Signatures of Archaic Adaptive Introgression in Present-Day Human Populations
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Abstract
Comparisons of DNA from archaic and modern humans show that these groups interbred, and in some cases received an evolutionary advantage from doing so. This process-adaptive introgression-may lead to a faster rate of adaptation than is predicted from models with mutation and selection alone. Within the last couple of years, a series of studies have identified regions of the genome that are likely examples of adaptive introgression. In many cases, once a region was ascertained as being introgressed, commonly used statistics based on both haplotype as well as allele frequency information were employed to test for positive selection. Introgression by itself, however, changes both the haplotype structure and the distribution of allele frequencies, thus confounding traditional tests for detecting positive selection. Therefore, patterns generated by introgression alone may lead to false inferences of positive selection. Here we explore models involving both introgression and positive selection to investigate the behavior of various statistics under adaptive introgression. In particular, we find that the number and allelic frequencies of sites that are uniquely shared between archaic humans and specific present-day populations are particularly useful for detecting adaptive introgression. We then examine the 1000 Genomes dataset to characterize the landscape of uniquely shared archaic alleles in human populations. Finally, we identify regions that were likely subject to adaptive introgression and discuss some of the most promising candidate genes located in these regions.
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Evidence that RNA Viruses Drove Adaptive Introgression between Neanderthals and Modern Humans
Enard, D., & Petrov, D. A. (2018) · Cell · doi:10.1016/j.cell.2018.08.034 · Cited by 208 · see citing works
Genomic insights into population history and biological adaptation in Oceania
Choin, J., Mendoza-Revilla, J., Arauna, L. R., Cuadros-Espinoza, S., Cassar, O., Larena, M., Ko, A. M.-S., Harmant, C., Laurent, R., Verdu, P., et al. (2021) · Nature · doi:10.1038/s41586-021-03236-5 · Cited by 208 · see citing works
Sams, A. J., Dumaine, A., Nédélec, Y., Yotova, V., Alfieri, C., Tanner, J. E., Messer, P. W., & Barreiro, L. B. (2016) · Genome Biology · doi:10.1186/s13059-016-1098-6 · Cited by 140 · see citing works
Detecting adaptive introgression in human evolution using convolutional neural networks
Gower, G., Picazo, P. I., Fumagalli, M., & Racimo, F. (2021) · eLife · doi:10.7554/elife.64669 · Cited by 95 · see citing works
Self-citationFunctional implications of Neandertal introgression in modern humans
Dannemann, M., Prüfer, K., & Kelso, J. (2017) · Genome biology · doi:10.1186/s13059-017-1181-7 · Cited by 92 · see citing works
Something old, something borrowed: admixture and adaptation in human evolution
Dannemann, M., & Racimo, F. (2018) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2018.05.009 · Cited by 87 · see citing works
Self-citationQuantifying the contribution of Neanderthal introgression to the heritability of complex traits
McArthur, E., Rinker, D. C., & Capra, J. A. (2021) · Nature Communications · doi:10.1038/s41467-021-24582-y · Cited by 71 · see citing works
“Many of these 52 alleles influence systems that directly interact with the environment, such as the immune 53 system, hair and skin, response to oxygen(20), and metabolism.(7,21,22) 54 In spite of these potential adaptive benefits of admixture, theory and simulations suggest 55 that introgressed alleles were largely d…”
BackgroundChen, N., Xia, X., Hanif, Q., Zhang, F., Dang, R., Huang, B., Lyu, Y., Luo, X., Zhang, H., Yan, H., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43626-z · Cited by 83 · see citing works
Model‐based detection and analysis of introgressed Neanderthal ancestry in modern humans
Steinrücken, M., Spence, J. P., Kamm, J. A., Wieczorek, E., & Song, Y. S. (2018) · Molecular Ecology · doi:10.1111/mec.14565 · Cited by 73 · see citing works
Gouy, A., & Excoffier, L. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msz306 · Cited by 63 · see citing works
Silvert, M., Quintana-Murci, L., & Rotival, M. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.04.016 · Cited by 58 · see citing works
Population history and gene divergence in native Mexicans inferred from 76 human exomes
Ávila-Arcos, M. C., McManus, K. F., Sandoval, K., Rodríguez-Rodríguez, J. E., Villa-Islas, V., Martin, A. R., Luisi, P., Peñaloza-Espinosa, R. I., Eng, C., Huntsman, S., et al. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msz282 · Cited by 50 · see citing works
Recent Selection and Introgression Facilitated High-Altitude Adaptation in Cattle
Lyu, Y., Wang, F., Cheng, H., Han, J., Dang, R., Xia, X., Wang, H., Zhong, J., Lenstra, J. A., Zhang, H., et al. (2024) · Science Bulletin · doi:10.1016/j.scib.2024.05.030 · Cited by 50 · see citing works
Neanderthal introgression reintroduced functional ancestral alleles lost in Eurasian populations
Rinker, D. C., Simonti, C. N., McArthur, E., Shaw, D., Hodges, E., & Capra, J. A. (2020) · Nature Ecology & Evolution · doi:10.1038/s41559-020-1261-z · Cited by 44 · see citing works
Zhang, X., Kim, B., Singh, A., Sankararaman, S., Durvasula, A., & Lohmueller, K. E. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad001 · Cited by 29 · see citing works
The Impact of Modern Admixture on Archaic Human Ancestry in Human Populations
Witt, K. E., Funk, A., Añorve-Garibay, V., Fang, L. L., & Huerta-Sánchez, E. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad066 · Cited by 29 · see citing works
“Notably, these populations also harbor remnants of archaic ancestry (Sankararaman et al. 2014, 2016; Racimo et al. 2017) as they are the descendants of ancestral populations that interbred with archaic humans in the past.”
BackgroundInfluentialSelf-citationArchaic Introgression Shaped Human Circadian Traits
Velazquez-Arcelay, K., Colbran, L. L., McArthur, E., Brand, C. M., Rinker, D. C., Siemann, J. K., McMahon, D. G., & Capra, J. A. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad203 · Cited by 18 · see citing works
“Previous studies in humans found a correlation between latitude and chronotype (morningness vs. eveningness) variation (Leocadio-Miguel et al. 2017; Randler and Rahafar 2017; Lowden et al. 2018) and a latitudinal cline in some circadian allele frequencies (Dorokhov et al. 2018; Putilov et al. 2018,…”
BackgroundA signature of Neanderthal introgression on molecular mechanisms of environmental responses
Findley, A. S., Zhang, X., Boye, C., Lin, Y. L., Kalita, C. A., Barreiro, L., Lohmueller, K. E., Pique-Regi, R., & Luca, F. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009493 · Cited by 14 · see citing works
Guan, X., Xiang, W., Qu, K., Ahmed, Z., Liu, J., Cai, M., Zhang, J., Chen, N., Lei, C., & Huang, B. (2025) · BMC Genomics · doi:10.1186/s12864-024-11033-3 · Cited by 10 · see citing works
Human genetic adaptation related to cellular zinc homeostasis
Roca-Umbert, A., Garcia-Calleja, J., Vogel-González, M., Fierro-Villegas, A., Ill-Raga, G., Herrera-Fernández, V., Bosnjak, A., Muntané, G., Gutiérrez, E., Campelo, F., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010950 · Cited by 8 · see citing works
“U and Q95 statistics [41] testing for archaic introgression in CHB and CEU (phase 3 1000 GP sequencing data) were computed twice in the form U (10%, 50%, 100”
Influential
- Authors
- Racimo, F., Marnetto, D., & Huerta-Sánchez, E.
- Affiliations
- University of California, Berkeley (US)
- University of Turin (IT)
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-10-18
- Volume
- 34
- Issue
- 2
- Pages
- msw216
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- PMC
- PMC5400396
- OpenAlex
- W2534489581
- Cited by
- 200
- References
- 16
- Citations by year
- 2026: 13 · 2025: 18 · 2024: 23 · 2023: 23 · 2022: 17 · 2021: 30 · 2020: 17 · 2019: 19 · 2018: 18 · 2017: 17 · 2016: 5
- FWCI
- 76.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Biology and Evolution (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
- Funders
- National Science Foundation (1557151)
- National Institutes of Health
- University of California Merced
- National Human Genome Research Institute (R01HG003229)
- Division of Environmental Biology
- Topics
- Social Sciences › Anthropology › Pleistocene-Era Hominins and Archaeology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- adaptive introgression, archaic human admixture, Neanderthal introgression, Denisovan introgression, positive selection detection, haplotype structure, allele frequency distribution, 1000 Genomes Project, human population genomics, candidate genes
- MeSH terms
- DNA, Ancient, Adaptation, Biological, Alleles, Animals, Computer Simulation, Biological Evolution, Gene Frequency, Genetics, Population, Haplotypes, Humans, Phylogeny, Selection, Genetic, Sequence Analysis, DNA, Evolution, Molecular, Databases, Nucleic Acid, Neanderthals
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