# Accurate detection of somatic single-nucleotide variants from bulk RNA-seq data using RNA-MosaicHunter

**Authors:** August Yue Huang, Yuchen Cheng, Jayoung Ku, Boxun Zhao, Junseok Park, Dachan Kim, Jaejoon Choi, Eunjung Alice Lee

PMC · DOI: 10.1093/nar/gkaf1450 · Nucleic Acids Research · 2026-01-08

## TL;DR

RNA-MosaicHunter is a new tool that accurately detects somatic mutations in RNA-seq data, revealing their role in aging and diseases like Alzheimer's.

## Contribution

RNA-MosaicHunter introduces a novel method for detecting somatic single-nucleotide variants from bulk RNA-seq data, particularly in non-cancer contexts.

## Key findings

- RNA-MosaicHunter achieved high precision (94.7% in TCGA and 99.3% in a cell-line mixture) in detecting somatic variants.
- The tool revealed a higher burden of somatic single-nucleotide variants in Alzheimer’s disease brain samples compared to controls.
- RNA-MosaicHunter outperformed existing methods in capturing mutation patterns linked to normal aging in GTEx RNA-seq data.

## Abstract

Somatic variants are increasingly recognized as contributors to diverse non-cancer, developmental, and aging-related disorders. However, most tools for detecting somatic single-nucleotide variants (sSNVs) were designed for DNA sequencing and primarily tailored to cancer datasets, leaving a critical gap in harnessing the rich potential of RNA-seq for sSNV identification, particularly in non-cancer tissues with low mutation rates. Here, we introduce RNA-MosaicHunter, a novel bioinformatic tool for accurate sSNV detection from bulk RNA-seq. In two benchmarking datasets, it demonstrated high precision (94.7% in TCGA and 99.3% in a cell-line mixture) with sensitivities of 53.4% and 38.9%, respectively, in the default mode that maximizes precision. We then applied RNA-MosaicHunter to profile 827 RNA-seq samples in three tissue types from the Genotype Tissue Expression project (GTEx), where it outperformed previous methods in capturing mutational characteristics associated with normal aging. We further utilized RNA-MosaicHunter to analyze RNA-seq data from 382 Alzheimer’s disease (AD) brain samples and 480 age-matched controls and revealed a significantly higher burden of sSNVs in AD cerebral cortex, suggesting the potential contribution of sSNVs to AD pathogenesis. RNA-MosaicHunter enables accurate profiling and characterization of sSNVs from RNA-seq data, advancing the understanding of the role of somatic variants across diverse tissues and diseases.

Graphical Abstract

## Linked entities

- **Diseases:** Alzheimer’s disease (MONDO:0004975)

## Full-text entities

- **Diseases:** AD (MESH:D000544), cancer (MESH:D009369)

## Full text

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## Figures

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## References

86 references — full list in the complete paper: https://tomesphere.com/paper/PMC12781890/full.md

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Source: https://tomesphere.com/paper/PMC12781890