GWAS meta-analysis using a graph-based pan-genome enhanced gene mining efficiency for agronomic traits in rice.
- 2025-04-03
- Nature communications 16(1)
- Longbo Yang
- Wenchuang He
- Yiwang Zhu
- Yang Lv
- Yilin Li
- Qianqian Zhang
- Yifan Liu
- Zhiyuan Zhang
- Tianyi Wang
- Hua Wei
- Xinglan Cao
- Yan Cui
- Bin Zhang
- Wu Chen
- Huiying He
- Xianmeng Wang
- Dandan Chen
- Congcong Liu
- Chuanlin Shi
- Xiangpei Liu
- Qiang Xu
- Qiaoling Yuan
- Xiaoman Yu
- Hongge Qian
- Xiaoxia Li
- Bintao Zhang
- Hong Zhang
- Yue Leng
- Zhipeng Zhang
- Xiaofan Dai
- Mingliang Guo
- Juqing Jia
- Qian Qian
- Lianguang Shang
- PubMed: 40180959
- DOI: 10.1038/s41467-025-58081-1
Study Design
- Type
- Meta-Analysis
- Population
- rice accessions from six panels (7765 accessions)
- Methods
- meta-analysis of six independent GWAS experiments, integrating a rice pan-genome graph to identify structural variants
- Funding
- Unclear
- Rigorous Journal
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.