4.7 Article

Unraveling the complexity of faba bean (Vicia faba L.) transcriptome to reveal cold-stress-responsive genes using long-read isoform sequencing technology

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-00506-0

Keywords

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Funding

  1. KAERI, Republic of Korea
  2. Radiation Technology R&D Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT [NRF-2017M2A2A6A05018538]

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The study sequenced the faba bean leaf transcriptome using the PacBio single-molecule long-read isoform sequencing platform, identifying 28569 nonredundant unigenes and revealing a complex transcriptome. Predicted proteins and transcription factors suggested an abundance of stress resistance genes in the faba bean genome.
Faba bean (Vicia faba L.), a globally important grain legume providing a stable source of dietary protein, was one of the earliest plant cytogenetic models. However, the lack of draft genome annotations and unclear structural information on mRNA transcripts have impeded its genetic improvement. To address this, we sequenced faba bean leaf transcriptome using the PacBio single-molecule long-read isoform sequencing platform. We identified 28,569 nonredundant unigenes, ranging from 108 to 9669 bp, with a total length of 94.5 Mb. Many unigenes (3597, 12.5%) had 2-20 isoforms, indicating a highly complex transcriptome. Approximately 96.5% of the unigenes matched sequences in public databases. The predicted proteins and transcription factors included NB-ARC, Myb_domain, C3H, bHLH, and heat shock proteins, implying that this genome has an abundance of stress resistance genes. To validate our results, we selected WCOR413-15785, DHN2-12403, DHN2-14197, DHN2-14797, COR15-14478, and HVA22-15 unigenes from the ICE-CBF-COR pathway to analyze their expression patterns in cold-treated samples via qRT-PCR. The expression of dehydrin-related genes was induced by cold stress. The assembled data provide the first insights into the deep sequencing of full-length RNA from faba bean at the single-molecule level. This study provides an important foundation to improve gene modeling and protein prediction.

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