Grapevine pangenome facilitates trait genetics and genomic breeding

Grapevine breeding is hindered by a limited understanding of the genetic basis of complex agronomic traits. This study constructs a graph-based pangenome reference (Grapepan v.1.0) from 18 newly generated phased telomere-to-telomere assemblies and 11 published assemblies. Using Grapepan v.1.0, we build a variation map with 9,105,787 short variations and 236,449 structural variations (SVs) from the resequencing data of 466 grapevine cultivars. Integrating SVs into a genome-wide association study, we map 148 quantitative trait loci for 29 agronomic traits (50.7% newly identified), with 12 traits significantly contributed by SVs. The estimated heritability improves by 22.78% on average when including SVs. We discovered quantitative trait locus regions under divergent artificial selection in metabolism and berry development between wine and table grapes, respectively. Moreover, significant genetic correlations were detected among the 29 traits. Under a polygenic model, we conducted genomic predictions for each trait. In general, our study facilitates the breeding of superior cultivars via the genomic selection of multiple traits.

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Publication Details

Journal
Nature Genetics
Published
2024-11-04
DOI
https://doi.org/10.1038/s41588-024-01967-5
Citations
76
Primary Topic
Horticultural and Viticultural Research
Type
article
Field-Weighted Citation Impact
45.57
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article

Grapevine pangenome facilitates trait genetics and genomic breeding

Lingfei Shangguan, Qiming Long, Zhongxin Jin, Xinyu Wu et al.
76 citations
Nature Genetics
Horticultural and Viticultural Research
45.57
article

Grapevine pangenome facilitates trait genetics and genomic breeding

Lingfei Shangguan, Qiming Long, Zhongxin Jin, Xinyu Wu, Yanling Peng, Yanhua Ren, Yu Gan, Jinggui Fang, Sanwen Huang, Bilal Ahmad, Zhongjie Liu, Shuo Cao, Xuejing Cao, Brandon S. Gaut, Jinfeng Chen, Xiangpeng Leng, Chonghuai Liu, Dan Pei, Zhenya Liu, Mengqing Ge, Xiaodong Xu, Nan Wang, Wénwén Liú, Yuting Liu, Chuan Zhang, Lei Sun, Fan Zhang, Xu Wang, Zhong Haixia, Hua Xiao, Chaochao Li, Zhi‐Yao Ma, Tianyu Dong, Xiucai Fan, Mengrui Du, Yongfeng Zhou, Hui Xue, Xiangnian Su, Yiwen Wang, Guizhou Huang, Ying Su
article en
76 citations

Abstract

Grapevine breeding is hindered by a limited understanding of the genetic basis of complex agronomic traits. This study constructs a graph-based pangenome reference (Grapepan v.1.0) from 18 newly generated phased telomere-to-telomere assemblies and 11 published assemblies. Using Grapepan v.1.0, we build a variation map with 9,105,787 short variations and 236,449 structural variations (SVs) from the resequencing data of 466 grapevine cultivars. Integrating SVs into a genome-wide association study, we map 148 quantitative trait loci for 29 agronomic traits (50.7% newly identified), with 12 traits significantly contributed by SVs. The estimated heritability improves by 22.78% on average when including SVs. We discovered quantitative trait locus regions under divergent artificial selection in metabolism and berry development between wine and table grapes, respectively. Moreover, significant genetic correlations were detected among the 29 traits. Under a polygenic model, we conducted genomic predictions for each trait. In general, our study facilitates the breeding of superior cultivars via the genomic selection of multiple traits.

Nature GeneticsVol. 56(12)
Chinese Academy of Tropical Agricultural Sciences (CN), Nanjing Agricultural University (CN), Qingdao Agricultural University (CN), Chinese Academy of Sciences (CN), University of California, Irvine (US), Agricultural Genomics Institute at Shenzhen (CN), Tropical Crops Genetic Resources Institute (CN), Xinjiang Academy of Agricultural Sciences (CN), Zhengzhou Fruit Research Institute (CN), Chinese Academy of Agricultural Sciences (CN), Ministry of Agriculture and Rural Affairs (CN), Institute of Zoology (CN)
Zero hunger
Openalex Percentile: Top 0%
Horticultural and Viticultural Research
45.57
DOIOpen Access PDFOpenAlex
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