Assessing the functional structure of genomic data

Motivation: The availability of genome-scale data has enabled an abundance of novel analysis techniques for investigating a variety of systems-level biological relationships. As thousands of such datasets become available, they provide an opportunity to study high-level associations between cellular pathways and processes. This also allows the exploration of shared functional enrichments between diverse biological datasets, and it serves to direct experimenters to areas of low data coverage or with high probability of new discoveries

A new, highly conserved domain in Swi2/Snf2 is required for SWI/SNF remodeling

SWI/SNF is an ATP-dependent remodeler that mobilizes nucleosomes and has important roles in gene regulation. The catalytic subunit of SWI/SNF has an ATP-dependent DNA translocase domain that is essential for remodeling. Besides the DNA translocase domain there are other domains in the catalytic subunit of SWI/SNF that have important roles in mobilizing nucleosomes. One of these domains, termed SnAC (Snf2 ATP Coupling), is conserved in all eukaryotic SWI/SNF complexes and is located between the ATPase and A-T hook domains. Here, we show that the SnAC domain is essential for SWI/SNF activity. The SnAC domain is not required for SWI/SNF complex integrity, efficient nucleosome binding, or recruitment by acidic transcription activators. The SnAC domain is however required in vivo for transcription regulation by SWI/SNF as seen by alternative carbon source growth assays, northern analysis, and genome-wide expression profiling. The ATPase and nucleosome mobilizing activities of SWI/SNF are severely affected when the SnAC domain is removed or mutated. The SnAC domain positively regulates the catalytic activity of the ATPase domain of SWI/SNF to hydrolyze ATP without significantly affecting its affinity for ATP

Minimal components of the RNA polymerase II transcription apparatus determine the consensus TATA box

In Saccharomyces cerevisiae, multiple approaches have arrived at a consensus TATA box sequence of TATA(T/A)A(A/T)(A/G). TATA-binding protein (TBP) affinity alone does not determine TATA box function. To discover how a minimal set of factors required for basal and activated transcription contributed to the sequence requirements for a functional TATA box, we performed transcription reactions using highly purified proteins and CYC1 promoter TATA box mutants. The TATA box consensus sequence is a good predictor of promoter activity. However, several nonconsensus sequences are almost fully functional, indicating that mechanistic requirements are not the only selective pressure on the TATA box. We also found that the effect of a mutation at a certain position is often dependent on other bases within a particular TATA box. Although activators and coactivators strongly influence TBP recruitment and stability at promoters, neither Mediator, the activator Gal4-V16, nor TFIID specifically compensate for the low transcription levels of the weak TATA boxes. The addition of Mediator to purified transcription reactions did, however, increase the functional selectivity for certain consensus TATA sequences. Transcription in whole-cell extracts or in vivo with these TATA box mutants indicated that factors, other than those in our purified system, may help initiate transcription from weak TATA boxes

Systematic Planning of Genome-Scale Experiments in Poorly Studied Species

Genome-scale datasets have been used extensively in model organisms to screen for specific candidates or to predict functions for uncharacterized genes. However, despite the availability of extensive knowledge in model organisms, the planning of genome-scale experiments in poorly studied species is still based on the intuition of experts or heuristic trials. We propose that computational and systematic approaches can be applied to drive the experiment planning process in poorly studied species based on available data and knowledge in closely related model organisms. In this paper, we suggest a computational strategy for recommending genome-scale experiments based on their capability to interrogate diverse biological processes to enable protein function assignment. To this end, we use the data-rich functional genomics compendium of the model organism to quantify the accuracy of each dataset in predicting each specific biological process and the overlap in such coverage between different datasets. Our approach uses an optimized combination of these quantifications to recommend an ordered list of experiments for accurately annotating most proteins in the poorly studied related organisms to most biological processes, as well as a set of experiments that target each specific biological process. The effectiveness of this experiment- planning system is demonstrated for two related yeast species: the model organism Saccharomyces cerevisiae and the comparatively poorly studied Saccharomyces bayanus. Our system recommended a set of S. bayanus experiments based on an S. cerevisiae microarray data compendium. In silico evaluations estimate that less than 10% of the experiments could achieve similar functional coverage to the whole microarray compendium. This estimation was confirmed by performing the recommended experiments in S. bayanus, therefore significantly reducing the labor devoted to characterize the poorly studied genome. This experiment-planning framework could readily be adapted to the design of other types of large-scale experiments as well as other groups of organisms

Inferring Condition-Specific Modulation of Transcription Factor Activity in Yeast through Regulon-Based Analysis of Genomewide Expression

Background: A key goal of systems biology is to understand how genomewide mRNA expression levels are controlled by transcription factors (TFs) in a condition-specific fashion. TF activity is frequently modulated at the post-translational level through ligand binding, covalent modification, or changes in sub-cellular localization. In this paper, we demonstrate how prior information about regulatory network connectivity can be exploited to infer condition-specific TF activity as a hidden variable from the genomewide mRNA expression pattern in the yeast Saccharomyces cerevisiae. Methodology/Principal Findings: We first validate experimentally that by scoring differential expression at the level of gene sets or "regulons" comprised of the putative targets of a TF, we can accurately predict modulation of TF activity at the post-translational level. Next, we create an interactive database of inferred activities for a large number of TFs across a large number of experimental conditions in S. cerevisiae. This allows us to perform TF-centric analysis of the yeast regulatory network. Conclusions/Significance: We analyze the degree to which the mRNA expression level of each TF is predictive of its regulatory activity. We also organize TFs into "co-modulation networks" based on their inferred activity profile across conditions, and find that this reveals functional and mechanistic relationships. Finally, we present evidence that the PAC and rRPE motifs antagonize TBP-dependent regulation, and function as core promoter elements governed by the transcription regulator NC2. Regulon-based monitoring of TF activity modulation is a powerful tool for analyzing regulatory network function that should be applicable in other organisms. Tools and results are available online at http://bussemakerlab.org/RegulonProfiler/

DOD Weapon System Cybersecurity: How Effective?

Naval Postgraduate School Acquisition Research Progra

Factors controlling internal initiation of transcription at PRY3 in budding yeast

Transcription initiation from within the coding regions of genes has been observed in budding yeast as a natural phenomenon induced by environmental changes. However, such ‘internal initiation’ events have also been observed in mutant yeast strains with aberrant chromatin structure. Failure to suppress initiation from cryptic internal promoters is thought to result from either loss of appropriate nucleosome density or loss of appropriate histone modifications in the coding region. PRY3 is a gene previously shown to undergo internal initiation in response to mating pheromone. This project aimed to uncover which factors are involved in suppressing inappropriate transcription initiation from an internal TATA-box at PRY3 in the absence of mating pheromone. This work demonstrates that factors controlling nucleosome density (Spt6, Spn1 and Spt10) but not histone deacetylation (Eaf3) are required to suppress internal initiation at PRY3 in the absence of mating pheromone. In addition, TATA-box binding protein (TBP) is required for internal initiation at PRY3. Taken together, these results indicate that internal initiation at PRY3 is predominantly suppressed by a nucleosome reassembly mechanism rather than histone modifications, and suggest that the transcriptional output at PRY3 is controlled by competition between TBP and nucleosomes for binding an internal TATA-box

Changes in genomewide occupancy of core transcriptional regulators during heat stress

Organisms respond to heat stress by reprogramming gene expression. In Saccharomyces cerevisiae, heat-induced genes tend to be regulated by factors that belong to the Spt-Ada-Gcn5 acetyltransferase (SAGA) transcription regulatory pathway, whereas heat-repressed genes tend to be regulated by a parallel pathway involving transcription factor IID (TFIID). Here, we examine whether heat stress affects the occupancy of representative factors of each pathway at promoter regions throughout the yeast genome. Representatives of the SAGA pathway include the TATA binding protein, Spt3, and Mot1. Representatives of the TFIID pathway include the TATA binding protein, TAF1, and Bdf1. We find that heat stress causes disassembly of the TFIID pathway at genes that are inhibited by stress. In contrast, heat induces assembly of the SAGA pathway at stress-induced genes, although many also assemble along the TFIID pathway. Other genes were found to assemble almost exclusively along the TFIID pathway. Strikingly, these genes are lowly transcribed and are generally not induced. Thus, heat stress leads to factor assembly along each pathway but with distinct transcriptional outcomes. Further investigation of these pathways reveals that Bdf1 and Mot1 negatively regulate the SAGA pathway in different ways. The findings suggest that Bdf1 blocks assembly, whereas Mot1 promotes disassembly of the transcription machinery