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dc.contributor.authorShim, Woo Jun
dc.contributor.authorSinniah, Enakshi
dc.contributor.authorXu, Jun
dc.contributor.authorVitrinel, Burcu
dc.contributor.authorAlexanian, Michael
dc.contributor.authorAndreoletti, Gaia
dc.contributor.authorShen, Sophie
dc.contributor.authorSun, Yuliangzi
dc.contributor.authorBalderson, Brad
dc.contributor.authorBoix, Carles
dc.contributor.authorPeng, Guangdun
dc.contributor.authorJing, Naihe
dc.contributor.authorWang, Yuliang
dc.contributor.authorKellis, Manolis
dc.contributor.authorTam, Patrick P.L.
dc.contributor.authorSmith, Aaron
dc.contributor.authorPiper, Michael
dc.contributor.authorChristiaen, Lionel
dc.contributor.authorNguyen, Quan
dc.contributor.authorBodén, Mikael
dc.contributor.authorPalpant, Nathan J.
dc.date.accessioned2022-08-05T17:08:52Z
dc.date.available2021-09-20T18:21:30Z
dc.date.available2022-08-05T17:08:52Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/132257.2
dc.description.abstract© 2020 The Authors Determining genes that orchestrate cell differentiation in development and disease remains a fundamental goal of cell biology. This study establishes a genome-wide metric based on the gene-repressive trimethylation of histone H3 at lysine 27 (H3K27me3) across hundreds of diverse cell types to identify genetic regulators of cell differentiation. We introduce a computational method, TRIAGE, which uses discordance between gene-repressive tendency and expression to identify genetic drivers of cell identity. We apply TRIAGE to millions of genome-wide single-cell transcriptomes, diverse omics platforms, and eukaryotic cells and tissue types. Using a wide range of data, we validate the performance of TRIAGE in identifying cell-type-specific regulatory factors across diverse species including human, mouse, boar, bird, fish, and tunicate. Using CRISPR gene editing, we use TRIAGE to experimentally validate RNF220 as a regulator of Ciona cardiopharyngeal development and SIX3 as required for differentiation of endoderm in human pluripotent stem cells. A record of this paper's transparent peer review process is included in the Supplemental Information. Perturbing genes controlling cell decisions have major implications in development or disease. However, identifying key regulatory genes from the thousands expressed in a cell is challenging. TRIAGE is a computational method that distills patterns of epigenetic repression across diverse cell types to infer regulatory genes using input gene expression data from any cell type. Demonstrating its utility, we combine single-cell RNA-seq and TRIAGE to identify and experimentally confirm novel regulators of heart development in evolutionarily distant species.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/j.cels.2020.11.001en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcePMCen_US
dc.titleConserved Epigenetic Regulatory Logic Infers Genes Governing Cell Identityen_US
dc.typeArticleen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalCell Systemsen_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
dc.date.updated2021-01-07T19:06:01Z
dspace.orderedauthorsShim, WJ; Sinniah, E; Xu, J; Vitrinel, B; Alexanian, M; Andreoletti, G; Shen, S; Sun, Y; Balderson, B; Boix, C; Peng, G; Jing, N; Wang, Y; Kellis, M; Tam, PPL; Smith, A; Piper, M; Christiaen, L; Nguyen, Q; Bodén, M; Palpant, NJen_US
dspace.date.submission2021-01-07T19:06:15Z
mit.journal.volume11en_US
mit.journal.issue6en_US
mit.licensePUBLISHER_CC
mit.metadata.statusPublication Information Neededen_US


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