核心SNP:在作物中从全基因组SNP数据集中进行核心标志物概况选择的高效管道
Tingyu Dou1, Chunchao Wang1, Yanling Ma1
1Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
BMC plant biology
|November 21, 2023
概括
核心SNP管道有效地从大型作物数据集中选择最小单核酸多态 (SNP) 标记集. 这有助于区分植物品种,用于生殖质识别和知识产权保护.
科学领域:
- 农业科学 农业科学
- 遗传学 是一个遗传学.
- 生物信息学是一种生物信息学.
背景情况:
- DNA标记物概况对于生殖质的识别,注册和差异性,统一性和稳定性 (DUS) 测试至关重要.
- 从大型单核酸多态 (SNP) 数据集中选择最佳标记集,以实现最大的样本差异化是具有挑战性的.
研究的目的:
- 开发一个高效的管道,CoreSNP,从全基因组SNP数据中选择最小标记器集.
- 确保选定的标记物能够可靠地区分单个样本.
主要方法:
- 开发了CoreSNP管道,采用了"分裂与征服"战略和"贪"算法.
- 集成的可调节参数用于样本区分和处理缺失位置的数据集.
- 在各种作物数据集上测试管道,包括大麦,大豆,小麦,大米和玉米.
主要成果:
- 从各种作物 (SNP阵列,GBS,WGS数据集) 中有效地选择了几十个核心SNP,能够区分数千个样本.
- 核心SNP显示较低的链接不平衡 (LD) 和较高的多态信息含量 (PIC) 和小等位基因频率 (MAF),分布在染色体上.
- 确定了种群遗传多样性和数据集特征会影响核心标志物数量,以及核心SNP能够捕捉到种群结构.
结论:
- 核心SNP提供了一种有效的方法,用于从农作物的全基因组SNP数据中选择核心标记集.
- 这种方法与低密度SNP芯片或基因定型技术相结合,为评估遗传资源和区分作物品种提供了具有成本效益的解决方案.
- 预计CoreSNP将大大有利于生殖质比较和对新品种的知识产权保护.
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