TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse
Abstract Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrati...
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| Veröffentlicht in: | Nucleic acids research 2022-01, Vol.50 (D1), p.D391-D401 |
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| creator | Zhang, Yuexin Song, Chao Zhang, Yimeng Wang, Yuezhu Feng, Chenchen Chen, Jiaxin Wei, Ling Pan, Qi Shang, Desi Zhu, Yanbing Zhu, Jiang Fang, Shuangsang Zhao, Jun Yang, Yongsan Zhao, Xilong Xu, Xiaozheng Wang, Qiuyu Guo, Jincheng Li, Chunquan |
| description | Abstract
Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms. |
| doi_str_mv | 10.1093/nar/gkab950 |
| format | Article |
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Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.</description><identifier>ISSN: 0305-1048</identifier><identifier>EISSN: 1362-4962</identifier><identifier>DOI: 10.1093/nar/gkab950</identifier><identifier>PMID: 34718747</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Animals ; Chromatin - chemistry ; Chromatin - metabolism ; Database Issue ; Databases, Genetic ; Datasets as Topic ; Enhancer Elements, Genetic ; Gene Expression Regulation ; Gene Regulatory Networks ; Humans ; Internet ; Mice ; Molecular Sequence Annotation ; Promoter Regions, Genetic ; Software ; Transcription Factors - classification ; Transcription Factors - genetics ; Transcription Factors - metabolism ; Transcription, Genetic</subject><ispartof>Nucleic acids research, 2022-01, Vol.50 (D1), p.D391-D401</ispartof><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. 2022</rights><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-c0b22e0889b93bd8a54d08fcd6725d8c0884f6588677fd0d6a11e8af6295e9313</citedby><cites>FETCH-LOGICAL-c412t-c0b22e0889b93bd8a54d08fcd6725d8c0884f6588677fd0d6a11e8af6295e9313</cites><orcidid>0000-0002-5616-6910 ; 0000-0002-4700-5496</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728270/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728270/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,1598,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34718747$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Yuexin</creatorcontrib><creatorcontrib>Song, Chao</creatorcontrib><creatorcontrib>Zhang, Yimeng</creatorcontrib><creatorcontrib>Wang, Yuezhu</creatorcontrib><creatorcontrib>Feng, Chenchen</creatorcontrib><creatorcontrib>Chen, Jiaxin</creatorcontrib><creatorcontrib>Wei, Ling</creatorcontrib><creatorcontrib>Pan, Qi</creatorcontrib><creatorcontrib>Shang, Desi</creatorcontrib><creatorcontrib>Zhu, Yanbing</creatorcontrib><creatorcontrib>Zhu, Jiang</creatorcontrib><creatorcontrib>Fang, Shuangsang</creatorcontrib><creatorcontrib>Zhao, Jun</creatorcontrib><creatorcontrib>Yang, Yongsan</creatorcontrib><creatorcontrib>Zhao, Xilong</creatorcontrib><creatorcontrib>Xu, Xiaozheng</creatorcontrib><creatorcontrib>Wang, Qiuyu</creatorcontrib><creatorcontrib>Guo, Jincheng</creatorcontrib><creatorcontrib>Li, Chunquan</creatorcontrib><title>TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse</title><title>Nucleic acids research</title><addtitle>Nucleic Acids Res</addtitle><description>Abstract
Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.</description><subject>Animals</subject><subject>Chromatin - chemistry</subject><subject>Chromatin - metabolism</subject><subject>Database Issue</subject><subject>Databases, Genetic</subject><subject>Datasets as Topic</subject><subject>Enhancer Elements, Genetic</subject><subject>Gene Expression Regulation</subject><subject>Gene Regulatory Networks</subject><subject>Humans</subject><subject>Internet</subject><subject>Mice</subject><subject>Molecular Sequence Annotation</subject><subject>Promoter Regions, Genetic</subject><subject>Software</subject><subject>Transcription Factors - classification</subject><subject>Transcription Factors - genetics</subject><subject>Transcription Factors - metabolism</subject><subject>Transcription, Genetic</subject><issn>0305-1048</issn><issn>1362-4962</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNp9kUFv1DAQRi0EotvCiTvyCSFVobZjJw6HSlBRWqlSL-VsTezJrktiBzup1H9fo10quHCaw_f0ZkYfIe84-8RZV58FSGfbn9B3ir0gG143opJdI16SDauZqjiT-ogc53zPGJdcydfkqJYt161sN-T-zsbLr5DxMwVq4zQn3GHI_gGpgwX6ktAhJurQRufDli47pAm36whLTI90SRCyTX5efAxFUA1gS5CpD3S3ThAoBEenuGZ8Q14NMGZ8e5gn5Mflt7uLq-rm9vv1xZebykoulsqyXghkWnd9V_dOg5KO6cG6phXKaVsSOTRK66ZtB8dcA5yjhqERncKu5vUJOd9757Wf0FkM5cjRzMlPkB5NBG_-TYLfmW18MLoVWrSsCD4eBCn-WjEvZvLZ4jhCwPKIEarjgnPVtAU93aM2xZwTDs9rODO_2zGlHXNop9Dv_77smf1TRwE-7IG4zv81PQHHtpuP</recordid><startdate>20220107</startdate><enddate>20220107</enddate><creator>Zhang, Yuexin</creator><creator>Song, Chao</creator><creator>Zhang, Yimeng</creator><creator>Wang, Yuezhu</creator><creator>Feng, Chenchen</creator><creator>Chen, Jiaxin</creator><creator>Wei, Ling</creator><creator>Pan, Qi</creator><creator>Shang, Desi</creator><creator>Zhu, Yanbing</creator><creator>Zhu, Jiang</creator><creator>Fang, Shuangsang</creator><creator>Zhao, Jun</creator><creator>Yang, Yongsan</creator><creator>Zhao, Xilong</creator><creator>Xu, Xiaozheng</creator><creator>Wang, Qiuyu</creator><creator>Guo, Jincheng</creator><creator>Li, Chunquan</creator><general>Oxford University Press</general><scope>TOX</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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5616-6910</orcidid><orcidid>https://orcid.org/0000-0002-4700-5496</orcidid></search><sort><creationdate>20220107</creationdate><title>TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse</title><author>Zhang, Yuexin ; Song, Chao ; Zhang, Yimeng ; Wang, Yuezhu ; Feng, Chenchen ; Chen, Jiaxin ; Wei, Ling ; Pan, Qi ; Shang, Desi ; Zhu, Yanbing ; Zhu, Jiang ; Fang, Shuangsang ; Zhao, Jun ; Yang, Yongsan ; Zhao, Xilong ; Xu, Xiaozheng ; Wang, Qiuyu ; Guo, Jincheng ; Li, Chunquan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c412t-c0b22e0889b93bd8a54d08fcd6725d8c0884f6588677fd0d6a11e8af6295e9313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Animals</topic><topic>Chromatin - chemistry</topic><topic>Chromatin - metabolism</topic><topic>Database Issue</topic><topic>Databases, Genetic</topic><topic>Datasets as Topic</topic><topic>Enhancer Elements, Genetic</topic><topic>Gene Expression Regulation</topic><topic>Gene Regulatory Networks</topic><topic>Humans</topic><topic>Internet</topic><topic>Mice</topic><topic>Molecular Sequence Annotation</topic><topic>Promoter Regions, Genetic</topic><topic>Software</topic><topic>Transcription Factors - classification</topic><topic>Transcription Factors - genetics</topic><topic>Transcription Factors - metabolism</topic><topic>Transcription, Genetic</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yuexin</creatorcontrib><creatorcontrib>Song, Chao</creatorcontrib><creatorcontrib>Zhang, Yimeng</creatorcontrib><creatorcontrib>Wang, Yuezhu</creatorcontrib><creatorcontrib>Feng, Chenchen</creatorcontrib><creatorcontrib>Chen, Jiaxin</creatorcontrib><creatorcontrib>Wei, Ling</creatorcontrib><creatorcontrib>Pan, Qi</creatorcontrib><creatorcontrib>Shang, Desi</creatorcontrib><creatorcontrib>Zhu, Yanbing</creatorcontrib><creatorcontrib>Zhu, Jiang</creatorcontrib><creatorcontrib>Fang, Shuangsang</creatorcontrib><creatorcontrib>Zhao, Jun</creatorcontrib><creatorcontrib>Yang, Yongsan</creatorcontrib><creatorcontrib>Zhao, Xilong</creatorcontrib><creatorcontrib>Xu, Xiaozheng</creatorcontrib><creatorcontrib>Wang, Qiuyu</creatorcontrib><creatorcontrib>Guo, Jincheng</creatorcontrib><creatorcontrib>Li, Chunquan</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><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>PubMed Central (Full Participant titles)</collection><jtitle>Nucleic acids research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yuexin</au><au>Song, Chao</au><au>Zhang, Yimeng</au><au>Wang, Yuezhu</au><au>Feng, Chenchen</au><au>Chen, Jiaxin</au><au>Wei, Ling</au><au>Pan, Qi</au><au>Shang, Desi</au><au>Zhu, Yanbing</au><au>Zhu, Jiang</au><au>Fang, Shuangsang</au><au>Zhao, Jun</au><au>Yang, Yongsan</au><au>Zhao, Xilong</au><au>Xu, Xiaozheng</au><au>Wang, Qiuyu</au><au>Guo, Jincheng</au><au>Li, Chunquan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse</atitle><jtitle>Nucleic acids research</jtitle><addtitle>Nucleic Acids Res</addtitle><date>2022-01-07</date><risdate>2022</risdate><volume>50</volume><issue>D1</issue><spage>D391</spage><epage>D401</epage><pages>D391-D401</pages><issn>0305-1048</issn><eissn>1362-4962</eissn><abstract>Abstract
Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>34718747</pmid><doi>10.1093/nar/gkab950</doi><orcidid>https://orcid.org/0000-0002-5616-6910</orcidid><orcidid>https://orcid.org/0000-0002-4700-5496</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Animals Chromatin - chemistry Chromatin - metabolism Database Issue Databases, Genetic Datasets as Topic Enhancer Elements, Genetic Gene Expression Regulation Gene Regulatory Networks Humans Internet Mice Molecular Sequence Annotation Promoter Regions, Genetic Software Transcription Factors - classification Transcription Factors - genetics Transcription Factors - metabolism Transcription, Genetic |
| title | TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse |
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