Dataset Information

Decoupling of evolutionary changes in transcription factor binding and gene expression in mammals.

ABSTRACT: To understand the evolutionary dynamics between transcription factor (TF) binding and gene expression in mammals, we compared transcriptional output and the binding intensities for three tissue-specific TFs in livers from four closely related mouse species. For each transcription factor, TF-dependent genes and the TF binding sites most likely to influence mRNA expression were identified by comparing mRNA expression levels between wild-type and TF knockout mice. Independent evolution was observed genome-wide between the rate of change in TF binding and the rate of change in mRNA expression across taxa, with the exception of a small number of TF-dependent genes. We also found that binding intensities are preferentially conserved near genes whose expression is dependent on the TF, and the conservation is shared among binding peaks in close proximity to each other near the TSS. Expression of TF-dependent genes typically showed an increased sensitivity to changes in binding levels as measured by mRNA abundance. Taken together, these results highlight a significant tolerance to evolutionary changes in TF binding intensity in mammalian transcriptional networks and suggest that some TF-dependent genes may be largely regulated by a single TF across evolution.

SUBMITTER: Wong ES

PROVIDER: S-EPMC4315291 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Decoupling of evolutionary changes in transcription factor binding and gene expression in mammals.

Wong Emily S ES Thybert David D Schmitt Bianca M BM Stefflova Klara K Odom Duncan T DT Flicek Paul P

Genome research 20141113 2

To understand the evolutionary dynamics between transcription factor (TF) binding and gene expression in mammals, we compared transcriptional output and the binding intensities for three tissue-specific TFs in livers from four closely related mouse species. For each transcription factor, TF-dependent genes and the TF binding sites most likely to influence mRNA expression were identified by comparing mRNA expression levels between wild-type and TF knockout mice. Independent evolution was observed ...[more]

PMID: 25394363

Similar Datasets

Project description:Empirical studies have revealed that regulatory DNA sequences such as enhancers or promoters often harbor multiple binding sites for the same transcription factor. Such "homotypic site clustering" has been hypothesized as arising out of functional requirements of the sequences. Here, we propose an alternative explanation of this phenomenon that multisite enhancers are common because they are favored by evolutionary sampling of the genotype-phenotype landscape. To test this hypothesis, we developed a new computational framework specialized for population genetic simulations of enhancer evolution. It uses a thermodynamics-based model of enhancer function, integrating information from strong as well as weak binding sites, to determine the strength of selection. Using this framework, we found that even when simpler genotypes exist for a desired strength of regulation, relatively complex genotypes (enhancers with more sites) are more readily reached by the simulated evolutionary process. We show that there are more ways to "build" a fit genotype with many weak sites than with a few strong sites, and this is why evolution finds complex genotypes more often. Our claims are consistent with an empirical analysis of binding site content in enhancers characterized in Drosophila melanogaster and their orthologs in other Drosophila species. We also characterized a subtle but significant difference between genotypes likely to be sampled by evolution and equally fit genotypes one would obtain by uniform sampling of the fitness landscape, that is, an "evolutionary signature" in enhancer sequences. Finally, we investigated potential effects of other factors, such as rugged fitness landscapes, short local duplications, and noise characteristics of enhancers, on the emergence of homotypic site clustering. Homotypic site clustering is an important contributor to the complexity and function of cis-regulatory sequences. This work provides a simple null hypothesis for its origin, against which alternative adaptationist explanations may be evaluated, and cautions against "evolutionary mirages" present in common features of genomic sequence. The quantitative framework we develop here can be used more generally to understand how mechanisms of enhancer action influence their composition and evolution.

Dataset Information

Decoupling of evolutionary changes in transcription factor binding and gene expression in mammals.

Publications

Decoupling of evolutionary changes in transcription factor binding and gene expression in mammals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets