ClonalOrigin

ClonalOrigin infers and reconstructs recombination events and their ancestral origins in bacterial genomes to elucidate evolutionary history.

Key Features:

• Reconstruction of recombination events: Uses a mathematical model that represents the donor and recipient of each DNA import as ancestors within the sampled genomes, simplifying coalescent with gene conversion models.
• Comparative genomic analysis: Detects DNA imports that replace homologous segments by analyzing bacterial genome sequence alignments.
• Monte Carlo Markov Chain inference: Performs inference under its model using a Monte Carlo Markov Chain algorithm on sequence data alignments, implemented with parallelization to handle whole-genome alignments.
• Simulation validation and parameter estimation: Demonstrated via simulations to identify individual recombination events and to estimate global recombination rate parameters accurately.

Scientific Applications:

• Evolutionary dynamics of bacterial populations: Enables analysis of the frequency and distribution of recombination events to study bacterial evolutionary dynamics.
• Study of closely related organisms: Facilitates detection of elevated recombination rates in closely related bacterial strains.
• Localization of recombination-rich regions: Identifies broad genomic regions with elevated levels of recombination.
• Microbial evolution and comparative genomics: Applies to genomic datasets from bacteria and archaea to investigate microbial evolution, genetic diversity, and evolutionary history.

Methodology:

Computational methods include a mathematical model framing donor and recipient as ancestral lineages within the sample (simplifying coalescent with gene conversion), MCMC inference on sequence data alignments with parallelization for whole-genome alignments, and simulation-based validation of event detection and recombination rate estimation.