Interest of using imputation for genomic evaluation in layer chicken

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Poultry Science

Background:

• Genomic selection (GS) in chickens relies on high-density (HD) SNP chips, which are costly for large-scale application.
• Developing cost-effective low-density (LD) SNP chips requires imputation of missing markers to maintain genomic evaluation accuracy.

Purpose of the Study:

• To assess the impact of imputation on genomic evaluation accuracy using LD SNP chips in layer chickens.
• To compare the accuracy of genomic estimated breeding values (GEBV) derived from imputed LD genotypes versus HD genotypes.

Main Methods:

• Two LD SNP chip designs (equidistant and linkage disequilibrium) were evaluated.
• Single-step genomic best linear unbiased prediction (GBLUP) was used for genomic evaluation.
• Accuracy was assessed by comparing GEBV from LD (imputed and non-imputed) and HD genotypes, with offspring GEBV as a reference.

Main Results:

• Spearman correlations between GEBV from HD and LD genotypes (with imputation) exceeded 0.94 with >3K SNPs.
• Imputation reduced candidate reordering, maintaining high correlations for top individuals.
• Without imputation, correlations were substantially lower (<0.85) depending on the LD design and SNP count.

Conclusions:

• Imputation is crucial for maintaining high genomic evaluation accuracy with LD SNP chips in chickens.
• LD SNP chips combined with imputation offer a cost-effective alternative to HD chips for genomic selection.
• The choice between equidistant and LD-based imputation designs did not significantly impact GEBV accuracy.