Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors

By Jie Wang, Jiali Zhuang, Sowmya Iyer, Xin-Ying Lin, T. Whitfield, Melissa C. Greven, Brian G. Pierce, Xianjun Dong, Anshul B Kundaje, Yong Cheng and 6 more. Genome Research, 2012

872 citations recorded by the source corpus.

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) has become the dominant technique for mapping the transcription factor (TF) binding regions genome-wide. We performed an integrative analysis centered around 457 ChIP-seq data sets on 119 human TFs generated by the ENCODE Consortium. We identified highly enriched sequence motifs in most data sets, revealing new motifs and validating known ones. The motif sites (TF binding sites) are evolutionarily highly conserved and show distinct footprints upon DNase I digestion. We frequently detected secondary motifs in addition to the canonical motifs of the TFs, indicating tethered binding and cobinding between multiple TFs. We observed significant position and orientation preferences between many cobinding TFs. Genes specifically expressed in a cell line are often associated with a greater occurrence of nearby TF binding in that cell line. We observed cell-line-specific secondary motifs that mediate the binding of the histone deacetylase HDAC2 and the enhancer-binding protein EP300. TF binding sites are located in GC-rich, nucleosome-depleted, and DNase I sensitive regions, flanked by well-positioned nucleosomes, and many of these features show cell type specificity. The GC-richness may be beneficial for regulating TF binding, because, when unoccupied by a TF, these regions are occupied by nucleosomes in vivo. We present the results of our analysis in a TF-centric web repository Factorbook (http://factorbook.org) and will continually update this repository as more ENCODE data are generated.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ea19872ecc3e8e4768ce922544ad775cffd79855

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Citations in the corpus

Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest (2018, background): “Besides motif combinations, cell-type specificity may also be affected by the spatial arrangement of the motifs, existing histone modifications and DNA accessibility [13, 18, 19], and long range interactions [59].”
Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features (2014, methodology): “[18] PWMs if the q-value (false discovery rate) ,0.”
Comprehensive molecular portraits of invasive lobular breast cancer (2015, background): “3,976 most variable methylation probes mapping to FOXA1 binding sites (Table S3) and methylated in normal samples (Ross-Innes et al., 2012; Wang et al., 2012).”
Genomic positional conservation identifies topological anchor point (tap)RNAs linked to developmental loci (2016, methodology): “Using TF ChIP-seq peaks from the ENCODE project (The ENCODE Project Consortium, 2012; Wang et al., 2012), we observed a highly concordant pattern of occupancy in the promoters of pcRNAs and associated genes (Pearson correlation coefficient = 0.67, p-value < 1 × 10−3, Figure 2H).”
iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections (2014, methodology): “To evaluate the performance of iRegulon, we derived direct target gene sets for 115 sequence-specific TFs from the ENCODE ChIP-Seq data [46], and for each target set we investigate whether the ChIP’ped TF can be correctly recovered (see Materials and Methods).”
hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets (2019, methodology): “Putative motifs of the TF in a dataset were identified using a similar method proposed by Wang and colleagues [17].”
Learning from mistakes: Accurate prediction of cell type-specific transcription factor binding (2017, methodology): “…(Math-69 elier et al. , 2016), UniProbe (Newburger and Bulyk, 2009) or CisBP (Weirauch et al. , 2014), or from motif collections like Factorbook (Wang et al. , 2012), the ENCODE-71 motif collection (Kheradpour and Kellis, 2014), or Homer (Heinz et al. , 2010), while some perform de-novo motif…”