FADU: a Quantification Tool for Prokaryotic Transcriptomic Analyses.

Area of Science:

• Computational Biology
• Genomics
• Bioinformatics

Background:

• RNA sequencing (RNA-Seq) quantification tools are often optimized for human data with well-annotated full-length transcripts.
• Prokaryotic RNA-Seq analysis faces challenges due to the lack of full-length transcript annotation and the presence of operons.
• Existing tools struggle with accurate gene quantification in prokaryotes because operons contain multiple genes on a single transcript, leading to ambiguous fragment assignments.

Purpose of the Study:

• To introduce FADU (Feature Aggregate Depth Utility), a novel quantification tool specifically designed for prokaryotic RNA-Seq analyses.
• To address the challenge of quantifying genes within operons in prokaryotic transcriptomics data.
• To improve the accuracy of gene abundance estimation in prokaryotic RNA-Seq studies.

Main Methods:

• FADU assigns partial count values proportionally to the length of RNA fragments overlapping target features (genes).
• Performance comparison of FADU against established tools (eXpress, featureCounts, HTSeq, kallisto, Salmon).
• Evaluation using paired-end read datasets from three prokaryotic organisms: *Ehrlichia chaffeensis*, *Escherichia coli*, and *Wolbachia* endosymbiont *w*Bm.

Main Results:

• FADU demonstrated superior accuracy in quantifying operonic genes across all tested prokaryotic datasets.
• The tool effectively derives proportional counts for multigene fragments within operons, resolving ambiguity.
• FADU minimizes errors associated with improperly assigning fragment counts from polycistronic transcripts.

Conclusions:

• FADU provides a more accurate method for gene quantification in prokaryotic RNA-Seq, particularly for operonic regions.
• The tool enhances the reliability of transcriptomics analyses in bacteria and other prokaryotic systems.
• FADU is available as an open-source tool to facilitate prokaryotic transcriptomics research.