Combined genomic evaluation of Merino and Dohne Merino Australian sheep populations

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2024-09-30 DOI:10.1186/s12711-024-00934-2
Marine Wicki, Daniel J. Brown, Phillip M. Gurman, Jérôme Raoul, Andrés Legarra, Andrew A. Swan
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Abstract

The Dohne Merino sheep was introduced to Australia from South Africa in the 1990s. It was primarily used in crosses with the Merino breed sheep to improve on attributes such as reproduction and carcass composition. Since then, this breed has continued to expand in Australia but the number of genotyped and phenotyped purebred individuals remains low, calling into question the accuracy of genomic selection. The Australian Merino, on the other hand, has a substantial reference population in a separate genomic evaluation (MERINOSELECT). Combining these resources could fast track the impact of genomic selection on the smaller breed, but the efficacy of this needs to be investigated. This study was based on a dataset of 53,663 genotypes and more than 2 million phenotypes. Its main objectives were (1) to characterize the genetic structure of Merino and Dohne Merino breeds, (2) to investigate the utility of combining their evaluations in terms of quality of predictions, and (3) to compare several methods of genetic grouping. We used the ‘LR-method’ (Linear Regression) for these assessments. We found very low Fst values (below 0.048) between the different Merino lines and Dohne breed considered in our study, indicating very low genetic differentiation. Principal component analysis revealed three distinct groups, identified as purebred Merino, purebred Dohne, and crossbred animals. Considering the whole population in the reference led to the best quality of predictions and the largest increase in accuracy (from ‘LR-method’) from pedigree to genomic-based evaluations: 0.18, 0.14 and 0.16 for yearling fibre diameter (YFD), yearling greasy fleece weight (YGFW) and yearling liveweight (YWT), respectively. Combined genomic evaluations showed higher accuracies than the evaluation based on the Dohne reference only (accuracies increased by 0.16, 0.06 and 0.07 for YFD, YGFW, and YWT, respectively). For the combined genomic evaluations, metafounder models were more accurate than Unknown Parent Groups models (accuracies increased by 0.04, 0.04 and 0.06 for YFD, YGFW and YWT, respectively). We found promising results for the future transition of the Dohne breed from pedigree to genomic selection. A combined genomic evaluation, with the MERINOSELECT evaluation in addition to using metafounders, is expected to enhance the quality of genomic predictions for the Dohne Merino breed.
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美利奴羊和多恩美利奴羊澳大利亚种群的联合基因组评估
多恩美利奴羊于 20 世纪 90 年代从南非引入澳大利亚。它主要用于与美利奴羊杂交,以改善繁殖和胴体成分等特性。从那时起,该品种在澳大利亚不断扩大,但基因分型和表型纯种个体的数量仍然很少,这使基因组选择的准确性受到质疑。另一方面,澳大利亚美利奴在单独的基因组评估(MERINOSELECT)中拥有大量的参考群体。将这些资源结合起来,可以快速追踪基因组选择对小型品种的影响,但其有效性还有待研究。这项研究基于 53663 个基因型和 200 多万个表型的数据集。研究的主要目的是:(1)描述美利奴和多恩美利奴品种的遗传结构特征;(2)从预测质量的角度研究综合评估的效用;(3)比较几种遗传分组方法。我们使用 "LR 法"(线性回归)进行这些评估。我们在研究中发现,不同美利奴品系和多恩品种之间的 Fst 值非常低(低于 0.048),表明遗传分化程度非常低。主成分分析显示出三个不同的群体,即纯种美利奴、纯种多恩和杂交动物。从基于血统的评估到基于基因组的评估,将整个种群作为参照物可获得最佳的预测质量和最大的准确性提高(从 "LR-方法"):一岁犊牛纤维直径(YFD)、一岁犊牛绒毛重量(YGFW)和一岁犊牛活重(YWT)的准确度分别为 0.18、0.14 和 0.16。综合基因组评价的准确度高于仅基于多恩参考的评价(YFD、YGFW 和 YWT 的准确度分别提高了 0.16、0.06 和 0.07)。在综合基因组评估中,元创始人模型比未知亲本组模型更准确(YFD、YGFW 和 YWT 的准确率分别提高了 0.04、0.04 和 0.06)。我们发现,未来多恩品种从血统选育过渡到基因组选育的结果很有希望。除了使用元创始者之外,结合 MERINOSELECT 评估进行基因组评估有望提高多恩美利奴品种的基因组预测质量。
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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