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.

葡萄藤育种受到对复杂农艺性状遗传基础的有限理解的阻碍。本研究从 18 个新生成的分阶段端粒到端粒组装和 11 个已发表的组装中构建了一个基于图的泛基因组参考 （Grapepan v.1.0）。使用 Grapepan v.1.0，我们从 466 个葡萄品种的重测序数据中构建了一个包含 9,105,787 个短变异和 236,449 个结构变异 （SV） 的变异图。将 SVs 整合到全基因组关联研究中，我们为 29 个农艺性状绘制了 148 个数量性状位点（50.7% 新发现），其中 12 个性状由 SV 显着贡献。当包括 SV 时，估计的遗传力平均提高了 22.78%。我们分别发现了葡萄酒和鲜食葡萄之间代谢和浆果发育的不同人工选择下的数量性状位点区域。此外，在 29 个性状中检测到显着的遗传相关性。在多基因模型下，我们对每个性状进行了基因组预测。一般来说，我们的研究通过多个性状的基因组选择促进了优良品种的育种。