title: Comprehensive prediction in 78 human cell lines reveals rigidity and compactness of transcription factor dimers.
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.
authors.affiliation: Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672, Singapore.
authors.forename: Aleksander
authors.initials: A
authors.lastname: Jankowski
authors.forename: Ewa
authors.initials: E
authors.lastname: Szczurek
authors.forename: Ralf
authors.initials: R
authors.lastname: Jauch
authors.forename: Jerzy
authors.initials: J
authors.lastname: Tiuryn
authors.forename: Shyam
authors.initials: S
authors.lastname: Prabhakar
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D001665:Binding Sites; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D003198:Computer Simulation; D016384:Consensus Sequence; D053837:DNA Cleavage; D003850:Deoxyribonuclease I / Q000737:chemistry; D019143:Evolution, Molecular; D051541:Hepatocyte Nuclear Factor 3-alpha / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological; D011485:Protein Binding; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps; D055503:Protein Multimerization; D014157:Transcription Factors / Q000378:metabolism
chemical_list: C496499:FOXA1 protein, human; D051541:Hepatocyte Nuclear Factor 3-alpha; D014157:Transcription Factors; D003850:Deoxyribonuclease I
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