ArticleNucleic acids research2014
CCAT: Combinatorial Code Analysis Tool for transcriptional regulation.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Identification of transcription factor co-binding patterns with non-negative matrix factorization.Nucleic acids research · 2024Article
- Intraepithelial Lymphocytes of the Intestine.Annual review of immunology · 2024Review
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- Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome.Genome research · 2021Article
- Accurate prediction ofNAR genomics and bioinformatics · 2021Article
- Integrative analyses of single-cell transcriptome and regulome using MAESTRO.Genome biology · 2020Article
- Article
- Systematic target function annotation of human transcription factors.BMC biology · 2018Article
- Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization.PloS one · 2018Article
- Transcription factor-DNA binding: beyond binding site motifs.Current opinion in genetics & development · 2017Review
- Motif comparison based on similarity of binding affinity profiles.Bioinformatics (Oxford, England) · 2016Article
- Combinatorial Cis-regulation in Saccharomyces Species.G3 (Bethesda, Md.) · 2016Article
- Mapping and analysis of Caenorhabditis elegans transcription factor sequence specificities.eLife · 2015Article
- Pervasive variation of transcription factor orthologs contributes to regulatory network evolution.PLoS genetics · 2015Article
- Absence of a simple code: how transcription factors read the genome.Trends in biochemical sciences · 2014Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Combinatorial interplay among transcription factors (TFs) is an important mechanism by which transcriptional regulatory specificity is achieved. However, despite the increasing number of TFs for which either binding specificities or genome-wide occupancy data are known, knowledge about cooperativity between TFs remains limited. To address this, we developed a computational framework for predicting genome-wide co-binding between TFs (CCAT, Combinatorial Code Analysis Tool), and applied it to Drosophila melanogaster to uncover cooperativity among TFs during embryo development. Using publicly available TF binding specificity data and DNaseI chromatin accessibility data, we first predicted genome-wide binding sites for 324 TFs across five stages of D. melanogaster embryo development. We then applied CCAT in each of these developmental stages, and identified from 19 to 58 pairs of TFs in each stage whose predicted binding sites are significantly co-localized. We found that nearby binding sites for pairs of TFs predicted to cooperate were enriched in regions bound in relevant ChIP experiments, and were more evolutionarily conserved than other pairs. Further, we found that TFs tend to be co-localized with other TFs in a dynamic manner across developmental stages. All generated data as well as source code for our front-to-end pipeline are available at http://cat.princeton.edu.
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Registered trials
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.