Population Genomics of Selective Sweeps
Summary
Population genomics of selective sweeps examines how beneficial mutations rise in frequency within populations and leave distinctive signatures in genome-wide data. When a favourable allele increases rapidly to high frequency, linked neutral variation is reduced or distorted, creating patterns identifiable through statistical and computational tools. Research combines dense polymorphism surveys, haplotype structure analysis and demographic modelling to distinguish true selection events from background processes such as population bottlenecks or migration. Advances in high-throughput sequencing have expanded analyses from model organisms to wildlife and crop species, illuminating adaptation to pathogens, climate, diet and chemical stressors. Machine learning methods now augment classical summary-statistic approaches, offering greater sensitivity to subtle, soft or incomplete sweeps and enabling detection in unphased data. Integrating experimental and ecological contexts enhances understanding of the molecular basis of adaptation, with applications in conservation genetics, agriculture and human health.
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Population Genomics of Selective Sweeps publication trend
The graph below shows the total number of articles in population genomics of selective sweeps across all publications each year (not limited to Nature Index journals).
Technical terms
Selective sweep: A process by which a beneficial mutation rapidly rises to high frequency, reducing genetic variation at linked sites.
Hard selective sweep: A sweep originating from a single new mutation that goes to fixation, leaving a strong, narrow signature.
Soft selective sweep: A sweep arising from multiple adaptive haplotypes either from standing variation or recurrent mutation, producing a broader signature.
Haplotype phasing: The inference of which alleles co-occur on the same chromosome copy, essential for haplotype-based statistics.
Standing genetic variation: Pre-existing alleles in a population before an environmental change, serving as a substrate for adaptation.
Linkage disequilibrium: The non-random association of alleles at different loci, exploited to detect selection footprints.
References
- A Novel Approach Utilizing Domain Adversarial Neural Networks for the Detection and Classification of Selective Sweeps. Advanced Science (2024).
- selscan 2.0: scanning for sweeps in unphased data. Bioinformatics (2024).
- Versatile Detection of Diverse Selective Sweeps with Flex-Sweep. Molecular Biology and Evolution (2023).
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