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基于模拟的QTL映射在环境和基因型x环境相互作用效应下的效率评估

Grace Sunshine David¹, José Marcelo Soriano Viana², Kaio Olimpio das Graças Dias²

¹Department of Crop Science, University of Calabar, Calabar, Cross River State, Nigeria.

|November 30, 2023

概括

这项研究模拟了定量特征位置 (QTL) 映射,发现基因型x环境相互作用使特征预测复杂化. 然而,尽管存在这些复杂性,单个和跨环境分析仍然有效用于QTL检测.

科学领域:

定量遗传学是一个量子遗传学.
植物育种植物育种
生物信息学是一种生物信息学.

背景情况:

定量特征位置 (QTL) 映射对于理解复杂特征至关重要.
基因型x环境 (GxE) 相互作用显著影响特征表达和QTL映射效率.
准确的QTL检测需要强大的方法,考虑到环境因素.

研究的目的:

用模拟来评估基因,环境和GxE相互作用对QTL映射效率的影响.
评估单个和跨环境的QTL映射模型的性能.
在多环境试验中确定QTL映射的可预测性.

主要方法:

在六个环境中模拟了300个重组杂交系 (RILs) 的基因型,其中有977个SNP.
对谷物产量的表型RIL,特征遗传率在30%至80%之间.
应用单个和多个QTL模型,分析单个和跨环境数据.

主要成果:

复杂的GxE相互作用减少了QTL遗传性和映射功率之间的相关性.
单个和跨环境分析检测到所有模拟的高平均功率 (28-100%) 的QTL.
两种模型都保持了低的错误阳性率 (平均值为1%) 和低的错误阳性率 (平均值为1%) 6%) 和精确的QTL定位 (平均值). 2 cM偏差). 这种偏差是

结论:

在多环境试验中,由于GxE相互作用的不确定性,QTL映射是不可预测的.
尽管存在挑战,单个和跨环境分析表明QTL检测的效率.
有效的QTL映射策略必须考虑环境影响和GxE相互作用.

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