Design of a Bovine Low-Density SNP Array Optimized for Imputation

Didier Boichard,Tad S Sonstegard,Kimberly J Gietzen,André Eggen,George R Wiggans,Hoyoung Chung,Curtis P Van Tassell,Karine A Viaud-Martinez,For The Bovine Ld Consortium ,Xavier David,Sébastien Fritz,Romain Dassonneville,Cynthia T Lawley,Paul M Vanraden,Ben J Hayes

doi:10.1371/journal.pone.0034130

Abstract

The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs) that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where densities were increased. The chip also includes SNPs on the Y chromosome and mitochondrial DNA loci that are useful for determining subspecies classification and certain paternal and maternal breed lineages. The total number of SNPs was 6,909. Accuracy of imputation to Illumina BovineSNP50 genotypes using the BovineLD chip was over 97% for most dairy and beef populations. The BovineLD imputations were about 3 percentage points more accurate than those from the Illumina GoldenGate Bovine3K BeadChip across multiple populations. The improvement was greatest when neither parent was genotyped. The minor allele frequencies were similar across taurine beef and dairy breeds as was the proportion of SNPs that were polymorphic. The new BovineLD chip should facilitate low-cost genomic selection in taurine beef and dairy cattle.

Highlights

Genetic improvement of several key agricultural species is accelerating with the adoption of genomic selection [1,2,3]
The chip includes single-nucleotide polymorphisms (SNPs) on the Y chromosome and mitochondrial DNA (mtDNA) loci that are useful for gender checking, determining subspecies classification and identifying certain paternal and maternal breed lineages
Accuracy of imputation to BovineSNP50 genotypes using the BovineLD chip was .99% when both parents were genotyped in the North American BovineSNP50 reference population

Summary

Introduction

Genetic improvement of several key agricultural species is accelerating with the adoption of genomic selection [1,2,3]. With this method, animals or plants can be selected for breeding on the basis of their genetic merit predicted by markers spanning the entire genome. Genomic selection opens new opportunities for sustainable management of populations by more efficiently selecting for traits that have low heritability, e.g. fitness traits, or traits that are difficult to measure. This method is useful for managing the accumulation of inbreeding within breeds with a small effective population size. Genomic selection has been deployed at a rapid pace, and most countries with major dairy breeding programs rely heavily on this new technology [5]

Methods

Results

Conclusion