The BulkECexplorer compiles endothelial bulk transcriptomes to predict functional versus leaky transcription

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Transcriptomic data from RNA sequencing (RNA-seq) is crucial for understanding cell type molecular activity.
• Technical limitations in RNA-seq, like low read depth or gene dropout, can lead to undetected functional genes.
• Conversely, low-expressed messenger RNAs (mRNAs) may be mistakenly identified as biologically irrelevant products of leaky transcription.

Purpose of the Study:

• To develop a method for more accurate representation of a cell type's functional transcriptome.
• To predict whether detected transcripts in bulk RNA-seq datasets are products of active or leaky transcription.
• To present the BulkECexplorer compendium for vascular endothelial cell subtypes.

Main Methods:

• Compilation of 240 bulk RNA-seq datasets from five vascular endothelial cell subtypes into a compendium.
• Application of established classification models to predict the nature of detected transcripts.
• Development of the BulkECexplorer tool for transcript analysis.

Main Results:

• The BulkECexplorer compendium provides transcript counts for genes of interest in endothelial cells.
• It predicts whether detected transcripts are likely products of active gene expression or leaky transcription.
• The resource offers a validated approach for transcriptomic data analysis in specific cell types.

Conclusions:

• The BulkECexplorer compendium enhances the accurate understanding of endothelial cell transcriptomes.
• This approach provides a reliable method to differentiate functional gene expression from transcriptional noise.
• The developed methodology serves as a blueprint for creating similar tools for other cell types.