PacBio full-length transcriptome and WGCNA reveal varietal co-expression networks and regulatory dynamics during tea plant (Camellia sinensis) bud dormancy

Bud dormancy in tea tree ( Camellia sinensis ) is a key adaptive trait that strongly influences tea yield and quality. However, its molecular basis remains less well characterized than that of model plants and deciduous fruit trees. Previous studies have linked hormone homeostasis, carbohydrate status, and stress signaling to dormancy regulation, but most have relied on short-read RNA-seq or candidate-gene approaches, leaving isoform diversity and network-level regulation insufficiently resolved. Here, we combined PacBio Iso-Seq with expression profiling and weighted gene co-expression network analysis (WGCNA) to investigate three tea cultivars with contrasting dormancy characteristics: YC4H (short dormancy), FD (early bud break), and YH3/YC3H (intermediate dormancy). PacBio sequencing generated high-quality full-length transcripts and enabled accurate characterization of transcript structures without assembly. This dataset revealed 151,674-186,949 cultivar-specific transcripts, extensive alternative splicing events (including 7,130 retained-intron events in FD_Mix), and 93,072-100,010 candidate long non-coding RNAs (lncRNAs), including a high-confidence subset supported by all four prediction tools. PacBio-derived transcripts were then used as a reference for Illumina-based expression quantification, which supported transcript-level analyses and WGCNA. Global expression profiling and principal component analysis showed clear separation among cultivars and dormancy stages. Differential expression and co-expression analyses identified dynamic transcriptomic changes associated with phytohormone signaling, carbohydrate metabolism, stress responses, cell-cycle reactivation, and protein quality control. WGCNA identified 20 co-expression modules showing cultivar- and stage-associated patterns. Together, these results provide a transcriptome resource and a set of candidate regulatory pathways and hub genes associated with tea bud dormancy transitions, and they offer a useful framework for future functional studies and breeding-oriented investigations.

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Journal
Frontiers in Plant Science
Published
2026-04-27
DOI
https://doi.org/10.3389/fpls.2026.1738399
Primary Topic
Plant Molecular Biology Research
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article
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article

PacBio full-length transcriptome and WGCNA reveal varietal co-expression networks and regulatory dynamics during tea plant (Camellia sinensis) bud dormancy

Xiuming Zhai, Min Tang, Yujia Hou, Jie Li et al.
Frontiers in Plant Science
Plant Molecular Biology Research
article

PacBio full-length transcriptome and WGCNA reveal varietal co-expression networks and regulatory dynamics during tea plant (Camellia sinensis) bud dormancy

Xiuming Zhai, Min Tang, Yujia Hou, Jie Li, Fuliang Xiao, Wei Zhang, Surong Gao
article en

Abstract

Bud dormancy in tea tree ( Camellia sinensis ) is a key adaptive trait that strongly influences tea yield and quality. However, its molecular basis remains less well characterized than that of model plants and deciduous fruit trees. Previous studies have linked hormone homeostasis, carbohydrate status, and stress signaling to dormancy regulation, but most have relied on short-read RNA-seq or candidate-gene approaches, leaving isoform diversity and network-level regulation insufficiently resolved. Here, we combined PacBio Iso-Seq with expression profiling and weighted gene co-expression network analysis (WGCNA) to investigate three tea cultivars with contrasting dormancy characteristics: YC4H (short dormancy), FD (early bud break), and YH3/YC3H (intermediate dormancy). PacBio sequencing generated high-quality full-length transcripts and enabled accurate characterization of transcript structures without assembly. This dataset revealed 151,674-186,949 cultivar-specific transcripts, extensive alternative splicing events (including 7,130 retained-intron events in FD_Mix), and 93,072-100,010 candidate long non-coding RNAs (lncRNAs), including a high-confidence subset supported by all four prediction tools. PacBio-derived transcripts were then used as a reference for Illumina-based expression quantification, which supported transcript-level analyses and WGCNA. Global expression profiling and principal component analysis showed clear separation among cultivars and dormancy stages. Differential expression and co-expression analyses identified dynamic transcriptomic changes associated with phytohormone signaling, carbohydrate metabolism, stress responses, cell-cycle reactivation, and protein quality control. WGCNA identified 20 co-expression modules showing cultivar- and stage-associated patterns. Together, these results provide a transcriptome resource and a set of candidate regulatory pathways and hub genes associated with tea bud dormancy transitions, and they offer a useful framework for future functional studies and breeding-oriented investigations.

Frontiers in Plant ScienceVol. 17
Council of Agriculture (TW), Enshi Tujia and Miao Autonomous Prefecture Academy of Agricultural Sciences (CN), Chongqing Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 13%
Plant Molecular Biology Research
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