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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
Published on: December 27, 2010
An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence
Aaron J Stern1, Peter R Wilton2, Rasmus Nielsen2,3
1Graduate Group in Computation Biology, University of California, Berkeley, Berkeley, California, United States of America.
A new method, CLUES, enhances natural selection detection from DNA data by approximating the full likelihood function. This approach offers improved power and reliable allele frequency trajectory inferences compared to existing methods.
Area of Science:
- Evolutionary Biology
- Population Genetics
- Bioinformatics
Background:
- Current methods for detecting natural selection from DNA sequence data often rely on summary statistics or composite likelihoods, limiting their use of available information.
- These limitations hinder accurate detection and characterization of selection events.
Purpose of the Study:
- To introduce a novel importance sampling approach, CLUES (Coordinated Likelihood Using Importance Sampling), for approximating the full likelihood function of the selection coefficient.
- To enhance the detection of natural selection, estimation of selection coefficients, and inference of allele frequency trajectories from DNA sequence data.
Main Methods:
- CLUES treats the ancestral recombination graph (ARG) as a latent variable, integrating it out using Markov Chain Monte Carlo (MCMC) methods.
- The method approximates the full likelihood function for the selection coefficient, enabling a more comprehensive analysis of DNA sequence data.
Main Results:
- Extensive simulations demonstrate that CLUES uniformly improves power for detecting selection compared to popular methods like nSL and SDS.
- CLUES provides reliable inferences of allele frequency trajectories under various conditions and can detect recent changes in selection strength.
- Application to human populations revealed insights into lactase persistence (MCM6), EDAR SNP age in Han Chinese, and selection on pigmentation genes (ASIP, KITLG, TYR, OCA2/HERC2).
Conclusions:
- CLUES represents a significant advancement in detecting natural selection and inferring evolutionary histories from DNA sequence data.
- The method's ability to utilize the full information in DNA sequences and its improved performance over existing techniques make it a valuable tool for population geneticists.
- Analysis of specific human genes highlights the method's utility in uncovering detailed patterns of recent and ancient selection.
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