ncDNA and drift drive binding site accumulation

BMC Evolutionary Biology. 2012;12(1):159 DOI 10.1186/1471-2148-12-159

 

Journal Homepage

Journal Title: BMC Evolutionary Biology

ISSN: 1471-2148 (Online)

Publisher: BMC

LCC Subject Category: Science: Biology (General): Evolution

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS


Ruths Troy

Nakhleh Luay

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 17 weeks

 

Abstract | Full Text

<p>Abstract</p> <p>Background</p> <p>The amount of transcription factor binding sites (TFBS) in an organism’s genome positively correlates with the complexity of the regulatory network of the organism. However, the manner by which TFBS arise and accumulate in genomes and the effects of regulatory network complexity on the organism’s fitness are far from being known. The availability of TFBS data from many organisms provides an opportunity to explore these issues, particularly from an evolutionary perspective.</p> <p>Results</p> <p>We analyzed TFBS data from five model organisms – <it>E. coli K12</it>, <it>S. cerevisiae</it>, <it>C. elegans</it>, <it>D. melanogaster</it>, <it>A. thaliana</it> – and found a positive correlation between the amount of non-coding DNA (ncDNA) in the organism’s genome and regulatory complexity. Based on this finding, we hypothesize that the amount of ncDNA, combined with the population size, can explain the patterns of regulatory complexity across organisms. To test this hypothesis, we devised a genome-based regulatory pathway model and subjected it to the forces of evolution through population genetic simulations. The results support our hypothesis, showing neutral evolutionary forces alone can explain TFBS patterns, and that selection on the regulatory network function does not alter this finding.</p> <p>Conclusions</p> <p>The <it>cis</it>-regulome is not a clean functional network crafted by adaptive forces alone, but instead a data source filled with the noise of non-adaptive forces. From a regulatory perspective, this evolutionary noise manifests as complexity on both the binding site and pathway level, which has significant implications on many directions in microbiology, genetics, and synthetic biology.</p>