Predictions of Patterns of Response to Artificial Selection in Lines Derived From Natural Populations

• Published in: Genetics (Austin) Vol. 169; no. 1; pp. 411 - 425
• Main Authors: Zhang, Xu-Sheng, Hill, William G
• Format: Journal Article
• Language: English
• Published: United States Genetics Soc America 01.01.2005; Genetics Society of America
• Subjects: Artificial Intelligence; Evolutionary biology; Frequency distribution; Genetics, Population; Humans; Investigations; Linkage Disequilibrium; Models, Genetic; Natural populations; Population genetics; Predictive Value of Tests; Quantitative genetics; Quantitative Trait, Heritable; Selection, Genetic
• ISSN: 0016-6731; 1943-2631; 1943-2631
• DOI: 10.1534/genetics.104.032573

The pattern of response to artificial selection on quantitative traits in laboratory populations can tell us something of the genetic architecture in the natural population from which they were derived. We modeled artificial selection in samples drawn from natural populations in which variation had been maintained by recurrent mutation, with genes having an effect on the trait, which was subject to real stabilizing selection, and a pleitropic effect on fitness (the joint-effect model). Natural selection leads to an inverse correlation between effects and frequencies of genes, such that the frequency distribution of genes increasing the trait has an extreme U-shape. In contrast to the classical infinitesimal model, an early accelerated response and a larger variance of response among replicates were predicted. However, these are reduced if the base population has been maintained in the laboratory for some generations by random sampling prior to artificial selection. When multiple loci and linkage are also taken into account, the gametic disequilibria generated by the Bulmer and Hill-Robertson effects are such that little or no increase in variance and acceleration of response in early generations of artificial selection are predicted; further, the patterns of predicted responses for the joint-effect model now become close to those of the infinitesimal model. Comparison with data from laboratory selection experiments shows that, overall, the analysis did not provide clear support for the joint-effect model or a clear case for rejection.