文献类型： 外文期刊

作者： Zhou, Yao ¹ ; Zhang, Zhiyang ¹ ; Bao, Zhigui ¹ ; Li, Hongbo ¹ ; Lyu, Yaqing ¹ ; Zan, Yanjun ¹ ; Wu, Yaoyao ¹ ; Cheng, Lin ¹ ; Fang, Yuhan ¹ ; Wu, Kun ¹ ; Zhang, Jinzhe ³ ; Lyu, Hongjun ¹ ; Lin, Tao ⁶ ; Gao, Qiang ⁷ ; Saha, Surya ⁸ ; Mueller, Lukas ⁸ ; Fei, Zhangjun ⁸ ; Stadler, Thomas ¹⁰ ; Xu, Shizhong ¹² ; Zhang, Zhiwu ¹³ ; Speed, Doug ¹⁴ ; Huang, Sanwen ¹ ;

作者机构： 1.Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Minist Agr & Rural Affairs,Shenzhen Branch, Genome Anal Lab,Guangdong Lab Lingnan Modern Agr, Shenzhen, Peoples R China

2.Swedish Univ Agr Sci, Umea Plant Sci Ctr, Dept Forestry Genet & Plant Physiol, Umea, Sweden

3.Chinese Acad Agr Sci, Minist Agr, Key Lab Biol & Genet Improvement Hort Crops, Sino Dutch Joint Lab Hort Genom, Beijing, Peoples R China

4.Chinese Acad Agr Sci, Inst Vegetables & Flowers, Beijing, Peoples R China

5.Shandong Acad Agr Sci, Inst Vegetables,Shandong Prov Key Lab Biol Greenh, Natl Improvement Ctr Vegetables,Minist Agr & Rura, Shandong Branch,Huang Huai Hai Reg Sci Observat &, Jinan, Peoples R China

6.China Agr Univ, Coll Hort, State Key Lab Agrobiotechnol, Beijing, Peoples R China

7.Boke Biotech, Wuxi, Jiangsu, Peoples R China

8.Cornell Univ, Boyce Thompson Inst, Ithaca, NY USA

9.ARS, USDA, Robert W Holley Ctr Agr & Hlth, Ithaca, NY USA

10.Swiss Fed Inst Technol, Inst Integrat Biol, Zurich, Switzerland

11.Swiss Fed Inst Technol, Basel Plant Sci Ctr, Zurich, Switzerland

12.Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA

13.Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA

14.Aarhus Univ, Quantitat Genet & Genom QGG, Aarhus, Denmark

期刊名称：NATURE （ 影响因子：69.504； 五年影响因子：63.58 ）

ISSN： 0028-0836

年卷期： 2022 年 606 卷 7914 期

页码：

收录情况： SCI

摘要： Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits(1,2). The solution to this problem is to identify all causal genetic variants and to measure their individual contributions(3,4). 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 forgenome-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.