Genome biologyBioinformaticsPeer-reviewed journal article
A base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding
Abstract
While methylation of CpG dinucleotides is traditionally considered antagonistic to the DNA-binding activity of most transcription factors (TFs), recent in vitro studies have revealed a more complex picture, suggesting that over a third of TFs may preferentially bind to methylated sequences. Expanding these in vitro observations to in vivo TF binding preferences, however, is challenging, as the effect of methylation of individual CpG sites cannot be easily isolated from the confounding effects of DNA accessibility and regional DNA methylation. As a result, the in vivo methylation preferences of most TFs remain uncharacterized. Here, we introduce joint accessibility-methylation-sequence (JAMS) models, which connect the strength of the binding signal observed in ChIP-seq to the DNA accessibility of the binding site, regional methylation level, DNA sequence, and base-resolution cytosine methylation. We show that JAMS models quantitatively explain the TF binding strength, recapitulate cell type-specific TF binding, and have high precision for inferring intra-motif methylation effects. Analysis of 2209 ChIP-seq experiments resulted in high-confidence JAMS models for 260 TFs, revealing that 45% of TFs are inhibited by intra-motif methylation in vivo. In contrast, only 16 TFs (6%) preferentially bind to methylated sites, including 11 novel methyl-binding TFs that are mostly from the multi-zinc finger family of TFs. Our study substantially expands the repertoire of in vivo methyl-binding TFs, but also suggests that most TFs that prefer methylated CpGs in vitro present themselves as methylation agnostic in vivo, potentially due to the balancing effect of competition with other methyl-binding proteins.
- organism: human
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 9
- FWCI
- 0.57
- Field percentile
- top 43%
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