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Phenotypic Profiling of the Human Genome Reveals Gene Products Involved in Plasma Membrane Targeting of SRC Kinases

Julia Ritzerfeld1, Steffen Remmele2, Tao Wang1, Koen Temmerman1, Britta Brügger1, Sabine Wegehingel1, Stella Tournaviti1, Jeroen R.P.M. Strating1, Felix T. Wieland1, Beate Neumann3, Jan Ellenberg3, Chris Lawerenz5, Jürgen Hesser2, Holger Erfle4, Rainer Pepperkok3, and Walter Nickel1*

*corresponding author ([email protected])

1Heidelberg University Biochemistry Center, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany 2Universitätsmedizin Mannheim, 68167 Mannheim, Germany 3European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany 4Bioquant-Zentrum, Heidelberg University, 69120 Heidelberg, Germany 5Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

Running title: Identification of Novel Factors Involved in SRC Targeting

Key words: SRC kinase; SH4 domain; YES1, Leishmania HASPB; Plasma membrane targeting; Intracellular trafficking; Endosomal recycling

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Summary

SRC proteins are non-receptor tyrosine kinases that play key roles in regulating signal transduction by a diverse set of cell surface receptors. They contain N- terminal SH4 domains that are modified by fatty acylation and are functioning as membrane anchors. Acylated SH4 domains in turn are both necessary and sufficient to mediate specific targeting of SRC kinases to the inner leaflet of plasma membranes. Acylation of most SRC kinases proceeds in two steps with co- translational N-terminal myristoylation being followed by palmitoylation of cysteine residues, a process that occurs at the cytoplasmic leaflet of Golgi membranes. Intracellular transport of SRC kinases from Golgi membranes to the inner leaflet of the plasma membrane depends on microdomains into which SRC kinases partition upon palmitoylation. In the current study, we established a live cell imaging screening system to identify gene products involved in plasma membrane targeting of SRC kinases. Based on siRNA arrays and a human model cell line expressing two kinds of SH4 reporter molecules, we conducted a genome-wide analysis of SH4- dependent protein targeting using an automated microscopy platform. We identified and validated 54 gene products whose down-regulation causes intracellular retention of SH4 reporter molecules. To detect and quantify this phenotype, we developed a software-based image analysis tool. Among the identified gene products we found factors involved in lipid metabolism, intracellular transport and cellular signalling processes. Furthermore, we identified proteins that are either associated with SRC kinases or are related to various known functions of SRC kinases such as other kinases and phosphatases potentially involved in SRC-mediated signal transduction. Finally, we identified gene products whose function is less defined or entirely unknown. Our findings provide a major resource for future studies unravelling the molecular mechanisms that underlie proper targeting of SRC kinases to the inner leaflet of plasma membranes.

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Introduction

The SRC protein family consists of non-receptor tyrosine kinases that play key roles in cellular signal transduction. They are involved in the regulation of fundamental cellular processes including cell growth, differentiation as well as migration and survival (Parsons and Parsons 2004). The general SRC kinase architecture consists of four domains, three of which are directly linked to the signal transduction pathways they are involved in. The SH3 domain mediates interactions with other signalling molecules, the SH2 domain is required for phosphotyrosine recognition and the SH1 domain contains the kinase activity (Boggon and Eck 2004). By contrast, the fourth domain (SH4) is solely responsible for membrane attachment and targeting to plasma membranes.

The molecular mechanism by which SRC kinases and other peripheral membrane proteins such as Leishmania hydrophilic acylated surface protein B (HASPB) are anchored in the inner leaflet of plasma membranes is based on post-translational lipid modifications within their N-terminal SH4 domains. Following removal of the N- terminal methionine residue SH4 proteins become myristoylated at the N-terminus via an amide linkage (Resh 1999; Resh 2004). The second acylation step involves the modification of at least one cysteine residue by palmitoylation resulting in a thioester linkage (Linder and Deschenes 2007). Thus, most SRC kinases carry two binding sites for membrane anchoring. This feature has been generalized as the two signal hypothesis that was originally developed for mammalian Ras proteins (Hancock et al. 1990). As a variation of this principle, instead of palmitoylation, a second membrane binding site can be formed by a cluster of basic amino acids as is the case for the prototype member of the family, SRC (Smotrys and Linder 2004). While the enzymes involved in N-myristoylation of SH4 domains have been known for many years (Resh 1999), the enzymology of protein palmitoylation has been revealed only recently with so-called DHHC (Asp-His-His-Cys) proteins acting as S- acyltransferases (Mitchell et al. 2006; Linder and Deschenes 2007).

N-terminal SH4 domains are sufficient for intracellular targeting of for example GFP fusion proteins to the inner leaflet of plasma membranes (McCabe and Berthiaume 1999; Denny et al. 2000; McCabe and Berthiaume 2001; Stegmayer et al. 2005; Tournaviti et al. 2007; Tournaviti et al. 2009). Myristoylation of SH4 domains occurs cotranslationally and results in a transient insertion into intracellular membranes in a perinuclear region where they colocalize with Golgi markers (Wolven et al. 1997; Denny et al. 2000; Stegmayer et al. 2005; Tournaviti et al. 2007). Recently, using semisynthetic substrates corresponding to various kinds of palmitoylated proteins, it

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has been suggested that palmitoylation of all cellular target proteins occurs specifically at the Golgi (Rocks et al. 2010). In this way, palmitoylation appears to be controlled spatially rather than being controlled by enzymatic specificity of acyl transferases, an observation that is consistent with the observed functional redundancy of DHHC acyl transferases that catalyze protein palmitoylation (Hou et al. 2009).

Interestingly, palmitoylation of SH4 domains is required for SRC kinases to properly partition into membrane microdomains (Brown and London 1998; Webb et al. 2000; Edidin 2003; Smotrys and Linder 2004; Linder and Deschenes 2007). This, in turn, causes retention of SRC kinases at the level of Golgi membranes, i.e. forward transport to the inner leaflet of the plasma membrane is blocked under these experimental conditions. These observations suggest that membrane microdomains serve as sorting and transport platforms required for proper targeting of SH4 proteins. Besides these insights, however, our knowledge remains poor with regard to mechanistic details of SH4-domain-dependent protein targeting to the inner leaflet of plasma membranes.

In the current study we have conducted an unbiased RNAi screening approach analyzing the entire human genome for factors involved in proper targeting of SH4 proteins. We have established an experimental model system based on two different SH4 domains that are fused to GFP and mCherry, respectively, and are expressed simultaneously in HeLa cells in a doxycycline-dependent manner. Under control conditions both of these SH4 fusion proteins primarily localize to plasma membranes with only a minor fraction being detected intracellularly. For both primary screening and validation experiments cells were grown on siRNA arrays (Erfle et al. 2004; Neumann et al. 2006; Simpson et al. 2007; Neumann et al. 2010). A software tool was developed to detect and quantify perinuclear accumulation of one or both SH4 reporter molecules. Hits identified during primary screening were validated using independent siRNAs. All data on experimental conditions and results of the screening procedure were stored in a web-based database. The final list of validated gene products whose down-regulation causes intracellular retention of SH4 reporter molecules consists of 54 gene products. It contains proteins with well-defined functions in lipid metabolism, intracellular transport and cellular signalling processes as well as other functional classes. Additionally, a number of proteins were identified whose function is less defined or entirely unknown. Thus, the current study provides a major resource for studying the mechanistic details of microdomain-dependent Golgi to plasma membrane trafficking of SRC kinases.

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Results

An experimental model system to study SH4-domain-dependent protein targeting to plasma membranes

To study intracellular SH4-domain-dependent transport to the plasma membrane using a genome-wide RNAi screening approach, we engineered a human model cell line expressing two distinct SH4-domain-containing fusion proteins. These contained the N-terminal 18 amino acids of either Leishmania HASPB (Denny et al. 2000; Stegmayer et al. 2005) or of the mammalian SRC kinase YES1 (Tournaviti et al. 2009) fused to GFP (SH4-HASPB-GFP) and mCherry (SH4-YES1-mCherry), respectively. Both fusion proteins are substrates for N-terminal myristoylation and subsequent palmitoylation (cysteine 5 in HASPB; cysteine 3 in YES1, Fig. S1, panel A). Simultaneous expression of both SH4-HASPB-GFP and SH4-YES1-mCherry in stably transducted HeLa cells was controlled by a doxycycline-sensitive transactivator and, therefore, could be induced by doxycycline as demonstrated by flow cytometry (Fig. S1, panel B). Upon expression, employing confocal microscopy, both reporter proteins were found to localize at the plasma membrane establishing that N- terminal SH4 domains are sufficient for proper targeting (Fig. S2, panel C; (McCabe and Berthiaume 1999; Denny et al. 2000; McCabe and Berthiaume 2001; Stegmayer et al. 2005)).

Palmitoylation-dependent transport to the plasma membrane of SH4 reporter proteins

For both SH4-HASPB-GFP and SH4-YES1-mCherry, delivery to the plasma membrane depends on the acylation state of the respective SH4 domain. Substitution of the myristoylated glycine residue in SH4-HASPB not only prevents myristoylation, but also blocks palmitoylation (McCabe and Berthiaume 1999; Denny et al. 2000; Stegmayer et al. 2005; Tournaviti et al. 2009), i.e. N-terminal myristoylation is a prerequisite for palmitoylation to occur. A lack of acylation resulting from a deletion of the myristoylation site in turn renders both SH4-HASPB and SH4-YES1-containing fluorescent reporter proteins incapable of interacting with cellular membranes, resulting in cytoplasmic localization (Fig. 1A, subpanels b and e). By contrast, disruption of the palmitoylation site in HASPB does not affect myristoylation (McCabe and Berthiaume 1999; Denny et al. 2000; Stegmayer et al. 2005) and results in intracellular retention at perinuclear membranes (Fig. 1A, subpanel c). This effect is more pronounced in case of SH4-HASPB-GFP but can also be observed for SH4-

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YES1-GFP (Fig. 1A, subpanel f). Alternatively, palmitoylation can also be blocked with a non-metabolizable palmitate analogue, 2-bromo-palmitate (2-BP, (Webb et al. 2000; Resh 2006)) that inhibits transport of SH4 fusion proteins to the plasma membrane (Fig. 1, panel B). Again, pharmacological inhibition of palmitoylation caused a more pronounced transport block of SH4-HASPB-GFP when compared to SH4-YES1-mCherry (Fig. 1, panel B). In the context of the current study, palmitoylation-deficient mutant forms of SH4 reporter proteins as well as pharmacological inhibition of SH4 palmitoylation were used as positive controls to implement the high content screening system as it was designed to detect and quantify intracellular retention of SH4 fusion proteins.

A software-based image analysis tool to detect and quantify intracellular retention of SRC kinases

Microscopy-based high-content screening approaches result in extremely large sets of image-based data, requiring the development of tools to achieve an efficient, unbiased and quantitative analysis of phenotypes of interest (Boland et al. 1998; Conrad et al. 2004; Carpenter et al. 2006; Neumann et al. 2006; Glory and Murphy 2007; Harder et al. 2008; Wang et al. 2008a; Walter et al. 2010). Based on general tools such as cell segmentation techniques (Elowitz et al. 2002; Megason and Fraser 2007; Wang et al. 2008b), we developed a software-based image analysis module specifically tailored to detect and quantify intracellular retention of SH4 fusion proteins. This software tool identifies individual cells, detects different cellular compartments and classifies cells according to intensity distributions between such compartments (Fig. S2). This classification can be conducted for different fluorescence channels simultaneously, i.e. the two different fusion proteins used in this study could be analyzed independently. Furthermore, the software module was designed in a way that a potential low quality of image-based screening data such as low resolution and out-of-focus images, local contaminations, areas of different cell densities as well as varying signal intensities did not result in wrong classification of phenotypes.

A crucial step for automated image analysis was the correct identification and segmentation of individual cells since this step provides the basis for intensity feature extractions from different cellular areas and, therefore, has a direct impact on both quality and reliability of the results. Cell identification was based on the detection of stained cell nuclei by an adaptive thresholding approach. Due to the application of a stepwise convergence of intensities to the intensity of cell nuclei,

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this approach is invariant to different nuclear intensities between different images and therefore more reliable than fixed thresholding approaches. Using cell nuclei as a seed point, the shape of individual cells was identified by a classifier-enhanced region-growing approach. Cell boundaries were determined by two criteria: i.) a large GFP intensity difference between inner and outer pixels and ii.) a lower GFP intensity of the outer pixels compared to a local brightness threshold for a given cell. These criteria were not only sufficient to determine the shape of cells independently of the distribution of reporter intensities inside the cell, but also provided reliable data when fluorescence intensities varied between cells. Following determination of cell shape, cells characterized by abnormal size and shape were classified as invalid and excluded from further analysis. The fluorescence distribution of the remaining cells was used to classify localization of the reporter proteins within one of three possible intracellular compartments, i.) the nucleus, ii.) the cytosol (including all membrane-compartments that are present in the cytoplasm such as the Golgi) and iii.) the plasma membrane (Fig. S2A). Intensity features from the complete cell area as well as the three cellular compartments were extracted and used for classification of individual cells (Fig. S2B). Based on these criteria, perinuclear retention at for example Golgi membranes should result in an increased cytoplasmic intensity compared to nuclear and membrane-associated intensities. A detailed description of the software-based image analysis tool used in this study is given in 'Materials and Methods'.

Based on the use of acylation-deficient variant forms of SH4 fusion proteins (Fig. 1A) and pharmacological inhibition of palmitoylation using 2-BP (Fig. 1B), intracellular accumulation of one or both reporter proteins and, therefore, redistribution of fluorescence intensity from the plasma membrane to intracellular compartments in individual cells was used to evaluate the image analysis software described above. Indeed, the phenotype of highest interest, i.e. perinuclear retention, could be detected in about 80% of cells expressing the HASPB palmitoylation mutant (SH4- HASPB-Δpalm-GFP; Fig. 1C, subpanel a). The software tool was also capable of identifying gradual effects evoked by treatment of cells expressing the wild-type form of SH4-HASPB-GFP with the palmitoylation inhibitor 2-BP. Here, a range between 60% and 85% of cells with significant perinuclear retention of SH4-HASPB- GFP was observed depending on the inhibitor concentration applied to the cells (Fig. 1C, subpanel b).

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Automated high-content screening to identify gene products involved in SH4- domain-dependent targeting to plasma membranes

To identify proteins involved in SH4-domain-dependent transport to the plasma membrane, we used siRNA arrays covering all protein-coding genes known in the human genome. Each of the more than 21000 genes was targeted with at least two independent siRNAs. As described previously (Erfle et al. 2004; Neumann et al. 2006; Erfle et al. 2007; Simpson et al. 2007; Neumann et al. 2010), siRNAs were immobilized on LabTek imaging chambers in 384-spot arrays and used for reverse transfection of a stable HeLa cell line stably transduced with SH4-HASPB-GFP and SH4-YES1-mCherry (Fig. S1). 36 hours after transfection, expression of SH4 fusion proteins was induced by doxycycline followed by live-cell imaging 48 hours post- transfection (Fig. S3). Various control siRNAs were tested such as a scrambled siRNA, a siRNA targeting GFP to down-regulate SH4-HASPB-GFP as well as a siRNA to down-regulate INCENP, an inner centromere protein whose absence is known to cause mitotic defects and the formation of multinucleated cells (Neumann et al. 2010). Indeed, reverse transfection of a scrambled siRNA did not cause any pronounced effects on cellular morphology and SH4 fusion protein localization (Fig. S4, panels A-C). By contrast, a siRNA directed against GFP resulted in efficient silencing of the SH4-HASPB-GFP fusion protein without any detectable effect on SH4-YES1-mCherry (Fig. S4, panels D-F). Finally, as expected, siRNA-mediated down-regulation of INCENP resulted in the appearance of enlarged and multinucleated cells (Fig. S4, panels E-I). Thus, using the high content screening platform described, the expected phenotypes of control siRNAs could be detected in a reliable manner.

Primary screening and validation of candidate gene products

For high content screening purposes, acquisition of experimental data was followed by automated image analysis using a software-based image analysis tool. This analysis was used to determine scores as distance to the median of each 384-spot siRNA array expressed in standard deviations (Fig. S3). To analyze the robustness of the system, the scores of 2286 negative controls (scrambled siRNA) contained in the siRNA library were analyzed separately for the two fusion proteins, SH4-HASPB-GFP and SH4-YES1-mCherry. In case of SH4-HASPB-GFP (Fig. 2, panels A and E), about 97% of the negative controls did not return scores above a threshold of 2.5. In case of SH4-YES1-Cherry (Fig. 2, panels B and F), 98% of the negative controls were below a threshold of 3.5. Based on these data, scores of 2.5 for SH4-HASPB-GFP and 3.5

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for YES1-mCherry in both replicates in any of the classes of phenotypes defined above were chosen as suitable thresholds for initial identification of potential phenotypes. This procedure was complemented by a manual inspection of images and resulted in the identification of 286 gene products in primary screening with a potential role in SH4-domain-dependent protein targeting (Table S1).

As a positive control for intracellular transport processes, the library contained a siRNA directed against the coatomer subunit COPB1 (Rothman 1994; Rothman and Wieland 1996; Simpson et al. 2007), i.e. each 384-spot siRNA array contained up to 4 positive controls. Interestingly, down-regulation of COPB1 caused strong intracellular retention of SH4-HASPB-GFP (Fig. 2, panels C and G), however, only a mild effect was observed for SH4-YES1-mCherry (Fig. 2, panels D and H). Of the 898 individual experiments using a siRNA directed against COPB1, 86% showed a score above the threshold defined for SH4-HASPB-GFP. By contrast, only 14% caused a detectable intracellular retention of SH4-YES1-mCherry. Overall, these results indicate that the experimental system described in this study is characterized by a high robustness and sensitivity and thus generates well-reproducible data.

Validation and classification of gene products identified during primary screening

Candidate gene products identified during primary screening were validated using two additional siRNAs targeting different sequence areas of the respective mRNA. This analysis was conducted in triplicates using siRNA-coated 96-well plates (Erfle et al. 2008). Again, reverse transfection was achieved by cultivating cells on siRNA- coated wells for 36 hours. Expression of SH4 fusion proteins was induced by doxycycline for 12 hours. 48 hours post-transfection, images were acquired and analyzed using the software-based image analysis tool. Scores were calculated based on 15 negative control experiments on each plate and thresholds were adapted accordingly. In this set of experiments, down-regulation of 54 target genes resulted in a score above 2 in at least two out of three replicates (Table 1).

Validated gene products were classified with regard to function as well as subcellular localization and membrane association (for detailed information please visit https://ichip.bioquant.uni-heidelberg.de as indicated in 'Materials and Methods'). The majority of gene products whose RNAi-mediated down-regulation was found to affect SH4-dependent targeting were membrane proteins. In addition, besides soluble cytoplasmic proteins, a small fraction of gene products were secretory proteins. As summarized in Table 1 and Table S2, we found factors known to be

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involved in for example protein transport, lipid homeostasis and protein modifications. Furthermore, a number of cell surface receptors and extracellular components were identified that may affect SH4-domain-dependent trafficking by various kinds of signalling processes.

A role of lipid homeostasis in SH4-dependent protein transport

SH4-domain-dependent trafficking was shown to depend on cholesterol-dependent membrane microdomains (Brown and London 1998; Webb et al. 2000; Edidin 2003; Smotrys and Linder 2004; Linder and Deschenes 2007). Consistent with that we retrieved genes whose products are involved in the biosynthesis of so-called 'raft lipids' or in general lipid homeostasis. A prominent example turned out to be mevalonate-diphospho-dehydrogenase (MVD; (Toth and Huwyler 1996)), an enzyme that decarboxylates mevalonate pyrophosphate and produces isopentenyl pyrophosphate (activated isoprene), a critical intermediate in the biosynthesis of cholesterol. As shown in Fig. 3A (subpanels d and h), siRNA-mediated down- regulation of MVD caused intracellular retention of both SH4-HASPB-GFP and SH4- YES1-mCherry. Similarly, we identified sphingomyelin phosphodiesterase (acid-like 3B; SMPDL3B; (Marchesini and Hannun 2004)) that catalyzes hydrolysis of sphingomyelin to phosphatidylcholine and ceramide. Again, its down-regulation inhibited transport of both SH4 fusion proteins (Fig. 3A, panels c and g). Finally, we discovered acyl-coenzyme-A dehydrogenase (ACADVL) as a gene product whose down-regulation affects SH4-dependent trafficking. ACADVL is a mitochondrial enzyme that catalyzes the first step in mitochondrial β-oxidation and is specific for very-long-chain fatty acids. As shown in Fig. 3 (panels b and f), its down-regulation resulted in perinuclear accumulation of both SH4 fusion proteins. Thus, we have identified three enzymes involved in lipid metabolism two of which directly participate in the biosynthesis of raft lipids such as cholesterol (Simons and Ikonen 1997; Simons and Toomre 2000; Simons and Vaz 2004) and ceramide (Bollinger et al. 2005). Additionally, depletion of ACADVL may affect SH4-dependent protein targeting by an indirect mechanism disturbing lipid homeostasis.

To further validate as to whether homeostasis of cholesterol as a raft lipid is indeed required for correct targeting of SH4-proteins to the plasma membrane, we tested whether down-regulation of MVD under the experimental conditions used indeed causes cellular cholesterol levels to drop. Cholesterol levels were determined by nano-electrospray ionisation mass spectrometry using phosphatidylcholine (PC) as a bulk lipid to normalize data. Relative to PC, upon treatment of cells with siRNAs

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targeted against MVD, we found a reduction of cellular cholesterol by 30% (Fig. S5, panel A). Under these conditions, MVD protein levels were reduced to about 50% (Fig. S5, panel C) and MVD mRNA levels were reduced by more than 80% (Fig. S5, panel B). To further challenge the hypothesis that cholesterol homeostasis is essential for targeting of SH4-proteins to the plasma membrane, we treated cells with methyl-β- cyclodextrin (MβCD) to deplete cellular cholesterol. As indicated in Fig. 3B, treatment with 5 to 10 mM MβCD resulted in pronounced intracellular retention of SH4-HASPB- GFP as well as SH4-YES1-mCherry (Fig. 3B, subpanels e-f, i-j), concomitant with a reduction of cellular cholesterol by 50% relative to PC (Fig. S5, panel A). These findings are consistent with other studies in which reduction of cholesterol levels by 30-50% was found to have a significant impact on cholesterol-dependent processes such as shedding of the type XIII collagen ectodomain (Vaisanen et al. 2006). To test whether stress potentially exerted by MβCD causes a pleiotropic effect on SH4- dependent protein transport to the plasma membrane, we treated cells with ouabain, an unrelated inhibitor that blocks the activity of the Na+/K+ ATPase. Similar to MβCD, this treatment caused a mild effect on overall cell morphology, however, it did not result in perinuclear accumulation of SH4-HASPB-GFP or SH4-YES1-mCherry (Fig. 3B, subpanels c and d). To further analyze whether intracellular retention was indeed a direct result of cholesterol depletion, MβCD-treated cells were rescued by replenishment with exogenous cholesterol. This treatment resulted in a pronounced re-localization of both SH4-HASPB-GFP and SH4-YES1-mCherry to the plasma membrane (Fig. 3B, subpanels g-h and k-l).

Our combined findings establish that interference with cellular cholesterol levels results in pronounced intracellular retention of SH4-proteins and further corroborate the role of cholesterol-dependent microdomains in SH4-domain-dependent protein transport to plasma membranes.

Analysis of protein kinase C alpha as a component of SH4-domain-dependent protein transport

Since phosphorylation of SH4-domain-containing proteins such as SRC kinases has been implicated in regulation of endosomal recycling (Sandilands et al. 2004; Sandilands and Frame 2008; Tournaviti et al. 2009), another interesting result of this study was the identification of members of the protein kinase C family of serine/threonine kinases. As shown in Fig. 4A, concomitant with reduction of PRKCA protein levels to around 20% compared to a treatment with a scrambled siRNA (Fig. S5B), siRNA-mediated down-regulation of PRKCA caused perinuclear accumulation

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of SH4 fusion proteins. This effect was not dependent on the fluorescent reporter protein fused to the respective SH4-domain, as knockdown of PRKCA in stable cell lines expressing either SH4-HASPB-mCherry (Fig. S6A, subpanel c) or SH4-YES1-GFP (Fig. S6, subpanel f) also resulted in an intracellular retention. To test whether PKC activity is required for plasma-membrane targeting of SH4-proteins, stable HeLa cells were treated with the protein kinase C inhibitor GÖ 6983 resulting in pronounced intracellular retention of both SH4-HASPB-GFP (Fig. 4C, subpanel c) an SH4-YES1-GFP (Fig. 4C, subpanel d).

These findings indicate that protein phosphorylation by PKC plays an important role in SH4-domain-dependent protein transport, however, it remains to be clarified whether PRKCA directly targets SH4 domains or whether other substrates of this kinase are affecting SH4-dependent trafficking.

Analysis of coatomer as a component of SH4-domain-dependent protein targeting

As mentioned above, COPB1 (β-COP) is a subunit of the coatomer complex that was identified and validated to be required for proper targeting of SH4 fusion proteins (Table 1 and Table S2, Fig. 2). Since coatomer is a hetero-heptameric complex we further evaluated the COPB1 phenotype based on the assumption that coatomer is required as a protein complex, i.e. coatomer subunits other than COPB1 should give a similar phenotype when down-regulated by RNA interference. In a first step we extended our studies to ARCN1 (δ-COP) (Fig. 5A) and assessed down-regulation of both COPB1 and ARCN1 by quantitative western blotting (Fig. 5B). These studies established efficient down-regulation at the protein level of each subunit by the respective siRNA to around 40% or even below 20%, respectively (Fig. S5E). As can be expected for a stoichiometric protein complex, down-regulation of COPB1 also caused a loss of ARCN1 and vice versa. As shown in Fig. 5A, down-regulation of ARCN1 resulted in a pronounced intracellular retention of SH4-HASPB-GFP, while targeting of SH4-YES1-mCherry was only mildly affected. These differential effects were not caused by the different fluorescent reporter proteins fused to the SH4 domains of HASPB and YES1, since stable HeLa cells expressing SH4-HASPB-mCherry (Fig. S6A, subpanel b) also showed strong intracellular retention of the SH4 fusion protein upon downregulation of COPB1. Similarly, knockdown of COPB1 in stable HeLa cells expressing SH4-YES1-GFP resulted in a mild retention of the SH4 fusion protein (Fig. S6A, subpanel e). These studies were further extended towards COPA (α-COP) and COPB2 (β'-COP), two additional subunits of coatomer. Again, following transfection of the corresponding siRNAs, strong intracellular retention was observed

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for SH4-HASPB-GFP (Fig. S6B, subpanels a, d) but only a mild effect on targeting of SH4-YES1-mCherry (Fig. S6B, subpanels b, e). To address whether intracellular retention evoked by knockdown of coatomer subunits was indeed a result of depletion of the coatomer protein complex, we microinjected stable HeLa cells expressing SH4-HASPB-mCherry with recombinant coatomer before transfection with siRNAs targeted against COPB1. Indeed, targeting of SH4 fusion proteins was unaffected in cells that were microinjected with coatomer demonstrating a role for coatomer in proper targeting of SH4-HASPB-GFP, however, it does not appear to play an essential role in targeting of SH4-YES1-mCherry. (Fig. 5C).

Coatomer and PRKCA as components in plasma membrane transport of endogenous YES1 and other SH4 proteins

To address whether our experimental system is capable of identifying components required for transport of endogenous SH4 proteins, we analyzed the localization of endogenous YES1 after knockdown of factors identified and validated in this study. Transfection of siRNAs directed against COPB1 (Fig. 6A, subpanels d-f) and PRKCA (Fig. 6A, subpanels g-i) not only resulted in an intracellular retention of SH4-HASPB- mCherry, but also affected plasma membrane targeting of endogenous YES1 visualized by immunolabeling with specific antibodies. We further analyzed whether the identified components required for plasma membrane targeting of HASPB and YES1 also affected transport of other SH4-domain-containing proteins. Among those were other members of the SRC family kinases (SFKs) such as SRC (non- palmitoylated), LCK and FYN (both dually palmitoylated) whose SH4 domains were expressed as GFP fusion proteins in stable HeLa cells (Shenoy-Scaria et al. 1993; Koegl et al. 1994; Resh 1994). Upon downregulation of COPB1 and PRKCA, we observed differential effects on targeting of the different SH4 fusion proteins. RNAi- mediated downregulation of COPB1 (Fig. 6B, subpanels d-f) resulted in an enhanced intracellular retention of SH4-LCK-GFP and SH4-SRC-GFP, however, it did not influence plasma membrane targeting of SH4-FYN-GFP. Knockdown of PRKCA (Fig. 6B, subpanels g-i) caused strong intracellular accumulation of SH4-LCK-GFP and also affected the localization of SH4-SRC-GFP. Again, transport of SH4-FYN-GFP was not affected. These findings support previous data showing that different SH4- domain-containing proteins localize to different subcellular membranes and traffic along different routes, often dependent on the acylation pattern present in the respective SH4 domain (Shenoy-Scaria et al. 1994; Sandilands et al. 2004; Kasahara et al. 2007). The finding that both coatomer and PRKCA exert effects on SH4-LCK- GFP and SH4-SRC-GFP, but do not affect transport of SH4-FYN-GFP, which is directly

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targeted to the plasma membrane without passing through the Golgi system, may indicate that both factors play a role in SH4-dependent transport at the level of the Golgi or the endosomal system.

Besides the examples given above and as documented in table 1 and table S2, we were also able to identify gene products with so far unknown functions. Additionally, gene products were identified that are likely to have a rather indirect impact on SH4- domain-dependent targeting such as factors regulating gene expression. This observation is also consistent with a relatively large number of factors that localize to the nucleus.

Discussion

SRC kinases and other peripheral membrane proteins contain acylated SH4 domains that mediate both association with membranes and proper targeting to specific subcellular membranes. While the physical association of SH4 domains with membranes is understood in great detail, their role in intracellular sorting and plasma membrane targeting as well as the function of membrane microdomains in this process is poorly understood. The aim of the current study was to conduct a global analysis of the human genome to reveal gene products involved in SH4- domain-dependent plasma membrane targeting of acylated proteins, such as SRC kinases. Stable cell lines were engineered that express two different kinds of SH4 fusion proteins in a doxycycline-dependent manner. An experimental system was developed to detect and quantify intracellular retention of SH4 proteins, which was combined with siRNA arrays to individually down-regulate every single gene known in the human genome. Live-cell imaging was conducted employing an automated wide-field microscopy platform. Using a software-based image analysis tool, intracellular retention of SH4 fusion proteins could be detected and quantified for each individual experimental condition of down-regulation of a specific gene product. The two different SH4 fusion proteins were analyzed simultaneously in order to identify potential differences in SH4-dependent trafficking depending on the individual properties of a given SH4 domain.

To characterize the experimental system described we reasoned that general components of intracellular transport might be required for targeting of SH4 fusion

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proteins. More specifically, since all palmitoylated proteins have been proposed to contact the Golgi (Rocks et al. 2010), we hypothesized that the heterooligomeric coatomer complex may play a role in SH4-dependent trafficking. Indeed, siRNA- mediated down-regulation of the COPB1 gene consistently resulted in perinuclear retention of SH4 fusion proteins. We further concluded that down-regulation of coatomer subunits that exist in just one isoform (e.g. COPA, COPB1, COPB2 and ARCN1 (δ-COP); (Wegmann et al. 2004)) should result in a similar phenotype, which was indeed the case. In addition, we could show that downregulation of single coatomer subunits affected protein levels of other subunits as well and, hence, most likely results in a destabilization of the complete coatomer complex. Moreover, RNAi-mediated down-regulation of endogenous coatomer subunits did not affect SH4-dependent trafficking when cells were microinjected with recombinant coatomer. Therefore, using our experimental system, we were able to identify COPB1 as a component of a multi-protein complex, which plays an important role in SH4- dependent protein transport.

Another protein whose down-regulation caused a pronounced effect on SH4- dependent protein transport was a protein kinase, PRKCA. Moreover, using a pharmacological inhibitor of protein kinase C, we could demonstrate a requirement for protein kinase C activity in correct targeting of SH4 proteins to the plasma membrane. Whether SH4 domains are direct targets for phosphorylation by PRKCA or whether other target proteins play direct roles in SH4-domain-dependent protein transport remains a subject for further investigation.

Regarding further requirements of SH4-dependent trafficking, a major result of this study was the identification of enzymes that play key roles in lipid biosynthesis and homeostasis. Among those was a key factor of cholesterol biosynthesis, MVD, the enzyme that generates activated isoprene. Downregulation of MVD indeed caused reduced cellular cholesterol levels that were correlated with intracellular accumulation of SH4 proteins. Furthermore, pharmacological depletion of cellular cholesterol also inhibited transport of SH4 proteins, an effect that could be reversed upon replenishment with exogenous cholesterol. Taken together, our findings corroborate the role of cholesterol-dependent membrane microdomains in SH4 trafficking (McCabe and Berthiaume 1999; Webb et al. 2000; McCabe and Berthiaume 2001; Tournaviti et al. 2009). They are further consistent with other large scale RNAi approaches suggesting that RNAi-mediated down-regulation of MVD affects cholesterol-dependent processes such as Dengue virus replication (Rothwell et al. 2009).

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Another interesting observation of this study were differences between the two SH4 domain used as targeting motifs. Compared to the YES1 SH4 domain, down- regulation of coatomer subunits had a much more pronounced inhibitory effect on plasma membrane targeting of a fusion protein containing the SH4 domain of HASPB indicating differential requirements depending on different kinds of SH4 domains. Consistently, factors involved in transport of those two SH4 domains were shown to have differential effects on fusion proteins containing SH4 domains of other SRC kinases, such as LCK, SRC and FYN as well as on endogenous YES1. Differential transport requirements are also evident from the complete list of validated gene products shown in Table 1 and Table S2. Of the 54 gene products shown to play a role in SH4-dependent trafficking, 13 were found to primarily function in HASPB targeting, 18 appeared to be specific for YES1 targeting and 23 were found to be required for both transport processes. These observations are generally consistent with earlier findings from other groups suggesting the existence of multiple pathways of SH4 trafficking (Sato et al. 2009). Furthermore, our data show that the experimental model system is not only suited to identify general components involved in SH4-dependent transport processes but also reveals differential requirements when different SH4 domains are directly compared. These findings also directly exclude potential pleiotropic effects and emphasize the capability of the experimental system to reveal differences between various kinds of SH4-dependent trafficking.

The 54 gene products validated in this study to play a role in targeting of SH4- domain-dependent protein targeting were classified into 8 groups according to experimentally shown or annotated functions (Table 1 and Table S2). As expected, we found a number of membrane receptors as well as kinases and phosphatases whose down-regulation affects SH4-dependent trafficking. Besides gene products involved in the formation or the removal of other post-translational modifications as well as a relatively large group of gene products involved in the regulation of gene expression, we also revealed 7 gene products whose functions are entirely unknown.

It is clear that the current screening approach cannot be considered as compre- hensive since obviously a number of gene products that are known to play a role in SH4-dependent targeting were not returned as hits. For example we could not identify a single DHHC protein, the enzymes that mediate palmitoylation of SH4 proteins (Smotrys et al. 2005; Mitchell et al. 2006). In the light of recent findings, it is clear that this phenomenon is due to functional redundancy within the family of DHHC proteins (Hou et al. 2009; Rocks et al. 2010), making it impossible to evoke a phenotype by down-regulation of individual members of the DHHC family. In this

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sense, the siRNA screening effort presented in this study cannot be considered as an attempt to identify all gene products that play a role in SH4-dependent protein targeting but rather provides a major resource of a subgroup of proteins with non- redundant functions in this process.

Acknowledgements

We thank Timo Sachsenheimer and Iris Leibrecht for technical support. This work was supported by the Peter and Traudl Engelhorn foundation (JR), the DFG collaborative research center TRR83 (WN, BB, FW) as well as DFG cluster of excellence CellNetworks (WN, RP, JE, BB, FW).

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Materials and methods

Generation of stable HeLa cell lines expressing acylated SH4 fusion proteins

Constructs encoding acylated fluorescent reporter proteins (SH4-YES1-mCherry, SH4-HASPB-GFP (see Suppl. 1), SH4-YES1-GFP, SH4-HASPB-mCherry, SH4-LCK-GFP, SH4-SRC-GFP, SH4-FYN-GFP) were cloned into the retroviral expression vector pRevTRE2. Following retroviral transduction of HeLa cells, constructs were stably inserted into the target genome followed by the isolation of cell lines using fluorescence activated cell sorting as described previously (Engling et al. 2002). Doxycycline-dependent expression of the respective SH4 fusion proteins was confirmed by analytical flow cytometry.

Analysis of the subcellular localization of SH4 fusion proteins using live-cell confocal and wide-field fluorescence microscopy

HeLa cells were cultivated on 8-well LabTek imaging chambers (Nunc) and induced to express fluorescent SH4 fusion proteins by cultivation in the presence of 1 µg/ml doxycycline for 12 to 24 hours. To inhibit protein palmitoylation, cells were cultivated in the presence of 2-bromopalmitate (2-bromohexadecanoic acid; Sigma- Aldrich). Cells were cultivated in the presence of the protein kinase C inhibitor GÖ 6983 (Sigma-Aldrich) for 16 hours. 30 minutes prior to imaging, the medium was replaced by prewarmed CO2-independent medium (Invitrogen) and cells were analyzed on a LSM 510 confocal microscope (Zeiss), an Axiovert fluorescence wide- field microscope (Zeiss) or a Scan^R screening microscope (Olympus).

Genome-wide primary screening for factors involved in subcellular localization of acylated SH4 fusion proteins

Genome-wide primary screening was conducted by reverse transfection of cells with a siRNA library (Ambion) consisting of ∼ 52.000 siRNAs targeting all genes known in the human genome (ensembl version 27) with at least two siRNAs per gene. This siRNA library was arranged in 384-spot siRNA arrays (Erfle et al. 2004; Neumann et al. 2006; Erfle et al. 2007; Simpson et al. 2007; Neumann et al. 2010). Per array, 120.000 cells were seeded and, 36 hours post-transfection, expression of SH4 fusion protein was induced by the incubation of cells for 12 h in the presence of 1

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µg/ml doxycycline. Growth medium was replaced by prewarmed CO2-independent medium (without phenol-red, Invitrogen) containing 0.2 µg/ml Hoechst 33342 (Sigma-Aldrich) for labelling of cell nuclei. 48 hours post-transfection, siRNA arrays were loaded onto an Olympus Scan^R screening microscope with a 37°C incubation chamber and images from the GFP, Cherry and Hoechst channel were acquired by automated live-cell fluorescence microscopy at 10x magnification. Images were analyzed using the image analysis tool described below.

Validation of gene products identified during primary screening

Validation screening was conducted by reverse transfection of a newly designed siRNA library consisting of 776 silencer select siRNAs (Ambion) targeting 311 human genes (ensembl version 53). Validation was conducted on siRNA-coated 96-well plates (Erfle et al. 2008) in four replicates. 4.000 cells were seeded per well using a FlexDrop system (Perkin Elmer). 36 hours post-transfection, SH4 fusion protein expression was induced by cultivation in the presence of 1 µg/ml doxycycline for 12 hours. Growth medium was replaced by prewarmed CO2-independent medium (without phenol-red, Invitrogen) containing 0.2 µg/ml Hoechst 33342 (Sigma- Aldrich) to label cell nuclei. 48 hours post-transfection, siRNA-coated 96-well plates were loaded onto an Olympus Scan^R screening microscope with a 37°C incubation chamber and two images per well were acquired for each channel by automated live- cell fluorescence microscopy at 10x magnification. Images were analyzed using the image analysis tool described below.

A software-based image analysis tool to detect and quantify intracellular retention of SH4 fusion proteins

Based on general techniques to analyze microscopy-based imaging data such as cell segmentation (Elowitz et al. 2002; Megason and Fraser 2007; Wang et al. 2008b), an image analysis tool was developed to automatically detect and quantify intracellular retention of SH4 fusion proteins as a desired phenotype. In order to achieve optimal cell detection, cell nuclei were segmented by Hoechst staining in a first step as a prerequisite for cell segmentation (Rosenfeld et al. 2005; Gordon et al. 2007). Since intensity values of nuclei in any given Hoechst image were within a certain range, thresholding techniques could be applied (Wu et al. 2000). However, due to varying nuclear intensities within the complete screening data set, an adaptive thresholding technique was required for reliable determination of cell nuclei. Starting with a high

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value, the threshold was gradually decreased until the size of segmented nuclei was consistent with the assumed size. In an additional step, segmented nuclei were post- processed removing local contaminations and other artefacts in the region of the nucleus.

Segmented cell nuclei were the basis of a classifier-enhanced region growing method used to segment complete cells. This method requires a seed point provided by cell nuclei and a criterion to detect cell boundaries, which was achieved by a rule- based classifier. The classifier uses both local cell brightness in the area of the nucleus and a gradient of fluorescence intensities across the whole area of the cell. The cell boundary is recognized when the brightness of an inspected pixel is below the minimal brightness in the area of the nucleus and the gradient magnitude is above a certain threshold. This approach is suitable to segment the whole cell area and allows for the detection of changes of gradient magnitudes within the cytoplasm, which is the case when the fluorescent reporter protein accumulates in a perinuclear region, a distribution indicative for localization in Golgi membranes or recycling endosomes. An important feature of this method is its ability to segment cells independently of local brightness. Due to the choice of nuclei as seed points and the methodology to detect cell boundaries, it was possible to detect individual cells with similar fluorescence intensities even when multiple cells formed direct plasma membrane contacts. Additionally, cell clusters with overlapping cell boundaries were detected by the proximity of their nuclei and were excluded from further analysis.

Cell segmentation was finally used to define three cellular regions, the nucleus, the cytoplasm and the cell boundary. To detect the cell boundary, the difference between the original and an eroded cell segmentation result was determined. Following the determination of the nucleus and the cell boundary, the remaining cellular area was defined as the interior of the cell along with all organelles such as the Golgi that are embedded in the cytoplasm. Ratios of mean values and standard deviations of each cell and its constituent parts were calculated for brightness-invariant classification of phenotypes. This was achieved using a decision tree based on the analysis of the extracted features for all phenotypes. Dependent on the intensity distribution between the three cellular compartments, three classes of phenotypes were defined termed "cytoplasm", "Golgi" and "Golgi strong".

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Calculation of scores from classification results derived from the automated image analysis tool

Results of cell classification were subjected to further analysis to calculate scores. The percentage of cells displaying a classified phenotype was determined for each image. In the validation screening procedure, cells from both images of the same well were combined for further analysis. Both the median and the standard deviation of a complete array were calculated and used to determine a score for each experimental condition. This score was expressed as the distance in standard deviations to the median of the respective 384-spot siRNA array. In validation screening, median and standard deviation from all negative controls analyzed on the same plate were used for the determination of scores. In primary screening, the hit threshold for SH4-HASPB-GFP was set to a score of 2.5 for both replicates and to 2 (3/4 or 2/3 replicates) in validation screening. For potential hits from the so-called “druggable genome”, SH4-HASPB-GFP hits were included in the validation screening procedure when the hit threshold was above 5 on only one replicate. The hit threshold for SH4-YES1-Cherry was adjusted to a score of 3.5 in primary screening (both replicates) and 2 in validation screening (3/4 or 2/3 replicates). All potential hits derived from primary screening that were identified with the automated image analysis tool were further subjected to manual inspection.

A web-based database to store RNAi screening data

All original data along with relevant information on experimental conditions and reagents used in this study were stored in a web-based database. It can be accessed at: https://ichip.bioquant.uni-heidelberg.de (User: "ichipguest"; Password: "Dec5ex2h").

Liquid-phase transfection of stable HeLa cells with siRNAs directed against MVD, coatomer subunits and PRKCA

Stably transduced HeLa cells were transfected with siRNAs directed against MVD (Ambion, s9094), the coatomer subunits COPA (Ambion, 146404), COPB1 (Ambion, 24546), COPB2 (Ambion, 137699), ARCN1 (Ambion, 10234), and a siRNA directed against PRKCA (Ambion, s11093) as well as a scrambled siRNA (Ambion, 103860 or neg. control #1) in 24-well plates using oligofectamine (Invitrogen). For each well, 50 pmol of siRNA were preincubated with 12 µl of diluted (1:4) oligofectamine for 20

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minutes at room temperature before addition to cells. 32-36 hours post- transfection, cells were passaged and cultivated in 8-well LabTek imaging chambers (Nunc). Expression of SH4 fusion proteins was induced by cultivating cells in the presence of 1 µg/ml doxycycline for 12-18 hours. For MVD knockdowns, cells were cultivated in DMEM containing 10% delipidated FCS (PAN Biotech).

Quantification of RNAi mediated knockdown efficiencies of MVD, coatomer subunits and PRKCA employing Western blot analysis and quantitative real-time PCR

Stable HeLa cells expressing SH4-HASPB-GFP and SH4-YES1-mCherry were transfected with a scrambled siRNA (Ambion, 103860) and siRNAs directed against GFP (Ambion, 4626), MVD (Ambion, s9094), COPB1 (Ambion, 24546) and, ARCN1 (Ambion, 10234) or PRKCA (Ambion, s11093) on 6-well plates using 300 pmol of siRNA. For MVD knockdowns, cells were cultivated in DMEM containing 10% delipidated FCS (PAN Biotech). 24 hours post-transfection, reporter protein expression was induced by cultivation in the presence of 1 µg/ml doxycycline for further 24 hours. 48 hours post-transfection, cells were harvested. For Western Blot analysis, 60µg of total protein from the post-nuclear supernatant were subjected to SDS-PAGE on NuPAGE 4-12% gradient gels (Invitrogen). Gels were blotted on PVDF membranes and specific proteins were detected using polyclonal antibodies raised against GFP, MVD (Santa Cruz, sc-160550), COPB1 and ARCN1 and mouse monoclonal antibodies against PRKCA (Abcam, ab31) and GAPDH (Ambion, 4300). Signals were detected and quantified using a LICOR infrared imaging system. For real-time PCR, RNA was extracted using the RNeasy Mini Kit (Qiagen) and used for cDNA synthesis applying the ImProm-II Reverse Transcription System (Promega). Using the TaqMan Gene Expression assay (Ambion, Hs00159403_m1), mRNA levels were determined using a StepOne Real-Time PCR System (Applied Biosystems).

Depletion of cellular cholesterol and cholesterol rescue

Stable HeLa cells were incubated for 20 hours in the presence of 1µg/ml doxycycline to induce expression of SH4-HASPB-GFP and SH4-YES1-mCherry in DMEM containing 10% delipidated FCS (PAN Biotech). For cholesterol depletion, cells were incubated for 1 hour in the presence of 5-10 mM methyl-β-cyclodextrin (MβCD, Sigma-Aldrich) before analysis by live-cell confocal microscopy. Subsequently, for cholesterol replenishment, water-soluble cholesterol (Sigma-Aldrich) was added to the MβCD-treated cells in a 1:10 ratio (0.5 mM cholesterol to 5mM MβCD-treated

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cells and 1mM cholesterol to 10mM MβCD-treated cells) and incubated for 1.5 h before analysis by live-cell confocal microscopy. Control cells were incubated for 20 hours with 50 nM ouabain in DMEM containing 10% delipidated FCS and analyzed by live-cell confocal microscopy.

Immunostaining of stable HeLa cells

Stable HeLa cells grown on cover slips were fixed in 5% PFA for 5 min at room temperature, quenched in 50mM NH4Cl for 5 min and permeabilized in 0.1 % TX-100 for 5 min before blocking in 1% BSA for 1 hour. Endogenous YES1 was labelled by incubation with a specific antibody (BD, 610375) diluted 1:250 in 1% BSA for 1 hour. Samples were incubated with a Alexa488-labelled secondary antibody (Invitrogen) diluted 1:1000 in 1% BSA for 1 hour and mounted in LinMount (Linaris) mounting medium.

Microinjection of recombinant coatomer

Recombinant coatomer (∼1.3 mg/ml) (Sahlmuller et al. 2011) or the respective buffer was co-injected with 1:10 diluted Alexa488-labelled secondary antibodies (Invitrogen) into stable HeLa cells using a FemtoJet microinjection device (Eppendorf) mounted on an Axiovert 35 microscope (Zeiss). 3-6 hours after microinjection, cells were transfected with a siRNA against COPB1 (Ambion, 24546) and induced for reporter protein expression 4 hours post-transfection. Cells were analyzed by live- cell confocal microscopy 30 hours after transfection.

Determination of cellular cholesterol levels using nano-electrospray ionisation mass spectrometry

Stable HeLa cells were cultivated in DMEM containing 10% delipidated FCS (PAN Biotech GmbH) and transfected with a siRNA directed against MVD (Ambion, s9094) for 48 hours or treated with 10 mM methyl-β-cyclodextrin (Sigma-Aldrich) for 30 minutes. Control cells were cultivated in normal DMEM (untreated) or in DMEM containing 10% delipidated FCS (mock). Either whole cells or membranes isolated by ultracentrifugation of postnuclear supernatants from homogenized cells were subjected to lipid extraction and mass spectrometric quantification of cholesterol and PC as described previously (Merz et al. 2011).

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Figure legends

Figure 1: Plasma membrane targeting of SH4 fusion proteins depends on N- terminal acylation and can be measured using an image analysis tool. (A) Stable HeLa cells expressing GFP fusion proteins containing either wild-type or mutant forms of the SH4 domains of either HASPB or YES1 were induced for reporter protein expression and subjected to live cell confocal microscopy to determine the subcellular localization of the SH4 fusion proteins. (B) Stable HeLa cells expressing both SH4-HASPB-GFP and SH4-YES1-mCherry were treated with the palmitoylation inhibitor 2-bromopalmitate (2-BP). Subcellular localization of SH4 fusion proteins was analyzed by live-cell confocal microscopy. (C) Widefield images from stable HeLa cells expressing wild-type or mutant SH4 domains of HASPB (a) or from HeLa cells expressing SH4-HASPB-GFP under treatment with 2-BP (b) were analyzed with the automated image analysis tool and evaluated for the detection of hit phenotypes.

Figure 2: Robustness and sensitivity of the experimental system at the level of primary screening. Stable HeLa cells were cultivated on 384-well siRNA arrays for 36 hours, followed by the induction of expression of SH4-HASPB-GFP and SH4- YES1-mCherry. Nuclei were labelled and cells were subjected to live cell fluorescence microscopy in areas of immobilized siRNAs. Enlarged image details from primary screening data after transfection of a scrambled siRNA (A-B) and a siRNA targeted against the coatomer subunit COPB1 (C-D) are shown. Scores of all individual control experiments from primary screening were calculated using the image analysis tool described and are shown for SH4-HASPB-GFP (E, G) and SH4-YES1- mCherry (F, H), respectively. Negative controls (scrambled siRNA) are shown in panels E and F. Positive controls (siRNA targeted against COPB1) are shown in panels G and H. Scores below the defined hit threshold lie between the dashed lines within the grey shaded area.

Figure 3: Interference with cellular lipid metabolism by RNAi-mediated downregulation of metabolic enzymes or pharmacological cholesterol depletion causes intracellular retention of SH4 proteins. (A) HeLa cells expressing SH4- HASPB-GFP and SH4-YES1-mCherry were reverse transfected with a scrambled siRNA (a, e) and siRNAs targeted against acyl-coenzyme A-dehydrogenase, very long chain (ACADVL; b, f), sphingomyelin phosphodiesterase, acid-like, 3B (SMPDL3B; c, g) and mevalonate (diphospho) decarboxylase (MVD; d, h) and subjected to live cell fluorescence microscopy. Enlarged image details from original data from the validation screen are shown. (B) HeLa cells expressing SH4-HASPB-GFP and SH4- YES1-mCherry were treated with methyl-β-cyclodextrin (MβCD) to deplete cellular

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cholesterol and analyzed by live-cell confocal microscopy to determine the subcellular localization of SH4 fusion proteins. Subsequently, the same cells were supplemented with cholesterol and analyzed by live-cell confocal microscopy again. Control cells were treated with 50mM ouabain and analyzed by live-cell confocal microscopy.

Figure 4: Characterization and validation of PRKCA as a component in SH4- dependent protein transport. (A) HeLa cells expressing SH4-HASPB-GFP and SH4- YES1-mCherry were transfected with a scrambled siRNA (a-c) and a siRNA directed against PRKCA (d-f) and subjected to live-cell confocal microscopy to determine the localization of both SH4 fusion proteins. (B) Equal protein amounts of total cell lysates from transfected and induced cells were subjected to SDS-PAGE and Western blot analysis with antibodies directed against GFP, PRKCA and GAPDH. (C) Stable HeLa cells expressing SH4-HASPB-GFP (a, c) or SH4-YES1-GFP (b, d) were cultured in the presence of 10μM protein kinase C inhibitor GÖ 6983 for 16 hours (c, d) and analyzed by live-cell confocal microscopy for subcellular localization of both SH4 fusion proteins.

Figure 5: Characterization and validation of coatomer as a component in SH4- dependent protein transport. (A) HeLa cells expressing SH4-HASPB-GFP and SH4- YES1-mCherry were transfected with a scrambled siRNA (a-c), siRNAs directed against COPB1 (d-f) and ARCN1 (g-i) and subjected to live-cell confocal microscopy to determine the localization of both SH4 fusion proteins. (B) Equal protein amounts of total cell lysates from transfected and induced cells were subjected to SDS-PAGE and Western blot analysis with antibodies directed against GFP, COPB1, ARCN1 and GAPDH. (C) HeLa cells expressing SH4-HASPB-mCherry were coinjected with recombinant coatomer and an Alexa-488-labelled secondary antibody before transfection with a siRNA directed against COPB1. 30 hours post-transfection, cells were analyzed by live-cell confocal microscopy to determine the subcellular localization of the SH4 fusion protein in microinjected cells.

Figure 6: PRKCA and coatomer play differential roles in transport of endogenous YES1 and other SH4 proteins. (A) Stable HeLa cells expressing SH4- HASPB-mCherry were transfected with a scrambled siRNA (a-c) and siRNAs directed against COPB1 (d-f) and PRKCA (g-i) and induced for reporter protein expression. 48h post-transfection, cells were fixed, subjected to immunostaining against endogenous YES1 and subsequently analyzed by confocal microscopy. (B) Stable HeLa cells expressing fusion proteins of the SH4 domains of the acylated SRC kinases LCK, SRC and FYN were transfected with a scrambled siRNA (a-c) and siRNAs

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directed against COPB1 (d-f) and PRKCA (g-i). 48 hours post-transfection, cells were analyzed by live-cell confocal microscopy to determine the subcellular localization of the respective SH4-protein.

Fig. S1: SH4-domain-containing fusion constructs and their doxycycline- dependent expression and plasma-membrane-localization in stably tranduced HeLa cells. Fluorescent fusion proteins containing N-terminal SH4 domains were used to stably transduce HeLa cells. Expression was under the control of a doxycycline-dependent transactivator. (A) SH4-HASPB-GFP consisted of the N- terminal 18 amino acids of Leishmania Hydrophilic Acylated Surface Protein B (HASPB) fused to green fluorescent protein (GFP). SH4-YES1-mCherry consisted of the N-terminal 18 amino acids of the human orthologue of the SRC kinase YES1 fused to the red fluorescent protein mCherry. Both proteins are myristoylated at the N-terminal glycine residue (pink) and palmitoylated at a downstream cysteine residue (blue). (B) Stable HeLa cells were incubated in the presence of doxycycline to induce expression of both SH4-HASPB-GFP and SH4-YES1-mCherry and analyzed by flow cytometry. (C) Stable HeLa cells were treated with doxycycline to induce simultaneous expression of SH4-HASPB-GFP and SH4-YES1-mCherry and analyzed by live cell confocal microscopy to determine the subcellular localization of both fusion proteins.

Fig. S2: Cell segmentation and classification using an automated image analysis tool. (A) Individual cells were segmented into three different compartments: the plasma membrane, the cytoplasm and the nucleus. (B) Intensity features were extracted for the whole cell area as well as for each cellular compartment and used for cell classification according to the depicted decision tree.

Fig. S3: Workflow of the primary RNAi screening procedure. (A) HeLa cells were cultivated for 36 hours on 384-spot siRNA arrays containing positive (blue and green dots) and negative (red dots) controls to down-regulate target proteins. Afterwards, expression of SH4-HASPB-GFP and SH4-YES1-mCherry was induced by doxycycline. (B) 48 hours post-transfection, nuclei were labelled and images were acquired for the three available channels (Hoechst, Cherry, GFP) using an automated wide-field microscopy platform. (C) Images were analyzed using the image analysis tool described in the main text resulting in the calculation of scores for each experimental condition. Scores above 2.5 and 3.5 for SH4-HASPB-GFP and SH4- YES1-mCherry, respectively, were classified as hits and resulted in the identification of 286 potential hits during the primary screening procedure.

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Fig. S4: Phenotypic changes following siRNA-mediated down-regulation of control proteins. HeLa cells were cultivated on siRNA arrays to down-regulate target proteins followed by the induction of expression of SH4-HASPB-GFP and SH4-YES1- mCherry, respectively. Cell nuclei were labelled and cells were subjected to automated live-cell fluorescence microscopy 48 hours post-transfection in areas containing spots with immobilized siRNAs as indicated by dashed circles. Images from all three channels are shown. (A-C) scrambled siRNA; (D-F) siRNA targeted against GFP; (G-I) siRNA targeting the inner centromere protein INCENP.

Fig. S5: Quantification of cellular cholesterol levels and knockdown efficiencies at the mRNA and protein level. (A) Cholesterol / PC ratios were determined by nano-electrospray ionisation mass spectrometry as described previously (Merz et al. 2011). Following treatment of cells with either a siRNA targeting MVD or treatment with methyl-β-cyclodextrin, lipid analysis was performed from both whole cells and cellular membranes (n≥3). (B) MVD mRNA levels were quantified by quantitative real-time PCR in HeLa cells expressing SH4-HASPB-GFP and SH4-YES1-mCherry. (n=3). (C-E) Total cell lysates from HeLa cells expressing SH4-HASPB-GFP and SH4- YES1-mCherry after transfection with the siRNAs indicated were analyzed by SDS- PAGE and Western blotting. (C) Quantification of MVD protein levels after knockdown of MVD. Data were normalized to the scrambled control. (n=4) (D) Quantification of PRKCA protein levels after knockdown of PRKCA. Data were normalized to the scrambled control. (n=3) (A representative Western blot is shown in figure 4.) (E) Quantification of protein levels of COPB1 and ARCN1 after knockdown with the respective siRNAs. Data were normalized to the scrambled control. (n=3) (A representative Western blot is shown in figure 5.)

Fig. S6: Analysis of the influence of the fluorescent proteins fused to SH4- domains on the subcellular localization of SH4 fusion proteins and the role of other coatomer subunits on SH4-dependent protein transport. (A) Stable HeLa cells expressing SH4-HASPB-mCherry (a-c) or SH4-YES1-GFP (d-f), respectively, were transfected with a scrambled siRNA (a,d) and siRNAs directed against COPB1 (b,e) and PRKCA (c,f) and subjected to live-cell confocal microscopy to determine the subcellular localization of SH4 fusion proteins. (B) Stable HeLa cells simultaneously expressing SH4-HASPB-GFP and SH4-YES1-mCherry were transfected with siRNAs directed against COPA (a-c) and COPB2 (d-f) and analyzed by live-cell fluorescence microscopy to determine the subcellular localization of both SH4 fusion proteins. (The respective control with a scrambled siRNA is shown in figure 5.)

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Table 1: Validated gene products with a putative function in SH4-domain- dependent intracellular trafficking.

Table S1: Gene products targeted in the validation screen.

Table S2: Validated gene products with a putative function in SH4-domain- dependent intracellular trafficking.

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Figures

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Tables

Table 1:

SH4-YES1- Gene Symbol Entrez Gene ID RefSeq siRNA ID antisense siRNA sequence SH4-HASPB-GFP mCherry Lipid Metabolism ACADVL 37 NM_000018 s208 AAACUGUUCAUUGACAAUCcc 3.4 6.1 MVD 4597 NM_002461 s224074 UUUUUAACUGGUCCUGGUGca 2.8 SMPDL3B 27293 NM_014474 s26101 UGCUAUGACGCGAUGAUGCtt 5.0 SREBF2 6721 NM_004599 s28 UUUGACCUUUGCAUCAUCCaa 2.1 Transport Factors COPA 1314 NM_004371 s3369 AAAGCGAGUUUUCUCAUCCtt 7.6 5.5 s3371 UGGAUUAGCAUGACAGACCtt 7.0 4.2 COPB1 1315 NM_016451 s3372 UCUUUGACUUUACAUCUCCtt 6.1 2.6 s18420 UCGAUAUUCUUUAACUUGCtt 2.6 KIF20B 9585 NM_016195 s18421 UGCUGAACUAAUACGUUUGgg 2.6 s11768 UUCUUGUAAGUAACUCUCGat 6.5 RAN 5901 NM_006325 s11769 UUUCCUGUCCUUAAUAUCCac 4.8 Protein Phosphorylation PRKCA 5578 NM_002737 s11093 UGCGGAUUUAGUGUGGAGCgg 4.3 3.3 (PRKCA)PRKCB 5579 NM_212535 s11096 AAAUCGGUCAGUUUCAUCCgg 3.3 2.6 PTPRD 5789 NM_001040712 s11540 UACAUUCGCGUAUCUAUUCtt 2.4 Other Protein Modifications ACY3 91703 NM_080658 s40752 UUCGCGAUUAAGCAGGUGCcc 2.8 3.2 GALNTL4 374378 NM_198516 s51536 AAAGUUGUCAUAUUUGAUGtt 2.7 LIPT2 387787 XM_370636 s226411 AAUUGAGAAAUGACAAUCUat 5.0 5.3 NAA35 60560 NM_024635 s34135 UUUACGUACUUUGCCGUCCat 3.9 3.4 Membrane Receptors BAI3 577 NM_001704 s1878 UGGAUUGCUAAGCUCAUUCat 3.2 CDH26 60437 NM_021810 s34067 AGCAGGAGUAGAGUGUAUGtt 3.1 2.8 IL7R 3575 XM_001127146 s7325 UGGUUAGUAAGAUAGGAUCca 2.5 3.5 ITGAV 3685 NM_002210 s7569 UAGGGUACACUUCAAGACCag 4.9 7.1 s7575 AGCCGUGUAACAUUCCUCCag 4.4 3.2 ITGB1 3688 NM_002211 s7576 UAAUCGCAAAACCAACUGCtg 5.0 3.2 s7574 UGCUGUUCCUUUGCUACGGtt 3.6 LILRB5 10990 NM_006840 s21637 AAAAAGAAAGUGUCUAUCUga 2.4 OR10V1 390201 NM_001005324 s52738 UCAGGGUCAGGUGAGAAUGga 2.9 2.5 TGFBR1 7046 NM_004612 s14073 AGUCUUUCAACGUAGUACCct 5.0 Gene Regulation and Expression s18876 UUCACGAACCUGAAUAUCCaa 3.3 3.9 EIF4A3 9775 NM_014740 s18877 UGAUCUGCUUGAUUGCUCGtt 4.5 4.0 HNRNPA1 3178 NM_002136 s6710 UUAUCUGGUACCAUUAUUCaa 2.4 RPS26P35 441377 XM_496991 s54340 UCUUUAAGAACUCAGCUCCtt 3.4 RPL21P62 442160 XM_001128707 s54494 UAACUUGUUUGUUUACAACaa 2.8 RPS26P8 644191 XM_930072 s55596 UCACAUACAGUUUGGGAAGca 2.7 MBD3L2 125997 NM_144614 s42925 UGGAUUUCUCGUUUCUUCUgt 3.6 RPL23AP82 284942 NM_203302 s49770 UCAGGACAAAUCAGGGUGGtg 3.2 2.3 PHF5A 84844 NM_032758 s39506 AUAGGAGUCACAAAUCACAca 4.2 3.5 s224297 UGGCAGGUAACGGCGAAUGat 3.7 2.9 POLR2F 5435 NM_021974 s10809 UGUGGUGAUUCGCUUCUGGtt 2.7 s20796 UCGUUGUUCACAUGUAGGGca 5.1 8.2 PRPF8 10594 NM_006445 s20797 AUGCGAUCAAUGUAUCUGCag 3.7 6.8 PRPF31 26121 NM_015629 s25122 UACUUAUCCCGGAUGAACUta 2.5 s194744 UAUAACUUGACCAACAGCCtc 3.7 RPL18 6141 NM_000979 s194745 UAGGAUCCAGGGUUAGUUUtt 3.0 s12186 UAUCUCGGCUCUUAGAGUGct 3.0 RPL21 6144 NM_000982 s12187 UAACAUUGUAGACUCUUCCag 2.9 RPS25P6 401206 XM_937380 s53508 UAAGUUAUUGAGCUUGUCCcg 3.8 3.8 SF3A1 10291 NM_001005409 s20117 UCAAUAUCCAGACCUGGUGcg 2.8 ZNF326 284695 NM_182975 s195972 UUCCAUUAAAGCCCUGAUAag 2.4 Others A2M 2 NM_000014 s819 UCGUUCUUAACCAUCACUGtg 3.2 2.9 ATP6AP2 10159 NM_005765 s19790 UUUCGGAAAACAACAGACCct 2.3 CACNA1S 779 NM_000069 s2297 UUCCGGUUUAUUUGGGUCCca 4.1 CHERP 10523 NM_006387 s20627 UUUGUUCUCUUCUCCGAGCct 2.8 3.1 DBH 1621 NM_000787 s3947 ACUGUGACCACCUUUCUCCca 2.7 CDC37P1 390688 NM_001080829 s52851 UCUUCAUCAUCGCUCAGUGtg 2.9 MAGEB1 4112 NM_002363 s8455 UUUAUACUUACGUAGAAUGaa 2.3 SHC1 6464 NM_003029 s12811 AAAUGAGAUAGAUUGCAUGtg 4.0 SOBP 55084 NM_018013 s30136 AAGUAGUUCGCAGUUAUUCtt 3.4 3.5 TMEM126A 84233 NM_032273 s38695 AAUCCAGUAACUUAAGAUGtt 2.1 YAP1 10413 NM_006106 s20367 UGAUUUAAGAAGUAUCUCUga 2.2 Unknown PATE2 399967 NM_212555 s53217 UAAUGAUACAUGCUCUGCCct 3.4 3.6 C12orf36 283422 NM_182558 s49233 UAGUGGAGCAUGAAGUGUCtt 3.0 C16orf71 146562 NM_139170 s44876 UCUGGAAUCAGGGAGGUUUgg 3.2 FAM108A1 81926 NM_001130111 s230886 UUAAUUUCCGUUUUCACGUat 2.2

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Table S1:

Gene Symbol Full Gene Name Entrez Gene ID RefSeq A2M alpha-2-macroglobulin 2 NM_000014 ABHD15 abhydrolase domain containing 15 116236 NM_198147 ACADVL acyl-Coenzyme A dehydrogenase, very long chain 37 NM_000018 ACSS1 acyl-CoA synthetase short-chain family member 1 84532 NM_032501 ACY3 aspartoacylase (aminocyclase) 3 91703 NM_080658 ADAM33 ADAM metallopeptidase domain 33 80332 NM_153202 AFF2 AF4/FMR2 family, member 2 2334 NM_002025 ALX1 ALX homeobox 1 8092 NM_006982 ANGPTL4 angiopoietin-like 4 51129 NM_001039667 ANKRD20A3 ankyrin repeat domain 20 family, member A3 441425 NM_001012419 ANKRD45 ankyrin repeat domain 45 339416 NM_198493 ANXA1 annexin A1 301 NM_000700 ANXA5 annexin A5 308 NM_001154 amyloid beta (A4) precursor protein-binding, family B, member 1 APBB1IP 54518 NM_019043 interacting protein ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 64411 NM_022481 ARF3 ADP-ribosylation factor 3 377 NM_001659 ARF5 ADP-ribosylation factor 5 381 NM_001662 ARHGAP1 Rho GTPase activating protein 1 392 NM_004308 ARHGAP6 Rho GTPase activating protein 6 395 NM_006125 ARHGDIA Rho GDP dissociation inhibitor (GDI) alpha 396 NM_004309 ARMC8 armadillo repeat containing 8 25852 NM_014154 ATP2A2 ATPase, Ca++ transporting, cardiac muscle, slow twitch 2 488 NM_170665 ATP6AP2 ATPase, H+ transporting, lysosomal accessory protein 2 10159 NM_005765 ATP6V1B2 ATPase, H+ transporting, lysosomal 56/58kDa, V1 subunit B2 526 NM_001693 UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase B3GNT8 374907 NM_198540 8 B4GALNT1 beta-1,4-N-acetyl-galactosaminyl transferase 1 2583 NM_001478 BAI3 brain-specific angiogenesis inhibitor 3 577 NM_001704 BBX bobby sox homolog (Drosophila) 56987 NM_020235 BCKDK branched chain ketoacid dehydrogenase kinase 10295 NM_005881 BCL9L B-cell CLL/lymphoma 9-like 283149 NM_182557 BDH2 3-hydroxybutyrate dehydrogenase, type 2 56898 NM_020139 BIN3 bridging integrator 3 55909 NM_018688 BPIL1 bactericidal/permeability-increasing protein-like 1 80341 NM_025227 BTBD10 BTB (POZ) domain containing 10 84280 NM_032320 BTN2A2 butyrophilin, subfamily 2, member A2 10385 NM_006995 C12orf36 chromosome 12 open reading frame 36 283422 NM_182558 C16orf71 chromosome 16 open reading frame 71 146562 NM_139170 C1orf101 chromosome 1 open reading frame 101 257044 NM_173807 C20orf166 chromosome 20 open reading frame 166 128826 NM_178463 C6orf125 chromosome 6 open reading frame 125 84300 NM_032340 C9orf116 chromosome 9 open reading frame 116 138162 NM_001048265 CACNA1S calcium channel, voltage-dependent, L type, alpha 1S subunit 779 NM_000069 calcium/calmodulin-dependent protein kinase (CaM kinase) II CAMK2D 817 NM_172115 delta CAPN12 calpain 12 147968 NM_144691 CAPN7 calpain 7 23473 NM_014296 CARM1 coactivator-associated arginine methyltransferase 1 10498 NM_199141 calcium/calmodulin-dependent serine protein kinase (MAGUK CASK 8573 NM_003688 family) CCDC43 coiled-coil domain containing 43 124808 NM_144609

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CCNE1 cyclin E1 898 NM_001238 CD46 CD46 molecule, complement regulatory protein 4179 NM_002389 CDC37P1 cell division cycle 37 homolog (S. cerevisiae) pseudogene 1 390688 NM_001080829 CDH26 cadherin-like 26 60437 NM_021810 cadherin, EGF LAG seven-pass G-type receptor 2 (flamingo CELSR2 1952 NM_001408 homolog, Drosophila) CHERP calcium homeostasis endoplasmic reticulum protein 10523 NM_006387 CHN1 chimerin (chimaerin) 1 1123 NM_001822 CHRNA5 cholinergic receptor, nicotinic, alpha 5 1138 NM_000745 CHRNB1 cholinergic receptor, nicotinic, beta 1 (muscle) 1140 NM_000747 CLCN2 chloride channel 2 1181 NM_004366 CLIC2 chloride intracellular channel 2 1193 NM_001289 CSNK2B casein kinase 2, beta polypeptide 1460 NM_001320 DBH dopamine beta-hydroxylase (dopamine beta-monooxygenase) 1621 NM_000787 DDOST dolichyl-diphosphooligosaccharide--protein glycosyltransferase 1650 NM_005216 DIRAS2 DIRAS family, GTP-binding RAS-like 2 54769 NM_017594 DNASE1L3 deoxyribonuclease I-like 3 1776 NM_004944 DNTT deoxynucleotidyltransferase, terminal 1791 NM_004088 dual specificity phosphatase 11 (RNA/RNP complex 1- DUSP11 8446 NM_003584 interacting) EBP emopamil binding protein (sterol isomerase) 10682 NM_006579 EIF4A3 eukaryotic translation initiation factor 4A, isoform 3 9775 NM_014740 EIF4G2 eukaryotic translation initiation factor 4 gamma, 2 1982 NM_001042559 GPR144 G protein-coupled receptor 144 347088 NM_182611 EXOSC1 exosome component 1 51013 NM_016046 F2RL3 coagulation factor II (thrombin) receptor-like 3 9002 NM_003950 FAH fumarylacetoacetate hydrolase (fumarylacetoacetase) 2184 NM_000137 FAM108A1 family with sequence similarity 108, member A1 81926 NM_001130111 FAM177B family with sequence similarity 177, member B 400823 NM_207468 FAM3C family with sequence similarity 3, member C 10447 NM_001040020 FYVE, RhoGEF and PH domain containing 1 (faciogenital FGD1 2245 NM_004463 dysplasia) fibroblast growth factor receptor 3 (achondroplasia, thanatophoric FGFR3 2261 NM_000142 dwarfism) FLRT2 fibronectin leucine rich transmembrane protein 2 23768 NM_013231 FXYD domain containing ion transport regulator 1 FXYD1 5348 NM_005031 (phospholemman) FZD10 frizzled homolog 10 (Drosophila) 11211 NM_007197 GABRB2 gamma-aminobutyric acid (GABA) A receptor, beta 2 2561 NM_000813 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N- GALNT11 63917 NM_022087 acetylgalactosaminyltransferase 11 (GalNAc-T11) UDP-N-acetyl-alpha-D-galactosamine:polypeptide N- GALNTL4 374378 NM_198516 acetylgalactosaminyltransferase-like 4 GLT8D2 glycosyltransferase 8 domain containing 2 83468 NM_031302 GOLGA5 golgi autoantigen, golgin subfamily a, 5 9950 NM_005113 GPR139 G protein-coupled receptor 139 124274 NM_001002911 GPR162 G protein-coupled receptor 162 27239 NM_014449 GPR50 G protein-coupled receptor 50 9248 NM_004224 GPR75 G protein-coupled receptor 75 10936 NM_006794 GRB2 growth factor receptor-bound protein 2 2885 NM_002086 GRIA2 glutamate receptor, ionotropic, AMPA 2 2891 NM_001083619 GYLTL1B glycosyltransferase-like 1B 120071 NM_152312 HABP2 hyaluronan binding protein 2 3026 NM_004132 HAS1 hyaluronan synthase 1 3036 NM_001523 HFM1 HFM1, ATP-dependent DNA helicase homolog (S. cerevisiae) 164045 NM_001017975 HIR histone cell cycle regulation defective homolog A (S. HIRA 7290 NM_003325 cerevisiae) HNRNPA1 heterogeneous nuclear ribonucleoprotein A1 3178 NM_002136 HPGDS hematopoietic prostaglandin D synthase 27306 NM_014485

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HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 3291 NM_000196 HTR2B 5-hydroxytryptamine (serotonin) receptor 2B 3357 NM_000867 HTR4 5-hydroxytryptamine (serotonin) receptor 4 3360 NM_000870 HTRA3 HtrA serine peptidase 3 94031 NM_053044 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 3418 NM_002168 IDH3B isocitrate dehydrogenase 3 (NAD+) beta 3420 NM_006899 IFNGR1 interferon gamma receptor 1 3459 NM_000416 IFT57 intraflagellar transport 57 homolog (Chlamydomonas) 55081 NM_018010 IL13RA1 interleukin 13 receptor, alpha 1 3597 NM_001560 IL17RB interleukin 17 receptor B 55540 NM_018725 IL7R interleukin 7 receptor 3575 XM_001127146 integrin, alpha V (vitronectin receptor, alpha polypeptide, antigen ITGAV 3685 NM_002210 CD51) integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen ITGB1 3688 NM_033668 CD29 includes MDF2, MSK12) KARS lysyl-tRNA synthetase 3735 NM_005548 potassium voltage-gated channel, shaker-related subfamily, KCNA6 3742 NM_002235 member 6 potassium voltage-gated channel, subfamily H (eag-related), KCNH1 3756 NM_172362 member 1 potassium voltage-gated channel, subfamily H (eag-related), KCNH8 131096 NM_144633 member 8 KDSR 3-ketodihydrosphingosine reductase 2531 NM_002035 KIAA1211 KIAA1211 protein 57482 NM_020722 KIF20B kinesin family member 20B 9585 NM_016195 KIF5B kinesin family member 5B 3799 NM_004521 KIFC3 kinesin family member C3 3801 NM_005550 KLF2 Kruppel-like factor 2 (lung) 10365 NM_016270 L1CAM L1 cell adhesion molecule 3897 NM_000425 L3MBTL4 l(3)mbt-like 4 (Drosophila) 91133 NM_173464 LAPTM5 lysosomal multispanning membrane protein 5 7805 NM_006762 LEPR leptin receptor 3953 NM_001003679 LEPREL2 leprecan-like 2 10536 NM_014262 LEPROT leptin receptor overlapping transcript 54741 NM_017526 leukocyte immunoglobulin-like receptor, subfamily A (with TM LILRA2 11027 NM_006866 domain), member 2 leukocyte immunoglobulin-like receptor, subfamily B (with TM LILRB4 11006 NM_001081438 and ITIM domains), member 4 leukocyte immunoglobulin-like receptor, subfamily B (with TM LILRB5 10990 NM_006840 and ITIM domains), member 5 LIPT2 lipoyl(octanoyl) transferase 2 (putative) 387787 XM_370636 LPAR6 lysophosphatidic acid receptor 6 10161 NM_005767 LY6G5B lymphocyte antigen 6 complex, locus G5B 58496 NM_021221 M6PR mannose-6-phosphate receptor (cation dependent) 4074 NM_002355 MAGEB1 melanoma antigen family B, 1 4112 NM_002363 MAGEB4 melanoma antigen family B, 4 4115 NM_002367 MAPKAP1 mitogen-activated protein kinase associated protein 1 79109 NM_024117 MBD3L2 methyl-CpG binding domain protein 3-like 2 125997 NM_144614 MBTPS1 membrane-bound transcription factor peptidase, site 1 8720 NM_003791 MCF2L2 MCF.2 cell line derived transforming sequence-like 2 23101 NM_015078 MDH1 malate dehydrogenase 1, NAD (soluble) 4190 NM_005917 MEIG1 meiosis expressed gene 1 homolog (mouse) 644890 NM_001080836 macrophage migration inhibitory factor (glycosylation-inhibiting MIF 4282 NM_002415 factor) MLST8 MTOR associated protein, LST8 homolog (S. cerevisiae) 64223 NM_022372 membrane protein, palmitoylated 7 (MAGUK p55 subfamily MPP7 143098 NM_173496 member 7) MSI2 musashi homolog 2 (Drosophila) 124540 NM_138962 MVD mevalonate (diphospho) decarboxylase 4597 NM_002461 MYLK3 myosin light chain kinase 3 91807 NM_182493

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NAA35 N(alpha)-acetyltransferase 35, NatC auxiliary subunit 60560 NM_024635 NAE1 NEDD8 activating enzyme E1 subunit 1 8883 NM_001018159 NARS asparaginyl-tRNA synthetase 4677 NM_004539 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, NDUFB5 4711 NM_002492 16kDa NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 8, NDUFB8 4714 NM_005004 19kDa NADH dehydrogenase (ubiquinone) Fe-S protein 2, 49kDa NDUFS2 4720 NM_004550 (NADH-coenzyme Q reductase) NEK10 NIMA (never in mitosis gene a)- related kinase 10 152110 NM_001031741 NETO1 neuropilin (NRP) and tolloid (TLL)-like 1 81832 NM_138966 NKD1 naked cuticle homolog 1 (Drosophila) 85407 NM_033119 NR2F1 nuclear receptor subfamily 2, group F, member 1 7025 NM_005654 NR4A3 nuclear receptor subfamily 4, group A, member 3 8013 NM_173198 NSMCE4A non-SMC element 4 homolog A (S. cerevisiae) 54780 NM_017615 NUDT18 nudix (nucleoside diphosphate linked moiety X)-type motif 18 79873 NM_024815 NUDT9P1 Putative nucleoside diphosphate-linked moiety X motif 9P1 119369 NR_002779 NXF3 nuclear RNA export factor 3 56000 NM_022052 ODZ1 odz, odd Oz/ten-m homolog 1(Drosophila) 10178 NM_014253 OPRK1 opioid receptor, kappa 1 4986 NM_000912 OR10V1 olfactory receptor, family 10, subfamily V, member 1 390201 NM_001005324 OR1C1 olfactory receptor, family 1, subfamily C, member 1 26188 NM_012353 OR4D1 olfactory receptor, family 4, subfamily D, member 1 26689 NM_012374 OR7C1 olfactory receptor, family 7, subfamily C, member 1 26664 NM_198944 OTUD7B OTU domain containing 7B 56957 NM_020205 PACSIN3 protein kinase C and casein kinase substrate in neurons 3 29763 NM_016223 PAOX polyamine oxidase (exo-N4-amino) 196743 NM_207127 PATE2 prostate and testis expressed 2 399967 NM_212555 PBX4 pre-B-cell leukemia homeobox 4 80714 NM_025245 PCCA propionyl Coenzyme A carboxylase, alpha polypeptide 5095 NM_000282 PDC phosducin 5132 NM_002597 PDE8A phosphodiesterase 8A 5151 NM_002605 PDLIM5 PDZ and LIM domain 5 10611 NM_001011513 PEX19 peroxisomal biogenesis factor 19 5824 NM_002857 PGGT1B protein geranylgeranyltransferase type I, beta subunit 5229 NM_005023 PHF5A PHD finger protein 5A 84844 NM_032758 PHKA2 phosphorylase kinase, alpha 2 (liver) 5256 NM_000292 PLAUR plasminogen activator, urokinase receptor 5329 NM_002659 PLS3 plastin 3 (T isoform) 5358 NM_005032 PLSCR4 phospholipid scramblase 4 57088 NM_020353 POLE2 polymerase (DNA directed), epsilon 2 (p59 subunit) 5427 NM_002692 POLR2F polymerase (RNA) II (DNA directed) polypeptide F 5435 NM_021974 POLR2L polymerase (RNA) II (DNA directed) polypeptide L, 7.6kDa 5441 NM_021128 POTEE POTE ankyrin domain family, member E 445582 NM_001083538 POTEG POTE ankyrin domain family, member G 404785 NM_001005356 PPID peptidylprolyl isomerase D (cyclophilin D) 5481 NM_005038 PPP1R13L protein phosphatase 1, regulatory (inhibitor) subunit 13 like 10848 NM_006663 PRKCA protein kinase C, alpha 5578 NM_002737 PRKCB protein kinase C, beta 5579 NM_212535 PRPF31 PRP31 pre-mRNA processing factor 31 homolog (S. cerevisiae) 26121 NM_015629 PRPF8 PRP8 pre-mRNA processing factor 8 homolog (S. cerevisiae) 10594 NM_006445 PRPS1L1 phosphoribosyl pyrophosphate synthetase 1-like 1 221823 NM_175886 PRPSAP1 phosphoribosyl pyrophosphate synthetase-associated protein 1 5635 NM_002766 PRY PTPN13-like, Y-linked 9081 NM_004676 PRY2 PTPN13-like, Y-linked 2 442862 NM_001002758 PTPN9 protein tyrosine phosphatase, non-receptor type 9 5780 NM_002833 PTPRC protein tyrosine phosphatase, receptor type, C 5788 NM_002838

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PTPRD protein tyrosine phosphatase, receptor type, D 5789 NM_001040712 PTPRK protein tyrosine phosphatase, receptor type, K 5796 NM_002844 PYCR2 pyrroline-5-carboxylate reductase family, member 2 29920 NM_013328 phosphorylase, glycogen; muscle (McArdle syndrome, glycogen PYGM 5837 NM_005609 storage disease type V) RAB7L1 RAB7, member RAS oncogene family-like 1 8934 NM_003929 RAN RAN, member RAS oncogene family 5901 NM_006325 RARA retinoic acid receptor, alpha 5914 NM_000964 RARG retinoic acid receptor, gamma 5916 NM_000966 RASA4 RAS p21 protein activator 4 10156 NM_001079877 RCHY1 ring finger and CHY zinc finger domain containing 1 25898 NM_001008925 RHOBTB2 Rho-related BTB domain containing 2 23221 NM_015178 RHOD ras homolog gene family, member D 29984 NM_014578 RNF169 ring finger protein 169 254225 XM_495886 RPL18 ribosomal protein L18 6141 NM_000979 RPL21 ribosomal protein L21 6144 NM_000982 RPL21P16 ribosomal protein L21 pseudogene 16 729402 NM_001139505 RPL21P62 ribosomal protein L21 pseudogene 62 442160 XM_001128707 RPL23AP82 ribosomal protein L23a pseudogene 82 284942 NM_203302 RPS2 ribosomal protein S2 6187 NM_002952 RPS25 ribosomal protein S25 6230 NM_001028 RPS25P6 ribosomal protein S25 pseudogene 6 401206 XM_937380 RPS26P10 ribosomal protein S26 pseudogene 10 401470 XM_376787 RPS26P35 ribosomal protein S26 pseudogene 35 441377 XM_496991 RPS26P8 ribosomal protein S26 pseudogene 8 644191 XM_930072 RPS6KL1 ribosomal protein S6 kinase-like 1 83694 NM_031464 SAP30L SAP30-like 79685 NM_024632 SDF2L1 stromal cell-derived factor 2-like 1 23753 NM_022044 SEC24C SEC24 related gene family, member C (S. cerevisiae) 9632 NM_004922 SEC31B SEC31 homolog B (S. cerevisiae) 25956 NM_015490 SERPINB4 serpin peptidase inhibitor, clade B (ovalbumin), member 4 6318 NM_002974 SEZ6L2 seizure related 6 homolog (mouse)-like 2 26470 NM_201575 SF3A1 splicing factor 3a, subunit 1, 120kDa 10291 NM_001005409 SFT2D2 SFT2 domain containing 2 375035 NM_199344 SHC (SRC homology 2 domain containing) transforming protein SHC1 6464 NM_003029 1 SLC26A2 solute carrier family 26 (sulfate transporter), member 2 1836 NM_000112 SLC2A9 solute carrier family 2 (facilitated glucose transporter), member 9 56606 NM_001001290 SLC44A4 solute carrier family 44, member 4 80736 NM_025257 SLCO6A1 solute carrier organic anion transporter family, member 6A1 133482 NM_173488 SMPDL3B sphingomyelin phosphodiesterase, acid-like 3B 27293 NM_014474 SOBP sine oculis binding protein homolog (Drosophila) 55084 NM_018013 SOD2 superoxide dismutase 2, mitochondrial 6648 NM_001024465 SORBS1 sorbin and SH3 domain containing 1 10580 NM_001034954 spleen focus forming virus (SFFV) proviral integration oncogene SPI1 6688 NM_001080547 spi1 SREBF2 sterol regulatory element binding transcription factor 2 6721 NM_004599 STARD9 StAR-related lipid transfer (START) domain containing 9 57519 XM_001129482 STK16 serine/threonine kinase 16 8576 NM_001008910 STS steroid sulfatase (microsomal), arylsulfatase C, isozyme S 412 NM_000351 STX2 syntaxin 2 2054 NM_001980 STYK1 serine/threonine/tyrosine kinase 1 55359 NM_018423 TAS2R1 taste receptor, type 2, member 1 50834 NM_019599 TAS2R5 taste receptor, type 2, member 5 54429 NM_018980 TBX2 T-box 2 6909 NM_005994 transforming growth factor, beta receptor I (activin A receptor TGFBR1 7046 NM_004612 type II-like kinase, 53kDa)

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TGS1 trimethylguanosine synthase homolog (S. cerevisiae) 96764 NM_024831 TIAM1 T-cell lymphoma invasion and metastasis 1 7074 NM_003253 TM7SF2 transmembrane 7 superfamily member 2 7108 NM_003273 TMEM126A transmembrane protein 126A 84233 NM_032273 TMEM150A transmembrane protein 150A 129303 NM_001031738 TPO thyroid peroxidase 7173 NM_000547 TPP2 tripeptidyl peptidase II 7174 NM_003291 TPSAB1 tryptase alpha/beta 1 7177 NM_003294 TPSB2 tryptase beta 2 64499 NM_024164 TRIM11 tripartite motif-containing 11 81559 NM_145214 TRIM23 tripartite motif-containing 23 373 NM_033228 transient receptor potential cation channel, subfamily M, member TRPM5 29850 NM_014555 5 TUBGCP5 tubulin, gamma complex associated protein 5 114791 NM_052903 TWF1 twinfilin, actin-binding protein, homolog 1 (Drosophila) 5756 NM_002822 TXNL4A thioredoxin-like 4A 10907 NM_006701 UACA uveal autoantigen with coiled-coil domains and ankyrin repeats 55075 NM_001008224 UBE2L6 ubiquitin-conjugating enzyme E2L 6 9246 NM_004223 UGT1A10 UDP glucuronosyltransferase 1 family, polypeptide A10 54575 NM_019075 UGT1A3 UDP glucuronosyltransferase 1 family, polypeptide A3 54659 NM_019093 UGT2B7 UDP glucuronosyltransferase 2 family, polypeptide B7 7364 XM_001128725 USP33 ubiquitin specific peptidase 33 23032 NM_015017 USP8 ubiquitin specific peptidase 8 9101 NM_005154 VCL vinculin 7414 NM_014000 VDAC2 voltage-dependent anion channel 2 7417 NM_003375 YAP1 YES1-associated protein 1, 65kDa 10413 NM_006106 YSK4 yeast Sps1/Ste20-related kinase 4 (S. cerevisiae) 80122 NM_001018046 ZMYND10 zinc finger, MYND-type containing 10 51364 NM_015896 ZNF276 zinc finger protein 276 92822 NM_152287 ZNF326 zinc finger protein 326 284695 NM_182975 ZNF641 zinc finger protein 641 121274 NM_152320

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Table S2:

Gene Full Gene Entrez Antisense siRNA SH4-HASPB- SH4-YES1- RefSeq siRNA ID Symbol Name Gene ID Sequence GFP mCherry

Lipid Metabolism acyl-Coenzyme A AAACUGUUCAUU ACADVL 37 NM_000018 s208 3.4 6.1 dehydrogenase, GACAAUCcc very long chain mevalonate UUUUUAACUGG MVD (diphospho) 4597 NM_002461 s224074 2.8 UCCUGGUGca decarboxylase sphingomyelin phosphodiester UGCUAUGACGC SMPDL3B 27293 NM_014474 s26101 5.0 ase, acid-like GAUGAUGCtt 3B sterol regulatory element binding UUUGACCUUUG SREBF2 6721 NM_004599 s28 2.1 transcription CAUCAUCCaa factor 2 Transport Factors coatomer COPA protein AAAGCGAGUUU 1314 NM_004371 s3369 7.6 5.5 (COPA) complex, UCUCAUCCtt subunit alpha coatomer UGGAUUAGCAU s3371 7.0 4.2 COPB1 protein GACAGACCtt 1315 NM_016451 (COPB1) complex, UCUUUGACUUU s3372 6.1 2.6 subunit beta 1 ACAUCUCCtt UCGAUAUUCUU s18420 2.6 kinesin family UAACUUGCtt KIF20B 9585 NM_016195 member 20B UGCUGAACUAAU s18421 2.6 ACGUUUGgg UUCUUGUAAGU RAN, member s11768 6.5 AACUCUCGat RAN RAS oncogene 5901 NM_006325 UUUCCUGUCCU family s11769 4.8 UAAUAUCCac Protein Phosphorylation PRKCA protein kinase UGCGGAUUUAG 5578 NM_002737 s11093 4.3 3.3 (PRKCA) C, alpha UGUGGAGCgg protein kinase AAAUCGGUCAG PRKCB 5579 NM_212535 s11096 3.3 2.6 C, beta UUUCAUCCgg protein tyrosine UACAUUCGCGU PTPRD phosphatase, 5789 NM_001040712 s11540 2.4 AUCUAUUCtt receptor type, D Other Protein Modifications aspartoacylase UUCGCGAUUAA ACY3 (aminocyclase) 91703 NM_080658 s40752 2.8 3.2 GCAGGUGCcc 3 UDP-N-acetyl- alpha-D- galactosamine: AAAGUUGUCAUA GALNTL4 polypeptide N- 374378 NM_198516 s51536 2.7 UUUGAUGtt acetylgalactosa minyltransferas e-like 4 lipoyl(octanoyl) AAUUGAGAAAUG LIPT2 transferase 2 387787 XM_370636 s226411 5.0 5.3 ACAAUCUat (putative) N(alpha)- acetyltransferas UUUACGUACUU NAA35 60560 NM_024635 s34135 3.9 3.4 e 35, NatC UGCCGUCCat auxiliary subunit

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Membrane Receptors brain-specific UGGAUUGCUAA BAI3 angiogenesis 577 NM_001704 s1878 3.2 GCUCAUUCat inhibitor 3 AGCAGGAGUAG CDH26 cadherin 26 60437 NM_021810 s34067 3.1 2.8 AGUGUAUGtt interleukin 7 UGGUUAGUAAG IL7R 3575 XM_001127146 s7325 2.5 3.5 receptor AUAGGAUCca integrin, alpha V (vitronectin UAGGGUACACU ITGAV receptor, alpha 3685 NM_002210 s7569 4.9 7.1 UCAAGACCag polypeptide, antigen CD51) integrin, beta 1 AGCCGUGUAAC s7575 4.4 3.2 (fibronectin AUUCCUCCag receptor, beta UAAUCGCAAAAC s7576 5.0 3.2 ITGB1 polypeptide, 3688 NM_002211 CAACUGCtg antigen CD29 UGCUGUUCCUU includes MDF2, s7574 3.6 MSK12) UGCUACGGtt leukocyte immunoglobulin -like receptor, AAAAAGAAAGUG LILRB5 subfamily B 10990 NM_006840 s21637 2.4 UCUAUCUga (with TM and ITIM domains), member 5 olfactory receptor, family UCAGGGUCAGG OR10V1 390201 NM_001005324 s52738 2.9 2.5 10, subfamily V, UGAGAAUGga member 1 transforming AGUCUUUCAAC TGFBR1 growth factor, 7046 NM_004612 s14073 5.0 GUAGUACCct beta receptor I Gene Regulation and Expression

eukaryotic UUCACGAACCU s18876 3.3 3.9 translation GAAUAUCCaa EIF4A3 9775 NM_014740 initiation factor UGAUCUGCUUG s18877 4.5 4.0 4A3 AUUGCUCGtt heterogeneous nuclear UUAUCUGGUAC HNRNPA1 3178 NM_002136 s6710 2.4 ribonucleoprotei CAUUAUUCaa n A1 ribosomal UCUUUAAGAACU RPS26P35 protein S26 441377 XM_496991 s54340 3.4 CAGCUCCtt pseudogene 35 ribosomal UAACUUGUUUG RPL21P62 protein L21 442160 XM_001128707 s54494 2.8 UUUACAACaa pseudogene 62 ribosomal UCACAUACAGUU RPS26P8 protein S26 644191 XM_930072 s55596 2.7 UGGGAAGca pseudogene 8 methyl-CpG UGGAUUUCUCG MBD3L2 binding domain 125997 NM_144614 s42925 3.6 UUUCUUCUgt protein 3-like 2 ribosomal RPL23AP8 UCAGGACAAAUC protein L23a 284942 NM_203302 s49770 3.2 2.3 2 AGGGUGGtg pseudogene 82 PHD finger AUAGGAGUCACA PHF5A 84844 NM_032758 s39506 4.2 3.5 protein 5A AAUCACAca polymerase UGGCAGGUAAC s224297 3.7 2.9 (RNA) II (DNA GGCGAAUGat POLR2F 5435 NM_021974 directed) UGUGGUGAUUC s10809 2.7 polypeptide F GCUUCUGGtt PRP8 pre- UCGUUGUUCAC s20796 5.1 8.2 mRNA AUGUAGGGca PRPF8 10594 NM_006445 processing AUGCGAUCAAU s20797 3.7 6.8 factor 8 GUAUCUGCag

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homolog (S. cerevisiae) PRP31 pre- mRNA processing UACUUAUCCCG PRPF31 26121 NM_015629 s25122 2.5 factor 31 GAUGAACUta homolog (S. cerevisiae) UAUAACUUGACC s194744 3.7 ribosomal AACAGCCtc RPL18 6141 NM_000979 protein L18 UAGGAUCCAGG s194745 3.0 GUUAGUUUtt UAUCUCGGCUC s12186 3.0 ribosomal UUAGAGUGct RPL21 6144 NM_000982 protein L21 UAACAUUGUAGA s12187 2.9 CUCUUCCag ribosomal UAAGUUAUUGA RPS25P6 protein S25 401206 XM_937380 s53508 3.8 3.8 GCUUGUCCcg pseudogene 6 splicing factor UCAAUAUCCAGA SF3A1 3a, subunit 1, 10291 NM_001005409 s20117 2.8 CCUGGUGcg 120kDa zinc finger UUCCAUUAAAGC ZNF326 284695 NM_182975 s195972 2.4 protein 326 CCUGAUAag Others alpha-2- UCGUUCUUAAC A2M 2 NM_000014 s819 3.2 2.9 macroglobulin CAUCACUGtg ATPase, H+ transporting, UUUCGGAAAACA ATP6AP2 lysosomal 10159 NM_005765 s19790 2.3 ACAGACCct accessory protein 2 calcium channel, voltage- UUCCGGUUUAU CACNA1S 779 NM_000069 s2297 4.1 dependent, L UUGGGUCCca type, alpha 1S subunit calcium homeostasis UUUGUUCUCUU CHERP endoplasmic 10523 NM_006387 s20627 2.8 3.1 CUCCGAGCct reticulum protein dopamine beta- hydroxylase (dopamine ACUGUGACCAC DBH 1621 NM_000787 s3947 2.7 beta- CUUUCUCCca monooxygenas e) cell division cycle 37 UCUUCAUCAUC CDC37P1 homolog (S. 390688 NM_001080829 s52851 2.9 GCUCAGUGtg cerevisiae) pseudogene 1 melanoma UUUAUACUUAC MAGEB1 antigen family 4112 NM_002363 s8455 2.3 GUAGAAUGaa B, 1 SHC (SRC homology 2 domain AAAUGAGAUAGA SHC1 6464 NM_003029 s12811 4.0 containing) UUGCAUGtg transforming protein 1 sine oculis binding protein AAGUAGUUCGC SOBP 55084 NM_018013 s30136 3.4 3.5 homolog AGUUAUUCtt (Drosophila) TMEM126 transmembrane AAUCCAGUAACU 84233 NM_032273 s38695 2.1 A protein 126A UAAGAUGtt

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YES1- associated UGAUUUAAGAA YAP1 10413 NM_006106 s20367 2.2 protein 1, GUAUCUCUga 65kDa Unknown prostate and UAAUGAUACAUG PATE2 testis 399967 NM_212555 s53217 3.4 3.6 CUCUGCCct expressed 2 chromosome 12 UAGUGGAGCAU C12orf36 open reading 283422 NM_182558 s49233 3.0 GAAGUGUCtt frame 36 chromosome 16 UCUGGAAUCAG C16orf71 open reading 146562 NM_139170 s44876 3.2 GGAGGUUUgg frame 71 family with FAM108A sequence UUAAUUUCCGU 81926 NM_001130111 s230886 2.2 1 similarity 108, UUUCACGUat member A1

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Phenotypic profiling of the human genome reveals gene products involved in plasma membrane targeting of Src kinases

Julia Ritzerfeld, Steffen Remmele, Tao Wang, et al.

Genome Res. published online July 27, 2011 Access the most recent version at doi:10.1101/gr.116087.110

Supplemental http://genome.cshlp.org/content/suppl/2011/07/19/gr.116087.110.DC1 Material

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Accepted Peer-reviewed and accepted for publication but not copyedited or typeset; Manuscript accepted manuscript is likely to differ from the final, published version.

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