OrthoMCL: identification of ortholog groups for eukaryotic genomes
The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes...
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Veröffentlicht in: | Genome research 2003-09, Vol.13 (9), p.2178-2189 |
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description | The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of "recent" paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. |
doi_str_mv | 10.1101/gr.1224503 |
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Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of "recent" paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome.</description><identifier>ISSN: 1088-9051</identifier><identifier>ISSN: 1054-9803</identifier><identifier>DOI: 10.1101/gr.1224503</identifier><identifier>PMID: 12952885</identifier><language>eng</language><publisher>United States: Cold Spring Harbor Laboratory Press</publisher><subject>Animals ; Arabidopsis - genetics ; Caenorhabditis elegans - genetics ; Computational Biology - methods ; Drosophila melanogaster - genetics ; Eukaryotic Cells - chemistry ; Eukaryotic Cells - metabolism ; Genome ; Genome, Fungal ; Genome, Plant ; Genome, Protozoan ; Humans ; Internet ; Methods ; Plasmodium falciparum - genetics ; Saccharomyces cerevisiae - genetics ; Sequence Homology, Nucleic Acid ; Software</subject><ispartof>Genome research, 2003-09, Vol.13 (9), p.2178-2189</ispartof><rights>Copyright © 2003, Cold Spring Harbor Laboratory Press 2003</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c511t-7878f67d07bc9a4cc4f2fdb7288bd26972534943ac61b1ca3e1f5556c096ae5a3</citedby><cites>FETCH-LOGICAL-c511t-7878f67d07bc9a4cc4f2fdb7288bd26972534943ac61b1ca3e1f5556c096ae5a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC403725/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC403725/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12952885$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Li</creatorcontrib><creatorcontrib>Stoeckert, Jr, Christian J</creatorcontrib><creatorcontrib>Roos, David S</creatorcontrib><title>OrthoMCL: identification of ortholog groups for eukaryotic genomes</title><title>Genome research</title><addtitle>Genome Res</addtitle><description>The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of "recent" paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome.</description><subject>Animals</subject><subject>Arabidopsis - genetics</subject><subject>Caenorhabditis elegans - genetics</subject><subject>Computational Biology - methods</subject><subject>Drosophila melanogaster - genetics</subject><subject>Eukaryotic Cells - chemistry</subject><subject>Eukaryotic Cells - metabolism</subject><subject>Genome</subject><subject>Genome, Fungal</subject><subject>Genome, Plant</subject><subject>Genome, Protozoan</subject><subject>Humans</subject><subject>Internet</subject><subject>Methods</subject><subject>Plasmodium falciparum - genetics</subject><subject>Saccharomyces cerevisiae - genetics</subject><subject>Sequence Homology, Nucleic Acid</subject><subject>Software</subject><issn>1088-9051</issn><issn>1054-9803</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkTtPwzAUhT2AaCks_ACUiQEpxc_YQWKAipdU1AVmy3Hs1JDExU6Q-PekasRjYrrD-e7RJx0AThCcIwTRRRXmCGPKINkDUwSFSHPI0AQcxvgKISRUiAMwQThnWAg2BTer0K3902J5mbjStJ2zTqvO-TbxNvHbrPZVUgXfb2JifUhM_6bCp--cTirT-sbEI7BvVR3N8Xhn4OXu9nnxkC5X94-L62WqGUJdygUXNuMl5IXOFdWaWmzLgg8eRYmznGNGaE6J0hkqkFbEIMsYyzTMM2WYIjNwtevd9EVjSj3YBlXLTXDNYCS9cvJv0rq1rPyHpJBsy2fgbPwP_r03sZONi9rUtWqN76PkJMMEcv4viITAnFMxgOc7UAcfYzD2WwZBuZ1DVkGOcwzw6W_9H3TcgnwBWw6Iww</recordid><startdate>200309</startdate><enddate>200309</enddate><creator>Li, Li</creator><creator>Stoeckert, Jr, Christian J</creator><creator>Roos, David S</creator><general>Cold Spring Harbor Laboratory Press</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>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>200309</creationdate><title>OrthoMCL: identification of ortholog groups for eukaryotic genomes</title><author>Li, Li ; Stoeckert, Jr, Christian J ; Roos, David S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c511t-7878f67d07bc9a4cc4f2fdb7288bd26972534943ac61b1ca3e1f5556c096ae5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Animals</topic><topic>Arabidopsis - genetics</topic><topic>Caenorhabditis elegans - genetics</topic><topic>Computational Biology - methods</topic><topic>Drosophila melanogaster - genetics</topic><topic>Eukaryotic Cells - chemistry</topic><topic>Eukaryotic Cells - metabolism</topic><topic>Genome</topic><topic>Genome, Fungal</topic><topic>Genome, Plant</topic><topic>Genome, Protozoan</topic><topic>Humans</topic><topic>Internet</topic><topic>Methods</topic><topic>Plasmodium falciparum - genetics</topic><topic>Saccharomyces cerevisiae - genetics</topic><topic>Sequence Homology, Nucleic Acid</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Li</creatorcontrib><creatorcontrib>Stoeckert, Jr, Christian J</creatorcontrib><creatorcontrib>Roos, David S</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genome research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Li</au><au>Stoeckert, Jr, Christian J</au><au>Roos, David S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>OrthoMCL: identification of ortholog groups for eukaryotic genomes</atitle><jtitle>Genome research</jtitle><addtitle>Genome Res</addtitle><date>2003-09</date><risdate>2003</risdate><volume>13</volume><issue>9</issue><spage>2178</spage><epage>2189</epage><pages>2178-2189</pages><issn>1088-9051</issn><issn>1054-9803</issn><abstract>The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of "recent" paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome.</abstract><cop>United States</cop><pub>Cold Spring Harbor Laboratory Press</pub><pmid>12952885</pmid><doi>10.1101/gr.1224503</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Arabidopsis - genetics Caenorhabditis elegans - genetics Computational Biology - methods Drosophila melanogaster - genetics Eukaryotic Cells - chemistry Eukaryotic Cells - metabolism Genome Genome, Fungal Genome, Plant Genome, Protozoan Humans Internet Methods Plasmodium falciparum - genetics Saccharomyces cerevisiae - genetics Sequence Homology, Nucleic Acid Software |
title | OrthoMCL: identification of ortholog groups for eukaryotic genomes |
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