Dysregulation of signal transduction by the RAS family of guanosine 5’-triphosphate (GTP) hydrolases (GTPases) can have profound effects on human development and cause genetic disorders collectively termed RASopathies (Castel et al., 2020; Rauen, 2013). Ras GTPases exhibit high affinity toward guanine nucleotides and act as molecular switches by mediating GTP hydrolysis. The nucleotide cycling of RAS GTPases is tightly regulated by GTPase activating proteins (GAPs; e.g. neurofibromin) and guanine nucleotide exchange factors (GEFs; e.g. SOS1) that facilitate nucleotide hydrolysis or loading, respectively (Simanshu et al., 2017). Upon GTP binding, RAS proteins undergo a conformational change, which promotes the interaction with different protein effectors that activate downstream signaling pathways, including Raf/MEK/ERK mitogen activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) pathways. Although GAPs and GEFs can rapidly affect the nucleotide cycling of RAS proteins, and hence their activity, other accessory proteins can modulate downstream signaling by regulating the stability and/or activity of RAS GTPases.

Noonan syndrome (NS) is a common RASopathy that is characterized by craniofacial dysmorphism, short stature, congenital heart disease, and developmental delays. The cause of NS has been linked to genetic alterations that result in hyperactivation of the Raf/MEK/ERK MAPK pathway, including recently reported gain-of-function mutations in the RAS GTPase RIT1 and loss-of-function mutations in the BTB protein LZTR1 (Aoki et al., 2013; Yamamoto et al., 2015; Johnston et al., 2018). We have previously reported that RIT1 is mostly bound to GTP in cells, suggesting that it either lacks a GAP, uses a less active GAP, or relies on its intrinsic GTPase activity (Castel et al., 2019). An alternative regulatory mechanism of RIT1 activity is through protein degradation; we identified a Cullin-3 RING E3 ubiquitin ligase complex (CRL3) that uses LZTR1 as a substrate receptor (CRL3^LZTR1) to bind RIT1 and promote its ubiquitination and proteasomal degradation. CRL3^LZTR1 binds to GDP-bound RIT1 and maintains tight regulation of RIT1 protein levels. Importantly, NS-associated RIT1 and LZTR1 missense mutations disrupt CRL3^LZTR1-RIT1 binding, thus relieving RIT1 from its negative regulatory mechanism (Castel, 2022).

LZTR1 has been reported to regulate the protein stability of other RAS GTPases by similar mechanisms (Bigenzahn et al., 2018; Steklov et al., 2018; Abe et al., 2020). In this study, we employed a molecular evolutionary approach to elucidate the functional relationship and co-evolution of LZTR1 and its cognate RAS GTPase substrate(s), including the evaluation of LZTR1 loss-of-function mutations in invertebrate and mammalian model organisms.

The RAS family of GTPase proteins has been previously shown to be well-conserved across species and LZTR1 has been proposed to regulate a subset of these proteins (Rojas et al., 2012). Therefore, to understand how LZTR1 has evolved in comparison with other RAS GTPases, we performed protein alignment analysis of the human orthologs of KRAS, RIT1, and LZTR1 orthologs from human and common model organisms. Consistent with previous studies, KRAS was highly conserved in less complex organisms, including fission yeast (Ras1; 60% protein identity) (Figure 1a). In contrast, we found that RIT1 rapidly diverged in less complex organisms and a mildly conserved protein in Drosophila melanogaster (RIC; 60% protein identity) was the most distant ortholog that could be found in these laboratory model species. LZTR1 followed a similar pattern as RIT1; we could identify an ortholog in fruit flies (CG3711/LZTR1; 60% protein identity), but not in the roundworm Caenorhabditis elegans (Figure 1a). These analyses suggest that RIT1 and LZTR1 are more likely to have functionally co-evolved than KRAS and LZTR1. To further assess the biochemical relationship between these proteins across model organisms, we generated recombinant proteins for the KRAS, RIT1, and LZTR1 orthologs from mouse (Mus musculus), zebrafish (Danio rerio), and fruit fly (Drosophila melanogaster) and tested their ability to interact in pull down assays. All LZTR1 orthologs preferentially interacted with RIT1 orthologs (Figure 1b, Figure 1—figure supplement 1), indicating that this interaction that we previously reported for human proteins is also conserved in less complex model organisms.

Figure 1 with 1 supplement see all

Download asset Open asset

Figure 1—source data 1

Raw data for Figure 1.

https://cdn.elifesciences.org/articles/76495/elife-76495-fig1-data1-v2.zip

Download elife-76495-fig1-data1-v2.zip

To better understand the role of the LZTR1 ortholog in Drosophila melanogaster, we isolated Lztr1 loss-of-function mutations by using two independent CRISPR/Cas9 gene editing approaches. One resulting allele, Lztr1¹, causes a frameshift at the beginning of the second exon and encodes a short, truncated product. Another allele, Lztr1², lacks all coding sequences and is, therefore, a null mutation (Figure 2a). Lztr1 null flies were normal and fertile and did not display any obvious phenotype. A previous study showed that flies expressing RNA interference constructs against Lztr1 displayed minor defects in wing vein patterning (Bigenzahn et al., 2018); however, we did not find consistent vein defects in our null mutants (Figure 2b).

Figure 2

Download asset Open asset

Figure 2—source data 1

Raw data for Figure 2.

https://cdn.elifesciences.org/articles/76495/elife-76495-fig2-data1-v2.zip

Download elife-76495-fig2-data1-v2.zip

Next, we undertook label-free proteomics to quantify the levels of Ras family proteins in head extracts from Lztr1² and background matched control (yw) flies. Ric levels were upregulated ~11 times in Lztr1² fly heads relative to the control, while Ras85D (the HRAS, KRAS, and NRAS ortholog, hereafter referred to as Ras) levels were only modestly altered in both backgrounds (~1.5-fold difference) (Figure 2c). Similarly, Ras64D (the MRAS ortholog) was only upregulated ~1.6-fold in Lztr1² mutant heads. To validate these results, we generated Drosophila transgenic lines carrying N-terminally HA tagged Ric or Ras genes under the control of their natural genomic sequences, thereby facilitating detection of both products at their endogenous levels. Both transgenes were then placed in the Lztr1² mutant background to assess the effect of Lztr1 depletion on Ric and Ras protein stability. Consistent with our mass spectrometry results, HA-Ric levels were elevated in the absence of Lztr1, while HA-Ras levels remained barely altered in either mutant adult flies or third-instar larvae (Figure 2d–e). Altogether, these experiments show that Drosophila Lztr1 preferentially regulates Ric rather than Ras levels, as seen with the corresponding mammalian orthologs.

Given the absence of a phenotype in fruit flies, we examined the effect of Lztr1 deletion in mice. Steklov et al had previously reported that Lztr1 heterozygous knockout mice display typical features of NS, suggestive of haploinsufficiency (Steklov et al., 2018). In humans, NS-associated variants are most commonly found as bi-allelic loss-of-function variants that are inherited in an autosomal recessive manner; although there are few heterozygous variants that segregate as autosomal dominant, these are single nucleotide variants that likely act as dominant negatives (Johnston et al., 2018; Yamamoto et al., 2015; Motta et al., 2019). Hence, we further analyzed the potential NS-like phenotype of heterozygous Lztr1 deletion in the mouse as previously described in other mouse models (Araki et al., 2004; Wu et al., 2011; Hernández-Porras et al., 2014; Castel et al., 2019). Heterozygous mice did not exhibit significant changes in body weight and, overall, their morphology appeared normal (Figure 3a, Figure 3—figure supplement 1). The morphology of the skull, which generally shows dysmorphic features in mouse models of NS (round skull, blunt snout, and hypertelorism), was assessed using micro-computed tomography (µCT) and did not have significant differences when compared to wild-type littermates (Figure 3b). In addition, we assessed whether heterozygous mice displayed either cardiomegaly or splenomegaly, as these signs have been observed in other NS-like mouse models, but we failed to observe differences with wild-type animals (Figure 3c–d). No significant changes in RAS GTPases levels were seen either in tissue extracts from these mice (Figure 3—figure supplement 1). These results indicate that Lztr1 heterozygous mice do not exhibit the typical features seen in other NS mouse models and indicate that Lztr1 is haplosufficient for this phenotype. In support of these observations in mice, NS families carrying LZTR1 alleles generally exhibit an autosomal recessive inheritance pattern and bi-allelic inactivation of LZTR1 is required to exhibit a NS phenotype (Johnston et al., 2018). In addition, analysis of LZTR1 variants in the genome aggregation database (gnomAD) shows that many loss-of-function variants are observed in healthy individuals (pLI = 0; o/e = 2.28) (Karczewski et al., 2020). This indicates that these heterozygous loss-of-function variants are tolerated and are found in non-syndromic individuals. Thus, these data suggest haploinsufficiency of LZTR1 in humans is unlikely to lead to NS.

Figure 3 with 1 supplement see all

Download asset Open asset

Figure 3—source data 1

Raw data for Figure 3.

https://cdn.elifesciences.org/articles/76495/elife-76495-fig3-data1-v2.zip

Download elife-76495-fig3-data1-v2.zip

We and others have previously shown that Lztr1 knockout mice are embryonically lethal (Steklov et al., 2018; Castel et al., 2019); however, the reason for such lethality remains largely unknown. A previous study showed that Lztr1-associated embryonic lethality can be rescued by administering a MEK1/2 inhibitor to pregnant females, indicating that the phenotype is largely dependent on MAPK hyperactivation (Steklov et al., 2018). In fact, in other murine NS models, excessive activation of MAPK during embryonic development results in lethality, as seen in the Kras^V14I model (Hernández-Porras et al., 2014). Interestingly, this phenotype appears to be more prominent in certain mouse background strains, such as C57BL/6 N, and more permissive in 129Sv (Araki et al., 2004; Hernández-Porras et al., 2015). Since our Lztr1 mutant mice are in the C57BL/6 N strain, we hypothesized that mouse background affects embryonic lethality. Backcrossing our mice to 129Sv females yielded heterozygous Lztr1 mutant mice in a 50% mixed background. After one backcross (referred to as F1), using a heterozygous x heterozygous breeding scheme, we obtained 1/55 (~1.8%) homozygous viable mice. At F2, we obtained 3/45 (~6.7%) homozygous viable mice. At F3, we obtained 3/34 (~8.8%) homozygous viable mice (Figure 3e). In contrast, mice in the 129Sv pure background did not yield any homozygous viable mice, suggesting that a combination of strain-specific genetic modifiers is likely required to tolerate Lztr1 deletion. In Raf1 D486N NS mice, a potential gene modifier was mapped at chromosome 8 of the 129Sv strain (Wu et al., 2012); however, we hypothesize that in the context of Lztr1, a negative gene modifier is also likely to be located in the Y chromosome of the 129Sv strain, given that we do not yield any homozygous viable mice after Y-chromosome fixing.

The limited number of viable homozygous Lztr1 knockout mice prevented us from undertaking quantitative phenotyping; however, when compared to wild type littermates, Lztr1 knockout mice appeared smaller, displayed characteristic dysmorphic facial features (round snout, hypertelorism, low set of ears, and proptosis), and exhibited cardiomegaly, consistent with other mouse models of NS (Figure 3f). In addition, Lztr1 knockout mice exhibited increased levels of Rit1 in all the tissues that we analyzed, while RAS levels remained mostly unchanged (Figure 3g).

Next, we sought to investigate the cause of embryonic lethality in Lztr1 knockout mice. We and others had previously shown that many embryos survive to late developmental stages (i.e. embryonic day (E)17.5–19.5), therefore, we harvested embryos on day E18.5. Most embryos display extensive hemorrhages (Figure 4a) and, consistent with this observation, conditional deletion of Lztr1 in blood vessels has been previously shown to cause vascular leakage (Sewduth et al., 2020). Since many NS alleles that cause lethality in mice have been related to cardiovascular dysfunction, we analyzed the heart phenotype of E18.5 embryos. Valve leaflets and endocardial cushions were normal, in contrast to the previous Ptpn11 NS-associated alleles (Araki et al., 2004). In Lztr1 knockout embryos, the ventricular myocardial wall showed defects that are compatible with ventricular noncompaction cardiomyopathy, similar to that seen in the Ptpn11 Q79R transgenic mouse model (Nakamura et al., 2007). Detailed analysis of compact and trabecular myocardial thickness showed significant differences in mutant embryos (Figure 4b). In addition, we observed interventricular septal defects in ~20% mutant hearts. Although the heart phenotype is striking, it is likely that embryonic lethality results from a combination of vascular and cardiac defects during development.

Figure 4 with 1 supplement see all

Download asset Open asset

Figure 4—source data 1

Raw data for Figure 4 and Figure 4—figure supplement 1.

https://cdn.elifesciences.org/articles/76495/elife-76495-fig4-data1-v2.zip

Download elife-76495-fig4-data1-v2.zip

Lztr1 embryonic lethality provides a unique model to undertake a genetic epistatic rescue experiment to assess which RAS GTPase is the critical downstream substrate of the CRL3^LZTR1 complex. We have previously shown that at the biochemical level CRL3^LZTR1 complex preferentially binds and promotes degradation of RIT1. Therefore, we generated Rit1 knockout mice to test whether Rit1 depletion can rescue Lztr1-mediated embryonic lethality. To avoid potential heterosis, we generated Rit1 knockouts in the C57BL6/N background; mice were born at expected Mendelian ratios, were fertile, and did not exhibit any visible phenotype, similar to a previous Rit1 null mouse strain (Cai et al., 2011). We confirmed the elimination of Rit1 by immunoblot in different tissues, including brain, lung, and heart (Figure 4c). Next, we crossed Rit1 knockout mice with Lztr1 heterozygous mice to obtain both Lztr1^-/+/Rit1^+/+ and Lztr1^-/+/Rit1^-/- progeny. As previously shown, a heterozygous breeding scheme with Lztr1^-/+/Rit1^+/+ mice did not yield any viable Lztr1 knockout mice (Figures 3e and 4d; Sewduth et al., 2020). In contrast, when Lztr1^-/+/Rit1^-/- breeders were used, we obtained 13/85 (~15.3%) mice that were double knockout (DKO) for both Lztr1 and Rit1 (Figure 4d). This result shows that Rit1 deletion can rescue the embryonic lethality caused by Lztr1 deletion in mice, indicating that Rit1 is the critical substrate of the CRL3^LZTR1 complex during embryonic development. The resulting DKO mice appeared normal, were fertile, and were absent of any detectable phenotype that resembled other NS mouse models, as assessed by size, heart weight, and cranial morphology (Figure 4—figure supplement 1). In addition, Lztr1/Rit1 DKO embryos harvested at E18.5 showed a complete rescue of the cardiac phenotype, which were indistinguishable from Rit1 KO embryos (Figure 4e, Figure 4—figure supplement 1e). To assess whether the Rit1 dependency established by Lztr1/Rit1 DKO mice is correlated to a rescue of MAPK pathway hyperactivation, we isolated primary mouse embryonic fibroblasts (MEF) from wild type, Lztr1 KO, Rit1 KO, and Lztr1/Rit1 DKO embryos (Figure 4f). We then subjected these MEFs to FBS stimulation and observed a noticeable decrease in MAPK signaling in cells devoid of both LZTR1 and RIT1 compared to LZTR1 KO cells, both by immunoblot and using the two well-characterized MAPK-regulated transcriptional targets Spry2 and Dusp6 (Figure 4g–h). This indicated that, in our MEF cells, MAPK pathway hyperactivation is mediated by RIT1 protein stabilization in the absence of CRL3^LZTR1 regulation.

Many human RAS proteins are highly conserved in less complex organisms and a common ancestor Ras protein has been described in distant relatives such as yeast and slime mold, among other Eukarya (Cox and Der, 2010). Phylogenetic analyses of certain regulators of RAS function, such as GAPs and GEFs, highlight the prominence of early RAS activity regulation and its robust coevolution; with ancestral genomes harboring multiple GAP and GEF genes for a single RAS GTPase and a notable expansion of GAP genes congruent with the expansion of RAS GTPases in eukaryotes (van Dam et al., 2011; van Dam et al., 2009). The high percentage of GTP-loaded RIT1 in mammalian cells indicates the potential absence or evolutionary loss of GAP-mediated regulation and highlights the importance of alternative RIT1 regulatory mechanisms, such as protein turnover. Here, we show that in contrast to the highly conserved protein KRAS, both RIT1 and LZTR1 proteins are less conserved in lower organisms. Despite this, LZTR1 orthologs of invertebrate model organisms retain preferential binding toward their respective RIT1, but not RAS, orthologs. Moreover, fruit flies exhibit strong conservation of the LZTR1-mediated protein degradation mechanism with specificity toward RIT1, as we had previously described with human orthologs, but minimal activity toward other fruit fly RAS GTPases. These data indicate a functional co-evolution between LZTR1 and RIT1.

We also demonstrate that, in contrast to previous reports, LZTR1 is haplosufficient in mice (Steklov et al., 2018). However, homozygous knockout mutations are not tolerated due to embryonic lethality caused by aberrant cardiovascular development concomitant with severe peripheral hemorrhaging and ventricular septal defects, which can be rescued by Rit1 germline deletion. Interestingly, Sewduth et al., demonstrate that pharmacological inhibition of the RAF/MEK/ERK MAPK or AKT pathway was unable to fully rescue the embryonic lethality and vascular defects of mice with conditional Lztr1 KO in blood vessels (Sewduth et al., 2020). Given that our Lztr1/Rit1 DKO mice did not exhibit cardiovascular abnormalities during embryogenesis, excessive accumulation of Rit1 protein in Lztr1 KO cells likely results in the hyperactivation or dysregulation of additional Rit1 effector pathways that contribute to Lztr1^-/- embryonic lethality (Cuevas-Navarro et al., 2021; Meyer Zum Büschenfelde et al., 2018; Vichas et al., 2021).

While other RAS GTPases have cognate GAPs and GEFs that regulate their activity, RIT1 GAPs and GEFs remain to be identified. Supported by the robust functional and evolutionary relationship between LZTR1 and RIT1 described here, we posit that LZTR1 may have co-evolved with RIT1 as an alternative mechanism to regulate RIT1 GTPase activity.

All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for all Figures.

1. 1. Abe T
   2. Umeki I
   3. Kanno SI
   4. Inoue SI
   5. Niihori T
   6. Aoki Y

   (2020) LZTR1 facilitates polyubiquitination and degradation of RAS-GTPases

   Cell Death and Differentiation 27:1023–1035.

   https://doi.org/10.1038/s41418-019-0395-5

   • PubMed
   • Google Scholar
2. 1. Aoki Y
   2. Niihori T
   3. Banjo T
   4. Okamoto N
   5. Mizuno S
   6. Kurosawa K
   7. Ogata T
   8. Takada F
   9. Yano M
   10. Ando T
   11. Hoshika T
   12. Barnett C
   13. Ohashi H
   14. Kawame H
   15. Hasegawa T
   16. Okutani T
   17. Nagashima T
   18. Hasegawa S
   19. Funayama R
   20. Nagashima T
   21. Nakayama K
   22. Inoue S-I
   23. Watanabe Y
   24. Ogura T
   25. Matsubara Y

   (2013) Gain-of-function mutations in RIT1 cause Noonan syndrome, a RAS/MAPK pathway syndrome

   American Journal of Human Genetics 93:173–180.

   https://doi.org/10.1016/j.ajhg.2013.05.021

   • PubMed
   • Google Scholar
3. 1. Araki T
   2. Mohi MG
   3. Ismat FA
   4. Bronson RT
   5. Williams IR
   6. Kutok JL
   7. Yang W
   8. Pao LI
   9. Gilliland DG
   10. Epstein JA
   11. Neel BG

   (2004) Mouse model of Noonan syndrome reveals cell type- and gene dosage-dependent effects of Ptpn11 mutation

   Nature Medicine 10:849–857.

   https://doi.org/10.1038/nm1084

   • PubMed
   • Google Scholar
4. 1. Bigenzahn JW
   2. Collu GM
   3. Kartnig F
   4. Pieraks M
   5. Vladimer GI
   6. Heinz LX
   7. Sedlyarov V
   8. Schischlik F
   9. Fauster A
   10. Rebsamen M
   11. Parapatics K
   12. Blomen VA
   13. Müller AC
   14. Winter GE
   15. Kralovics R
   16. Brummelkamp TR
   17. Mlodzik M
   18. Superti-Furga G

   (2018) LZTR1 is a regulator of RAS ubiquitination and signaling

   Science (New York, N.Y.) 362:1171–1177.

   https://doi.org/10.1126/science.aap8210

   • PubMed
   • Google Scholar
5. 1. Bischof J
   2. Maeda RK
   3. Hediger M
   4. Karch F
   5. Basler K

   (2007) An optimized transgenesis system for Drosophila using germ-line-specific phiC31 integrases

   PNAS 104:3312–3317.

   https://doi.org/10.1073/pnas.0611511104

   • PubMed
   • Google Scholar
6. 1. Bischof J
   2. Björklund M
   3. Furger E
   4. Schertel C
   5. Taipale J
   6. Basler K

   (2013) A versatile platform for creating A comprehensive UAS-ORFeome library in Drosophila

   Development (Cambridge, England) 140:2434–2442.

   https://doi.org/10.1242/dev.088757

   • PubMed
   • Google Scholar
7. 1. Cai W
   2. Rudolph JL
   3. Harrison SMW
   4. Jin L
   5. Frantz AL
   6. Harrison DA
   7. Andres DA

   (2011) An evolutionarily conserved Rit GTPase-p38 MAPK signaling pathway mediates oxidative stress resistance

   Molecular Biology of the Cell 22:3231–3241.

   https://doi.org/10.1091/mbc.E11-05-0400

   • PubMed
   • Google Scholar
8. 1. Castel P
   2. Cheng A
   3. Cuevas-Navarro A
   4. Everman DB
   5. Papageorge AG
   6. Simanshu DK
   7. Tankka A
   8. Galeas J
   9. Urisman A
   10. McCormick F

   (2019) RIT1 oncoproteins escape LZTR1-mediated proteolysis

   Science (New York, N.Y.) 363:1226–1230.

   https://doi.org/10.1126/science.aav1444

   • PubMed
   • Google Scholar
9. 1. Castel P
   2. Rauen KA
   3. McCormick F

   (2020) The duality of human oncoproteins: drivers of cancer and congenital disorders

   Nature Reviews. Cancer 20:383–397.

   https://doi.org/10.1038/s41568-020-0256-z

   • PubMed
   • Google Scholar
10. 1. Castel P

    (2022) Defective protein degradation in genetic disorders

    Biochimica et Biophysica Acta. Molecular Basis of Disease 1868:166366.

    https://doi.org/10.1016/j.bbadis.2022.166366

    • PubMed
    • Google Scholar
11. 1. Chalkley RJ
    2. Baker PR
    3. Medzihradszky KF
    4. Lynn AJ
    5. Burlingame AL

    (2008) In-depth analysis of tandem mass spectrometry data from disparate instrument types

    Molecular & Cellular Proteomics 7:2386–2398.

    https://doi.org/10.1074/mcp.M800021-MCP200

    • PubMed
    • Google Scholar
12. 1. Choi M
    2. Chang CY
    3. Clough T
    4. Broudy D
    5. Killeen T
    6. MacLean B
    7. Vitek O

    (2014) MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments

    Bioinformatics (Oxford, England) 30:2524–2526.

    https://doi.org/10.1093/bioinformatics/btu305

    • PubMed
    • Google Scholar
13. 1. Cox AD
    2. Der CJ

    (2010) Ras history: The saga continues

    Small GTPases 1:2–27.

    https://doi.org/10.4161/sgtp.1.1.12178

    • PubMed
    • Google Scholar
14. 1. Cuevas-Navarro A
    2. Van R
    3. Cheng A
    4. Urisman A
    5. Castel P
    6. McCormick F

    (2021) The RAS GTPase RIT1 compromises mitotic fidelity through spindle assembly checkpoint suppression

    Current Biology 31:3915–3924.

    https://doi.org/10.1016/j.cub.2021.06.030

    • PubMed
    • Google Scholar
15. 1. Hernández-Porras I
    2. Fabbiano S
    3. Schuhmacher AJ
    4. Aicher A
    5. Cañamero M
    6. Cámara JA
    7. Cussó L
    8. Desco M
    9. Heeschen C
    10. Mulero F
    11. Bustelo XR
    12. Guerra C
    13. Barbacid M

    (2014) K-RasV14I recapitulates Noonan syndrome in mice

    PNAS 111:16395–16400.

    https://doi.org/10.1073/pnas.1418126111

    • PubMed
    • Google Scholar
16. 1. Hernández-Porras I
    2. Jiménez-Catalán B
    3. Schuhmacher AJ
    4. Guerra C

    (2015) The impact of the genetic background in the Noonan syndrome phenotype induced by K-Ras(V14I

    Rare Diseases (Austin, Tex.) 3:e1045169.

    https://doi.org/10.1080/21675511.2015.1045169

    • PubMed
    • Google Scholar
17. 1. Johnston JJ
    2. van der Smagt JJ
    3. Rosenfeld JA
    4. Pagnamenta AT
    5. Alswaid A
    6. Baker EH
    7. Blair E
    8. Borck G
    9. Brinkmann J
    10. Craigen W
    11. Dung VC
    12. Emrick L
    13. Everman DB
    14. van Gassen KL
    15. Gulsuner S
    16. Harr MH
    17. Jain M
    18. Kuechler A
    19. Leppig KA
    20. McDonald-McGinn DM
    21. Can NTB
    22. Peleg A
    23. Roeder ER
    24. Rogers RC
    25. Sagi-Dain L
    26. Sapp JC
    27. Schäffer AA
    28. Schanze D
    29. Stewart H
    30. Taylor JC
    31. Verbeek NE
    32. Walkiewicz MA
    33. Zackai EH
    34. Zweier C
    35. Members of the Undiagnosed Diseases Network
    36. Zenker M
    37. Lee B
    38. Biesecker LG

    (2018) Autosomal recessive Noonan syndrome associated with biallelic LZTR1 variants

    Genetics in Medicine 20:1175–1185.

    https://doi.org/10.1038/gim.2017.249

    • PubMed
    • Google Scholar
18. 1. Karczewski KJ
    2. Francioli LC
    3. Tiao G
    4. Cummings BB
    5. Alföldi J
    6. Wang Q
    7. Collins RL
    8. Laricchia KM
    9. Ganna A
    10. Birnbaum DP
    11. Gauthier LD
    12. Brand H
    13. Solomonson M
    14. Watts NA
    15. Rhodes D
    16. Singer-Berk M
    17. England EM
    18. Seaby EG
    19. Kosmicki JA
    20. Walters RK
    21. Tashman K
    22. Farjoun Y
    23. Banks E
    24. Poterba T
    25. Wang A
    26. Seed C
    27. Whiffin N
    28. Chong JX
    29. Samocha KE
    30. Pierce-Hoffman E
    31. Zappala Z
    32. O’Donnell-Luria AH
    33. Minikel EV
    34. Weisburd B
    35. Lek M
    36. Ware JS
    37. Vittal C
    38. Armean IM
    39. Bergelson L
    40. Cibulskis K
    41. Connolly KM
    42. Covarrubias M
    43. Donnelly S
    44. Ferriera S
    45. Gabriel S
    46. Gentry J
    47. Gupta N
    48. Jeandet T
    49. Kaplan D
    50. Llanwarne C
    51. Munshi R
    52. Novod S
    53. Petrillo N
    54. Roazen D
    55. Ruano-Rubio V
    56. Saltzman A
    57. Schleicher M
    58. Soto J
    59. Tibbetts K
    60. Tolonen C
    61. Wade G
    62. Talkowski ME
    63. Neale BM
    64. Daly MJ
    65. MacArthur DG
    66. Genome Aggregation Database Consortium

    (2020) The mutational constraint spectrum quantified from variation in 141,456 humans

    Nature 581:434–443.

    https://doi.org/10.1038/s41586-020-2308-7

    • PubMed
    • Google Scholar
19. 1. Kondo S
    2. Ueda R

    (2013) Highly improved gene targeting by germline-specific Cas9 expression in Drosophila

    Genetics 195:715–721.

    https://doi.org/10.1534/genetics.113.156737

    • PubMed
    • Google Scholar
20. 1. Meyer Zum Büschenfelde U
    2. Brandenstein LI
    3. von Elsner L
    4. Flato K
    5. Holling T
    6. Zenker M
    7. Rosenberger G
    8. Kutsche K

    (2018) RIT1 controls actin dynamics via complex formation with RAC1/CDC42 and PAK1

    PLOS Genetics 14:e1007370.

    https://doi.org/10.1371/journal.pgen.1007370

    • PubMed
    • Google Scholar
21. 1. Motta M
    2. Fidan M
    3. Bellacchio E
    4. Pantaleoni F
    5. Schneider-Heieck K
    6. Coppola S
    7. Borck G
    8. Salviati L
    9. Zenker M
    10. Cirstea IC
    11. Tartaglia M

    (2019) Dominant Noonan syndrome-causing LZTR1 mutations specifically affect the Kelch domain substrate-recognition surface and enhance RAS-MAPK signaling

    Human Molecular Genetics 28:1007–1022.

    https://doi.org/10.1093/hmg/ddy412

    • PubMed
    • Google Scholar
22. 1. Nakamura T
    2. Colbert M
    3. Krenz M
    4. Molkentin JD
    5. Hahn HS
    6. Dorn GW
    7. Robbins J

    (2007) Mediating ERK 1/2 signaling rescues congenital heart defects in a mouse model of Noonan syndrome

    The Journal of Clinical Investigation 117:2123–2132.

    https://doi.org/10.1172/JCI30756

    • PubMed
    • Google Scholar
23. 1. Rauen KA

    (2013) The RASopathies

    Annual Review of Genomics and Human Genetics 14:355–369.

    https://doi.org/10.1146/annurev-genom-091212-153523

    • PubMed
    • Google Scholar
24. 1. Reiter L
    2. Rinner O
    3. Picotti P
    4. Hüttenhain R
    5. Beck M
    6. Brusniak MY
    7. Hengartner MO
    8. Aebersold R

    (2011) mProphet: automated data processing and statistical validation for large-scale SRM experiments

    Nature Methods 8:430–435.

    https://doi.org/10.1038/nmeth.1584

    • PubMed
    • Google Scholar
25. 1. Ren X
    2. Sun J
    3. Housden BE
    4. Hu Y
    5. Roesel C
    6. Lin S
    7. Liu LP
    8. Yang Z
    9. Mao D
    10. Sun L
    11. Wu Q
    12. Ji JY
    13. Xi J
    14. Mohr SE
    15. Xu J
    16. Perrimon N
    17. Ni JQ

    (2013) Optimized gene editing technology for Drosophila melanogaster using germ line-specific Cas9

    PNAS 110:19012–19017.

    https://doi.org/10.1073/pnas.1318481110

    • PubMed
    • Google Scholar
26. 1. Rojas AM
    2. Fuentes G
    3. Rausell A
    4. Valencia A

    (2012) The Ras protein superfamily: evolutionary tree and role of conserved amino acids

    The Journal of Cell Biology 196:189–201.

    https://doi.org/10.1083/jcb.201103008

    • PubMed
    • Google Scholar
27. 1. Schilling B
    2. Rardin MJ
    3. MacLean BX
    4. Zawadzka AM
    5. Frewen BE
    6. Cusack MP
    7. Sorensen DJ
    8. Bereman MS
    9. Jing E
    10. Wu CC
    11. Verdin E
    12. Kahn CR
    13. Maccoss MJ
    14. Gibson BW

    (2012) Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation

    Molecular & Cellular Proteomics 11:202–214.

    https://doi.org/10.1074/mcp.M112.017707

    • PubMed
    • Google Scholar
28. 1. Sewduth RN
    2. Pandolfi S
    3. Steklov M
    4. Sheryazdanova A
    5. Zhao P
    6. Criem N
    7. Baietti MF
    8. Lechat B
    9. Quarck R
    10. Impens F
    11. Sablina AA

    (2020) The Noonan Syndrome Gene Lztr1 Controls Cardiovascular Function by Regulating Vesicular Trafficking

    Circulation Research 126:1379–1393.

    https://doi.org/10.1161/CIRCRESAHA.119.315730

    • PubMed
    • Google Scholar
29. 1. Simanshu DK
    2. Nissley DV
    3. McCormick F

    (2017) RAS Proteins and Their Regulators in Human Disease

    Cell 170:17–33.

    https://doi.org/10.1016/j.cell.2017.06.009

    • PubMed
    • Google Scholar
30. 1. Steklov M
    2. Pandolfi S
    3. Baietti MF
    4. Batiuk A
    5. Carai P
    6. Najm P
    7. Zhang M
    8. Jang H
    9. Renzi F
    10. Cai Y
    11. Abbasi Asbagh L
    12. Pastor T
    13. De Troyer M
    14. Simicek M
    15. Radaelli E
    16. Brems H
    17. Legius E
    18. Tavernier J
    19. Gevaert K
    20. Impens F
    21. Messiaen L
    22. Nussinov R
    23. Heymans S
    24. Eyckerman S
    25. Sablina AA

    (2018) Mutations in LZTR1 drive human disease by dysregulating RAS ubiquitination

    Science (New York, N.Y.) 362:1177–1182.

    https://doi.org/10.1126/science.aap7607

    • PubMed
    • Google Scholar
31. 1. van Dam TJP
    2. Rehmann H
    3. Bos JL
    4. Snel B

    (2009) Phylogeny of the CDC25 homology domain reveals rapid differentiation of Ras pathways between early animals and fungi

    Cellular Signalling 21:1579–1585.

    https://doi.org/10.1016/j.cellsig.2009.06.004

    • PubMed
    • Google Scholar
32. 1. van Dam TJP
    2. Bos JL
    3. Snel B

    (2011) Evolution of the Ras-like small GTPases and their regulators

    Small GTPases 2:4–16.

    https://doi.org/10.4161/sgtp.2.1.15113

    • PubMed
    • Google Scholar
33. 1. Vichas A
    2. Riley AK
    3. Nkinsi NT
    4. Kamlapurkar S
    5. Parrish PCR
    6. Lo A
    7. Duke F
    8. Chen J
    9. Fung I
    10. Watson J
    11. Rees M
    12. Gabel AM
    13. Thomas JD
    14. Bradley RK
    15. Lee JK
    16. Hatch EM
    17. Baine MK
    18. Rekhtman N
    19. Ladanyi M
    20. Piccioni F
    21. Berger AH

    (2021) Integrative oncogene-dependency mapping identifies RIT1 vulnerabilities and synergies in lung cancer

    Nature Communications 12:4789.

    https://doi.org/10.1038/s41467-021-24841-y

    • PubMed
    • Google Scholar
34. 1. Wu X
    2. Simpson J
    3. Hong JH
    4. Kim KH
    5. Thavarajah NK
    6. Backx PH
    7. Neel BG
    8. Araki T

    (2011) MEK-ERK pathway modulation ameliorates disease phenotypes in a mouse model of Noonan syndrome associated with the Raf1(L613V) mutation

    The Journal of Clinical Investigation 121:1009–1025.

    https://doi.org/10.1172/JCI44929

    • PubMed
    • Google Scholar
35. 1. Wu X
    2. Yin J
    3. Simpson J
    4. Kim KH
    5. Gu S
    6. Hong JH
    7. Bayliss P
    8. Backx PH
    9. Neel BG
    10. Araki T

    (2012) Increased BRAF heterodimerization is the common pathogenic mechanism for noonan syndrome-associated RAF1 mutants

    Molecular and Cellular Biology 32:3872–3890.

    https://doi.org/10.1128/MCB.00751-12

    • PubMed
    • Google Scholar
36. 1. Yamamoto GL
    2. Aguena M
    3. Gos M
    4. Hung C
    5. Pilch J
    6. Fahiminiya S
    7. Abramowicz A
    8. Cristian I
    9. Buscarilli M
    10. Naslavsky MS
    11. Malaquias AC
    12. Zatz M
    13. Bodamer O
    14. Majewski J
    15. Jorge AAL
    16. Pereira AC
    17. Kim CA
    18. Passos-Bueno MR
    19. Bertola DR

    (2015) Rare variants in SOS2 and LZTR1 are associated with Noonan syndrome

    Journal of Medical Genetics 52:413–421.

    https://doi.org/10.1136/jmedgenet-2015-103018

    • PubMed
    • Google Scholar

Author details

1. Antonio Cuevas-Navarro

   Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, United States

   Contribution

   Data curation, Investigation, Methodology, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

2. Laura Rodriguez-Muñoz

   Institute for Molecular Biology of Barcelona, Consejo Superior de Investigaciones Científicas, Barcelona, Spain

   Contribution

   Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Joaquim Grego-Bessa

   Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain

   Contribution

   Investigation, Methodology, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0938-2346

4. Alice Cheng

   Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, United States

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

5. Katherine A Rauen

   1. UC Davis MIND Institute, University of California Davis, Sacramento, United States
   2. Department of Pediatrics, University of California Davis, Sacramento, United States

   Contribution

   Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

6. Anatoly Urisman

   Department of Anatomic Pathology, University of California San Francisco, San Francisco, United States

   Contribution

   Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8364-5303

7. Frank McCormick

   Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, United States

   Contribution

   Funding acquisition, Supervision, Writing – review and editing

   Competing interests

   is a consultant for Ideaya Biosciences, Kura Oncology, Leidos Biomedical Research, Pfizer, Daiichi Sankyo, Amgen, PMV Pharma, OPNA-IO, and Quanta Therapeutics and has received research grants from Boehringer-Ingelheim and is a consultant for and cofounder of BridgeBio Pharma

8. Gerardo Jimenez

   1. Institute for Molecular Biology of Barcelona, Consejo Superior de Investigaciones Científicas, Barcelona, Spain
   2. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

   Contribution

   Funding acquisition, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

9. Pau Castel

   Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, United States

   Contribution

   Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review and editing

   For correspondence

   pau.castel@nyulangone.org

   Competing interests

   PC is a founder and advisory board of Venthera

   "This ORCID iD identifies the author of this article:" 0000-0002-4972-4347

• 1,595

  views

• 251

  downloads

• 9

  citations

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