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一个低覆盖范围的Skim测序和归算管道,用于基因组选择
Sajal R Sthapit1, Jared Crain2, Steve Larson3
1The Land Institute, Salina, Kansas, USA.
The plant genome
|October 23, 2025
概括
基因组选择 (GS) 使用低覆盖范围的脱皮测序提供了一种具有成本效益的方法来改善植物育种. 这种方法的准确性与中间小麦草的基因型测序相似,使作物发展速度更快.
科学领域:
- 植物育种和遗传学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 基因组选择 (GS) 通过提高选择精度和减少周期时间来加速植物育种.
- 多年作物,如中间小麦草 (IWG) 显著受益于GS,因为长时间的评估期.
- 实施GS需要负担得起,高密度的基因标记系统可扩展到大型育种计划.
研究的目的:
- 评估使用低覆盖范围的全基因组脱脂测序 (skim-seq) 在中间小麦草 (IWG) 中对GS的可行性.
- 使用STITCH软件优化skim-seq数据的归算参数.
- 为了将skim-seq的预测准确性与IWG中的GS的基因型测序 (GBS) 进行比较.
主要方法:
- 实施了超低覆盖率 (0.01x-0.05x) 的全基因组脱皮测序,用于GS的育种计划规模.
- 使用STITCH (通过构建哈普洛类型对传算进行测序) 软件来赋予遗传标记.
- 优化的归算参数,包括序列覆盖和祖先的单元型号号.
- 进行了交叉验证,以在IWG中对五个特征进行Skim-seq和GBS数据之间的GS准确性进行比较.
主要成果:
- 对IWG中的五个特征,Skim-seq数据实现了与GBS (r = 0.29-0.55) 相比的交叉验证准确度 (r = 0.29-0.61),可与GBS (r = 0.29-0.55) 相比.
- 低覆盖范围的skim-seq,当归算时,在具有大型基因组的多多年生植物物种中,为GS提供了可行的GBS替代方案.
- 开发的方法是可扩展的,适用于各种作物,促进GS的实施.
结论:
- 低覆盖范围的skim-seq是一种具有成本效益和准确的方法,用于中间小麦草的基因组选择.
- 这种方法产生了对技术进步稳固的档案序列数据.
- 可扩展的方法使GS在各种作物种的育种计划中得到更广泛的采用.
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