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Why Hunter-Gatherer Populations Do Not Show Signs of Pleistocene Demographic Expansions

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Why Hunter-Gatherer Populations Do Not Show Signs of Pleistocene Demographic Expansions Proc. Natl. Acad. Sci. USA Vol. 96, pp. 10597–10602, September 1999 Anthropology Why hunter-gatherer populations do not show signs of Pleistocene demographic expansions LAURENT EXCOFFIER† AND STEFAN SCHNEIDER Genetics and Biometry Laboratory, Department of Anthropology, University of Geneva, CP 24, 1211 Geneva 24, Switzerland Communicated by Henry C. Harpending, University of Utah, Salt Lake City, UT, July 13, 1999 (received for review January 26, 1999) ABSTRACT The mitochondrial DNA diversity of 62 hu- some Amerindian populations and some hunter-gatherer pop- man population samples was examined for potential signals of ulations (HGPs) from different continents. A multivariate population expansions. Stepwise expansion times were esti- analysis of genetic distances reveals that the most divergent mated by taking into account heterogeneity of mutation rates populations do not show signs of Pleistocene expansions, among sites. Assuming an mtDNA divergence rate of 33% per particularly in Africa and in America. Otherwise, the genetic million years, most populations show signals of Pleistocene affinities among populations are found in good agreement with expansions at around 70,000 years (70 KY) ago in Africa and geography. The puzzling lack of signal of Pleistocene expan- Asia, 55 KY ago in America, and 40 KY ago in Europe and the sions in hunter-gatherers is discussed. We propose that the Middle East, whereas the traces of the oldest expansions are Holocene HGPs lost previous signals of Pleistocene expan- found in East Africa (110 KY ago for the Turkana). The sions because of post-Neolithic population bottlenecks; this genetic diversity of two groups of populations (most Amerin- conclusion is supported by computer simulations. dian populations and present-day hunter-gatherers) cannot be explained by a simple stepwise expansion model. A multivar- iate analysis of the genetic distances among 61 populations MATERIALS AND METHODS reveals that populations that did not undergo demographic Samples. The 62 population samples analyzed consist of a total expansions show increased genetic distances from other pop- of 2,778 individuals; these populations are listed in Table 1. ulations, confirming that the demography of the populations Ethnically heterogeneous population samples and samples with strongly affects observed genetic affinities. The absence of fewer than 20 individuals were not considered in this study. traces of Pleistocene expansions in present-day hunter- Detecting Demographic Expansions. Traces of population gatherers seems best explained by the occurrence of recent expansions were examined by using two different approaches. bottlenecks in those populations, implying a difference be- First, we computed Fu’s FS statistic (18) in all samples. This tween Pleistocene (Ϸ1,800 KY to 10 KY ago) and Holocene (10 statistic is particularly sensitive to population growth. It is KY to present) hunter-gatherers demographies, a difference based on the probability of having a number of alleles greater that occurred after, and probably in response to, the Neolithic or equal to the observed number in a sample drawn from a expansions of the other populations. stationary population with parameter ␪ ϭ 2Nu (where N is the population effective size, and u is the mutation rate for the A wealth of data on human mtDNA diversity has accumulated whole sequence). Here, ␪ is estimated by equating it with the over the past few years, with more than 4,000 sequences from average number of observed pairwise differences. The FS the first hypervariable region (HV1) being available (1). significance was tested with a coalescent simulation program Previous analyses of some of these data have led to important (modified from ref. 19), as implemented in a new version of the results about the evolution of the mtDNA molecule, such as a computer program ARLEQUIN (20). Basically, the testing pro- very rapid evolutionary rate (2–5) associated with a strong cedure consisted of random samples generating from a sta- heterogeneity of mutation rates (6). These data have also led tionary population with estimated parameter ˆ␪, and of recom- to important conclusions about human evolution, e.g., a prob- puting the FS statistic for each sample. Five thousand simula- ably recent and unique African origin for all modern humans tions were carried out to obtain the null distribution of the FS (7), a recent origin of Amerindian populations from North statistic and its P value. Significantly large negative FS values East Asia (see, for example, ref. 8), or the occurrence of large are interpreted here as evidence for population expansion population expansions as inferred from the observed pattern (18). Secondly, the distribution of the number of pairwise of molecular diversity and the star-shape of phylogenetic trees differences between sequences within a sample (the mismatch (9, 10). Past demographic events seem to have had a profound distribution) was used to estimate the timing of demographic effect on the amount and the pattern of mtDNA and on expansion (the method proposed by Rogers and Harpending nuclear diversity (11–14). Current calibrations of those expan- in ref. 9). This method is based on an infinite-site model and sions point to the Pleistocene (15), with the oldest expansions assumes that a stepwise expansion occurred some time in the apparently having occurred in Africa; this conclusion could past from a small stationary population to a large stationary partly explain the increased diversity observed on that conti- population; this seems to be a good approximation of expo- nent (16, 17). nential or logistic growth (9). Although the infinite-site model In this paper, we report on an extensive study of the is adequate under small departures from a pure infinite-site molecular diversity in 62 worldwide population samples. We model (21), we have recently extended the Rogers and Harp- looked for genetic signals of population growth and estimated ending model to accommodate a more realistic mutation the timing of the putative demographic expansions. Most model (22): we have used a Kimura two-parameter mutation human populations show significant signs of Pleistocene ex- pansion, although there are interesting exceptions, such as Abbreviations: CI, confidence intervals; HGP, hunter-gatherer pop- ulation; HV1, hypervariable region 1; KY, 1,000 years; SSD, sum of The publication costs of this article were defrayed in part by page charge squared differences. A Commentary on this article begins on page 10562. payment. This article must therefore be hereby marked ‘‘advertisement’’ in †To whom reprint requests should be addressed at: Department of accordance with 18 U.S.C. §1734 solely to indicate this fact. Anthropology, 12 rue Gustave Revilliod, 1227 Geneva, Switzerland. PNAS is available online at www.pnas.org. E-mail: [email protected]. 10597 Downloaded by guest on September 25, 2021 10598 Anthropology: Excoffier and Schneider Proc. Natl. Acad. Sci. USA 96 (1999) Table 1. Fu’s FS statistics and expansion times (␶) estimated from mtDNA HV1 sequences ࿣ Samples Abbr.* nFS P(FS)† ␶‡ P§ t,KY¶ t 95% CI, KY Ref. Asia and Oceania Asia Asi 24 Ϫ19.87 0.000 8.94 0.994 73 46–87 55 Australia Desert AusD 51 Ϫ11.76 0.000 6.35 0.510 48 26–68 56 Australia Riverine AusR 63 Ϫ3.91 0.131 10.08 0.144 76 44–107 56 Hong-Kong H-K 20 Ϫ15.58 0.000 7.71 0.667 58 35–82 57 Japan Jap 61 Ϫ25.03 0.000 6.00 0.368 40 25–76 58 Luzon Philippines Luz 36 Ϫ19.72 0.000 5.38 0.006 86 51–105 55 Papua New Guinea 1 PNG1 20 Ϫ5.56 0.012 9.61 0.861 97 39–168 3 Papua New Guinea 2 PNG2 24 Ϫ8.16 0.004 10.30 0.599 84 48–151 59 Sabah Borneo Sab 37 Ϫ10.63 0.000 4.88 0.126 78 44–95 55 Taiwan Tai 33 Ϫ10.52 0.000 4.84 0.783 77 38–115 55 Vanuatu Melanesia Van 51 Ϫ20.83 0.000 5.45 0.423 87 46–124 55 America Chile Chi 45 Ϫ12.33 0.000 10.79 0.754 59 26–99 8 Colombia Col 20 Ϫ0.74 0.374 9.89 0.020 67 34–99 8 Kuna Panama Kun 63 2.78 0.868 5.29** 0.054 43 13–87 37 Mapuche Argentina Map 39 Ϫ0.39 0.490 7.52 0.009 76 41–106 60 Ngobe Panama Ngo 46 3.39 0.902 5.50** 0.056 45 15–140 36 Nuu-Chah-Nulth Canada Nuu 63 Ϫ11.29 0.002 7.20 0.465 55 28–82 3 Africa !Kung Botswana Kng 25 Ϫ1.74 0.198 1.14** 0.138 9 0–81 7 East Pygmies Rep. Congo Pyg 20 Ϫ0.02 0.520 9.95 0.004 81 37–129 7 Fulbe Ful 61 Ϫ23.51 0.000 7.20 0.444 59 35–112 40 Hausa Nigeria Hau 20 Ϫ13.64 0.000 7.18 0.833 59 33–77 40 Herero Botswana Her 27 0.24 0.589 5.09** 0.205 51 16–67 7 Kikuyu Kenya Kik 25 Ϫ13.70 0.000 9.38 0.258 77 44–145 40 Mandenka Senegal Man 119 Ϫ25.03 0.000 6.72 0.847 68 36–154 61 Somali Som 27 Ϫ14.89 0.000 8.90 0.786 73 45–91 40 Tuareg Niger Tua 26 Ϫ10.26 0.001 5.83 0.177 48 30–93 40 Turkana Kenya Tur 37 Ϫ24.47 0.000 13.40 0.523 110 73–138 40 Yoruba Nigeria Yor 34 Ϫ25.15 0.000 7.78 0.764 64 39–104 7, 40 Europe, Middle East, India Albania Alb 42 Ϫ25.54 0.000 3.62 0.638 37 21–76 Unpubl. Algeria Alg 85 Ϫ12.06 0.002 6.51 0.074 66 35–95 62 Basques 1 Ba1 45 Ϫ22.54 0.000 2.17 0.267 18 6–58 63 Basques 2 Ba2 61 Ϫ26.58 0.000 2.07 0.491 21 8–60 62 Bavaria Bav 49 Ϫ25.96 0.000 3.97 0.771 40 24–50 64 Bulgaria Bul 30 Ϫ14.40 0.000 4.11 0.435 34 19–67 65 Cornwall Cor 69 Ϫ26.11 0.000 1.91 0.612 19 6–44 64 Denmark Den 33 Ϫ18.79 0.000 6.25 0.320 63 33–92 64 England Eng 100 Ϫ25.71 0.000 2.98 0.771 24 11–68 66 Estonia Est 28 Ϫ18.77 0.000 2.80 0.766 23 9–52 67 Finland Fin 50 Ϫ25.94 0.000 4.21 0.754 34 20–42 67 Germany Ger 106 Ϫ25.54 0.000 4.22 0.402 43 32–62 64 Havik India Hav 48 Ϫ18.27 0.000 4.60 0.495 35 20–80 68 Iceland Ice 39 Ϫ22.19 0.000 4.61 0.223 38 24–60 67 German speakers
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