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Linc2function: A Comprehensive Pipeline and Webserver for Long Non-Coding RNA (lncRNA) Identification and Functional
Yashpal Ramakrishnaiah1,2, Adam P Morris3, Jasbir Dhaliwal2
1Central Clinical School, Monash University, Melbourne, VIC 3000, Australia.
Epigenomes
|September 27, 2023
Summary
This study introduces a new pipeline for annotating long non-coding RNAs (lncRNAs) at the transcript level. It integrates structural and interaction data for comprehensive functional analysis, aiding disease research.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Long non-coding RNAs (lncRNAs) are crucial regulators of cellular functions and potential disease biomarkers, yet their specific roles and transcript isoforms are largely uncharacterized.
- Current methods for lncRNA analysis primarily focus on gene-level investigations and sequence-based discrimination, limiting comprehensive functional annotation and cross-species applicability.
Purpose of the Study:
- To develop and validate a novel computational pipeline for high-throughput, isoform-level annotation of long non-coding RNAs (lncRNAs).
- To enhance the understanding of lncRNA mechanisms in pathological processes by integrating secondary structure and interactome information.
- To address challenges in annotating lncRNAs for new species and improve the generalizability of in silico prediction methods.
Main Methods:
- Developed a computational pipeline integrating transcript sequence, secondary structure, and interactome information for lncRNA annotation.
- Employed transcript-level analysis to discriminate lncRNAs from coding RNAs and predict functional motifs and target biomolecules.
- Validated the pipeline's effectiveness through comprehensive annotation of lncRNAs associated with two specific disease groups.
Main Results:
- The proposed pipeline enables comprehensive functional annotation of lncRNAs by incorporating diverse data types beyond primary sequence.
- Successfully demonstrated the pipeline's capability in annotating lncRNAs related to specific disease cohorts.
- The developed pipeline overcomes limitations of reference-based and sequence-only methods, improving accuracy and generalizability.
Conclusions:
- Integrating transcript sequence, secondary structure, and interactome data is essential for accurate and comprehensive lncRNA functional annotation.
- The developed pipeline provides a robust tool for isoform-level lncRNA identification and annotation, advancing our understanding of lncRNA roles in disease.
- The pipeline's open-source availability and web server interface promote accessibility for researchers and non-technical users alike.
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