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

• Main Authors: Katy Denise Heath, Scott eNuismer
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-04-01
• Series: Frontiers in Genetics
• Subjects: Symbiosis; pathogen; Epistasis; Coevolution; intergenomic epistasis
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fgene.2014.00077/full

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.