The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep.

Chen Wei,Yajun Zhang,Kechuan Tian,Xinming Xu,Wensheng Zhao,Hanpeng Luo,Xuefeng Fu,Hanikezi Tulafu,Bingru Zhao,Xixia Huang,Jiang Di,Weiwei Wu,Yuezhen Tian,Yachun Wang,Maerziya Yasen

doi:10.3390/ani10040569

Abstract

Simple SummaryGenetic improvement of wool production and quality traits in fine-wool sheep is an appealing option for enhancing the market value of wool products. We estimated genetic parameters and the accuracies of estimated breeding values for various wool production and quality traits in fine-wool sheep using pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) strategies. ssGBLUP performed slightly better than PBLUP for the studied traits. Therefore, the single-step genetic evaluation method could be successfully implemented in genomic evaluations of fine-wool sheep and the prediction of future breeding values in young Merino sheep as part of an early preselection strategy in the near future.Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

Highlights

In China, sheep and lambs are raised mainly in large farm flocks in the northern border regions and northwestern regions and in small ranching operations in the northeast
The heritabilities estimated for wool traits with single-step genomic best linear unbiased prediction (ssGBLUP) were slightly higher than those obtained with pedigree-based best linear unbiased prediction (PBLUP)
Little improvement occurred in terms of the accuracy of the estimated heritability, as the standard errors were similar between models with the

Summary

Introduction

In China, sheep and lambs are raised mainly in large farm flocks in the northern border regions and northwestern regions and in small ranching operations in the northeast. Over the last two decades, the wool clips in areas of major production have become progressively finer, while textile technology for processing superfine-wool types has improved. Wool quality and production traits are key features that reflect a fine-wool sheep’s economic value. Subjectively-assessed wool traits are widely used to select breeding ewes and rams in the sheep industry. These traits are often used together to determine the quality and grade of wool, as well as the main criteria for determining the price of wool. Breeding programs for fine-wool sheep have traditionally focused on improving wool production and wool quality. The genetic improvement of these traits is an appealing option for enhancing the market value of wool products

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