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Isoformic: a workflow for transcript-level RNA-seq interpretation.

Izabela Mamede^1,2, Lucio R Queiroz^1,3, Carlos Mata-Machado¹

¹Laboratory of Genetics Biochemistry, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.

NAR Genomics and Bioinformatics

|December 5, 2025

Summary

This summary is machine-generated.

Isoformic is a new R pipeline for analyzing RNA sequencing data at the transcript level. It helps uncover complex gene expression patterns missed by traditional gene-level analysis, revealing biologically relevant transcript variants.

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Transcriptome analysis is crucial in modern biology but often overlooks alternative splicing and transcription initiation/termination.
Most mammalian genes (over 95%) produce multiple transcripts, yet short-read RNA sequencing (RNA-seq) analysis struggles with transcript-level interpretation.
Existing tools lack accuracy, consistency with annotations, and efficient downstream biological interpretation capabilities.

Purpose of the Study:

To introduce Isoformic, a customizable R pipeline for transcript-level analysis of short-read RNA-seq data.
To enable detection of transcript-level changes, visualization of exon-intron structures, and functional enrichment analysis stratified by transcript type.
To enhance the resolution of RNA-seq studies and uncover regulatory roles of alternative transcription events.

Main Methods:

Development of a customizable R pipeline named Isoformic.
Processing of differential expression results to identify transcript-level alterations.
Validation using diverse datasets including preeclampsia, SARS-CoV-2 infection, and murine anxiety models.
Compatibility with the GENCODE reference transcriptome.

Main Results:

Isoformic successfully detects genes with transcript-level changes.
The pipeline visualizes exon-intron structures and performs transcript-type-stratified functional enrichment.
Validated studies revealed biologically relevant transcript variants and their potential phenotypic associations.
Isoformic enhances the interpretability of RNA-seq data.

Conclusions:

Isoformic provides a robust solution for transcript-level analysis of short-read RNA-seq data.
The pipeline overcomes limitations of existing tools, offering improved accuracy and biological insights.
Isoformic empowers researchers to explore the functional significance of alternative transcription events.