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The spatial distribution of fixed mutations within genes coding for proteins.

R Holmquist, M Goodman, T Conroy

    Journal of Molecular Evolution
    |January 1, 1983
    PubMed
    Summary
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    The Poisson distribution inaccurately models base substitutions in protein-coding genes. New analysis reveals negative binomial and geometric densities better describe evolutionary patterns, necessitating revised estimates of genetic divergence.

    Area of Science:

    • Molecular Evolution
    • Bioinformatics
    • Genomics

    Background:

    • Accurate modeling of base substitutions is crucial for understanding gene evolution.
    • Previous studies often relied on the Poisson distribution to model these changes.
    • Extensive amino acid sequence data is now available for comparative analysis.

    Purpose of the Study:

    • To investigate the spatial distribution of base substitutions in protein-coding genes.
    • To evaluate the suitability of the Poisson density for modeling substitution patterns.
    • To identify more appropriate statistical models for evolutionary inference.

    Main Methods:

    • Analysis of extensive amino acid sequence data from five protein families: alpha crystallin A chain, myoglobin, alpha and beta hemoglobin, and cytochromes c.

    Related Experiment Videos

  • Statistical comparison of observed base substitution patterns against the Poisson density.
  • Fitting alternative statistical distributions, including the negative binomial and geometric densities, to the experimental data.

    • Main Results:

    • The Poisson density failed to approximate the observed base substitution patterns across all examined protein families.
    • For beta hemoglobin, the probability of observed results arising from a Poisson process was extremely low (10^-44).
    • The negative binomial density provided a reasonable fit, with the geometric density describing most of the data effectively.

    Conclusions:

    • The commonly used Poisson model is inadequate for describing base substitution distributions in protein-coding genes.
    • The negative binomial and geometric densities offer better statistical frameworks for evolutionary analysis.
    • Existing estimates of total base substitutions between genes require significant revision based on these findings.