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LncRAnalyzer: a robust workflow for long non-coding RNA discovery using RNA-Seq.

Shinde Nikhil¹, Habeeb Shaik Mohideen², Raja Natesan Sella¹

¹Membrane Protein Interaction Lab, Department of Genetic Engineering, SRM Institute of Science and Technology, Chengalpattu District, Tamil Nadu, 603203, India.

The Plant Journal : for Cell and Molecular Biology

|October 17, 2025

Summary

This summary is machine-generated.

LncRAnalyzer is a new automated pipeline for identifying long non-coding RNAs (lncRNAs). It improves accuracy and reduces errors compared to existing methods, aiding plant research.

Keywords:

LncRAnalyzer RNA‐Seq Sorghum bicolor genomics long non‐coding RNA

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Long non-coding RNAs (lncRNAs) are crucial RNA molecules lacking protein-coding potential.
Identifying lncRNAs is challenging due to their low abundance and complex expression patterns.
Distinguishing lncRNAs from protein-coding transcripts requires sophisticated filtering methods.

Purpose of the Study:

To develop an automated bioinformatics pipeline, LncRAnalyzer, for accurate lncRNA identification across 60 species.
To enhance lncRNA prediction by minimizing the inclusion of protein-coding or partially protein-coding transcripts.
To provide a comprehensive tool for analyzing lncRNA origins, including those from Transposable Elements (TEs) in plants.

Main Methods:

Developed LncRAnalyzer, an automated pipeline utilizing retrained models for 60 species.
Employed eight distinct approaches within the workflow to refine lncRNA identification.
Performed 10-fold cross-validation using sorghum RNA-Seq data and known lncRNA/CDS sequences.
Benchmarked LncRAnalyzer against LncPipe, LncEvo, lncRNA-Annotation, and Plant-LncPipe.

Main Results:

LncRAnalyzer demonstrated superior performance compared to standard models and other approaches in sorghum validation.
The pipeline effectively reduces the identification of non-protein-coding transcripts (NPCTs).
Benchmarking confirmed LncRAnalyzer as more comprehensive, user-friendly, and accurate than existing pipelines.
The workflow successfully identified lncRNA origins from various plant Transposable Elements (TEs).

Conclusions:

LncRAnalyzer offers a robust and accurate solution for lncRNA identification in diverse species.
The pipeline simplifies the complex process of lncRNA annotation and analysis.
LncRAnalyzer is a valuable tool for plant genomics research, particularly for studying TE-derived lncRNAs.