article: The small GTPase RAS is among the most prevalent oncogenes. The evolutionarily conserved RAF-MEK-MAPK module that lies downstream of RAS is one of the main conduits through which RAS transmits proliferative signals in normal and cancer cells. Genetic and biochemical studies conducted over the last two decades uncovered a small set of factors regulating RAS/MAPK signaling. Interestingly, most of these were found to control RAF activation, thus suggesting a central regulatory role for this event. Whether additional factors are required at this level or further downstream remains an open question. To obtain a comprehensive view of the elements functionally linked to the RAS/MAPK cascade, we used a quantitative assay in Drosophila S2 cells to conduct a genome-wide RNAi screen for factors impacting RAS-mediated MAPK activation. The screen led to the identification of 101 validated hits, including most of the previously known factors associated to this pathway. Epistasis experiments were then carried out on individual candidates to determine their position relative to core pathway components. While this revealed several new factors acting at different steps along the pathway—including a new protein complex modulating RAF activation—we found that most hits unexpectedly work downstream of MEK and specifically influence MAPK expression. These hits mainly consist of constitutive splicing factors and thereby suggest that splicing plays a specific role in establishing MAPK levels. We further characterized two representative members of this group and surprisingly found that they act by regulating mapk alternative splicing. This study provides an unprecedented assessment of the factors modulating RAS/MAPK signaling in Drosophila. In addition, it suggests that pathway output does not solely rely on classical signaling events, such as those controlling RAF activation, but also on the regulation of MAPK levels. Finally, it indicates that core splicing components can also specifically impact alternative splicing.
  The RAS/MAPK pathway consists of a core module of three kinases (RAF, MEK, and ERK/MAPK) that transmit signals downstream of the small GTPase RAS. Upstream factors such as receptor tyrosine kinases (RTKs), which respond to extracellular signals, lead to RAS activation by a guanine nucleotide exchange factor (GEF). GTP-loaded RAS then triggers the sequential activation of RAF, MEK, and MAPK; active RAF phosphorylates and activates MEK, which in turn phosphorylates and activates MAPK [1]. Unlike RAF and MEK, MAPK has a variety of cytoplasmic and nuclear substrates that include transcription factors such as c-Jun, c-Fos, p53, ELK1, c-Myc, c-Myb, STAT1/3, SRF, and SMAD1/2/3/4 [2]–[4]. Phosphorylation of these targets, and others, by MAPK induces a wide range of cellular responses that include proliferation, differentiation, and survival [5]. Also, RAS/MAPK signaling' s important role in oncogenesis and various developmental disorders has been recognized early on and abundantly studied [6], [7]. Over the last two decades, genetic screens in metazoan models such as Drosophila and Caenorhabditis elegans have been instrumental in identifying a growing list of key regulators of the RAS/MAPK pathway such as sos [8], csw [9], ksr [10]–[12], Cbl [13], dos [14], mts/PP2A [15], sur-8/soc-2 [16], [17], cnk [18], spry [19], sur-6 [20], PTP-ER [21], let-7 [22], alph/PP2C [23], and hyp/ave [24], [25]. Thus, these studies and research conducted in other systems have revealed a large network of factors whose regulatory activity converges on the core MAPK module [1], [5], [6], [26], [27]. This regulatory network includes complex features such as feedback loops [28]–[30], compartmentalization [1], [31], crosstalk with other signaling pathways [32], allosteric modulation via dimerization [27], [33], and the formation of larger order complexes called nanoclusters [34]. While the function of the core module is well characterized, many aspects of the network that surround it are still poorly understood, including its protein composition. Also, many of the identified regulators influence RAS-mediated RAF activation, which is in agreement with the fact that this particular step is subjected to a tight and complex regulation [27]. In comparison, fewer positively acting components have been found to act downstream of RAF, suggesting that MEK and MAPK activation depends on more simple regulatory mechanisms. Alternatively, such modulators might have eluded detection. Finally, most of the regulatory input that has been described so far acts at the post-translational level. Comparatively little is known on how RAS/MAPK component expression is controlled. The success of the aforementioned genetic screens typically relied on the qualitative modification of a visible phenotype. This consideration, together with the technical limitations associated with genetic screening procedures, usually limit results to a handful of confirmed hits. RNA interference (RNAi) used as a functional genomics tool provides the possibility of a more comprehensive type of analysis providing a systematic means to functionally annotate the genome [35], [36]. Moreover, the possibility of using quantitative assays, in particular, allows for the identification of a much wider range of regulators [37]. However, the considerable number of candidates often identified by this methodology has made the perspective of rapid functional annotation a daunting task. Here, we present the results of a genome-wide RNAi screen in Drosophila S2 cells that specifically focused on signal regulation between RAS and MAPK. Validated hits were submitted to a series of secondary assays aimed at positioning their regulatory input with respect to the three core kinases. In addition to identifying and correctly positioning most of the components previously known to mediate RAS-induced MAPK activation, the screen led to the discovery of several new factors that act at different steps along the pathway. Notably, we identified five novel components that act upstream of RAF. The homologs of these five proteins are part of a complex named striatin-interacting phosphatase and kinase complex (STRIPAK) [38] that also includes PP2A, which is known to regulate RAF activation [39], [40]. Unexpectedly, the majority of our candidates did not map to the interval between RAS and RAF, but were instead positioned further downstream. These included some transcription factors that we found regulate the transcript abundance of mek, mapk, or of the MAPK phosphatase PTP-ER. However, most of the novel factors were associated with mRNA processing and were found to act downstream of MEK and to regulate mapk splicing. Among these were components of the exon junction complex (EJC), which we and others have previously reported to be involved in regulating the splicing of the mapk pre-mRNA [41], [42]. In particular, depletion of the EJC was found to alter the splicing of mapk' s long introns and cause a reduction in the amount of functional protein product. In this study, we focus on the function of a larger group of canonical splicing factors that also regulate mapk splicing. We show that the impact of these factors on alternative splicing (AS) of mapk differs from what we previously described for the EJC, indicating that two different types of regulatory input act on this step in mapk expression. Thus, in addition to providing a comprehensive view of regulatory factors influencing signal transmission between RAS and MAPK, this work suggests that pathway output does not solely rely on post translational regulatory events, such as those controlling RAF activation, but is also tightly governed by the regulation of the expression of core components. In particular, the expression of MAPK emerges as a focal point for multiple different regulatory inputs.
  To systematically search for and categorize new factors that specifically modulate signaling between RAS and MAPK, we employed a screening strategy that involved three distinct steps: (1) a primary genome-wide RNAi screen, (2) a validation screening step aimed at eliminating false positives, and (3) validated candidates were submitted to a series of a secondary screens to establish the position of their regulatory input relative to known pathway components (epistasis) and assess their specificity to RAS/MAPK signaling (Figure S1A). We employed an automated immunofluorescence-based microscopy assay that quantitatively detected variations of dually phosphorylated MAPK (pMAPK) in Drosophila S2 cells. This assay was used to screen a genome-wide long double-stranded RNA (dsRNA) library for modulation of pMAPK levels induced by RASV12 expression (Figure S1B and S1C). The results from this primary screen and all subsequent screens are made available online at the IRIC RNAi database (http: //www. bioinfo. iric. ca/iricrnai). 309 hit genes, which reproducibly altered pMAPK signal, were identified in the primary screen (Table S1). Importantly, core RAS/MAPK pathway components (e. g. , raf/phl, mek/Dsor1, mapk/rl, cnk, and ksr) were amongst the strongest hits that decreased the pMAPK signal (Figure 1A; Table S1). Other known positively acting genes were also identified, such as 14-3-3ζ and the RAF chaperone Cdc37 [43]. Another expected hit was βggt-I, which encodes a factor involved in RAS prenylation [10], [44], [45]. Also expected, the PP2C phosphatase alph was identified as a negative regulator [23]. We next conducted two successive validation steps to address readily identifiable sources of false positives, namely effects on the pMet-RASV12 expression system and dsRNA off-target effects. 101 genes of the initial 309 primary hits passed both validation criteria (Figure S2; Table S1; Text S1). Validated genes were then assigned to broad functional categories on the basis of their associated gene ontology (GO) terms and on the functions of predicted homologs. Interestingly, transcription and mRNA processing factors composed, together, roughly half of our candidates (Figure 1B), and mRNA processing was the most highly enriched GO term of our hit set (Table S2). Despite the fact that mRNA splicing factors are often enriched in RNAi screen hit lists [46], we chose not to apply a selection bias against any group of genes at this stage. Therefore, all of the candidate genes passing both primary and validation screen criteria were evaluated in secondary screens without distinction. To further characterize the 101 candidate genes, we conducted a series of secondary screens that can be subdivided into three groups: (1) MAPK activation induced by stimuli upstream of RAS, (2) epistasis screens involving MAPK activation at the level of or downstream of RAS, and (3) JNK activation screens aimed at addressing specificity to the MAPK pathway context (Figure S3; detailed results in Tables S3, S4, S5). Four distinct MAPK activation assays using RTKs or GAP RNAi (Figure S3) were conducted to assess the degree to which pathway activity could be perturbed by depletion of the candidate genes in different activation contexts occurring upstream of RAS. Although a few exceptions were found, in most cases, we observed signal modulation that was generally consistent with our RASV12 results. Next, epistasis experiments were carried out using S2 cell lines expressing either constitutively activated forms of RAF or MEK (Figures 2 and S3). The aim of these experiments was to position the identified genes in relation to the core kinases of the pathway by comparing the values from the RAS, RAF, and MEK activation assays. To do this, we calculated the correlation of our screening data with theoretical profiles of hypothetical components acting within three possible epistasis intervals (RAS-RAF, RAF-MEK, and MEK-MAPK) using an uncentered Pearson' s correlation metric (Figure 2C; Table S3; Text S1). All known pathway components were positioned correctly by this approach. For example, Ras85D, ksr, cnk, hyp/ave, 14-3-3ζ, 14-3-3ε, and βggt-I are part of a group of genes that suppressed RASV12, but not activated RAF or activated MEK; these components were thus correctly positioned in the RAS-RAF interval (Figure 2B and 2C). Nine additional genes also fell into this category (Table S3) and therefore represent potentially novel pathway regulators acting at this level. Strikingly, while only eight hits (including the RAF chaperone Cdc37) mapped between RAF and MEK, most of the candidates (69) were assigned to the MEK-MAPK interval (Table S3), with the majority of these being factors not previously linked to RAS/MAPK signaling. This unexpected finding suggests that additional regulatory events that escaped prior detection are lying downstream of MEK. RAC1V12 and peptidoglycan (PGN) were then used as stimuli in two JNK activation assays as a proxy to evaluate specificity to the RAS/MAPK signaling context (Figure S3). Very few of the candidates modulated pJNK to a similar extent as they did pMAPK (Table S4). One of these was the ALPH PP2C phosphatase, whose depletion increased both pMAPK and pJNK signals. This is consistent with our recent findings demonstrating that ALPH negatively regulates both MAPK and JNK signaling [23], [47]. Remarkably, the vast majority of the RNA processing factors identified in the primary screen did not modulate pJNK levels and thereby argued for their specific role in RAS/MAPK signaling (Table S4). We next submitted our secondary screen data to unsupervised hierarchical clustering to group candidates with similar profiles together (Figure 3A). Bona fide pathway components with similar functions are clearly grouped together by this analysis. For example, Ras85D, ksr, cnk, and hyp all act at the level of RAF activation and all show very similar profiles. Both 14-3-3 isoforms, which also act at this level, are grouped together and are also close to the first group of genes involved in RAF activation, as is βggt-I, a component involved in RAS prenylation. On the basis of these findings, we can expect that candidates who have a similar profile to bona fide RAS/MAPK pathway components might in fact share the same function as these components. Following this, we sought to identify putative protein complexes as well as related factors in our set of candidates by constructing a protein interaction network (PIN) based on publicly available protein and genetic interaction data (Figure 3B). The canonical RAS/MAPK components are clearly grouped together in this network and at least two other complexes can be clearly distinguished. The first consists of components of the STRIPAK complex and the second is composed primarily of mRNA processing factors. Remarkably, the components of both complexes also group together in similar functional profiles in our clustering analysis (groups “1” and “2” in both panels of Figure 3). Given that several of our candidate genes are linked to RNA processing and transcription, we hypothesized that these factors might be acting on the expression of one or multiple RAS/MAPK pathway components. We first investigated the impact of our candidates on the expression of core RAS/MAPK pathway component transcripts (Ras85D, raf, mek, mapk, ksr, cnk, and PTP-ER) by quantitative PCR (qPCR) (Figure S4A; Tables S5 and S8). A specific effect on the mapk transcript was observed upon depletion of mago and eIF4AIII (Figure 4A; Tables S5 and S6) as we have previously reported [41]. At least three other factors (Cdk12, Fip1, and CG1603) also seemed to modulate the transcript levels of mapk. Moreover, two factors, gfzf and CG4936, were found to modulate the levels of mek and PTP-ER, respectively (Figure 4A; Table S6). CG1603, gfzf, and CG4936 were subsequently tested in larval eye disc tissue where similar results were obtained (Figure 4B). Surprisingly, aside from the candidates mentioned above, most hits did not appear to cause a significant change in the transcript levels of pathway components. We had previously observed that qPCR assays targeting mapk are not always strongly affected by the splicing changes induced by EJC depletion. On the other hand, a reverse transcription PCR (RT-PCR) assay spanning the whole mapk transcript is a more sensitive tool allowing for detection of small splicing changes [41]. Based on this premise, and on the fact that almost all the splicing factors we identified mapped downstream of MEK, we decided to systematically examine the impact of these factors on mapk splicing. Consequently, we used the RT-PCR assay that had been used with the EJC to examine mapk splicing. Interestingly, not only did this experiment reveal that nearly all the splicing factors in our set caused shifts in the mapk RT-PCR profile, but these RT-PCR profiles were also clearly different from those produced by EJC depletion (Figure S5). Thus, while the impact of most of our candidates on mapk expression may not be apparent when measuring total transcript abundance, a clear impact on the different mapk isoforms can be observed by RT-PCR, indicating that these factors regulate AS of mapk. In the case of the EJC, the splicing changes were accompanied by a corresponding decrease in MAPK protein levels. Because of this decrease, we decided to also measure the impact of our candidates on MAPK protein levels using quantitative immunofluorescence. This analysis confirmed that most of the factors positioned downstream of MEK (including most of the RNA processing factors) also caused a reduction of MAPK protein levels. Conversely, AKT protein levels, which were used as a control, were not generally sensitive to depletion of these same factors (Figure 5A). We also verified the impact on MAPK and two other pathway components (RAS and CNK) by Western blot. Most candidates that caused a reduction in MAPK levels did not impact the levels of RAS, CNK, or AKT (Figure S6), which mirrored the results from the immunofluorescence experiment. Thus, both evaluations of MAPK protein levels agreed with the RT-PCR experiments suggesting that the changes in splicing results in a reduction of MAPK protein abundance. Most of the other hits, including those positioned at the RAS-RAF and RAF-MEK intervals, did not appear to cause a change in the expression of RAS/MAPK pathway components. However, we observed that a minority of candidates seemed to cause fluctuations in multiple proteins or transcripts. Likewise, these candidates also tended to impact some or all of the non-RAS/MAPK related assays we tested them in (Table S5). Moreover, these hits were also more frequently present in hit lists of other published RNAi screens (Table S4). Consequently, in order to discriminate such non-specific hits from higher quality candidates, we derived a scoring system that factored in results from the pJNK assays, pMet-green fluorescent protein (GFP) expression, hit occurrence in previously published RNAi screens, and the impact on measured protein and transcript levels (see Table S4; Text S1). As expected, a few of the splicing factors in our list had low specificity scores. On the other hand, most of the factors that selectively affected MAPK levels, including the majority of the splicing factors, were not present in previous screen hit lists more frequently than bona fide RAS/MAPK factors and generally displayed a good specificity to the RAS/MAPK context (Tables S4 and S5). This finding suggests that discriminating against an entire category of genes on the basis of the enrichment of that category in previous screen hit sets is a strategy that can lead to elimination of meaningful candidates. Most of the positive regulators positioned in the RAS-RAF interval were factors that had previously been linked either to RAS prenylation or regulation of RAF activation. As previously mentioned, one of the RAS prenylation factors we identified was βggt-I, which was originally identified in Drosophila [10], [45]. In addition to βggt-I, two other factors that are known to function in RAS prenylation in other organisms were also identified: Hmgcr and Fnta (CG2976). FNTA is the alpha farnesyltransferase subunit for mammalian RAS proteins [48]. The hydroxymethylglutaryl-CoA reductase HMGCR functions in the cholesterol biosynthesis pathway and is required for farnesylation of RAS and other membrane-associated proteins [49], [50]. In our Western blot experiments, all three of these factors were observed to cause a mobility shift in RAS suggesting that RAS geranylgeranylation is impaired [51], and thus that these factors act on RAS in Drosophila (Figure S6A, S6C, and S6J). RAF activation is arguably the most tightly regulated step of the MAPK module [1], [27], [52]. Multiple components are involved in a series of events that link up RAF to RAS, anchor RAF at the plasma membrane, allow RAF to adopt and maintain an active conformation and finally enable efficient substrate targeting [52]. Phosphorylation and dephosphorylation events control progression throughout these steps [52]. Of these, the removal of the phosphate moiety on the S346 residue of Drosophila RAF (equivalent to S259 of human RAF1) is one of the pivotal regulatory events as it is thought to trigger the release of 14-3-3, which otherwise sequesters RAF in the cytoplasm [52]. Of the factors involved in RAF activation, all of the expected factors (ksr, cnk, hyp, 14-3-3ε, and 14-3-3ζ) were correctly positioned at the RAS-RAF interval (Figure 2B). Two other candidates, Pp1-87B and Sur-8, also clustered together with the set of known factors acting in the RAS-RAF interval. These two factors had not previously been shown to act on MAPK signaling in Drosophila, but evidence from other organisms indicates that they might act at this level [16], [17], [40], which is consistent with our results. Of particular interest, one study has found a mammalian complex composed of PP1, SUR-8, and MRAS and linked it to dephosphorylation of the S259 residue on C-RAF [53]. The only other positive regulators in the RAS-RAF epitasis group that were not previously linked to RAS/MAPK signaling were five components that form the smallest of two complexes in our network (CKA, STRIP, SLMAP, FGOP2, and MOB4) (Figure 3B). Three of these components are distantly related to budding yeast alpha factor arrest (FAR) complex components, which are involved in signaling G1 arrest upon alpha factor stimulation [54]. More recently, a protein complex comprising Striatin, the catalytic subunit of PP2A, the STE20 family kinase STK24, and four additional core proteins was identified in human cells and named the STRIPAK complex [38]. The core of this complex was suggested to serve as a protein platform that specifies PP2A and/or STK24 action. Remarkably, the five RAS-RAF proteins identified are homologs of the non-catalytic members that make up the core STRIPAK complex. CKA, which is the fly Striatin homolog, has previously been demonstrated genetically to act as a positive regulator of JNK signaling [55]. MOB4 has also been previously studied genetically in Drosophila, where it appears to participate in mitotic spindle assembly [56]. The three other members, STRIP, FGOP2, and SLMAP, have not been extensively studied in flies and are named on the basis of their mammalian counterparts. Consistent with their ability to work together as a complex, the five STRIPAK homologs had similar effects in all the secondary screens and epitope-tagged variants co-immunoprecipitated in binary co-expression experiments (Figures 3A and S7). Notably, their depletion also suppressed JNK activation induced by RAC1V12, suggesting that CKA/Striatin modulates signaling through this pathway and that the other STRIPAK members act in conjunction with Striatin in this context. This is also consistent with the findings that TRAF3-interacting JNK-activating modulator (T3JAM), one of the SLMAP homologs, is linked to JNK signaling [57] and with a recent report that identified Cka as a suppressor of JNK signaling [58]. Furthermore, depletion of STRIPAK components reduced pMAPK signal induced by insulin, activated Sevenless RTK (SEVS11) and GAP RNAi, but only marginally affected EGFR signaling (Figure S5). This suggests that the role of STRIPAK differs depending on the MAPK and JNK activation contexts. To confirm the involvement of STRIPAK complex components in RAS/MAPK signaling in vivo, we conducted genetic interaction experiments using Cka/Striatin mutant alleles [55]. RAS/MAPK activity is required for neuronal photoreceptor and cone cell differentiation during Drosophila eye development [59], [60]. Expression of RasV12 under the control of the eye specific sev promoter/enhancer regulatory sequences produces extra photoreceptor cells, which causes a characteristic rough-eye phenotype (Figure 6B) [61]. This rough eye phenotype was dominantly suppressed in a Cka heterozygous mutant background (Figures 6E and S8A). Extra wing vein material produced by a constitutively active Egfr allele, EgfrElp, was also dominantly suppressed by Cka mutant alleles to a degree comparable to a weak loss-of-function allele of rl/mapk (Figure S8E and S8J). In agreement with these results, wing vein deletions were significantly enhanced in a shp-2/csw hemyzygous mutant background when a Cka mutation was introduced in this context (Figure S8D, S8I, and S8K). Moreover, consistent with the role of STRIPAK in RAS/MAPK signaling, loss-of-function of Cka activity impaired R7 photoreceptor cell differentiation, which is a classical RAS/MAPK-dependent developmental event (Figure S9). In addition to PP2A/mts, we noted that some of the other STRIPAK components described in Goudreault and colleagues [38] were not identified in our primary screen. However, one of these, GckIII, was one of the validated regulator in the InR-driven MAPK screen reported by Adam Friedman and Norbert Perrimon [62]. This raised the possibility that GckIII might have an impact on pathway activity in alternate activation contexts. To address this, we examined the effects of depleting GckIII in RASV12, insulin, and GAP RNAi assays. We found that while this had little impact on RASV12-induced MAPK activation, GckIII depletion had an effect comparable to Fgop2 depletion in the insulin and GAP RNAi contexts (unpublished data). This indicates that GckIII may function upstream or in parallel to RAS and raises the intriguing possibility that the STRIPAK complex regulates multiple aspects of the larger RTK/RAS/MAPK pathway. Since Striatins are defined as PP2A regulatory (B) subunits [63] and STRIPAK was initially described as a PP2A associated complex, it is possible that STRIPAK assumes this role in the context of RAF activation. We observed a modulation of RASV12 signaling upon depletion of the catalytic subunit of PP2A (mts), but not of the regulatory B subunit, tws, which support the notion that STRIPAK components are functioning as PP2A regulatory (B) subunits in this context (unpublished data). A similar function for STRIPAK has recently been described in the context of Hippo signaling, where it was found to associate with PP2A and HPO [64]. Finally, in agreement with our findings, another recent report has linked the CKA subunit to RAS/MAPK signaling [65] and another study conducted in Neurospora has indicated that MAPK regulates STRIPAK function, suggesting the possibility of regulatory feedback phosphorylation [66]. Only 13 of our candidates were found to act downstream of RAF and upstream of MEK. Of these, the RAF chaperone Cdc37 was the only bona fide pathway regulator. Among the others, CG8878 was of interest as it is the homolog of the mammalian Vaccinia-Related Kinase (VRK) genes of which two (VRK1 and VRK3) have been recently identified in a recent screen for KRAS synthetic-lethal factors [67]. Also, another study has shown that VRK2 interacts with MEK and KSR1, potentially acting on MEK activation [68]. However, in this context, VRK2 acts as a negative regulator whereas CG8878 appears to act positively on RAS signaling in our experiments. The most interesting candidate that fell within the RAF-MEK interval was GST-containing FLYWCH zinc-finger protein (gfzf). GFZF was initially found because of the property of its GST domain to bind to glutathione sepharose beads [69]. It does not, however, have any clearly identified function assigned to it, though there are indications that it may act as a co-factor for the E2F transcription factor [70]. Also, recent RNAi screens have suggested that gfzf may be acting downstream of PDGF to control cell size [71] and as a factor functioning in the G2/M DNA damage checkpoint [72]. In our qPCR experiments, gfzf clearly stood out from other candidates as it was the only factor that caused a strong reduction in mek transcript levels and had the closest profile to the mek RNAi itself (Figures 4A, 4B, and S4A). This observation also extended to the protein product as we observed a clear reduction in MEK levels upon gfzf knockdown (Figure 4C). In flies, two different gfzf loss of function alleles suppressed the RasV12 rough eye phenotype (Figures 6F and S8A). gfzfcz811also increased the severity of wing vein deletions in hemizygous cswlf males (Figure S8D and S8K). Finally, knocking down gfzf reduced RASV12-induced hemocyte proliferation (Figure 7A). Together, these observations suggest gfzf is regulating mek, possibly by acting as a positive transcription factor. Since FLYWCH domain proteins have been found to negatively control miRNA expression in C. elegans [73], one interesting alternative is that gfzf represses the production of a miRNA that targets the mek transcript. Another candidate, CG9797, was clustered close to gfzf through the functional screen data and the qPCR results (Figures 3A and S4A), and its protein product is predicted to interact with GFZF (Figure 3B). In the qPCR screen, CG9797 knockdown caused a weak reduction in mek transcript levels; it is the fourth strongest hit in terms of reducing mek levels, after the dsRNAs targeting gfzf, mek, and RpL24 (Table S5). From this, and since CG9797 encodes another zinc finger protein, it is possible that this factor works in conjunction with GFZF as a transcriptional regulator. Recently, the chromatin remodeling factors Geminin and Brahma have been found to modulate MEK protein expression in drosophila wing discs [74], raising the possibility that gfzf might be acting in conjunction with these factors. mRNA processing and transcription factors formed the largest group of hits in our study and also the largest complex in our network analysis (Figures 3B and S1B), and almost all these factors mapped to the MEK-MAPK epistasis interval (Table S5). While the majority of the candidates in this category cause changes in mapk expression, one clear exception was CG4936. This gene encodes a zinc finger protein of unknown function that is distantly related to human ZBTB20, a BCL-6 like transcription factor that is expressed in hematopoietic tissues and lymphoid neoplasms [75]. CG4936 also mapped downstream of MEK, but was not found to influence mapk expression. A first clue as to the function of this factor was provided by the observation that CG4936 behaved very similarly to PTP-ER in our functional screens; of all the candidates, it has the closest profile to PTP-ER (Figure 3A). One of the two MEKEE-based MAPK activation assays involved the use of PTP-ER RNAi to increase the pMAPK signal. Surprisingly, while both PTP-ER and CG4936 RNAi significantly increase MEKEE-induced pMAPK levels, combining CG4936 and PTP-ER RNAi did not have an additive effect on pMAPK levels (Figure 2B; Table S5). This finding suggests that these factors work together in the same regulatory pathway. CG4936 also clustered close to PTP-ER in our qPCR screen (Figure S4A). Consistent with this, both qPCR and protein analysis revealed that CG4936 knockdown respectively caused a specific reduction in PTP-ER transcript and protein levels (Figure 4A, 4B, and 4D). Furthermore, in our genetic interaction experiments, flies trans-heterozygous for two P-element insertion alleles of CG4936 (CG4936EY10172/CG4936DG10305) showed an enhancement of the RasV12 rough eye phenotype (Figure 6G) and suppressed lethality and phenotypes caused by a homozygous mapk/rl1 hypomorphic allele (Figure S8C, S8G, and S8H). CG4936EY10172 alone suppressed the lethality and wing vein deletions of cswlf hemizygous males (Figure S8I and S8K), as did the double CG4936 mutant (unpublished data). Moreover, cswlf homozygous females were observed in a background heterozygous for CG4936EY10172, which is indicative of suppression as cswlf is recessive lethal. Altogether, these data suggest that CG4936 acts on PTP-ER transcription and that this action has bearing on RAS/MAPK dependent developmental processes. Excepting CG4936, most of the other candidates positioned downstream of MEK (39) caused a decrease in MAPK protein levels (<−0. 25 log2-fold and p<1×10−5) (Table S5). A few of these factors caused a significant and reproducible reduction in mapk transcript levels as well, without significantly impacting the levels of other RAS/MAPK pathway components (Figure S4A; Table S5). These factors include two EJC components (eIF4AIII and mago) as well as three other candidates: Cdk12, Fip1, and CG1603. Depletion of these latter candidates led to a significant drop in mapk transcript levels as measured by qPCR (Figure 4A; Table S6). However, these three factors could be distinguished from the EJC components by the fact that they did not cause a shift in the mapk RT-PCR profile (Figure S5), but only a decrease in the overall transcript abundance, suggesting that they do act at a different step of mapk expression. Finally, lethal alleles of CG1603 and Fip1 dominantly suppressed a RasV12 induced rough eye phenotype (Figures 6H and S8A). The CG1603 allele also suppressed the extra wing vein phenotype caused by EgfrElp, as did Cdk12KG05512 (Figure S8E and S8J). However, none of the alleles had a readily observable impact on cswlf phenotypes (unpublished data); although Fip1 did cause a slight enhancement of cswlf lethality (Figure S8I). Finally, consistent with our cell culture data, knockdown of CG1603 in larval imaginal disc clones was found to cause a pronounced decrease in MAPK protein levels (Figure 7C). Cdk12 is the main RNA polymerase II C-terminal domain kinase. Phosphorylation of the C-terminal domain of RNAP II is required for transcription elongation, RNA processing, and splicing [76], [77]. Thus it is possible that Cdk12 influences either of these steps in the case of mapk expression although it does not seem to induce AS. CDK12 has previously been shown to function in conjunction with Cyclin L in regulating AS [78]. Consistent with these data, the Drosophila CycL ortholog, CG16903, was also a hit in our screen that mapped to the MEK-MAPK interval (Table S3) and caused a shift in the mapk RT-PCR profile (Figure S5). However, CG16903 did not significantly change mapk transcript levels measured by qPCR (Table S5). Fip1 is also involved in transcript processing; its best studied ortholog in yeast is part of the pre-mRNA cleavage and polyadenylation complex [79]. mRNA polyadenylation plays an important part in stabilizing spliceosome assembly on the 3′ most exon of the transcript, is an important pre-requisite for effective mRNA export, and also influences mRNA stability [80]–[82]. Thus, like Cdk12, Fip1 may be regulating mapk expression by controlling transcript abundance or by influencing splicing efficiency. CG1603 encodes a protein of unknown function that contains MADF type zinc finger domains that are related to Myb DNA binding domains [83]. CG1603 is poorly conserved in humans, bearing distant homology to ZNF664 and ZNF322. Interestingly, ZNF322 was found to act as a transcriptional co-activator of SRF and AP-1 in humans, which would position it downstream of MAPK signaling [84], thus representing a potential feedback mechanism. The majority of the factors that were observed to lower MAPK levels were either spliceosome components or factors associated to the splicing machinery (Figure 5A; Table S5). Intriguingly, multiple lines of evidence suggested that these splicing components can also play a specific role in modulating RAS/MAPK signaling: (1) most splicing factors did not have any detectable impact on CNK, AKT, and RAS levels, even though these proteins are all derived from intron-containing genes (Figure S6), (2) depletion of most splicing factors by RNAi did not significantly modulate PGN (peptidoglycan) and RAC1V12-induced JNK activation (Figure 3A; Table S4), and (3) these splicing factors scored as hits in previous screens less often than bona fide RAS/MAPK pathway components (Table S4). Accordingly, the majority of these splicing factors were categorized in the high specificity group. Importantly, many of these had impacts on MAPK levels that were comparable to or greater in strength than those splicing factors of the lower specificity group. This finding suggests that the higher specificity score is not simply attributable to lower knockdown efficiency or a weaker impact on constitutive splicing. Interestingly, one indication that the canonical splicing factors might be acting differently on MAPK signaling than the EJC came from our qPCR expression data. Namely, some high specificity splicing factors such as the CG10754 (the counterpart of human SF3A2, a U2 small nuclear ribonucleic particle [snRNP] associated factor involved in branch point binding [85]), CG3198 (the ortholog of LUC7L3, a predicted splicing factor [86]), Prp19 (the central component of the PRP19 spliceosomal complex involved in C complex assembly [87]), as well as CG4849 and CG6686 (two predicted tri-snRNP components [88], [89]) all caused a reduction in MAPK protein levels comparable to the EJC factors mago and eIF4AIII. However, no reduction of mapk mRNA was observed by qPCR (Figure 4A; Table S5). Furthermore, another important difference between the EJC and the canonical splicing factors was that the depletion of many candidates of the latter group caused an increase in nuclear pre-mRNA retention as measured by fluorescence in situ hybridization using a poly-A probe (Figure S4B and S4C) [90]. This indicates—as might be expected—that most of these splicing factors also play a more general role in splicing. The key difference between the EJC and canonical splicing factors suggested by the qPCR and pre-mRNA export data was readily observable using the whole-transcript mapk RT-PCR assay; both groups caused an alteration in the mapk RT-PCR product, but the canonical splicing factors produced a clearly different pattern (Figure S5). Since most of the candidates in the canonical splicing factors group produced similar shifts in the mapk RT-PCR profile, we selected two representative factors for more detailed follow-up experiments. The first, Prp19, was selected because it is a core spliceosome component that caused a strong reduction in MAPK levels and had a clear impact on the mapk RT-PCR profile (Figures 5A, 5B, and 8B). The second, Caper, was selected because it is a serine rich (SR) AS factor [91] that did not perturb global pre-mRNA export, and it caused a weaker reduction in MAPK protein levels and a less severe change in the mapk RT-PCR profile (Figures 5A, 5B, 8B, and S5). Consistent with the protein expression data, while both factors clearly altered the mapk RT-PCR products, similar RT-PCR assays targeting Ras85D, raf, mek, cnk, or ksr did not display any obvious change (unpublished data). Also, Western blot experiments showed a clear drop in MAPK protein levels with no effect on RAS, RAF, MEK, or AKT (Figure 5B); this suggests that splicing of mapk, and not of other pathway components, is affected. Also lending strength to the idea that splicing factors may have a specific role in the RAS/MAPK context was the fact that three Prp19 alleles and one Prp8 allele, were isolated by our group in an independent genetic screen for modifiers of a dominant-negative form of CNK (Figure S8B and CB, ML, MS, and MT, unpublished data). In addition to this finding, Prp8 has been previously found to enhance the small wing phenotype induced by expression of the Egfr inhibitor aos [92]. Consistent with this result, the Prp19 and Prp8 alleles dominantly suppressed the RASV12 rough eye phenotype, as did an allele of Caper (Figures 6I, 6J, and S8A). The Prp19 alleles also dramatically enhanced cswlf lethality and suppressed the EgfrElp wing phenotype (Figure S8E, S8I, and S8J). Moreover, in mapk/rl1 homozygous flies, Prp19 and Caper alleles enhanced the severity of wing vein deletions and rough eye phenotypes (Figures 6K–6R, S8G, and S8H). Importantly, although flies carrying one copy of both Caperf07714 and Prp19CE162 were perfectly viable, this allelic combination was entirely lethal in a mapk/rl1 homozygous background (Figure S8G). This result constitutes another indication that these splicing factors are acting in concert on mapk expression. Finally, splicing of mapk was found to be altered in Prp19CE162 flies also homozygous for rl1 (Figure S10A and S10B). The rl1 mutant alone reduces mapk transcript levels without altering the RT-PCR splicing profile [93; and unpublished data]. Complementing the genetic interaction experiments, expression of Prp19 RNAi reduced the RasV12-induced proliferation of larval hemocytes (Figure 7A). In addition, clonal tissue expressing Prp19 RNAi in wing imaginal discs consistently caused a reduction in MAPK levels (Figure 7D), although the reduction was not as pronounced as that of mapk RNAi. Clonal regions sometimes showed signs of apoptosis (in one of the two RNAi constructs tested and in wing discs in particular) suggesting that these tissues may be more sensitive to knockdown of Prp19 than S2 cells. Finally, splicing of mapk was found to be altered in wing disc segments where Caper had been knocked down (Figure S10C). Altogether, these experiments suggest that these transcription and splicing factors are important in regulating MAPK levels, and thus are important for MAPK signaling. Furthermore, our genetic interaction data suggests that they can act in a number of different in vivo contexts. In particular, the Prp19 alleles had an impact in all our RAS/MAPK genetic interaction experiments and displayed some of the strongest phenotype modifications. Thus, of the different groups of candidates, it is quite possible that splicing factors are relevant to the broadest range of RAS/MAPK regulatory and developmental contexts. Prp19 and Caper RNAi display similar mapk RT-PCR profiles, but Caper produces a more subtle shift in product size with less lower size bands observable (Figure 8B). To verify that these changes in the RT-PCR profile of mapk were due to altered splicing, we cloned and sequenced the RT-PCR products. We found that the lower size mapk transcripts produced by both Caper and Prp19 RNAi were generated by a series of exon skipping events and, to a lesser extent, by retention of the 5′ most intron of the RB/RE isoforms (Figure 8A–8D; Table S7). Prp19 and Caper RNAi produced many single exon skipping events with exons IV and VII being the most frequently skipped. These AS events differed from those we had previously observed in EJC depleted samples, where skipping of multiple consecutive exons was observed immediately to the 3′ end of exon I [41]. Interestingly, exon skipping events associated with the EJC mostly resulted in frameshifting due to the loss of the start site in exon II and/or skipping of exon III. On the other hand, the skipping of exons IV and VII associated with Prp19 and Caper produce an in-frame deletion potentially giving rise to a truncated protein product. The fact that we did not observe any smaller size products may be due to the epitope being removed or to the smaller products being unstable and degraded (MAPK is mostly composed of a kinase domain and it is likely that these deletions would disrupt proper folding). In order to confirm that depletion of Prp19 and Caper produced AS changes in mapk that were different from those produced by EJC depletion, we designed RT-PCR assays aimed at detecting specific AS events. Using primer pairs in which the 5′ primer overlapped the exon junction between exons I and III or exons I and IV, we were able to detect an enrichment in exon II–III and II–IV skipping in eIF4AIII depleted samples, consistent with our previous results. However, these exon skipping events were not enriched in Caper and Prp19 RNAi samples. Conversely, using the same strategy, increased skipping of exons IV and VII was observed for Caper and Prp19, but not for eIF4AIII (Figure 8E). Also, using primers targeting the exons on either side of the skipped exons, we were able to detect both the canonical and the alternative transcripts produced by either Prp19 or Caper depletion in both S2 cells and wing disc tissue (Figures 8E and S10C). In sum, multiple lines of evidence indicate that Prp19 and Caper cause specific changes in mapk splicing that differ from those associated to the EJC. This finding suggests that at least two different types of regulation act on mapk AS. By extension, it is likely that the other splicing factors identified in our screen can be grouped with Caper and Prp19—and not the EJC—since they produced mapk RT-PCR profiles similar to these factors.
  With the exception of the well described regulation of RAS by let-7 family miRNAs [22], surprisingly little is known on the regulation of MAPK module component expression. It was therefore surprising to find that our largest group of hits specifically decreased MAPK levels. Yet, control of MAPK expression is not unprecedented. For example, in yeast, both the FUS3 and HOG1 MAPKs are transcriptional targets of their respective pathways [94]. Pumilio mRNA binding proteins are also known to reduce MAPK activity by lowering the expression of the C. elegans MAPK, Mpk-1, as well as ERK2/MAPK1 and p38α/MAPK14 in human embryonic stem (ES) cells, through the binding of specific sites on the 3′ UTR of their respective transcripts [95]. Finally, LARP-1 RNA-binding proteins have been found to control the abundance of the transcripts of Mpk-1 and other pathway members in the C. elegans germ line [96]. In this study, we found that multiple splicing factors act downstream of MEK to specifically control MAPK levels. While some of these factors were associated with the regulation of AS, most were components of the spliceosome or factors that co-purify with the spliceosome. Interestingly, many lines of evidence suggest that AS can be modified by spliceosomal factors [97]–[106]. Global analyses of splicing events in yeast using a series of temperature sensitive alleles and deletions of splicing factors, found that spliceosome components differed in terms of which splicing events they altered [98], [99], [105]. Among these, the yeast homologs of Prp19, Prp8, U4-U6-60K, l (3) 72Ab, Prp6, SmD2, SF3a120, CG4849, and CG10333—factors included in our set of hits—were found to differentially modulate the splicing of specific sets of transcripts [98]. Moreover, studies conducted in Drosophila using an RNAi-based strategy have demonstrated that knocking down many so-called “core” spliceosome components caused specific changes in specific AS contexts [100], [101]. In particular, some of the “core” components identified in our screen have been shown to have selective effects. For example, knocking down Prp6, l (3) 72Ab, crn, Caper, SF3a120, and CG10418, was found to differentially influence AS of Dscam, para, TAF1, and/or dAdar [100], [101]. In mammals, SmB was also recently shown to be involved in regulating inclusion of alternative exons [103]. Finally, our observation that a Prp19 knockdown had specific effects on MAPK protein levels and the identification of Prp19 (as well as Prp8) in a separate CNK-based genetic screen supports the notion that these splicing factors are important for mapk expression in vivo. Thus, the fact that we identified specific spliceosome components in our screen and not others may reflect the importance of these particular components in regulating mapk splicing. The specific elements of the mapk gene structure that dictate requirement of particular splicing factors have yet to be determined. Likewise, many—if not most—other genes may have structures that preclude AS regulation by components of the spliceosome. Still, AS processes in at least four other Drosophila genes seem to involve some of the same components of the splicing machinery that we have linked to mapk, indicating that a common characteristic may dictate the involvement of these spliceosome components in AS. On the other hand, the fact that some of the spliceosome factors are involved in specific AS contexts and not others, suggests that key differences exist. This observation is important as it implies that specific AS events can be modulated by controlling the activity of these spliceosomal factors. In support of this idea, one of the previously mentioned studies indicates that the control of TAF1 AS by a series of splicing factors—which include Caper and other spliceosome components—is downstream of a Camptothecin-induced ATR pathway [101]. Another example is the regulation of CD44 AS by RAS/MAPK-induced phosphorylation of Sam68, which has been found to function by regulating the activity of the U2AF65 spliceosome component [107]. In addition to Sam68, other splicing factors and spliceosome components—including some that were identified in our screen—were recently found to be the targets of ERK phosphorylation [108]–[110]. Finally, a general splicing repressor, SRp38, has also been shown to function as a sequence specific splicing activator upon phosphorylation in response to cellular stress [111]. One explanation for our results, as well as some of the previous observations, would be that some of the spliceosomal factors in our set may be interchangeable or function as non-essential co-regulators. Thus, removing these components would not greatly disrupt general spliceosome function, but rather lead to an altered spliceosome activity that selectively impacts sensitive AS contexts. An example of this is the interplay between PUF60 and U2AF65, which both function in 3′ splice site recognition; the two factors can either work cooperatively or independently, producing different splicing outcomes on the basis of the presence or absence of either protein [112]. A further example is the stress-induced relocalization of certain spliceosome and splicing factors that leads to changes in spliceosome configuration and AS [113]. Cellular stress has also been associated with the production of “non-productive” AS variants or silent messengers (transcripts that are either degraded by the quality control machinery or that do not encode functional proteins) [114], [115]. In fact, the AS we observed in mapk is reminiscent of the AS observed for the E3 ligase MDM2 following camptothecin-induced genotoxic stress [116]. In this study, the authors found that stress induced a number of non-productive MDM2 transcript isoforms that resulted in lower MDM2 protein levels and a stabilization of the MDM2 target, p53. It will be important to determine whether stress—or another signal—acts to control MAPK protein levels by inducing the AS we observe in our experiments. The discovery that MAPK expression is specifically modulated by mRNA processing factors raises multiple questions. Not only will it be vital to define the upstream signals that dictate this activity but it will also be important to assess which other genes are similarly regulated and to identify the common characteristic that renders them sensitive to this type of regulation. Also, the time frame within which these changes occur will have implications as to the role that this type of regulation can play in MAPK signaling. Typically, RAS/MAPK signal modulation has been observed to occur through either rapid post-translational mechanisms or through slightly slower mechanisms involving control of protein stability and transcriptional control. However, the reduction in protein levels we observed as a consequence of AS are only apparent over a period of days, probably because the MAPK protein is relatively stable. This finding indicates that this regulation will not be relevant over the shorter timeframes of previously characterized regulatory events and also implies that a prolonged stimulus will be necessary to produce the effects we observe. Therefore, control of mapk splicing may be more important in the context of certain tissues and organs, in development or in disease. Interestingly, the abundance of core spliceosome components has been shown to be regulated and vary both temporally and across different tissues [117]–[121]. What is more, disruption in core spliceosome components has also been found to cause changes in AS in diseases such as spinal muscular atrophy and retinis pigmentosa [122]. Mutations in splicing factors have also been found to occur in a large proportion of myelodysplasia patients [104], [123] as well as in melanoma [106]. Another study has shown that, in glioblastomas and astrocytomas, splicing factors controlled by c-Myc play a role in controlling the expression of pyruvate kinase, a factor that is important for aerobic glycolysis [124]. It will be interesting to explore whether, in contexts such as these, the altered activity of splicing factors may regulate MAPK levels with important functional consequences for either normal or diseased cellular function.
  pMet-RasV12 S2 cells diluted in Schneider medium (to a concentration of 1×106 cells/ml) were distributed in 96 well clear plates (Corning) containing 5 µl dsRNA aliquots at a concentration of ∼200 ng/µl. Plates were placed in plastic containers to reduce evaporation and incubated at 27°C for four days. RasV12 expression was induced by adding 0. 7 mM CuSO4 to medium 24 h prior to fixation. Cells were resuspended and transferred to concanavalin A coated plates and allowed to settle and adhere for 1 h. Cells were then fixed in 4% paraformaldehyde/PBS, washed, and blocked in 0. 2% Triton X-100/0. 2% BSA/PBS (PBT/BSA) and incubated overnight with an anti-pMAPK antibody (1/2,000; Sigma number M8159), washed in PBT/BSA, and revealed using an anti-mouse Alexa Fluor 555-conjugated secondary antibody (1/1,000; Invitrogen number A-21424). DAPI (0. 04 µg/ml) was used to stain nuclei. Mowiol (9. 6% PVA, Fluka) was added to wells prior to imaging. An automated fluorescence microscopy system (Zeiss Axiovert) was employed for plate imaging. Autofocus, image acquisition, and analysis were conducted using MetaMorph (Molecular Devices) software. The cell-scoring application in MetaMorph was used for cell segmentation and quantification of fluorescent signal. Candidates were assigned to one of three possible epistasis intervals (RAS-RAF, RAF-MEK, or MEK-MAPK) on the basis of the data from the following secondary screens: (1) RASV12, (2) RAFED, (3) RAFCT, (4) RAFEDCT, (5) MEKEE, (6) MEKEE+PTP-ER dsRNA. The correlations between normalized secondary screen log transformed values and three predetermined epistasis profiles were calculated using a modified uncentered Pearson' s correlation: Where r is the correlation value [−1,1], x is the secondary screen value (for screens number 1,2, 3,4, 5, and 6), y is the predetermined profile value, and w is the weight applied to a given screening experiment (where w = [3 1 1 1 1 2]; see Text S1). The following predetermined epistasis profiles y were used: RAS−RAF = [1 0 0 0 0 0] RAF−MEK = [1 1 1 1 0 0] MEK−MAPK = [1 1 1 1 1 1] A negative r indicates reverse correlation and is observed for positive pathway regulators. Fly husbandry was conducted according to standard procedures. All crosses were performed at 25°C. The sev-RasV12 line has been described previously [45]. EgfrElp was described in [125]. The Cka alleles [55] were kindly provided by S. Hou. The cswlf [126] flies were originally obtained from L. Perkins. The mapkE1171 allele was identified in a genetic screen as a dominant suppressor of a dominant negative form of KSR [127]. The Prp19CE162, Prp19CE40, Prp19TE1036, and Prp8CE309 alleles were recovered in a genetic screen for modifiers of a dominant negative form of CNK (CB, ML, MS, and MT, unpublished data). RNAi fly lines were obtained from the VDRC [128]. All other fly lines described herein were obtained from the Bloomington stock center. Adult fly eyes were imaged using a stereomicroscope (Leica MZ FL III) and CombineZP, a freely available software package (http: //www. hadleyweb. pwp. blueyonder. co. uk/CZP/News. htm), was used for focus stacking. Adobe Lightroom and GNU Image Manipulation Program (GIMP) were used for image processing. Wings were mounted in Permount (Fisher) on glass slides and imaged using a Nanozoomer (Hamamatsu). RNAi clones were generated using a line carrying a heat shock inducible flip-out actin promoter driving the expression of GAL4 and GFP in clonal tissues (hs-flp; ; Act5C>CD2>Gal4, UAS-GFP). L1 larvae were heat shocked for 15 minutes at 37°C and later collected for dissection upon reaching late L3 (wandering) stage. Third instar eye-antennal and wing discs were dissected in Schneider medium, fixed, and stained with DAPI and an anti-MAPK antibody (1/1,000, Cell Signaling number 4695) following the same procedure described above for S2 cells. The following Drosophila genes are named on the basis of their human counterparts: Fnta (farnesyl transferase alpha; CG2976), Fgop2 (fibroblast growth factor receptor 1 oncogene partner 2; CG10158), Slmap (sarcolemma associated protein; CG17494), Strip (Striatin interacting protein; CG11526). Ras85D (refers to the Drosophila gene encoding RAS), ras (gene encoding an IMP dehydrogenase) is referred to by its full name, “raspberry, ” to avoid confusion. Following the nomenclature recommended by Flybase, gene symbols are in lower-cased italics and protein symbols are in upper-case without italics. hyp (hyphen; designates the ave/hyp gene).
summary: The RAS/MAPK pathway is a cornerstone of the cell proliferation signaling apparatus. It has a notable involvement in cancer as mutations in the components of the pathway are associated with aberrant proliferation. Previous work has focused predominantly on post-translational regulation of RAS/MAPK signaling such that a large and intricate network of factors is now known to act on core pathway components. However, regulation at the pre-translational level has not been examined nearly as extensively and is comparatively poorly understood. In this study, we used an unbiased and global screening approach to survey the Drosophila genome—using Drosophila cultured cells—for novel regulators of this pathway. Surprisingly, a majority of our hits were associated to either transcription or mRNA splicing. We used a series of secondary screening assays to determine which part of the RAS/MAPK pathway these candidates target. We found that these factors were not equally distributed along the pathway, but rather converged predominantly on mapk mRNA expression and processing. Our findings raise the intriguing possibility that regulation of mapk transcript production is a key step for a diverse set of regulatory inputs, and may play an important part in RAS/MAPK signaling dynamics.
keywords: insulin-dependent signal transduction
  invertebrates
  functional genomics
  mechanisms of signal transduction
  animals
  animal models
  drosophila melanogaster
  model organisms
  mapk signaling cascades
  drosophila
  research and analysis methods
  erk signaling cascade
  gene expression
  insects
  arthropoda
  systems biology
  biochemistry
  rna
  signal transduction
  rna processing
  cell biology
  genetics
  biology and life sciences
  genomics
  molecular cell biology
  cell signaling
  organisms
  signaling cascades
title: A Functional Screen Reveals an Extensive Layer of Transcriptional and Splicing Control Underlying RAS/MAPK Signaling in Drosophila