Principal component analysis (PCA) was applied to evaluate the genetic variability and relationship between 15 morphometric traits in 91,483 Campolina horses, as well as to propose an index based on an aggregate genotype that promotes a particular selection objective. PCA was applied to the genetic (co)variance matrix among variables. After calculation of the principal components, the breeding values were estimated to obtain an index related to the component that explained most of the variation. The first principal component (PC1) accounted for 97.8% of the total additive genetic variance of the traits. PC1 contrasted animals in terms of body size (wither, back and croup heights, body length, and thoracic girth). PC1 traits showed higher heritabilities and positive and high genetic correlations. An index was obtained (HPC1) with the combination of the breeding values of different traits from PC1 which permitted the use of this index as an aggregate genotype to identify the best animals for selection. The second principal component (PC2) was much smaller and grouped traits related to head and neck morphometry, among others. These traits are commonly used for breed qualification, a fact explaining the small variation in this component. An evaluation of the effect of HPC1 on withers height in two-trait analysis was also made which provided positive genetic correlations of moderate to high magnitude (0.73-0.86), indicating that selection for this trait (important in Campolina horses) is accounted for in the index. The use of HCP1 could be considered as an important alternative to selection since it does not consider a single trait but rather a set of variables that capture body proportions.

中文翻译：

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Campolina 马形态特征的主成分

应用主成分分析 (PCA) 来评估 91,483 匹 Campolina 马的 15 个形态特征之间的遗传变异性和关系，并提出基于促进特定选择目标的聚合基因型的指数。PCA 应用于变量之间的遗传（共）方差矩阵。在计算主成分后，估计育种值以获得与解释大部分变异的成分相关的指数。第一主成分（PC1）占性状总加性遗传方差的97.8%。PC1 在体型（马肩隆、背部和臀部高度、体长和胸围）方面对比了动物。PC1 性状显示出更高的遗传力和正高的遗传相关性。获得了一个指数 (HPC1)，结合了来自 PC1 的不同性状的育种值，允许使用该指数作为聚合基因型来识别最佳动物进行选择。第二个主成分 (PC2) 小得多，并且与头颈部形态测量相关的分组特征等。这些性状通常用于品种鉴定，这一事实解释了这一组成部分的微小变化。还对 HPC1 在双性状分析中对马肩隆高度的影响进行了评估，该评估提供了中到高量级 (0​​.73-0.86) 的正遗传相关性，表明对这种性状的选择（在 Campolina 马中很重要）在指数。