Preliminary study regarding use of genomic selection in Romanian cattle breeds evaluation

Mihail Alexandru Gras, Cătălin Mircea Rotar, Horia Grosu, Rodica Ștefania Pelmuș, Cristina Lazăr
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Abstract

Abstract In Romania, the livestock is very scattered on the diverse environmental conditions. Due to difficulties regarding data collection, with the help of genomic selection, the paradigm of genetic improvement of economical traits in Romanian cattle breeds can be changed. Population studied in this paper consist in animals genotyped using 60k SNP panel. Association studies were performed for estimate the effect of SNP polymorphism on milk yield at 305 days. Genetic evaluation was compared under four statistical methodologies were compared under six scenarios 5k, 10k, 15k, 20k, 25k and 37k SNP panels. High association with phenotypes were displayed by 38 SNP’s. Generally, accuracy of the studied models, tend to increase with complexity (informational input). The model with the lowest accuracy was Sire-Model (36.6% accuracy). Adding information in Animal Model increase accuracy of estimation and finally, adding genomic information the accuracy was maximized to 69.9%. For each lactation all the statistical models return highly correlated breeding values. The highest (97.2%) and the lowest (79.2%) rank correlation are registered between Test-Day and Animal Model for the first and second lactation. Genomic evaluation is a more feasible methodology than classical breeding value estimation, in term of accuracy of selection and the quality of the parentage information.
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基因组选择在罗马尼亚牛品种评价中的应用初步研究
在罗马尼亚,家畜分布非常分散,环境条件各异。由于数据收集方面的困难,在基因组选择的帮助下,罗马尼亚牛品种经济性状的遗传改良范式可以改变。本文研究的群体包括使用60k SNP面板进行基因分型的动物。通过关联研究估计SNP多态性对305天产奶量的影响。在4种统计方法下进行遗传评价比较,并在5k、10k、15k、20k、25k和37k SNP面板6种情况下进行比较。38个SNP显示与表型高度相关。一般来说,所研究模型的准确性往往随着复杂性(信息输入)的增加而增加。准确率最低的模型为sir - model,准确率为36.6%。在动物模型中加入信息提高了估计的准确性,最后加入基因组信息使估计的准确性达到最大,达到69.9%。对于每次哺乳,所有统计模型都返回高度相关的繁殖值。第一次和第二次泌乳试验日与动物模型之间的等级相关性最高(97.2%)和最低(79.2%)。在选择的准确性和亲本信息的质量方面,基因组评估是一种比传统育种价值评估更可行的方法。
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