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dc.contributor.authorVijayabaskar, MS
dc.contributor.authorGoode, DK
dc.contributor.authorObier, N
dc.contributor.authorLichtinger, M
dc.contributor.authorEmmett, AML
dc.contributor.authorAbidin, FNZ
dc.contributor.authorShar, N
dc.contributor.authorHannah, R
dc.contributor.authorAssi, SA
dc.contributor.authorLie-A-Ling, Michael
dc.contributor.authorGottgens, B
dc.contributor.authorLacaud, Georges
dc.contributor.authorKouskoff, V
dc.contributor.authorBonifer, C
dc.contributor.authorWesthead, DR
dc.date.accessioned2019-12-09T17:23:39Z
dc.date.available2019-12-09T17:23:39Z
dc.date.issued2019en
dc.identifier.citationVijayabaskar MS, Goode DK, Obier N, Lichtinger M, Emmett AML, Abidin FNZ, et al. Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets. PLoS Comput Biol. 2019;15(11):e1007337.en
dc.identifier.pmid31682597en
dc.identifier.doi10.1371/journal.pcbi.1007337en
dc.identifier.urihttp://hdl.handle.net/10541/622623
dc.description.abstractGene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.en
dc.language.isoenen
dc.relation.urlhttps://dx.doi.org/10.1371/journal.pcbi.1007337en
dc.titleIdentification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasetsen
dc.typeArticleen
dc.contributor.departmentSchool of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leedsen
dc.identifier.journalPLoS Computational Biologyen


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