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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
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Local adaptation and archaic introgression shape global diversity at human structural variant loci
Stephanie M Yan1, Rachel M Sherman2, Dylan J Taylor1
1Department of Biology, Johns Hopkins University, Baltimore, Baltimore, United States.
Elife
|September 16, 2021
Summary
Large genomic structural variants (SVs) were analyzed in human evolution using advanced sequencing methods. A Neanderthal-introgressed immune gene variant shows local adaptation in Southeast Asian populations.
Area of Science:
- Genomics
- Human Evolution
- Population Genetics
Background:
- Large genomic insertions and deletions (structural variants or SVs) are key sources of functional variation.
- Short-read sequencing technologies present challenges in resolving these SVs, limiting our understanding of their role in human evolution.
Purpose of the Study:
- To develop and apply a graph-based method for genotyping SVs discovered by long-read sequencing using short-read data.
- To identify SVs under local adaptation in diverse human populations.
Main Methods:
- Genotyping of long-read-discovered SVs in short-read data from diverse human genomes using a graph-based approach.
- Application of an admixture-aware method to detect SVs with extreme frequency differentiation, indicative of local adaptation.
Main Results:
- Identified 220 SVs showing patterns of local adaptation.
- Discovered two top variants at the immunoglobulin heavy chain locus, associated with a haplotype near fixation in Southeast Asian populations.
- Found evidence that this adaptive haplotype originated from Neanderthal gene flow, highlighting immune genes as targets of adaptive introgression.
Conclusions:
- Recent technical advances enable the resolution of SVs and the study of their evolutionary impact.
- Immune-related genes were likely targets of adaptive introgression from Neanderthals.
- The study resolves previously obscured signatures of key evolutionary events in challenging genomic regions.
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