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Ghost population

From Wikipedia, the free encyclopedia

In genetic research, a "ghost population" refers to a population that has been inferred when analyzing genomes through the use of statistical techniques,[1] yet which has not been adequately associated with a physical specimen.[2][3][4]: 1 [5]: 30 [6]: 173 

Researchers may infer "ghost" populations when they identify sections of an individual's genome as displaying "excessively high sequence diversity"[2] compared to the rest of their population,[2][4]: 2  as such variation may reflect the individuals' inheritance of material ultimately sourced from members of "other", notably diverged lineages.[2][4]: 1–2  However, "ghost" populations may not be so easily identified by contrast within a population when their inputs become common.[3] Recently, a number of scholars have thus argued that analysis of population history can be improved by accounting for scenarios in which "ghost" populations have contributed similar material to various groups, as such analysis may disentangle various otherwise muddied relationships.[7][8][3]

Importantly, the term "ghost population" is a functional term used in science and not a prescriptive one: populations are "ghosts" when they are inferred through scientific methods yet not identified with specific remains, and cease to be so if/when such remains are identified.[9]: 191, 200–201 [10][better source needed][5][better source needed] For example, when Hall (2017) responded to Pagani et. al. (2016)'s[11] claim that certain Oceanian populations had ancestry from an unknown "ghost" population, he noted that this ancestry was probably not "ghost" ancestry because it could reasonably be attributed to a branch of Denisovans.[12][original research?]

Background

[edit]

In 2004, it was proposed that maximum likelihood or Bayesian approaches that estimate the migration rates and population sizes using coalescent theory can use datasets that contain a population that has no data. This is referred to as a "ghost population". The manipulation allows exploration in the effects of missing populations on the estimation of population sizes and migration rates between two specific populations. The biases of the inferred population parameters depend on the magnitude of the migration rate from the unknown sister populations.[1] The technique for deriving ghost populations attracted criticism because ghost populations were the result of statistical models, along with their limitations.[13]

Population genetics

[edit]

Humans

[edit]

In 2012, DNA analysis and statistical techniques were used to infer that a now-extinct human population in northern Eurasia had interbred with both the ancestors of Europeans and a Siberian group that later migrated to the Americas. The group was referred to as a ghost population because they were identified by the echoes that they leave in genomes—not by bones or ancient DNA.[14] In 2013, another study found the remains of a member of this ghost group, fulfilling the earlier prediction that they had existed.[15][16]

According to a study published in 2020, there are indications that 2% to 19% (or about ≃6.6 and ≃7.0%) of the DNA of four West African populations may have come from an unknown archaic hominin that split from the ancestor of Homo Sapiens (Modern Humans) and Neanderthals between 360 kya to 1.02 mya.

The study suggests that Basal West Africans did not split before Neanderthals split from modern humans,[17] and that even before 300,000 BP to 200,000 BP, when the ancestors of the modern San split from other modern sister groups of humans, the group to split the most early from modern humans may have been Basal West Africans.[17]

However, the study also suggests that at least part of this archaic admixture is also present in Eurasians/non-Africans, and that the admixture event or events range from 0 to 124 ka B.P, which includes the period before the Out-of-Africa migration and prior to the African/Eurasian split (thus affecting in part the common ancestors of both Africans and Eurasians/non-Africans).[18][19][20] Another study, in 2020, which discovered substantial amounts of previously undescribed human genetic variation, also found ancestral genetic variation in Africans that predates modern humans and was lost in most non-Africans.[21]

In 2026, a new method to discover archaic ancestry via study of the DNA of contemporary humans is being explored by a computational biologist at University of California (Berkeley), Yulin Zhang, and geneticist Arjun Biddanda. Their initial research uses a mathematical model entitled TRACE (Tracking Archaic Contributions via ARG Estimation). All of the populations Zang and her team studied suggest a "ghost" lineage that they estimate separated as a sister population from that of modern humans earlier than 500,000 years ago at approximately the same time as that of the Denisovan and the Neanderthal populations did.[22]

Other animals

[edit]

In 2015, a study of the lineage and early migration of the domestic pig found that the best model that fitted the data included gene flow from a ghost population during the Pleistocene that is now extinct.[23]

A 2018 study suggests that the common ancestor of the wolf and the coyote may have interbred with an unknown canid that is related to the dhole.[24]

See also

[edit]

References

[edit]
  1. 1 2 Beerli, P (2004). "Effect of unsampled populations on the estimation of population sizes and migration rates between sampled populations". Molecular Ecology. 13 (4): 827–836. Bibcode:2004MolEc..13..827B. doi:10.1111/j.1365-294x.2004.02101.x. PMID 15012758. S2CID 18326408.
  2. 1 2 3 4 Thomas, M.; Gilbert, P.; Lalueza-Fox, Carles (2023). "Paleogenomics of Extinct and Archaic Hominins". In Pollard, A. Mark; Makarewicz, Cheryl A.; Armitage, Ruth Ann (eds.). Handbook of Archaeological Sciences (2 ed.). Wiley. ISBN 9781119592082.
  3. 1 2 3 Hibbins, Mark S.; W Hahn, Matthew (11 November 2021). Turelli, M (ed.). "Phylogenomic Approaches to Detecting and Characterizing Introgression". Genetics. 220 (2) iyab173. doi:10.1093/genetics/iyab173. PMC 9208645. PMID 34788444.
  4. 1 2 3 Ottenburghs Jente, BioEssays, Jente (2020). "Ghost Introgression: Spooky Gene Flow in the Distant Past". BioEssays. 42 (6) 2000012. doi:10.1002/bies.202000012. PMID 32227363. Retrieved 3 September 2026.
  5. 1 2 Brahic, Catherine (13 October 2018). "The Ghosts Within". New Scientist. 240 (3199). NewScientist: 30–33. doi:10.1016/S0262-4079(18)31847-5.
  6. ↑ Bryant, Christopher; Brown, Valerie A. (2021). "Inheriting the Earth". Cooperative Evolution: Reclaiming Darwin's Vision. Australia: Australian National University Press. pp. 163–178. doi:10.22459/CE.2021. ISBN 9781760464295. Archived from the original on 18 January 2022. Retrieved 3 September 2026.
  7. ↑ Sethuraman, Arun; Lynch, Mellisa; Wanjiku Michael, Margaret; Kuzminskiy (11 August 2025). Schrider., D (ed.). "Accounting For Gene Flow From Unsampled Ghost Populations While Estimating Evolutionary History". Genes Genomes Genetics (G3). 15 (10) jkaf180. doi:10.1093/g3journal/jkaf180. PMC 12506660. PMID 40796159.
  8. ↑ Hey, Jody; Chung, Yujin; Sethuraman, Arun; Lachance, Joseph; Tishkoff, Sarah; Sousa, Victor C; Wang, Yong (20 August 2018). Kim, Yuseob (ed.). "Phylogeny Estimation by Integration over Isolation with Migration Models". Molecular Biology and Evoluion (Oxford Journals). 35 (11): 2805–2818. doi:10.1093/molbev/msy162. PMC 6231491. PMID 30137463.
  9. ↑ Higham, Tom (2021). "Homo Erectus and the Ghost Population". The World Before Us: The New Science Behind Our Human Origins. Yale University Press. pp. 191–201. doi:10.2307/j.ctv1sfsdqn.18. ISBN 9780300271126. JSTOR j.ctv1sfsdqn.18. Retrieved 3 September 2026.
  10. ↑ Pettit, Paul (2023). "Ghosts and indigenes". Homo Sapiens Rediscovered: The Scientific Revolution Rewriting Our Origins (The Rediscovered Series). Thames & Hudson. ISBN 9780500777503.
  11. ↑ Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mörseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; DeGiorgio, Michael; Saag, Lauri; Wall, Jeffrey D; Cardona, Alexia; Mägi, Reedik; Sayres, Melissa A Wilson; Kaewert, Sarah; Inchley, Charlotte; L Scheib, Christiana; Järve, Mari; Karmin, Monika; Jacobs, Guy S; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Basu Mallick, Chandana; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C; Lambert, David M; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Lubov Atramentova, Olga Utevska, François-Xavier Ricaut, Nicolas Brucato, Herawati Sudoyo, Thierry Letellier, Murray P Cox, Nikolay A Barashkov, Vedrana Skaro, Lejla Mulahasanovic, Dragan Primorac, Hovhannes Sahakyan, Maru Mormina, Christina A Eichstaedt, Daria V Lichman, Syafiq Abdullah, Gyaneshwer Chaubey, Joseph T S Wee, Evelin Mihailov, Alexandra Karunas, Sergei Litvinov, Rita Khusainova, Natalya Ekomasova, Vita Akhmetova, Irina Khidiyatova, Damir Marjanović, Levon Yepiskoposyan, Doron M Behar, Elena Balanovska, Andres Metspalu, Miroslava Derenko, Boris Malyarchuk, Mikhail Voevoda, Sardana A Fedorova, Ludmila P Osipova, Marta Mirazón Lahr, Pascale Gerbault, Matthew Leavesley, Andrea Bamberg Migliano, Michael Petraglia, Oleg Balanovsky, Elza K Khusnutdinova, Ene Metspalu, Mark G Thomas, Andrea Manica, Rasmus Nielsen, Richard Villems, Eske Willerslev, Toomas Kivisild, Mait Metspalu (21 September 2016). "Genomic Analyses Inform On Migration Events During The Peopling of Eurasia". Nature. 583 (7428): 238–242. Bibcode:2016Natur.538..238P. doi:10.1038/nature19792. PMC 5164938. PMID 27654910.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  12. ↑ Wall, Jeffrey D. (4 May 2017). "Inferring Human Demographic Histories of Non-African Populations from Patterns of Allele Sharing". American Journal of Human Genetics. 100 (5): 766–772. doi:10.1016/j.ajhg.2017.04.002. PMC 5402348. PMID 28475895.
  13. ↑ Skatkin, M (2005). "Seeing ghosts: the effect of unsampled populations on migration rates estimated for sampled populations". Molecular Ecology. 14 (1): 67–73. Bibcode:2005MolEc..14...67S. doi:10.1111/j.1365-294X.2004.02393.x. PMID 15643951. S2CID 17600283.
  14. ↑ Patterson, N (2012). "Ancient admixture in human history". Genetics. 192 (3): 1065–93. doi:10.1534/genetics.112.145037. PMC 3522152. PMID 22960212.
  15. ↑ Raghavan, M (2013). "Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans". Nature. 505 (7481): 87–91. Bibcode:2014Natur.505...87R. doi:10.1038/nature12736. PMC 4105016. PMID 24256729.
  16. ↑ Callaway, E (2015). ""Ghost population" hints at long-lost migration to the Americas". Nature. doi:10.1038/nature.2015.18029. S2CID 181337948.
  17. 1 2 Skoglund, Pontus; et al. (2017). "Reconstructing Prehistoric African Population Structure". Cell. 171 (1): 59–71.e21. Bibcode:2017Cell..171...59S. doi:10.1016/j.cell.2017.08.049. ISSN 0092-8674. OCLC 7144495602. PMC 5679310. PMID 28938123. S2CID 1257429.
  18. ↑ Arun Durvasula; Sriram Sankararaman (2020). "Recovering signals of ghost archaic introgression in African populations". Science Advances. 6 (7) eaax5097. Bibcode:2020SciA....6.5097D. doi:10.1126/sciadv.aax5097. PMC 7015685. PMID 32095519. "Non-African populations (Han Chinese in Beijing and Utah residents with northern and western European ancestry) also show analogous patterns in the CSFS, suggesting that a component of archaic ancestry was shared before the split of African and non-African populations... One interpretation of the recent time of introgression that we document is that archaic forms persisted in Africa until fairly recently. Alternately, the archaic population could have introgressed earlier into a modern human population, which then subsequently interbred with the ancestors of the populations that we have analyzed here. The models that we have explored here are not mutually exclusive, and it is plausible that the history of African populations includes genetic contributions from multiple divergent populations, as evidenced by the large effective population size associated with the introgressing archaic population... Given the uncertainty in our estimates of the time of introgression, we wondered whether jointly analyzing the CSFS from both the CEU (Utah residents with Northern and Western European ancestry) and YRI genomes could provide additional resolution. Under model C, we simulated introgression before and after the split between African and non-African populations and observed qualitative differences between the two models in the high-frequency–derived allele bins of the CSFS in African and non-African populations (fig. S40). Using ABC to jointly fit the high-frequency–derived allele bins of the CSFS in CEU and YRI (defined as greater than 50% frequency), we find that the lower limit on the 95% credible interval of the introgression time is older than the simulated split between CEU and YRI (2800 versus 2155 generations B.P.), indicating that at least part of the archaic lineages seen in the YRI are also shared with the CEU..."
  19. ↑ Supplementary Materials for Recovering signals of ghost archaic introgression in African populations", section "S8.2" "We simulated data using the same priors in Section S5.2, but computed the spectrum for both YRI [West African Yoruba] and CEU [a population of European origin]. We found that the best fitting parameters were an archaic split time of 27,000 generations ago (95% HPD: 26,000-28,000), admixture fraction of 0.09 (95% HPD: 0.04-0.17), admixture time of 3,000 generations ago (95% HPD: 2,800-3,400), and an effective population size of 19,700 individuals (95% HPD: 19,300-20,200). We find that the lower bound of the admixture time is further back than the simulated split between CEU and YRI (2155 generations ago), providing some evidence in favor of a pre-Out-of-Africa event. This model suggests that many populations outside of Africa should also contain haplotypes from this introgression event, though detection is difficult because many methods use unadmixed outgroups to detect introgressed haplotypes [Browning et al., 2018, Skov et al., 2018, Durvasula and Sankararaman, 2019] (5, 53, 22). It is also possible that some of these haplotypes were lost during the Out-of-Africa bottleneck."
  20. ↑ Durvasula, Arun; Sankararaman, Sriram (2020). "Recovering signals of ghost archaic introgression in African populations". Science Advances. 6 (7) eaax5097. Bibcode:2020SciA....6.5097D. doi:10.1126/sciadv.aax5097. PMC 7015685. PMID 32095519. S2CID 211472946.
  21. ↑ Bergström, A; McCarthy, S; Hui, R; Almarri, M; Ayub, Q (2020). "Insights into human genetic variation and population history from 929 diverse genomes". Science. 367 (6484) eaay5012. Bibcode:2020Sci...367y5012B. doi:10.1126/science.aay5012. PMC 7115999. PMID 32193295. "An analysis of archaic sequences in modern populations identifies ancestral genetic variation in African populations that likely predates modern humans and has been lost in most non-African populations... We found small amounts of Neanderthal ancestry in West African genomes, most likely reflecting Eurasian admixture. Despite their very low levels or absence of archaic ancestry, African populations share many Neanderthal and Denisovan variants that are absent from Eurasia, reflecting how a larger proportion of the ancestral human variation has been maintained in Africa."
  22. ↑ Yulin Zhang, Arjun Biddanda, Sarah A. Johnson, Colm O’Dushlaine, Priya Moorjani, Recovering signatures of archaic hominin introgression using ancestral recombination graphs, Science, July 30, 2026
  23. ↑ Frantz, L (2015). "Evidence of long-term gene flow and selection during domestication from analyses of Eurasian wild and domestic pig genomes". Nature Genetics. 47 (10): 1141–1148. Bibcode:2015NaGen..47.1141F. doi:10.1038/ng.3394. PMID 26323058. S2CID 205350534.
  24. ↑ Gopalakrishnan, Shyam; Sinding, Mikkel-Holger S.; Ramos-Madrigal, Jazmín; Niemann, Jonas; Samaniego Castruita, Jose A.; Vieira, Filipe G.; Carøe, Christian; Montero, Marc de Manuel; Kuderna, Lukas; Serres, Aitor; González-Basallote, Víctor Manuel; Liu, Yan-Hu; Wang, Guo-Dong; Marques-Bonet, Tomas; Mirarab, Siavash; Fernandes, Carlos; Gaubert, Philippe; Koepfli, Klaus-Peter; Budd, Jane; Rueness, Eli Knispel; Heide-Jørgensen, Mads Peter; Petersen, Bent; Sicheritz-Ponten, Thomas; Bachmann, Lutz; Wiig, Øystein; Hansen, Anders J.; Gilbert, M. Thomas P. (2018). "Interspecific Gene Flow Shaped the Evolution of the Genus Canis". Current Biology. 28 (21): 3441–3449.e5. Bibcode:2018CBio...28E3441G. doi:10.1016/j.cub.2018.08.041. PMC 6224481. PMID 30344120.
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