Advances in computational analysis of metagenome sequences
Summary Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies. Large data sets of short sequence reads are mapped onto a cus...
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description | Summary
Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies. Large data sets of short sequence reads are mapped onto a custom microbial reference sequence. If a bacterial pangenome of completely sequenced genomes is taken as a reference, the output consists of the distribution of bacterial taxa in and bacterial gene contents of the metagenome. The relative abundance of functional categories and of individual pathways and fitness traits encoded by the metagenomic gene pool provides insight into habitat‐specific features of the microbial community. Polymorphic sites in sequence reads may resolve the number and abundance of individual clonal complexes of dominant species in the polymicrobial community. These SNPs and de novo mutations may be exploited to trace the spatiotemporal spread of clones and the emergence of novel traits such as fitness or resistance determinants. In conclusion, massively parallel sequencing of metagenomic DNA allows deep insights into the composition and the genetic repertoire of polymicrobial communities. |
doi_str_mv | 10.1111/j.1462-2920.2012.02843.x |
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Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies. Large data sets of short sequence reads are mapped onto a custom microbial reference sequence. If a bacterial pangenome of completely sequenced genomes is taken as a reference, the output consists of the distribution of bacterial taxa in and bacterial gene contents of the metagenome. The relative abundance of functional categories and of individual pathways and fitness traits encoded by the metagenomic gene pool provides insight into habitat‐specific features of the microbial community. Polymorphic sites in sequence reads may resolve the number and abundance of individual clonal complexes of dominant species in the polymicrobial community. These SNPs and de novo mutations may be exploited to trace the spatiotemporal spread of clones and the emergence of novel traits such as fitness or resistance determinants. In conclusion, massively parallel sequencing of metagenomic DNA allows deep insights into the composition and the genetic repertoire of polymicrobial communities.</description><identifier>ISSN: 1462-2912</identifier><identifier>EISSN: 1462-2920</identifier><identifier>DOI: 10.1111/j.1462-2920.2012.02843.x</identifier><identifier>PMID: 22882611</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>Animal, plant and microbial ecology ; Bacteria - classification ; Bacteria - genetics ; Biological and medical sciences ; Chromosome Mapping ; Fundamental and applied biological sciences. Psychology ; General aspects ; Genes ; Genetics ; Metagenome - genetics ; Metagenomics ; Microbial ecology ; Microbiology - trends ; Sequence Analysis, DNA</subject><ispartof>Environmental microbiology, 2013-01, Vol.15 (1), p.1-5</ispartof><rights>2012 Society for Applied Microbiology and Blackwell Publishing Ltd</rights><rights>2014 INIST-CNRS</rights><rights>2012 Society for Applied Microbiology and Blackwell Publishing Ltd.</rights><rights>Copyright © 2013 Society for Applied Microbiology and Blackwell Publishing Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4983-f1d7ee872465a401bf72762e3691cb81125c37677ebe0f590442e6c262228963</citedby><cites>FETCH-LOGICAL-c4983-f1d7ee872465a401bf72762e3691cb81125c37677ebe0f590442e6c262228963</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1462-2920.2012.02843.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1462-2920.2012.02843.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,4010,27900,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27081236$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22882611$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Davenport, Colin F.</creatorcontrib><creatorcontrib>Tümmler, Burkhard</creatorcontrib><title>Advances in computational analysis of metagenome sequences</title><title>Environmental microbiology</title><addtitle>Environ Microbiol</addtitle><description>Summary
Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies. Large data sets of short sequence reads are mapped onto a custom microbial reference sequence. If a bacterial pangenome of completely sequenced genomes is taken as a reference, the output consists of the distribution of bacterial taxa in and bacterial gene contents of the metagenome. The relative abundance of functional categories and of individual pathways and fitness traits encoded by the metagenomic gene pool provides insight into habitat‐specific features of the microbial community. Polymorphic sites in sequence reads may resolve the number and abundance of individual clonal complexes of dominant species in the polymicrobial community. These SNPs and de novo mutations may be exploited to trace the spatiotemporal spread of clones and the emergence of novel traits such as fitness or resistance determinants. In conclusion, massively parallel sequencing of metagenomic DNA allows deep insights into the composition and the genetic repertoire of polymicrobial communities.</description><subject>Animal, plant and microbial ecology</subject><subject>Bacteria - classification</subject><subject>Bacteria - genetics</subject><subject>Biological and medical sciences</subject><subject>Chromosome Mapping</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Genes</subject><subject>Genetics</subject><subject>Metagenome - genetics</subject><subject>Metagenomics</subject><subject>Microbial ecology</subject><subject>Microbiology - trends</subject><subject>Sequence Analysis, DNA</subject><issn>1462-2912</issn><issn>1462-2920</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkk2LFDEQhoMo7rruX5AGEbx0m6qkk7TgYVn2C1ZFWNi9hUymWnrsj7HT7c78exNnHMGL5pAU5HmrKvWGsQx4AXG9WxUgFeZYIS-QAxYcjRTF5gk7Plw8PcSAR-xFCCvOQQvNn7MjRGNQARyz92fLH673FLKmz_zQrefJTc3QuzZzcduGJmRDnXU0ua_UDx1lgb7PlBQv2bPatYFO9-cJu7u8uDu_zm8_X92cn93mXlZG5DUsNZHRKFXpJIdFrVErJKEq8AsDgKUXWmlNC-J1WXEpkZRHhbHLSokT9naXdj0OsXKYbNcET23rehrmYEGgMFyU3PwbRS0QVMwc0dd_oathHuOLE6VUgkSizI7y4xDCSLVdj03nxq0FbpMTdmXTkG0auE1O2F9O2E2UvtoXmBcdLQ_C36OPwJs94IJ3bT1GG5rwh9PcAIr0_g877rFpafvfDdiLjzcpivp8p2_CRJuD3o3frIrfobT3n64sflEgH-6lvRY_AQqSr0U</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Davenport, Colin F.</creator><creator>Tümmler, Burkhard</creator><general>Blackwell Publishing Ltd</general><general>Blackwell</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>IQODW</scope><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>7QH</scope><scope>7QL</scope><scope>7ST</scope><scope>7T7</scope><scope>7TN</scope><scope>7U9</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H94</scope><scope>H95</scope><scope>H97</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>SOI</scope><scope>7X8</scope></search><sort><creationdate>201301</creationdate><title>Advances in computational analysis of metagenome sequences</title><author>Davenport, Colin F. ; Tümmler, Burkhard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4983-f1d7ee872465a401bf72762e3691cb81125c37677ebe0f590442e6c262228963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Animal, plant and microbial ecology</topic><topic>Bacteria - classification</topic><topic>Bacteria - genetics</topic><topic>Biological and medical sciences</topic><topic>Chromosome Mapping</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Genes</topic><topic>Genetics</topic><topic>Metagenome - genetics</topic><topic>Metagenomics</topic><topic>Microbial ecology</topic><topic>Microbiology - trends</topic><topic>Sequence Analysis, DNA</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Davenport, Colin F.</creatorcontrib><creatorcontrib>Tümmler, Burkhard</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Oceanic Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Environmental microbiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Davenport, Colin F.</au><au>Tümmler, Burkhard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Advances in computational analysis of metagenome sequences</atitle><jtitle>Environmental microbiology</jtitle><addtitle>Environ Microbiol</addtitle><date>2013-01</date><risdate>2013</risdate><volume>15</volume><issue>1</issue><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>1462-2912</issn><eissn>1462-2920</eissn><abstract>Summary
Second‐generation sequencing technologies are revolutionizing the study of metagenomes. Whole‐genome shotgun sequencing of metagenomic DNA may become an attractive alternative to the current widely used ribosomal RNA gene studies. Large data sets of short sequence reads are mapped onto a custom microbial reference sequence. If a bacterial pangenome of completely sequenced genomes is taken as a reference, the output consists of the distribution of bacterial taxa in and bacterial gene contents of the metagenome. The relative abundance of functional categories and of individual pathways and fitness traits encoded by the metagenomic gene pool provides insight into habitat‐specific features of the microbial community. Polymorphic sites in sequence reads may resolve the number and abundance of individual clonal complexes of dominant species in the polymicrobial community. These SNPs and de novo mutations may be exploited to trace the spatiotemporal spread of clones and the emergence of novel traits such as fitness or resistance determinants. In conclusion, massively parallel sequencing of metagenomic DNA allows deep insights into the composition and the genetic repertoire of polymicrobial communities.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><pmid>22882611</pmid><doi>10.1111/j.1462-2920.2012.02843.x</doi><tpages>5</tpages></addata></record> |
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subjects | Animal, plant and microbial ecology Bacteria - classification Bacteria - genetics Biological and medical sciences Chromosome Mapping Fundamental and applied biological sciences. Psychology General aspects Genes Genetics Metagenome - genetics Metagenomics Microbial ecology Microbiology - trends Sequence Analysis, DNA |
title | Advances in computational analysis of metagenome sequences |
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