ArticleGenome research2013
Comprehensive prediction in 78 human cell lines reveals rigidity and compactness of transcription factor dimers.
Article in Genome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
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- Base-resolution models of transcription-factor binding reveal soft motif syntax.Nature genetics · 2021Article
- Asymmetric Conservation within Pairs of Co-Occurred Motifs Mediates Weak Direct Binding of Transcription Factors in ChIP-Seq Data.International journal of molecular sciences · 2020Article
- A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package.Nucleic acids research · 2019Article
- Homodimerization regulates an endothelial specific signature of the SOX18 transcription factor.Nucleic acids research · 2018Article
- TICA: Transcriptional Interaction and Coregulation Analyzer.Genomics, proteomics & bioinformatics · 2018Article
- coTRaCTE predicts co-occurring transcription factors within cell-type specific enhancers.PLoS computational biology · 2018Article
- DNA-mediated dimerization on a compact sequence signature controls enhancer engagement and regulation by FOXA1.Nucleic acids research · 2018Article
- Synergistic co-regulation and competition by a SOX9-GLI-FOXA phasic transcriptional network coordinate chondrocyte differentiation transitions.PLoS genetics · 2018Article
- Genomic and molecular control of cell type and cell type conversions.Cell regeneration (London, England) · 2017Review
- Quantitative profiling of selective Sox/POU pairing on hundreds of sequences in parallel by Coop-seq.Nucleic acids research · 2017Article
- Romulus: robust multi-state identification of transcription factor binding sites from DNase-seq data.Bioinformatics (Oxford, England) · 2016Article
- Enhanceosome transcription factors preferentially dimerize with high mobility group proteins.BMC systems biology · 2016Article
- Changes in the enhancer landscape during early placental development uncover a trophoblast invasion gene-enhancer network.Placenta · 2016Article
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Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The binding of transcription factors (TFs) to their specific motifs in genomic regulatory regions is commonly studied in isolation. However, in order to elucidate the mechanisms of transcriptional regulation, it is essential to determine which TFs bind DNA cooperatively as dimers and to infer the precise nature of these interactions. So far, only a small number of such dimeric complexes are known. Here, we present an algorithm for predicting cell-type-specific TF-TF dimerization on DNA on a large scale, using DNase I hypersensitivity data from 78 human cell lines. We represented the universe of possible TF complexes by their corresponding motif complexes, and analyzed their occurrence at cell-type-specific DNase I hypersensitive sites. Based on ∼1.4 billion tests for motif complex enrichment, we predicted 603 highly significant cell-type-specific TF dimers, the vast majority of which are novel. Our predictions included 76% (19/25) of the known dimeric complexes and showed significant overlap with an experimental database of protein-protein interactions. They were also independently supported by evolutionary conservation, as well as quantitative variation in DNase I digestion patterns. Notably, the known and predicted TF dimers were almost always highly compact and rigidly spaced, suggesting that TFs dimerize in close proximity to their partners, which results in strict constraints on the structure of the DNA-bound complex. Overall, our results indicate that chromatin openness profiles are highly predictive of cell-type-specific TF-TF interactions. Moreover, cooperative TF dimerization seems to be a widespread phenomenon, with multiple TF complexes predicted in most cell types.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.