Background A significant proportion of perinatal losses in pigs occurs due to congenital malformations. The purpose of this study is the identification of genomic loci associated with fetal malformations in piglets. Methods The malformations were divided into two groups: associated with limb defects (piglet splay leg) and associated with other congenital anomalies found in newborn piglets. 148 Landrace and 170 Large White piglets were selected for the study. A genome-wide association study based on the gradient boosting machine algorithm was performed to identify markers associated with congenital anomalies and piglet splay leg. Results Forty-nine SNPs (23 SNPs in Landrace pigs and 26 SNPs in Large White) were associated with congenital anomalies, 22 of which were localized in genes. A total of 156 SNPs (28 SNPs in Landrace; 128 in Large White) were identified for piglet splay leg, of which 79 SNPs were localized in genes. We have demonstrated that the gradient boosting machine algorithm can identify SNPs and their combinations associated with significant selection indicators of studied malformations and productive characteristics. Data availability Genotyping and phenotyping data are available at http://www.compubioverne.group/data-and-software/.

中文翻译：

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检测新生仔猪基因组区域相关畸形：一种机器学习方法

背景 猪围产期损失的很大一部分是由于先天性畸形造成的。本研究的目的是鉴定与仔猪胎儿畸形相关的基因组位点。方法将畸形分为两组：与肢体缺陷相关（仔猪张开腿）和与新生仔猪其他先天性异常相关。选择了 148 头长白猪和 170 头大白猪进行研究。进行了基于梯度增强机算法的全基因组关联研究，以识别与先天性异常和仔猪张开腿相关的标记。结果 49 个 SNP（长白猪 23 个 SNP，大白猪 26 个 SNP）与先天性异常相关，其中 22 个位于基因中。共有 156 个 SNP（长白中 28 个 SNP；128 个大白）被鉴定为小猪张开腿，其中 79 个 SNP 定位于基因中。我们已经证明，梯度增强机算法可以识别与研究畸形和生产特征的重要选择指标相关的 SNP 及其组合。数据可用性基因分型和表型数据可在 http://www.compubioverne.group/data-and-software/ 获得。