在两种大米 (Oryza sativa L.) 种群中,使用全基因组关联研究衍生的标记物重量提高了抗爆性基因组预测能力
Félicien Akohoue1, Cristian Camilo Herrera2, Silvio James Carabali Balanta2
1Rice Program, International Centre for Tropical Agriculture (CIAT), Alliance Bioversity and CIAT, Americas Hub, Km 17 Recta Cali-Palmira, CP 763537, Palmira, Colombia. F.Akohoue@cgiar.org.
概括
将全基因组关联研究 (GWAS) 与基因组选择 (GS) 整合起来,提高了对米爆耐药性的预测准确性. 标记物权重策略提高了基因组最佳线性无偏预测 (GBLUP) 高达37%,加速了遗传收益.
科学领域:
- 植物育种和遗传学
- 基因组学和生物信息学
- 提高作物质量 提高作物质量
背景情况:
- 由Magnaporthe oryzae引起的水爆发是对全球水生产的重大威胁.
- 叶子爆炸 (BL) 和恐慌爆炸 (PB) 的遗传复杂性阻碍了基因组选择 (GS) 中的准确预测.
- 传统的基因组最佳线性无偏预测 (GBLUP) 假定标记者的贡献是平等的,可能缺少关键的抵抗位置.
研究的目的:
- 为了剖析大米中BL和PB耐药性的遗传结构.
- 为了评估加权GBLUP模型的性能,整合GWAS数据.
- 通过使用标记权重策略,提高米粉爆炸耐药性的预测准确度.
主要方法:
- 全基因组关联研究 (GWAS) 以确定标记特征关联 (MTA).
- 评估了三种加权的GBLUP模型:基于FST的 (FST-w),加值效应的平方 (AE-w) 和基于-log10 (p) 的 (-log10 (p) -w).
- 对两种不同种群的BL和PB耐药性的分析.
主要成果:
- 确定了对抗爆炸的显著MTA,包括Pi2/Pi9和Pi33.3附近的位置.
- 观察到BL和PB之间的中度遗传相关性 (0.43-0.44),表明共享遗传控制.
- AE-w和 -log10的p) -w模型将GBLUP预测能力提高了4-37%,并减少了预测错误.
结论:
- 将GWAS与GS (GS+GWAS) 整合起来,可显著提高诸如抗爆等复杂特征的预测准确度.
- 标记物权重是提高在米育种中基因组选择效率的实用策略.
- 这些发现可以加速改进米抗爆方案的遗传收益.
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