Alex N. Nguyen Ba

A high-definition view of functional genetic variation from natural yeast genomes

The question of how genetic variation in a population influences phenotypic variation and evolution is of major importance in modern biology. Yet much is still unknown about the relative functional importance of different forms of genome variation and how they are shaped by evolutionary processes. Here we address these questions by population level sequencing of 42 strains from the budding yeast Saccharomyces cerevisiae and its closest relative S. paradoxus. We find that genome content variation, in the form of presence or absence as well as copy number of genetic material, is higher within S. cerevisiae than within S. paradoxus, despite genetic distances as measured in single-nucleotide polymorphisms being vastly smaller within the former species. This genome content variation, as well as loss-of-function variation in the form of premature stop codons and frameshifting indels, is heavily enriched in the subtelomeres, strongly reinforcing the relevance of these regions to functional evolution. Genes affected by these likely functional forms of variation are enriched for functions mediating interaction with the external environment (sugar transport and metabolism, flocculation, metal transport, and metabolism). Our results and analyses provide a comprehensive view of genomic diversity in budding yeast and expose surprising and pronounced differences between the variation within S. cerevisiae and that within S. paradoxus. We also believe that the sequence data and de novo assemblies will constitute a useful resource for further evolutionary and population genomics studies.

Proteome-wide discovery of evolutionary conserved sequences in disordered regions.

A statistical analysis method can identify short, functionally important linear motifs in disordered regions of proteins. Finding the Hidden Meaning in Disordered Regions Many proteins, including those involved in signal transduction, have large disordered regions, in addition to their clearly defined domains or motifs. Although these disordered regions are functionally important, identifying the important residues in these regions has proved challenging because the regions are not visualized in crystal structures and tend to exhibit high sequence divergence. Nguyen Ba et al. modified the phylogenetic hidden Markov model so that it could be applied to these disordered regions. Application of this method to yeast proteins not only revealed the presence of known short conserved motifs in proteins not known to have these motifs but also predicted previously unknown short conserved motifs. Experimental analysis suggested that both sets of motifs were functionally important. Thus, this approach should provide an effective method for discovering biologically important conserved motifs within the disordered regions of proteins. At least 30% of human proteins are thought to contain intrinsically disordered regions, which lack stable structural conformation. Despite lacking enzymatic functions and having few protein domains, disordered regions are functionally important for protein regulation and contain short linear motifs (short peptide sequences involved in protein-protein interactions), but in most disordered regions, the functional amino acid residues remain unknown. We searched for evolutionarily conserved sequences within disordered regions according to the hypothesis that conservation would indicate functional residues. Using a phylogenetic hidden Markov model (phylo-HMM), we made accurate, specific predictions of functional elements in disordered regions even when these elements are only two or three amino acids long. Among the conserved sequences that we identified were previously known and newly identified short linear motifs, and we experimentally verified key examples, including a motif that may mediate interaction between protein kinase Cbk1 and its substrates. We also observed that hub proteins, which interact with many partners in a protein interaction network, are highly enriched in these conserved sequences. Our analysis enabled the systematic identification of the functional residues in disordered regions and suggested that at least 5% of amino acids in disordered regions are important for function.

Evolution of Characterized Phosphorylation Sites in Budding Yeast

Phosphorylation is one of the most studied and important regulatory mechanisms that modulate protein function in eukaryotic cells. Recently, several studies have investigated the evolution of phosphorylation sites identified by high-throughput methods. These studies have revealed varying degrees of evidence for constraint and plasticity, and therefore, there is currently no consensus as to the evolutionary properties of this important regulatory mechanism. Here, we present a study of high-confidence annotated sites from budding yeast and show that these sites are significantly constrained compared with their flanking region in closely related species. We show that this property does not change in structured or unstructured regions. We investigate the birth, death and compensation rates of the phosphorylation sites and test if sites are more likely to be gained or lost in proteins with greater numbers of sites. Finally, we also show that this evolutionary conservation can yield significant improvement for kinase target predictions when the kinase recognition motif is known, and can be used to infer the recognition motif when a set of targets is known. Our analysis indicates that phosphorylation sites are under selective constraint, consistent with their functional importance. We also find that a small fraction of phosphorylation sites turnover during evolution, which may be an important process underlying the evolution of regulatory networks.

High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome

BackgroundComparative genomics is a formidable tool to identify functional elements throughout a genome. In the past ten years, studies in the budding yeast Saccharomyces cerevisiae and a set of closely related species have been instrumental in showing the benefit of analyzing patterns of sequence conservation. Increasing the number of closely related genome sequences makes the comparative genomics approach more powerful and accurate.ResultsHere, we report the genome sequence and analysis of Saccharomyces arboricolus, a yeast species recently isolated in China, that is closely related to S. cerevisiae. We obtained high quality de novo sequence and assemblies using a combination of next generation sequencing technologies, established the phylogenetic position of this species and considered its phenotypic profile under multiple environmental conditions in the light of its gene content and phylogeny.ConclusionsWe suggest that the genome of S. arboricolus will be useful in future comparative genomics analysis of the Saccharomyces sensu stricto yeasts.

A quantitative literature-curated gold standard for kinase-substrate pairs

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/ ), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.

The Structure of an NDR/LATS Kinase-Mob Complex Reveals a Novel Kinase-Coactivator System and Substrate Docking Mechanism.

Eukaryotic cells commonly use protein kinases in signaling systems that relay information and control a wide range of processes. These enzymes have a fundamentally similar structure, but achieve functional diversity through variable regions that determine how the catalytic core is activated and recruited to phosphorylation targets. “Hippo” pathways are ancient protein kinase signaling systems that control cell proliferation and morphogenesis; the NDR/LATS family protein kinases, which associate with “Mob” coactivator proteins, are central but incompletely understood components of these pathways. Here we describe the crystal structure of budding yeast Cbk1–Mob2, to our knowledge the first of an NDR/LATS kinase–Mob complex. It shows a novel coactivator-organized activation region that may be unique to NDR/LATS kinases, in which a key regulatory motif apparently shifts from an inactive binding mode to an active one upon phosphorylation. We also provide a structural basis for a substrate docking mechanism previously unknown in AGC family kinases, and show that docking interaction provides robustness to Cbk1’s regulation of its two known in vivo substrates. Co-evolution of docking motifs and phosphorylation consensus sites strongly indicates that a protein is an in vivo regulatory target of this hippo pathway, and predicts a new group of high-confidence Cbk1 substrates that function at sites of cytokinesis and cell growth. Moreover, docking peptides arise in unstructured regions of proteins that are probably already kinase substrates, suggesting a broad sequential model for adaptive acquisition of kinase docking in rapidly evolving intrinsically disordered polypeptides.

Detecting Functional Divergence after Gene Duplication through Evolutionary Changes in Posttranslational Regulatory Sequences

Gene duplication is an important evolutionary mechanism that can result in functional divergence in paralogs due to neo-functionalization or sub-functionalization. Consistent with functional divergence after gene duplication, recent studies have shown accelerated evolution in retained paralogs. However, little is known in general about the impact of this accelerated evolution on the molecular functions of retained paralogs. For example, do new functions typically involve changes in enzymatic activities, or changes in protein regulation? Here we study the evolution of posttranslational regulation by examining the evolution of important regulatory sequences (short linear motifs) in retained duplicates created by the whole-genome duplication in budding yeast. To do so, we identified short linear motifs whose evolutionary constraint has relaxed after gene duplication with a likelihood-ratio test that can account for heterogeneity in the evolutionary process by using a non-central chi-squared null distribution. We find that short linear motifs are more likely to show changes in evolutionary constraints in retained duplicates compared to single-copy genes. We examine changes in constraints on known regulatory sequences and show that for the Rck1/Rck2, Fkh1/Fkh2, Ace2/Swi5 paralogs, they are associated with previously characterized differences in posttranslational regulation. Finally, we experimentally confirm our prediction that for the Ace2/Swi5 paralogs, Cbk1 regulated localization was lost along the lineage leading to SWI5 after gene duplication. Our analysis suggests that changes in posttranslational regulation mediated by short regulatory motifs systematically contribute to functional divergence after gene duplication.

Polymorphism Analysis Reveals Reduced Negative Selection and Elevated Rate of Insertions and Deletions in Intrinsically Disordered Protein Regions

Intrinsically disordered protein regions are abundant in eukaryotic proteins and lack stable tertiary structures and enzymatic functions. Previous studies of disordered region evolution based on interspecific alignments have revealed an increased propensity for indels and rapid rates of amino acid substitution. How disordered regions are maintained at high abundance in the proteome and across taxa, despite apparently weak evolutionary constraints, remains unclear. Here, we use single nucleotide and indel polymorphism data in yeast and human populations to survey the population variation within disordered regions. First, we show that single nucleotide polymorphisms in disordered regions are under weaker negative selection compared with more structured protein regions and have a higher proportion of neutral non-synonymous sites. We also confirm previous findings that nonframeshifting indels are much more abundant in disordered regions relative to structured regions. We find that the rate of nonframeshifting indel polymorphism in intrinsically disordered regions resembles that of noncoding DNA and pseudogenes, and that large indels segregate in disordered regions in the human population. Our survey of polymorphism confirms patterns of evolution in disordered regions inferred based on longer evolutionary comparisons.

Predicting kinase substrates using conservation of local motif density

MOTIVATION Protein kinases represent critical links in cell signaling. A central problem in computational biology is to systematically identify their substrates. RESULTS This study introduces a new method to predict kinase substrates by extracting evolutionary information from multiple sequence alignments in a manner that is tolerant to degenerate motif positioning. Given a known consensus, the new method (ConDens) compares the observed density of matches to a null model of evolution and does not require labeled training data. We confirmed that ConDens has improved performance compared with several existing methods in the field. Further, we show that it is generalizable and can predict interesting substrates for several important eukaryotic kinases where training data is not available. AVAILABILITY AND IMPLEMENTATION ConDens can be found at http://www.moseslab.csb.utoronto.ca/andyl/. CONTACT alan.moses@utoronto.ca SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Functional Analysis of Kinases and Transcription Factors in Saccharomyces cerevisiae Using an Integrated Overexpression Library

Kinases and transcription factors (TFs) are key modulators of important signaling pathways and their activities underlie the proper function of many basic cellular processes such as cell division, differentiation, and development. Changes in kinase and TF dosage are often associated with disease, yet a systematic assessment of the cellular phenotypes caused by the combined perturbation of kinases and TFs has not been undertaken. We used a reverse-genetics approach to study the phenotypic consequences of kinase and TF overexpression (OE) in the budding yeast, Saccharomyces cerevisiae. We constructed a collection of strains expressing stably integrated inducible alleles of kinases and TFs and used a variety of assays to characterize the phenotypes caused by TF and kinase OE. We used the Synthetic Genetic Array (SGA) method to examine dosage-dependent genetic interactions (GIs) between 239 gain-of-function (OE) alleles of TFs and six loss-of-function (LOF) and seven OE kinase alleles, the former identifying Synthetic Dosage Lethal (SDL) interactions and the latter testing a GI we call Double Dosage Lethality (DDL). We identified and confirmed 94 GIs between 65 OE alleles of TFs and 9 kinase alleles. Follow-up experiments validated regulatory relationships between genetically interacting pairs (Cdc28–Stb1 and Pho85–Pdr1), suggesting that GI studies involving OE alleles of regulatory proteins will be a rich source of new functional information.