GWAS meta-analysis using a graph-based pan-genome enhanced gene mining efficiency for agronomic traits in rice

被引：0

作者：

Yang, Longbo ^{[1
,2
]}

He, Wenchuang ^{[2
]}

Zhu, Yiwang ^{[2
]}

Lv, Yang ^{[2
]}

Li, Yilin ^{[1
,2
]}

Zhang, Qianqian ^{[1
,2
]}

Liu, Yifan ^{[1
,2
]}

Zhang, Zhiyuan ^{[1
,2
]}

Wang, Tianyi ^{[2
]}

Wei, Hua ^{[2
]}

Cao, Xinglan ^{[2
]}

Cui, Yan ^{[2
]}

Zhang, Bin ^{[2
]}

Chen, Wu ^{[2
]}

He, Huiying ^{[2
]}

Wang, Xianmeng ^{[2
]}

Chen, Dandan ^{[2
]}

Liu, Congcong ^{[2
]}

Shi, Chuanlin ^{[2
]}

Liu, Xiangpei ^{[2
]}

Xu, Qiang ^{[2
]}

Yuan, Qiaoling ^{[2
]}

Yu, Xiaoman ^{[2
]}

Qian, Hongge ^{[2
]}

Li, Xiaoxia ^{[2
]}

Zhang, Bintao ^{[2
]}

Zhang, Hong ^{[2
]}

Leng, Yue ^{[2
]}

Zhang, Zhipeng ^{[2
]}

Dai, Xiaofan ^{[2
]}

Guo, Mingliang ^{[2
]}

Jia, Juqing ^{[1
]}

Qian, Qian ^{[2
,3
,4
,5
]}

Shang, Lianguang ^{[2
,4
,5
]}

机构：

[1] Shanxi Agr Univ, Coll Agr, Jinzhong 030801, Shanxi, Peoples R China

[2] Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Minist Agr & Rural Affairs, Genome Anal Lab,Guangdong Lab Lingnan Modern Agr,S, Shenzhen 518120, Peoples R China

[3] China Natl Rice Res Inst, State Key Lab Rice Biol, Hangzhou 310006, Peoples R China

[4] Yazhouwan Lab, 8 Huanjin Rd, Sanya 572024, Hainan, Peoples R China

[5] Chinese Acad Agr Sci, Natl Nanfan Res Inst Sanya, Academician Workstat, Sanya 572024, Peoples R China

来源：

NATURE COMMUNICATIONS | 2025年 / 16卷 / 01期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

WIDE ASSOCIATION; GRAIN-SIZE; YIELD; TOOL; QUALITY; GROWTH;

D O I：

10.1038/s41467-025-58081-1

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Genome-wide association studies (GWASs) encounter limitations from population structure and sample size, restricting their efficacy. Though meta-analysis mitigates these issues, its application in rice research remains limited. Here, we report a large-scale meta-analysis of six independent GWAS experiments in rice to mine genes for key agronomic traits. By integrating a rice pan-genome graph to identify structural variants, we obtained 6,604,898 SNP and 42,879 PAV variants for the six panels (7765 accessions). Meta-analysis significantly improved quantitative trait loci (QTLs) detection and hidden heritability by up to 43 and 37.88%, respectively. Among 156 QTLs identified for six agronomic traits, 116 were exclusively detected through meta-analysis, highlighting its superior resolution. Two novel QTLs governing grain width and length were functionally validated through CRISPR/Cas9, confirming their candidate genes. Our findings underscore the utility and potential advantages of this pan-genome-based meta-GWAS approach, providing a scalable model for efficiently gene mining from diverse rice germplasms.

引用

页数：9

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