Abstract
Simple SummaryThe domesticated yak is among the most important livestock species on the Qinghai-Tibet Plateau. Breeders have the task of developing varieties that provide growth performance and disease resistance. Traditional breeding processes rely on complete family pedigree information and large numbers of data records. However, there are inevitably records that are missing, including incomplete pedigrees and long-term data tracking, resulting in prolonged breeding cycles, reduced breeding efficiency, and the lack of economic benefit. Genome selection (GS), also known as whole genomic selection (WGS), can significantly reduce the selection cycle of quantitative traits and accelerate genetic progression while displaying appropriate prediction accuracy (PA). It combines a reference population and single nucleotide polymorphism (SNP) loci rather than pedigrees to estimate the effect of all SNPs. Then breeding values of target traits are predicted. The key for GS is genomic prediction (GP) and an assessment of PA.The aim of this study was to explore the possibility of applying GP to important economic traits in the domesticated yak, thus providing theoretical support for its molecular breeding. A reference population was constructed consisting of 354 polled yaks, measuring four growth traits and eight hematological traits related to resistance to disease (involved in immune response and phagocytosis). The Illumina bovine HD 770k chip was used to obtain SNP information of all the individuals. With these genotypes and phenotypes, GBLUP, Bayes B and Bayes Cπ methods were used to predict genomic estimated breeding values (GEBV) and assess prediction capability. The correlation coefficient of the association of GEBV with estimated breeding value (EBV) was used as PA for each trait. The prediction accuracy varied from 0.043 to 0.281 for different traits. Each trait displayed similar PAs when using the three methods. Lymphocyte counts (LYM) exhibited the highest predictive accuracy (0.319) during all GP, while chest girth (CG) provided the lowest predictive accuracy (0.043). Our results showed moderate PA in most traits such as body length (0.212) and hematocrit (0.23). Those traits with lower PA could be improved by using SNP chips designed specifically for yak, a better optimized reference group structure, and more efficient statistical algorithms and tools.
Highlights
The polled yak is a newly cultivated breed that provides meat, milk, and other products to local people on the Qinghai-Tibet Plateau [1]
The 96,087 single nucleotide polymorphism (SNP) loci and 354 individuals remaining were used for GS
genomic best linear unbiased prediction (GBLUP), Bayes B, and Bayes Cπ were selected as methods to predict the genomic estimated breeding values (GEBV) of 12 target traits with processed data, including phenotype and genotype data
Summary
The polled yak is a newly cultivated breed that provides meat, milk, and other products to local people on the Qinghai-Tibet Plateau [1]. Compared with the common domesticated yak, they exhibit a hornless trait with better growth performance [2]. Due to the disappearance of horns, evolutionarily used for self-defense and in competition for a mate, the polled yak is suitable for large-scale production and resource management [3]. The majority of important economic traits of yaks are affected by multiple genes [4]. Conventional breeding depends mainly on an assessment of appearance, measurement of performance, pedigree, and assessment of phenotypes to estimate breeding values [5]. These methods have resulted in great progress in yak breeding in the past. Important economic traits are difficult to measure, which in any case are too costly, making improvements to livestock traits relatively slow [6]
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