bioRxivGenomicsPreprint
Pangenome analyses of tea plant reveal structural variations driven gene expression alterations and agronomic trait diversification
Lingling TaoiD, Junyan ZhuiD, Jianbing HuiD, Jun WuiD, Chunlin CheniD, Youyong LiiD, Fangdong LiiD, Hongrong CheniD, Songyan HuangiD, Qianqian ZhouiD, Yuanyan ZhaoiD, Yanping HuiD, Shengrui LiuiD, Kun DongiD, L. CheniD, Benying LiuiD, Xiaochun WaniD, Enhua XiaiD, Yongfeng ZhouiD, Chaoling WeiiD
Abstract
Tea plants, one of the worlds most economically significant beverage crops, exhibit extensive genetic diversity and a rich array of secondary metabolites. While structural variations (SVs) are key drivers of phenotypic innovation, their regulatory roles in transcriptional networks and agronomic trait diversification remain underexplored in this perennial crop. We constructed a pangenome from 21 representative tea accessions and their wild relatives. Comparative analysis revealed that wild relatives harbor a greater abundance of gibberellin-related genes, whereas cultivated accessions exhibit an expansion of defense-related genes. We identified 522,428 non-redundant SVs, primarily insertions/deletions (73.56%), which were enriched in promoter regions. These SVs influenced the expression of genes governing flavor compounds, including those involved in flavonoid, amino acid, and terpenoid biosynthesis. Population SV analysis of 275 tea accessions uncovered three haplotypes in the ANS3 gene promoter region, with Hap1, containing a 192 bp insertion, predominantly found in wild relatives but largely lost in modern cultivars. This insertion enhanced CtANS3 expression, increasing anthocyanin accumulation. Additionally, a 159 bp insertion in the CtLRR1 promoter reduced resistance to Colletotrichum gloeosporioides in wild relatives. Our findings underscore SVs as pivotal regulators of genomic diversity, flavor differentiation, and adaptive evolution in tea plant domestication.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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