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多祖先全基因组关联元分析确定了猪中基于计算机断层扫描的尸体组成特征的候选基因

He Han^1,2, Pengfei Yu^1,2, Zhenyang Zhang^1,2

¹Zhejiang Key Laboratory of nutrition and breeding for high-quality animal products, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China.

Genetics, selection, evolution : GSE

|December 17, 2025

概括

这项研究使用计算机断层扫描和全基因组关联分析来发现影响猪尸体特征的遗传因素. 鉴定的基因提供了通过分子育种改善肉质的目标.

科学领域:

动物遗传学动物遗传学
基因组学就是基因组学.
定量特征位置 (QTL) 分析分析.

背景情况:

尸体的组成特征 (瘦肉,骨百分比,肋骨数) 对于养猪的利能力至关重要.
测量这些特征的传统方法具有侵入性和劳动密集性.
计算机断层扫描 (CT) 为广泛的数据收集提供了非侵入性的体内表型鉴定,但遗传基础尚未得到充分探索.

研究的目的:

为了确定与基于CT的猪尸体组成特征相关的遗传位置.
为了提高基因组预测准确性,这些特征使用识别的遗传变异.
为了精确确定影响尸体组成的候选基因.

主要方法:

多祖先全基因组关联元分析 (MA-GWAMA) 基于四种猪品种的低覆盖全基因组测序数据.
后分析确定了11个独立的全基因组显著位置.
将MA-GWAMA结果与公开的eQTL和单细胞数据集成.

主要成果:

确定了11个独立的全基因组显著位置与尸体组成特征相关.
权重MA-GWAMA显著SNP在独立人群中提高了多达79.4%的基因组预测准确性.
优先考虑的候选基因:瘦肉百分比的ALPK2,肋骨数量的ABCD4和SLC8A3.

结论:

CT表型与多组组合相结合,有效地剖析了猪尸体特征的遗传结构.
优先选择的变体和基因作为分子育种计划的有价值的目标.
这项研究推动了通过遗传选择提高猪肉质量的努力.

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