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Front Genet. 2014 Apr 11;5:77. doi: 10.3389/fgene.2014.00077. eCollection 2014.

Connecting functional and statistical definitions of genotype by genotype interactions in coevolutionary studies.

Author information

1
Department of Plant Biology, University of Illinois Urbana, IL, USA.
2
Department of Biological Sciences, University of Idaho Moscow, ID, USA.

Abstract

Predicting how species interactions evolve requires that we understand the mechanistic basis of coevolution, and thus the functional genotype-by-genotype interactions (G × G) that drive reciprocal natural selection. Theory on host-parasite coevolution provides testable hypotheses for empiricists, but depends upon models of functional G × G that remain loosely tethered to the molecular details of any particular system. In practice, reciprocal cross-infection studies are often used to partition the variation in infection or fitness in a population that is attributable to G × G (statistical G × G). Here we use simulations to demonstrate that within-population statistical G × G likely tells us little about the existence of coevolution, its strength, or the genetic basis of functional G × G. Combined with studies of multiple populations or points in time, mapping and molecular techniques can bridge the gap between natural variation and mechanistic models of coevolution, while model-based statistics can formally confront coevolutionary models with cross-infection data. Together these approaches provide a robust framework for inferring the infection genetics underlying statistical G × G, helping unravel the genetic basis of coevolution.

KEYWORDS:

coevolution; epistasis; intergenomic epistasis; pathogen; symbiosis

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