Graph pangenome captures missing heritability and empowers tomato breeding

Yao Zhou, Zhiyang Zhang, Zhigui Bao, Hongbo Li, Yaqing Lyu, Yanjun Zan, Yaoyao Wu, Lin Cheng, Yuhan Fang, Kun Wu, Jinzhe Zhang, Hongjun Lyu, Tao Lin, Qiang Gao, Surya Saha, Lukas Mueller, Zhangjun Fei, Thomas Städler, Shizhong Xu, Zhiwu Zhang, Doug Speed and Sanwen Huang ()
Additional contact information
Yao Zhou: Chinese Academy of Agricultural Sciences
Zhiyang Zhang: Chinese Academy of Agricultural Sciences
Zhigui Bao: Chinese Academy of Agricultural Sciences
Hongbo Li: Chinese Academy of Agricultural Sciences
Yaqing Lyu: Chinese Academy of Agricultural Sciences
Yanjun Zan: Chinese Academy of Agricultural Sciences
Yaoyao Wu: Chinese Academy of Agricultural Sciences
Lin Cheng: Chinese Academy of Agricultural Sciences
Yuhan Fang: Chinese Academy of Agricultural Sciences
Kun Wu: Chinese Academy of Agricultural Sciences
Jinzhe Zhang: Sino-Dutch Joint Laboratory of Horticultural Genomics, and Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences
Hongjun Lyu: Chinese Academy of Agricultural Sciences
Tao Lin: China Agricultural University
Qiang Gao: Boke Biotech
Surya Saha: Cornell University
Lukas Mueller: Cornell University
Zhangjun Fei: Cornell University
Thomas Städler: ETH Zurich
Shizhong Xu: University of California
Zhiwu Zhang: Washington State University
Doug Speed: Aarhus University
Sanwen Huang: Chinese Academy of Agricultural Sciences

Nature, 2022, vol. 606, issue 7914, 527-534

Abstract: Abstract Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits1,2. The solution to this problem is to identify all causal genetic variants and to measure their individual contributions3,4. Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used for genome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding.

Date: 2022
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DOI: 10.1038/s41586-022-04808-9

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