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November 1, 1994Genetics305 citationsOpen Access

Genetic and statistical analyses of strong selection on polygenic traits: what, me normal?

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MTMichael TurelliNBNick Barton

Key Points

  • To establish a comprehensive statistical and population genetic framework evaluating how strong truncation and disruptive selection affect polygenic traits and testing the robustness of the standard Gaussian assumption.
  • Formulated an analytical framework representing haploid genotypes via multilocus cumulants and calculated selection effects on non-central moments using generating functions.
  • Derived exact recursions accounting for meiotic recombination permutations to determine next-generation cumulants across additive polygenic traits under the infinitesimal limit.
  • Standard Gaussian approximations accurately predict changes in population mean and genetic variance under strong truncation and disruptive selection.
  • Higher-order linkage disequilibria generate negligible deviations from normality, confirming that empirical prediction errors in artificial selection are not driven by linkage-disequilibrium non-normality.
  • Changes in genetic variance observed after 10 or more generations of selection are predominantly driven by locus-specific allele frequency dynamics rather than statistical departures from normality.

Abstract

We develop a general population genetic framework for analyzing selection on many loci, and apply it to strong truncation and disruptive selection on an additive polygenic trait. We first present statistical methods for analyzing the infinitesimal model, in which offspring breeding values are normally distributed around the mean of the parents, with fixed variance. These show that the usual assumption of a Gaussian distribution of breeding values in the population gives remarkably accurate predictions for the mean and the variance, even when disruptive selection generates substantial deviations from normality. We then set out a general genetic analysis of selection and recombination. The population is represented by multilocus cumulants describing the distribution of haploid genotypes, and selection is described by the relation between mean fitness and these cumulants. We provide exact recursions in terms of generating functions for the effects of selection on non-central moments. The effects of recombination are simply calculated as a weighted sum over all the permutations produced by meiosis. Finally, the new cumulants that describe the next generation are computed from the non-central moments. Although this scheme is applied here in detail only to selection on an additive trait, it is quite general. For arbitrary epistasis and linkage, we describe a consistent infinitesimal limit in which the short-term selection response is dominated by infinitesimal allele frequency changes and linkage disequilibria. Numerical multilocus results show that the standard Gaussian approximation gives accurate predictions for the dynamics of the mean and genetic variance in this limit. Even with intense truncation selection, linkage disequilibria of order three and higher never cause much deviation from normality. Thus, the empirical deviations frequently found between predicted and observed responses to artificial selection are not caused by linkage-disequilibrium-induced departures from normality. Disruptive selection can generate substantial four-way disequilibria, and hence kurtosis; but even then, the Gaussian assumption predicts the variance accurately. In contrast to the apparent simplicity of the infinitesimal limit, data suggest that changes in genetic variance after 10 or more generations of selection are likely to be dominated by allele frequency dynamics that depend on genetic details.

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Cite This Study

Turelli et al. (1994) studied this question.

synapsesocial.com/papers/69d7edd15c3030ff03d184b5https://doi.org/10.1093/genetics/138.3.913
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