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美国荷斯坦小母牛饲料效率的基因组评估。

Genomic evaluation of feed efficiency in US Holstein heifers.

机构信息

STgenetics, Navasota, TX 77868.

STgenetics, Navasota, TX 77868.

出版信息

J Dairy Sci. 2023 Oct;106(10):6986-6994. doi: 10.3168/jds.2023-23258. Epub 2023 May 18.

Abstract

There is growing interest in improving feed efficiency traits in dairy cattle. The objectives of this study were to estimate the genetic parameters of residual feed intake (RFI) and its component traits [dry matter intake (DMI), metabolic body weight (MBW), and average daily gain (ADG)] in Holstein heifers, and to develop a system for genomic evaluation for RFI in Holstein dairy calves. The RFI data were collected from 6,563 growing Holstein heifers (initial body weight = 261 ± 52 kg; initial age = 266 ± 42 d) for 70 d, across 182 trials conducted between 2014 and 2022 at the STgenetics Ohio Heifer Center (South Charleston, OH) as part of the EcoFeed program, which aims to improve feed efficiency by genetic selection. The RFI was estimated as the difference between a heifer's actual feed intake and expected feed intake, which was determined by regression of DMI against midpoint MBW, age, and ADG across each trial. A total of 61,283 SNPs were used in genomic analyses. Animals with phenotypes and genotypes were used as training population, and 4 groups of prediction population, each with 2,000 animals, were selected from a pool of Holstein animals with genotypes, based on their relationship with the training population. All traits were analyzed using univariate animal model in DMU version 6 software. Pedigree information and genomic information were used to specify genetic relationships to estimate the variance components and genomic estimated breeding values (GEBV), respectively. Breeding values of the prediction population were estimated by using the 2-step approach: deriving the prediction equation of GEBV from the training population for estimation of GEBV of prediction population with only genotypes. Reliability of breeding values was obtained by approximation based on partitioning a function of the accuracy of training population GEBV and magnitudes of genomic relationships between individuals in the training and prediction population. Heifers had DMI (mean ± SD) of 8.11 ± 1.59 kg over the trial period, with growth rate of 1.08 ± 0.25 kg/d. The heritability estimates (mean ± SE) of RFI, MBW, DMI, and growth rate were 0.24 ± 0.02, 0.23 ± 0.02, 0.27 ± 0.02, and 0.19 ± 0.02, respectively. The range of genomic predicted transmitted abilities (gPTA) of the training population (-0.94 to 0.75) was higher compared with the range of gPTA (-0.82 to 0.73) of different groups of prediction population. Average reliability of breeding values from the training population was 58%, and that of prediction population was 39%. The genomic prediction of RFI provides new tools to select for feed efficiency of heifers. Future research should be directed to find the relationship between RFI of heifers and cows, to select individuals based on their lifetime production efficiencies.

摘要

人们对提高奶牛的饲料效率性状越来越感兴趣。本研究的目的是估计荷斯坦小母牛的剩余采食量(RFI)及其组成性状[干物质采食量(DMI)、代谢体重(MBW)和平均日增重(ADG)]的遗传参数,并开发一种用于荷斯坦奶牛小母牛 RFI 基因组评估的系统。RFI 数据来自 6563 头生长中的荷斯坦小母牛(初始体重=261±52kg;初始年龄=266±42d),在 2014 年至 2022 年间的 182 项试验中进行了 70 天的试验,这些试验在俄亥俄州 STgenetics 荷斯坦小母牛中心(南查尔斯顿,OH)进行,是生态饲料计划的一部分,该计划旨在通过遗传选择提高饲料效率。RFI 是通过回归小母牛的 DMI 与试验期间的中点 MBW、年龄和 ADG 来确定的,RFI 是通过回归小母牛的 DMI 与试验期间的中点 MBW、年龄和 ADG 来确定的。共使用了 61283 个 SNP 进行基因组分析。具有表型和基因型的动物被用作训练群体,根据与训练群体的关系,从具有基因型的荷斯坦动物群体中选择了 4 组预测群体,每组 2000 头。所有性状均采用 DMU 版本 6 软件中的单变量动物模型进行分析。系谱信息和基因组信息用于指定遗传关系,以分别估计方差分量和基因组估计育种值(GEBV)。使用两步法估计预测群体的育种值:从训练群体中推导出 GEBV 的预测方程,以仅使用基因型估计预测群体的 GEBV。通过基于训练群体 GEBV 的准确性和训练群体与预测群体个体之间基因组关系的大小的函数来近似获得育种值的可靠性。小母牛在试验期间的 DMI(平均值±SD)为 8.11±1.59kg,生长速度为 1.08±0.25kg/d。RFI、MBW、DMI 和生长速度的遗传力估计值(平均值±SE)分别为 0.24±0.02、0.23±0.02、0.27±0.02 和 0.19±0.02。训练群体的基因组预测传递能力(gPTA)范围(-0.94 至 0.75)高于不同预测群体的 gPTA 范围(-0.82 至 0.73)。来自训练群体的平均育种值可靠性为 58%,预测群体的可靠性为 39%。RFI 的基因组预测为小母牛的饲料效率选择提供了新的工具。未来的研究应致力于寻找小母牛和奶牛之间的 RFI 关系,以便根据个体的终生生产效率进行选择。

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