gdtools_mutations

gdtools_mutations predicts mutations by analyzing evidence entries in General Data (GD) files to identify structural variations such as chromosomal rearrangements and mobile genetic element insertions in haploid microbial genomes.

Key Features:

• Structural Variation Prediction: Predicts large-scale genomic rearrangements arising from recombination events involving mobile genetic elements or repetitive sequences in haploid microbial genomes.
• Integration with breseq Pipeline: Operates as part of the breseq pipeline and leverages split-read alignments and matches to repeat sequences to detect new sequence junctions in clonal samples.
• Statistical Model for Read Coverage: Uses a statistical model of read coverage evenness to distinguish true mutations from false positives, supporting reliable calls at modest read-depths (>40-fold).
• Biologically Relevant Mutation Descriptions: Combines predictions of new sequence junctions and deleted chromosomal regions to generate descriptions of mutations and their impacts on genes.
• Application in Microbial Research: Targets analyses in microbial epidemiology, experimental evolution, synthetic biology, and genetics to uncover mutations between closely related strains with available reference genomes.

Scientific Applications:

• Microbial Epidemiology: Identify structural variants to track the spread of pathogenic traits in microbial populations.
• Experimental Evolution: Characterize spontaneous mutations that drive evolutionary changes in microbes such as Escherichia coli.
• Synthetic Biology and Genetics: Reveal unintended genomic changes in genetically modified organisms to inform design and analysis.

Methodology:

Analyzes DNA resequencing evidence in GD files; uses split-read alignments to detect new sequence junctions including those involving repeat sequences; matches repeats and combines junction and deleted-region predictions; and applies a statistical model based on read coverage evenness to validate mutation calls.