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

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.
• 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.