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.
During transcription initiation by bacterial RNA polymerase, the sigma subunit recognizes the -35 and -10 promoter elements; free sigma, however, does not bind DNA. We selected ssDNA aptamers that strongly and specifically bound free sigma(A) from Thermus aquaticus. A consensus sequence, GTA(C/T)AATGGGA, was required for aptamer binding to sigma(A), with the TA(C/T)AAT segment making interactions similar to those made by the -10 promoter element (consensus sequence TATAAT) in the context of RNA polymerase holoenzyme. When in dsDNA form, the aptamers function as strong promoters for the T. aquaticus RNA polymerase sigma(A) holoenzyme. Recognition of the aptamer-based promoters depends on the downstream GGGA motif from the aptamers' common sequence, which is contacted by sigma(A) region 1.2 and directs transcription initiation even in the absence of the -35 promoter element. Thus, recognition of bacterial promoters is controlled by independent interactions of sigma with multiple basal promoter elements.
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 analytical 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.
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.
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