Extreme trait GWAS (Et-GWAS): Unraveling rare variants in the 3,000 rice genome.

IF 3.3 2区生物学 Q1 BIOLOGY

Life Science Alliance Pub Date : 2023-12-26 Print Date: 2024-03-01 DOI:10.26508/lsa.202302352

Niranjani Gnanapragasam, Vinukonda Vishnu Prasanth, Krishna Tesman Sundaram, Ajay Kumar, Bandana Pahi, Anoop Gurjar, Challa Venkateshwarlu, Sanjay Kalia, Arvind Kumar, Shalabh Dixit, Ajay Kohli, Uma Maheshwer Singh, Vikas Kumar Singh, Pallavi Sinha

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引用次数: 0

Abstract

Identifying high-impact, rare genetic variants associated with specific traits is crucial for crop improvement. The 3,010 rice genome (3K RG) dataset offers a valuable resource for discovering genomic regions with potential applications in crop breeding. We used Extreme Trait GWAS (Et-GWAS), employing bulk pooling and allele frequency measurement to efficiently extract rare variants from the 3K RG. This innovative approach facilitates the detection of associations between genetic variants and target traits, concentrating and quantifying rare alleles. In our study, on grain yield under drought stress, Et-GWAS successfully identified five key genes (OsPP2C11, OsK5.2, OsIRO2, OsPEX1, and OsPWA1) known for enhancing yield under drought. In addition, we examined the overlap of our results with previously reported qDTY-QTLs and observed that OsUCH1 and OsUCH2 genes were located within qDTY2.2 We compared Et-GWAS with conventional GWAS, finding it effectively capturing most candidate genes associated with the target trait. Validation with resistant starch showed similar results. To enhance user-friendliness, we developed a GUI for Et-GWAS; https://et-gwas.shinyapps.io/Et-GWAS/.

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极端性状 GWAS（Et-GWAS）：揭示 3000 个水稻基因组中的罕见变异。

鉴定与特定性状相关的高影响稀有遗传变异对作物改良至关重要。3010 个水稻基因组（3K RG）数据集为发现具有作物育种潜在应用价值的基因组区域提供了宝贵的资源。我们利用极端性状全球基因组分析（Extreme Trait GWAS，Et-GWAS），采用批量汇集和等位基因频率测量方法，从 3K RG 中高效提取稀有变异。这种创新方法有助于检测遗传变异与目标性状之间的关联，集中并量化稀有等位基因。在我们关于干旱胁迫下谷物产量的研究中，Et-GWAS 成功鉴定了五个已知能提高干旱下产量的关键基因（OsPP2C11、OsK5.2、OsIRO2、OsPEX1 和 OsPWA1）。2 我们将 Et-GWAS 与传统的 GWAS 进行了比较，发现它能有效捕获与目标性状相关的大多数候选基因。抗性淀粉的验证结果与之相似。为了提高用户友好性，我们开发了 Et-GWAS 的图形用户界面；https://et-gwas.shinyapps.io/Et-GWAS/。

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来源期刊

Life Science Alliance Agricultural and Biological Sciences-Plant Science

CiteScore

5.80

自引率

2.30%

发文量

241

审稿时长

10 weeks

期刊介绍： Life Science Alliance is a global, open-access, editorially independent, and peer-reviewed journal launched by an alliance of EMBO Press, Rockefeller University Press, and Cold Spring Harbor Laboratory Press. Life Science Alliance is committed to rapid, fair, and transparent publication of valuable research from across all areas in the life sciences.