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Updated: Jun 30, 2026

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

DiRT v2.0: An Optimized Pipeline for Detecting Dicistronic tRNA-mRNA Transcripts in Plants.

Fei Zheng1, Lakshay Anand2, Roberta Magnani2

  • 1School of Agriculture, Food and Wine, Adelaide University, Adelaide, SA, Australia.

Bio-Protocol
|June 29, 2026
PubMed
Summary
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Researchers developed DiRT v2, a computational tool to identify plant dicistronic tRNA-mRNA transcripts. This method enhances detection of tRNA-like structures and UTR-embedded candidates, aiding the study of RNA long-distance signaling.

Area of Science:

  • Plant molecular biology
  • Bioinformatics
  • Genomics

Background:

  • Transfer RNAs (tRNAs) traditionally function in protein synthesis.
  • Emerging evidence highlights tRNA roles in plant long-distance signaling.
  • Dicistronic tRNA-mRNA transcripts facilitate systemic RNA mobility.

Purpose of the Study:

  • To develop and validate a computational pipeline (DiRT v2) for detecting plant dicistronic tRNA-mRNA transcripts.
  • To improve the identification of tRNA-like structures (TLS) and UTR-embedded candidates.
  • To provide a robust method for analyzing RNA sequencing data for novel transcript discovery.

Main Methods:

  • Development of the DiRT v2 bioinformatics pipeline for analyzing next-generation RNA sequencing data.
  • Incorporation of statistical methods (Student's t-test, FDR < 0.05) using flanking intronic regions for robustness against contamination.
Keywords:
BioinformaticsDicistronic transcriptsMotif analysisNovel transcriptomic featuresTranscriptomic analysistRNA-mRNA

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  • Application of the pipeline to grapevine and Arabidopsis thaliana datasets, with in vitro validation via RT-PCR.

    • Main Results:

    • DiRT v2 successfully identifies dicistronic tRNA-mRNA transcripts, including functional tRNAs, tRNA-like structures (TLS), and UTR-embedded sequences.
    • The pipeline demonstrates improved accuracy and statistical validation compared to previous versions.
    • Novel tRNA and TLS dicistronic transcripts were identified in grapevine and Arabidopsis thaliana.

    Conclusions:

    • DiRT v2 offers a fast, reliable, and improved bioinformatics workflow for identifying plant dicistronic tRNA-mRNA transcripts.
    • The tool facilitates the functional characterization of these emerging signaling molecules.
    • This method advances the understanding of RNA-mediated communication in plants.