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Mechanistic Explanations for Restricted Evolutionary Paths That Emerge from Gene Regulatory Networks

Overview of attention for article published in PLOS ONE, April 2013
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Title
Mechanistic Explanations for Restricted Evolutionary Paths That Emerge from Gene Regulatory Networks
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0061178
Pubmed ID
Authors

James Cotterell, James Sharpe

Abstract

The extent and the nature of the constraints to evolutionary trajectories are central issues in biology. Constraints can be the result of systems dynamics causing a non-linear mapping between genotype and phenotype. How prevalent are these developmental constraints and what is their mechanistic basis? Although this has been extensively explored at the level of epistatic interactions between nucleotides within a gene, or amino acids within a protein, selection acts at the level of the whole organism, and therefore epistasis between disparate genes in the genome is expected due to their functional interactions within gene regulatory networks (GRNs) which are responsible for many aspects of organismal phenotype. Here we explore epistasis within GRNs capable of performing a common developmental function--converting a continuous morphogen input into discrete spatial domains. By exploring the full complement of GRN wiring designs that are able to perform this function, we analyzed all possible mutational routes between functional GRNs. Through this study we demonstrate that mechanistic constraints are common for GRNs that perform even a simple function. We demonstrate a common mechanistic cause for such a constraint involving complementation between counter-balanced gene-gene interactions. Furthermore we show how such constraints can be bypassed by means of "permissive" mutations that buffer changes in a direct route between two GRN topologies that would normally be unviable. We show that such bypasses are common and thus we suggest that unlike what was observed in protein sequence-function relationships, the "tape of life" is less reproducible when one considers higher levels of biological organization.

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Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
Germany 1 2%
Austria 1 2%
Unknown 45 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Bachelor 8 16%
Researcher 7 14%
Student > Master 5 10%
Other 4 8%
Other 9 18%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 42%
Biochemistry, Genetics and Molecular Biology 12 24%
Physics and Astronomy 6 12%
Engineering 2 4%
Computer Science 1 2%
Other 3 6%
Unknown 5 10%