Relationships play a very important role in studies on quantitative genetics. In traditional breeding, pedigree records are used to establish relationships between animals; while this kind of relationship actually represents one kind of relatedness, it cannot distinguish individual specificity, capture the variation between individuals or determine the actual genetic superiority of an animal. However, with the popularization of high-throughput genotypes, assessments of relationships among animals based on genomic information could be a better option. In this study, we compared the relationships between animals based on pedigree and genomic information from two pig breeding herds with different genetic backgrounds and a simulated dataset. Two different methods were implemented to calculate genomic relationship coefficients and genomic kinship coefficients, respectively. Our results show that, for the same kind of relative, the average genomic relationship coefficients (G matrix) were very close to the pedigree relationship coefficients (A matrix), and on average, the corresponding values were halved in genomic kinship coefficients (K matrix). However, the genomic relationship yielded a larger variation than the pedigree relationship, and the latter was similar to that expected for one relative with no or little variation. Two genomic relationship coefficients were highly correlated, for farm1, farm2 and simulated data, and the correlations for the parent-offspring, full-sib and half-sib were 0.95, 0.90 and 0.85; 0.93, 0.96 and 0.89; and 0.52, 0.85 and 0.77, respectively. When the inbreeding coefficient was measured, the genomic information also yielded a higher inbreeding coefficient and a larger variation than that yielded by the pedigree information. For the two genetically divergent Large White populations, the pedigree relationship coefficients between the individuals were 0, and 62 310 and 175 271 animal pairs in the G matrix and K matrix were greater than 0. Our results demonstrated that genomic information outperformed the pedigree information; it can more accurately reflect the relationships and capture the variation that is not detected by pedigree. This information is very helpful in the estimation of genomic breeding values or gene mapping. In addition, genomic information is useful for pedigree correction. Further, our findings also indicate that genomic information can establish the genetic connection between different groups with different genetic background. In addition, it can be used to provide a more accurate measurement of the inbreeding of an animal, which is very important for the assessment of a population structure and breeding plan. However, the approaches for measuring genomic relationships need further investigation.

中文翻译：

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根据谱系和基因组信息评估猪之间的关系。

在定量遗传学研究中，关系扮演着非常重要的角色。在传统的育种中，系谱记录用于建立动物之间的关系。这种关系实际上代表一种关联性，但不能区分个体特异性，捕捉个体之间的变异或确定动物的实际遗传优势。但是，随着高通量基因型的普及，基于基因组信息评估动物之间的关系可能是一个更好的选择。在这项研究中，我们根据血统和来自两个具有不同遗传背景的猪群的基因组信息和模拟数据集比较了动物之间的关系。实施了两种不同的方法来分别计算基因组关系系数和基因组亲属系数。我们的结果表明，对于同一种亲属，平均基因组关系系数（G矩阵）与血统关系系数（A矩阵）非常接近，平均而言，相应的值在基因组亲属系数（K矩阵）中减半）。但是，基因组关系产生的变异比谱系关系大，后者与一个亲戚的预期相似，无或几乎没有变异。农场1，农场2和模拟数据的两个基因组关系系数高度相关，父母-后代，全同胞和半同胞的相关系数分别为0.95、0.90和0.85。0.93、0.96和0.89；和0.52、0.85和0.77。当测量近交系数时，与系谱信息相比，基因组信息还产生了更高的近交系数和更大的变异。对于两个遗传上不同的大白种种群，个体之间的谱系关系系数为0，G矩阵和K矩阵中的62 310和175 271动物对大于0。我们的结果表明，基因组信息优于谱系信息。它可以更准确地反映出这种关系并捕获家谱未发现的变异。该信息对于估计基因组育种值或基因作图非常有帮助。此外，基因组信息对于谱系校正很有用。进一步，我们的发现还表明，基因组信息可以在具有不同遗传背景的不同群体之间建立遗传联系。另外，它可以用来提供对动物近交的更准确的测量，这对于评估种群结构和繁殖计划非常重要。但是，测量基因组关系的方法需要进一步研究。