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A likelihood method for the detection of selection and recombination using nucleotide sequences

N C Grassly1, E C Holmes

  • 1Wellcome Trust Centre for the Epidemiology of Infectious Disease, Department of Zoology, University of Oxford, U.K. nicholas.grassly@zoo.ox.ac.uk

Molecular Biology and Evolution
|March 1, 1997
PubMed
Summary

This study introduces a statistical method to detect varying evolutionary forces across DNA sequences. It identifies regions with different evolutionary histories, revealing insights into selection and recombination.

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Area of Science:

  • Evolutionary biology
  • Bioinformatics
  • Genomics

Background:

  • Nucleotide sequences can experience diverse evolutionary pressures.
  • Recombination and selection lead to varied evolutionary histories and rates within sequences.

Purpose of the Study:

  • To develop a statistical method for detecting evolutionary heterogeneity in nucleotide sequences.
  • To identify regions deviating from a single phylogenetic and substitution model.

Main Methods:

  • A likelihood-based statistical approach was employed.
  • The method identifies anomalous sequence regions inconsistent with a uniform evolutionary process.

Main Results:

  • Simulations validated the method's effectiveness.

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  • Application to primate, HIV-1, and Neisseria DNA sequences revealed significant findings.
  • Anomalous regions in HIV-1 suggested immune selection, while Neisseria sequences indicated recombination.

    • Conclusions:

    • The developed method successfully detects evolutionary heterogeneity in DNA.
    • Reanalysis of identified anomalous regions provides insights into biological processes like selection and recombination.
    • A computational tool is available to implement this detection method.