Strategies for implementing genomic selection in family-based aquaculture breeding schemes: double haploid sib test populations

Kahsay G Nirea,John A Woolliams,Theo He Meuwissen,Anna K Sonesson

doi:10.1186/1297-9686-44-30

Abstract

BackgroundSimulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs.MethodsSix alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat), paternal (Pat) or a mixture of maternal and paternal (MatPat) double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC), minimum coancestry mating (MinC), or random (RAND) mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes.ResultsResults showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed.ConclusionsIn conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the selection candidates and require the use of sib tests, such as disease resistance and meat quality.

Highlights

Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes
Simulation studies have examined possible strategies to implement genomic selection in family-based aquaculture breeding schemes, generally following two stages [8]: first, single nucleotide polymorphism (SNP) marker effects are estimated in a test population consisting of sibs of the selection candidates and second, genome-wide breeding values of the genotyped selection candidates are estimated by summing up the estimated SNP marker effects
Increases in genetic gain and selection accuracy and the reduction in genetic variance were greatest for the maternal and paternal (MatPat) scheme

Summary

Introduction

Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In traditional aquaculture breeding schemes, selection for traits that cannot be measured on the selection candidates (e.g. disease resistance and fillet quality) is based on a performance test of sibs of the candidates, i.e. information on test sibs is used to calculate breeding values for the selection of parents This is due to the fact that measuring meat quality traits requires killing of the fish result in an increase in the accuracy of selection for an individual without a phenotype provided that the test set is sufficiently large and relevant to the selected population [2]. Simulation studies have examined possible strategies to implement genomic selection in family-based aquaculture breeding schemes, generally following two stages [8]: first, SNP marker effects are estimated in a test population consisting of sibs of the selection candidates and second, genome-wide breeding values of the genotyped selection candidates are estimated by summing up the estimated SNP marker effects. Other studies have supported these findings [9]

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Conclusion