Gmel Annik Imogen, Burren Alexander, Neuditschko Markus
Animal GenoPhenomics, Agroscope, Rte de la Tioleyre 4, 1725 Posieux, Switzerland.
Equine Department, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, 8057 Zurich, Switzerland.
Animals (Basel). 2022 Aug 25;12(17):2186. doi: 10.3390/ani12172186.
Conformation traits such as joint angles are important selection criteria in equine breeding, but mainly consist of subjective evaluation scores given by breeding judges, showing limited variation. The horse shape space model extracts shape data from 246 landmarks (LM) and objective joint angle measurements from triplets of LM on standardized horse photographs. The heritability was estimated for 10 joint angles (seven were measured twice with different LM placements), and relative warp components of the whole shape, in 608 Franches-Montagnes (FM) horses (480 stallions, 68 mares and 60 geldings born 1940-2018, 3-25 years old). The pedigree data comprised 6986 horses. Genetic variances and covariances were estimated by restricted maximum likelihood model (REML), including the fixed effects birth year, age (linear and quadratic), height at withers (linear and quadratic), as well as postural effects (head, neck, limb position and body alignment), together with a random additive genetic animal component and the residual effect. Estimated heritability varied from 0.08 (stifle joint) to 0.37 (poll). For the shape, the type was most heritable (0.36 to 0.37) and evolved from heavy to light over time. Image-based phenotyping can improve the selection of horses for conformation traits with moderate heritability (e.g., poll, shoulder and fetlock).
诸如关节角度等体型特征是马匹育种中的重要选择标准,但主要由育种评判员给出的主观评估分数组成,变异有限。马形状空间模型从246个地标(LM)中提取形状数据,并从标准化马照片上的LM三元组中获取客观的关节角度测量值。对608匹汝拉山区马(FM)(480匹种马、68匹母马和60匹阉马,出生于1940年至2018年,年龄在3至25岁之间)的10个关节角度(其中7个用不同的LM放置方式测量了两次)以及整个形状的相对扭曲成分进行了遗传力估计。系谱数据包括6986匹马。通过限制最大似然模型(REML)估计遗传方差和协方差,包括固定效应出生年份、年龄(线性和二次)、肩高(线性和二次)以及姿势效应(头部、颈部、肢体位置和身体对齐),以及随机加性遗传动物成分和残差效应。估计的遗传力从0.08(膝关节)到0.37(头顶)不等。对于形状,体型类型的遗传力最高(0.36至0.37),并且随着时间的推移从重型向轻型演变。基于图像的表型分析可以改善对具有中等遗传力的体型特征(如头顶、肩部和球节)的马匹选择。