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Smaller Gene Networks Permit Longer Persistence in Fast-Changing Environments
Author(s) -
Jacob Malcom
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0014747
Subject(s) - heritability , genetic architecture , epistasis , biology , trait , persistence (discontinuity) , adaptation (eye) , population , evolutionary biology , environmental change , gene regulatory network , quantitative trait locus , genetics , missing heritability problem , gene–environment interaction , quantitative genetics , ecology , genetic variation , gene , computer science , climate change , demography , genotype , single nucleotide polymorphism , engineering , gene expression , geotechnical engineering , neuroscience , sociology , programming language
The environments in which organisms live and reproduce are rarely static, and as the environment changes, populations must evolve so that phenotypes match the challenges presented. The quantitative traits that map to environmental variables are underlain by hundreds or thousands of interacting genes whose allele frequencies and epistatic relationships must change appropriately for adaptation to occur. Extending an earlier model in which individuals possess an ecologically-critical trait encoded by gene networks of 16 to 256 genes and random or scale-free topology, I test the hypothesis that smaller, scale-free networks permit longer persistence times in a constantly-changing environment. Genetic architecture interacting with the rate of environmental change accounts for 78% of the variance in trait heritability and 66% of the variance in population persistence times. When the rate of environmental change is high, the relationship between network size and heritability is apparent, with smaller and scale-free networks conferring a distinct advantage for persistence time. However, when the rate of environmental change is very slow, the relationship between network size and heritability disappears and populations persist the duration of the simulations, without regard to genetic architecture. These results provide a link between genes and population dynamics that may be tested as the -omics and bioinformatics fields mature, and as we are able to determine the genetic basis of ecologically-relevant quantitative traits.

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