Design of a low density SNP chip for genotype imputation in layer chickens

The main goal of selection is to choose breeders of the next generation among a set of selection candidates. In genomic selection, the choice of breeders is based on the use of information on DNA polymorphisms, in particular SNP, in addition of performance measures. Since 2013, a commercial high density genotyping chip (600,000 markers) for chicken allowed the implementation of genomic selection in layer and broiler breeding. However, genotyping costs with this chip still remain high for a routine use on a large number of selection candidates. Consequently, it is interesting to develop, at a lower cost, low density genotyping chips. To do so, a set of SNP markers has to be selected to enable an imputation (prediction) of missing genotypes with highaccuracy on a high density chip (HD chip).In this perspective, we conducted various simulation studies to choose the optimal strategy for low density genotyping of two different lines of laying hen. Different low density genotyping chips were designed according to two methodologies: a choice of SNP depending on a clustering of SNP based on linkage disequilibrium threshold or a choice of SNP at regular intervals (kb) along each chromosome. Imputation accuracy was assessed as the mean correlation between true and imputed genotypes. Results showed that correlations were more sensitive to false imputation of SNPs with low Minor Allele Frequency (MAF) with the equidistant methodology. Imputation accuracy improved with SNP density and when a higher LD threshold is used for SNP selection. Given the particular structure of the avian genome with chromosomes of very heterogeneous sizes and extents of LD, imputation accuracy differed according to the type of chromosome. All thesimulation studies showed that linkage disequilibrium methodology enabled to get better results of imputation than with equidistant methodology.