Literature DB >> 20659477

Evolutionary dynamics, epistatic interactions, and biological information.

Christopher C Strelioff1, Richard E Lenski, Charles Ofria.   

Abstract

We investigate a definition of biological information that connects population genetics with the tools of information theory by focusing on the distribution of genotypes found in a population. Previous research has treated loci as non-interacting by making specific approximations in the calculation of information-theoretic quantities. We expand earlier mathematical forms to include epistasis, or interactions between mutations at all pairs of loci. Application of our improved measure of biological information to evolution on two-locus, two-allele fitness landscapes demonstrates that mutual information between loci reflects epistatic interaction of mutations. Finally, we consider four-locus, two-allele fitness landscapes with modular structure. As modular interactions are inherently epistatic, we demonstrate that our refined approximation provides insight into the underlying structure of these non-trivial fitness landscapes.
Copyright © 2010 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20659477     DOI: 10.1016/j.jtbi.2010.07.025

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  4 in total

1.  Information theory, evolutionary innovations and evolvability.

Authors:  Andreas Wagner
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-12-05       Impact factor: 6.237

2.  Critical mutation rate has an exponential dependence on population size in haploid and diploid populations.

Authors:  Elizabeth Aston; Alastair Channon; Charles Day; Christopher G Knight
Journal:  PLoS One       Date:  2013-12-27       Impact factor: 3.240

3.  Drake's rule as a consequence of approaching channel capacity.

Authors:  Alexey A Shadrin; Dmitri V Parkhomchuk
Journal:  Naturwissenschaften       Date:  2014-09-17

4.  Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

Authors:  Aditi Gupta; Christoph Adami
Journal:  PLoS Genet       Date:  2016-03-30       Impact factor: 5.917

  4 in total

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