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Chromosome-level reference genome of Tetrastigma hemsleyanum (Vitaceae) provides insights into genomic evolution and the biosynthesis of phenylpropanoids and flavonoids.

Yingxiong QiuXinyi ZhangChaoqian RenXinhan XuHans Peter ComesWeimei JiangChengxin FuHuixia FengLiming CaiDe-Yuan HongKunlun LiGuoyin KaiYing-Xiong Qiu
Published in: The Plant journal : for cell and molecular biology (2023)
Here, we present a high-quality chromosome-scale genome assembly (2.19 Gb) and annotation of Tetrastigma hemsleyanum, a perennial herbaceous liana native to subtropical China with diverse medicinal applications. Approximately 73% of the genome was comprised of transposable elements (TEs), of which long terminal repeat retrotransposons (LTR-RTs) were a predominant group (69% of the genome). The genome size increase of T. hemsleyanum (relative to Vitis species) was mostly due to the proliferation of LTR-RTs. Of the different modes of gene duplication identified, transposed duplication (TRD) and dispersed duplication (DSD) were the predominant ones. Genes, particularly those involved in the phenylpropanoid-flavonoid (PF) pathway and those associated with therapeutic properties and environmental stress resistance, were significantly amplified through recent tandem duplications. We dated the divergence of two intraspecific lineages in Southwest (SW) versus Central-South-East (CSE) China to the late Miocene (approximately 5.2 million years ago). Of those, the former showed more upregulated genes and metabolites. Based on resequencing data of 38 individuals representing both lineages, we identified various candidate genes related to 'response to stimulus' and 'biosynthetic process', including ThFLS11, which is putatively involved in flavonoid accumulation. Overall, this study provides abundant genomic resources for future evolutionary, ecological, and functional genomics studies in T. hemsleyanum and related species.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • genome wide identification
  • ms ms
  • climate change
  • rna seq
  • genetic diversity
  • electronic health record
  • risk assessment
  • artificial intelligence
  • deep learning