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Analytical framework for identifying and differentiating recent hitchhiking and severe bottleneck effects from
1Theoretical Biology and Biophysics and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America. sargsyan@lanl.gov
Plos One
|June 5, 2012
Summary
This study introduces a new analytical framework to identify recent genetic homogenization events at multiple DNA loci. The method successfully differentiates these events in human and HIV DNA sequences, supporting evolutionary hypotheses.
Area of Science:
- Population Genetics
- Evolutionary Biology
- Genomics
Background:
- Hitchhiking and bottleneck effects homogenize genetic diversity, making event identification difficult.
- Distinguishing these homogenization signatures from DNA sequence data at single loci is challenging.
Purpose of the Study:
- Develop an analytical framework to identify and differentiate recent homogenization events at multiple neutral loci in low recombination regions.
- Model the dynamics of genetic diversity following a homogenization event using established population genetics models.
Main Methods:
- Derived analytical expressions for the distribution, mean, and variance of polymorphic sites under homogenization.
- Developed three likelihood-ratio based tests for identifying and differentiating homogenization events.
- Applied the framework to human and HIV DNA sequence data.
Main Results:
- The framework can identify recent homogenization events in human DNA sequences, particularly with effective population sizes >= 50,000, aligning with the 'Out of Africa' hypothesis.
- Applied to HIV-1 sequences, the framework provided estimates for seroconversion times that showed significant discrepancies with traditional methods.
Conclusions:
- The developed framework provides a robust method for detecting and differentiating recent homogenization events across multiple genetic loci.
- The findings have implications for understanding human population history and the evolutionary dynamics of viral infections like HIV.
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