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Related Experiment Videos

Evolution of simple sequence repeats

G I Bell1

  • 1Theoretical Biology and Biophysics MS K710, Los Alamos National Laboratory, NM 87545, USA.

Computers & Chemistry
|March 1, 1996
PubMed
Summary
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Simple Sequence Repeats (SSRs) length distributions can be explained by unbiased random walk models. These models, including the Birth and Death Model and Random Walk Model, accurately represent SSR abundance and length variations in eukaryote DNA.

Area of Science:

  • Genetics
  • Bioinformatics
  • Population Genetics

Background:

  • Simple Sequence Repeats (SSRs) are highly polymorphic DNA regions in eukaryotes.
  • SSRs exhibit frequent length mutations, typically involving the gain or loss of a single repeat unit.
  • Understanding the mechanisms driving SSR length distributions is crucial for genetic studies.

Purpose of the Study:

  • To investigate whether unbiased random walk models can explain the observed abundances and length distributions of SSRs.
  • To compare two specific random walk models: the Birth and Death Model (BDM) and the Random Walk Model (RWM).

Main Methods:

  • Developed two unbiased random walk models: a continuous-time BDM and a discrete-time RWM.
  • Incorporated parameters for source rate (S) and termination time (T) reflecting mutation and selection processes.

Related Experiment Videos

  • Analyzed expected repeat numbers (N(k)) for infinite and finite termination times.
  • Compared model predictions with empirical data from GT.AC repeats in human DNA.
  • Main Results:

    • Both BDM and RWM provide reasonable fits to SSR length distributions when averaged over multiple loci.
    • The models accurately represent both the absolute number of loci and their length distributions.
    • Founder effects are significant for individual loci, making averaged data more suitable for model comparison.
    • For GT.AC repeats in humans, both models fit well with an initial repeat length (n0) of two units.

    Conclusions:

    • Unbiased random walk models, particularly when considering averaged data, can effectively explain SSR length distributions.
    • The BDM and RWM provide a theoretical framework for understanding SSR evolution and polymorphism.
    • The findings have implications for SSR marker selection and analysis in genetic research.