基于母猪生育状况的循环小非编码RNA转录组的分歧
Lauren Fletcher1, Xiaoshu Zhan2, Riddhi Chabrotra1
1Department of Animal Biosciences, University of Guelph, Ontario N1G 2W1, Canada.
Animal reproduction science
|July 11, 2025
概括
研究人员在猪中确定了小型非编码RNA (sncRNA) 生物标记物,以改善对生殖潜力的选择. 这些生物标志物准确地分类了高与不育母猪,有助于猪肉生产的遗传改进.
科学领域:
- 动物科学动物科学
- 遗传学 是一个遗传学.
- 生物技术是生物技术.
背景情况:
- 猪肉行业生产率的生殖性能至关重要.
- 生殖特征的遗传选择受到低遗传性和不利的遗传关联的阻碍.
- 小型非编码RNAs (sncRNAs) 显示出作为生物标记物的潜力,以增强雌猪生殖潜力的选择.
研究的目的:
- 为了比较不孕 (INF) 和高生殖潜力 (HRP) 的母猪之间的循环血清sncRNA概况.
- 确定与母猪生殖潜力相关的候选microRNA (miRNA) 生物标志物.
- 用miRNA生物标志物评估机器学习模型对分类母猪生殖潜力的有效性.
主要方法:
- 从INF (n=30) 和HRP (n=50) 雌性猪的血清样本上进行了小RNA测序.
- 差异表达分析在两组之间确定了显著的sncRNA和miRNA.
- 一个支持向量机 (SVM) 模型被训练使用选定的候选miRNA生物标记物进行分类.
主要成果:
- 确定了19种显著差异表达的sncRNA和13种差异表达的miRNA.
- 已知几个DEmiRNA在女性生殖和不孕症中的作用.
- SVM模型在分类生殖潜力方面取得了高准确性 (91%),对HRP具有高灵敏度 (96%),对INF具有高特异性 (83%).
结论:
- 候选miRNA生物标记物,包括miR-140-3p,miR-215-5p和miR-7142-3p,有望提高选择效率.
- 开发的SVM模型显示了在农场繁殖群的选择中实际应用的潜力.
- 需要在更大的队列中进一步验证,以确认可通用性和实际实用性.
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