Full-Length Transcriptome Analysis Reveals Candidate Genes Involved with Terpenoid Biosynthesis in Hemsleya omeiensis
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https://figshare.com/articles/dataset/Full-Length_Transcriptome_Analysis_Reveals_Candidate_Genes_Involved_with_Terpenoid_Biosynthesis_in_i_Hemsleya_omeiensis_i_/30427894
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Hemsleya omeiensis is an important medicinal plant in the Cucurbitaceae, whose tubers are abundant in triterpenoids such as Cucurbitacin IIa. However, the molecular basis of their biosynthesis remains poorly characterized and genomic resources for this species are limited. This study aimed to elucidate the molecular mechanisms of triterpenoid biosynthesis and provide a valuable genetic resources. We integrated PacBio Iso-Seq full-length transcriptome sequencing with Illumina RNA-Seq to generate the first high-quality full-length reference transcriptome for H. omeiensis.Using transcriptomes from leaves, stems, and tubers, we systematically identified and annotated protein-coding genes, transcription factors, lncRNAs, and SSR markers. We obtained 22,238 non-redundant unigenes (most > 1 kb) and utilized short reads to correct sequencing errors , thereby enhancing accuracy. Over 8,000 high-confidence lncRNAs and numerous SSR loci were identified. Differential expression analysis revealed that genes involved in cucurbitacin biosynthesis are enriched in tubers, displaying distinct tissue specificity: upstream precursor synthesis genes (e.g., HMG1, ERG10) were highly expressed across all three tissues, backbone synthesis genes (e.g., SQS) were broadly expressed, while downstream modification genes (e.g., HcAT1) were preferentially expressed in tubers. This pattern aligns with the accumulation of Cucurbitacin IIa in this organ. RT-qPCR validation comfirmed the RNA-Seq expression trends (R² > 0.90), identifying ERG10 and HcOSC4 candidates for functional characterization. This study establishes a foundational full-length transcriptomic resource for H. omeiensis and clarifies the tissue-specific molecular features of hemslecin biosynthesis. It provides crucial data for future functional analyses, evolutionary studies of metabolic pathways, molecular breeding and sustainable resource utilization.
创建时间:
2025-10-24



