Chen Y, Atashi H, Mota R R, Grelet C, Vanderick S, Hu H, Gengler N
TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), Gembloux, Belgium.
Department of Animal Science, Shiraz University, Shiraz, Iran.
J Anim Breed Genet. 2023 Nov;140(6):695-706. doi: 10.1111/jbg.12819. Epub 2023 Aug 12.
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.
氮(N)利用效率(NUE)是奶牛的一个具有经济重要性的性状。最近,我们提出了一种新的氮效率指数(NEI),它同时考虑了NUE和氮污染。本研究旨在验证NEI及其构成性状的基因组预测,并研究直接从NEI估计的SNP效应与间接从其构成性状估计的SNP效应之间的关系。NEI的构成包括氮摄入量(NINT)、乳真蛋白氮(MTPN)和乳尿素氮产量的基因组估计育种值。编辑后的数据是分布在773个牛群中的52,064头奶牛的132,899条记录。系谱包含122,368个个体。4514个个体有566,294个SNP的基因型数据。总共4413头奶牛(包括181头有基因型的)和56头公牛(包括32头有基因型的)被选为验证群体。使用线性回归方法,利用最佳线性无偏预测(BLUP)和单步基因组BLUP(ssGBLUP)来验证NEI及其构成性状的基因组预测。对于NEI及其构成性状,从ssGBLUP获得的验证群体的平均理论准确性高于从BLUP获得的,范围从0.57(MTPN)到0.72(NINT)。在ssGBLUP下估计的有基因型的奶牛中,观察到NEI及其构成性状的最高平均预测准确性,范围从0.48(MTPN)到0.66(NINT)。此外,从NEI构成性状估计的SNP效应乘以相对权重与直接从NEI估计的相同。本研究初步表明基因组预测可用于NEI,然而,我们承认需要在更大的数据集中对该结果进行进一步验证。此外,NEI的SNP效应可以使用从其构成性状估计的SNP效应间接计算。本研究为在未来的常规基因组评估计划中添加基因组信息以建立NEI提供了基础。