Understanding transcriptional regulation by integrative analysis of transcription factor binding data

Cheng, Chao; Alexander, Roger; Min, Renqiang; Leng, Jing; Yip, Kevin Y.; Rozowsky, Joel S.; Yan, Koon-Kiu; Dong, Xianjun; Djebali, Sarah; Ruan, Yijun; Davis, Carrie A.; Carninci, Piero; Lassmann, Timo; Gingeras, Thomas R.; Guigó Serra, Roderic; Birney, Ewan; Weng, Zhiping; Snyder, Michael; Gerstein, Mark B.

Understanding transcriptional regulation by integrative analysis of transcription factor binding data

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dc.contributor.author Cheng, Chaoca
dc.contributor.author Alexander, Rogerca
dc.contributor.author Min, Renqiangca
dc.contributor.author Leng, Jingca
dc.contributor.author Yip, Kevin Y.ca
dc.contributor.author Rozowsky, Joel S.ca
dc.contributor.author Yan, Koon-Kiuca
dc.contributor.author Dong, Xianjunca
dc.contributor.author Djebali, Sarahca
dc.contributor.author Ruan, Yijunca
dc.contributor.author Davis, Carrie A.ca
dc.contributor.author Carninci, Pieroca
dc.contributor.author Lassmann, Timoca
dc.contributor.author Gingeras, Thomas R.ca
dc.contributor.author Guigó Serra, Rodericca
dc.contributor.author Birney, Ewanca
dc.contributor.author Weng, Zhipingca
dc.contributor.author Snyder, Michaelca
dc.contributor.author Gerstein, Mark B.ca
dc.date.accessioned 2014-07-18T08:38:56Z
dc.date.available 2014-07-18T08:38:56Z
dc.date.issued 2012ca
dc.description.abstract Statistical models have been used to quantify the relationship between gene expression and transcription factor (TF) binding signals. Here we apply the models to the large-scale data generated by the ENCODE project to study transcriptional regulation by TFs. Our results reveal a notable difference in the prediction accuracy of expression levels of transcription start sites (TSSs) captured by different technologies and RNA extraction protocols. In general, the expression levels of TSSs with high CpG content are more predictable than those with low CpG content. For genes with alternative TSSs, the expression levels of downstream TSSs are more predictable than those of the upstream ones. Different TF categories and specific TFs vary substantially in their contributions to predicting expression. Between two cell lines, the differential expression of TSS can be precisely reflected by the difference of TF-binding signals in a quantitative manner, arguing against the conventional on-and-off model of TF binding. Finally, we explore the relationships between TF-binding signals and other chromatin features such as histone modifications and DNase hypersensitivity for determining expression. The models imply that these features regulate transcription in a highly coordinated manner.
dc.description.sponsorship This work has been carried out under AL Williams Professorship funds
dc.format.mimetype application/pdfca
dc.identifier.citation Cheng C, Alexander R, Min R, Leng J, Yip KY, Rozowsky J et al. Understanding transcriptional regulation by integrative analysis of transcription factor binding data. Genome Res. 2012;22(9):1658-67. DOI: 10.1101/gr.136838.111ca
dc.identifier.doi http://dx.doi.org/10.1101/gr.136838.111
dc.identifier.issn 1088-9051ca
dc.identifier.uri http://hdl.handle.net/10230/22638
dc.language.iso engca
dc.publisher Cold Spring Harbor Laboratory Press (CSHL Press)ca
dc.relation.ispartof Genome Research. 2012;22(9):1658-67
dc.rights.accessRights info:eu-repo/semantics/openAccessca
dc.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
dc.subject.other Genòmica
dc.subject.other Expressió gènica
dc.subject.other Transcripció genètica
dc.title Understanding transcriptional regulation by integrative analysis of transcription factor binding dataca
dc.type info:eu-repo/semantics/articleca
dc.type.version info:eu-repo/semantics/publishedVersionca

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Articles (Departament de Medicina i Ciències de la Vida)
Articles (Center for Genomic Regulation (CRG))