Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.

Many disease states result from gene overexpression, often in a specific genetic context. To explore gene overexpression phenotypes systematically, we assembled an array of 5280 yeast strains, each containing an inducible copy of an S. cerevisiae gene, covering >80% of the genome. Approximately 15% of the overexpressed genes (769) reduced growth rate. This gene set was enriched for cell cycle-regulated genes, signaling molecules, and transcription factors. Overexpression of most toxic genes resulted in phenotypes different from known deletion mutant phenotypes, suggesting that overexpression phenotypes usually reflect a specific regulatory imbalance rather than disruption of protein complex stoichiometry. Global overexpression effects were also assayed in the context of a cyclin-dependent kinase mutant (pho85Delta). The resultant gene set was enriched for Pho85p targets and identified the yeast calcineurin-responsive transcription factor Crz1p as a substrate. Large-scale application of this approach should provide a strategy for identifying target molecules regulated by specific signaling pathways.

Discovering target and off-target effects of specific compounds is critical to drug discovery and development. We generated a compendium of "chemical-genetic interaction" profiles by testing the collection of viable yeast haploid deletion mutants for hypersensitivity to 82 compounds and natural product extracts. To cluster compounds with a similar mode-of-action and to reveal insights into the cellular pathways and proteins affected, we applied both a hierarchical clustering and a factorgram method, which allows a gene or compound to be associated with more than one group. In particular, tamoxifen, a breast cancer therapeutic, was found to disrupt calcium homeostasis and phosphatidylserine (PS) was recognized as a target for papuamide B, a cytotoxic lipopeptide with anti-HIV activity. Further, the profile of crude extracts resembled that of its constituent purified natural product, enabling detailed classification of extract activity prior to purification. This compendium should serve as a valuable key for interpreting cellular effects of novel compounds with similar activities.

Several developmental pathways contribute to processes that regulate tissue growth and organ size. The Hippo pathway has emerged as one such critical regulator. However, how Hippo signaling is integrated with other pathways to coordinate these processes remains unclear. Here, we show that the Hippo pathway restricts Wnt/beta-Catenin signaling by promoting an interaction between TAZ and DVL in the cytoplasm. TAZ inhibits the CK1delta/epsilon-mediated phosphorylation of DVL, thereby inhibiting Wnt/beta-Catenin signaling. Abrogation of TAZ levels or Hippo signaling enhances Wnt3A-stimulated DVL phosphorylation, nuclear beta-Catenin, and Wnt target gene expression. Mice lacking Taz develop polycystic kidneys with enhanced cytoplasmic and nuclear beta-Catenin. Moreover, in Drosophila, Hippo signaling modulates Wg target gene expression. These results uncover a cytoplasmic function of TAZ in regulating Wnt signaling and highlight the role of the Hippo pathway in coordinating morphogenetic signaling with growth control.

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases are known to target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisae. Correlation of these motifs with kinase primary sequence has uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P−3 Arg specificity among members of the CMGC group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo, and we identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of new kinase substrates across eukaryotes.

To facilitate large-scale functional studies in Drosophila, the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) was established along with several goals: developing efficient vectors for RNAi that work in all tissues, generating a genome-scale collection of RNAi stocks with input from the community, distributing the lines as they are generated through existing stock centers, validating as many lines as possible using RT-qPCR and phenotypic analyses, and developing tools and web resources for identifying RNAi lines and retrieving existing information on their quality. With these goals in mind, here we describe in detail the various tools we developed and the status of the collection, which is currently composed of 11,491 lines and covering 71% of Drosophila genes. Data on the characterization of the lines either by RT-qPCR or phenotype is available on a dedicated website, the RNAi Stock Validation and Phenotypes Project (RSVP, http://www.flyrnai.org/RSVP.html), and stocks are available from three stock centers, the Bloomington Drosophila Stock Center (United States), National Institute of Genetics (Japan), and TsingHua Fly Center (China). KEYWORDS RNAi; Drosophila; screens; phenotypes; functional genomics A striking finding from the genomic revolution and wholegenome sequencing is the amount of information missing on gene function. Although Drosophila is arguably the bestunderstood multicellular organism and a proven model system for human diseases, mutations mapped to specific genes with readily detectable phenotypes have been isolated for 15% of the .13919 annotated fly coding genes (http:// flybase.org/; FlyBase R6.06). The lack of information on the majority of genes (the "phenotype gap") suggests that researchers have been unable to either assay their roles experimentally and/or resolve issues of functional redundancy. In addition, some phenotypes may be only detected on specific diets and environments. Further, our understanding of the function of many genes for which we have some information is limited by pleiotropy, whereby an earlier function of the gene prevents analysis of later functions.The availability of in vivo RNAi has revolutionized the ability of Drosophila researchers to disrupt the activity of single genes with spatial and temporal resolution (Dietzl et al. 2007; see review by Perrimon et al. 2010), and thus address the phenotype gap. Motivated by the power of the approach and the needs of the community, three large-scale efforts, the Vienna Drosophila RNAi Center (VDRC, http:// stockcenter.vdrc.at/control/main), the National Institute of Genetics (NIG, http://www.shigen.nig.ac.jp/fly/nigfly/index.jsp), and the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) (http://www.flyrnai.org/TRiP-HOME. html) have over the years generated large numbers of RNAi lines that aim to cover all Drosophila genes. These resources are proving invaluable to address a myriad of questions in various biological and biomedical fields including but not limite...

Mapping transcriptional regulatory networks is difficult because many transcription factors (TFs) are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual TFs that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast TFs that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, indicating that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5-TCACGCAA as a binding sequence for Hms1p, a TF that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of TF activities and mapping targets that could be adapted to any organism with transgenic technology.microarray ͉ overexpression ͉ yeast D elineation of transcriptional control networks is critical to understanding how the physiology of cells and organisms is orchestrated. One of the most surprising results of genome sequencing from yeast to vertebrates is the large amount of conserved intergenic sequence, much of which is presumably cis-regulatory (1-3). Moreover, in most sequenced genomes, a correspondingly large proportion of genes appear to encode transcription factors (TFs), typically 3-6% of all genes (4, 5). Even in yeast, a relatively well studied organism, physiological functions and͞or DNA-binding sites remain unknown for roughly half of all apparent sequence-specific DNA-binding TFs (4, 6), suggesting that there are many more transcriptional regulatory pathways than are currently known.Several strategies have been devised to decipher regulatory codes, but none is without caveats. Algorithms that seek conserved promoter elements (1, 2) or common sequence elements in promoters of coexpressed genes (7, 8) can identify potential cis-regulatory sequences, but do not inherently identify the binding TF. Microarray-based biochemical approaches promise to rapidly identify sequence preferences of individual TFs, but additional influences apparently contribute to site occupancy in vivo (9, 10). ChIP-chip (4, 11, 12) identifies sequences bound by a TF in vivo, but positive results often depend on identifying conditions under which the TF is DNA-bound; moreover, bound sites may not be active (13).Artificial activation of TFs by genetic modification is a promising experimental strategy for demonstrating functionality of TFs in vivo without knowing the natural condition under which the TF acts. Devaux et al. (14) showed a nearly perfect correspondence between the target genes activated by a well studied gain-of-function mutation in PDR1 (PDR1-3), and those activated by an inducible fusion protein consisting of the Pdr1p DNA-binding domain (DBD) an...

The tuberous sclerosis complex (TSC) family of tumor suppressors, TSC1 and TSC2, function together in an evolutionarily conserved protein complex that is a point of convergence for major cell signaling pathways that regulate mTOR complex 1 (mTORC1). Mutation or aberrant inhibition of the TSC complex is common in various human tumor syndromes and cancers. The discovery of novel therapeutic strategies to selectively target cells with functional loss of this complex is therefore of clinical relevance to patients with nonmalignant TSC and those with sporadic cancers. We developed a CRISPR-based method to generate homogeneous mutant Drosophila cell lines. By combining TSC1 or TSC2 mutant cell lines with RNAi screens against all kinases and phosphatases, we identified synthetic interactions with TSC1 and TSC2. Individual knockdown of three candidate genes (mRNA-cap, Pitslre, and CycT; orthologs of RNGTT, CDK11, and CCNT1 in humans) reduced the population growth rate of Drosophila cells lacking either TSC1 or TSC2 but not that of wild-type cells. Moreover, individual knockdown of these three genes had similar growth-inhibiting effects in mammalian TSC2-deficient cell lines, including human tumor-derived cells, illustrating the power of this cross-species screening strategy to identify potential drug targets.