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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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Related Experiment Video

Updated: Feb 7, 2026

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

RNA variant identification discrepancy among splice-aware alignment algorithms.

Ji Hyung Hong¹, Yoon Ho Ko^1,2, Keunsoo Kang³

¹Division of Oncology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

|August 3, 2018

Summary

This summary is machine-generated.

Evaluating RNA sequencing alignment algorithms revealed that splice-aware aligners identified few common RNA editing sites. RNA quality and read mapping at splice junctions significantly impact variant detection, necessitating careful consideration in RNA variant analysis.

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Published on: October 9, 2016

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Next-generation sequencing (NGS) provides molecular maps, including transcriptomes via RNA sequencing (RNA-seq).
RNA-seq quantifies gene expression but also identifies RNA variants, though RNA's dynamic nature requires careful analysis.
Splice-aware alignment is crucial for accurate RNA variant detection.

Purpose of the Study:

To evaluate the performance of popular splice-aware alignment algorithms for RNA variant-calling analysis.
To assess the impact of mapped reads on splice junctions and RNA quality on variant detection.
To identify potential RNA editing sites (pRESs) unique to breast cancer tissue.

Main Methods:

Performed RNA-seq on invasive ductal carcinoma and adjacent normal breast tissue samples.
Evaluated splice-aware aligners: HISAT2, STAR, STAR (two-pass mode), Subread, and Subjunc.
Analyzed mapped reads on splice junctions and assessed RNA quality's effect on variant calling.

Main Results:

Less than 2% of potential RNA editing sites (pRESs) were common across all evaluated alignment algorithms.
Mapped reads on splice junctions were a primary cause for discrepancies in pRES identification.
RNA quality significantly influenced the outcome of RNA variant analysis.
BDH1, CCDC137, and TBC1D10A transcripts showed unique non-synonymous RNA variants in cancer tissue.

Conclusions:

Researchers must consider bioinformatic (aligner choice, read mapping) and experimental (RNA quality) factors in RNA variant analysis.
The choice of splice-aware aligner impacts RNA variant detection, with significant differences observed.
Unique RNA variants in specific genes (BDH1, CCDC137, TBC1D10A) in breast cancer warrant further clinical validation.