Quantification of single cell-type-specific alternative transcript initiation.

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Cells utilize distinct Transcriptional Start Regions (TSRs) to produce various gene isoforms, regulated by transcription factors for tissue-specific expression.
• The selective activation mechanisms of different TSRs across various tissues and cell types are not well understood.

Purpose of the Study:

• To introduce TSRdetector, a novel bioinformatic method for detecting significant alterations in gene TSR usage across different conditions.
• To enable the analysis of differential TSR usage in both single-cell (scRNA-seq) and bulk RNA sequencing (bulk-RNA-seq) data.

Main Methods:

• TSRdetector processes RNA-seq data to identify dominant TSRs and compute differential usage between conditions.
• The method was applied to human kidney snRNA-seq, mouse B-cell differentiation scRNA-seq, and human ESC bulk-RNA-seq datasets.

Main Results:

• TSRdetector identified significant TSR usage alterations in all tested datasets, correlating with epigenetic landscape changes.
• Alterations in TSR usage can modify transcript isoforms and protein products, sometimes without affecting overall gene expression.
• A substantial portion of observed TSR usage changes occurred independently of global gene expression levels, highlighting novel regulatory mechanisms.

Conclusions:

• TSRdetector is a user-friendly package for analyzing differential TSR usage from scRNA-seq and bulk-RNA-seq data.
• The tool facilitates the exploration of alternative transcription initiation events at the single-cell level.
• Findings reveal unique transcriptional regulations independent of expression levels, impacting isoform diversity.