拼接变体在牛群复杂特征的形成中的功能影响
Mathieu Charles1,2, Nicolas Gaiani1, Marie-Pierre Sanchez1
1Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Nature communications
|April 24, 2025
概括
研究人员确定了38种与复杂的牛特征相关的拼接破坏变异,其中3种被证实是因果关系的. 这一进步提高了对畜牧业绩效遗传影响的理解,并有助于基因组预测的准确性.
科学领域:
- 基因组学和生物信息学
- 动物育种与遗传学
背景情况:
- 全基因组关联研究 (GWAS) 识别了牛农学特征的遗传变异,但经常发现与因果变异相关的标记物,限制了基因组预测的准确性.
- 了解遗传变异如何影响基因表达,特别是通过RNA剪接,对于识别实际因果变异及其功能至关重要.
研究的目的:
- 用高通量策略在牛基因组中功能性分析拼接破坏变异.
- 通过将GWAS与RNA拼接分析相结合,识别影响牛群复杂特征的因果变异.
- 评估人类衍生的拼接预测因子对牛基因组的适用性.
主要方法:
- 在归算的全基因组序列数据上利用全基因组关联研究 (GWAS).
- 采用高通量策略,涉及大规模并行报告测试 (MPRA) 以功能测试变体.
- 应用深度学习算法用于预测牛基因组中的拼接破坏变异.
主要成果:
- 确定了38种与牛复杂特征相关的拼接破坏变异.
- 将这些变异中的三种分类为潜在的因果关系,为特征确定提供了直接的见解.
- 证实了与牛表型相关的定量特征位点 (QTL) 内的连接破坏变异普遍存在.
- 验证了在牛环境中为人类开发的拼接预测器的有效性.
结论:
- 将RNA拼接分析与GWAS整合在一起,有效地识别了牛的因果变异.
- 在牛中复杂特征的遗传结构中,Splice破坏型变体发挥着重要作用.
- 开发的方法通过确定功能变异来提高准确基因组预测的潜力.
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