CoChat
Sign Up
Cited by 12

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Unveiling recent and ongoing adaptive selection in human populations

Gao, Ziyue·2024·PLOS Biology
DOI 10.1371/journal.pbio.3002469PMC PMC10796035
Open this paper in CoChat — free account

Abstract

Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pbio.3002469

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 87

  1. BF Voight, 2006, A map of recent positive selection in the human genome, PLoS Biol, 4, e72, 10.1371/journal.pbio.0040072 · DOI
  2. H Mostafavi, 2017, Identifying genetic variants that affect viability in large cohorts, PLoS Biol, 15, e2002458, 10.1371/journal.pbio.2002458 · DOI
  3. YB Simons, 2018, A population genetic interpretation of GWAS findings for human quantitative traits, PLoS Biol, 16, e2002985, 10.1371/journal.pbio.2002985 · DOI
  4. F Ruzicka, 2022, Polygenic signals of sex differences in selection in humans from the UK Biobank, PLoS Biol, 20, e3001768, 10.1371/journal.pbio.3001768 · DOI
  5. CA Cassa, 2017, Estimating the selective effects of heterozygous protein-truncating variants from human exome data, Nat Genet, 49, 806, 10.1038/ng.3831 · DOI
  6. KJ Karczewski, 2020, The mutational constraint spectrum quantified from variation in 141,456 humans, Nature, 581, 434, 10.1038/s41586-020-2308-7 · DOI · Paper page
  7. EJ Gardner, 2022, Reduced reproductive success is associated with selective constraint on human genes, Nature, 603, 858, 10.1038/s41586-022-04549-9 · DOI · Paper page
  8. R Nielsen, 2007, Recent and ongoing selection in the human genome, Nat Rev Genet, 8, 857, 10.1038/nrg2187 · DOI
  9. M Hernandez, 2021, Scanning the human genome for “signatures” of positive selection: Transformative opportunities and ethical obligations, Evol Anthropol, 30, 113, 10.1002/evan.21893 · DOI
  10. S Fan, 2016, Going global by adapting local: A review of recent human adaptation, Science, 354, 54, 10.1126/science.aaf5098 · DOI
  11. P Pavlidis, 2010, Searching for footprints of positive selection in whole-genome SNP data from nonequilibrium populations, Genetics, 185, 907, 10.1534/genetics.110.116459 · DOI
  12. BM Peter, 2012, Distinguishing between selective sweeps from standing variation and from a de novo mutation, PLoS Genet, 8, e1003011, 10.1371/journal.pgen.1003011 · DOI · Paper page
  13. Y Field, 2016, Detection of human adaptation during the past 2000 years, Science, 354, 760, 10.1126/science.aag0776 · DOI · Paper page
  14. PF Palamara, 2018, High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability, Nat Genet, 50, 1311, 10.1038/s41588-018-0177-x · DOI
  15. J Nait Saada, 2020, Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations, Nat Commun, 11, 6130, 10.1038/s41467-020-19588-x · DOI
  16. HA Hejase, 2020, From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection, Trends Genet, 36, 243, 10.1016/j.tig.2019.12.008 · DOI
  17. L Speidel, 2019, A method for genome-wide genealogy estimation for thousands of samples, Nat Genet, 51, 1321, 10.1038/s41588-019-0484-x · DOI · Paper page
  18. AJ Stern, 2019, An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data, PLoS Genet, 15, e1008384, 10.1371/journal.pgen.1008384 · DOI
  19. P Skoglund, 2018, Ancient Genomics of Modern Humans: The First Decade, Annu Rev Genomics Hum Genet, 19, 381, 10.1146/annurev-genom-083117-021749 · DOI · Paper page
  20. M Dehasque, 2020, Inference of natural selection from ancient DNA, Evol Lett, 4, 94, 10.1002/evl3.165 · DOI
  21. S Marciniak, 2017, Harnessing ancient genomes to study the history of human adaptation, Nat Rev Genet, 18, 659, 10.1038/nrg.2017.65 · DOI
  22. Y Souilmi, 2022, Admixture has obscured signals of historical hard sweeps in humans, Nat Ecol Evol, 6, 2003, 10.1038/s41559-022-01914-9 · DOI
  23. RA Mathias, 2012, Adaptive evolution of the FADS gene cluster within Africa, PLoS ONE, 7, e44926, 10.1371/journal.pone.0044926 · DOI
  24. M Fumagalli, 2015, Greenlandic Inuit show genetic signatures of diet and climate adaptation, Science, 349, 1343, 10.1126/science.aab2319 · DOI
  25. MT Buckley, 2017, Selection in Europeans on Fatty Acid Desaturases Associated with Dietary Changes, Mol Biol Evol, 34, 1307, 10.1093/molbev/msx103 · DOI
  26. S Mathieson, 2018, FADS1 and the Timing of Human Adaptation to Agriculture, Mol Biol Evol, 35, 2957, 10.1093/molbev/msy180 · DOI
  27. I. Mathieson, 2020, Limited Evidence for Selection at the FADS Locus in Native American Populations, Mol Biol Evol, 37, 2029, 10.1093/molbev/msaa064 · DOI · Paper page
  28. D Ju, 2021, The evolution of skin pigmentation-associated variation in West Eurasia, Proc Natl Acad Sci U S A, 118
  29. T Davy, 2023, Hunter-gatherer admixture facilitated natural selection in Neolithic European farmers, Curr Biol, 33, 1365, 10.1016/j.cub.2023.02.049 · DOI
  30. MK Le, 2022, 1,000 ancient genomes uncover 10,000 years of natural selection in Europe, bioRxiv
  31. I Hamid, 2021, Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde, Elife, 10
  32. ET Norris, 2020, Admixture-enabled selection for rapid adaptive evolution in the Americas, Genome Biol, 21, 29, 10.1186/s13059-020-1946-2 · DOI
  33. I Mathieson, 2022, Direct detection of natural selection in Bronze Age Britain, Genome Res, 32, 2057, 10.1101/gr.276862.122 · DOI
  34. S Wilde, 2014, Direct evidence for positive selection of skin, hair, and eye pigmentation in Europeans during the last 5,000 y, Proc Natl Acad Sci U S A, 111, 4832, 10.1073/pnas.1316513111 · DOI · Paper page
  35. J Klunk, 2022, Evolution of immune genes is associated with the Black Death, Nature, 611, 312, 10.1038/s41586-022-05349-x · DOI
  36. AR Barton, 2023, Insufficient evidence for natural selection associated with the Black Death, bioRxiv
  37. S Gopalakrishnan, 2022, The population genomic legacy of the second plague pandemic, Curr Biol, 32, 4743, 10.1016/j.cub.2022.09.023 · DOI
  38. R Hui, 2023, Medieval social landscape through the genetic history of Cambridgeshire before and after the Black Death, bioRxiv
  39. TA Mousseau, 1987, Natural selection and the heritability of fitness components, Heredity (Edinb), 59, 181, 10.1038/hdy.1987.113 · DOI
  40. FR Day, 2016, Physical and neurobehavioral determinants of reproductive onset and success, Nat Genet, 48, 617, 10.1038/ng.3551 · DOI
  41. N Barban, 2016, Genome-wide analysis identifies 12 loci influencing human reproductive behavior, Nat Genet, 48, 1462, 10.1038/ng.3698 · DOI
  42. I Mathieson, 2023, Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus, Nat Hum Behav, 7, 790, 10.1038/s41562-023-01528-6 · DOI
  43. K Ye, 2017, Dietary adaptation of FADS genes in Europe varied across time and geography, Nat Ecol Evol, 1, 167, 10.1038/s41559-017-0167 · DOI
  44. KM Siewert, 2017, Detecting Long-Term Balancing Selection Using Allele Frequency Correlation, Mol Biol Evol, 34, 2996, 10.1093/molbev/msx209 · DOI
  45. BD Bitarello, 2018, Signatures of Long-Term Balancing Selection in Human Genomes, Genome Biol Evol, 10, 939, 10.1093/gbe/evy054 · DOI
  46. Y Wu, 2022, GWAS on birth year infant mortality rates provides evidence of recent natural selection, Proc Natl Acad Sci U S A, 119, e2117312119, 10.1073/pnas.2117312119 · DOI
  47. S Pavard, 2021, Evolutionary demographic models reveal the strength of purifying selection on susceptibility alleles to late-onset diseases, Nat Ecol Evol, 5, 392, 10.1038/s41559-020-01355-2 · DOI
  48. R Blekhman, 2008, Natural selection on genes that underlie human disease susceptibility, Curr Biol, 18, 883, 10.1016/j.cub.2008.04.074 · DOI
  49. EH Corder, 1993, Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families, Science, 261, 921, 10.1126/science.8346443 · DOI · Paper page
  50. K Christensen, 2006, The quest for genetic determinants of human longevity: challenges and insights, Nat Rev Genet, 7, 436, 10.1038/nrg1871 · DOI
  51. Tobacco and Genetics Consortium, 2010, Genome-wide meta-analyses identify multiple loci associated with smoking behavior, Nat Genet, 42, 441, 10.1038/ng.571 · DOI · Paper page
  52. EA Lucotte, 2016, Detection of Allelic Frequency Differences between the Sexes in Humans: A Signature of Sexually Antagonistic Selection, Genome Biol Evol, 8, 1489, 10.1093/gbe/evw090 · DOI
  53. KR Kasimatis, 2021, Evaluating human autosomal loci for sexually antagonistic viability selection in two large biobanks, Genetics, 217, 1, 10.1093/genetics/iyaa015 · DOI
  54. F Ruzicka, 2022, An unbiased test reveals no enrichment of sexually antagonistic polymorphisms on the human X chromosome, Proc Biol Sci, 289, 20212314
  55. KR Kasimatis, 2019, Limits to Genomic Divergence Under Sexually Antagonistic Selection, G3 (Bethesda), 9, 3813, 10.1534/g3.119.400711 · DOI
  56. C Cheng, 2016, Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies, PLoS Genet, 12, e1006170, 10.1371/journal.pgen.1006170 · DOI
  57. T Bersaglieri, 2004, Genetic signatures of strong recent positive selection at the lactase gene, Am J Hum Genet, 74, 1111, 10.1086/421051 · DOI
  58. MC Mills, 2022, The challenge of detecting recent natural selection in human populations, Proc Natl Acad Sci U S A, 119, e2203237119, 10.1073/pnas.2203237119 · DOI
  59. A Fry, 2017, Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population, Am J Epidemiol, 186, 1026, 10.1093/aje/kwx246 · DOI · Paper page
  60. R. Fisher, 1918, The correlation between relatives on the supposition of mendelian inheritance, Trans R Soc Edinb, 53, 399
  61. KE Lohmueller, 2006, Variants associated with common disease are not unusually differentiated in frequency across populations, Am J Hum Genet, 78, 130, 10.1086/499287 · DOI
  62. MC Turchin, 2012, Evidence of widespread selection on standing variation in Europe at height-associated SNPs, Nat Genet, 44, 1015, 10.1038/ng.2368 · DOI · Paper page
  63. MR Robinson, 2015, Population genetic differentiation of height and body mass index across Europe, Nat Genet, 47, 1357, 10.1038/ng.3401 · DOI
  64. M Zoledziewska, 2015, Height-reducing variants and selection for short stature in Sardinia, Nat Genet, 47, 1352, 10.1038/ng.3403 · DOI
  65. F Racimo, 2018, Detecting Polygenic Adaptation in Admixture Graphs, Genetics, 208, 1565, 10.1534/genetics.117.300489 · DOI
  66. MD Edge, 2019, Reconstructing the History of Polygenic Scores Using Coalescent Trees, Genetics, 211, 235, 10.1534/genetics.118.301687 · DOI
  67. AJ Stern, 2021, Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies, Am J Hum Genet, 108, 219, 10.1016/j.ajhg.2020.12.005 · DOI
  68. SC Stearns, 2010, Measuring selection in contemporary human populations, Nat Rev Genet, 11, 611, 10.1038/nrg2831 · DOI
  69. JP Beauchamp, 2016, Genetic evidence for natural selection in humans in the contemporary United States, Proc Natl Acad Sci U S A, 113, 7774, 10.1073/pnas.1600398113 · DOI · Paper page
  70. FC Tropf, 2015, Human fertility, molecular genetics, and natural selection in modern societies, PLoS ONE, 10, e0126821, 10.1371/journal.pone.0126821 · DOI · Paper page
  71. JS Sanjak, 2018, Evidence of directional and stabilizing selection in contemporary humans, Proc Natl Acad Sci U S A, 115, 151, 10.1073/pnas.1707227114 · DOI
  72. C Zhu, 2023, Amplification is the primary mode of gene-by-sex interaction in complex human traits, Cell Genom, 3, 100297, 10.1016/j.xgen.2023.100297 · DOI
  73. J Wang, 2021, Sex-specific associations of circulating testosterone levels with all-cause and cause-specific mortality, Eur J Endocrinol, 184, 723, 10.1530/EJE-20-1253 · DOI
  74. J Novembre, 2018, Tread Lightly Interpreting Polygenic Tests of Selection, Genetics, 208, 1351, 10.1534/genetics.118.300786 · DOI · Paper page
  75. JJ Berg, 2019, Reduced signal for polygenic adaptation of height in UK Biobank, Elife, 8
  76. M Sohail, 2019, Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies, Elife, 8
  77. H Mostafavi, 2020, Variable prediction accuracy of polygenic scores within an ancestry group, Elife, 9
  78. AA Zaidi, 2020, Demographic history mediates the effect of stratification on polygenic scores, Elife
  79. AP Schoech, 2019, Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection, Nat Commun, 10, 790, 10.1038/s41467-019-08424-6 · DOI · Paper page
  80. MG Bulmer, 1972, The genetic variability of polygenic characters under optimizing selection, mutation and drift, Genet Res, 19, 17, 10.1017/S0016672300014221 · DOI
  81. S Yair, 2022, Population differentiation of polygenic score predictions under stabilizing selection, Philos Trans R Soc Lond B Biol Sci, 377, 20200416, 10.1098/rstb.2020.0416 · DOI
  82. R Lande, 1983, The Measurement of Selection on Correlated Characters, Evolution, 37, 1210, 10.2307/2408842 · DOI
  83. B Bulik-Sullivan, 2015, An atlas of genetic correlations across human diseases and traits, Nat Genet, 47, 1236, 10.1038/ng.3406 · DOI · Paper page
  84. M Szpak, 2019, How well do we understand the basis of classic selective sweeps in humans?, FEBS Lett, 593, 1431, 10.1002/1873-3468.13447 · DOI
  85. FW Stearns, 2010, One hundred years of pleiotropy: a retrospective, Genetics, 186, 767, 10.1534/genetics.110.122549 · DOI
  86. I. Mathieson, 2020, Human adaptation over the past 40,000 years, Curr Opin Genet Dev, 62, 97, 10.1016/j.gde.2020.06.003 · DOI
  87. EM Koch, 2021, Maintenance of Complex Trait Variation: Classic Theory and Modern Data, Front Genet, 12, 763363, 10.3389/fgene.2021.763363 · DOI

Cited by

Sorted by citations

Metadata

Authors
Gao, Z.
ORCID
Gao, Ziyue
Venue
PLOS Biology
Publisher
Public Library of Science (PLoS)
Published
2024-01-18
Volume
22
Issue
1
Pages
e3002469
ISSN
1545-7885
DOI
10.1371/journal.pbio.3002469
PMC
PMC10796035
Cited by
12
References
15
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Alfred P. Sloan Foundation (FG-2021-15702)
  • National Institute of General Medical Sciences (R35GM146810)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review