Directionality of Epistasis in a Murine Intercross Population

Abstract

Directional epistasis describes a situation in which epistasis consistently increases or decreases the effect of allele substitutions, thereby affecting the amount of additive genetic variance available for selection in a given direction. This study applies a recent parameterization of directionality of epistasis to empirical data. Data stems from a QTL mapping study on an intercross between inbred mouse (Mus musculus) strains LG/J and SM/J, originally selected for large and small body mass, respectively. Results show a negative average directionality of epistasis for body-composition traits, predicting a reduction in additive allelic effects and in the response to selection for increased size. Focusing on average modification of additive effect of single loci, we find a more complex picture, whereby the effects of some loci are enhanced consistently across backgrounds, while effects of other loci are decreased, potentially contributing to either enhancement or reduction of allelic effects when selection acts at single loci. We demonstrate and discuss how the interpretation of the overall measurement of directionality depends on the complexity of the genotype-phenotype map. The measure of directionality changes with the power of scale in a predictable way; however, its expected effect with respect to the modification of additive genetic effects remains constant. E PISTASIS is present when the effect of a genetic substitution depends on the genotypes at other loci. At the population level, this means that average allelic effects change as allele frequencies at other loci change, and thus that gene effects can evolve. The evolutionary significance of epistasis has been recognized mainly in relation to the allele-frequency changes that are caused by genetic drift (e.g

Genotype-Phenotype Maps Maximizing Evolvability: Modularity Revisited

“…The B matrix represents a linear genotype-phenotype map. Nevertheless, epistasis is a common finding in empirical studies across species (e.g., Wolf et al 2000;Cheverud et al 2001;Bradshaw et al 2005;Brem and Kruglyak 2005;Malmberg et al 2005;West et al 2007;Le Rouzic et al 2008;Pavlicev et al 2010). So far modeling the effects of epistasis on evolvability has been restricted to the univariate case (Hermisson et al 2003;Carter et al 2005;Hansen et al 2006; but see Hansen and Wagner 2001).…”

“…So far modeling the effects of epistasis on evolvability has been restricted to the univariate case (Hermisson et al 2003;Carter et al 2005;Hansen et al 2006; but see Hansen and Wagner 2001). When epistasis affects pleiotropic genes, it can change variances and covariances of traits in a variety of ways, depending on exactly how gene substitutions modify the effects of each other (Hansen and Wagner 2001;Cheverud et al 2004;Carter et al 2005;Hansen 2006;Wolf et al 2006;Pavlicev et al 2008Pavlicev et al , 2010Pavlicev et al , 2011a. Expanding the existing study of effects of epistasis on evolvability to the multivariate case will reveal to what extent epistasis may allow pleiotropy to evolve in a manner that could increase evolvability, or alternatively, decrease evolvability through canalization.…”

A modelling framework for the analysis of artificial-selection time series

“…mutational variance, effective population size), it can be estimated from QTL data Pavlicev et al, 2010), and thus has the potential to help linking the results of reductionist geneticarchitecture dissections and selection-response approaches. mutational variance, effective population size), it can be estimated from QTL data Pavlicev et al, 2010), and thus has the potential to help linking the results of reductionist geneticarchitecture dissections and selection-response approaches.…”

“…Directional epistasis or dominance on a linear scale might vanish on a different scale (Pavlicev et al, 2010), or, on the contrary, apparent additivity might hide interesting physiological interactions. Directional epistasis or dominance on a linear scale might vanish on a different scale (Pavlicev et al, 2010), or, on the contrary, apparent additivity might hide interesting physiological interactions.…”

The Evolution of Trade-Offs Under Directional and Correlational Selection

“…Phenotypic models of trait evolution typically focus upon models in which trade‐offs and other bivariate relationships are represented by deterministic equations that describe the consequences of changes in one trait upon other traits and thus the overall trait means (Maynard Smith 1982; Roff 1992, 2002, 2010; Stearns 1992; Charnov 1993; Houston and McNamara 1999; Clark and Mangel 2001; Kokko 2007). In contrast, quantitative genetic theory focuses upon the population variances and covariances and uses the breeder's equation or its multivariate equivalent consisting of the product of the genetic variance–covariance matrix, G , and the vector of selection gradients, β to predict the change in trait means (: Bulmer 1985; Falconer 1989; Lynch and Walsh 1997; Roff 1997, 2010). While the phenotypic models use the functional form of the trade‐off, quantitative genetic models subsume this in the assumed multivariate normal distribution of traits.…”