Interest of using imputation for genomic evaluation in layer chicken

Abstract

With the availability of the 600K Affymetrix Axiom high-density ( HD ) single nucleotide polymorphism ( SNP ) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values ( GEBV ) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits.

Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens

“…Aliloo et al [ 7 ] showed in bovines that the correlations between GEBVs estimated with the HD SNP chip (Illumina BovineHD BeadChip with 777 K SNPs) and GEBVs estimated with imputed low-density SNP chip of 4,013 and 25,410 SNP were, respectively 0.9398 and 0.9927. These results can be compared with the results presented in Herry et al [ 60 ], where several low-density SNP chips were designed according to an equidistant methodology or a methodology based on linkage disequilibrium. The same individuals were used in this study, and the impact of the use of these low-density SNP chips on genomic evaluations was evaluated.…”

“…With imputed 50 K genotyping from 6 K SNPs, Pearson correlations were 0.61 for milk yield and 0.62 for somatic cell score. Likewise, Herry et al [ 60 ] showed that the use of equidistant low-density SNP chips with an SNP density higher than 2 K SNPs led to no difference in Pearson correlations compared with that obtained using the HD SNP chip. Indeed, for the 2Kequi SNP chip, the correlations were 0.4929 for EW, 0.3126 for ESC, 0.3775 for ESS and 0.4157 for AH.…”

“…The previous work of Herry el al. [ 60 ] showed a low impact of imputation errors on genomic evaluations of the selection candidates using low-density SNP chips with more than 3 K SNPs. Consequently, the next step was to validate the simulated in silico GGRS and ddRADseq methods by investigating the impact of imputed HD genotyping of the selection candidates on genomic evaluations.…”