Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data
Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements...
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Veröffentlicht in: | Molecular cell 2018-09, Vol.71 (5), p.858-871.e8 |
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creator | Pliner, Hannah A. Packer, Jonathan S. McFaline-Figueroa, José L. Cusanovich, Darren A. Daza, Riza M. Aghamirzaie, Delasa Srivatsan, Sanjay Qiu, Xiaojie Jackson, Dana Minkina, Anna Adey, Andrew C. Steemers, Frank J. Shendure, Jay Trapnell, Cole |
description | Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of “chromatin hubs”—they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD1 in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. Our strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.
[Display omitted]
•Cicero connects regulatory DNA elements to target genes•Co-accessible elements form chromatin hubs•Chromatin hubs are co-regulated during skeletal muscle development•Cicero can help reveal the mechanisms of cis-regulation on a genome-wide scale
Pliner et al. introduce Cicero, a software program to connect distal regulatory elements with target genes using single-cell ATAC-seq data. They find evidence that groups of co-accessible elements form chromatin hubs and undergo coordinated changes in histone marks that are predictive of changes in gene expression in skeletal muscle development. |
doi_str_mv | 10.1016/j.molcel.2018.06.044 |
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[Display omitted]
•Cicero connects regulatory DNA elements to target genes•Co-accessible elements form chromatin hubs•Chromatin hubs are co-regulated during skeletal muscle development•Cicero can help reveal the mechanisms of cis-regulation on a genome-wide scale
Pliner et al. introduce Cicero, a software program to connect distal regulatory elements with target genes using single-cell ATAC-seq data. They find evidence that groups of co-accessible elements form chromatin hubs and undergo coordinated changes in histone marks that are predictive of changes in gene expression in skeletal muscle development.</description><identifier>ISSN: 1097-2765</identifier><identifier>EISSN: 1097-4164</identifier><identifier>DOI: 10.1016/j.molcel.2018.06.044</identifier><identifier>PMID: 30078726</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adolescent ; algorithms ; ATAC-seq ; Cell Differentiation - genetics ; chromatin ; Chromatin - genetics ; chromatin accessibility ; Chromatin Assembly and Disassembly - genetics ; co-accessibility ; DNA ; DNA - genetics ; Enhancer Elements, Genetic - genetics ; Female ; gene expression regulation ; Gene Expression Regulation - genetics ; gene regulation ; genes ; Genes, Homeobox - genetics ; histones ; Histones - genetics ; Humans ; machine learning ; myoblast differentiation ; myoblasts ; Myoblasts - physiology ; regulatory sequences ; single-cell ; transcription factors ; Transcription Factors - genetics</subject><ispartof>Molecular cell, 2018-09, Vol.71 (5), p.858-871.e8</ispartof><rights>2018</rights><rights>Copyright © 2018. Published by Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c613t-563c0adc0f0fcc40d56eb07850496784d9c2170bb6857a08dd990a99870a06993</citedby><cites>FETCH-LOGICAL-c613t-563c0adc0f0fcc40d56eb07850496784d9c2170bb6857a08dd990a99870a06993</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1097276518305471$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,3537,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30078726$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pliner, Hannah A.</creatorcontrib><creatorcontrib>Packer, Jonathan S.</creatorcontrib><creatorcontrib>McFaline-Figueroa, José L.</creatorcontrib><creatorcontrib>Cusanovich, Darren A.</creatorcontrib><creatorcontrib>Daza, Riza M.</creatorcontrib><creatorcontrib>Aghamirzaie, Delasa</creatorcontrib><creatorcontrib>Srivatsan, Sanjay</creatorcontrib><creatorcontrib>Qiu, Xiaojie</creatorcontrib><creatorcontrib>Jackson, Dana</creatorcontrib><creatorcontrib>Minkina, Anna</creatorcontrib><creatorcontrib>Adey, Andrew C.</creatorcontrib><creatorcontrib>Steemers, Frank J.</creatorcontrib><creatorcontrib>Shendure, Jay</creatorcontrib><creatorcontrib>Trapnell, Cole</creatorcontrib><title>Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data</title><title>Molecular cell</title><addtitle>Mol Cell</addtitle><description>Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of “chromatin hubs”—they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD1 in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. Our strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.
[Display omitted]
•Cicero connects regulatory DNA elements to target genes•Co-accessible elements form chromatin hubs•Chromatin hubs are co-regulated during skeletal muscle development•Cicero can help reveal the mechanisms of cis-regulation on a genome-wide scale
Pliner et al. introduce Cicero, a software program to connect distal regulatory elements with target genes using single-cell ATAC-seq data. They find evidence that groups of co-accessible elements form chromatin hubs and undergo coordinated changes in histone marks that are predictive of changes in gene expression in skeletal muscle development.</description><subject>Adolescent</subject><subject>algorithms</subject><subject>ATAC-seq</subject><subject>Cell Differentiation - genetics</subject><subject>chromatin</subject><subject>Chromatin - genetics</subject><subject>chromatin accessibility</subject><subject>Chromatin Assembly and Disassembly - genetics</subject><subject>co-accessibility</subject><subject>DNA</subject><subject>DNA - genetics</subject><subject>Enhancer Elements, Genetic - genetics</subject><subject>Female</subject><subject>gene expression regulation</subject><subject>Gene Expression Regulation - genetics</subject><subject>gene regulation</subject><subject>genes</subject><subject>Genes, Homeobox - genetics</subject><subject>histones</subject><subject>Histones - genetics</subject><subject>Humans</subject><subject>machine learning</subject><subject>myoblast differentiation</subject><subject>myoblasts</subject><subject>Myoblasts - physiology</subject><subject>regulatory sequences</subject><subject>single-cell</subject><subject>transcription factors</subject><subject>Transcription Factors - genetics</subject><issn>1097-2765</issn><issn>1097-4164</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkUtv1DAUhS0EoqXwDxDKkk3CteM49gZplPKoVAHisUSW49xMPXLiYnsq9d_jaoYCG1jZss859_ER8pxCQ4GKV7tmCd6ibxhQ2YBogPMH5JSC6mtOBX94vLNedCfkSUo7AMo7qR6Tkxaglz0Tp-T74CzGUH2KODmbU2Vdqj_jdu9NDvG2Ov-wqS7WjNHY7MKaqjmGpfri1q3HekDvq-GqvJjs1mpjLabkRuddLk6TzVPyaDY-4bPjeUa-vX3zdXhfX358dzFsLmsraJvrTrQWzGRhhtlaDlMncCwddsCV6CWflGW0h3EUsusNyGlSCoxSsgcDQqn2jLw-5F7vxwUni2uOxuvr6BYTb3UwTv_9s7orvQ03WnSSKdGWgJfHgBh-7DFlvbhUluvNimGfNGOMQtdRyv8vBcnbVjJKi5QfpDaGlCLO9x1R0HcQ9U4fIOo7iBqELhCL7cWf09ybflH7PS6Wnd44jDpZh6stCCParKfg_l3hJwLOr9s</recordid><startdate>20180906</startdate><enddate>20180906</enddate><creator>Pliner, Hannah A.</creator><creator>Packer, Jonathan S.</creator><creator>McFaline-Figueroa, José L.</creator><creator>Cusanovich, Darren A.</creator><creator>Daza, Riza M.</creator><creator>Aghamirzaie, Delasa</creator><creator>Srivatsan, Sanjay</creator><creator>Qiu, Xiaojie</creator><creator>Jackson, Dana</creator><creator>Minkina, Anna</creator><creator>Adey, Andrew C.</creator><creator>Steemers, Frank J.</creator><creator>Shendure, Jay</creator><creator>Trapnell, Cole</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</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>7S9</scope><scope>L.6</scope><scope>5PM</scope></search><sort><creationdate>20180906</creationdate><title>Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data</title><author>Pliner, Hannah A. ; Packer, Jonathan S. ; McFaline-Figueroa, José L. ; Cusanovich, Darren A. ; Daza, Riza M. ; Aghamirzaie, Delasa ; Srivatsan, Sanjay ; Qiu, Xiaojie ; Jackson, Dana ; Minkina, Anna ; Adey, Andrew C. ; Steemers, Frank J. ; Shendure, Jay ; Trapnell, Cole</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c613t-563c0adc0f0fcc40d56eb07850496784d9c2170bb6857a08dd990a99870a06993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adolescent</topic><topic>algorithms</topic><topic>ATAC-seq</topic><topic>Cell Differentiation - genetics</topic><topic>chromatin</topic><topic>Chromatin - genetics</topic><topic>chromatin accessibility</topic><topic>Chromatin Assembly and Disassembly - genetics</topic><topic>co-accessibility</topic><topic>DNA</topic><topic>DNA - genetics</topic><topic>Enhancer Elements, Genetic - genetics</topic><topic>Female</topic><topic>gene expression regulation</topic><topic>Gene Expression Regulation - genetics</topic><topic>gene regulation</topic><topic>genes</topic><topic>Genes, Homeobox - genetics</topic><topic>histones</topic><topic>Histones - genetics</topic><topic>Humans</topic><topic>machine learning</topic><topic>myoblast differentiation</topic><topic>myoblasts</topic><topic>Myoblasts - physiology</topic><topic>regulatory sequences</topic><topic>single-cell</topic><topic>transcription factors</topic><topic>Transcription Factors - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pliner, Hannah A.</creatorcontrib><creatorcontrib>Packer, Jonathan S.</creatorcontrib><creatorcontrib>McFaline-Figueroa, José L.</creatorcontrib><creatorcontrib>Cusanovich, Darren A.</creatorcontrib><creatorcontrib>Daza, Riza M.</creatorcontrib><creatorcontrib>Aghamirzaie, Delasa</creatorcontrib><creatorcontrib>Srivatsan, Sanjay</creatorcontrib><creatorcontrib>Qiu, Xiaojie</creatorcontrib><creatorcontrib>Jackson, Dana</creatorcontrib><creatorcontrib>Minkina, Anna</creatorcontrib><creatorcontrib>Adey, Andrew C.</creatorcontrib><creatorcontrib>Steemers, Frank J.</creatorcontrib><creatorcontrib>Shendure, Jay</creatorcontrib><creatorcontrib>Trapnell, Cole</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</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>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Molecular cell</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pliner, Hannah A.</au><au>Packer, Jonathan S.</au><au>McFaline-Figueroa, José L.</au><au>Cusanovich, Darren A.</au><au>Daza, Riza M.</au><au>Aghamirzaie, Delasa</au><au>Srivatsan, Sanjay</au><au>Qiu, Xiaojie</au><au>Jackson, Dana</au><au>Minkina, Anna</au><au>Adey, Andrew C.</au><au>Steemers, Frank J.</au><au>Shendure, Jay</au><au>Trapnell, Cole</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data</atitle><jtitle>Molecular cell</jtitle><addtitle>Mol Cell</addtitle><date>2018-09-06</date><risdate>2018</risdate><volume>71</volume><issue>5</issue><spage>858</spage><epage>871.e8</epage><pages>858-871.e8</pages><issn>1097-2765</issn><eissn>1097-4164</eissn><abstract>Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of “chromatin hubs”—they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD1 in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. Our strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.
[Display omitted]
•Cicero connects regulatory DNA elements to target genes•Co-accessible elements form chromatin hubs•Chromatin hubs are co-regulated during skeletal muscle development•Cicero can help reveal the mechanisms of cis-regulation on a genome-wide scale
Pliner et al. introduce Cicero, a software program to connect distal regulatory elements with target genes using single-cell ATAC-seq data. They find evidence that groups of co-accessible elements form chromatin hubs and undergo coordinated changes in histone marks that are predictive of changes in gene expression in skeletal muscle development.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30078726</pmid><doi>10.1016/j.molcel.2018.06.044</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent algorithms ATAC-seq Cell Differentiation - genetics chromatin Chromatin - genetics chromatin accessibility Chromatin Assembly and Disassembly - genetics co-accessibility DNA DNA - genetics Enhancer Elements, Genetic - genetics Female gene expression regulation Gene Expression Regulation - genetics gene regulation genes Genes, Homeobox - genetics histones Histones - genetics Humans machine learning myoblast differentiation myoblasts Myoblasts - physiology regulatory sequences single-cell transcription factors Transcription Factors - genetics |
title | Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data |
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