验证荷斯坦奶牛泌乳早期氮效率指数及其组成性状的基因组预测。

IF 1.9 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Y. Chen, H. Atashi, R. R. Mota, C. Grelet, S. Vanderick, H. Hu, GplusE Consortium, N. Gengler
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引用次数: 0

摘要

氮利用效率是奶牛的重要经济性状。最近,我们提出了一个新的氮效率指数(NEI),它同时考虑了NUE和氮污染。本研究旨在验证NEI及其组成性状的基因组预测,并研究直接从NEI估计的SNP效应与其组成性状间接估计的SNPs效应之间的关系。NEI组成包括N摄入量(NINT)、牛奶真蛋白N(MTPN)和牛奶尿素N产量的基因组估计育种值。编辑后的数据为132899份记录,涉及分布在773个牛群中的52064头奶牛。该谱系包含122368只动物。4514个个体可获得566294个SNP的基因型数据。共选择4413头奶牛(包括181只基因型)和56头公牛(包括32只基因型型)作为验证群体。采用线性回归方法,采用最佳线性无偏预测(BLUP)和单步基因组BLUP(ssGBLUP)对NEI及其组成性状的基因组预测进行了验证。从ssGBLUP获得的验证群体的NEI及其组成性状的平均理论准确度高于从BLUP获得的,范围为0.57(MTPN)至0.72(NINT)。在ssGBLUP下估计的基因型奶牛的NEI及其组成性状的平均预测准确率最高,范围为0.48(MTPN)至0.66(NINT)。此外,从NEI组成性状中估计的SNP效应乘以相对重量与直接从NEI中估计的相同。这项研究初步表明,基因组预测可以用于NEI,然而,我们承认需要在更大的数据集中进一步验证这一结果。此外,NEI的SNP效应可以使用从其组成特征估计的SNP效果来间接计算。这项研究为添加基因组信息以建立NEI作为未来常规基因组评估计划的一部分提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validating genomic prediction for nitrogen efficiency index and its composition traits of Holstein cows in early lactation

Nitrogen (N) use efficiency (NUE) is an economically important trait for dairy cows. Recently, we proposed a new N efficiency index (NEI), that simultaneously considers both NUE and N pollution. This study aimed to validate the genomic prediction for NEI and its composition traits and investigate the relationship between SNP effects estimated directly from NEI and indirectly from its composition traits. The NEI composition included genomic estimated breeding value of N intake (NINT), milk true protein N (MTPN) and milk urea N yield. The edited data were 132,899 records on 52,064 cows distributed in 773 herds. The pedigree contained 122,368 animals. Genotypic data of 566,294 SNP was available for 4514 individuals. A total of 4413 cows (including 181 genotyped) and 56 bulls (including 32 genotyped) were selected as the validation populations. The linear regression method was used to validate the genomic prediction of NEI and its composition traits using best linear unbiased prediction (BLUP) and single-step genomic BLUP (ssGBLUP). The mean theoretical accuracies of validation populations obtained from ssGBLUP were higher than those obtained from BLUP for both NEI and its composition traits, ranging from 0.57 (MTPN) to 0.72 (NINT). The highest mean prediction accuracies for NEI and its composition traits were observed for the genotyped cows estimated under ssGBLUP, ranging from 0.48 (MTPN) to 0.66 (NINT). Furthermore, the SNP effects estimated from NEI composition traits, multiplied by the relative weight were the same as those estimated directly from NEI. This study preliminary showed that genomic prediction can be used for NEI, however, we acknowledge the need for further validation of this result in a larger dataset. Moreover, the SNP effects of NEI can be indirectly calculated using the SNP effects estimated from its composition traits. This study provided a basis for adding genomic information to establish NEI as part of future routine genomic evaluation programs.

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来源期刊
Journal of Animal Breeding and Genetics
Journal of Animal Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
5.20
自引率
3.80%
发文量
58
审稿时长
12-24 weeks
期刊介绍: The Journal of Animal Breeding and Genetics publishes original articles by international scientists on genomic selection, and any other topic related to breeding programmes, selection, quantitative genetic, genomics, diversity and evolution of domestic animals. Researchers, teachers, and the animal breeding industry will find the reports of interest. Book reviews appear in many issues.
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