Discovery and characterization of new transcripts from RNA-seq data in mouse CD4(+) T cells

Area of Science:

• Transcriptomics
• Immunology
• Bioinformatics

Background:

• RNA-sequencing (RNA-seq) is routinely used for transcriptome profiling and identifying splice variants.
• However, the discovery and validation of entirely new transcripts are underexplored areas.
• A significant portion of assembled transcripts from RNA-seq may represent novel, uncharacterized messages.

Purpose of the Study:

• To develop and apply a computational and experimental workflow for characterizing and validating novel transcripts.
• To identify and experimentally validate previously uncharacterized transcripts from mouse CD4(+) T cells.
• To investigate early gene expression changes following T cell receptor stimulation.

Main Methods:

• Preparation of two RNA-seq libraries from resting and T cell receptor-stimulated mouse CD4(+) T cells.
• Application of a novel computational/experimental workflow to analyze RNA-seq data.
• Experimental validation of identified novel transcripts.

Main Results:

• Approximately 5% of assembled transcripts were unknown to Ensembl, robustly expressed but lacking evolutionary conservation.
• The workflow successfully characterized and validated 23 mouse transcripts uncharacterized by Ensembl.
• Seven of these validated transcripts are not supported by any existing database, suggesting they are likely new messages.
• Rapid upregulation of regulatory molecules was observed within 4 hours of T cell receptor stimulation.

Conclusions:

• The developed workflow is effective for identifying and validating novel transcripts from RNA-seq data.
• The study identified likely novel transcripts, expanding the known mouse transcriptome.
• Early CD4(+) T cell activation involves rapid changes in regulatory molecule expression, warranting further investigation.