Comparing genomic prediction accuracy from purebred, crossbred and combined purebred and crossbred reference populations in sheep.

Nasir Moghaddar,Julius Hj Van Der Werf,Andrew A Swan

doi:10.1186/s12711-014-0058-4

Nasir Moghaddar, Julius Hj Van Der Werf + Show 1 more

Open Access

https://doi.org/10.1186/s12711-014-0058-4

Copy DOI

Abstract

BackgroundThe accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. In some industries, such as sheep and beef cattle, data are often available from a mixture of breeds, multiple strains within a breed or from crossbred animals. The objective of this study was to compare the accuracy of genomic prediction for several economically important traits in sheep when using data from purebreds, crossbreds or a combination of those in a reference population.MethodsThe reference populations were purebred Merinos, crossbreds of Border Leicester (BL), Poll Dorset (PD) or White Suffolk (WS) with Merinos and combinations of purebred and crossbred animals. Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), using a genomic relationship matrix calculated based on 48 599 Ovine SNP (single nucleotide polymorphisms) genotypes. The accuracy of GBV was assessed in a group of purebred industry sires based on the correlation coefficient between GBV and accurate estimated breeding values based on progeny records.ResultsThe accuracy of GBV for Merino sires increased with a larger purebred Merino reference population, but decreased when a large purebred Merino reference population was augmented with records from crossbred animals. The GBV accuracy for BL, PD and WS breeds based on crossbred data was the same or tended to decrease when more purebred Merinos were added to the crossbred reference population. The prediction accuracy for a particular breed was close to zero when the reference population did not contain any haplotypes of the target breed, except for some low accuracies that were obtained when predicting PD from WS and vice versa.ConclusionsThis study demonstrates that crossbred animals can be used for genomic prediction of purebred animals using 50 k SNP marker density and GBLUP, but crossbred data provided lower accuracy than purebred data. Including data from distant breeds in a reference population had a neutral to slightly negative effect on the accuracy of genomic prediction. Accounting for differences in marker allele frequencies between breeds had only a small effect on the accuracy of genomic prediction from crossbred or combined crossbred and purebred reference populations.

Highlights

The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes
Statistical methods Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), replacing the pedigree-based numerator relationship matrix with a genomic relationship matrix [18,19] based on marker genotypes
The GBV accuracy of Merino sires was higher for post-weaning weight (PWWT) than for the other two traits

Summary

Introduction

The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. For a given reference population size, Ibanez -Escriche et al [7] reported similar prediction accuracy for a single breed when using either purebreds or crossbreds in a reference population, while Toosi et al [5] reported slightly lower prediction accuracy from crossbreds than purebreds These simulation results depend on the assumptions made about the underlying genetic model and the degree of LD that exists within and across breeds. Analysis of real data has shown that information from other breeds generally does not increase the prediction accuracy of a given breed at a 50 k marker density in dairy cattle [8,9,10], beef cattle [11] or sheep [12,13]. These results suggest that LD between markers and putative QTL mostly does not extend across breeds at a 50 k marker density

Objectives

Methods

Results

Discussion

Conclusion