Efficiency of marker-assisted selection in the improvement of quantitative traits.

TLDR

Marker-assisted selection (MAS) integrates molecular genetics with traditional phenotypic selection. The study derives selection indices that maximize improvement in quantitative traits by combining marker polymorphism data with phenotypic variation. The authors analyze statistical limits of MAS and outline that initial genotyping of hundreds of markers on hundreds to thousands of individuals, with fewer markers in later generations, supports the selection indices. MAS can substantially increase selection efficiency after hybridization, with gains and required sample sizes depending on genetic parameters and the selection scheme.

Abstract

Abstract Molecular genetics can be integrated with traditional methods of artificial selection on phenotypes by applying marker-assisted selection (MAS). We derive selection indices that maximize the rate of improvement in quantitative characters under different schemes of MAS combining information on molecular genetic polymorphisms (marker loci) with data on phenotypic variation among individuals (and their relatives). We also analyze statistical limitations on the efficiency of MAS, including the detectability of associations between marker loci and quantitative trait loci, and sampling errors in estimating the weighting coefficients in the selection index. The efficiency of artificial selection can be increased substantially using MAS following hybridization of selected lines. This requires initially scoring genotypes at a few hundred molecular marker loci, as well as phenotypic traits, on a few hundred to a few thousand individuals; the number of marker loci scored can be greatly reduced in later generations. The increase in selection efficiency from the use of marker loci, and the sample sizes necessary to achieve them, depend on the genetic parameters and the selection scheme.