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New methods for inferring population dynamics from microbial sequences.

Marcos Pérez-Losada1, Megan L Porter, Loubna Tazi

  • 1Department of Integrative Biology, 157 Widtsoe Building, Brigham Young University, Provo, UT 84602, USA. mp323@byu.edu

Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases
|April 22, 2006
PubMed
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DNA sequence data is increasingly used for microbial population genetics and phylogenetics. This review covers essential analytical methods for evolutionary and demographic studies using microbial DNA and amino acid sequences.

Area of Science:

  • Microbiology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • High-throughput sequencing and automation have made DNA data accessible for microbial population studies.
  • Sequence data is amenable to evolutionary analysis, driving its use in microbial genetics.

Purpose of the Study:

  • To review commonly used, improved, and new methodologies for microbial sequence data analysis.
  • To highlight useful approaches for inferring population dynamics and evolutionary relationships.

Main Methods:

  • Sequence alignment and model selection.
  • Bifurcating and network phylogenetic approaches.
  • Methods for demographic history, population structure, and parameter estimation (recombination, diversity, growth, selection).

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Main Results:

  • Discussion of various analytical techniques applicable to nucleotide and amino acid sequences.
  • Focus on methods particularly useful for microbial sequence analysis.

Conclusions:

  • Sequence-based methods are crucial for understanding microbial evolution and population dynamics.
  • The review provides a guide to essential analytical tools for microbial sequence data.