baerhunter: an R package for the discovery and analysis of expressed non-coding regions in bacterial RNA-seq data

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Standard bacterial transcriptomic analysis often overlooks crucial non-coding RNA elements like small RNAs, long antisense RNAs, and untranslated regions (UTRs).
• This oversight stems from the limitations of incomplete genome annotation files used in conventional bioinformatics pipelines.

Purpose of the Study:

• To introduce baerhunter, an automated method for discovering expressed non-coding RNAs and UTRs from RNA-seq data.
• To provide a tool that integrates the analysis of both coding and non-coding genomic features.

Main Methods:

• Development of baerhunter, a coverage-based method implemented in the R programming language.
• Utilizing RNA-seq reads mapped to a reference genome for identifying non-coding elements and UTRs.
• Integration of the core algorithm into a pipeline for comprehensive downstream analysis.

Main Results:

• Baerhunter automates the discovery of expressed non-coding RNAs and UTRs.
• The method demonstrates favorable performance compared to existing popular alternatives in initial tests with simulated and real data.
• The pipeline facilitates downstream analysis of both coding and non-coding genomic features.

Conclusions:

• Baerhunter offers a simple, extensible, and customizable solution for uncovering functional non-coding elements in bacterial transcriptomes.
• The tool addresses a critical gap in standard bioinformatics pipelines, enabling more complete genomic analysis.
• The R package is publicly available, promoting wider adoption and further development in the field.