tatajuba

Tatajuba identifies and classifies homopolymeric tracts within sequencing reads to quantify length variation that can drive phase variation and alter bacterial gene expression.

Key Features:

• Automated identification: Detects potential homopolymeric tracts within sequencing data, addressing artefacts from repetitive sequences and decreased base diversity.
• Phenotypic impact analysis: Assesses putative effects of tract length variation on phenotype by linking tract variation to gene expression changes associated with phase variation.
• Polymorphism detection: Highlights polymorphic homopolymeric tracts across samples to reveal genetic variability relevant to bacterial adaptation.
• Scalability: Performs exhaustive exploration of homopolymeric features across large sequencing datasets.

Scientific Applications:

• Analysis in Campylobacter and Bordetella: Applied to sequencing data from Campylobacter jejuni and three Bordetella species to confirm known associations between homopolymer tract variation and phenotypic impact and to identify additional candidate variable tracts.

Methodology:

Implemented in C for efficient processing of large sequencing datasets.