数字农科院2.0

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

文献类型： 外文期刊

作者： Xu Wang;Zhongjie Liu;Fan Zhang;Hua Xiao;Shuo Cao;Hui Xue;Wenwen Liu;Ying Su;Zhenya Liu;Haixia Zhong;Fuchun Zhang;Bilal Ahmad;Qiming Long;Yingchun Zhang;Yuting Liu;Yu Gan;Ting Hou;Zhongxin Jin;Xinyu Wu;Guotian Liu;Yiwen Wang;Yanling Peng;Yongfeng Zhou

作者机构：

关键词： （1-1-1）comparative genomics;convergent evolution;genomic breeding;genomic selection;grape breeding;introgression;seed abortion;seedlessness;structural variations;viticulture

期刊名称： Current Biology

ISSN： 0960-9822

年卷期： 2024 年 34 卷 16 期

页码：

收录情况： SCIE（2024版）

摘要： Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, “Thompson Seedless” (TS, syn. “Sultania”) and “Black Monukka” (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to “Sultania.” Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

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