Dataset Information

Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions.

ABSTRACT: BACKGROUND: The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability in bacterial populations and is gained through lateral gene transfer, allowing subpopulations of bacteria to better adapt to specific niches. Low-cost and high-throughput sequencing platforms have created an exponential increase in genome sequence data and an opportunity to study the pan-genomes of many bacterial species. In this study, we describe a new online pan-genome sequence analysis program, Panseq. RESULTS: Panseq was used to identify Escherichia coli O157:H7 and E. coli K-12 genomic islands. Within a population of 60 E. coli O157:H7 strains, the existence of 65 accessory genomic regions identified by Panseq analysis was confirmed by PCR. The accessory genome and binary presence/absence data, and core genome and single nucleotide polymorphisms (SNPs) of six L. monocytogenes strains were extracted with Panseq and hierarchically clustered and visualized. The nucleotide core and binary accessory data were also used to construct maximum parsimony (MP) trees, which were compared to the MP tree generated by multi-locus sequence typing (MLST). The topology of the accessory and core trees was identical but differed from the tree produced using seven MLST loci. The Loci Selector module found the most variable and discriminatory combinations of four loci within a 100 loci set among 10 strains in 1 s, compared to the 449 s required to exhaustively search for all possible combinations; it also found the most discriminatory 20 loci from a 96 loci E. coli O157:H7 SNP dataset. CONCLUSION: Panseq determines the core and accessory regions among a collection of genomic sequences based on user-defined parameters. It readily extracts regions unique to a genome or group of genomes, identifies SNPs within shared core genomic regions, constructs files for use in phylogeny programs based on both the presence/absence of accessory regions and SNPs within core regions and produces a graphical overview of the output. Panseq also includes a loci selector that calculates the most variable and discriminatory loci among sets of accessory loci or core gene SNPs. AVAILABILITY: Panseq is freely available online at http://76.70.11.198/panseq. Panseq is written in Perl.

SUBMITTER: Laing C

PROVIDER: S-EPMC2949892 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions.

Laing Chad C Buchanan Cody C Taboada Eduardo N EN Zhang Yongxiang Y Kropinski Andrew A Villegas Andre A Thomas James E JE Gannon Victor P J VP

BMC bioinformatics 20100915

<h4>Background</h4>The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability in bacterial populations and is gained through lateral gene transfer, allowing subpopulations of bacteria to better adapt to specific niches. Low-cost and high-throughput sequencing platforms have created an exponential increase in genome sequence data and an opportunity to study the pan-genomes of many bacterial ...[more]

PMID: 20843356

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Project description:MotivationThe Human Reference Epigenome Map, generated by the Roadmap Epigenomics Consortium, contains thousands of genome-wide epigenomic datasets that describe epigenomes of a variety of different human tissue and cell types. This map has allowed investigators to obtain a much deeper and more comprehensive view of our regulatory genome, e.g. defining regulatory elements including all promoters and enhancers for a given tissue or cell type. An outstanding task is to combine and compare different epigenomes in order to identify regions with epigenomic features specific to certain types of tissues or cells, e.g. lineage-specific regulatory elements. Currently available tools do not directly address this question. This need motivated us to develop a tool that allows investigators to easily identify regions with epigenetic features unique to specific epigenomes that they choose, making detection of common regulatory elements and/or cell type-specific regulatory elements an interactive and dynamic experience.ResultsAn online tool EpiCompare was developed to assist investigators in exploring the specificity of epigenomic features across selected tissue and cell types. Investigators can design their test by choosing different combinations of epigenomes, and choosing different classification algorithms provided by our tool. EpiCompare will then identify regions with specified epigenomic features, and provide a quality assessment of the predictions. Investigators can interact with EpiCompare by investigating Roadmap Epigenomics data, or uploading their own data for comparison. We demonstrate that by using specific combinations of epigenomes we can detect developmental lineage-specific enhancers. Finally, prediction results can be readily visualized and further explored in the WashU Epigenome Browser.Availability and implementationEpiCompare is freely available on the web at http://epigenome.wustl.edu/EpiCompare/.Contacttwang@genetics.wustl.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

Project description:BACKGROUND:Rapidly accumulating genome sequence data from multiple species offer powerful opportunities for the detection of DNA sequence evolution. Phylogenetic tree construction and codon-based tests for natural selection are the prevailing tools used to detect functionally important evolutionary change in protein coding sequences. These analyses often require multiple DNA sequence alignments that maintain the correct reading frame for each collection of putative orthologous sequences. Since this feature is not available in most alignment tools, codon reading frames often must be checked manually before evolutionary analyses can commence. RESULTS:Here we report an online codon-preserved alignment tool (OCPAT) that generates multiple sequence alignments automatically from the coding sequences of any list of human gene IDs and their putative orthologs from genomes of other vertebrate tetrapods. OCPAT is programmed to extract putative orthologous genes from genomes and to align the orthologs with the reading frame maintained in all species. OCPAT also optimizes the alignment by trimming the most variable alignment regions at the 5' and 3' ends of each gene. The resulting output of alignments is returned in several formats, which facilitates further molecular evolutionary analyses by appropriate available software. Alignments are generally robust and reliable, retaining the correct reading frame. The tool can serve as the first step for comparative genomic analyses of protein-coding gene sequences including phylogenetic tree reconstruction and detection of natural selection. We aligned 20,658 human RefSeq mRNAs using OCPAT. Most alignments are missing sequence(s) from at least one species; however, functional annotation clustering of the ~1700 transcripts that were alignable to all species shows that genes involved in multi-subunit protein complexes are highly conserved. CONCLUSION:The OCPAT program facilitates large-scale evolutionary and phylogenetic analyses of entire biological processes, pathways, and diseases.

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Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions.

Publications

Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions.

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