Graph pangenome captures missing heritability and empowers tomato breeding

TY - JOUR

T1 - Graph pangenome captures missing heritability and empowers tomato breeding

AU - Zhou, Yao

AU - Zhang, Zhiyang

AU - Bao, Zhigui

AU - Li, Hongbo

AU - Lyu, Yaqing

AU - Zan, Yanjun

AU - Wu, Yaoyao

AU - Cheng, Lin

AU - Fang, Yuhan

AU - Wu, Kun

AU - Zhang, Jinzhe

AU - Lyu, Hongjun

AU - Lin, Tao

AU - Gao, Qiang

AU - Saha, Surya

AU - Mueller, Lukas

AU - Fei, Zhangjun

AU - Städler, Thomas

AU - Xu, Shizhong

AU - Zhang, Zhiwu

AU - Speed, Doug

AU - Huang, Sanwen

PY - 2022/6/16

Y1 - 2022/6/16

N2 - 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 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.

AB - 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 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.

KW - ANNOTATION

KW - GENOME

KW - STRUCTURAL VARIATION

KW - TOOL

KW - TRANSCRIPTOME

UR - http://www.scopus.com/inward/record.url?scp=85131514247&partnerID=8YFLogxK

U2 - 10.1038/s41586-022-04808-9

DO - 10.1038/s41586-022-04808-9

M3 - Journal article

C2 - 35676474

SN - 0028-0836

VL - 606

SP - 527

EP - 534

JO - Nature

JF - Nature

IS - 7914

ER -