基因型调用方法对多倍体中全基因组关联和基因组预测的影响
Joyce N Njuguna1, Lindsay V Clark2, Alexander E Lipka1
1Department of Crop Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
The plant genome
|October 31, 2023
概括
准确的基因型调用多倍种作物对于分子育种至关重要. 像连续基因型的polyRAD这样的贝叶斯方法可以改善全基因组关联研究和基因组预测准确性,特别是在低测序深度.
科学领域:
- 农业科学 农业科学
- 遗传学 是一个遗传学.
- 生物信息学是一种生物信息学.
背景情况:
- 准确的遗传变体发现对于作物分子育种至关重要.
- 减少表征测序提供了具有成本效益的基因型定型,但在多倍体中面临着挑战.
- 贝叶斯统计方法提高了复杂的多倍体基因组中的基因型调用准确度.
研究的目的:
- 评估贝叶斯基因型调用算法 (polyRAD,EBG,updog) 对于多种植的作物.
- 评估连续基因型与离散基因型对GWAS和基因组预测的影响.
- 为了优化多类物种的成本效益高的分子育种策略.
主要方法:
- 三个贝叶斯基因型调用算法的实证和模拟数据分析.
- 全基因组协会研究 (GWAS) 和基因组预测分析.
- 在不同的读取深度下,连续和离散的基因型调用的比较.
主要成果:
- 贝叶斯算法在经验数据中显示了对GWAS和基因组预测的各种下游影响.
- polyRAD在GWAS功率方面表现出优势,并在低读取深度下降了虚假阳性.
- 连续基因型通过最大限度地减少基因型错误来提高基因组预测的准确性,特别是在较低的测序深度.
结论:
- 在polyRAD中的贝叶斯算法与连续基因型相结合,可以在多倍种作物中提供准确且经济高效的GWAS和基因组预测.
- 这种方法有助于在农业上重要的多类物种的分子育种方面取得进展.
- 优化基因型调用策略对于利用下一代测序在作物改进中至关重要.
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