TSSpredator

TSSpredator predicts transcription start sites (TSS) from RNA-seq data to map and compare genome-wide promoters across strains and conditions.

Key Features:

• Automated TSS detection and classification: Detects and classifies transcription start sites genome-wide from RNA-seq signal.
• Input format support: Processes RNA-seq data provided as wiggle files.
• Comparative SuperGenome annotation: Integrates a SuperGenome approach that aligns RNA-seq data from multiple strains into a unified coordinate system derived from whole-genome alignments.
• dRNA-seq support for promoter mapping: Utilizes differential RNA-seq (dRNA-seq) data to generate promoter maps and distinguish primary TSS.
• Cross-organism applicability: Applied to Campylobacter jejuni and adaptable for comparative analysis in other prokaryotic and eukaryotic contexts.

Scientific Applications:

• Transcriptome organization: Provides genome-wide promoter maps to investigate transcriptome architecture.
• Strain-specific TSS discovery: Identifies conserved and strain-specific transcriptional start sites across isolates.
• Promoter polymorphism analysis: Reveals single-nucleotide polymorphisms (SNPs) within promoter regions that contribute to differential transcriptional outputs.
• sRNA repertoire characterization: Detects unique small RNA (sRNA) repertoires specific to certain strains.
• CRISPR-related discovery: Aided the identification of a minimal CRISPR system characterized by reliance on host factors and trans-encoded sRNAs for crRNA maturation.

Methodology:

Processes RNA-seq wiggle files and employs differential RNA-seq (dRNA-seq) to detect and classify TSS, integrating comparative TSS annotation via a SuperGenome approach that maps RNA-seq data from multiple strains into a common coordinate system derived from whole-genome alignments; implemented in Java.