Defining bacterial regulons using ChIP-seq
•ChIP-seq is a powerful method for identifying transcription factor binding in vivo.•Correlation of ChIP-seq and transcriptomic data can identify bacterial regulons.•An overview of ChIP-seq methodology and data analysis in bacteria is provided.•ChIP-seq sample preparation, data analysis, and computa...
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Veröffentlicht in: | Methods (San Diego, Calif.) Calif.), 2015-09, Vol.86 (C), p.80-88 |
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creator | Myers, Kevin S. Park, Dan M. Beauchene, Nicole A. Kiley, Patricia J. |
description | •ChIP-seq is a powerful method for identifying transcription factor binding in vivo.•Correlation of ChIP-seq and transcriptomic data can identify bacterial regulons.•An overview of ChIP-seq methodology and data analysis in bacteria is provided.•ChIP-seq sample preparation, data analysis, and computational analyses are reviewed.
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein–DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data. |
doi_str_mv | 10.1016/j.ymeth.2015.05.022 |
format | Article |
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Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein–DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data.</description><identifier>ISSN: 1046-2023</identifier><identifier>EISSN: 1095-9130</identifier><identifier>DOI: 10.1016/j.ymeth.2015.05.022</identifier><identifier>PMID: 26032817</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Bacteria - genetics ; Bacterial regulons ; Binding Sites ; Bioinformatics analysis of genomic data ; ChIP-seq ; Computational Biology - methods ; DNA-Binding Proteins - chemistry ; DNA-Binding Proteins - genetics ; Genome-wide analysis ; High-Throughput Nucleotide Sequencing - methods ; Molecular Biology - methods ; Oligonucleotide Array Sequence Analysis - methods ; Regulon - genetics ; Sequence Analysis, DNA - methods ; Systems biology ; Transcription factor binding sites ; Transcriptional regulation</subject><ispartof>Methods (San Diego, Calif.), 2015-09, Vol.86 (C), p.80-88</ispartof><rights>2015 Elsevier Inc.</rights><rights>Copyright © 2015 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c501t-f0d380380a6c98a2cf820f855fef96ce5c5688572879fa40bda7f8764df2ba033</citedby><cites>FETCH-LOGICAL-c501t-f0d380380a6c98a2cf820f855fef96ce5c5688572879fa40bda7f8764df2ba033</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ymeth.2015.05.022$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,315,781,785,886,3551,27929,27930,46000</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26032817$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1250945$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Myers, Kevin S.</creatorcontrib><creatorcontrib>Park, Dan M.</creatorcontrib><creatorcontrib>Beauchene, Nicole A.</creatorcontrib><creatorcontrib>Kiley, Patricia J.</creatorcontrib><title>Defining bacterial regulons using ChIP-seq</title><title>Methods (San Diego, Calif.)</title><addtitle>Methods</addtitle><description>•ChIP-seq is a powerful method for identifying transcription factor binding in vivo.•Correlation of ChIP-seq and transcriptomic data can identify bacterial regulons.•An overview of ChIP-seq methodology and data analysis in bacteria is provided.•ChIP-seq sample preparation, data analysis, and computational analyses are reviewed.
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein–DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data.</description><subject>Bacteria - genetics</subject><subject>Bacterial regulons</subject><subject>Binding Sites</subject><subject>Bioinformatics analysis of genomic data</subject><subject>ChIP-seq</subject><subject>Computational Biology - methods</subject><subject>DNA-Binding Proteins - chemistry</subject><subject>DNA-Binding Proteins - genetics</subject><subject>Genome-wide analysis</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Molecular Biology - methods</subject><subject>Oligonucleotide Array Sequence Analysis - methods</subject><subject>Regulon - genetics</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Systems biology</subject><subject>Transcription factor binding sites</subject><subject>Transcriptional regulation</subject><issn>1046-2023</issn><issn>1095-9130</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kF1LwzAUhoMobk5_gSDDKxE6T9IlTS-8kPk1GOiFXocsPdkyunZLWmH_3tRNL4UXciDP-eAh5JLCiAIVd6vRbo3NcsSA8hHEMHZE-hRynuQ0heOuHouEAUt75CyEFQBQlslT0mMCUiZp1ie3j2hd5arFcK5Ng97pcuhx0ZZ1FYZt6D4my-l7EnB7Tk6sLgNeHN4B-Xx--pi8JrO3l-nkYZYYDrRJLBSphBgtTC41M1YysJJzizYXBrnhQkqeMZnlVo9hXujMykyMC8vmGtJ0QK73c-vQOBWMa9AsTV1VaBpFGYd8zCN0s4c2vt62GBq1dsFgWeoK6zYomlEuRDQDEU33qPF1CB6t2ni31n6nKKjOpFqpH5OqM6kghrHYdXVY0M7XWPz1_KqLwP0ewOjiy6HvTsXKYOF8d2lRu38XfAPyiIM4</recordid><startdate>20150915</startdate><enddate>20150915</enddate><creator>Myers, Kevin S.</creator><creator>Park, Dan M.</creator><creator>Beauchene, Nicole A.</creator><creator>Kiley, Patricia J.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>OTOTI</scope></search><sort><creationdate>20150915</creationdate><title>Defining bacterial regulons using ChIP-seq</title><author>Myers, Kevin S. ; Park, Dan M. ; Beauchene, Nicole A. ; Kiley, Patricia J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c501t-f0d380380a6c98a2cf820f855fef96ce5c5688572879fa40bda7f8764df2ba033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Bacteria - genetics</topic><topic>Bacterial regulons</topic><topic>Binding Sites</topic><topic>Bioinformatics analysis of genomic data</topic><topic>ChIP-seq</topic><topic>Computational Biology - methods</topic><topic>DNA-Binding Proteins - chemistry</topic><topic>DNA-Binding Proteins - genetics</topic><topic>Genome-wide analysis</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Molecular Biology - methods</topic><topic>Oligonucleotide Array Sequence Analysis - methods</topic><topic>Regulon - genetics</topic><topic>Sequence Analysis, DNA - methods</topic><topic>Systems biology</topic><topic>Transcription factor binding sites</topic><topic>Transcriptional regulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Myers, Kevin S.</creatorcontrib><creatorcontrib>Park, Dan M.</creatorcontrib><creatorcontrib>Beauchene, Nicole A.</creatorcontrib><creatorcontrib>Kiley, Patricia J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>OSTI.GOV</collection><jtitle>Methods (San Diego, Calif.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Myers, Kevin S.</au><au>Park, Dan M.</au><au>Beauchene, Nicole A.</au><au>Kiley, Patricia J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Defining bacterial regulons using ChIP-seq</atitle><jtitle>Methods (San Diego, Calif.)</jtitle><addtitle>Methods</addtitle><date>2015-09-15</date><risdate>2015</risdate><volume>86</volume><issue>C</issue><spage>80</spage><epage>88</epage><pages>80-88</pages><issn>1046-2023</issn><eissn>1095-9130</eissn><abstract>•ChIP-seq is a powerful method for identifying transcription factor binding in vivo.•Correlation of ChIP-seq and transcriptomic data can identify bacterial regulons.•An overview of ChIP-seq methodology and data analysis in bacteria is provided.•ChIP-seq sample preparation, data analysis, and computational analyses are reviewed.
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein–DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>26032817</pmid><doi>10.1016/j.ymeth.2015.05.022</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Bacteria - genetics Bacterial regulons Binding Sites Bioinformatics analysis of genomic data ChIP-seq Computational Biology - methods DNA-Binding Proteins - chemistry DNA-Binding Proteins - genetics Genome-wide analysis High-Throughput Nucleotide Sequencing - methods Molecular Biology - methods Oligonucleotide Array Sequence Analysis - methods Regulon - genetics Sequence Analysis, DNA - methods Systems biology Transcription factor binding sites Transcriptional regulation |
title | Defining bacterial regulons using ChIP-seq |
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