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Related Experiment Videos

Population genetics of microbial pathogens estimated from multilocus sequence typing (MLST) data.

Marcos Pérez-Losada1, Emily B Browne, Aaron Madsen

  • 1Department of Integrative Biology, Brigham Young University, Provo, UT 84602, USA. mp323@email.byu.edu

Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases
|March 1, 2006
PubMed
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Population genetics in microbes reveals extensive variation in recombination (rho) and mutation (Theta) rates, with both factors contributing equally to genetic diversity. Molecular adaptation was significant in many pathogens, with some showing consistent selection across species.

Area of Science:

  • Microbial population genetics
  • Evolutionary biology
  • Bioinformatics

Background:

  • Estimating population recombination (rho), mutation (Theta), and adaptive selection is crucial for understanding microbial evolution.
  • Explicit statistical frameworks, or evolutionary models, are used to infer these parameters from gene sequences.

Purpose of the Study:

  • To estimate population recombination (rho) and mutation (Theta) rates using a coalescent approach.
  • To detect adaptive selection using heterogeneous codon-based and amino acid property models.
  • To analyze these parameters across 91 housekeeping gene regions in 1 fungal and 16 bacterial pathogens.

Main Methods:

  • Coalescent-based estimation of population recombination (rho) and mutation (Theta) parameters.
  • Application of heterogeneous codon-based and amino acid property models to infer adaptive selection.

Related Experiment Videos

  • Analysis of microbial sequences from Multi-Locus Sequence Typing (MLST) databases.

    • Main Results:

    • Population parameters (rho, Theta, selection) showed extensive variation across species and loci, without apparent correlation.
    • Estimated recombination rates generally agreed with previous studies; the rho/Theta ratio indicated similar contributions to allele emergence.
    • Recurrent mutation increased Theta estimates by up to 39% under finite-site models compared to infinite-site models.
    • Significant molecular adaptation was detected in 28 loci across 13 pathogens, with three loci showing concordant selection patterns in multiple species.

    Conclusions:

    • Microbial population genetics parameters are highly variable and contribute jointly to genetic diversity.
    • Molecular adaptation is a significant evolutionary force in many microbial pathogens, sometimes acting consistently across related species.
    • The choice of mutation model (finite vs. infinite sites) can substantially impact Theta estimates.