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Alternative RNA Splicing

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Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Related Experiment Video

Updated: Jul 28, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Alternative splicing analysis benchmark with DICAST.

Amit Fenn^1,2, Olga Tsoy², Tim Faro¹

¹Chair of Experimental Bioinformatics, Technical University of Munich, 85354 Freising, Germany.

NAR Genomics and Bioinformatics

|June 1, 2023

Summary

This summary is machine-generated.

This study benchmarks RNA-seq tools for alternative splicing event detection, finding STAR and HISAT2 offer the best performance. DICAST provides a framework for robust event detection using consensus approaches.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Alternative splicing significantly increases transcriptome and proteome diversity in biological systems.
Numerous computational tools exist for analyzing RNA-sequencing (RNA-seq) data, but benchmarks often overlook event detection.
Event detection tools offer granular insights into alternative splicing mechanisms, crucial for understanding health and disease.

Purpose of the Study:

To comprehensively benchmark splice-aware mapping and alternative splicing event detection tools.
To introduce DICAST, a framework for analyzing alternative splicing events.
To propose a standardized reporting format for alternative splicing analysis.

Main Methods:

Extensive benchmarking of eleven splice-aware mapping tools and eight event detection tools.
Utilized simulated RNA-seq data and whole blood RNA-seq datasets for evaluation.
Developed the DICAST framework integrating multiple analysis tools for a consensus approach.

Main Results:

STAR and HISAT2 showed the optimal balance between performance and computational runtime for mapping.
Performance varied significantly among event detection tools, with no single tool excelling universally.
The DICAST framework enables a consensus strategy for improved robustness in event detection.

Conclusions:

The choice of mapping tools impacts alternative splicing analysis; STAR and HISAT2 are recommended.
A consensus approach using multiple event detection tools is crucial for reliable results.
Standardized reporting is needed to unify formats and guide future development in alternative splicing analysis.