Elena D. Stavrovskaya

RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

BackgroundGenome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria.ResultsTo explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).ConclusionsWe tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S. oneidensis MR-1. Analysis of correlations in gene expression patterns helps to interpret the reconstructed regulatory network. The inferred regulatory interactions will provide an additional regulatory constrains for an integrated model of metabolism and regulation in S. oneidensis MR-1.

Integrated Analysis of Whole-Genome ChIP-Seq and RNA-Seq Data of Primary Head and Neck Tumor Samples Associates HPV Integration Sites with Open Chromatin Marks

Chromatin alterations mediate mutations and gene expression changes in cancer. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has been utilized to study genome-wide chromatin structure in human cancer cell lines, yet numerous technical challenges limit comparable analyses in primary tumors. Here we have developed a new whole-genome analytic pipeline to optimize ChIP-Seq protocols on patient-derived xenografts from human papillomavirus-related (HPV+) head and neck squamous cell carcinoma (HNSCC) samples. We further associated chromatin aberrations with gene expression changes from a larger cohort of the tumor and normal samples with RNA-Seq data. We detect differential histone enrichment associated with tumor-specific gene expression variation, sites of HPV integration in the human genome, and HPV-associated histone enrichment sites upstream of cancer driver genes, which play central roles in cancer-associated pathways. These comprehensive analyses enable unprecedented characterization of the complex network of molecular changes resulting from chromatin alterations that drive HPV-related tumorigenesis. Cancer Res; 77(23); 6538-50. ©2017 AACR.

StereoGene: rapid estimation of genome-wide correlation of continuous or interval feature data

Motivation Genomics features with similar genome‐wide distributions are generally hypothesized to be functionally related, for example, colocalization of histones and transcription start sites indicate chromatin regulation of transcription factor activity. Therefore, statistical algorithms to perform spatial, genome‐wide correlation among genomic features are required. Results Here, we propose a method, StereoGene, that rapidly estimates genome‐wide correlation among pairs of genomic features. These features may represent high‐throughput data mapped to reference genome or sets of genomic annotations in that reference genome. StereoGene enables correlation of continuous data directly, avoiding the data binarization and subsequent data loss. Correlations are computed among neighboring genomic positions using kernel correlation. Representing the correlation as a function of the genome position, StereoGene outputs the local correlation track as part of the analysis. StereoGene also accounts for confounders such as input DNA by partial correlation. We apply our method to numerous comparisons of ChIP‐Seq datasets from the Human Epigenome Atlas and FANTOM CAGE to demonstrate its wide applicability. We observe the changes in the correlation between epigenomic features across developmental trajectories of several tissue types consistent with known biology and find a novel spatial correlation of CAGE clusters with donor splice sites and with poly(A) sites. These analyses provide examples for the broad applicability of StereoGene for regulatory genomics. Availability and implementation The StereoGene C ++ source code, program documentation, Galaxy integration scripts and examples are available from the project homepage http://stereogene.bioinf.fbb.msu.ru/ Contact favorov@sensi.org Supplementary information Supplementary data are available at Bioinformatics online.

Chromatin and Polycomb: Biology and bioinformatics

All cells of a multicellular eukaryotic organism carry almost the same genome, still they obviously demonstrate phenotypes of very divergent kinds. The most probable explanation of the divergence is that different groups of genes are expressed in cells of different types. Expression is regulated at all steps between DNA and a protein, but transcription regulation is the most common regulatory mechanism. Transcription factors, which bind to specific areas of chromatin, can mediate the regulation. Their binding depends on the chromatin structure, which drastically differs among cell types. The key role in the structural organization is played by covalent histone modifications in chromatin. A combination of particular modifications in a chromatin region determines its structure and, consequently, its accessibility for enzymes. The best studied histone modifications are described in the review. Each modification has its specific mechanism that the cell uses to establish or to eliminate it. Activity of various Polycomb complexes is a key mechanism that represses chromatin and plays a central role, for example, in cell differentiation. The compositions and functionality of Polycomb complexes in various species are considered. Owing to modern experimental techniques, ample data are currently available for histone modifications and other epigenomic features of chromatin in various tissues and organisms, allowing bioinformatic investigation of the epigenome. Many computational and visualization methods have been developed for such studies, and the main of them are covered in the review.