Heterogeneity of transcription factor binding specificity models within and across cell lines.
Complex gene expression patterns are mediated by the binding of transcription factors (TFs) to specific genomic loci. The in vivo occupancy of a TF is, in large part, determined by the TF's DNA binding interaction partners, motivating genomic context-based models of TF occupancy. However, approaches thus far have assumed a uniform TF binding model to explain genome-wide cell-type-specific binding sites. Therefore, the cell type heterogeneity of TF occupancy models, as well as the extent to which binding rules underlying a TF's occupancy are shared across cell types, has not been investigated. Here, we develop an ensemble-based approach (TRISECT) to identify the heterogeneous binding rules for cell-type-specific TF occupancy and analyze the inter-cell-type sharing of such rules. Comprehensive analysis of 23 TFs, each with ChIP-seq data in four to 12 different cell types, shows that by explicitly capturing the heterogeneity of binding rules, TRISECT accurately identifies in vivo TF occupancy. Importantly, many of the binding rules derived from individual cell types are shared across cell types and reveal distinct yet functionally coherent putative target genes in different cell types. Closer inspection of the predicted cell-type-specific interaction partners provides insights into the context-specific functional landscape of a TF. Together, our novel ensemble-based approach reveals, for the first time, a widespread heterogeneity of binding rules, comprising the interaction partners within a cell type, many of which nevertheless transcend cell types. Notably, the putative targets of shared binding rules in different cell types, while distinct, exhibit significant functional coherence.
Department of Computer Science, University of Maryland, College Park, Maryland 20742, USA; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA;
Mahfuza
M
Sharmin
Department of Computer Science, University of Maryland, College Park, Maryland 20742, USA; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA;
Héctor Corrada
HC
Bravo
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA; Department of Cell and Molecular Biology, University of Maryland, College Park, Maryland 20742, USA.
Sridhar
S
Hannenhalli
D001665:Binding Sites / Q000235:genetics; D019070:Cell Lineage / Q000235:genetics; D019295:Computational Biology; D004268:DNA-Binding Proteins / Q000235:genetics*; D005786:Gene Expression Regulation; D018740:Genetic Heterogeneity; D023281:Genomics; D006801:Humans; D011485:Protein Binding / Q000235:genetics*; D012680:Sensitivity and Specificity; D014157:Transcription Factors / Q000235:genetics*
D004268:DNA-Binding Proteins; D014157:Transcription Factors