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dc.contributor.authorLewis, Sophia
dc.contributor.authorvan Hoff, John Peter
dc.contributor.authorKarun, Vivek
dc.contributor.authorHashimoto, Tatsunori Benjamin
dc.contributor.authorSherwood, Richard I.
dc.contributor.authorO'Donnell, Charles William
dc.contributor.authorBarkal, Amira A.
dc.contributor.authorJaakkola, Tommi S.
dc.contributor.authorGifford, David K.
dc.date.accessioned2015-12-14T02:21:40Z
dc.date.available2015-12-14T02:21:40Z
dc.date.issued2014-01
dc.date.submitted2013-03
dc.identifier.issn1087-0156
dc.identifier.issn1546-1696
dc.identifier.urihttp://hdl.handle.net/1721.1/100228
dc.description.abstractWe describe protein interaction quantitation (PIQ), a computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning techniques, PIQ identified binding sites for >700 TFs from one DNase I hypersensitivity analysis followed by sequencing (DNase-seq) experiment with accuracy comparable to that of chromatin immunoprecipitation followed by sequencing (ChIP-seq). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into prepancreatic and intestinal endoderm. We identified 120 and experimentally validated eight 'pioneer' TF families that dynamically open chromatin. Four pioneer TF families only opened chromatin in one direction from their motifs. Furthermore, we identified 'settler' TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and nondirectional pioneer activity shapes the chromatin landscape for population by settler TFs.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Common Fund 5UL1DE019581)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Common Fund RL1DE019021)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Common Fund 5TL1EB008540)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant 1U01HG007037)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant 5P01NS055923)en_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/nbt.2798en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleDiscovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shapeen_US
dc.typeArticleen_US
dc.identifier.citationSherwood, Richard I, Tatsunori Hashimoto, Charles W O’Donnell, Sophia Lewis, Amira A Barkal, John Peter van Hoff, Vivek Karun, Tommi Jaakkola, and David K Gifford. “Discovery of Directional and Nondirectional Pioneer Transcription Factors by Modeling DNase Profile Magnitude and Shape.” Nature Biotechnology 32, no. 2 (January 19, 2014): 171–178.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorHashimoto, Tatsunori Benjaminen_US
dc.contributor.mitauthorO'Donnell, Charles Williamen_US
dc.contributor.mitauthorJaakkola, Tommi S.en_US
dc.contributor.mitauthorGifford, David K.en_US
dc.relation.journalNature Biotechnologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSherwood, Richard I; Hashimoto, Tatsunori; O'Donnell, Charles W; Lewis, Sophia; Barkal, Amira A; van Hoff, John Peter; Karun, Vivek; Jaakkola, Tommi; Gifford, David Ken_US
dc.identifier.orcidhttps://orcid.org/0000-0003-0521-5855
dc.identifier.orcidhttps://orcid.org/0000-0002-2199-0379
dc.identifier.orcidhttps://orcid.org/0000-0003-1709-4034
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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