选择性基因型和表型化用于优化基因组预测模型,用于不同多样性的种群
Marina Ćeran1, Vuk Đorđević2, Jegor Miladinović2
1Laboratory for Biotechnology, Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Maksima Gorkog 30, 21000 Novi Sad, Serbia.
Plants (Basel, Switzerland)
|April 13, 2024
概括
选择性基因型和表型化提高了大豆育种中的基因组预测准确性. 这些方法降低了成本,同时保持了遗传多样性,并加速了改善作物产量的遗传收益.
科学领域:
- 植物育种 植物育种
- 遗传学 是一个遗传学.
- 农业科学 农业科学
背景情况:
- 粮食安全受到人口增长和气候变化的威胁.
- 大豆 (Glycine max) 育种的目标是提高生产率和可持续性.
- 基因组选择 (GS) 使用全基因组标记加速遗传收益.
研究的目的:
- 对大豆产量预测准确性的选择性基因型和表型方法进行评估.
- 确定最佳标记物选择和基因型减少策略.
- 评估对基因型和表型成本的影响.
主要方法:
- 应用的标记物选择策略:SNP修剪,标记物效应估计,随机选择,GWAS.
- 通过选择保持遗传多样性的核心集来减少基因型数量.
- 在重组杂交系,多家族多样性系和生殖血集合中评估预测能力.
主要成果:
- 基于模型的标记物选择子集在不同种群中最适合.
- 与随机选择相比,选择性表型化提高了预测能力.
- 通过AN方法和75%的种群大小获得的最高预测能力.
结论:
- 选择性基因型和表型是大豆基因组选择的有效工具.
- 这些策略可以降低成本,同时提高或保持选择准确性.
- 这些方法的整合支持可持续的农业强化.
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