape and size of organs. To this end, assessing the genetic regulation of size is significantly facilitated by using quantifiable changes in organ size and shape.

The Drosophila melanogaster female reproductive system is a useful paradigm to study quantitative anatomical traits. In these organs, the effects of multiple genes and the environment combine to produce a quantitative phenotype: a species-specific average number of egg-producing ovarian tubes called ovarioles. Fruit fly ovaries can contain as few as one and as many as 50 ovarioles per ovary, depending on the species (Kambysellis and Heed, 1971; King, 1970; Markow et al., 2009; Sarikaya et al., 2019), with each ovariole capable of producing eggs. Ovariole number, therefore, may affect the reproductive fitness of Drosophila species by determining the potential of an adult female to produce eggs (Klepsatel et al., 2013b; R' kha et al., 1997). While ovariole number within a species can vary across temperatures (Azevedo et al., 1996), altitudinal and latitudinal clines (Capy et al., 1994; David and Bocquet, 1975), under constant environmental conditions ovariole number is highly stereotypic (Capy et al., 1993; Klepsatel et al., 2013a; R'Kha et al., 1991; R' kha et al., 1997). The reproducibility of ovariole number thus indicates a strong genetic component (Sarikaya et al., 2019). Genome wide association studies and quantitative trait locus mapping have demonstrated that the ovariole number is a highly polygenic trait (Bergland et al., 2008; Lobell et al., 2017; Orgogozo et al., 2006; Wayne et al., 2001; Wayne et al., 1997; Wayne and McIntyre, 2002). In contrast, functional genetic studies have identified only a small number of genes whose activity regulates ovariole number (discussed below). Thus, the complexity of the genetic regulation of this important trait remains largely unknown.

The determination of ovariole number in D. melanogaster occurs during late larval and pupal development (King et al., 1968). Each ovariole in the adult fly arises from a single primordial structure called a terminal filament (TF), which forms in the late third instar larval ovary (Godt and Laski, 1995) by convergent extension (Keller, 2006) of the terminal filament cells (TFCs) (Godt and Laski, 1995; Sahut-Barnola et al., 1996). TFCs are first specified from an anterior population of somatic cells in the larval ovary by the expression of transcription factors including Bric-à-brac 1/2 (bric-à-brac 1/2; bab1/2) and Engrailed (engrailed; en) (Godt and Laski, 1995; Sahut-Barnola et al., 1995). Initially a loosely arranged group in the anterior of the larval ovary, TFCs undergo morphogenetic movements to give rise to the ordered columns of cells that are TFs. Cell intercalation during convergent extension is dependent on the actin regulators Cofilin (twinstar; tsr) and the large Maf factor Traffic Jam (traffic jam; tj), and on E-cadherin dependent adhesion (Chen et al., 2001; Godt and Laski, 1995). Regulation of ovariole number is thus largely dependent on the specification of the TFCs and their rearrangement into TFs (Sarikaya and Extavour, 2015).

We previously showed that the regulation of both TFC and TF number is dependent on the Hippo signalling pathway (Sarikaya and Extavour, 2015), a pan-metazoan regulator of organ and tissue size (Hilman and Gat, 2011; Sebé-Pedrós et al., 2012). At the core of the Hippo kinase cascade are two protein kinases, Hippo (hippo; hpo) and Warts (warts; wts), which prevent the nuclear localisation of the transcriptional co-activator Yorkie (yorkie; yki). Yki and the transcription factor Scalloped (scalloped; sd) together initiate the transcription of multiple target genes, including those that promote cell proliferation and survival. In the D. melanogaster larval ovary, loss of Hpo in the somatic cells causes an increase in nuclear Yki, leading to an increase in TFCs, TFs, ovariole number and egg laying in adults (Sarikaya and Extavour, 2015).

Production of fertile eggs from a stereotypic number of ovarioles requires a spatially and temporally coordinated interplay of signalling between the somatic and germ line cells of the ovary. Thus, signalling amongst somatic and germ line cells in the larval ovary is crucial to all stages of ovarian development (Ables and Drummond-Barbosa, 2017; Gilboa, 2015; Green et al., 2011; LaFever and Drummond-Barbosa, 2005; LaFever et al., 2010; Sarikaya and Extavour, 2015). For instance, disruptions in insulin or Tor signalling affect both somatic and germ line cell proliferation (Gancz and Gilboa, 2013; Green and Extavour, 2012; Hsu and Drummond-Barbosa, 2009; LaFever and Drummond-Barbosa, 2005; LaFever et al., 2010; Sarikaya et al., 2012). Similarly, ecdysone pulses from the prothoracic gland regulate the timely differentiation of the primordial germ cells (PGCs) and the somatic TFCs (Gancz et al., 2011; Hodin and Riddiford, 1998; Hodin and Riddiford, 2000b). Both Hpo and ecdysone signalling also control the proportion of germ line to somatic cells by differentially regulating proliferation of both cell types (Gancz et al., 2011; Sarikaya and Extavour, 2015).

Although it is clear that genes function together in regulatory networks (Gonzalez and Kann, 2012), determining how the few genes functionally verified as required for ovariole development and function work together to coordinate ovariole number and ovarian function more generally is a challenge, because most genes or pathways have been considered individually. An alternative approach that is less often applied to animal developmental genetics, is a systems biology representation of complex biological systems as networks (Barabási and Albert, 1999; Watts and Strogatz, 1998). Protein-protein interaction networks (PINs) are such an example (Albert and Barabási, 2002). The availability of high-throughput molecular biology datasets from, for example, yeast two-hybrid, protein CHiP and microarrays has allowed for the emergence of large scale interaction networks representing both functional and physical molecular interactions (Barabási and Oltvai, 2004; Berger et al., 2007; Giot et al., 2003; Gonzalez and Kann, 2012).

With ample evidence that signalling in the ovary can affect ovarian development, but few genes functionally verified to date, we aimed to identify novel regulators of ovariole development by functionally testing all known members of all characterized D. melanogaster signalling pathways. We used tissue-specific RNAi to systematically knock down 463 genes in the larval ovary and looked for modifiers of the hpo loss of function egg laying and ovariole number phenotypes. To analyse the results of this phenotypic analysis, we used topology-driven network analysis to identify genetic networks regulating these phenotypes, thus generating hypotheses about the relationships between these networks. With this systems biology approach, we identify not only signalling pathway genes, but also previously untested genes that affect these reproductive traits. Functional testing showed that these novel genes affect ovariole number and/or egg laying, providing us with a novel in silico method to identify target genes that affect ovarian development and function. We use these findings to propose putative developmental regulatory networks underlying one or both of ovariole formation and egg laying.

Results

An RNAi modifier screen for signalling pathway involvement in ovariole number

To systematically ascertain the function of signalling pathway genes and their interactions with Hippo signalling in the development of the D. melanogaster ovary, we first curated a list of all known and predicted signalling genes (Gramates et al., 2017; Kanehisa et al., 2010; Mbodj et al., 2013). We identified 475 genes belonging to the 14 developmental signalling pathways characterised in D. melanogaster (Table 1; Supplementary file 1), and obtained UAS:RNAi lines for 463 of these genes from the Vienna Drosophila RNAi centre (VDRC) or the TRiP collections at the Bloomington Drosophila Stock centre (BDSC) (all D. melanogaster genetic lines used are listed in Materials and methods).

Table 1
Number of candidate genes tested in each signalling pathway.

Candidate genes are grouped by their reported roles in one or more signalling pathways based on published literature. Genes in this list are not necessarily unique to a single pathway, but rather may function in more than one signalling pathway. The list of specific genes per pathway that were included in the screen for functional analysis (Figure 1) is found in the Supplementary file 1.

Signalling pathwayNumber of genes in screen
EGF45
FGF25
FOXO67
Hippo60
JAK/STAT31
JNK28
MAPK29
Notch48
SHH54
TGF B52
Toll36
VEGF17
Wnt125
mTOR36

We previously showed that reducing the levels of hpo in the somatic cells of the larval ovary using traffic jam Gal4 (tj:Gal4) driving hpo[RNAi] increased both ovariole number and egg laying of adult female flies (Sarikaya and Extavour, 2015). To identify genes that modify these phenotypes, we used tj:Gal4 to drive simultaneous hpo[RNAi] and RNAi against a signalling candidate gene, and quantified the phenotypic change (Figure 1a–d). We observed that on driving two copies of hpo[RNAi] using tj:Gal4, we obtained a further increase in both egg laying and ovariole number (Figure 1e). This indicates that ovaries have further potential to increase ovariole number and egg laying beyond the increase induced by tj:Gal4 driving one copy of hpo[RNAi], and that tj:Gal4 can drive the expression of two RNAi constructs, indicating that our screen could identify both enhancers and suppressors of the tj:Gal4 >hpo[RNAi] phenotype.

Figure 1 with 1 supplement see all
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Screen methodology.

(a,b,c) Diagrammatic representation of screen workflow. (d) Distributions of results of genes in the three screens. n = number of genes tested in each screen (see also Table 2). (e) Total eggs laid by three female flies over five days (left panel) and ovariole number (right panel) of Oregon R (top row), tj:Gal4 driving one copy of UAS:hpo[RNAi] (middle row), and tj:Gal4 driving two copies of UAS:hpo[RNAi] (bottom row), showing that, the previously reported tj:Gal4 >hpo[RNAi] ovariole number and egg laying phenotypes (Sarikaya and Extavour, 2015) can be modified by further UAS:RNAi-mediated gene knockdown. Distribution of egg laying and ovariole number of controls in each screen batch is illustrated in Figure 1—figure supplement 1.

We proceeded to identify modifiers of the tj:Gal4 >hpo[RNAi] phenotype by crossing males of each of the 463 candidate genes RNAis individually with tj:Gal4 >hpo[RNAi] females, and performing three phenotypic screens on the offspring. In the first screen (Figure 1a), we measured egg laying of three F1 female offspring (tj:Gal4 >hpo[RNAi], signalling candidate[RNAi]) over five days. To address batch variation (Figure 1—figure supplement 1), we standardised egg laying measurements by calculating the Z scores (Zgene = number of standard deviations from the mean) for each candidate line relative to its batch controls. 190 genes had an egg laying |Zgene| below 1. Previous studies have shown that the egg laying of newly eclosed adult mated females correlates with ovariole number during the first five days (Klepsatel et al., 2013b). We therefore eliminated these 190 genes from subsequent screening, because the change in egg laying was so modest that we considered these candidates were unlikely to show changes in ovariole number when compared to controls.

In the second screen (Figure 1b), we measured egg laying in a wild-type background (tj >signalling candidate[RNAi]) for the 273 remaining candidate genes. For the third screen (Figure 1c), we quantified the ovariole number of tj:Gal4 >hpo[RNAi], signalling candidate[RNAi] F1 adult females for the same 273 candidate genes. To choose candidates from the second and third screens for further study, we wished to account for the fact that the two screens had different effective numbers of data points. This was because egg laying data were obtained from individual vials of three females over five days, while ovariole numbers were obtained from 20 ovaries from ten females (see Materials and methods). We therefore selected the 67 genes with a |Zgene| above two for ovariole number (Figure 1c and d; Table 2), and the 49 genes with a more conservative |Zgene| above five for egg laying (Figure 1a, b and d; Table 2), for a total of 116 positive candidates for subsequent analyses.

Table 2
Results of the three functional genetic screens.

Number of genes tested in each screen and cumulative results. ‘Negative effect’ corresponds to a reduction in eggs laid or number of ovarioles below the Z score (Zgene) threshold for each phenotype. ‘Positive effect’ indicates an increase above the set Zgene thresholds. Zgene thresholds for each category in each screen are indicated in brackets. The primary filter of |Zgene| < 1 was applied only to the hpo[RNAi] Egg Laying screen shown in Figure 1a. The list of specific genes that exceeded our chosen Zgene thresholds for each scored phenotype (Figure 1) and were therefore considered to have a positive or negative effect on the phenotype, is found in the Supplementary file 1. The 12 genes for which RNAi stocks were unavailable at the time of testing are listed in Table 3.

Egg laying screensHpo[RNAi] Egg Laying
(Figure 1a)		Egg laying
(Figure 1b)		Ovariole number screenHpo[RNAi] Ovariole
Number (Figure 1c)
RNAi stocks unavailable120RNAi stocks unavailable0
Primary filter (|Zgene| < 1)190N/APrimary filter (|Zgene| < 1)N/A
No effect (−5 < |Zgene| < 5)214224No effect (−2< |Zgene| < 2)206
Negative effect (Zgene < −5)4844Negative effect (Zgene < −2)54
Positive effect (Zgene > 5)115Positive effect (Zgene > 2)13
Total475273Total273

Ovariole number is weakly correlated with egg laying

Standardisation of the results from the three screens using Z scores allowed us to compare the effects of individual genes on one or both of egg laying and ovariole number. We performed a pairwise comparison of the Zgene values for all combinations of screens, and considered genes with |Zgene| values that were above the thresholds set for the phenotype in each screen (above two for ovariole number, above five for egg laying; green dots in Figure 2a–c). Across all three screens, loss of function of our positive candidates yielded reductions in ovariole number and egg laying more commonly than increases (Figure 2a–c). Comparing the |Zgene| values of egg laying and ovariole number of tj:Gal4 >hpo[RNAi], signalling candidate[RNAi] adult females revealed that genes that caused a change in egg laying did not always similarly affect ovariole number, and vice versa (Figure 2a). We therefore hypothesise that egg laying and ovariole number may be regulated by genetically separable mechanisms. This hypothesis notwithstanding, we observed a weak but statistically significant correlation between egg laying and ovariole number (p=1e10−5; Figure 2d), and this correlation was most significant in adult females that had a drastic reduction in both phenotypes (Figure 2a).

Figure 2
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Relationship between Egg Laying and Ovariole Number phenotypes generated in the screens.

(a) Scatter plots of the Z score for each gene (Zgene) of egg laying versus the ovariole number of adult tj >hpo[RNAi], candidate[RNAi] females. (b) Scatter plots of the Z score for each gene (Zgene) of egg laying of adult tj >candidate[RNAi] females versus the ovariole number of adult tj >hpo[RNAi], candidate[RNAi] females. (c) Scatter plots of the Z score for each gene (Zgene) of egg laying of adult tj >candidate[RNAi] females versus egg laying of adult tj >hpo[RNAi], candidate[RNAi] females. In a, b and c, bar graphs on the top and right sides of each panel show the distribution of genes in each axis of the adjacent scatter plots. Green dots = genes that meet the Zgene threshold for the indicated phenotype. Grey dots = genes that do not meet the Zgene threshold for the indicated phenotype. Dark grey dotted lines = thresholds for each phenotype: |Zgene| > 5 for Egg Laying and |Zgene| > 2 for Ovariole Number. In a and c, the white vertical bar removes all genes in the tj >hpo[RNAi], candidate[RNAi] with a |Zgene| < 1 for egg laying. These genes were not measured in the other two conditions and are therefore not represented in the scatter plots. (d) Correlation between non-zero Ovariole Number and Egg Laying values.

No single signalling pathway dominates regulation of ovariole number or egg laying

We found that at least some genes from all tested signalling pathways could affect both egg laying and ovariole number (Figure 3). To determine if some pathway(s) appeared to play a more important role than others in these processes, we asked whether any of our screens were enriched for genes from a specific signalling pathway. To measure enrichment, we compared the distribution of individual pathway genes among the positive candidates in each screen, to a randomly sampled null distribution of pathway genes among a group of the same number of genes randomly selected from our curated list of 463 signalling genes (Figure 3a). Involvement of a pathway in the regulation of a phenotype would be reflected in a difference between the representation of pathway genes in an experimentally derived list and a randomly selected group of signalling genes. We found that rather than only one or a few pathways showing functional evidence of regulating ovariole number or egg laying, nearly all pathways affected both phenotypes (Figure 3a). We further tested this result by calculating the hypergeometric p-value for the enrichment of each signalling pathway, in each of the three groups of genes. Consistent with the results of the random sampling approach (Figure 3a), we found that most pathway members were not significantly enriched for egg laying or ovariole number phenotypes (Figure 3b). The absence of significant enrichment of any specific pathway is not simply attributable to the pool of genes that were screened, because our experimental manipulations of ovariole number and egg laying did cause a change in the distribution of signalling pathway members (Figure 3—figure supplement 1). Instead, both phenotypes appeared to be regulated by members of most or all signalling pathways (Figure 3). The only two exceptions to this trend were a greater than twofold enrichment of (1) genes from the Notch signalling pathway in the regulation of ovariole number (p-value<0.05, pink bar in Figure 3a,b), and (2) members of the Hedgehog (Hh) signalling pathway in the regulation of Hippo-dependent egg laying (p-value<0.05, brown bar in Figure 3a and b; Figure 3—figure supplement 2). In summation, our analyses of the enrichment of signalling pathways within the different screens indicated that both ovariole number and egg laying are regulated by genes from nearly all described animal signalling pathways (Figure 3a), rather than being dominated by any single pathway.

Figure 3 with 2 supplements see all
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Enrichment of genes of individual signalling pathways among the experimentally obtained positive candidates of each screen.

(a) Enrichment/depletion analysis to identify over- or under- represented members of individual signalling pathways among positive candidates of each screen. Positive Z scores represent an enrichment, and negative Z scores represent depletion, of genes of a pathway among those genes that experimentally affected the phenotype enrichment and depletion are defined relative to a null distribution of the expected number of members of a signalling pathway among a group containing the same number of randomly selected signalling genes. (b) Fold enrichment and hypergeometric p-value calculation to identify over- or under-representation of the genes of a pathway in each screen. Significantly enriched pathways (coloured bars: brown = Hedgehog; pink = Notch) are defined by having a hypergeometric p-value less than 0.05. Enrichment/depletion analysis of the 273 signalling pathway genes above the threshold |Zgene| > 1 (Figure 1a) before screening is illustrated in Figure 3—figure supplement 1. Figure 3—figure supplement 2 compares the Zgene of egg laying of adult females of tj >hpo[RNAi],candidate[RNAi] plotted against Zgene of egg laying of tj >candidate[RNAi] adult females displayed by pathway.

Comparing the results of the Egg Laying screens performed in a wild type background (Figure 1b) or in a hpo[RNAi] background (Figure 1a), revealed that most of the genes that met a threshold of |Zgene| > 5 in one screen, did not meet that threshold in the other screen (Figure 2c). This result suggests the existence of both Hippo-dependent and Hippo-independent mechanisms of regulation of egg laying. The interpretations of separable Hippo-dependent and -independent regulation of egg laying, and of the separable regulation of ovariole number and egg laying, were supported by the results of the network analysis described in the following section.

Centrality of genes in the ovarian protein-protein interaction networks can predict the likelihood of loss of function phenotypic effects

The finding that these reproductive traits were regulated by the genes of all signalling pathways led us to consider the broader topology of putative gene regulatory networks in the analysis of our data. Previously characterised genes in the ovary are often pleiotropic and can regulate both ovariole number and egg laying (Gilboa, 2015; Sarikaya and Extavour, 2015). As with proteins in a linear pathway, proteins in a protein-protein interaction network (PIN) are more likely to function in conjunction with genes that are connected to them within the network (e.g. Ideker and Sharan, 2008; Jeong et al., 2001). Centrality is one measure of the connectedness of a gene in the PIN and can be used to identify the most important functional centres within a protein network (Hahn and Kern, 2005; Ma'ayan, 2011). Most centrality measures use path length, which is a measure of the number of other proteins required to link any two proteins in the network. Here, we used four commonly used metrics to quantify gene centrality, each measuring slightly different properties (Jalili et al., 2016; Koschützki and Schreiber, 2008). (1) Degree centrality is proportional to the number of proteins that a given protein directly interacts with. (2) Betweenness centrality measures the number of shortest paths amongst all the shortest paths between all pairs of proteins that require passing through a particular protein. (3) Closeness centrality measures the average shortest path that connects a given protein to all other proteins in the network. (4) Eigenvector centrality is a measure of the closeness of a given protein to other highly connected proteins within the network.

We hypothesised that if the candidate genes we identified in our screen as playing roles in ovarian function worked together as a PIN, then the degree of centrality of a gene might be an indicator of function. To test this hypothesis, we first compiled a PIN consisting of all described interactions between D. melanogaster proteins, from the combination of publicly available protein-protein interaction (PPI) studies in the DroID database (see Materials and methods). We then calculated the four centrality measures described above for all genes within the D. melanogaster PIN (Supplementary file 1). We rank ordered only the genes tested in each screen by their score for each centrality measure, and asked whether their rank order correlated with the results of the screen, plotting these results as a receiver operating characteristic (ROC) curve. Positive correlations between centrality (a continuous variable) and phenotype (a binary variable: above or below the |Zgene| threshold) are reflected in an area under the curve (AUC) of more than 0.5. We found that the higher the centrality score, the greater the likelihood that a gene had |Zgene| values above our threshold for effects on ovariole number and egg laying (Figure 4a; Figure 4—source data 1). This supports the premise that the positive candidates identified in our screen function together as a network in the regulation of either ovariole number or egg laying. Interestingly, while the centrality of genes did predict whether a gene would affect our phenotypes of interest, it could only weakly predict the strength of that effect (p-value<0.05 in Figure 4—figure supplement 1).

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Screened genes function as a network.

(a) Receiver operating characteristic (ROC) curves of genes ordered by rank for each of four network centrality metrics (Betweenness centrality, Eigenvector centrality, Closeness centrality and Degree centrality) versus a binary outcome (above or below Z score threshold) for each of the three screens. For each screen and metric, the Area Under the Curve (AUC) is >0.5 (Figure 4—source data 1). (b) Genes whose |Zgene| value was above the threshold (green dots; Table 2) in all three screens were assigned to the Core seed list. (c) Genes whose |Zgene| value was above the threshold (green dots; Table 2) in each screen were assigned to the corresponding seed list. Figure 4—source data 1 Tabulates the AUC values for the ROC curves for each centrality measure for the three screens (a). Figure 4—figure supplement 1 Compares the distribution of Zgene scores of the positive candidate genes for the first and fifth quintile genes sorted by their centrality metrics. Figure 4—figure supplement 2 compares the network metrics of the four gene lists in b to two null distribution of genes selected from the PIN.

Figure 4—source data 1

Area under the curve (AUC) of ROC curves.

AUC values for the ROC curves for each centrality measure for the three screens (Figure 4a). AUC values range from 0 to 1. A score above 0.5 indicates a positive correlation between the continuous variable (centrality) and the binary variable (above or below the Z score threshold). A score of 0.5 or less indicates no correlation between the variables.

https://cdn.elifesciences.org/articles/54082/elife-54082-fig4-data1-v2.docx

Genes regulating egg laying and ovariole number regulation form non-random gene interaction networks

The centrality analyses above suggested that the genes implicated in ovariole number and egg laying displayed characteristics of a functional network. PINs can often be further sorted into a collection of sub-networks. A sub-network is a smaller selection of proteins from the PIN. Examples of such sub-networks could be proteins within the same subcellular organelle (Foster et al., 2006) or genes that are expressed at the same time (Spellman et al., 1998), thus making them likely to function together (Srinivasan et al., 2007). A putative module is a sub-network that can perform regulatory functions as a unit, independent of other sub-networks, and has key measurable features (Barabási and Oltvai, 2004; Hartwell et al., 1999; Ravasz et al., 2002; Yook et al., 2004). Genes and interactions between genes are not mutually exclusive to such putative modules and can be shared between putative modules. We therefore asked if our sub-networks, consisting of genes that showed similar mutant phenotypes, might display features of modularity. To determine whether genes that were implicated in regulation of ovariole number and egg laying interacted with each other in specific groups more than would be expected by chance, we created four lists of genes, called ‘seed’ lists, based on their individual phenotypic effects based on our screen results: (1) the core seed list, including genes positive in all three screens (Figure 4b); (2) the egg laying seed list, including genes positive in the wild type background egg laying screen (Figure 1b; Figure 4c); (3) the hpo[RNAi] egg laying seed list, including genes positive in the hpo[RNAi] background egg laying screen (Figure 1a; Figure 4c); and (4) the hpo[RNAi] ovariole seed list, including genes positive in the hpo[RNAi] background ovariole number screen (Figure 1c; Figure 4c). Interestingly, the core seed list, comprising genes that affected all three measured phenotypes, only consisted of genes that caused a reduction in both ovariole number and egg laying (Figure 4b).

We then asked whether the members of these four seed lists were more connected than would be expected by chance. In other words, we formally tested them for modularity as defined above. Meeting our criteria for modularity would suggest that the genes in these phenotypically separated seed lists might operate together as putative functional modules within the Drosophila PIN. We performed our modularity test using four commonly measured network metrics: (1) Largest Connected Component (LCC) (the number of proteins or nodes connected together by at least one interaction), (2) network density (the relative number of edges as compared to the theoretical maximum), (3) total number of edges, and (4) average shortest path (average of the minimum distances connecting any two proteins). We considered a sub-network to show modular features if they showed most of the following properties: higher LCC, higher network density, more edges, and shorter average shortest path length, when compared to a similarly sized, randomly sampled selection of genes from the PIN.

To determine whether these criteria would correctly identify signalling genes, which are known to function together as a module, we measured these four parameters in the original set of genes (all signalling genes) used in this study (Table 1). We found that the signalling genes display features of modularity when compared both to a randomly selected set of genes, as well as to a degree-controlled list of genes (Figure 4—figure supplement 2a). We then used this approach to test the modularity of the four phenotypic sub-networks, when compared to two different ‘control sub-networks’ consisting of a group of the same number of genes as contained in the sub-network, one chosen randomly from among the candidate genes from our initial screen list (Table 1), and the second chosen from a degree-controlled list of genes selected from the entire PIN (see Materials and methods: Building degree-controlled randomised networks). We found that the four predicted phenotypic sub-networks showed higher LCC, higher network density, and more edges (Figure 4—figure supplement 2b), compared to both ‘control sub-networks’. This result suggests that these sub-networks display many features of modularity (although their average shortest path length is higher than controls, rather than lower) and may function as putative modules within the PIN to regulate one or both of ovariole number or egg laying.

Based on published molecular interactions, in addition to the four criteria described above, further evidence for putative functional modules of genes can also be obtained by applying algorithms that use either the shortest path method (Bromberg et al., 2008) or the Steiner Tree approach (Huang and Fraenkel, 2009). Such methods identify and predict functional connections between the seed proteins, as well as additional nodes (proteins or genes) that have not been experimentally tested within the given parameters, but are known to interact with the seed genes in the PIN (Albert and Albert, 2004; Yu et al., 2006). This process can provide evidence for or against the existence of a predicted functional module, and subsequent experimental testing of this predicted module can confirm its functionality. Given its recent success in predicting gene modules, we applied the previously published Seed Connector Algorithm (SCA), a member of the Steiner Tree algorithm family (Wang et al., 2017; Wang and Loscalzo, 2018), to the groups of genes that had similar phenotypic effects in our screens (seed genes; Figure 4b and c). The SCA connects seed genes and previously untested novel genes (connectors) to each other using a known PIN, producing the largest possible connected putative module given the data. Using the PIN and the aforementioned four lists of seed genes, we applied a custom python implementation of the SCA (Materials and methods: 04_Seed-Connector.ipynb) to build and extract the largest possible (given our PIN) connected putative modules that regulate egg laying and ovariole number.

This SCA method yielded four putative modules, one for each seed list, which we initially referred to as the Core Module (Figure 5b), hpo[RNAi] Egg Laying module (Figure 5—figure supplement 1), Egg Laying Module (Figure 5—figure supplement 2), and hpo[RNAi] Ovariole Number Module (Figure 5—figure supplement 3) respectively. Each of these four putative modules contained seed genes, which had been functionally evaluated in our screens (green and red circles in Figure 5), as well as connector genes, which were genes newly predicted as regulators of these phenotypes (green and red triangles in Figure 5). Of the four putative modules generated by the SCA, we found that the Core module had higher centrality measures than the other three putative modules (Figure 5—figure supplement 4). We interpret this to mean that the genes regulating these ‘Core phenotypes’ are more strongly connected to each other.

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Representation of Seed Connector Algorithm (SCA) and output.

(a) Schematic representation of the SCA. The algorithm initialises by creating a sub-network of seed genes from the PIN and computes the Largest Connected Component (LCC) and coverage (number of genes from the seed set in the LCC). At each iteration, genes in the direct neighbourhood of the LCC (distance = 1) are added one at a time to the seed set, and the coverage and LCC are recomputed. This process is repeated for each gene in the direct neighbourhood, each time restarting from the seed set of the preceding iteration. If any gene outside the seed set but in the direct neighbourhood is found to maximise coverage while minimising the LCC, it is added to the seed set as a connector gene. Black arrows indicate the path taken by the algorithm for which the criteria of maximal coverage and minimal LCC are met; such a path would be used to proceed to the subsequent iteration. Grey arrows indicate paths that fail to meet these criteria; such paths would be disregarded. The iteration repeats until the coverage cannot be increased; in this schematic example, this state is achieved in iteration 3. (b) The Core sub-network generated by the SCA based on the results of the genetic screens (Figure 1a–c). The size and colour of the shapes indicate the relative Zgene score of ovariole number of adult tj >hpo[RNAi], candidate[RNAi] females. Circles indicate seed genes (functionally tested in the screen; Table 2; Supplementary file 1) while triangles are connector genes (novel predicted genes; Supplementary file 1, Figure 5—figure supplement 1, Figure 5—figure supplement 2, Figure 5—figure supplement 3). Green = genes with a positive Zgene score above the threshold; red = genes with a negative Zgene score above the threshold; grey = genes with Zgene values below the threshold. hpo[RNAi] Egg Laying, Egg laying and hpo[RNAi] Ovariole Number sub-networks generated by the SCA are illustrated in Figure 5—figure supplement 1; Figure 5—figure supplement 2; Figure 5—figure supplement 3, respectively. Figure 5—figure supplement 4 shows the distribution of the four centrality measures calculated for the genes in each of the four phenotypic sub-networks obtained from the SCA (Figure 5 and Figure 5—figure supplements 1, 2 and 3). Figure 5—figure supplement 5 compares the network metrics after application of the SCA. Figure 5—figure supplement 6 shows the enrichment/depletion of signalling pathway genes in each of the four sub-networks obtained from the SCA.

We found, however, that these four groups of genes produced by the SCA did not have increased LCC values, increased network density, more edges nor decreased average shortest path (Figure 5—figure supplement 5), compared to our ‘control sub-networks’. This result shows that the SCA in this instance does not provide evidence for putative functional modules from the four phenotypic sub-networks in our system, above and beyond the evidence provided by the application of the four network metrics discussed above. To be conservative in our description of these results, we therefore henceforth refer to these four groups of genes united by phenotype and with strong predicted interactions, as sub-networks rather than as modules. We noted that each of these four sub-networks contains genes from most, if not all, known signalling pathways, rather than only genes from a single pathway (Figure 5—figure supplement 6).

Low edge densities between sub-networks suggest genetically separable mechanisms of ovariole number and egg laying

Our network analysis identified four highly connected sub-networks of genes that regulate two distinct developmental processes, together with or independently of Hippo signalling activity: ovariole number determination, which occurs primarily during larval development, and egg laying, which takes place in adult life (Figure 5). We wished to assess the degree to which there might be any shared genetic components between these four phenotypic sub-networks, and whether the addition of connector genes by the SCA had any impact on this. To understand potential interactions between the phenotypic sub-networks in the regulation of both ovariole number and egg laying, we constructed a composite network of all genes in each of the four phenotypic sub-networks (Figure 5b; Figure 5—figure supplement 1; Figure 5—figure supplement 2; Figure 5—figure supplement 3), which we refer to as the ‘meta network’ (Figure 6a). We then grouped the genes of the meta network into seven bins based on their phenotypic effects as measured in the three screens, resulting in sub-groups I through VII shown in Figure 6a. To ask whether the genes in these phenotypic groupings showed any notable interaction patterns, we compared the connectivity between genes assigned to the same phenotypic group, to the connectivity of a group of the same size randomly assembled from the genes of the meta network (Figure 6—figure supplement 1). As a measure of connectivity, we used an edge density map, which reflects the number of interactions between the genes within a group and between groups. We quantified the deviation between the edge density of each of groups I through VII, and their corresponding randomly assigned groups of the same size, by computing their respective Z score. When we included only seed genes in each of groups I through VII, we found that the edge density values of these groups were somewhat lower (Z score <−1.5) than those of the randomised groups (Figure 6—figure supplement 1a). The single exception to this was group IV, whose members shared more edges with each other than did the members of its randomised comparison group of the same size (Figure 6—figure supplement 1a). In other words, these groups of phenotypically binned seed genes were not notably more connected to each other then we would expect by chance.

Figure 6 with 1 supplement see all
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Phenotypically separable sub-networks formed by analysis of the combined genes from all sub-networks.

The meta network is generated by the union of the genes in the four phenotypic sub-networks: hpo[RNAi] Egg Laying (Figure 5—figure supplement 1), Egg Laying (Figure 5—figure supplement 2), hpo[RNAi] Ovariole Number (Figure 5—figure supplement 3) and Core (Figure 5b). (a) The meta network is represented as a Venn diagram, in which each grey dotted outline represents the screen in which a given gene was identified as affecting the scored phenotype. Within each sub-network, grey circles indicate seed genes, and blue circles indicate connector genes. Solid grey lines indicate interactions between genes in the meta network from the PIN. (b) Edge densities between the seven sub-networks of the meta network. (c) Relative enrichment of screened members of the 14 tested developmental signalling pathways within the seven sub-networks of the meta network. Figure 6—figure supplement 1 compares the edge density of the seven sub-networks of the meta network to the edge densities of a random assignment of the positive candidates in the screen to a seven similarly sized sub-networks.

In contrast, expanding each of the seven phenotypic sub-groups to include both seed genes and the connector genes predicted by the SCA changed the edge densities of these groups relative to their randomised control groups. Specifically, edge densities were much lower between groups I, II and III (Z score < −3), and much higher within group IV (Z score >3) (Figure 6—figure supplement 1). This shows that applying the SCA to these phenotypically binned groups increased the non-random differences in connectivity between them that were already present within the seed genes (Figure 6—figure supplement 1a), thus clarifying the internal structure of the meta network.

We then asked if these seven sub-groups were as connected to each other, as were the genes within each of the sub-groups, again using the edge density assessment as described above (Figure 6b). This analysis yielded three principal findings. First, edge densities between the three groups corresponding to the three scored phenotypes (I, II and III in Figure 6a) were very low (Figure 6b).This implies that the genes in each of the groups that regulate only one phenotype (I, II and III in Figure 6a) share more interactions with themselves than with genes in the other two groups, suggesting that each of these initially scored phenotype can be largely regulated by an independent, non-interacting set of genes. Second, the core group (IV in Figure 6a) displayed a higher edge density with the other three groups (I, II and III in Figure 6a) than any of those three groups did with each other (Figure 6b). Consistent with the definition of core genes as regulating all three scored reproductive phenotypes, this result suggests that the core genes, in contrast to those from the other three groups, may share substantial functional interactions with genes of the other groups. Finally, three small additional groups emerged from this analysis (V, VI and VII in Figure 6a), suggesting small networks of genes that might work together to regulate two of the three scored phenotypes. In sum, this meta network analysis supports the hypothesis of three potentially largely non-interacting genetic networks that regulate Hippo-dependent ovariole number, Hippo-dependent egg laying, and Hippo-independent egg laying, respectively. The presence of smaller sub-networks (V, VI and VII in Figure 6a) that interact with each other further supports the observation that the putative modules predicted by the SCA – which we refer to as sub-networks – could include genes that function within more than one such sub-network (Figure 5—figure supplement 4). Moreover, each of these genetically separable sub-networks included genes in multiple signalling pathways (Figure 6c).

Network analysis predicts novel genes involved in egg laying and ovariole number

The four predicted phenotypic sub-networks produced by the SCA approach included connector genes that were not included in our original screen, and thus had not been tested for possible effects on our phenotypes of interest (triangles in Figure 5b; Figure 5—figure supplements 1–3). Given that prior work in human disease models showed that predicted disease modules can correctly identify gene involvement in the relevant diseases (Chen et al., 2006; Gonzalez et al., 2007; Wang et al., 2017; Wang and Loscalzo, 2018), we asked whether our deployment of the SCA had likewise successfully predicted novel, functionally important genes in each sub-network. To do this, we used UAS:RNAi lines for each connector, driven by tj:Gal4 to measure the effects of knocking down each of the connector genes (triangles in Figure 5b and Figure 5—figure supplement 1; Figure 5—figure supplement 2; Figure 5—figure supplement 3) both on phenotypes within the sub-network where they were predicted (Figure 7a–b, Figure 7—source data 1), and on either of the other two tested phenotypes (Figure 7c, Figure 7—source data 2).

Figure 7
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Positive prediction rates of the connector genes in each of the four sub-networks.

(a) Proportion of Core sub-network connector genes with |Zgene| above the threshold in each of the three screens. The ‘All phenotypes’ category includes the genes with |Zgene| above the threshold in all three screens. (b) Proportion of tested connector genes in each of the three sub-networks with |Zgene| above the threshold within their corresponding screen. (c) Proportion of all unique connector genes (dark grey bars) predicted by all four sub-networks compared to the proportion of signalling candidate genes (light grey bars) with |Zgene| above the respective threshold in any of the three phenotypic screens (Figure 1a, b and c). Positive connector and signalling candidates that were above the |Zgene| threshold in all three phenotypic screens (Figure 1a, b and c) are indicated in an ‘All phenotypes’ column. Statistical significance was computed using the binomial test, comparing the probability of a positive candidate amongst the connectors to the probability of a positive candidate amongst the signalling candidates (p-value is found below each bar). Figure 7—source data 1 tabulates the distribution of seed genes and connectors in each sub-network used in Figure 7a and b. Figure 7—source data 2 tabulates the unique connector and signalling genes above |Zgene| threshold for the three phenotypic measurements plotted in Figure 7c.The connector genes are listed in the Supplementary file 1 and can be identified under the column header [SubNetworkName]_Connector. The raw data for egg laying and ovariole number for each of the connector genes can be found within the Supplementary file 1.

Figure 7—source data 1

Distribution of seed genes and connectors in each sub-network.

Two genes that were above |Zgene| threshold (Table 2 and Figure 7—source data 1) in the hpo[RNAi] Egg Laying (CG12147) and hpo[RNAi] Ovariole Number seed list (CG6104) were not found in the PIN, and therefore not included in the network analysis or in this table (see Materials and methods for details). The removal of these two genes accounts for the difference between the number of positive candidates in Table 2 and Figure 7—source data 2, and the number of seed genes in these two sub-networks (Supplementary file 1 and Figure 7—source data 1). The proportion of connectors whose loss of function produced a significant phenotype (|Zgene| above threshold) is in parentheses and plotted in Figure 7a and b. All connectors except eukaryotic translation initiation factor three subunit j (eIF3J) in the hpo[RNAi] Egg Laying sub-network, for which no RNAi line was available at the time of testing, were tested. Therefore, the percentages of connectors above the threshold for the hpo[RNAi] Egg Laying sub-network were calculated out of 17 connectors.

https://cdn.elifesciences.org/articles/54082/elife-54082-fig7-data1-v2.docx
Figure 7—source data 2

Number of unique connector and signalling genes above |Zgene| threshold for the three phenotypes measured in this screen (Figure 1a, b and c).

Table indicates the number of unique genes among the connector genes and signalling genes screened, that had available RNAi lines at the time of analysis. The number of genes in the hpo[RNAi] Egg Laying sub-network that were above the primary filter of |Zgene| > 1 are also indicated. Percentage of the number of connectors and signalling candidates above threshold for each phenotype from the number of connectors above the primary filter is in parentheses and plotted in Figure 7c. All connectors except eukaryotic translation initiation factor three subunit j (eIF3J) in the hpo[RNAi] Egg Laying sub-network, for which no RNAi line was available at the time of testing, were tested. Therefore, the percentages of connectors above the threshold were calculated out of 32 unique connectors.

https://cdn.elifesciences.org/articles/54082/elife-54082-fig7-data2-v2.docx

Of the ten predicted novel connectors within the Core sub-network, loss of function of several of these had significant effects on at least one of the three scored phenotypes. Five affected ovariole number, two affected Hpo-dependent egg laying and one affected Hpo-independent egg laying. However, only one of them significantly altered all three scored phenotypes (Figure 7a; Figure 7—source data 1).

The predicted connector genes from two of the other three phenotypic sub-networks showed high positive prediction rates for novel genes within the sub-networks. RNAi against seven out of 18 of the hpo[RNAi] Egg Laying connectors, three out of 11 of the hpo[RNAi] Ovariole Number connectors, and none of the 11 Egg Laying connectors, significantly affected the sub-network phenotype (Figure 7—source data 1). Thus, although the Egg Laying connectors failed to impact this phenotype in our assay, 41.1% and 27.2% of the connectors from the other two sub-networks were correctly predicted (Figure 7b; Figure 7—source data 1).

In sum, taken across all sub-networks, this methodology correctly identified genes regulating at least one of the scored reproductive phenotypes, at significantly higher rates than those obtained in the original screen of 463 members of all known signalling pathways (Figure 7c; Figure 7—source data 2). By this measure, testing network-predicted novel genes derived from experimentally obtained data was even more successful than testing signalling pathways as a means of identifying novel genes that regulate ovariole number and egg laying.

Discussion

In this study, we have identified many novel genes that regulate one or both of egg laying and ovariole number. Though the development of the insect ovary has been studied for over 100 years, our understanding of the genetic mechanisms that regulate the development of the ovary is sparse. The female reproductive system and its ability to produce eggs are one of the key determinants for the survival of a species in an ecological niche. The genes we have uncovered here are possible targets for the regulation of the construction and function of the reproductive system in D. melanogaster, and potentially in other species of insects as well. Understanding the gene regulatory networks that regulate egg laying and ovariole development could provide a framework to understand the key regulatory steps during this process that may be modified over evolutionary time, to yield the wide diversity of ovariole numbers and fecundities displayed by extant insects. We suggest that, given our success in applying a network approach to the results of a traditional forward genetic screen, the field of developmental genetics should find it fruitful to apply network analyses to the interpretation of large scale transcriptomic and proteomic data.

Identification of regulatory sub-networks for ovariole development and egg laying

The D. melanogaster ovary is a commonly studied model for organogenesis (Chen et al., 2001; Godt and Laski, 1995; Lobell et al., 2017; Sarikaya and Extavour, 2015), stem cell maintenance (Gilboa, 2015) and interactions of development and ecology (Cohet and David, 1978; Hodin and Riddiford, 2000a; Klepsatel et al., 2013a; Sarikaya et al., 2019). Nevertheless, our understanding of the genetic mechanisms that regulate these processes remains fragmentary. In this paper, we have identified four distinct protein interaction sub-networks that regulate ovariole number and egg laying in the D. melanogaster ovary. These sub-networks consist of both novel and previously characterised genes that regulate either ovariole number or egg laying or both, thus enhancing our understanding of the genetic underpinnings of this reproductive system.

Of the four sub-networks, the Core sub-network affects both ovariole number and egg laying. The Core sub-network contains numerous housekeeping genes, including regulators of transcription, translation and cell division such as polo (Llamazares et al., 1991), cyclin K (Edwards et al., 1998), nucleosome assembly protein 1 (Ito et al., 1996) and eukaryotic translation release factor 1 (Chao et al., 2003). While polo and eukaryotic translation release factor one are members of signalling pathways, cyclin K and nucleosome assembly protein one are genes predicted by the SCA. Given that the Core sub-network largely consists of genes whose loss of function decreases both of these parameters, we hypothesise that these are essential genes for the basic structure and function of the ovaries. Essential genes are more interconnected in a PIN with higher centrality measures (Jeong et al., 2001; but see Yu et al., 2008) and interestingly, we find that the genes in the Core sub-network also have higher connectivity than those in the other three sub-networks (Figure 5—figure supplement 4).

In addition to genes that regulate basic cellular processes, the Core sub-network is enriched for the central components of the Hh signalling cascade, namely patched (ptc), smoothened (smo) and costa (cos) (Lee et al., 2016). However, we find that the loss of Hh ligand, which is expressed in the TF cells in the developing larval ovary (Lai et al., 2017), does not significantly affect either ovariole number or egg laying. Though surprising, ligand-independent activation of Hedgehog signalling has been observed before. For example, in the Drosophila eye, loss of either ptc or cos in clones leads to non-cell autonomous proliferation in wild type cells, as well as growth disadvantages in the mutant tissue (Christiansen et al., 2012). In another example, sufficient intracellular smo levels can also activate downstream transcription of Hh pathway targets, showing that Hh itself is not always required to activate the cascade (Jiang et al., 2018).

Development of the larval ovary

The hpo[RNAi] Ovariole Number sub-network is composed of genes that affect the Hippo signalling activity-dependent determination of ovariole number during development. Establishment of ovariole number occurs largely during the third instar stage of larval development in D. melanogaster (Godt and Laski, 1995; Hodin and Riddiford, 1998; King et al., 1968; Sahut-Barnola et al., 1996). During this period, the TFCs are specified in the anterior of the ovary and undergo rearrangement into stacks of cells called TFs, each of which gives rise to an ovariole (Godt and Laski, 1995; Sahut-Barnola et al., 1995). TF specification requires the expression of engrailed (En) (Bolívar et al., 2006) and the transcription factors Bab1 and Bab2, encoded by the bric-à-brac locus (Couderc et al., 2002; Godt et al., 1993). A third transcription factor, Lmx1a, was recently found to be necessary for the specification of the TFCs (Allbee et al., 2018). Our hpo[RNAi] Ovariole Number sub-network identifies numerous additional novel transcription factors including bunched (bun) and retinoblastoma-family protein (rbf), which we hypothesise could also be involved in the specification of ovariole number. bun and rbf have been implicated in the migration (Dobens et al., 2005) and endoreplication (Cayirlioglu et al., 2003) of the follicle cells during oogenesis, but have not, to our knowledge, been previously identified as playing a role in the context of larval ovary development.

The TFCs specified in the larval ovary undergo a process of convergent extension to form TFs. This process of convergent extension requires cell intercalation, and the actin depolymerising factor Cofilin, encoded by the gene twinstar, is essential to this process (Chen et al., 2001). During intercalation, the cells also dynamically modify their actin cytoskeleton and their expression of E-cadherin (Godt and Laski, 1995). Our hpo[RNAi] Ovariole Number sub-network further identifies Rho1 (Barrett et al., 1997) and Rho kinase (Rok) (Mizuno et al., 1999) as necessary for correct ovariole number. During the extension of the D. melanogaster embryonic germ band, a commonly studied model of convergent extension, the localised activation of the actin-myosin network facilitated by Rho1 and Rok is necessary for cell intercalation (Kasza et al., 2014). Given the known roles of Rho1 and Rok as regulators of the actin cytoskeleton (Ridley, 2006), we propose that TF assembly in the ovary requires both these proteins for correct cell intercalation. A third actin cytoskeleton regulator, misshapen (msn), was also identified by our hpo[RNAi] Ovariole Number sub-network. msn encodes a MAP kinase previously shown to regulate the polarisation of the actin cytoskeleton during oogenesis (Lewellyn et al., 2013), but has not, to our knowledge, been studied to date in the context of larval ovarian development.

We propose that the polarity of the somatic cells in the ovary is also necessary for correct larval ovary development, given the presence of the lateral membrane proteins discs large 1 (dlg1) and prickle (pk) in the ovariole sub-network. During the maturation of the TFs during larval development, the TFCs undergo significant cell shape changes, coincident with localised expression of beta-catenin and actin to the lateral edges of the TFCs (Godt and Laski, 1995). Restriction of the E-cadherin domain in epithelia requires establishment of the basolateral domain (Harris and Peifer, 2004) and we propose that testing a similar requirement for dlg1 and pk in the larval ovary would be a fruitful avenue for future studies.

Network analysis as a tool in developmental biology

Using a systems biology approach to analyse RNAi screening data has proven fruitful, providing us with new insights into the development and function of the D. melanogaster ovary by identifying novel and previously understudied genes that regulate this process. Systematic analysis of the function of single genes in development has been a historical convention and has provided valuable and precise genetic interaction information (Jansen et al., 2002; von Mering et al., 2002). With the advent of genome-wide analysis, however, we can use data from a larger number of genes to predict the identity of additional functionally significant genes with relative ease (Yu et al., 2006). We note that the novel gene prediction rate within each individual sub-network ranged from as high as 41.1% from the hpo[RNAi] Ovariole Number sub-network to as low as 0% from the Egg Laying sub-network (Figure 7b; Figure 7—source data 1). We suggest that this may be due to multiple factors. Firstly, the possible incompleteness of the PIN is expected to lead to some areas of the network being sparse or non-existent (von Mering et al., 2002). If the sub-network of interest happens to fall in such regions of the PIN, prediction algorithms will fail. Secondly, the initial restriction of tested genes to signalling pathway members might have provided a seed list too sparse to usefully predict functional connectors. Finally, it could be the case that ‘Egg Laying’ is such a complex phenotype that its gene regulation cannot be adequately captured within a highly connected network of the type suited for identification by the analyses we have used here.

Ovariole number in D. melanogaster is the outcome of a discrete developmental process with a clear beginning and end, comprising a specific series of cellular behaviours that take place in the confines of one organ (Godt and Laski, 1995; Hodin and Riddiford, 2000a; Sahut-Barnola et al., 1996). Once established during larval life, ovariole number in Drosophila remains unaltered through to and during adulthood, even if oogenesis within those ovarioles suffers congenital or age-related defects (King, 1970). Because previous work suggested that ovariole number in Drosophila could have at least some predictive relation to egg laying (Cohet and David, 1978; Klepsatel et al., 2013b; Sarikaya and Extavour, 2015), we reasoned that scoring the latter phenotype in a primary screen (Figure 1a) could be an effective way to uncover ovariole number regulators (Figure 1c). While our results showed that this was true in many cases, it was also clear that these two traits can vary independently (Figure 2), highlighting the fact that ovariole number is not the only determinant of egg laying. Egg-laying dynamics, even during the limited five-day assay used in our study, are likely influenced not just by a single anatomical parameter such as ovariole number, but rather by many biological, biomechanical, hormonal and behavioural processes. Consequently, the sub-network we were able to extract from the results of this screen (Figure 1a and b) might be too coarse to extract novel genes that participate in the potentially complex gene interactions regulating egg laying. Furthermore, genes predicted within each of the sub-networks are unlikely to function exclusively within just one sub-network. This conclusion is supported by our observation that genes predicted to function in any of the sub-networks, also function in at least one of the four sub-networks at a higher rate than genes selected for screening by their presence in a signalling pathway (Figure 7c). We also observe that although substantial regions of the meta network do not share interactions with genes in the other sub-networks (Figure 6b), we do find smaller sub-networks where there is some overlap, further indicating pleiotropy of some genes in both egg laying and ovariole number regulation.

The predictive rates of the approach we have used here, although encouraging, are likely limited by the degree of noise in the high-throughput data used to generate the PIN (Li et al., 2010), the sparseness of the PIN, and the degree of misidentification of protein interactions (Zhang et al., 2017). Addressing one or more of these parameters could improve the outcomes of future network predictions from developmental genetics data. For example, the problem of sparseness, which is a paucity of high confidence detectable interactions relative to all biologically relevant interactions, has been addressed in other studies by using an ‘Interolog PIN’ (Matthews et al., 2001) in place of an organism-specific PIN. An Interolog PIN combines known interactions from multiple organisms and has been used successfully to identify, for example, gene modules relevant in squamous carcinoma, based on a starting dataset of microarray data on differentially expressed genes between cancer cells and the surrounding tissue (Wachi et al., 2005). Future studies applying such an Interolog PIN to the outcomes of genetic screens for developmental processes of interest could potentially overcome the problem of sparseness, as well as the biases towards proteins that are more heavily studied and thus better represented in organism-specific PINs.

Table 3
12 signalling candidate genes with no available RNAi lines at either BDSC or VDRC at the time of this study.
FbIDCG numberNameSymbol
FBgn0283468CG3412supernumerary limbsslmb
FBgn0267821CG5102daughterlessda
FBgn0266724CG5161TRAPP subunit 20Trs20
FBgn0267378CG7085sauronsau
FBgn0267487CG9181Protein tyrosine phosphatase 61FPtp61F
FBgn0267912CG9819Calcineurin A at 14FCanA-14F
FBgn0086371CG9829polypoly
FBgn0267350CG10260Phosphatidylinositol 4-kinase III alphaPI4KIIIalpha
FBgn0267698CG10295p21-activated kinasePak
FBgn0283462CG18279Immune induced molecule prepropeptideIMPPP
FBgn0267339CG33338p38c MAP kinasep38c
FBgn0085506CG40635-CG40635

Materials and methods

Key resources table
Reagent type
(species) or resource		DesignationSource or referenceIdentifiersAdditional
information
Chemical compound, drugHoechst 33321ThermoFisherH13991 ug/ml final concentration
Software, algorithmmatplotlibhttps://matplotlib.org/3.0.0
Software, algorithmnetworkxhttp://networkx.github.io/2.3
Software, algorithmnumpyhttps://www.numpy.org/1.11.3
Software, algorithmpandashttps://pandas.pydata.org /0.20.3
Software, algorithmprogressbarhttps://github.com/niltonvolpato/python-progressbar3.38.0
Software, algorithmscipyhttps://www.scipy.org/1.1.0
Software, algorithmseabornhttps://seaborn.pydata.org/0.9.0
Software, algorithmCytoscapehttps://cytoscape.org/3.4.0
Software, algorithmInkscapehttps://inkscape.org/0.92.3
Software, algorithmPython3https://www.python.org/3.7
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CanA1 (FBgn0010015) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01871}attP2Bloomington Drosophila Stock CenterBDSC:25850; FlyBase:FBst0025850;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fng (FBgn0011591) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01967}attP2Bloomington Drosophila Stock CenterBDSC:25947; FlyBase:FBst0025947;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Aplip1 (FBgn0040281) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02049}attP2Bloomington Drosophila Stock CenterBDSC:26024; FlyBase:FBst0026024;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)mdelta-HLH (FBgn0002734) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02101}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:26203; FlyBase:FBst0026203;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sima (FBgn0266411) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02105}attP2Bloomington Drosophila Stock CenterBDSC:26207; FlyBase:FBst0026207;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)m8-HLH (FBgn0000591) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02096}attP2Bloomington Drosophila Stock CenterBDSC:26322; FlyBase:FBst0026322;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pan (FBgn0085432) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02306}attP2Bloomington Drosophila Stock CenterBDSC:26743; FlyBase:FBst0026743;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CanB (FBgn0010014) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02616}attP2Bloomington Drosophila Stock CenterBDSC:27307; FlyBase:FBst0027307;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mib1 (FBgn0263601) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02629}attP2Bloomington Drosophila Stock CenterBDSC:27320; FlyBase:FBst0027320;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Nct (FBgn0039234) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02648}attP2Bloomington Drosophila Stock CenterBDSC:27498; FlyBase:FBst0027498;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cbl (FBgn0020224) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02650}attP2Bloomington Drosophila Stock CenterBDSC:27500; FlyBase:FBst0027500;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Atg12 (FBgn0036255) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02704}attP2Bloomington Drosophila Stock CenterBDSC:27552; FlyBase:FBst0027552;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fz2 (FBgn0016797) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02722}attP2Bloomington Drosophila Stock CenterBDSC:27568; FlyBase:FBst0027568;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Psn (FBgn0284421) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02760}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:27681; FlyBase:FBst0027681;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pi3K92E (FBgn0015279) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02770}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:27690; FlyBase:FBst0027690;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cdk4 (FBgn0016131) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02795}attP2Bloomington Drosophila Stock CenterBDSC:27714; FlyBase:FBst0027714;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mts (FBgn0004177) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02805}attP2Bloomington Drosophila Stock CenterBDSC:27723; FlyBase:FBst0027723;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pdk1 (FBgn0020386) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02807}attP2Bloomington Drosophila Stock CenterBDSC:27725; FlyBase:FBst0027725;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ds (FBgn0284247) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02842}attP2Bloomington Drosophila Stock CenterBDSC:28008; FlyBase:FBst0028008;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Hrs (FBgn0031450) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02860}attP2Bloomington Drosophila Stock CenterBDSC:28026; FlyBase:FBst0028026;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mam (FBgn0002643) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02881}attP2Bloomington Drosophila Stock CenterBDSC:28046; FlyBase:FBst0028046;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bun (FBgn0259176) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02954}attP2Bloomington Drosophila Stock CenterBDSC:28322; FlyBase:FBst0028322;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aos (FBgn0004569) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF03020}attP2Bloomington Drosophila Stock CenterBDSC:28383; FlyBase:FBst0028383;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pcx (FBgn0003048) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05038}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:28552; FlyBase:FBst0028552;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Su(fu) (FBgn0005355) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05045}attP2Bloomington Drosophila Stock CenterBDSC:28559; FlyBase:FBst0028559;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Apc2 (FBgn0026598) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05073}attP2Bloomington Drosophila Stock CenterBDSC:28585; FlyBase:FBst0028585;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of l(2)tid (FBgn0002174) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05082}attP2Bloomington Drosophila Stock CenterBDSC:28594; FlyBase:FBst0028594;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Su(H) (FBgn0004837) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05110}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:28900; FlyBase:FBst0028900;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of PDZ-GEF (FBgn0265778) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05139}attP2Bloomington Drosophila Stock CenterBDSC:28928; FlyBase:FBst0028928;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wntD (FBgn0038134) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05158}attP2Bloomington Drosophila Stock CenterBDSC:28947; FlyBase:FBst0028947;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cdk2 (FBgn0004107) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05163}attP2Bloomington Drosophila Stock CenterBDSC:28952; FlyBase:FBst0028952;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ci (FBgn0004859) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01715}attP2Bloomington Drosophila Stock CenterBDSC:28984; FlyBase:FBst0028984;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mgl (FBgn0261260) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02485}attP2Bloomington Drosophila Stock CenterBDSC:29324; FlyBase:FBst0029324;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)m4-BFM (FBgn0002629) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF03310}attP2Bloomington Drosophila Stock CenterBDSC:29378; FlyBase:FBst0029378;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wnt4 (FBgn0010453) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF03378}attP2Bloomington Drosophila Stock CenterBDSC:29442; FlyBase:FBst0029442;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Dif (FBgn0011274) under UAS control in the VALIUM10 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HM05257}attP2Bloomington Drosophila Stock CenterBDSC:30513; FlyBase:FBst0030513;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of InR (FBgn0283499) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01482}attP2Bloomington Drosophila Stock CenterBDSC:31037; FlyBase:FBst0031037;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cdc5 (FBgn0265574) and Roc1b (FBgn0040291) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01517}attP2Bloomington Drosophila Stock CenterBDSC:31067; FlyBase:FBst0031067;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Egfr (FBgn0003731) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01696}attP2Bloomington Drosophila Stock CenterBDSC:31183; FlyBase:FBst0031183;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of norpA (FBgn0262738) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01713}attP2Bloomington Drosophila Stock CenterBDSC:31197; FlyBase:FBst0031197;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CenG1A (FBgn0028509) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01807}attP2Bloomington Drosophila Stock CenterBDSC:31228; FlyBase:FBst0031228;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dsh (FBgn0000499) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01254}attP2Bloomington Drosophila Stock CenterBDSC:31307; FlyBase:FBst0031307;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tl (FBgn0262473) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01276}attP2Bloomington Drosophila Stock CenterBDSC:31477; FlyBase:FBst0031477;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of l(2)gl (FBgn0002121) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01073}attP2Bloomington Drosophila Stock CenterBDSC:31517; FlyBase:FBst0031517;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Jra (FBgn0001291) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01184}attP2Bloomington Drosophila Stock CenterBDSC:31595; FlyBase:FBst0031595;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Axn (FBgn0026597) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM04012}attP2Bloomington Drosophila Stock CenterBDSC:31705; FlyBase:FBst0031705;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gig (FBgn0005198) under UAS control in the VALIUM1 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM04083}attP2Bloomington Drosophila Stock CenterBDSC:31770; FlyBase:FBst0031770;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Med (FBgn0011655) under UAS control in the VALIUM10 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02218}attP2Bloomington Drosophila Stock CenterBDSC:31928; FlyBase:FBst0031928;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RagC-D (FBgn0033272) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00333}attP2Bloomington Drosophila Stock CenterBDSC:32342; FlyBase:FBst0032342;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of AMPKalpha (FBgn0023169) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00362}attP2Bloomington Drosophila Stock CenterBDSC:32371; FlyBase:FBst0032371;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rho1 (FBgn0014020) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00375}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32383; FlyBase:FBst0032383;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pk (FBgn0003090) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00408}attP2Bloomington Drosophila Stock CenterBDSC:32413; FlyBase:FBst0032413;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RpS6 (FBgn0261592) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00413}attP2Bloomington Drosophila Stock CenterBDSC:32418; FlyBase:FBst0032418;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of foxo (FBgn0038197) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00422}attP2Bloomington Drosophila Stock CenterBDSC:32427; FlyBase:FBst0032427;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Plc21C (FBgn0004611) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00436}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32438; FlyBase:FBst0032438;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp2 (FBgn0036046) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00476}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32475; FlyBase:FBst0032475;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hh (FBgn0004644) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00492}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32489; FlyBase:FBst0032489;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Spred (FBgn0020767) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00637}attP2Bloomington Drosophila Stock CenterBDSC:32852; FlyBase:FBst0032852;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of upd3 (FBgn0053542) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00646}attP2Bloomington Drosophila Stock CenterBDSC:32859; FlyBase:FBst0032859;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp1 (FBgn0044051) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00648}attP2Bloomington Drosophila Stock CenterBDSC:32861; FlyBase:FBst0032861;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp7 (FBgn0044046) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00649}attP2Bloomington Drosophila Stock CenterBDSC:32862; FlyBase:FBst0032862;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpA (FBgn0025637) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00657}attP2Bloomington Drosophila Stock CenterBDSC:32870; FlyBase:FBst0032870;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG3226 (FBgn0029882) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00662}attP2Bloomington Drosophila Stock CenterBDSC:32875; FlyBase:FBst0032875;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CtBP (FBgn0020496) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00677}attP2Bloomington Drosophila Stock CenterBDSC:32889; FlyBase:FBst0032889;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Hel89B (FBgn0022787) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00684}attP2Bloomington Drosophila Stock CenterBDSC:32895; FlyBase:FBst0032895;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tctp (FBgn0037874) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00701}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32911; FlyBase:FBst0032911;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of jub (FBgn0030530) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00714}attP2Bloomington Drosophila Stock CenterBDSC:32923; FlyBase:FBst0032923;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Gug (FBgn0010825) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00756}attP2Bloomington Drosophila Stock CenterBDSC:32961; FlyBase:FBst0032961;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sav (FBgn0053193) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00760}attP2Bloomington Drosophila Stock CenterBDSC:32965; FlyBase:FBst0032965;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bsk (FBgn0000229) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00777}attP2Bloomington Drosophila Stock CenterBDSC:32977; FlyBase:FBst0032977;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pgcl (FBgn0011822) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00792}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:32992; FlyBase:FBst0032992;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of polo (FBgn0003124) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00530}attP2Bloomington Drosophila Stock CenterBDSC:33042; FlyBase:FBst0033042;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cnk (FBgn0286070) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00238}attP2Bloomington Drosophila Stock CenterBDSC:33366; FlyBase:FBst0033366;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of kay (FBgn0001297) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00254}attP2Bloomington Drosophila Stock CenterBDSC:33379; FlyBase:FBst0033379;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of apolpp (FBgn0087002) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00265}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:33388; FlyBase:FBst0033388;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Su(var)205 (FBgn0003607) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00278}attP2Bloomington Drosophila Stock CenterBDSC:33400; FlyBase:FBst0033400;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tak1 (FBgn0026323) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00282}attP2Bloomington Drosophila Stock CenterBDSC:33404; FlyBase:FBst0033404;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hpo (FBgn0261456) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00006}attP2Bloomington Drosophila Stock CenterBDSC:33614; FlyBase:FBst0033614;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Akt1 (FBgn0010379) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00007}attP2Bloomington Drosophila Stock CenterBDSC:33615; FlyBase:FBst0033615;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of N (FBgn0004647) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00009}attP2Bloomington Drosophila Stock CenterBDSC:33616; FlyBase:FBst0033616;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of csw (FBgn0000382) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00012}attP2Bloomington Drosophila Stock CenterBDSC:33619; FlyBase:FBst0033619;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tor (FBgn0003733) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00021}attP2Bloomington Drosophila Stock CenterBDSC:33627; FlyBase:FBst0033627;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Stat92E (FBgn0016917) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00035}attP2Bloomington Drosophila Stock CenterBDSC:33637; FlyBase:FBst0033637;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Dsor1 (FBgn0010269) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00037}attP2Bloomington Drosophila Stock CenterBDSC:33639; FlyBase:FBst0033639;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pten (FBgn0026379) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00044}attP2Bloomington Drosophila Stock CenterBDSC:33643; FlyBase:FBst0033643;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CycD (FBgn0010315) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00059}attP2Bloomington Drosophila Stock CenterBDSC:33653; FlyBase:FBst0033653;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rel (FBgn0014018) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00070}attP2Bloomington Drosophila Stock CenterBDSC:33661; FlyBase:FBst0033661;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of upd1 (FBgn0004956) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00545}attP2Bloomington Drosophila Stock CenterBDSC:33680; FlyBase:FBst0033680;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp3 (FBgn0044050) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00546}attP2Bloomington Drosophila Stock CenterBDSC:33681; FlyBase:FBst0033681;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp4 (FBgn0044049) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00547}attP2Bloomington Drosophila Stock CenterBDSC:33682; FlyBase:FBst0033682;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp5 (FBgn0044048) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00548}attP2Bloomington Drosophila Stock CenterBDSC:33683; FlyBase:FBst0033683;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp6 (FBgn0044047) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00549}attP2Bloomington Drosophila Stock CenterBDSC:33684; FlyBase:FBst0033684;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of d (FBgn0262029) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01096}attP2Bloomington Drosophila Stock CenterBDSC:33754; FlyBase:FBst0033754;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Dad (FBgn0020493) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01102}attP2Bloomington Drosophila Stock CenterBDSC:33759; FlyBase:FBst0033759;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of inaC (FBgn0004784) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.JF02958}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:33768; FlyBase:FBst0033768;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wg (FBgn0284084) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00844}attP2Bloomington Drosophila Stock CenterBDSC:33902; FlyBase:FBst0033902;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of srl (FBgn0037248) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00858}attP2Bloomington Drosophila Stock CenterBDSC:33915; FlyBase:FBst0033915;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpC (FBgn0026175) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00871}attP2Bloomington Drosophila Stock CenterBDSC:33925; FlyBase:FBst0033925;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SPE (FBgn0039102) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00873}attP2Bloomington Drosophila Stock CenterBDSC:33926; FlyBase:FBst0033926;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Traf6 (FBgn0265464) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00880}attP2Bloomington Drosophila Stock CenterBDSC:33931; FlyBase:FBst0033931;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of upd2 (FBgn0030904) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00901}attP2Bloomington Drosophila Stock CenterBDSC:33949; FlyBase:FBst0033949;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tor (FBgn0021796) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00904}attP2Bloomington Drosophila Stock CenterBDSC:33951; FlyBase:FBst0033951;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dally (FBgn0263930) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00905}attP2Bloomington Drosophila Stock CenterBDSC:33952; FlyBase:FBst0033952;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rheb (FBgn0041191) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00923}attP2Bloomington Drosophila Stock CenterBDSC:33966; FlyBase:FBst0033966;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cat (FBgn0000261) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00990}attP2Bloomington Drosophila Stock CenterBDSC:34020; FlyBase:FBst0034020;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CycK (FBgn0025674) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01003}attP2Bloomington Drosophila Stock CenterBDSC:34032; FlyBase:FBst0034032;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wts (FBgn0011739) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00026}attP2Bloomington Drosophila Stock CenterBDSC:34064; FlyBase:FBst0034064;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of yki (FBgn0034970) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS00041}attP2Bloomington Drosophila Stock CenterBDSC:34067; FlyBase:FBst0034067;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of srp (FBgn0003507) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01083}attP2Bloomington Drosophila Stock CenterBDSC:34080; FlyBase:FBst0034080;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Fas2 (FBgn0000635) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01098}attP2Bloomington Drosophila Stock CenterBDSC:34084; FlyBase:FBst0034084;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF4E1 (FBgn0015218) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00969}attP2Bloomington Drosophila Stock CenterBDSC:34096; FlyBase:FBst0034096;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sema1a (FBgn0011259) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01307}attP2Bloomington Drosophila Stock CenterBDSC:34320; FlyBase:FBst0034320;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fz (FBgn0001085) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01308}attP2Bloomington Drosophila Stock CenterBDSC:34321; FlyBase:FBst0034321;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fj (FBgn0000658) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01310}attP2Bloomington Drosophila Stock CenterBDSC:34323; FlyBase:FBst0034323;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eve (FBgn0000606) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01312}attP2Bloomington Drosophila Stock CenterBDSC:34325; FlyBase:FBst0034325;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tll (FBgn0003720) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01316}attP2Bloomington Drosophila Stock CenterBDSC:34329; FlyBase:FBst0034329;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aPKC (FBgn0261854) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01320}attP2Bloomington Drosophila Stock CenterBDSC:34332; FlyBase:FBst0034332;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Vang (FBgn0015838) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01343}attP2Bloomington Drosophila Stock CenterBDSC:34354; FlyBase:FBst0034354;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Lst8 (FBgn0264691) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01350}attP2Bloomington Drosophila Stock CenterBDSC:34361; FlyBase:FBst0034361;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Lkb1 (FBgn0038167) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01351}attP2Bloomington Drosophila Stock CenterBDSC:34362; FlyBase:FBst0034362;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of puc (FBgn0243512) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01386}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34392; FlyBase:FBst0034392;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sxl (FBgn0264270) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00609}attP2Bloomington Drosophila Stock CenterBDSC:34393; FlyBase:FBst0034393;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cka (FBgn0044323) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00081}attP2Bloomington Drosophila Stock CenterBDSC:34522; FlyBase:FBst0034522;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bnl (FBgn0014135) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01046}attP2Bloomington Drosophila Stock CenterBDSC:34572; FlyBase:FBst0034572;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RagA-B (FBgn0037647) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01064}attP2Bloomington Drosophila Stock CenterBDSC:34590; FlyBase:FBst0034590;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wbp2 (FBgn0036318) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00563}attP2Bloomington Drosophila Stock CenterBDSC:34603; FlyBase:FBst0034603;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pip (FBgn0003089) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01288}attP2Bloomington Drosophila Stock CenterBDSC:34613; FlyBase:FBst0034613;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dome (FBgn0043903) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01293}attP2Bloomington Drosophila Stock CenterBDSC:34618; FlyBase:FBst0034618;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Stlk (FBgn0046692) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01295}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34620; FlyBase:FBst0034620;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of slp1 (FBgn0003430) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01107}attP2Bloomington Drosophila Stock CenterBDSC:34633; FlyBase:FBst0034633;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of slp2 (FBgn0004567) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01108}attP2Bloomington Drosophila Stock CenterBDSC:34634; FlyBase:FBst0034634;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hth (FBgn0001235) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01112}attP2Bloomington Drosophila Stock CenterBDSC:34637; FlyBase:FBst0034637;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RhoGEF2 (FBgn0023172) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01118}attP2Bloomington Drosophila Stock CenterBDSC:34643; FlyBase:FBst0034643;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wnt5 (FBgn0010194) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01119}attP2Bloomington Drosophila Stock CenterBDSC:34644; FlyBase:FBst0034644;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spi (FBgn0005672) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01120}attP2Bloomington Drosophila Stock CenterBDSC:34645; FlyBase:FBst0034645;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Galphao (FBgn0001122) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01129}attP2Bloomington Drosophila Stock CenterBDSC:34653; FlyBase:FBst0034653;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of shn (FBgn0003396) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01167}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34689; FlyBase:FBst0034689;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ser (FBgn0004197) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01179}attP2Bloomington Drosophila Stock CenterBDSC:34700; FlyBase:FBst0034700;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of H (FBgn0001169) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01182}attP2Bloomington Drosophila Stock CenterBDSC:34703; FlyBase:FBst0034703;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of opa (FBgn0003002) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01185}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34706; FlyBase:FBst0034706;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pkc53E (FBgn0003091) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01195}attP2Bloomington Drosophila Stock CenterBDSC:34716; FlyBase:FBst0034716;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hkb (FBgn0261434) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01216}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34736; FlyBase:FBst0034736;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gig (FBgn0005198) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01217}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34737; FlyBase:FBst0034737;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ken (FBgn0011236) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01219}attP2Bloomington Drosophila Stock CenterBDSC:34739; FlyBase:FBst0034739;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cact (FBgn0000250) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00084}attP2Bloomington Drosophila Stock CenterBDSC:34775; FlyBase:FBst0034775;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Bx42 (FBgn0004856) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00086}attP2Bloomington Drosophila Stock CenterBDSC:34777; FlyBase:FBst0034777;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rpt2 (FBgn0015282) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00104}attP2Bloomington Drosophila Stock CenterBDSC:34795; FlyBase:FBst0034795;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Skp2 (FBgn0037236) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00116}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:34807; FlyBase:FBst0034807;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of raptor (FBgn0029840) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00124}attP2Bloomington Drosophila Stock CenterBDSC:34814; FlyBase:FBst0034814;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sos (FBgn0001965) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00149}attP2Bloomington Drosophila Stock CenterBDSC:34833; FlyBase:FBst0034833;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Gprk2 (FBgn0261988) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00161}attP2Bloomington Drosophila Stock CenterBDSC:34843; FlyBase:FBst0034843;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of rl (FBgn0003256) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00173}attP2Bloomington Drosophila Stock CenterBDSC:34855; FlyBase:FBst0034855;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mwh (FBgn0264272) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00180}attP2Bloomington Drosophila Stock CenterBDSC:34862; FlyBase:FBst0034862;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Apc (FBgn0015589) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00188}attP2Bloomington Drosophila Stock CenterBDSC:34869; FlyBase:FBst0034869;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tao (FBgn0031030) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01226}attP2Bloomington Drosophila Stock CenterBDSC:34881; FlyBase:FBst0034881;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of 14-3-3epsilon (FBgn0020238) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01229}attP2Bloomington Drosophila Stock CenterBDSC:34884; FlyBase:FBst0034884;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sara (FBgn0026369) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01239}attP2Bloomington Drosophila Stock CenterBDSC:34894; FlyBase:FBst0034894;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gbb (FBgn0024234) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01243}attP2Bloomington Drosophila Stock CenterBDSC:34898; FlyBase:FBst0034898;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Atg8b (FBgn0038539) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01245}attP2Bloomington Drosophila Stock CenterBDSC:34900; FlyBase:FBst0034900;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rac1 (FBgn0010333) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01258}attP2Bloomington Drosophila Stock CenterBDSC:34910; FlyBase:FBst0034910;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ato (FBgn0010433) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01278}attP2Bloomington Drosophila Stock CenterBDSC:34929; FlyBase:FBst0034929;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dl (FBgn0260632) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00028}attP2Bloomington Drosophila Stock CenterBDSC:34938; FlyBase:FBst0034938;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mer (FBgn0086384) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00459}attP2Bloomington Drosophila Stock CenterBDSC:34958; FlyBase:FBst0034958;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mats (FBgn0038965) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00475}attP2Bloomington Drosophila Stock CenterBDSC:34959; FlyBase:FBst0034959;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ex (FBgn0004583) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00874}attP2Bloomington Drosophila Stock CenterBDSC:34968; FlyBase:FBst0034968;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ft (FBgn0001075) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00932}attP2Bloomington Drosophila Stock CenterBDSC:34970; FlyBase:FBst0034970;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of msk (FBgn0026252) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01408}attP2Bloomington Drosophila Stock CenterBDSC:34998; FlyBase:FBst0034998;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of baz (FBgn0000163) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01412}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35002; FlyBase:FBst0035002;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of arm (FBgn0000117) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01414}attP2Bloomington Drosophila Stock CenterBDSC:35004; FlyBase:FBst0035004;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Stam (FBgn0027363) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01429}attP2Bloomington Drosophila Stock CenterBDSC:35016; FlyBase:FBst0035016;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Gadd45 (FBgn0033153) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01436}attP2Bloomington Drosophila Stock CenterBDSC:35023; FlyBase:FBst0035023;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of htl (FBgn0010389) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01437}attP2Bloomington Drosophila Stock CenterBDSC:35024; FlyBase:FBst0035024;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tsh (FBgn0003866) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01443}attP2Bloomington Drosophila Stock CenterBDSC:35030; FlyBase:FBst0035030;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Socs36E (FBgn0041184) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01450}attP2Bloomington Drosophila Stock CenterBDSC:35036; FlyBase:FBst0035036;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cad99C (FBgn0039709) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01451}attP2Bloomington Drosophila Stock CenterBDSC:35037; FlyBase:FBst0035037;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pnt (FBgn0003118) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01452}attP2Bloomington Drosophila Stock CenterBDSC:35038; FlyBase:FBst0035038;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of numb (FBgn0002973) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01459}attP2Bloomington Drosophila Stock CenterBDSC:35045; FlyBase:FBst0035045;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of stan (FBgn0024836) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01464}attP2Bloomington Drosophila Stock CenterBDSC:35050; FlyBase:FBst0035050;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dco (FBgn0002413) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00001}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35134; FlyBase:FBst0035134;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CkIIalpha (FBgn0264492) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00003}attP2Bloomington Drosophila Stock CenterBDSC:35136; FlyBase:FBst0035136;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gish (FBgn0250823) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00005}attP2Bloomington Drosophila Stock CenterBDSC:35138; FlyBase:FBst0035138;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mkk4 (FBgn0024326) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00010}attP2Bloomington Drosophila Stock CenterBDSC:35143; FlyBase:FBst0035143;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CkIalpha (FBgn0015024) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00021}attP2Bloomington Drosophila Stock CenterBDSC:35153; FlyBase:FBst0035153;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of lic (FBgn0261524) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00022}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35154; FlyBase:FBst0035154;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Btk29A (FBgn0003502) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00027}attP2Bloomington Drosophila Stock CenterBDSC:35159; FlyBase:FBst0035159;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of alc (FBgn0260972) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00029}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35161; FlyBase:FBst0035161;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pka-C1 (FBgn0000273) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00038}attP2Bloomington Drosophila Stock CenterBDSC:35169; FlyBase:FBst0035169;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hpo (FBgn0261456) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00046}attP2Bloomington Drosophila Stock CenterBDSC:35176; FlyBase:FBst0035176;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of IKKbeta (FBgn0024222) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00058}attP2Bloomington Drosophila Stock CenterBDSC:35186; FlyBase:FBst0035186;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Aduk (FBgn0037679) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00059}attP2Bloomington Drosophila Stock CenterBDSC:35187; FlyBase:FBst0035187;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of put (FBgn0003169) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00069}attP2Bloomington Drosophila Stock CenterBDSC:35195; FlyBase:FBst0035195;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hep (FBgn0010303) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00089}attP2Bloomington Drosophila Stock CenterBDSC:35210; FlyBase:FBst0035210;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of brm (FBgn0000212) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00090}attP2Bloomington Drosophila Stock CenterBDSC:35211; FlyBase:FBst0035211;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pyd (FBgn0262614) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00109}attP2Bloomington Drosophila Stock CenterBDSC:35225; FlyBase:FBst0035225;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hyx (FBgn0037657) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00123}attP2Bloomington Drosophila Stock CenterBDSC:35238; FlyBase:FBst0035238;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of p38a (FBgn0015765) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00131}attP2Bloomington Drosophila Stock CenterBDSC:35244; FlyBase:FBst0035244;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of p38b (FBgn0024846) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00140}attP2Bloomington Drosophila Stock CenterBDSC:35252; FlyBase:FBst0035252;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of app (FBgn0260941) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00181}attP2Bloomington Drosophila Stock CenterBDSC:35280; FlyBase:FBst0035280;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sdt (FBgn0261873) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00193}attP2Bloomington Drosophila Stock CenterBDSC:35291; FlyBase:FBst0035291;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aux (FBgn0037218) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00213}attP2Bloomington Drosophila Stock CenterBDSC:35310; FlyBase:FBst0035310;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CaMKII (FBgn0264607) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00237}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35330; FlyBase:FBst0035330;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ask1 (FBgn0014006) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00238}attP2Bloomington Drosophila Stock CenterBDSC:35331; FlyBase:FBst0035331;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SAK (FBgn0026371) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00244}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35335; FlyBase:FBst0035335;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sgg (FBgn0003371) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00277}attP2Bloomington Drosophila Stock CenterBDSC:35364; FlyBase:FBst0035364;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hop (FBgn0004864) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00305}attP2Bloomington Drosophila Stock CenterBDSC:35386; FlyBase:FBst0035386;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mekk1 (FBgn0024329) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00322}attP2Bloomington Drosophila Stock CenterBDSC:35402; FlyBase:FBst0035402;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aop (FBgn0000097) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00324}attP2Bloomington Drosophila Stock CenterBDSC:35404; FlyBase:FBst0035404;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ras85D (FBgn0003205) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00336}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:35414; FlyBase:FBst0035414;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Nap1 (FBgn0015268) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00370}attP2Bloomington Drosophila Stock CenterBDSC:35445; FlyBase:FBst0035445;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of osa (FBgn0261885) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00372}attP2Bloomington Drosophila Stock CenterBDSC:35447; FlyBase:FBst0035447;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of key (FBgn0041205) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00088}attP2Bloomington Drosophila Stock CenterBDSC:35572; FlyBase:FBst0035572;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Stat92E (FBgn0016917) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00437}attP40/CyOBloomington Drosophila Stock CenterBDSC:35600; FlyBase:FBst0035600;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Gcn5 (FBgn0020388) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00439}attP40Bloomington Drosophila Stock CenterBDSC:35601; FlyBase:FBst0035601;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of TER94 (FBgn0261014) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00448}attP2Bloomington Drosophila Stock CenterBDSC:35608; FlyBase:FBst0035608;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wek (FBgn0001990) under UAS control in the VALIUM21 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLV21045}attP2Bloomington Drosophila Stock CenterBDSC:35680; FlyBase:FBst0035680;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bab2 (FBgn0025525) under UAS control in the VALIUM21 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLV21085}attP2Bloomington Drosophila Stock CenterBDSC:35720; FlyBase:FBst0035720;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Patj (FBgn0067864) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01489}attP2Bloomington Drosophila Stock CenterBDSC:35747; FlyBase:FBst0035747;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mtl (FBgn0039532) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01500}attP2Bloomington Drosophila Stock CenterBDSC:35754; FlyBase:FBst0035754;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gro (FBgn0001139) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01506}attP2Bloomington Drosophila Stock CenterBDSC:35759; FlyBase:FBst0035759;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wnt6 (FBgn0031902) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00457}attP2Bloomington Drosophila Stock CenterBDSC:35808; FlyBase:FBst0035808;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CycE (FBgn0010382) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00511}attP40Bloomington Drosophila Stock CenterBDSC:36092; FlyBase:FBst0036092;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Myd88 (FBgn0033402) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00183}attP2Bloomington Drosophila Stock CenterBDSC:36107; FlyBase:FBst0036107;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cul1 (FBgn0015509) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00561}attP2Bloomington Drosophila Stock CenterBDSC:36601; FlyBase:FBst0036601;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of chico (FBgn0024248) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01553}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:36665; FlyBase:FBst0036665;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rbf2 (FBgn0038390) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01586}attP2Bloomington Drosophila Stock CenterBDSC:36697; FlyBase:FBst0036697;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of rictor (FBgn0031006) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01588}attP2Bloomington Drosophila Stock CenterBDSC:36699; FlyBase:FBst0036699;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sty (FBgn0014388) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01599}attP2Bloomington Drosophila Stock CenterBDSC:36709; FlyBase:FBst0036709;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Zyx (FBgn0011642) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01606}attP40Bloomington Drosophila Stock CenterBDSC:36716; FlyBase:FBst0036716;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wnt2 (FBgn0004360) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01613}attP2Bloomington Drosophila Stock CenterBDSC:36722; FlyBase:FBst0036722;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rbf (FBgn0015799) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS03004}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:36744; FlyBase:FBst0036744;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dlg1 (FBgn0001624) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.JF02287}attP2Bloomington Drosophila Stock CenterBDSC:36771; FlyBase:FBst0036771;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dpp (FBgn0000490) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.JF02455}attP2Bloomington Drosophila Stock CenterBDSC:36779; FlyBase:FBst0036779;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Dl (FBgn0000463) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00520}attP40Bloomington Drosophila Stock CenterBDSC:36784; FlyBase:FBst0036784;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of HDAC1 (FBgn0015805) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01005}attP40Bloomington Drosophila Stock CenterBDSC:36800; FlyBase:FBst0036800;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Su(dx) (FBgn0003557) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01077}attP2Bloomington Drosophila Stock CenterBDSC:36836; FlyBase:FBst0036836;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pbl (FBgn0003041) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01092}attP2Bloomington Drosophila Stock CenterBDSC:36841; FlyBase:FBst0036841;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sod2 (FBgn0010213) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01015}attP40Bloomington Drosophila Stock CenterBDSC:36871; FlyBase:FBst0036871;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Art1 (FBgn0037834) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01072}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:36891; FlyBase:FBst0036891;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG10924 (FBgn0034356) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00200}attP2Bloomington Drosophila Stock CenterBDSC:36915; FlyBase:FBst0036915;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of trr (FBgn0023518) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01019}attP2Bloomington Drosophila Stock CenterBDSC:36916; FlyBase:FBst0036916;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Cdc42 (FBgn0010341) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00620}attP40Bloomington Drosophila Stock CenterBDSC:37477; FlyBase:FBst0037477;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of nej (FBgn0261617) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01507}attP2Bloomington Drosophila Stock CenterBDSC:37489; FlyBase:FBst0037489;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pvr (FBgn0032006) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01662}attP40Bloomington Drosophila Stock CenterBDSC:37520; FlyBase:FBst0037520;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cno (FBgn0259212) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00633}attP40Bloomington Drosophila Stock CenterBDSC:38194; FlyBase:FBst0038194;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pygo (FBgn0043900) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00647}attP40Bloomington Drosophila Stock CenterBDSC:38208; FlyBase:FBst0038208;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ed (FBgn0000547) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00648}attP40Bloomington Drosophila Stock CenterBDSC:38209; FlyBase:FBst0038209;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Nrg (FBgn0264975) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00656}attP40Bloomington Drosophila Stock CenterBDSC:38215; FlyBase:FBst0038215;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aph-1 (FBgn0031458) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01693}attP40Bloomington Drosophila Stock CenterBDSC:38249; FlyBase:FBst0038249;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cbt (FBgn0043364) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01726}attP40Bloomington Drosophila Stock CenterBDSC:38276; FlyBase:FBst0038276;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Vps36 (FBgn0086785) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01739}attP40Bloomington Drosophila Stock CenterBDSC:38286; FlyBase:FBst0038286;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of crb (FBgn0259685) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS01842}attP40Bloomington Drosophila Stock CenterBDSC:38373; FlyBase:FBst0038373;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tws (FBgn0004889) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL00670}attP40/CyOBloomington Drosophila Stock CenterBDSC:38899; FlyBase:FBst0038899;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of S (FBgn0003310) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL00686}attP2Bloomington Drosophila Stock CenterBDSC:38914; FlyBase:FBst0038914;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pvf3 (FBgn0085407) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS01876}attP40/CyOBloomington Drosophila Stock CenterBDSC:38962; FlyBase:FBst0038962;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CanB2 (FBgn0015614) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01886}attP2Bloomington Drosophila Stock CenterBDSC:38971; FlyBase:FBst0038971;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pi3K21B (FBgn0020622) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01907}attP40Bloomington Drosophila Stock CenterBDSC:38991; FlyBase:FBst0038991;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of par-6 (FBgn0026192) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01928}attP40Bloomington Drosophila Stock CenterBDSC:39010; FlyBase:FBst0039010;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pvf1 (FBgn0030964) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01958}attP40Bloomington Drosophila Stock CenterBDSC:39038; FlyBase:FBst0039038;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pka-C3 (FBgn0000489) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01970}attP2Bloomington Drosophila Stock CenterBDSC:39050; FlyBase:FBst0039050;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of DAAM (FBgn0025641) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01978}attP2Bloomington Drosophila Stock CenterBDSC:39058; FlyBase:FBst0039058;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of scrib (FBgn0263289) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01993}attP40/CyOBloomington Drosophila Stock CenterBDSC:39073; FlyBase:FBst0039073;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sina (FBgn0003410) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS02008}attP40Bloomington Drosophila Stock CenterBDSC:40842; FlyBase:FBst0040842;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of btl (FBgn0285896) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02038}attP2Bloomington Drosophila Stock CenterBDSC:40871; FlyBase:FBst0040871;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pp2B-14D (FBgn0011826) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02039}attP2Bloomington Drosophila Stock CenterBDSC:40872; FlyBase:FBst0040872;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Smurf (FBgn0029006) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02153}attP40Bloomington Drosophila Stock CenterBDSC:40905; FlyBase:FBst0040905;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CycB (FBgn0000405) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02163}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:40915; FlyBase:FBst0040915;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fu (FBgn0001079) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL00705}attP40Bloomington Drosophila Stock CenterBDSC:41588; FlyBase:FBst0041588;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ru (FBgn0003295) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01129}attP2Bloomington Drosophila Stock CenterBDSC:41593; FlyBase:FBst0041593;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ksr (FBgn0015402) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01134}attP2Bloomington Drosophila Stock CenterBDSC:41598; FlyBase:FBst0041598;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of slpr (FBgn0030018) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01187}attP2Bloomington Drosophila Stock CenterBDSC:41605; FlyBase:FBst0041605;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of p53 (FBgn0039044) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01220}attP40Bloomington Drosophila Stock CenterBDSC:41638; FlyBase:FBst0041638;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Smox (FBgn0025800) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02203}attP40Bloomington Drosophila Stock CenterBDSC:41670; FlyBase:FBst0041670;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of rho (FBgn0004635) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS02264}attP40Bloomington Drosophila Stock CenterBDSC:41699; FlyBase:FBst0041699;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of S6k (FBgn0283472) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS02267}attP2Bloomington Drosophila Stock CenterBDSC:41702; FlyBase:FBst0041702;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of snk (FBgn0003450) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02289}attP2Bloomington Drosophila Stock CenterBDSC:41723; FlyBase:FBst0041723;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ufd1-like (FBgn0036136) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01251}attP2Bloomington Drosophila Stock CenterBDSC:41823; FlyBase:FBst0041823;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RasGAP1 (FBgn0004390) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01258}attP2Bloomington Drosophila Stock CenterBDSC:41830; FlyBase:FBst0041830;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of 14-3-3zeta (FBgn0004907) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01310}attP40Bloomington Drosophila Stock CenterBDSC:41878; FlyBase:FBst0041878;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tkv (FBgn0003716) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01338}attP2Bloomington Drosophila Stock CenterBDSC:41904; FlyBase:FBst0041904;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of homer (FBgn0025777) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02301}attP2Bloomington Drosophila Stock CenterBDSC:41908; FlyBase:FBst0041908;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pll (FBgn0010441) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS02332}attP40Bloomington Drosophila Stock CenterBDSC:41935; FlyBase:FBst0041935;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of elB (FBgn0004858) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02357}attP2Bloomington Drosophila Stock CenterBDSC:41960; FlyBase:FBst0041960;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ea (FBgn0000533) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02358}attP2Bloomington Drosophila Stock CenterBDSC:41961; FlyBase:FBst0041961;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CycB3 (FBgn0015625) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02377}attP2Bloomington Drosophila Stock CenterBDSC:41979; FlyBase:FBst0041979;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of lgs (FBgn0039907) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02381}attP2Bloomington Drosophila Stock CenterBDSC:41983; FlyBase:FBst0041983;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Actbeta (FBgn0024913) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02057}attP40Bloomington Drosophila Stock CenterBDSC:42493; FlyBase:FBst0042493;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG5059 (FBgn0037007) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ02058}attP40Bloomington Drosophila Stock CenterBDSC:42494; FlyBase:FBst0042494;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of msn (FBgn0010909) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02084}attP40Bloomington Drosophila Stock CenterBDSC:42518; FlyBase:FBst0042518;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rassf (FBgn0039055) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02102}attP40Bloomington Drosophila Stock CenterBDSC:42534; FlyBase:FBst0042534;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sax (FBgn0003317) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02118}attP40/CyOBloomington Drosophila Stock CenterBDSC:42546; FlyBase:FBst0042546;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of et (FBgn0031055) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02213}attP40Bloomington Drosophila Stock CenterBDSC:42557; FlyBase:FBst0042557;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of nmo (FBgn0011817) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ02229}attP40Bloomington Drosophila Stock CenterBDSC:42570; FlyBase:FBst0042570;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG12147 (FBgn0037325) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02447}attP2Bloomington Drosophila Stock CenterBDSC:42612; FlyBase:FBst0042612;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Act5C (FBgn0000042) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02487}attP2Bloomington Drosophila Stock CenterBDSC:42651; FlyBase:FBst0042651;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Act87E (FBgn0000046) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02488}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:42652; FlyBase:FBst0042652;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of emc (FBgn0000575) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL00724}attP2Bloomington Drosophila Stock CenterBDSC:42768; FlyBase:FBst0042768;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of the Stellate gene family (FBgn0003523) plus Ste12DOR and SteXh:CG42398 (FBgn0044817 and FBgn0259817) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01156}attP2Bloomington Drosophila Stock CenterBDSC:42786; FlyBase:FBst0042786;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Socs44A (FBgn0033266) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02515}attP2Bloomington Drosophila Stock CenterBDSC:42830; FlyBase:FBst0042830;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gcm (FBgn0014179) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02582}attP40Bloomington Drosophila Stock CenterBDSC:42889; FlyBase:FBst0042889;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CkIIbeta (FBgn0000259) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02636}attP40Bloomington Drosophila Stock CenterBDSC:42943; FlyBase:FBst0042943;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of smo (FBgn0003444) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01472}attP2Bloomington Drosophila Stock CenterBDSC:43134; FlyBase:FBst0043134;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dock (FBgn0010583) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP .GL01519}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:43176; FlyBase:FBst0043176;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mad (FBgn0011648) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01527}attP40Bloomington Drosophila Stock CenterBDSC:43183; FlyBase:FBst0043183;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pp2A-29B (FBgn0260439) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01921}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:43283; FlyBase:FBst0043283;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG11658 (FBgn0036196) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02671}attP40Bloomington Drosophila Stock CenterBDSC:43298; FlyBase:FBst0043298;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Myc (FBgn0262656) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01314}attP40Bloomington Drosophila Stock CenterBDSC:43962; FlyBase:FBst0043962;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pav (FBgn0011692) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP .GL01316}attP40Bloomington Drosophila Stock CenterBDSC:43963; FlyBase:FBst0043963;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF4EHP (FBgn0053100) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02703}attP40Bloomington Drosophila Stock CenterBDSC:43990; FlyBase:FBst0043990;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Atg1 (FBgn0260945) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMS02750}attP40Bloomington Drosophila Stock CenterBDSC:44034; FlyBase:FBst0044034;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tefu (FBgn0045035) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02790}attP40Bloomington Drosophila Stock CenterBDSC:44073; FlyBase:FBst0044073;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bi (FBgn0000179) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02815}attP2Bloomington Drosophila Stock CenterBDSC:44095; FlyBase:FBst0044095;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mad2 (FBgn0035640) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01381}attP2Bloomington Drosophila Stock CenterBDSC:44430; FlyBase:FBst0044430;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ebi (FBgn0263933) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01413}attP40Bloomington Drosophila Stock CenterBDSC:44443; FlyBase:FBst0044443;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dx (FBgn0000524) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01607}attP2Bloomington Drosophila Stock CenterBDSC:44455; FlyBase:FBst0044455;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fz3 (FBgn0027343) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01626}attP2Bloomington Drosophila Stock CenterBDSC:44468; FlyBase:FBst0044468;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cos (FBgn0000352) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC02347}attP2Bloomington Drosophila Stock CenterBDSC:44472; FlyBase:FBst0044472;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of disp (FBgn0029088) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02877}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:44633; FlyBase:FBst0044633;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spen (FBgn0016977) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01647}attP40Bloomington Drosophila Stock CenterBDSC:50529; FlyBase:FBst0050529;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dlp (FBgn0041604) under UAS control in the VALIUM22 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01658}attP40Bloomington Drosophila Stock CenterBDSC:50540; FlyBase:FBst0050540;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wgn (FBgn0030941) under UAS control in the VALIUM22 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLC01716}attP2Bloomington Drosophila Stock CenterBDSC:50594; FlyBase:FBst0050594;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RpL8 (FBgn0261602) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC02977}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:50610; FlyBase:FBst0050610;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Act42A (FBgn0000043) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC02992}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:50625; FlyBase:FBst0050625;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tin (FBgn0004110) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03064}attP2Bloomington Drosophila Stock CenterBDSC:50663; FlyBase:FBst0050663;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of EcR (FBgn0000546) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03114}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:50712; FlyBase:FBst0050712;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of aru (FBgn0029095) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02966}attP2Bloomington Drosophila Stock CenterBDSC:50730; FlyBase:FBst0050730;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF4E4 (FBgn0035709) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21052}attP40Bloomington Drosophila Stock CenterBDSC:50951; FlyBase:FBst0050951;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pont (FBgn0040078) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21078}attP40Bloomington Drosophila Stock CenterBDSC:50972; FlyBase:FBst0050972;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dpn (FBgn0010109) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03154}attP2Bloomington Drosophila Stock CenterBDSC:51440; FlyBase:FBst0051440;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Spn27A (FBgn0028990) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03159}attP2Bloomington Drosophila Stock CenterBDSC:51445; FlyBase:FBst0051445;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ttv (FBgn0265974) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03225}attP40Bloomington Drosophila Stock CenterBDSC:51480; FlyBase:FBst0051480;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mipp2 (FBgn0026060) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03229}attP40/CyOBloomington Drosophila Stock CenterBDSC:51482; FlyBase:FBst0051482;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of kibra (FBgn0262127) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03256}attP2Bloomington Drosophila Stock CenterBDSC:51499; FlyBase:FBst0051499;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tld (FBgn0003719) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03275}attP2Bloomington Drosophila Stock CenterBDSC:51507; FlyBase:FBst0051507;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of S6kII (FBgn0262866) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03140}attP40Bloomington Drosophila Stock CenterBDSC:51694; FlyBase:FBst0051694;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ast (FBgn0015905) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03173}attP2Bloomington Drosophila Stock CenterBDSC:51700; FlyBase:FBst0051700;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ras (FBgn0003204) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03250}attP2Bloomington Drosophila Stock CenterBDSC:51717; FlyBase:FBst0051717;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)mgamma-HLH (FBgn0002735) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03315}attP2Bloomington Drosophila Stock CenterBDSC:51762; FlyBase:FBst0051762;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Src64B (FBgn0262733) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03327}attP40Bloomington Drosophila Stock CenterBDSC:51772; FlyBase:FBst0051772;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of brk (FBgn0024250) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03345}attP2Bloomington Drosophila Stock CenterBDSC:51789; FlyBase:FBst0051789;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ext2 (FBgn0029175) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03621}attP40Bloomington Drosophila Stock CenterBDSC:52883; FlyBase:FBst0052883;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pen-2 (FBgn0053198) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03648}attP40/CyOBloomington Drosophila Stock CenterBDSC:52908; FlyBase:FBst0052908;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tsc1 (FBgn0026317) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03672}attP40Bloomington Drosophila Stock CenterBDSC:52931; FlyBase:FBst0052931;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of NT1 (FBgn0261526) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21720}attP40Bloomington Drosophila Stock CenterBDSC:53003; FlyBase:FBst0053003;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of arr (FBgn0000119) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03571}attP40Bloomington Drosophila Stock CenterBDSC:53342; FlyBase:FBst0053342;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of kermit (FBgn0010504) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03578}attP40Bloomington Drosophila Stock CenterBDSC:53349; FlyBase:FBst0053349;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Sirt1 (FBgn0024291) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21708}attP40Bloomington Drosophila Stock CenterBDSC:53697; FlyBase:FBst0053697;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tow (FBgn0035719) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21747}attP40Bloomington Drosophila Stock CenterBDSC:53704; FlyBase:FBst0053704;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF4E3 (FBgn0265089) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21195}attP40Bloomington Drosophila Stock CenterBDSC:53880; FlyBase:FBst0053880;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hppy (FBgn0263395) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21199}attP40Bloomington Drosophila Stock CenterBDSC:53884; FlyBase:FBst0053884;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dome (FBgn0043903) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21208}attP40Bloomington Drosophila Stock CenterBDSC:53890; FlyBase:FBst0053890;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ocho (FBgn0040296) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21588}attP40/CyOBloomington Drosophila Stock CenterBDSC:54851; FlyBase:FBst0054851;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sqd (FBgn0263396) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03848}attP40Bloomington Drosophila Stock CenterBDSC:55169; FlyBase:FBst0055169;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mago (FBgn0002736) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03947}attP40Bloomington Drosophila Stock CenterBDSC:55260; FlyBase:FBst0055260;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of egr (FBgn0033483) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03963}attP40Bloomington Drosophila Stock CenterBDSC:55276; FlyBase:FBst0055276;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)m3-HLH (FBgn0002609) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC03989}attP2Bloomington Drosophila Stock CenterBDSC:55302; FlyBase:FBst0055302;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Coprox (FBgn0021944) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC04005}attP40/CyOBloomington Drosophila Stock CenterBDSC:55318; FlyBase:FBst0055318;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rab23 (FBgn0037364) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04039}attP40Bloomington Drosophila Stock CenterBDSC:55352; FlyBase:FBst0055352;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tsu (FBgn0033378) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04055}attP40Bloomington Drosophila Stock CenterBDSC:55367; FlyBase:FBst0055367;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Notum (FBgn0044028) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04067}attP40Bloomington Drosophila Stock CenterBDSC:55379; FlyBase:FBst0055379;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sd (FBgn0003345) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04092}attP40Bloomington Drosophila Stock CenterBDSC:55404; FlyBase:FBst0055404;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Raf (FBgn0003079) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03854}attP2Bloomington Drosophila Stock CenterBDSC:55679; FlyBase:FBst0055679;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Mo25 (FBgn0017572) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03865}attP2Bloomington Drosophila Stock CenterBDSC:55681; FlyBase:FBst0055681;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ptc (FBgn0003892) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03872}attP40Bloomington Drosophila Stock CenterBDSC:55686; FlyBase:FBst0055686;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pka-C2 (FBgn0000274) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04129}attP2Bloomington Drosophila Stock CenterBDSC:55859; FlyBase:FBst0055859;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sev (FBgn0003366) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC04136}attP2Bloomington Drosophila Stock CenterBDSC:55866; FlyBase:FBst0055866;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of shf (FBgn0003390) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04137}attP2Bloomington Drosophila Stock CenterBDSC:55867; FlyBase:FBst0055867;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of babo (FBgn0011300) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04142}attP2/TM3, Sb[1]Bloomington Drosophila Stock CenterBDSC:55871; FlyBase:FBst0055871;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Shark (FBgn0015295) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04146}attP2Bloomington Drosophila Stock CenterBDSC:55874; FlyBase:FBst0055874;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Drl-2 (FBgn0033791) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04172}attP2Bloomington Drosophila Stock CenterBDSC:55893; FlyBase:FBst0055893;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Takl2 (FBgn0039015) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC04181}attP2Bloomington Drosophila Stock CenterBDSC:55899; FlyBase:FBst0055899;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Takl1 (FBgn0046689) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04186}attP2Bloomington Drosophila Stock CenterBDSC:55903; FlyBase:FBst0055903;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Doa (FBgn0265998) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMC04193}attP2Bloomington Drosophila Stock CenterBDSC:55908; FlyBase:FBst0055908;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fus (FBgn0023441) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04208}attP40Bloomington Drosophila Stock CenterBDSC:55921; FlyBase:FBst0055921;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of grk (FBgn0001137) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04213}attP40Bloomington Drosophila Stock CenterBDSC:55926; FlyBase:FBst0055926;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of PpD3 (FBgn0005777) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS04508}attP40Bloomington Drosophila Stock CenterBDSC:57307; FlyBase:FBst0057307;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Nct (FBgn0039234) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04812}attP40Bloomington Drosophila Stock CenterBDSC:57497; FlyBase:FBst0057497;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG15436 (FBgn0031610) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04637}attP40Bloomington Drosophila Stock CenterBDSC:57867; FlyBase:FBst0057867;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Su(var)2–10 (FBgn0003612) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ21959}attP40Bloomington Drosophila Stock CenterBDSC:58067; FlyBase:FBst0058067;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Atg8a (FBgn0052672) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ22416}attP40Bloomington Drosophila Stock CenterBDSC:58309; FlyBase:FBst0058309;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spz (FBgn0003495) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ22258}attP40Bloomington Drosophila Stock CenterBDSC:58499; FlyBase:FBst0058499;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of AstC-R1 (FBgn0036790) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ23767}attP40/CyOBloomington Drosophila Stock CenterBDSC:62372; FlyBase:FBst0062372;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ku80 (FBgn0041627) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ24057}attP40/CyOBloomington Drosophila Stock CenterBDSC:62513; FlyBase:FBst0062513;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG2199 (FBgn0035213) under UAS control in the VALIUM20 vector.: y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.7.7 v[+t1.8]=TRiP.HMJ30228}attP40Bloomington Drosophila Stock CenterBDSC:63661; FlyBase:FBst0063661;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tsr (FBgn0011726) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00534}attP2Bloomington Drosophila Stock CenterBDSC:65055; FlyBase:FBst0065055;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG3630 (FBgn0023540) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC06220}attP2Bloomington Drosophila Stock CenterBDSC:65945; FlyBase:FBst0065945;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tub (FBgn0003882) under UAS control in the VALIUM20 vector.: y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS05426}attP40Bloomington Drosophila Stock CenterBDSC:66960; FlyBase:FBst0066960;
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF4E-6 (FBgn0039622) under UAS control.Vienna Drosophila Resource CenterVDRC:v17580
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gd (FBgn0000808) under UAS control.Vienna Drosophila Resource CenterVDRC:v14892
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Act88F (FBgn0000047) under UAS control.Vienna Drosophila Resource CenterVDRC:v9780
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eRF1 (FBgn0036974) under UAS control.Vienna Drosophila Resource CenterVDRC:v45027
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)m2-BFM (FBgn0002592) under UAS control.Vienna Drosophila Resource CenterVDRC:v30115
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tsl (FBgn0003867) under UAS control.Vienna Drosophila Resource CenterVDRC:v14430
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wbl (FBgn0004003) under UAS control.Vienna Drosophila Resource CenterVDRC:v13864
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of boss (FBgn0000206) under UAS control.Vienna Drosophila Resource CenterVDRC:v4365
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG32396 (FBgn0020251) under UAS control.Vienna Drosophila Resource CenterVDRC:v41896
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rac2 (FBgn0014011) under UAS control.Vienna Drosophila Resource CenterVDRC:v28926
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ihog (FBgn0031872) under UAS control.Vienna Drosophila Resource CenterVDRC:v29898
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sog (FBgn0003463) under UAS control.Vienna Drosophila Resource CenterVDRC:v37405
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG9314 (FBgn0032061) under UAS control.Vienna Drosophila Resource CenterVDRC:v44647
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sgl (FBgn0261445) under UAS control.Vienna Drosophila Resource CenterVDRC:v29434
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of mirr (FBgn0014343) under UAS control.Vienna Drosophila Resource CenterVDRC:v50134
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF-4B (FBgn0020660) under UAS control.Vienna Drosophila Resource CenterVDRC:v31364
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of rasp (FBgn0024194) under UAS control.Vienna Drosophila Resource CenterVDRC:v6459
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of PGRP-SA (FBgn0030310) under UAS control.Vienna Drosophila Resource CenterVDRC:v5594
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of sinah (FBgn0259794) under UAS control.Vienna Drosophila Resource CenterVDRC:v17118
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of lft (FBgn0032230) under UAS control.Vienna Drosophila Resource CenterVDRC:v32146
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pyr (FBgn0033649) under UAS control.Vienna Drosophila Resource CenterVDRC:v36524
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ssl (FBgn0015300) under UAS control.Vienna Drosophila Resource CenterVDRC:v17282
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pvf2 (FBgn0031888) under UAS control.Vienna Drosophila Resource CenterVDRC:v7628
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spz4 (FBgn0032362) under UAS control.Vienna Drosophila Resource CenterVDRC:v7679
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of IM23 (FBgn0034328) under UAS control.Vienna Drosophila Resource CenterVDRC:v15384
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of botv (FBgn0027535) under UAS control.Vienna Drosophila Resource CenterVDRC:v37186
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of G6P (FBgn0031463) under UAS control.Vienna Drosophila Resource CenterVDRC:v7261
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of stet (FBgn0020248) under UAS control.Vienna Drosophila Resource CenterVDRC:v7434
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RanBPM (FBgn0262114) under UAS control.Vienna Drosophila Resource CenterVDRC:v45981
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Src42A (FBgn0264959) under UAS control.Vienna Drosophila Resource CenterVDRC:v26019
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of nkd (FBgn0002945) under UAS control.Vienna Drosophila Resource CenterVDRC:v3004
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of boi (FBgn0040388) under UAS control.Vienna Drosophila Resource CenterVDRC:v3060
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CR45683; Tehao (FBgn0026760) under UAS control.Vienna Drosophila Resource CenterVDRC:v17903
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG45087; Pepck (FBgn0003067) under UAS control.Vienna Drosophila Resource CenterVDRC:v20529
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of RpL13A (FBgn0037351) under UAS control.Vienna Drosophila Resource CenterVDRC:v101369
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Usp7 (FBgn0030366) under UAS control.Vienna Drosophila Resource CenterVDRC:v110324
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of tsg (FBgn0003865) under UAS control.Vienna Drosophila Resource CenterVDRC:v108750
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of nec (FBgn0002930) under UAS control.Vienna Drosophila Resource CenterVDRC:v108366
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Nle (FBgn0021874) under UAS control.Vienna Drosophila Resource CenterVDRC:v110728
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Brd (FBgn0000216) under UAS control.Vienna Drosophila Resource CenterVDRC:v107929
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Shc (FBgn0015296) under UAS control.Vienna Drosophila Resource CenterVDRC:v103906
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Hs6st (FBgn0038755) under UAS control.Vienna Drosophila Resource CenterVDRC:v110424
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fz4 (FBgn0027342) under UAS control.Vienna Drosophila Resource CenterVDRC:v102339
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of bib (FBgn0000180) under UAS control.Vienna Drosophila Resource CenterVDRC:v103327
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Wnt10 (FBgn0031903) under UAS control.Vienna Drosophila Resource CenterVDRC:v100867
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tom (FBgn0026320) under UAS control.Vienna Drosophila Resource CenterVDRC:v101652
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Pli (FBgn0025574) under UAS control.Vienna Drosophila Resource CenterVDRC:v106776
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of drk (FBgn0004638) under UAS control.Vienna Drosophila Resource CenterVDRC:v105498
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of por (FBgn0004957) under UAS control.Vienna Drosophila Resource CenterVDRC:v100780
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of wls (FBgn0036141) under UAS control.Vienna Drosophila Resource CenterVDRC:v103812
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG6843 (FBgn0036827) under UAS control.Vienna Drosophila Resource CenterVDRC:v109411
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spz3 (FBgn0031959) under UAS control.Vienna Drosophila Resource CenterVDRC:v102871
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of kuz (FBgn0259984) under UAS control.Vienna Drosophila Resource CenterVDRC:v107036
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Hs3st-B (FBgn0031005) under UAS control.Vienna Drosophila Resource CenterVDRC:v110601
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Tace (FBgn0039734) under UAS control.Vienna Drosophila Resource CenterVDRC:v106335
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of eIF-1A (FBgn0026250) under UAS control.Vienna Drosophila Resource CenterVDRC:v100611
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Socs16D (FBgn0030869) under UAS control.Vienna Drosophila Resource CenterVDRC:v100568
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)malpha-BFM (FBgn0002732) under UAS control.Vienna Drosophila Resource CenterVDRC:v109384
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of E(spl)m6-BFM (FBgn0002632) under UAS control.Vienna Drosophila Resource CenterVDRC:v101965
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of VhaM8.9 (FBgn0037671) under UAS control.Vienna Drosophila Resource CenterVDRC:v105281
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of melt (FBgn0023001) under UAS control.Vienna Drosophila Resource CenterVDRC:v105110
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpB (FBgn0026176) under UAS control.Vienna Drosophila Resource CenterVDRC:v106521
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CkIIbeta2 (FBgn0026136) under UAS control.Vienna Drosophila Resource CenterVDRC:v102633
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spz6 (FBgn0035056) under UAS control.Vienna Drosophila Resource CenterVDRC:v100897
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Rok (FBgn0026181) under UAS control.Vienna Drosophila Resource CenterVDRC:v104675
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG9962 (FBgn0031441) under UAS control.Vienna Drosophila Resource CenterVDRC:v108721
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of spz5 (FBgn0035379) under UAS control.Vienna Drosophila Resource CenterVDRC:v102389
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Act57B (FBgn0000044) under UAS control.Vienna Drosophila Resource CenterVDRC:v102129
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ndl (FBgn0002926) under UAS control.Vienna Drosophila Resource CenterVDRC:v102818
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of vn (FBgn0003984) under UAS control.Vienna Drosophila Resource CenterVDRC:v109437
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ECSIT (FBgn0028436) under UAS control.Vienna Drosophila Resource CenterVDRC:v106141
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpE (FBgn0031074) under UAS control.Vienna Drosophila Resource CenterVDRC:v109539
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpF (FBgn0034863) under UAS control.Vienna Drosophila Resource CenterVDRC:v106572
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of kek1 (FBgn0015399) under UAS control.Vienna Drosophila Resource CenterVDRC:v101166
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ths (FBgn0033652) under UAS control.Vienna Drosophila Resource CenterVDRC:v102441
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Ilp8 (FBgn0036690) under UAS control.Vienna Drosophila Resource CenterVDRC:v102604
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG15800 (FBgn0034904) under UAS control.Vienna Drosophila Resource CenterVDRC:v110049
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of IM3 (FBgn0040736) under UAS control.Vienna Drosophila Resource CenterVDRC:v104908
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Roc1a (FBgn0025638) under UAS control.Vienna Drosophila Resource CenterVDRC:v106315
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dod (FBgn0015379) under UAS control.Vienna Drosophila Resource CenterVDRC:v110593
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of hipk (FBgn0035142) under UAS control.Vienna Drosophila Resource CenterVDRC:v108254
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of ave (FBgn0050476) under UAS control.Vienna Drosophila Resource CenterVDRC:v101471
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of boca (FBgn0004132) under UAS control.Vienna Drosophila Resource CenterVDRC:v108406
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of gskt (FBgn0046332) under UAS control.Vienna Drosophila Resource CenterVDRC:v107429
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of stumps (FBgn0020299) under UAS control.Vienna Drosophila Resource CenterVDRC:v105603
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of CG31431 (FBgn0051431) under UAS control.Vienna Drosophila Resource CenterVDRC:v104697
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of scw (FBgn0005590) under UAS control.Vienna Drosophila Resource CenterVDRC:v105303
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of fry (FBgn0016081) under UAS control.Vienna Drosophila Resource CenterVDRC:v103569
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of Krn (FBgn0052179) under UAS control.Vienna Drosophila Resource CenterVDRC:v104299
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of pxb (FBgn0053207) under UAS control.Vienna Drosophila Resource CenterVDRC:v102240
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cv-c (FBgn0285955) under UAS control.Vienna Drosophila Resource CenterVDRC:v105435
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of cic (FBgn0262582) under UAS control.Vienna Drosophila Resource CenterVDRC:v103805
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of dia (FBgn0011202) under UAS control.Vienna Drosophila Resource CenterVDRC:v103914
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of SkpD;SkpC (FBgn0026174) under UAS control.Vienna Drosophila Resource CenterVDRC:v109181
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of drk (FBgn0004638) under UAS control.Vienna Drosophila Resource CenterVDRC:v105498
Genetic reagent (D. melanogaster)D. melanogaster. Expresses dsRNA for RNAi of botv (FBgn0027535) under UAS control.Vienna Drosophila Resource CenterVDRC:v37186

Lead contact and materials availability

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This study did not generate new unique reagents. This study generated new python3 code available on GitHub: https://github.com/extavourlab/hpo_ova_eggL_screen; Kumar, 2020 (copy archived at https://github.com/elifesciences-publications/hpo_ova_eggL_screen).

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Cassandra G. Extavour (extavour@oeb.harvard.edu).

Experimental model and subject details

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Wild type and mutant lines of Drosophila melanogaster were obtained from publicly accessible stock centers and maintained as described in ‘Fly Stocks’ below. Genotypes and provenance are provided in the Key Resource Table. Candidate genes were randomly assigned to batches for screening (see the Supplementary file 1 for which genes were in each batch). F1 animals from the same cross were randomly assigned to experimental groups for phenotyping in all screens.

Method details

Fly stocks

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Flies were reared at 25°C at 60% humidity with standard Drosophila food (Sarikaya et al., 2012) containing yeast and in uncrowded conditions as previously defined (Sarikaya and Extavour, 2015). RNAi lines were obtained from the TRiP RNAi collection at the Bloomington Drosophila Stock Centre (BDSC) and from the Vienna Drosophila Resource Centre (VDRC). See Key Resources Table for complete list of stocks used in this study. Oregon R was used as a wild-type strain. The genotype of the traffic jam:Gal4 line used in the screen was y w; P{w[+mW.hs]=GawB}NP1624 (Kyoto Stock Center, K104–055; abbreviated hereafter as tj:Gal4). The hippo RNAi line used in the screen was y[1] v[1]; P{y[+t7.7]v[+t1.8]=TRiP. HMS00006}attP2 (BDSC:33614; abbreviated hereafter as hpo[RNAi]).

Egg and ovariole number counts

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Adult egg laying was quantified by crossing three virgin females of the desired genotype (see ‘Screen design’ below) with two males in a vial containing standard food and yeast granules (day one) and then transferring them into a fresh food vial without yeast granules for a 24 hr period. Eggs from vials were then counted by visual inspection of the surface of the food in the vial. Males and females were transferred to fresh food vials without yeast granules, every day thereafter until day six. All egg -laying measurements reported and analysed in the paper are the sum of the eggs laid by three adult female flies over the five days of this assay (days two through six without yeast granules). Data from any vial in which either a female or male died, during the course of the experiment, were not included in the analysis.

Ovariole number was quantified by mating ten virgin adult females with five virgin adult Oregon R males for three days post-eclosion in vials with yeast at 25°C and 60% humidity. After this three-day mating period, all 20 adult ovaries from the mated females were dissected in 1X PBS with 0.1% Triton-X-100 and stained with 1 µg/ml Hoechst 33321 (1:10,000 of a 10 mg/ml stock solution). Ovarioles were separated from each other with No. 5 forceps (Fine Science Tools) and counted by counting the number of germaria under a ZEISS Stemi 305 compact stereo microscope with a NIGHTSEA stereo microscope UV Fluorescence adaptor.

Screen design

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In the primary screen (Figure 1a: hpo[RNAi] Egg Laying), 463 candidate genes (Supplementary file 1) were screened for the effect of an RNAi-induced loss of gene function in a hpo[RNAi] background on the number of eggs laid in the first five days of mating (see ‘Egg and ovariole number counts’ above) by adult females. These females were the F1 offspring of UAS:candidate gene RNAi males crossed to P{w[+mW.hs]=GawB}NP1624; P{y[+t7.7] v[+t1.8]=TRiP.HMS00006}attP2 (tj:Gal4; UAS:hpo[RNAi]) virgin adult females (Figure 1a: hpo[RNAi] Egg Laying). All genes that yielded an egg laying count with a |Zgene| > 1 (see ‘Gene selection based on Z score and batch standardisation’ below) were selected to undergo two secondary screenings (n = 273, Table 2; Figure 1d). First, these genes were screened for effects on the egg laying of mated adult female offspring from a cross of UAS:candidate gene[RNAi] males and tj:Gal4 virgin adult females (Figure 1b: Egg Laying). Secondly, these genes were screened for effects on ovariole number in a hpo[RNAi] background. All 20 ovaries from ten adult female F1 offspring of a cross between UAS:candidate gene[RNAi] males to P{w[+mW.hs]=GawB}NP1624; P{y[+t7.7] v[+t1.8]=TRiP.HMS00006}attP2 (tj:Gal4; UAS:hpo[RNAi]) virgin adult females were scored for ovariole number (see ‘Egg and ovariole number counts’ above). (Figure 1c: hpo[RNAi] Ovariole Number).

Gene selection based on Z score and batch standardisation

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Candidate genes were screened in batches with an average size of 50 genes. For each batch, control flies were the female F1 offspring of Oregon R males crossed to P{w[+mW.hs]=GawB}NP1624; P{y[+t7.7] v[+t1.8]=TRiP.HMS00006}attP2 (tj:Gal4; UAS:hpo[RNAi]) virgin adult females. Because the control group in each batch had slightly different distributions of egg laying and ovariole number values (Figure 1—figure supplement 1), it was inappropriate to compare absolute mean values between genes that were scored in different batches. Instead, comparisons of the Z score of each candidate (Zgene) to its batch control group was used as a discriminant. This approach standardises for batch effects and allows the comparison of all genotypes within and across the primary and secondary screens with a single metric (Zgene).

Firstly, the mean and standard deviation of the eggs laid by the control genotype for a batch were calculated as μb and σb respectively. Then, using the number of eggs laid by adult females of a candidate gene RNAi (xgene) of the same batch, the Z score for the egg laying count of that gene (Zgene) was calculated as Zgene=xgene−μbσb. The same standardisation protocol was applied to both egg laying and ovariole number counts of every gene and its corresponding batch control.

Ovariole numbers were derived from counts of the number of ovarioles per ovary for 20 ovaries per candidate gene, and a threshold of |Zgene| > 2 was applied for ovariole number phenotype. Egg laying counts were derived from measurements of three females in a single vial per gene. We therefore chose to be more conservative in our Z score comparisons for the egg laying phenotype, than for ovariole number phenotype, and applied a stringent threshold of |Zgene| > 5 to select genes of interest. All genes with |Zgene| values above these thresholds are referred to throughout the study as ‘positive candidates’. (See Ipython notebooks 02_Z_score_calculation.ipynb and 02.2_Z_score_calculation_prediction.ipynb for code implementation and calculation of Z scores, and 06_Screen Analysis.ipynb for batch effects.)

Signalling pathway enrichment analysis

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To study the enrichment of a particular signalling pathway in a group of candidate genes that had similar phenotypic effects revealed by the screen, custom scripts (see 07_Signaling_pathway_analysis.ipynb for code implementation) were generated to implement two different methods (Figure 3a and b; Figure 3—figure supplement 1; Figure 5—figure supplement 6a,b).

The first method is a numerical method that uses random sampling to calculate the null distribution of the number of members (M) of a signalling pathway (S) that would be expected at random in a set of genes of size (N). The script randomly sampled N genes from among the 463 tested D. melanogaster signalling genes 10,000 times, and counted the number of genes (M) that were members of the signalling pathway S. Positive candidates in each of the three screens were sorted by their presence in signalling pathways and counted. The Z score was then calculated by comparing the experimentally observed number of positive candidates in each signalling pathway against the randomly sampled null distribution.

The second method used the hypergeometric p-value to calculate the probability of M members of a signalling pathway being in a group of N genes, given a starting population of 463 tested D. melanogaster signalling genes, and the known attribution to a pathway S of each gene.

Protein-Protein Interaction Network (PIN) building

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There is no standard complete Protein-Protein Interaction network (PIN) available for Drosophila melanogaster. However, there exist many smaller networks from different screens, as well as literature extractions. We therefore combined data from these sources and then created a PIN for use in the present study, as follows:

Step 1

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Several screens assessing protein-protein interactions have been centralised in a database called DroID: http://www.droidb.org. The version DroID_v2018_08 was used. All available datasets were first downloaded from that database using this link: http://www.droidb.org/Downloads.jsp. The description of all of these datasets can be found here: http://www.droidb.org/DBdescription.jsp.

Step 2

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We used the datasets from all screens that assessed direct protein-protein interactions and did not use the interolog database (predicted protein interaction based on mouse human and yeast PPIs). These direct assessment screens were seven in total, as follows:

We did not consider self-loop edges from proteins predicted to interact with themselves (homotypic or self-interactions). An important element to note is that the PPIs curated by FlyBase is a literature-based PPIs. FlyBase protein-protein interactions are experimentally derived physical interactions curated from the literature by FlyBase and does not include FlyBase-curated genetic interactions.

Step 3

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We concatenated the seven datasets listed above into a single unique database. A custom python script was created that downloads and reads each of the above seven unique PPI tables, and generates a single PIN (see 01_PIN_builder.ipynb). From this concatenation, a single-edge undirected network was created and saved. This network is hereafter referred to as the PIN (see 01_PIN_builder.ipynb). The PIN contains 10,632 proteins (nodes) and 85,019 interactions (edges), giving a network density of 0.0015.

Network metric computations

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The centrality of a node is often used as a measure of a node’s importance in a network. Within a PIN, the centrality of a gene reflects the number of interactions in which the gene directly or indirectly participates. Four different centrality metrics were computed for all genes in the PIN using the networkx python library:

  1. Betweenness reflects the number of shortest paths passing through a gene.

  2. Eigenvector is a measure of the influence of a gene in the network.

  3. Closeness measures the sum of shortest distance of a gene to all the other genes.

  4. Degree centrality corresponds to the normalised number of edges of a gene in the network.

While there exist more centrality measures, these four are commonly used to assess biological networks. These computed centrality parameters of the genes measured in the screen were computed with 03_ROC_curve_analysis_of_network_metrics.ipynb, and are reported in the Supplementary file 1 (see 09_Making_the_database_table.ipynb).

Receiver Operating Characteristic (ROC) curves

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To check whether the centrality of a gene in the network could predict the phenotypic effect produced by RNAi against that gene, ROC curves were plotted for the four aforementioned centrality measures of each gene in each screen. A ROC analysis is used to measure the correlation between a continuous variable (centrality) and a binary outcome (above or below Z score threshold). Therefore, for each screen, measured genes were rank ordered from high centrality to low centrality, and plotted against the binary outcome of |Zgene| being above or below the appropriate |Z score| threshold (>5 for egg laying and >2 for ovariole number). The Area Under the Curve (AUC) measures the extent of correlation between centrality and effect of a gene on measured phenotype. AUC above or below 0.5 indicates a positive or negative correlation respectively, while an AUC of 0.5 indicates no correlation of the parameters. The scikit-learn python package was used to calculate the AUC of each ROC curve plotted (see 03_ROC_curve_analysis_of_network_metrics.ipynb).

Building degree-controlled randomised networks

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We assessed the modularity of the networks by comparing the network metrics of each sub-network to a degree-controlled randomly sampled network. To generate this degree controlled random network, we applied a previously developed method (Guney et al., 2016). In short, nodes in the PPI are binned by degree with the minimum size of each bin being set at 100 nodes. Bins are constructed iteratively from the lowest degree to the highest degree in the network. To sample a set of nodes, the sub-network degree distribution is computed, using the bin cut-off, from the PPI. Then, nodes are randomly selected from each bin to match this degree distribution (see 05.2_Degree_Controlled_Testing.ipynb for code implementation).

Assessing the utility of the Seed Connector Algorithm in building network modules

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Network modules were assessed using the previously published Seed Connector Algorithm (SCA) (Wang et al., 2017; Wang and Loscalzo, 2018), implemented here in python (see 04_Seed-Connector.ipynb) and illustrated in Figure 5a. Creating a module using the SCA requires a list of seed genes and a PIN. From each of the three screens, we selected the genes whose |Zgene| value was above the threshold and created three seed lists, respectively (Figure 4c: Egg laying, hpo[RNAi] egg laying and hpo[RNAi] ovariole ‘seed’ list). A fourth list consisting of the intersection of the aforementioned seed lists was also collated and called the core ‘seed’ list (Figure 4b). Genes were assigned in the core list if they passed the Z threshold in all three screens. The SCA was then executed on each of these seed lists using the PIN. Not all genes in the four seed lists were found in the PIN (specifically, CG12147 in the hpo[RNAi] Egg Laying seed list and CG6104 in the hpo[RNAi] Ovariole number seed list were absent from the PIN) and were therefore eliminated from further network analysis. The removal of these two genes accounts for the variation in the number of positive candidates in Table 2 and the number of seed genes in the module. Modules were obtained for each seed list (Figure 5b; Figure 5—figure supplements 1–3) consisting of the seed genes (circles in Figure 5b and Figure 5—figure supplements 1–3) and previously untested genes added by the SCA (squares in Figure 5b and Figure 5—figure supplements 1–3) to increase the LCC size that we refer to as connector genes (see 04_Seed-Connector.ipynb). The results of the algorithm are summarised in the Supplementary file 1.

The modularity of the sub-networks was then assessed using four network metrics namely Largest Connected Component (LCC), number of edges, network density and average shortest path in the LCC. Each metric for each module was assessed using distance of the network metric to a null distribution. Initially, the null distribution was calculated by taking 1000 samples of 463 genes randomly selected from the PIN and calculating the above metrics. We found that the 463 genes selected in the signalling screen were already more connected than the null distribution of sets of 463 genes randomly selected from the PIN (Figure 5—figure supplement 4a). Therefore, to avoid a false positive detection of modularity, the four experimentally obtained sub-networks were compared to null distributions obtained by randomly sampling an equal number of genes from the 463 signalling candidate genes selected for our screen. For each of the four modules, comparison of the metrics was performed on the seed lists and the sub-network after the SCA. Most metrics were enriched in the seed group when compared to the null distribution with the exception of the Average shortest path (Figure 5—figure supplement 4b, light red line). The sub-networks obtained from the SCA further increased all four metrics suggesting the modularity of the four sub-networks (Figure 5—figure supplement 4b, dark red line; see 05_Network_Module_testing.ipynb for code implementation).

Meta network

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To build the meta network, the genes from all four sub-networks were concatenated into one network. This network was then visually sorted in an approach akin to projecting the network onto a Venn Diagram. The meta network was sorted by which of the three screens the gene was positive in. The intersections were genes whose |Zgene| value was above the threshold in more than one and possibly all three of the screening paradigms. For example, if a gene was found in the hpo[RNAi] Ovariole Number and Egg Laying sub-networks it is then assigned to the dual positive group hpo[RNAi] Ovariole Number/Egg Laying (Figure 6a, sub-network VI). After applying this grouping strategy, the connectivity across the groups was studied by calculating the edge density between all groups (density =Edges1;2Nodes1*Nodes2). Finally, the proportion of each signalling candidate in each of those groups was calculated by taking the number of members of a signalling pathway divided by the total members of a group (see Ipython notebook 08_MetaModule_Analysis.ipynb). A single gene, sloppy paired 1, was a seed in the Egg Laying sub-network and also a connector in the hpo[RNAi] Egg Laying sub-network; it fell within sub-network VII in the meta network, and is marked as a seed (grey) in Figure 6a.

Quantification and statistical analysis

Number of samples

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The number of samples across the different screens were as follows:

  • Hpo[RNAi] Egg Laying and Egg Laying screens

    • Controls: five vials of three females and two males

    • Sample: one vial of three females and two males

  • Hpo[RNAi] Ovariole number screen

    • Controls: 20 flies, two ovaries per fly considered as independent measurements

    • Sample: 10 flies, two ovaries per fly considered as independent measurements

Correction of batch effect

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Despite best efforts to maintain the exact same condition between each experiment, some variation was measured between the batches. Control flies showed variations in both measured phenotypes, ovariole number and egg laying (Figure 1—figure supplement 1). In order to compare the values measured across different batches, each sample was standardised by calculating its Z score (Zgene) to the control distribution. For each batch, the measurements for controls were pooled into a distribution, and the mean and standard deviation was computed. Then each sample was compared to its respective batch and its Z score computed (see ‘Gene selection based on Z score and batch standardisation’ for formula).

Statistical analysis

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All statistical analyses were performed using the scipy stats module (https://www.scipy.org/) and scikit-learn (https://scikit-learn.org/) python package. Statistical tests and p-values are reported in the figure legends. All statistical tests can be found in the Ipython notebooks mentioned below.

Data and code availability

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This study generated a series of python3 Ipython notebook files that perform the entire analysis presented in this study. All the results presented in this paper, including the figures with the exception of the network visualisations, which were created using Cytoscape3 (https://cytoscape.org/) can be reproduced by running the aforementioned python3 code. The raw data, calculations made with these data, and code used for calculations and analyses (Ipython notebooks) are available as supplementary information. For ease of access, legibility and reproducibility, the code and datasets have been deposited in a GitHub repository available at https://github.com/extavourlab/hpo_ova_eggL_screen.

Data availability

This study did not generate new unique reagents. This study generated new python3 code available on GitHub: https://github.com/extavourlab/hpo_ova_eggL_screen (copy archived at https://github.com/elifesciences-publications/hpo_ova_eggL_screen).

References

    1. Chao AT
    2. Dierick HA
    3. Addy TM
    4. Bejsovec A
    (2003)
    Mutations in eukaryotic release factors 1 and 3 act as general nonsense suppressors in Drosophila
    Genetics 165:601–612.
    1. Couderc JL
    2. Godt D
    3. Zollman S
    4. Chen J
    5. Li M
    6. Tiong S
    7. Cramton SE
    8. Sahut-Barnola I
    9. Laski FA
    (2002)
    The bric a brac locus consists of two paralogous genes encoding BTB/POZ domain proteins and acts as a homeotic and morphogenetic regulator of imaginal development in Drosophila
    Development 129:2419–2433.
    1. Godt D
    2. Couderc JL
    3. Cramton SE
    4. Laski FA
    (1993)
    Pattern formation in the limbs of Drosophila: bric à brac is expressed in both a gradient and a wave-like pattern and is required for specification and proper segmentation of the tarsus
    Development 119:799–812.
    1. Godt D
    2. Laski FA
    (1995)
    Mechanisms of cell rearrangement and cell recruitment in Drosophila ovary morphogenesis and the requirement of bric à brac
    Development 121:173–187.
  58. Book
    1. King RC
    (1970)
    Ovarian Development in Drosophila melanogaster
    Academic Press.

Decision letter

  1. Michael B Eisen
    Senior and Reviewing Editor; University of California, Berkeley, United States
  2. Felipe Aguilera
    Reviewer; University of Concepción, Chile
  3. Luke Lambourne
    Reviewer; Dana-Farber Cancer Institute, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This paper is amongst the first to show how computational network analyses based on protein-protein interactions can be successfully used to augment genetic screens to identify genes involved in essential developmental processes.

Decision letter after peer review:

Thank you for submitting your article "Topology-driven protein-protein interaction network analysis detects genetic modules regulating reproductive capacity" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Michael Eisen as the Senior and Reviewing Editor The following individuals involved in review of your submission have agreed to reveal their identity: Felipe Aguilera (Reviewer #2); Luke Lambourne (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to proceed without manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

This work aims to predict protein-protein interaction in a developmental context with a combination of approaches drawn from developmental genetics and system biology. This work represents an elegant study that combines computational biology and molecular developmental biology to explain how organ systems are formed.

Although it is our usual practice to combine the reviews into a single consensus, in this case I think the independent reviews offer distinct takes on the manuscript and suggestions for revisions and stand better on their own, although to expedite your revisions, I will summarize the main issues to address here:

Analysis:

Several issues were raised by reviewer 3 and during discussion:

1) Additional analysis is needed to support claim of non-random modules

In particular, the results of Figure 4 show that the positive pairs in the screen on average, tend to have higher degree in the network, which could be responsible for the higher connectivity of the seed genes, rather than them forming modules. This should be addressed with some form of control analysis.

2) Module separation

As a general rule, it is not surprising that the connectivity is higher within the output of the SCA algorithm, which returns a subnetwork of connected nodes, to the connectivity between two different SCA produced sub-networks. This is expected to happen with random lists of seed genes, and does not prove that functionally separate sub-networks have been identified. The claim is confusing given that there are shared subnetworks (V, VI, VII) which seems to contradict the idea of separate modules. Reviewer 3 offers several suggestions for how to make this analysis more convincing.

Writing and presentation:

1) In addition to suggestions about presentation in the reviews below, during discussion all three reviewers highlighted the value of the overall approach and felt that the manuscript merits publication in eLife. However there is a sense that the manuscripts lacks a clear take home message. This is not required for publication per se, but we all feel the manuscript could be made stronger in revisions by attempting to distill a take home message for readers.

2) The experimental validation results are not presented clearly. That section could benefit from more clarity in what specific aspects of the predictions are being tested and how the specific tests address them.

Reviewer #1:

In this study, the authors investigate the signaling pathways that regulate Drosophila ovary development and the rate of egg production. An earlier study from this lab identified a role for hippo signaling in these processes. Here, they performed an RNAi-based screen through 463 candidate genes involved in signal transduction to identify genetic modifiers of the hippo[RNAi] phenotype as well as genes that regulate the rate of egg laying through a potentially hippo-independent mechanism. The screens were well-designed and produced quantitative data that the authors could use to rank-order genes according to the strength and direction of the phenotype. Their strategy for assessing the rate of egg laying is in line with standard approaches in the field and their method of counting ovariole number is entirely appropriate. These screens identified a long list of genes, and they took a systems biology approach to assess the individual and combinatorial contributions of these genes to ovary development and function. These types of analyses are outside my area of expertise so I could not assess whether the appropriate computational methods were chosen and applied correctly. However, the writing of this section was clear to a non-expert and, taking their claims at face value, the data seem to support their interpretations.

In the final section of the manuscript they describe how their network analysis identified additional genes not uncovered by their screens and show that RNAi knockdown of these additional genes do, indeed, cause phenotypes in egg laying rates and ovariole number. This is a nice validation of the approach. As a minor point, the data presented in Figure 7 only summarize how many genes in the list showed a phenotype in each category but did not indicate what the genes are, which ones are associated with which phenotype, or what the z-scores were in each case (I could not find this information in the supplemental material either, though perhaps I missed it). If it has not been included already, the authors should provide this for completeness and to allow comparison to the other data in the study.

Overall, I think this study will be a useful though perhaps somewhat limited contribution to the field. The results of the screens provide a large amount of data for the field to build on and I appreciate their holistic approach to describing the interplay between genes and pathways in the regulation of processes as complex as development and oogenesis. At the same time, I struggled a bit to extract the most important take-away messages that change how I think about these processes. For example, they state in the Discussion that the core module consists of housekeeping genes and hedgehog pathway genes, but this could have largely been predicted from previous publications on this topic. Likewise, terminal filament formation is known to involve cell migration and, consistent with this, they find that several genes involved in cytoskeletal dynamics are important for proper specification of ovariole number. Though some of these genes have not been studied in this context, their involvement here is not too surprising. Nonetheless, it may be that the main innovation of this study is in the systems biology approach they have used to analyze the data, so I look forward to the online discussion with the other reviewers who have more expertise in this area.

Reviewer #2:

A general assessment of the work

This manuscript aims to predict protein-protein interaction in a developmental context. By using tissue-specific RNAi screening and systems biology approaches, the authors found known and unknown genes involved in ovarian development and function. A plethora of unknown genes was functionally tested, giving support to the topology-driven network analysis conducted, and the developmental regulatory modules found. This work represents an elegant study that combines computational biology and molecular developmental biology to explain how organ systems are formed.

Numbered summary of any substantive concerns

This article is generally well-structured, the data analysis is performed in a proper fashion, and the results are nicely presented, giving support to the major conclusions. I have no major concerns with regard to this manuscript, only some minor edits.

1) I am wondering if authors can give more detail regarding the paragraph starting "To choose candidates.…" I might be wrong, but have the feeling that this approach might produce bias in the results obtained by the authors.

2) In Figure 4—figure supplement 2, the authors show a comparison of Zgene scores of positive candidate genes sorted by centrality metrics. However, I wonder why the authors did not calculate p-values (significance level) between 1st and 5th quantile comparisons of Zgene scores shown in this figure? Significance levels in these comparisons might give strong support to the weak prediction of a gene that would affect a specific phenotype.

3) In Figure 6, for the sake of clarity, it is necessary to show the sloppy paired 1 gene in the meta-network analysis (Figure 6A). As is now shown in this figure, readers cannot see easily the importance of this gene within sub-network VII, which I think is one point that the authors want to highlight.

4) In step 3 in the protein-protein interaction network (PPI) building section (“Method Details” subsection), authors indicate that a custom python script was created to download and reads each of the PPI tables from DroID database, but I could not find this python script in the Github repository in the paper. Please, can authors upload this script in the repository?

Reviewer #3:

The authors present a novel study integrating the results of performing screens for regulators of reproduction in Drosophila with protein-protein interaction networks. Highly interesting, interdisciplinary work lying at the intersection of developmental and network biology. They identify genes regulating ovariole number and egg laying and analyze those genes in the context of PPI networks, predicting and experimentally testing additional novel reproductive regulatory genes with some success. However there are serious issues with the analysis supporting key claims in the manuscript related to network topology.

1) The claim of non-random modules is not supported by the analysis.

– The claim in the section title "Genes regulating egg laying and ovariole number regulation form non-random interaction modules" (L260-L261) is supported by Figure 5—figure supplement 4. In that figure both the seed genes and results from the SCA algorithm are compared to the subnetworks formed by randomly selected genes from the initial screen. This is a sensible comparison for the seed genes but not for the output of the SCA algorithm, since that algorithm builds a LCC (see Figure 5A) and so will obviously have a much larger LCC and be much more connected than randomly selected genes from the network.

– The results of Figure 4 show that the positive pairs in the screen on average, tend to have higher degree in the network, which could be responsible for the higher connectivity of the seed genes, rather than them forming modules. To account for this, the seed genes could be compared to a null distribution of degree-controlled randomized networks.

– The text reads "decreased average shorted path" (L331) but it is increased in 7 of 8 cases in the figure.

2) The claim of separate modules is not supported by the analysis.

– Similarly to point 1, it is not surprising that the connectivity is higher within the output of the SCA algorithm, which returns a subnetwork of connected nodes, to the connectivity between two different SCA produced sub-networks, that will happen with random lists of seed genes, it does not prove that functionally separate sub-networks have been identified.

– There are sizable shared subnetworks (V, VI, VII) which seems to contradict the idea of separate modules.

– The heat-map Figure 6B, shows very low edge density within the groups (diagonal squares), in contradiction to what is written in the text. This appears to be due to a miscalculation in the file 08_MetaModule_Analysis.ipynb in the Github repository: within the group the number of edges should be divided by (x2 – x) / 2 where x is the number of nodes in the group (assuming self-interactions are not considered), the edge density calculations between the different groups are correct.

– An alternative approach to this analysis could be to look at the connectivity of only the seed genes and not the connector genes in the different groups and comparing to a random assignment of group.

– Identifying modules of genes which affect one phenotype and not another is presumably made more difficult by the decision to filter candidate genes for two of the phenotypic screens based on the results of the first screen.

– The prediction results do not appear to be consistent with separate modules (see point 3 below).

3) The results of experimentally testing the predictions are presented in an unclear way, making it difficult for the reader to assess their accuracy.

The results in Figure 7A/B/C appear to show that the predictions from the modules are just as good for the phenotypes not associated with the module as for those associated with the module, e.g. for the EL phenotype there is one correct prediction from both the Core and EL modules and 9 correct predictions from the hpo[RNAi] ON/EL modules, with a similar number of predictions. So it would seem that these results suggest that, although there is positive predictive value overall relative to the initial signaling genes list, that the separate modules predicting their associated phenotype separately from the others is not supported by the data. This is not discussed in the text.

– From what I could understand, the fractions for the initial signaling gene lists for the EL and hpo[RNAi] ON phenotypes are not exactly consistent with the compared fractions of the predictions, due to the filtering applied on the hpo[RNAi] of |Z| > 1, for the initial screens. Perhaps the fractions for the 2 affected bars in Figure 7C could also be calculated with this threshold applied to remove genes?

– There are no p-values calculated, comparing the predictions to the original screens and no error bars shown in Figure 7.

– The title of Figure 7C could be changed to make it clearer that this contains predictions from all modules.

– There is no “All screens” column in either Figure 7C or Figure 7D for comparison.

https://doi.org/10.7554/eLife.54082.sa1

Author response

1) Although it is our usual practice to combine the reviews into a single consensus, in this case I think the independent reviews offer distinct takes on the manuscript and suggestions for revisions and stand better on their own, although to expedite your revisions, I will summarize the main issues to address here:

2) Analysis:

Several issues were raised by reviewer 3 and during discussion:

(2.1) Additional analysis is needed to support claim of non-random modules

In particular, the results of Figure 4 show that the positive pairs in the screen on average, tend to have higher degree in the network, which could be responsible for the higher connectivity of the seed genes, rather than them forming modules. This should be addressed with some form of control analysis.

We understand the concerns of the reviewer and we have modified our analysis to better support the claim of putative non-random modules. Firstly, we performed a new analysis, comparing the network metrics of the seed genes, to two different control groups: (a) a random selection of the same number of genes, chosen from among the signalling candidates, and (b) a degree-controlled random network of the same number of genes (new Figure 4—figure supplement 3). Our results indicate that in most cases, the seed gene lists display higher network metrics than both null distributions. We therefore interpret this as evidence that the seed genes may constitute a non-random putative interaction module, independent of application of the SCA.

On application of the SCA, we find that there is reduction of the difference in network metrics when compared to the two null distributions described above, of similarly sized seed lists selected from either (a) the signalling genes (light gray curve in new Figure 5—figure supplement 5) or (b) a degree-controlled seed list (dark grey curve in new Figure 5—figure supplement 5). We interpret this result to mean that though the SCA is able to predict genes that may function in the network, its application does not increase the modularity of the sub-network in this setting. We believe that this may also explain why genes predicted by the SCA are more likely to affect any of the three phenotypes measured, rather than the specific subnetwork in which they were predicted. We present and discuss these new control analyses in the revised manuscript paragraph six subsection “Genes regulating egg laying and ovariole number regulation form non-random gene interaction networks” and subsection “Building degree-controlled randomized networks”, and in the new figure supplements Figure 4—figure supplement 3 and Figure 5—figure supplement 5. We also qualify our description of the possible relationship between genes in the sub-networks under study, by calling them “putative modules” only when we describe them as predicted by the SCA, and subsequently as “sub-networks” throughout the revised manuscript. This comment is addressed in more detail in response to reviewer 3’s comments 2.1 and 2.2.

(2.2) Module separation

As a general rule, it is not surprising that the connectivity is higher within the output of the SCA algorithm, which returns a subnetwork of connected nodes, to the connectivity between two different SCA produced sub-networks. This is expected to happen with random lists of seed genes, and does not prove that functionally separate sub-networks have been identified. The claim is confusing given that there are shared subnetworks (V, VI, VII) which seems to contradict the idea of separate modules. Reviewer 3 offers several suggestions for how to make this analysis more convincing.

We understand the reviewers' point, and have addressed this in two major ways. First, we performed the suggested control analyses as described in response to comment 1 above, and in light of those results, are more conservative in our discussion and interpretation of the “connectedness” of the genes in phenotypically linked sub-networks. Second, we have revised the text to better convey what we meant in the original manuscript by “separate modules,” and now explain that one interpretation of the data is that genes in such sub-networks (as we now call them) may potentially function rather independently of other sub-networks, in regulating a given phenotype, or pairs of phenotypes We have more detailed explanations of this point in response to reviewer 3's comment 3.1, 3.2 and 3.6.

(3) Writing and presentation:

(3.1) In addition to suggestions about presentation in the reviews below, during discussion all three reviewers highlighted the value of the overall approach and felt that the manuscript merits publication in eLife. However there is a sense that the manuscripts lacks a clear take home message. This is not required for publication per se, but we all feel the manuscript could be made stronger in revisions by attempting to distill a take home message for readers.

We take this point, and in response have modified the Discussion section to better present what we believe are the most important take home messages of the paper. We have addressed this in further detail in response to reviewer 1’s comment 4.

(3.2) The experimental validation results are not presented clearly. That section could benefit from more clarity in what specific aspects of the predictions are being tested and how the specific tests address them.

To address this concern, we have made significant modifications to the presentation of experimental validation results. We have modified original Figure 7C as per the advice of the reviewer, and merged it with original Figure 7D to create a new Figure 7C, which we believe provides a better understanding of our results (discussed in detail in response to reviewer 3’s comment 4.2 ). We have also modified the description of Figure 7 in the revised results (subsection “Network analysis predicts novel genes involved in egg laying and ovariole number”; discussed in detail in response to reviewer 3’s comment 4.4) and Discussion (subsection “Network analysis as a tool in developmental biology”; discussed in detail in response to reviewer 3’s comment 4.1).

Reviewer #1:

(1) In this study, the authors investigate the signaling pathways that regulate DrosophilaDrosophila ovary development and the rate of egg production. An earlier study from this lab identified a role for hippo signaling in these processes. Here, they performed an RNAi-based screen through 463 candidate genes involved in signal transduction to identify genetic modifiers of the hippo[RNAi] phenotype as well as genes that regulate the rate of egg laying through a potentially hippo-independent mechanism. The screens were well-designed and produced quantitative data that the authors could use to rank-order genes according to the strength and direction of the phenotype. Their strategy for assessing the rate of egg laying is in line with standard approaches in the field and their method of counting ovariole number is entirely appropriate. These screens identified a long list of genes, and they took a systems biology approach to assess the individual and combinatorial contributions of these genes to ovary development and function. These types of analyses are outside my area of expertise so I could not assess whether the appropriate computational methods were chosen and applied correctly. However, the writing of this section was clear to a non-expert and, taking their claims at face value, the data seem to support their interpretations.

(2) In the final section of the manuscript they describe how their network analysis identified additional genes not uncovered by their screens and show that RNAi knockdown of these additional genes do, indeed, cause phenotypes in egg laying rates and ovariole number. This is a nice validation of the approach. As a minor point, the data presented in Figure 7 only summarize how many genes in the list showed a phenotype in each category but did not indicate what the genes are, which ones are associated with which phenotype, or what the z-scores were in each case (I could not find this information in the supplemental material either, though perhaps I missed it). If it has not been included already, the authors should provide this for completeness and to allow comparison to the other data in the study.

We appreciate the comments of the reviewer, which made us realize that we should emphasize more clearly where to find this information within the manuscript. The novel genes (i.e. connector genes) tabulated in original Figures 7, Figure 7—figure supplement 1 and Figure 7—figure supplement 2, are indicated as triangles with the gene names shown beside them, in each of the four putative modules generated by the SCA, shown in original Figure 5B and Figure 5—figure supplement 1-3. The genes are also listed in Table 4 and can be identified under the column header [ModuleName]_Connector. To highlight this for the reader, we have added new text to the revised legend of Figure 7 as follows: “The connector genes are listed in Table 4, and can be identified under the column header [ModuleName]_Connector. The raw data for egg laying and ovariole number for each of the connector genes can be found within Table 4.”.

(3) Overall, I think this study will be a useful though perhaps somewhat limited contribution to the field. The results of the screens provide a large amount of data for the field to build on and I appreciate their holistic approach to describing the interplay between genes and pathways in the regulation of processes as complex as development and oogenesis.

We thank the reviewer for this comment. The aim of the project was to indeed identify more genes that affect the development of the ovaries, both to advance the field of ovary development and also to provide an example of how such large datasets may be better used to enhance our understanding of complex developmental processes.

(4) At the same time, I struggled a bit to extract the most important take-away messages that change how I think about these processes. For example, they state in the discussion that the core module consists of housekeeping genes and hedgehog pathway genes, but this could have largely been predicted from previous publications on this topic. Likewise, terminal filament formation is known to involve cell migration and, consistent with this, they find that several genes involved in cytoskeletal dynamics are important for proper specification of ovariole number. Though some of these genes have not been studied in this context, their involvement here is not too surprising. Nonetheless, it may be that the main innovation of this study is in the systems biology approach they have used to analyze the data, so I look forward to the online discussion with the other reviewers who have more expertise in this area.

We appreciate this point, and in response have added the following text to the beginning of the revised Discussion to help clarify the take home messages of the work, as follows: “In this study, we have identified many novel genes that regulate either or both of egg laying and ovariole number. Though the development of the insect ovary has been studied for over 100 years, our understanding of the genetic mechanisms that regulate the development of the ovary is sparse. The female reproductive system and its ability to produce eggs are one of the key determinants for the survival of a species in an ecological niche. The genes we have uncovered here are possible targets for the regulation of the construction and function of the reproductive system in Drosophila melanogaster , and potentially in other species of insects as well. Understanding the gene regulatory networks that regulate egg laying and ovariole development could provide a framework to understand the key regulatory steps during this process that may be modified over evolutionary time, to yield the wide diversity of ovariole numbers and fecundities displayed by extant insects. We suggest that, given our success in applying a network approach to the results of a traditional forward genetic screen, the field of developmental genetics should find it fruitful to apply network analyses to the interpretation of large scale transcriptomic and proteomic data.”

Reviewer #2:

[…]

(2) Numbered summary of any substantive concerns

This article is generally well-structured, the data analysis is performed in a proper fashion, and the results are nicely presented, giving support to the major conclusions. I have no major concerns with regard to this manuscript, only some minor edits.

(2.1) I am wondering if authors can give more detail regarding the paragraph starting "To choose candidates.…" I might be wrong, but have the feeling that this approach might produce bias in the results obtained by the authors.

We acknowledge the concerns of the reviewer in this section, where we state our reasons for the setting of thresholds of phenotypic significance in the screens. We considered running our egg laying screen with multiple vials containing three flies each, but as we endeavoured to test many genes for multiple phenotypes with as high throughput but accurate a method as possible, we settled on using only a single vial of three flies to measure egg laying. Aiming to mitigate this bias, we did, however, set our thresholds for positive candidates in the egg laying at a higher value of |5| when compared to an ovariole number threshold of |2| to account for the difference in statistical power. We also address this concern in the Materials and methods section.

(2.2) In Figure 4—figure supplement 2, the authors show a comparison of Zgene scores of positive candidate genes sorted by centrality metrics. However, I wonder why the authors did not calculate p-values (significance level) between 1st and 5th quantile comparisons of Zgene scores shown in this figure? Significance levels in these comparisons might give strong support to the weak prediction of a gene that would affect a specific phenotype.

We have taken this suggestion and calculated the significance for the differences of Zgene scores between the 1st and 5th quintile. We have modified Figure 4—figure supplement 2 by adding asterisks to indicate significant differences reflected by these p-values, which are shown under each comparison. Significance thresholds were set at 0.05 and are indicated in the revised figure legend, which now contains new text as follows: “significant differences (p-value<0.05 Mann Whitney U test) are indicated by asterisks. p-values are displayed below every bar plot.” We also revised the text in subsection “Centrality of genes in the ovarian protein-protein interaction networks can predict the likelihood of loss of function phenotypic effects” that describes the relationship between the centrality of genes and the strength of phenotypic effect to include the relevant pvalue < 0.05 in Figure 4—figure supplement 2”

(2.3) In Figure 6, for the sake of clarity, it is necessary to show the sloppy paired 1 gene in the meta-network analysis (Figure 6A). As is now shown in this figure, readers cannot see easily the importance of this gene within sub-network VII, which I think is one point that the authors want to highlight.

This comment by the reviewer made us realize that we needed to clarify that our intention with the reference to slp1 in the legend of Figure 6A was simply to explain that it is a gene that is present both as a seed gene in the Egg Laying sub-network as well as a novel predicted gene (connector) in the hpo[RNAi] Egg Laying sub-network. For improved clarity, we have removed all mention of slp1 from the revised legend of Figure 6A and have instead explained its presence in two sub-networks within the revised “Meta network” section of the Materials and methods.

(2.4) In step 3 in the protein-protein interaction network (PPI) building section (“Method Details” subsection), authors indicate that a custom python script was created to download and reads each of the PPI tables from DroID database, but I could not find this python script in the Github repository in the paper. Please, can authors upload this script in the repository?

We thank the reviewer for pointing this out, and have both confirmed that the script is in the repository (called 01.1_PIN_builder.ipynb) and also added a reference to this script in subsection “Protein-Protein Interaction Network (PIN) building”.

Reviewer #3:

(1) The authors present a novel study integrating the results of performing screens for regulators of reproduction in Drosophila with protein-protein interaction networks. Highly interesting, interdisciplinary work lying at the intersection of developmental and network biology. They identify genes regulating ovariole number and egg laying and analyze those genes in the context of PPI networks, predicting and experimentally testing additional novel reproductive regulatory genes with some success. However there are serious issues with the analysis supporting key claims in the manuscript related to network topology.

We thank the reviewer for their very careful and thorough analysis of our work. We are also grateful for their appreciation of the key aspects and novelty of our work. We understand their reservations on some aspects of the manuscript and have attempted to address them with more analyses or through clearer explanations.

(2) The claim of non-random modules is not supported by the analysis.

We have both modified our analyses and performed new ones to more carefully assess this claim, and to more conservatively interpret the results of these assessments . We have a more detailed explanation below in our response to comment 2.1.

(2.1) The claim in the section title "Genes regulating egg laying and ovariole number regulation form non-random interaction modules" (L260-L261) is supported by Figure 5—figure supplement 4. In that figure both the seed genes and results from the SCA algorithm are compared to the subnetworks formed by randomly selected genes from the initial screen. This is a sensible comparison for the seed genes but not for the output of the SCA algorithm, since that algorithm builds a LCC (see Figure 5A) and so will obviously have a much larger LCC and be much more connected than randomly selected genes from the network.

We understand the concerns of the reviewer, and in response we have modified our analysis to better address this interpretation. Firstly, we compared the network metrics of the seed genes both to a similarly sized random selection of genes from the signalling candidates, and to a degree-controlled random network (see reference to Guney et al., 2016 in our response to comment 2.2 by this reviewer). Our results, shown in new Figure 4—figure supplement 3, indicate that the seed gene lists display higher network metrics than both null distributions in most cases. We therefore conclude that, independent of application of the SCA, the groups of seed genes display many features of modularity by this assessment, and this analysis thus suggests that they may function as putative modules. We report this in subsection “Genes regulating egg laying and ovariole number regulation form non-random gene interaction networks” of the revised manuscript.

Secondly, to directly address this important point by the reviewer, we assessed these network metrics in the putative modules generated by application of the SCA. We found that there was an overall reduction of network metrics when compared to null distributions of similarly sized seed lists selected from either the signalling genes (light gray curve in new Figure 5—figure supplement 5) or a degree-controlled seed list (dark grey curve in Figure 5—figure supplement 5). We therefore conclude that though the SCA may be able to correctly predict genes that may function in the network (as we present in revised Figure 7 and its two supplements), it does not increase the “modularity” of the sub-networks. We therefore conservatively refer to these connected groups of genes as “sub-networks” throughout the remainder of the manuscript. These analyses and interpretations are explained and presented in paragraph six of subsection “Genes regulating egg laying and ovariole number regulation form non-264 random gene interaction networks”.

(2.2) The results of Figure 4 show that the positive pairs in the screen on average, tend to have higher degree in the network, which could be responsible for the higher connectivity of the seed genes, rather than them forming modules. To account for this, the seed genes could be compared to a null distribution of degree-controlled randomized networks.

We understand the concern of the reviewer, and have implemented this suggestion as described in response to this reviewer’s comment 2.1 above, using the method of Guney and colleagues (Guney et al., 2016).

The revised Materials and methods section now contains the following text explaining the methodology for obtaining the degree-controlled randomized network, and mentioning the sections in the python code where this is applied, as follows. “Building degree-controlled randomized networks. We assessed the modularity of the networks by comparing the network metrics of each sub-network to a degree-controlled randomly sampled network. To generate this degree controlled random network, we applied a previously developed method (Guney et al., 2016). In short, nodes in the PPI are binned by degree with the minimum size of each bin being set at 100 nodes. Bins are constructed iteratively from the lowest degree to the highest degree in the network. To sample a set of nodes, the sub-network degree distribution is computed, using the bin cut-off, from the PPI. Then, nodes are randomly selected from each bin to match this degree distribution (see 05.2_Degree_Controlled_Testing.ipynb for code implementation).”

(2.3) The text reads "decreased average shorted path" (L331) but it is increased in 7 of 8 cases in the figure.

Our new analyses with more appropriate control groups for the SCA-generated putative modules do indeed often display relatively increased paths. This new result is described in paragraph six of subsection “Genes regulating egg laying and ovariole number regulation form non-random gene interaction networks”, and shown in new Figure 5—figure supplement 5.

(3) The claim of separate modules is not supported by the analysis.

We believe that this comment refers to our interpretation of the data shown in original Figure 6, which is discussed in subsection “Low edge densities between sub-networks suggest genetically separable mechanisms of ovariole number and egg laying”. This comment from the reviewer helped us realize that, in addition to performing the additional control analyses suggested in this reviewer’s comment 2.1, which encouraged us to be more conservative with our description of these gene groups and refer to them simply as “sub-networks” in the revised manuscript, we should improve the clarity of our interpretation of the groups of genes we present in Figure 6. In the “meta network” shown in this figure, we first separated genes into the seven different groups based on the phenotype(s) affected in their loss of function condition as assessed in our initial screens (Figure 1). Of these seven groups, three groups included genes that affected only one of the three measured phenotypes (groups I, II and III in Figure 6A), three groups included genes that affect two of the three phenotypes (groups V, VI and VII in Figure 6A), and the seventh group included genes that affected all three phenotypes (group IV in Figure 6A). The differences in protein-protein interactions between these seven different phenotypically binned groups suggested the possibility that each phenotype could be largely regulated by genes that do not interact very much with genes regulating another phenotype. We have added new text to this section in the revised manuscript with the aim of improving the explanation of our thought process for suggesting this interpretation. We further address related points in our responses to this reviewer’s comments 3.1 and 3.2 below.

(3.1) Similarly to point 1, it is not surprising that the connectivity is higher within the output of the SCA algorithm, which returns a subnetwork of connected nodes, to the connectivity between two different SCA produced sub-networks, that will happen with random lists of seed genes, it does not prove that functionally separate sub-networks have been identified.

We take this point by the reviewer, and in response to this and other reviewer comments, are more conservative in our interpretation of the functions of these gene groups in the revised manuscript. The seed lists for the SCA included any gene that affected a phenotype, unlike the seven groups of the meta network, which included genes that affected only one, two, or all three phenotypes. We have more detailed explanations in our responses to this reviewer’s comments 3.2, 3.4 and 3.6.

(3.2) There are sizable shared subnetworks (V, VI, VII) which seems to contradict the idea of separate modules.

We believe that we have addressed this comment by the modifications described in our response to comment 3 above. We hope that our revised section on low edge densities clarifies that we intended to communicate an interpretation of separable putative genetic interaction groups affecting one or more phenotypes, rather than independent functional modules, combined with our more conservative interpretations of these groups as simply “sub-networks,” has clarified our logic and intent here.

(3.3) The heat-map Figure 6B, shows very low edge density within the groups (diagonal squares), in contradiction to what is written in the text. This appears to be due to a miscalculation in the file 08_MetaModule_Analysis.ipynb in the Github repository: within the group the number of edges should be divided by (x2 – x) / 2 where x is the number of nodes in the group (assuming self-interactions are not considered), the edge density calculations between the different groups are correct.

We thank the reviewer for the thoroughness of their review, which has allowed us to correct this inadvertent mistake. We have now corrected the error in the formula in the code (file: 08_MetaModule_Analysis.ipynb) and updated the figure with the new densities. We are here attaching the new version of the figure for simplicity. This new, corrected result does indicate higher edge densities within groups, than between groups (new Figure 6B).

(3.4) An alternative approach to this analysis could be to look at the connectivity of only the seed genes and not the connector genes in the different groups and comparing to a random assignment of group.

We thank the reviewer for this suggestion. We have implemented it by adding the results of a new analysis, shown in new Figure 6—figure supplement 1 and described in the revised Results section in subsection “Low edge densities between sub-networks suggest genetically separable mechanisms of ovariole number and egg laying”. In this analysis, we ask if the seven groups of genes that we bin by phenotype in Figure 6A – considering either the seed genes alone, or the seed genes plus the connector genes predicted by the SCA – show connectivity different from that expected from a random group of genes of the same size. We found that the connectivity of the seed genes alone was not greater than expected by chance, but that including connector genes in the group changed their connectivity to be either higher or lower than that of a control group of randomized genes. This analysis helped clarify the internal structure of the meta network.

(3.5) Identifying modules of genes which affect one phenotype and not another is presumably made more difficult by the decision to filter candidate genes for two of the phenotypic screens based on the results of the first screen.

We agree with the reviewer that this screening strategy is likely to lead to us missing some genes that affect the second phenotype, if they did not pass our threshold for analysis based on the first screen. For this reason, we had included this explanatory text in the original manuscript “ Once established during larval life, ovariole number in Drosophila remains unaltered through to and during adulthood, even if oogenesis within those ovarioles suffers congenital or age-related defects (King, 1970). Because previous work suggested that ovariole number in Drosophila could have at least some predictive relation to egg laying (Cohet and David, 1978; Klepsatel et al., 2013b; Sarikaya and Extavour, 2015), we reasoned that scoring the latter phenotype in a primary screen (Figure 1A) could be an effective way to uncover ovariole number regulators (Figure 1C). While our results showed that this was true in many cases, it was also clear that these two traits can vary independently (Figure 2), highlighting the fact that ovariole number is not the only determinant of egg laying. Egg-laying dynamics, even during the limited five day assay used in our study, are likely influenced not just by a single anatomical parameter such as ovariole number, but rather by many biological, biomechanical, hormonal and behavioural processes.”. We have left this text unchanged in the revised manuscript.

(3.6) The prediction results do not appear to be consistent with separate modules (see point 3 below).

Thanks to this comment and others by this reviewer, we realised through our new analyses that the SCA results indeed do not support a prediction of functionally separate modules. We have therefore modified the text of the manuscript throughout the revised manuscript to reflect our new, more conservative interpretation of our results, as described in our response to this reviewer’s comment 2.1.

(4) The results of experimentally testing the predictions are presented in an unclear way, making it difficult for the reader to assess their accuracy.

To address this concern of the reviewer we have made significant modifications to the presentation of experimental validation results. We have modified Figure 7C as per the advice of the reviewer, and merged it with Figure 7D for better comparison (discussed in further detail in our response to this reviewer’s comment 4.2). We have also modified the description of the new Figure 7 in the Results (subsection “Network analysis predicts novel genes involved in egg laying and ovariole number”; discussed also in detail in our response to this reviewer’s comment 4.4) and the Discussion on the consequence of this result (subsection “Network analysis as a tool in developmental biology”; also discussed in detail in our response to this reviewer’s comment 4.1).

(4.1) The results in Figure 7A/B/C appear to show that the predictions from the modules are just as good for the phenotypes not associated with the module as for those associated with the module, e.g. for the EL phenotype there is one correct prediction from both the Core and EL modules and 9 correct predictions from the hpo[RNAi] ON/EL modules, with a similar number of predictions. So it would seem that these results suggest that, although there is positive predictive value overall relative to the initial signaling genes list, that the separate modules predicting their associated phenotype separately from the others is not supported by the data. This is not discussed in the text.

We have incorporated this important observation by the reviewer into a revised section of the Discussion, and have differentiated between prediction rates within the module, and prediction rates for genes involved in any of the phenotypic classes.

(4.2) From what I could understand, the fractions for the initial signaling gene lists for the EL and hpo[RNAi] ON phenotypes are not exactly consistent with the compared fractions of the predictions, due to the filtering applied on the hpo[RNAi] of |Z| > 1, for the initial screens. Perhaps the fractions for the 2 affected bars in Figure 7C could also be calculated with this threshold applied to remove genes?

We understand the comment of the reviewer as follows in the original Figure 7C, we compare the number of connectors from any of the three modules that are above the |Z| gene threshold of the screen. The |Z| gene threshold for the connectors in the Egg Laying and hpo[RNAi]EL screens are |5| while the |Z| gene threshold for the connectors in hpo[RNAi]ON Screen is |2|. Given that we are comparing the results of the connectors with the original signalling candidate screen results, the reviewer suggests that we utilise the same thresholds that we used in the original screen. We agree that this is logical, and accordingly, modified the thresholds for the connectors in what has become revised Figure 7C. The genes from the connector list were first subject to a threshold of |1| and the genes that were above this threshold were then counted depending on whether they were above the |Z| gene threshold |5| in Egg Laying and hpo[RNAi]Egg Laying screens and |2| in the hpo[RNAi]Ovariole Number screen. Application of this new method does not change the number of genes in the hpo[RNAi]Egg Laying screen, but does reduce the number of genes in the Egg Laying and hpo[RNAi]Ovariole Number screen. The results of these calculations have been added to the manuscript as new Figure 7—figure supplement 2.

(4.3) There are no p-values calculated, comparing the predictions to the original screens and no error bars shown in Figure 7.

This comment by the reviewer made us realize that reorganizing the figure could help with its interpretation and avoid the confusion inadvertently caused by the original version. Figures 7A and 7B, which remain unchanged from the original version in this revised manuscript, show the percentage of connector genes within each phenotypic bin, and therefore do not have error bars or p-values. In modified Figure 7C, the prediction rate comparisons between the connector candidates and the signalling candidates now indicate calculated p-values with asterisks. We have modified and merged former Figures 7C and 7D into a single new Figure 7C, shown above in our response to this reviewer’s comment 4.2.

(4.4) The title of Figure 7C could be changed to make it clearer that this contains predictions from all modules.

We have taken this suggestion by modifying the title of Figure 7C to read “Positive prediction rates of all unique connectors compared to signalling candidates”. We have also modified the legend of Figure 7C to improve the clarity of this point. The modified legend now reads as follows: “Proportion of all unique connector genes (dark grey bars) predicted by all four sub-networks compared to the proportion of signaling candidate genes (light grey bars) with |Zgene| above the respective threshold in any of the three phenotypic screens (Figure 1A, 1B, 1C). Positive connector and signaling candidates that were above the |Zgene| threshold in all three phenotypic screens (Figure 1A, 1B, 1C) are indicated in an “All phenotypes” column. Statistical significance was computed using the binomial test, comparing the probability of a positive candidate amongst the connectors to the probability of a positive candidate amongst the signalling candidates (p-value is found below each bar).”

(4.5) There is no “All screens” column in either Figure 7C or Figure 7D for comparison.

To address this comment, we have added an “All screens” column to both revised Figure 7C and 7D, which are discussed in detail in our response to this reviewer’s comment 4.2.

https://doi.org/10.7554/eLife.54082.sa2

Article and author information

Author details

  1. Tarun Kumar

    Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Contributed equally with
    Leo Blondel
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4071-4342

  2. Leo Blondel

    Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Contribution
    Conceptualization, Data curation, Software, Formal analysis, Validation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Tarun Kumar
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2276-4821

  3. Cassandra G Extavour

    1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
    2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing
    For correspondence
    extavour@oeb.harvard.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2922-5855

Funding

National Institutes of Health (1R01-HD073499)

  • Tarun Kumar
  • Cassandra G Extavour

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Senior and Reviewing Editor

  1. Michael B Eisen, University of California, Berkeley, United States

Reviewers

  1. Felipe Aguilera, University of Concepción, Chile
  2. Luke Lambourne, Dana-Farber Cancer Institute, United States

Publication history

  1. Received: December 1, 2019
  2. Accepted: September 1, 2020
  3. Accepted Manuscript published: September 9, 2020 (version 1)
  4. Version of Record published: October 12, 2020 (version 2)

Copyright

© 2020, Kumar et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Tarun Kumar
  2. Leo Blondel
  3. Cassandra G Extavour
(2020)
Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity
eLife 9:e54082.
https://doi.org/10.7554/eLife.54082

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