Abstract Santa Ines is a locally adapted hair sheep breed that is under large expansion in Brazil and other Tropical countries. This study aimed to evaluate the effect of different relationship matrices (A or H) on the estimation of genetic parameters and accuracy of (genomic) breeding values [(G)EBVs] for carcass traits measured in vivo in Santa Ines sheep. A total of 977, 890, 894, and 882 records for loin eye area (LEA), marbling score (MLE), subcutaneous fat thickness (SFT), and leg circumference (LEC), respectively, were included in this study. There were 1637 animals in the numerator relationship matrix (A). A total of 389 animals with phenotypic information were genotyped using the OvineSNP50 BeadChip. After the genotyping quality control, 388 samples and 42,748 SNPs remained in the dataset. The (co)variance components were estimated via Bayesian inference through single- and multi-trait analyses using the animal model with either the A or H matrix. The theoretical accuracies of (G)EBVs, Pearson correlation between breeding values estimated including or not genomic information, and Spearman rank correlation were used to evaluate the feasibility of incorporating genomic information in the analyses. Heritability estimates ranged from 0.12 ± 0.06 (SFT, using the A matrix) to 0.29 ± 0.07 (LEA, using the H matrix), in the single-trait analyses, and from 0.17 ± 0.05 (SFT, using A) to 0.33 ± 0.07 (LEA, using H), in a multi-trait setting. Direct genetic additive variance and heritability estimates were higher when including genomic information. Unfavorable and high genetic correlation was observed between LEA and SFT. The estimates of theoretical accuracy of (G)EBVs were higher in all the scenarios when genomic information was incorporated in the model. Gains in accuracy ranged from 0.013 to 0.039 units when genomic information was included in the analyses. Thus, if available, genomic information should be incorporated in the estimation of genetic parameters and breeding values for carcass traits measured in vivo in Santa Ines sheep.

中文翻译：

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热带气候适应性绵羊胴体性状（包括基因组信息）的遗传评估

摘要 Santa Ines 是一种适应当地的毛羊品种，在巴西和其他热带国家正在大规模扩张。本研究旨在评估不同关系矩阵（A 或 H）对 Santa Ines 绵羊体内测量的胴体性状的遗传参数估计和（基因组）育种值 [(G)EBV] 准确性的影响。本研究分别包括腰眼面积 (LEA)、大理石花纹评分 (MLE)、皮下脂肪厚度 (SFT) 和腿围 (LEC) 的 977、890、894 和 882 条记录。分子关系矩阵 (A) 中有 1637 只动物。使用 OvineSNP50 BeadChip 对总共 389 只具有表型信息的动物进行了基因分型。在基因分型质量控制之后，数据集中保留了 388 个样本和 42,748 个 SNP。使用具有 A 或 H 矩阵的动物模型，通过贝叶斯推理通过单性状和多性状分析估计（协）方差分量。(G)EBV 的理论准确性、估计的育种值之间的 Pearson 相关性（包括或不包括基因组信息）和 Spearman 等级相关性被用来评估在分析中纳入基因组信息的可行性。遗传力估计范围从 0.12 ± 0.06（SFT，使用 A 矩阵）到 0.29 ± 0.07（LEA，使用 H 矩阵），在单性状分析中，从 0.17 ± 0.05（SFT，使用 A）到 0.33 ± 0.07 （LEA，使用 H），在多特征设置中。当包括基因组信息时，直接遗传加性方差和遗传力估计值更高。在 LEA 和 SFT 之间观察到不利的和高度的遗传相关性。当基因组信息被纳入模型时，(G)EBV 的理论准确性的估计在所有场景中都更高。当分析中包含基因组信息时，准确性的增益范围为 0.013 到 0.039 个单位。因此，如果可用，基因组信息应纳入在 Santa Ines 绵羊体内测量的胴体性状的遗传参数和育种值的估计中。