Structure of the Transcriptional Regulatory Network Correlates with Regulatory Divergence in Drosophila

被引:20
|
作者
Yang, Bing [1 ]
Wittkopp, Patricia J. [1 ,2 ]
机构
[1] Univ Michigan, Dept Mol Cellular & Dev Biol, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
regulatory network; evolution; cis-regulation; transcription factor; in-degree; out-degree; gene expression; EVOLUTION; CIS; PLEIOTROPY; DISCOVERY; INFERENCE;
D O I
10.1093/molbev/msx068
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Transcriptional control of gene expression is regulated by biochemical interactions between cis-regulatory DNA sequences and trans-acting factors that form complex regulatory networks. Genetic changes affecting both cis- and trans-acting sequences in these networks have been shown to alter patterns of gene expression as well as higher-order organismal phenotypes. Here, we investigate how the structure of these regulatory networks relates to patterns of polymorphism and divergence in gene expression. To do this, we compared a transcriptional regulatory network inferred for Drosophila melanogaster to differences in gene regulation observed between two strains of D. melanogaster as well as between two pairs of closely related species: Drosophila sechellia and Drosophila simulans, and D. simulans and D. melanogaster. We found that the number of transcription factors predicted to directly regulate a gene ("in-degree") was negatively correlated with divergence in both gene expression (mRNA abundance) and cis-regulation. This observation suggests that the number of transcription factors directly regulating a gene's expression affects the conservation of cis-regulation and gene expression over evolutionary time. We also tested the hypothesis that transcription factors regulating more target genes (higher "out-degree") are less likely to evolve changes in their cis-regulation and expression (presumably due to increased pleiotropy), but found little support for this predicted relationship. Taken together, these data show how the architecture of regulatory networks can influence regulatory evolution.
引用
收藏
页码:1352 / 1362
页数:11
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