Understanding the full range of RNA molecules produced by a gene is essential for grasping how cells function, yet many analyses still overlook this complexity. Researchers from the Federal University of Minas Gerais, researchers introduce Isoformic, a new R based workflow that helps scientists see beyond gene level summaries and explore transcript level information hidden inside short read RNA sequencing data. This is important because most mammalian genes generate multiple transcript versions, each with its own potential biological role.

Isoformic helps researchers detect changes that occur at the transcript level, visualize exon and intron structures, and understand how different transcript types influence biological pathways. It is designed to address common challenges in transcript analysis such as low accuracy and inconsistent annotations. The authors validated Isoformic using datasets from studies of preeclampsia, SARS CoV 2 infection, and mouse anxiety models. Across these examples, Isoformic uncovered transcript variants that may help explain observable traits or disease related outcomes.

Because Isoformic is compatible with the widely used GENCODE transcriptome, it can be integrated into many existing workflows. By offering clearer insight into alternative transcription events, it gives researchers a deeper understanding of gene regulation and enriches the interpretation of RNA sequencing experiments.

Availability – https://github.com/luciorq/isoformic