Gene Mining and Genomics-Assisted Breeding Empowered by the Pangenome of Tea Plant Camellia Sinensis
Jan 1, 2023·,,,,,,,,,,,,,,,,,,,,,,·
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Shuai Chen
Pengjie Wang
Weilong Kong
Kun Chai
Shengcheng Zhang
Jiaxin Yu
Yibin Wang
Mengwei Jiang
Wenlong Lei
Xiao Chen
Wenling Wang
Yingying Gao
Shenyang Qu
Fang Wang
Yinghao Wang
Qing Zhang
Mengya Gu
Kaixing Fang
Chunlei Ma
Weijiang Sun
Naixing Ye
Hualing Wu
Xingtan Zhang
Abstract
Tea is one of the world’s oldest crops and is cultivated to produce beverages with various flavours. Despite advances in sequencing technologies, the genetic mechanisms underlying key agronomic traits of tea remain unclear. In this study, we present a high- quality pangenome of 22 elite cultivars, representing broad genetic diversity in the species. Our analysis reveals that a recent long terminal repeat burst contributed nearly 20% of gene copies, introducing functional genetic variants that affect phenotypes such as leaf colour. Our graphical pangenome improves the efficiency of genome-wide association studies and allows the identification of key genes controlling bud flush timing. We also identified strong correlations between allelic variants and flavour-related chemistries. These findings deepen our understanding of the genetic basis of tea quality and provide valuable genomic resources to facilitate its genomics- assisted breeding.
Type
Publication
Nature Plants