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基因组预测可以利用跨基因库的表型数据进行基因预测

Samira El Hanafi¹, Yong Jiang¹, Zakaria Kehel²

¹Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.

Frontiers in plant science

|September 13, 2023

概括

跨基因库预测显著提高了植物遗传资源的性能预测. 整合多样化的胚胎血收集,如IPK和ICARDA的收集,可以提高大麦育种的预测准确度.

科学领域:

农业科学农业科学
遗传学是一个遗传学.
植物育种植物育种

背景情况:

全基因组的预测对于繁殖和利用基因库资源至关重要.
基因库中的植物遗传资源往往存在信息缺口,限制了它们在预育种中的使用.
跨基因库的预测可以释放这些宝贵收藏的潜力.

研究的目的:

为了评估跨基因库预测大麦 (Hordeum vulgare L.) 生殖质的有效性.
为了比较不同的预测场景,包括在基因库内部和跨基因库的方法.
评估训练集大小和组成对预测准确性的影响.

主要方法:

利用了IPK的9,344个大麦加入和ICARDA的1,089个大麦加入的关于开花/标题日期,植物高度和千粒粒重量的历史数据.
我们比较了三个预测场景:基准 (ICARDA内部),跨基因库 (IPK培训,ICARDA测试) 和综合 (IPK + 30% ICARDA培训,ICARDA测试).
分析了不同场景的预测能力,以确定最有效的方法.

主要成果:

基因库内预测的准确性低至中,可能是由于训练数据有限.
使用综合训练集 (IPK + 30% ICARDA) 进行跨基因库预测,预测能力提高了多达九倍.
基因型×环境相互作用 (GEI) 构成了挑战,但被更大,连接的培训集所抵消.

结论:

跨基因库的预测,特别是综合训练集,显著改善了植物遗传资源的预测性特征.
这种方法可以增强全球基因库收藏的策划,并推进生物数字化资源中心的发展.
在基因库中增加训练数据克服了小的,孤立的数据集的局限性,并可能减轻GEI的影响.

关键词:

伊卡尔达 (ICARDA) 是一个城市.IPK IPK 是一个大麦大麦大麦大麦大麦大麦大麦大麦基因银行的基因银行基因组预测基因组预测预测预测能力预测能力

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