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开发小农杂交品种奶牛场遗传评估的灵活模型

R Costilla¹, J Zeng², M Al Kalaldeh³

¹AgResearch Limited, Ruakura Research Centre, Hamilton 3214, New Zealand; Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD 4067, Australia.

Journal of dairy science

|September 7, 2023

概括

基因组选择可以提高发展中国家的奶牛生产率. 一个新的灵活的贝叶斯模型 (BayesR) 有效地评估了小农场的牛奶产量,即使有有限的血统数据和小群规模.

科学领域:

动物遗传学动物遗传学
量化遗传学量化遗传学
乳制品科学乳制品科学

背景情况:

发展中国家的小农奶牛农场的生产率较低.
基因组选择提供了潜在的遗传收益,但需要针对有限的血统和小型农场规模进行量身定制的评估.

研究的目的:

提出和验证一个灵活的贝叶斯模型 (BayesR) 用于基因评估小农奶牛场的牛奶产量.
评估模型处理非遗传随机效应和变化的SNP变异的能力.

主要方法:

模拟使用印度杂交的乳牛基因型数据.
贝叶斯R模型应用于来自4,655头杂交母牛的真实数据,其中有106,109个牛奶记录和689,750个SNP.
基因组估计育种值 (GEBV) 的准确性和偏差估计的交叉验证.

主要成果:

贝叶斯R模型有效地分离了小群的遗传和非遗传参数.
随着农场规模增加到大约5头奶牛,GEBV的准确性增加了.
牛奶产量的估计遗传率为0.16,GEBV精度为0.45,偏差为1.04.
候选基因IMMP2L和ARHGEF2在顶级遗传变异附近被确定.

结论:

建议的贝叶斯模型适用于小农奶制品系统中的遗传评估.
低遗传性和GEBV准确性强调了需要更大的表型和基因型种群的需要.
增加群体大小 (3-5头牛) 可以改善这些系统中的遗传效应估计.

关键词:

贝耶斯R BayesR 在这里.在GWAS中,GWAS就是GWAS.在 QTL 时段,你会得到 QTL.发展中国家发展中国家发展中国家牛奶产量牛奶产量

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