One of the most powerful techniques for characterizing gene function is to generate transgenic animals in which an epitope tag such as GFP has been fused to the gene at its normal genomic location (Ross-Macdonald et al., 1999; Morin et al., 2001; Skarnes et al., 2004). These tagged proteins are extremely useful as they permit determination of protein localization in vivo as well as conditional, tissue specific, temporal and reversible removal of the tagged proteins (Nagarkar-Jaiswal et al., 2015). However, previous methods for generating protein trap alleles in Drosophila have allowed only about 800 genes to be successfully tagged (Kelso et al., 2004; Buszczak et al., 2007; Quinones-Coello et al., 2007; Aleksic et al., 2009; Lowe et al., 2014).

We previously developed a flexible system for engineering the Drosophila genome using the Minos-Mediated Integration Cassette (MiMIC) transposable element. We generated 15,660 strains with a single MiMIC inserted at random within the fly genome and mapped their insertion site (Bellen et al., 2011; Venken et al., 2011; Nagarkar-Jaiswal et al., 2015). MiMIC carries sequences that function as a gene and protein trap when inserted in the proper orientation in a coding intron. Moreover, its content can be replaced by Recombination-Mediated Cassette Exchange (RMCE) leading to the introduction of any desired DNA, such as an artificial exon that encodes a protein tag. This approach can potentially be used to tag thousands of genes. Currently, 2854 existing insertions are located within the coding introns of 1862 distinct genes (Nagarkar-Jaiswal et al., 2015), and MiMIC-like elements can now be placed in any gene of interest by CRISPR (Zhang et al., 2014). Unfortunately, the RMCE method needed to convert these insertions into functional protein traps requires embryonic injections of an appropriate donor DNA and screening of many offspring to identify the desired events, a labor and cost-intensive procedure that does not scale easily. We therefore developed a more efficient and economical in vivo genetic tagging methodology that can in principle be used to generate protein trap alleles of all Drosophila genes.

We developed a genetic strategy that allows the desired RMCE event to take place efficiently without the need for microinjection. The method uses FLP recombinase to release a genomically integrated DNA flanked by FRT sites into the nucleoplasm where it can efficiently undergo phiC31 integrase-mediated cassette exchange, as shown by Gohl et al. (2011). As shown in Figure 1A, we engineered three donor cassettes, one for each reading frame. The core, which contains a splice acceptor (SA) followed by a (GGS)₄ flexible linker, multiple tags (EGFP-FlAsH-StrepII-TEVcs-3xFlag {GFSTF}), another (GGS)₄ flexible linker, and a splice donor (SD), is flanked by two inverted attB sites for phiC31-mediated RMCE (Venken et al., 2011). We then cloned this cassette core between tandem FRT sites in a P-element transformation vector (Gong and Golic, 2003). FLP-mediated recombination between the tandem FRT sites excises a circular donor DNA molecule from its initial genetic locus, promoting its efficient recombination with a distal target site (Golic et al., 1997). A mini-white eye color marker gene between our donor cassette and one of the FRT sites allows us to monitor the presence or absence of the donor cassette in FLP recombinase-containing stocks.

Figure 1

Download asset Open asset

Figure 1—source data 1

List of constructs.

https://doi.org/10.7554/eLife.08469.003

Download elife-08469-fig1-data1-v2.doc

Figure 1—source data 2

List of fly strains generated.

Stocks #1 to 6 are stocks that contain the GFSTF construct (phase 0, 1, and 2) for tagging genes/proteins that map to chromosome II and III. Stocks # 7: FRT cassette maps to chromosome 2 and contains phase 0 construct; #8: FRT cassette maps to chromosome 2 and contains phase 1 construct; #9: FRT cassette maps to chromosome 2 and contains phase 2 construct; #10: FRT cassette maps to chromosome 3 and contains phase 0 construct; #11: FRT cassette maps to chromosome 3 and contains phase 1 construct; #12 FRT cassette maps to chromosome 3 and contains phase 2 construct.

https://doi.org/10.7554/eLife.08469.004

Download elife-08469-fig1-data2-v2.xlsx

We created 6 stocks (Figure 1—source data 2), each harboring one of the three donor transgenes located on the second or third chromosome, and a heat shock-inducible FLP recombinase and a germ line-expressed phiC31 integrase on the X-chromosome. Because the heat shock-inducible FLP recombinase is somewhat leaky at 18°C, the donor transgene is lost from these stocks at a low frequency, resulting in rare white-eyed flies, which we periodically discard.

To initiate RMCE, we crossed the appropriate donor flies to MiMIC-containing flies and heat shocked the resulting embryos and larvae (Figure 2). Within the primordial germ cells of some of the embryos and larvae, phiC31 integrase catalyzed recombination between attB sites in the donor and attP sites in the MiMIC transposon. The positive RMCE events were selected based on the loss of the y + marker present in the original MiMIC (Figure 2). We confirmed the integration and orientation of the donor cassette by PCR as described in Venken et al. (2011). Typically, 50% of the integration events are in the proper orientation.

Figure 2

Download asset Open asset

We observed one to ten RMCE events in 93 out of 113 attempts in our initial trial when we set up 3–7 crosses (Cross 2 in Figure 2). After PCR screening, 60/93 of the tested MiMICs allowed integration of at least one donor in the proper orientation to tag the endogenous gene (Supplementary file 1). In summary, we set up 3–7 vials for each starting cross and obtained 60/113 tagged genes. Since the efficiency of RMCE and the ease of detecting yellow⁻ progeny vary between different starting sites, we propose to set up 10–20 vials and to score more progeny to improve the success rate. The method has been found to work for a wide variety of genes including a gene located in a telomeric region (lethal giant larvae (l(2)gl)), suggesting that there may be few limitations in its applicability.

To ensure that the expression pattern and protein distribution correspond to the endogenous protein, we costained two tagged lines with GFP for which specific monoclonal antibodies are available: Eyes shut (Eys) (mAb 21A6,) and Delta (Dl) (mAb C594.9B) (Figure 3A). In both cases, the protein recognized by the mAb colocalizes with the GFP and match the described expression patterns (Das et al., 2013; Haltom et al., 2014). Note, however, that the GFP tagged Eys protein is present in the cytoplasm of the photoreceptors and the inter-rhabdomere spaces (IRS) of the photoreceptors, whereas the mAb against Eys mostly localizes to the IRS (Figure 3A). These data are in agreement with what we previously observed for numerous tagged proteins (Venken et al., 2011; Nagarkar-Jaiswal et al., 2015).

Figure 3

Download asset Open asset

We stained third instar larval brains and discs for the 60 tagged gene/proteins. The examples, shown in Figure 3B, include lethal (2) giant larvae (l(2)gl) (a), Delta (Dl) (b), and twins (tws) (c) whose expression patterns are consistent with published data (Kooh et al., 1993; Albertson and Doe, 2003; Chabu and Doe, 2009). Similarly, kayak/fos (kay) is expressed in wing disc nuclei (d) as described earlier (Zeitlinger and Bohmann, 1999). The expression pattern of the remaining genes has not been previously described (Figure 3B): Saposin-related (Sap-r) is expressed in a subset of cells in larval brain (e), Rad, Gem/Kir family member 3 (Rgk3) is enriched in mushroom body in L3 larval brain (f), Heterogeneous nuclear ribonucleoprotein at 98DE (Hrb98DE) is expressed in L3 larval brain (g), CG10086 is expressed in hindgut (h), and CG5656 is expressed in the cells of the cuticle (i). The expression patterns of all these genes as well as all the genes listed in Supplementary file 1 are documented in the MiMIC RMCE database at http://flypush.imgen.bcm.tmc.edu/pscreen/rmce/.

In summary, we developed a genetic tagging strategy that will greatly facilitate the EGFP tagging of nearly 2000 genes that already carry MiMIC insertions (Nagarkar-Jaiswal et al., 2015). The same strategies can also be used for tagging genes with other protein tags. In addition, a similar strategy based on lox sites instead of FRT cassettes has recently been developed to integrate an artificial exon carrying the GAL4 gene in MiMICs inserted in coding introns (Diao et al., 2015). These insertions are mutagenic but permit the expression of the endogenous wild-type and mutant cDNAs of Drosophila as well as other species under the control of UAS. Moreover, these tagging methods can now be combined with CRISPR directed integration of attP carrying cassettes similar to MiMIC in coding introns to tag almost every gene in Drosophila (Zhang et al., 2014).

1. 1. Albertson R
   2. Doe CQ

   (2003) Dlg, Scrib and Lgl regulate neuroblast cell size and mitotic spindle asymmetry

   Nature Cell Biology 5:166–170.

   https://doi.org/10.1038/ncb922

   • Google Scholar
2. 1. Aleksic J
   2. Lazic R
   3. Muller I
   4. Russell SR
   5. Adryan B

   (2009) Biases in Drosophila melanogaster protein trap screens

   BMC Genomics 10:249.

   https://doi.org/10.1186/1471-2164-10-249

   • Google Scholar
3. 1. Bellen HJ
   2. Levis RW
   3. He Y
   4. Carlson JW
   5. Evans-Holm M
   6. Bae E
   7. Kim J
   8. Metaxakis A
   9. Savakis C
   10. Schulze KL
   11. Hoskins RA
   12. Spradling AC

   (2011) The Drosophila gene disruption project: progress using transposons with distinctive site specificities

   Genetics 188:731–743.

   https://doi.org/10.1534/genetics.111.126995

   • Google Scholar
4. 1. Buszczak M
   2. Paterno S
   3. Lighthouse D
   4. Bachman J
   5. Planck J
   6. Owen S
   7. Skora AD
   8. Nystul TG
   9. Ohlstein B
   10. Allen A
   11. Wilhelm JE
   12. Murphy TD
   13. Levis RW
   14. Matunis E
   15. Srivali N
   16. Hoskins RA
   17. Spradling AC

   (2007) The carnegie protein trap library: a versatile tool for Drosophila developmental studies

   Genetics 175:1505–1531.

   https://doi.org/10.1534/genetics.106.065961

   • Google Scholar
5. 1. Chabu C
   2. Doe CQ

   (2009) Twins/PP2A regulates aPKC to control neuroblast cell polarity and self-renewal

   Developmental Biology 330:399–405.

   https://doi.org/10.1016/j.ydbio.2009.04.014

   • Google Scholar
6. 1. Das S
   2. Chen QB
   3. Saucier JD
   4. Drescher B
   5. Zong Y
   6. Morgan S
   7. Forstall J
   8. Meriwether A
   9. Toranzo R
   10. Leal SM

   (2013) The Drosophila T-box transcription factor midline functions within the Notch-Delta signaling pathway to specify sensory organ precursor cell fates and regulates cell survival within the eye imaginal disc

   Mechanisms of Development 130:577–601.

   https://doi.org/10.1016/j.mod.2013.08.001

   • Google Scholar
7. 1. Diao F
   2. Ironfield H
   3. Luan H
   4. Diao F
   5. Shropshire WC
   6. Ewer J
   7. Marr E
   8. Potter CJ
   9. Landgraf M
   10. White BH

   (2015) Plug-and-play genetic access to Drosophila cell types using exchangeable exon cassettes

   Cell Reports 10:1410–1421.

   https://doi.org/10.1016/j.celrep.2015.01.059

   • Google Scholar
8. 1. Fujita SC
   2. Zipursky SL
   3. Benzer S
   4. Ferrus A
   5. Shotwell SL

   (1982) Monoclonal antibodies against the Drosophila nervous system

   Proceedings of the National Academy of Sciences of USA 79:7929–7933.

   https://doi.org/10.1073/pnas.79.24.7929

   • Google Scholar
9. 1. Gohl DM
   2. Silies MA
   3. Gao XJ
   4. Bhalerao S
   5. Luongo FJ
   6. Lin CC
   7. Potter CJ
   8. Clandinin TR

   (2011) A versatile in vivo system for directed dissection of gene expression patterns

   Nature Methods 8:231–237.

   https://doi.org/10.1038/nmeth.1561

   • Google Scholar
10. 1. Golic MM
    2. Rong YS
    3. Petersen RB
    4. Lindquist SL
    5. Golic KG

    (1997) FLP-mediated DNA mobilization to specific target sites in Drosophila chromosomes

    Nucleic Acids Research 25:3665–3671.

    https://doi.org/10.1093/nar/25.18.3665

    • Google Scholar
11. 1. Gong WJ
    2. Golic KG

    (2003) Ends-out, or replacement, gene targeting in Drosophila

    Proceedings of the National Academy of Sciences of USA 100:2556–2561.

    https://doi.org/10.1073/pnas.0535280100

    • Google Scholar
12. 1. Haltom AR
    2. Lee TV
    3. Harvey BM
    4. Leonardi J
    5. Chen YJ
    6. Hong Y
    7. Haltiwanger RS
    8. Jafar-Nejad H

    (2014) The protein O-glucosyltransferase Rumi modifies eyes shut to promote rhabdomere separation in Drosophila

    PLOS Genetics 10:e1004795.

    https://doi.org/10.1371/journal.pgen.1004795

    • Google Scholar
13. 1. Kelso RJ
    2. Buszczak M
    3. Quinones AT
    4. Castiblanco C
    5. Mazzalupo S
    6. Cooley L

    (2004) Flytrap, a database documenting a GFP protein-trap insertion screen in Drosophila melanogaster

    Nucleic Acids Research 32:D418–D420.

    https://doi.org/10.1093/nar/gkh014

    • Google Scholar
14. 1. Kooh PJ
    2. Fehon RG
    3. Muskavitch MA

    (1993)

    Implications of dynamic patterns of Delta and Notch expression for cellular interactions during Drosophila development

    Development 117:493–507.

    • Google Scholar
15. 1. Lowe N
    2. Rees JS
    3. Roote J
    4. Ryder E
    5. Armean IM
    6. Johnson G
    7. Drummond E
    8. Spriggs H
    9. Drummond J
    10. Magbanua JP
    11. Naylor H
    12. Sanson B
    13. Bastock R
    14. Huelsmann S
    15. Trovisco V
    16. Landgraf M
    17. Knowles-Barley S
    18. Armstrong JD
    19. White-Cooper H
    20. Hansen C
    21. Phillips RG
    22. UK Drosophila Protein Trap Screening Consortium
    23. Lilley KS
    24. Russell S
    25. St Johnston D

    (2014) Analysis of the expression patterns, subcellular localisations and interaction partners of Drosophila proteins using a pigP protein trap library

    Development 141:3994–4005.

    https://doi.org/10.1242/dev.111054

    • Google Scholar
16. 1. Morin X
    2. Daneman R
    3. Zavortink M
    4. Chia W

    (2001) A protein trap strategy to detect GFP-tagged proteins expressed from their endogenous loci in Drosophila

    Proceedings of the National Academy of Sciences of USA 98:15050–15055.

    https://doi.org/10.1073/pnas.261408198

    • Google Scholar
17. 1. Nagarkar-Jaiswal S
    2. Lee PT
    3. Campbell ME
    4. Chen K
    5. Anguiano-Zarate S
    6. Gutierrez MC
    7. Busby T
    8. Lin WW
    9. He Y
    10. Schulze KL
    11. Booth BW
    12. Evans-Holm M
    13. Venken KJ
    14. Levis RW
    15. Spradling AC
    16. Hoskins RA
    17. Bellen HJ

    (2015) A library of MiMICs allows tagging of genes and reversible, spatial and temporal knockdown of proteins in Drosophila

    eLife 4:e05338.

    https://doi.org/10.7554/eLife.05338

    • Google Scholar
18. 1. Qi H
    2. Rand MD
    3. Wu X
    4. Sestan N
    5. Wang W
    6. Rakic P
    7. Xu T
    8. Artavanis-Tsakonas S

    (1999) Processing of the notch ligand delta by the metalloprotease Kuzbanian

    Science 283:91–94.

    https://doi.org/10.1126/science.283.5398.91

    • Google Scholar
19. 1. Quinones-Coello AT
    2. Petrella LN
    3. Ayers K
    4. Melillo A
    5. Mazzalupo S
    6. Hudson AM
    7. Wang S
    8. Castiblanco C
    9. Buszczak M
    10. Hoskins RA
    11. Cooley L

    (2007) Exploring strategies for protein trapping in Drosophila

    Genetics 175:1089–1104.

    https://doi.org/10.1534/genetics.106.065995

    • Google Scholar
20. 1. Ross-Macdonald P
    2. Coelho PS
    3. Roemer T
    4. Agarwal S
    5. Kumar A
    6. Jansen R
    7. Cheung KH
    8. Sheehan A
    9. Symoniatis D
    10. Umansky L
    11. Heidtman M
    12. Nelson FK
    13. Iwasaki H
    14. Hager K
    15. Gerstein M
    16. Miller P
    17. Roeder GS
    18. Snyder M

    (1999) Large-scale analysis of the yeast genome by transposon tagging and gene disruption

    Nature 402:413–418.

    https://doi.org/10.1038/46558

    • Google Scholar
21. 1. Skarnes WC
    2. von Melchner H
    3. Wurst W
    4. Hicks G
    5. Nord AS
    6. Cox T
    7. Young SG
    8. Ruiz P
    9. Soriano P
    10. Tessier-Lavigne M
    11. Conklin BR
    12. Stanford WL
    13. Rossant J
    14. International Gene Trap Consortium

    (2004) A public gene trap resource for mouse functional genomics

    Nature Genetics 36:543–544.

    https://doi.org/10.1038/ng0604-543

    • Google Scholar
22. 1. Venken KJ
    2. Schulze KL
    3. Haelterman NA
    4. Pan H
    5. He Y
    6. Evans-Holm M
    7. Carlson JW
    8. Levis RW
    9. Spradling AC
    10. Hoskins RA
    11. Bellen HJ

    (2011) MiMIC: a highly versatile transposon insertion resource for engineering Drosophila melanogaster genes

    Nature Methods 8:737–743.

    https://doi.org/10.1038/nmeth.1662

    • Google Scholar
23. 1. Zeitlinger J
    2. Bohmann D

    (1999)

    Thorax closure in Drosophila: involvement of Fos and the JNK pathway

    Development 126:3947–3956.

    • Google Scholar
24. 1. Zhang X
    2. Koolhaas WH
    3. Schnorrer F

    (2014) A versatile two-step CRISPR- and RMCE-based strategy for efficient genome engineering in Drosophila

    G3 4:2409–2418.

    https://doi.org/10.1534/g3.114.013979

    • Google Scholar

Author details

1. Sonal Nagarkar-Jaiswal

   Howard Hughes Medical Institute, Baylor College of Medicine, Houston, United States

   Contribution

   SN-J, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Steven Z DeLuca

   Competing interests

   The authors declare that no competing interests exist.

2. Steven Z DeLuca

   Department of Embryology, Howard Hughes Medical Institute, Carnegie Institution for Science, Baltimore, United States

   Contribution

   SZDL, Conception and design, Drafting or revising the article

   Contributed equally with

   Sonal Nagarkar-Jaiswal

   Competing interests

   The authors declare that no competing interests exist.

3. Pei-Tseng Lee

   Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States

   Contribution

   P-TL, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

4. Wen-Wen Lin

   Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States

   Contribution

   W-WL, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

5. Hongling Pan

   Howard Hughes Medical Institute, Baylor College of Medicine, Houston, United States

   Contribution

   HP, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

6. Zhongyuan Zuo

   Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States

   Contribution

   ZZ, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

7. Jiangxing Lv

   Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States

   Contribution

   JL, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

8. Allan C Spradling

   Department of Embryology, Howard Hughes Medical Institute, Carnegie Institution for Science, Baltimore, United States

   Contribution

   ACS, Conception and design, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

9. Hugo J Bellen

   1. Howard Hughes Medical Institute, Baylor College of Medicine, Houston, United States
   2. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
   3. Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
   4. Department of Neuroscience, Baylor College of Medicine, Houston, United States
   5. Program in Developmental Biology, Baylor College of Medicine, Houston, United States

   Contribution

   HJB, Conception and design, Drafting or revising the article

   For correspondence

   hbellen@bcm.edu

   Competing interests

   The authors declare that no competing interests exist.

• 7,270

  views

• 1,851

  downloads

• 131

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.