Graph-based pangenome provides insights into structural variations and genetic basis of metabolic traits in potato
Xiaoling Zhu, Rui Yang, Qiqi Liang, Yuye Yu, Tingting Wang, Meng Li, Ping Wang, Shaoyang Wang, Xianping Li, Qiongfen Yang, Huachun Guo, Sui QiJun, Qiang Wang, Hai Du, Qin Chen, Zhe Liang, Xuewei Wu, Qian Zeng, Binquan Huang
Abstract
Potato is the world's most important nongrain crop. In this study, to assess genetic diversity within the Petota section, 29 genomes from Petota and Etuberosum sections were newly de novo assembled and 248 accessions of wild potatoes, landraces, and modern cultivars were re-sequenced at >25× depth. Subsequently, a graph-based pangenome was constructed using DM8.1 as the backbone, integrating194,330 nonredundant structural variants. To characterize the metabolome of tubers and illuminate the genomic basis of metabolic traits, LC-MS/MS was employed to obtain the metabolome of 157 accessions, and 9,321 structural variants (SVs) were detected to be significantly associated with 1,258 distinct metabolites via PAV (presence and absence variations)-based metabolomics-GWAS analysis, including metabolites of flavonoids, phenolic acids, and phospholipids. To facilitate the utilization of pangenome resources, a comprehensive platform, the Potato Pangenome Database (PPDB), was developed. Our study provides a comprehensive genomic resource for dissecting the genomic basis of agronomic and metabolic traits in potato, which will accelerate functional genomics studies and genetic improvements in potato.