Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments.

Nucleic Acids Res
Authors
Keywords
Abstract

Recent advances in technology have led to a dramatic increase in the number of available transcription factor ChIP-seq and ChIP-chip data sets. Understanding the motif content of these data sets is an important step in understanding the underlying mechanisms of regulation. Here we provide a systematic motif analysis for 427 human ChIP-seq data sets using motifs curated from the literature and also discovered de novo using five established motif discovery tools. We use a systematic pipeline for calculating motif enrichment in each data set, providing a principled way for choosing between motif variants found in the literature and for flagging potentially problematic data sets. Our analysis confirms the known specificity of 41 of the 56 analyzed factor groups and reveals motifs of potential cofactors. We also use cell type-specific binding to find factors active in specific conditions. The resource we provide is accessible both for browsing a small number of factors and for performing large-scale systematic analyses. We provide motif matrices, instances and enrichments in each of the ENCODE data sets. The motifs discovered here have been used in parallel studies to validate the specificity of antibodies, understand cooperativity between data sets and measure the variation of motif binding across individuals and species.

Year of Publication
2014
Journal
Nucleic Acids Res
Volume
42
Issue
5
Pages
2976-87
Date Published
2014 Mar
ISSN
1362-4962
URL
DOI
10.1093/nar/gkt1249
PubMed ID
24335146
PubMed Central ID
PMC3950668
Links
Grant list
R01 HG004037 / HG / NHGRI NIH HHS / United States
HG004037 / HG / NHGRI NIH HHS / United States
HG006991 / HG / NHGRI NIH HHS / United States
HG007000 / HG / NHGRI NIH HHS / United States