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Updated: Aug 13, 2025
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Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
Published on: September 3, 2009
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Estimating Temporally Variable Selection Intensity from Ancient DNA Data
Zhangyi He1,2, Xiaoyang Dai3, Wenyang Lyu4
1Cancer Research UK Beatson Institute, Glasgow, United Kingdom.
Molecular Biology and Evolution
|January 20, 2023
Summary
Ancient DNA (aDNA) studies can now track genetic changes over time. A new Bayesian method improves the inference of selection by modeling DNA damage and fragmentation uncertainties.
Area of Science:
- Population Genetics
- Paleogenomics
- Bioinformatics
Background:
- Novel ancient DNA (aDNA) technologies provide temporally spaced genetic samples.
- These genetic time series enable direct assessment of allele frequency changes and inference of selection.
- Studying past selection is challenged by aDNA damage, fragmentation, low coverage, and small sample sizes.
Purpose of the Study:
- To introduce a novel Bayesian framework for inferring temporally variable selection.
- To enable modeling of sample uncertainties arising from aDNA damage and fragmentation.
- To reconstruct population allele frequency trajectories for better understanding of selection drivers.
Main Methods:
- Developed a Bayesian framework utilizing genotype likelihoods instead of allele frequencies.
- Modeled uncertainties associated with damaged and fragmented aDNA molecules.
- Applied the framework to ancient horse coat coloration loci.
Main Results:
- The novel Bayesian framework effectively models aDNA uncertainties.
- Reconstruction of allele frequency trajectories provides insights into selection drivers.
- Incorporating sample uncertainties significantly improves the inference of selection.
Conclusions:
- The developed Bayesian framework overcomes key challenges in aDNA-based selection inference.
- This approach enhances the power to study past selection events, including domestication.
- The method offers a robust tool for analyzing genetic time series from ancient populations.
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