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<p>Wild apple (<i>Docynia indica</i>) is an ethnomedicinal plant consumed by ethnic groups in Northeast India. This wild apple possesses various medicinal properties, including antidiabetic, analgesic, and anti-inflammatory effects. Considering its ethnomedicinal value, the present study aims to enrich genetic resources and explore <i>D. indica</i> for potential antidiabetic drug discovery. We performed transcriptome analysis using next-generation sequencing (NGS) and generated approximately 4.2 GB of data for both leaf and fruit tissue. A total of 134,376 transcripts were generated through de novo assembly. After removing redundant sequences, 108,857 unique transcripts were identified, leading to the detection of 61,122 coding DNA sequences (CDS). Functional annotation revealed 57,554 transcripts with significant database hits, while 3,568 transcripts did not match any known sequences. This indicates involvement in species-specific pathways, potentially linked to metabolite biosynthesis for ethnic medicinal practices, including diabetes treatment. Additionally, 3,402 newly identified microsatellite markers from this study could be utilized for future program development. Differentially expressed transcripts between leaves and fruits revealed 10 downregulated genes in fruits and 2 in leaves, providing a platform for exploring novel metabolic pathways specific to <i>D. indica</i>.</p>

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Enriching genomic resources of wild apple Docynia indica (Wall.) decne using tissue-specific transcriptome profiling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月11日

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  • Mehzabin Rahman,
  • Md Aminul Islam,
  • Rodali Das,
  • Naba Kumar Hazarika,
  • Kishor Goswami,
  • Pranjan Barman

摘要

Wild apple (Docynia indica) is an ethnomedicinal plant consumed by ethnic groups in Northeast India. This wild apple possesses various medicinal properties, including antidiabetic, analgesic, and anti-inflammatory effects. Considering its ethnomedicinal value, the present study aims to enrich genetic resources and explore D. indica for potential antidiabetic drug discovery. We performed transcriptome analysis using next-generation sequencing (NGS) and generated approximately 4.2 GB of data for both leaf and fruit tissue. A total of 134,376 transcripts were generated through de novo assembly. After removing redundant sequences, 108,857 unique transcripts were identified, leading to the detection of 61,122 coding DNA sequences (CDS). Functional annotation revealed 57,554 transcripts with significant database hits, while 3,568 transcripts did not match any known sequences. This indicates involvement in species-specific pathways, potentially linked to metabolite biosynthesis for ethnic medicinal practices, including diabetes treatment. Additionally, 3,402 newly identified microsatellite markers from this study could be utilized for future program development. Differentially expressed transcripts between leaves and fruits revealed 10 downregulated genes in fruits and 2 in leaves, providing a platform for exploring novel metabolic pathways specific to D. indica.