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RESEARCH ARTICLE

Application of single-step GBLUP in New Zealand Romney sheep

M. A. Nilforooshan https://orcid.org/0000-0003-0339-5442
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Department of Mathematics and Statistics, University of Otago, PO Box 56, Dunedin 9054, New Zealand. Present address: Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand. Email: mohammad.nilforooshan@lic.co.nz

Animal Production Science 60(9) 1136-1144 https://doi.org/10.1071/AN19315
Submitted: 16 January 2019  Accepted: 6 November 2019   Published: 21 April 2020

Abstract

Context: In New Zealand, Romney is the most predominant breed and is reared as a dual-purpose sheep. The number of genotypes is rapidly increasing in the sheep population, and making use of both genotypes and pedigree information is of importance for genetic evaluations. Single-step genomic best linear unbiased prediction (ssGBLUP) is a method for simultaneous prediction of genetic merits for genotyped and non-genotyped animals. The combination and the compatibility of the genomic relationship matrix (G) and the pedigree relationship matrix for genotyped animals (A22) is important for unbiased ssGBLUP.

Aims: The aim of the present study was to find an optimum genetic relationship matrix for ssGBLUP weaning-weight evaluation of Romney sheep in New Zealand.

Methods: Data consisted of adjusted weaning weights for 2 422 011 sheep, 50K single-nucleotide polymorphism genotypes for 13 304 animals and 3 028 688 animals in the pedigree. Blending of G and A22 was tested with weights (k) ranging from 0.2 to 0.99 (kG + (1 – k)A22), followed by none or one of the three methods of tuning G to A22.

Key results: The averages of G and A22 were close to each other for overall, diagonal and off-diagonal elements. Therefore, differently tuned G performed similarly. However, elements of G showed larger variation than did the elements of A22 and, on average, genotyped animals were less related in G than in A22. Correlations between genomic estimated breeding values (GEBV) for the top 500 genotyped animals, as well as the rank correlations, were almost 1 among ssGBLUP evaluations using tuned G. The corresponding correlations with BLUP evaluations were increased by blending G with a larger proportion of A22, and were further increased by tuning G, indicating improved compatibility between G and A22. Blending and tuning G suppressed the inflation of GEBV and bias and it moved the genetic trend closer to the genetic trend obtained from BLUP.

Conclusions: A combination of blending and tuning G to A22, with a blending rate of 0.5 at most, is recommended for weaning weight of Romney sheep in New Zealand. Failure to do that resulted in inflated GEBV that can reduce the accuracy of selection, especially for genotyped animals.

Implications: There is a growing interest in the single-step GBLUP method for simultaneous genetic evaluation of genotyped and non-genotyped animals, in which genomic and pedigree relationship matrices are admixed. Using data from New Zealand Romney sheep, we have shown that adjustment of the genomic relationship matrix on the basis of the pedigree relationship matrix is necessary to avoid inflated evaluations. Improving the compatibility between genomic and pedigree relationship matrices is important for obtaining accurate and unbiased single-step GBLUP evaluations.

Additional keywords: evaluation, genomics, quantitative genetics, weaning.


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