MacIsaac KD, Lo KA, Gordon W, Motola S, Mazor T, Fraenkel E. A quantitative model of transcriptional regulation reveals the influence of binding location on expression.
PLoS Comput Biol 2010;
6:e1000773. [PMID:
20442865 PMCID:
PMC2861697 DOI:
10.1371/journal.pcbi.1000773]
[Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2009] [Accepted: 03/30/2010] [Indexed: 11/19/2022] Open
Abstract
Understanding the mechanistic basis of transcriptional regulation has been a central focus of molecular biology since its inception. New high-throughput chromatin immunoprecipitation experiments have revealed that most regulatory proteins bind thousands of sites in mammalian genomes. However, the functional significance of these binding sites remains unclear. We present a quantitative model of transcriptional regulation that suggests the contribution of each binding site to tissue-specific gene expression depends strongly on its position relative to the transcription start site. For three cell types, we show that, by considering binding position, it is possible to predict relative expression levels between cell types with an accuracy approaching the level of agreement between different experimental platforms. Our model suggests that, for the transcription factors profiled in these cell types, a regulatory site's influence on expression falls off almost linearly with distance from the transcription start site in a 10 kilobase range. Binding to both evolutionarily conserved and non-conserved sequences contributes significantly to transcriptional regulation. Our approach also reveals the quantitative, tissue-specific role of individual proteins in activating or repressing transcription. These results suggest that regulator binding position plays a previously unappreciated role in influencing expression and blurs the classical distinction between proximal promoter and distal binding events.
Gene expression is controlled, in large part, by regulatory proteins called transcription factors that bind specific sites in the genome. A major focus of molecular biology has been understanding how these transcription factors interact with the cell's transcriptional machinery, the genome, and with each other to turn genes' expression on and off in various physiological contexts. Previous approaches for modeling transcriptional regulation have focused on the complex combinatorial interactions between groups of transcription factors at regulatory sites, or on the specific activating or repressive functions of individual proteins. In this work, we present a new modeling framework and demonstrate that an equally important, and previously overlooked, consideration in predicting the effect that a regulatory site has on gene expression is simply its location relative to the transcription start site of nearby genes. Our results show that, in general, the closer a binding event is to a gene's transcription start site, the more it influences expression. We also show that considering the particular proteins bound at a regulatory site helps predict the expression of nearby genes. However, considering the sequence conservation level of these sites does not lead to more accurate predictions.
Collapse