ArticleMolecular biology and evolution2021
The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects.
Article in Molecular biology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.
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98 citing papers in PubMed.
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- Inferring the Relative Contributions of Evolutionary Processes Shaping X Chromosome Dynamics in the Common Marmoset (Callithrix jacchus) in the Presence of Twinning and Hematopoietic Chimerism.Genome biology and evolution · 2026Article
- Targeted chromosomal sequencing of wild bonobos identifies a genetically distinct subpopulation east of the Lomami river.Genome biology · 2026Article
- Evolution of quantitative traits with background selection.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- On the use of generative models for demographic inference in malaria vectors from genomic data.G3 (Bethesda, Md.) · 2026Article
- Neural posterior estimation for population genetics.Genetics · 2026Article
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- Inferring Patterns of Purifying, Positive, and Balancing Selection in the Coppery Titi Monkey (Plecturocebus cupreus) Utilizing a Well-Fit Evolutionary Baseline Model.Genome biology and evolution · 2026Article
- Insights into human adaptation from ancient DNA.Nature genetics · 2026Review
- Genome-wide SNP data reveal hidden hierarchical population structure and demographic history of endangered black-and-white snub-nosed monkeys (Rhinopithecus bieti).Molecular biology and evolution · 2026Article
- Inferring the Demographic History of Coppery Titi Monkeys (Plecturocebus cupreus) From High-Quality, Whole-Genome, Population-Level Data.American journal of primatology · 2026Article
- Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Deep learning reveals genomic regions introgressed between two recurrently hybridizing lynx species.Molecular biology and evolution · 2026Article
- Neural posterior estimation for population genetics.bioRxiv : the preprint server for biology · 2026Article
- ThebioRxiv : the preprint server for biology · 2026Article
- The distribution of fitness effects of new mutations in regulatory regions of thebioRxiv : the preprint server for biology · 2026Article
- Minor Allele Frequency Filtering Can Strongly Bias Uniqueness Estimates Within and Across Species.Ecology and evolution · 2026Article
38 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
Current procedures for inferring population history generally assume complete neutrality-that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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