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在使用全基因组序列数据的优先变异来揭示猪中与脂肪相关的特征的新型和密切相关的关联信号

E Molinero¹, R N Pena¹, J Estany¹

¹Department of Animal Science, University of Lleida, 191 Av. Alcalde Rovira Roure, 25198 Lleida, Spain; Agrotecnio-CERCA Center, 191 Av. Alcalde Rovira Roure, 25198 Lleida, Spain.

Animal : an international journal of animal bioscience

|April 18, 2025

概括

全基因组测序 (WGS) 数据有助于确定猪脂肪特征的新遗传关联. 研究人员发现了17个新的定量特征位置,改善了我们对复杂特征遗传学的理解.

科学领域:

动物遗传学和动物基因组学
定量特征位置 (QTL) 发现发现
畜牧业生产特征畜牧业生产特征

背景情况:

大多数生产特征的遗传变异仍然未被绘制.
全基因组测序 (WGS) 提供了比标记阵列更高的分辨率,用于发现新的关联和解决链接信号.
从WGS数据中识别复杂特征的因果变异是具有挑战性的,因为高维度和链接不平衡.

研究的目的:

评估WGS数据对揭示猪脂肪含量和成分特征中较弱遗传效应关联的有用性.
为了确定与Duroc猪种群的生产特征相关的新型遗传变异.
改进复杂特征的验证研究的变异优先级策略.

主要方法:

根据205个个人的WGS数据,从154个候选基因中优先考虑了182个变异,条件是LEPR和SCD基因.
对于这些优先变异,基因型为971头猪 (确认组).
使用全基因组显著性值 (q值<0.05) 测试优先变异和脂肪特征之间的关联.

主要成果:

确定了17个可能独立的定量特征位点 (8.4%的研究基因),与至少一个脂肪特征有显著关联.
发现了背部脂肪厚度 (ABCC2),酸含量 (MOGAT2) 和单不和脂肪酸含量 (PLPP1) 的新相关性.
揭示了较弱遗传效应的细粒度,一些基因位置可能会掩盖附近基因的效应 (例如,DGAT2,FADS2).

结论:

在发现较弱的遗传效应和精制复杂特征的关联信号方面,WGS数据非常有价值.
新的基因 (ABCC2,MOGAT2,PLPP1) 与猪的重要脂肪沉积和组成特征有关.
改善变异优先级的建议包括更大的发现集,增强的功能注释和整合多omics数据.

关键词:

脂肪酸是一种脂肪酸.精细地图的绘制.全基因组关联研究研究.链接不平衡链接不平衡定量性特征位置 (loci loci) 是一个定量性特征位置.

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