A key goal of biology is to construct networks that predict complex system behavior. We combine multiple types of molecular data, including genotypic, expression, transcription factor binding site (TFBS), and protein-protein interaction (PPI) data previously generated from a number of yeast experiments, in order to reconstruct causal gene networks. Networks based on different types of data are compared using metrics devised to assess the predictive power of a network. We show that a network reconstructed by integrating genotypic, TFBS and PPI data is the most predictive. This network is used to predict causal regulators responsible for hot spots of gene expression activity in a segregating yeast population. We also show that the network can elucidate the mechanisms by which causal regulators give rise to larger-scale changes in gene expression activity. We then prospectively validate predictions, providing direct experimental evidence that predictive networks can be constructed by integrating multiple, appropriate data types.
Peptide recognition modules mediate many protein-protein interactions critical for the assembly of macromolecular complexes. Complete genome sequences have revealed thousands of these domains, requiring improved methods for identifying their physiologically relevant binding partners. We have developed a strategy combining computational prediction of interactions from phage-display ligand consensus sequences with large-scale two-hybrid physical interaction tests. Application to yeast SH3 domains generated a phage-display network containing 394 interactions among 206 proteins and a two-hybrid network containing 233 interactions among 145 proteins. Graph theoretic analysis identified 59 highly likely interactions common to both networks. Las17 (Bee1), a member of the Wiskott-Aldrich Syndrome protein (WASP) family of actin-assembly proteins, showed multiple SH3 interactions, many of which were confirmed in vivo by coimmunoprecipitation.
Pathogenicity in Francisella tularensis subspecies .Sequencing of the non-pathogenic
Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed.
Abstract. Sequence analysis of chromosome IX of Saccharomyces cerevisiae revealed an open reading frame of 166 residues, designated TPM2, having 64.5 % sequence identity to
BackgroundCharacterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.ResultsWe demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.ConclusionsHS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1479-3) contains supplementary material, which is available to authorized users.
Genetic selections were used to find peptides that inhibit biological pathways in budding yeast. The peptides were presented inside cells as peptamers, surface loops on a highly expressed and biologically inert carrier protein, a catalytically inactive derivative of staphylococcal nuclease. Peptamers that inhibited the pheromone signaling pathway, transcriptional silencing, and the spindle checkpoint were isolated. Putative targets for the inhibitors were identified by a combination of two-hybrid analysis and genetic dissection of the target pathways. This analysis identified Ydr517w as a component of the spindle checkpoint and reinforced earlier indications that Ste50 has both positive and negative roles in pheromone signaling. Analysis of transcript arrays showed that the peptamers were highly specific in their effects, which suggests that they may be useful reagents in organisms that lack sophisticated genetics as well as for identifying components of existing biological pathways that are potential targets for drug discovery.
Cytokinesis in Saccharomyces cerevisiae involves coordination between actomyosin ring contraction and septum formation and/or targeted membrane deposition. We show that Mlc1p, a light chain for Myo2p (type V myosin) and Iqg1p (IQGAP), is the essential light chain for Myo1p, the only type II myosin in S. cerevisiae. However, disruption or reduction of Mlc1p–Myo1p interaction by deleting the Mlc1p binding site on Myo1p or by a point mutation in MLC1, mlc1-93, did not cause any obvious defect in cytokinesis. In contrast, a different point mutation, mlc1-11, displayed defects in cytokinesis and in interactions with Myo2p and Iqg1p. These data suggest that the major function of the Mlc1p–Myo1p interaction is not to regulate Myo1p activity but that Mlc1p may interact with Myo1p, Iqg1p, and Myo2p to coordinate actin ring formation and targeted membrane deposition during cytokinesis. We also identify Mlc2p as the regulatory light chain for Myo1p and demonstrate its role in Myo1p ring disassembly, a function likely conserved among eukaryotes.
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