下一代测序技术和统计工具的应用,用于识别牲畜耐热度的途径和生物标志物
Gajendirane Kalaignazhal1,2, Veerasamy Sejian1, Silpa Mullakkalparambil Velayudhan1
1Rajiv Gandhi Institute of Veterinary Education and Research, Kurumbapet 605009, Puducherry, India.
Veterinary sciences
|December 27, 2024
概括
气候变化通过热应激影响畜牧业生产. 使用先进的技术识别耐热品种.
科学领域:
- 动物科学动物科学
- 遗传学 遗传学 是一个
- 适应气候变化 适应气候变化
背景情况:
- 气候变化导致异常天气模式,对农场动物生产率产生负面影响.
- 热应激是降低畜牧业绩效和造成经济损失的主要因素.
- 确定耐热的牲畜品种对于可持续农业至关重要.
研究的目的:
- 通过使用"omics"和统计方法,审查评估牲畜耐热性的进展.
- 突出了解耐热性背后的遗传因素的重要性.
- 探索生物技术工具在培育耐热牲畜方面的潜力.
主要方法:
- 利用下一代生物技术工具,如全转录组分析,全元基因组测序和双硫酸盐测序.
- 使用统计模型,包括全基因组关联研究 (GWAS) 和选择签名分析.
- 审查最近的"奥米克"方法和统计模型,用于评估牲畜的耐热性.
主要成果:
- 确定牲畜中耐热性潜在的遗传标记物.
- 发现与耐热性相关的候选生物标志物.
- "奥米克"方法为提高耐热性提供了养殖牲畜的机会.
结论:
- 先进的"omics"技术和统计模型是识别耐热牲畜的关键.
- 标记器辅助育种选择可以结合耐热性的遗传标记物.
- 这些方法可以彻底改变畜牧业生产,以满足气候变化下的全球粮食需求.
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