2013
DOI: 10.1093/molbev/mst156
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Human Genetic Data Reveal Contrasting Demographic Patterns between Sedentary and Nomadic Populations That Predate the Emergence of Farming

Abstract: Demographic changes are known to leave footprints on genetic polymorphism. Together with the increased availability of large polymorphism data sets, coalescent-based methods allow inferring the past demography of populations from their present-day patterns of genetic diversity. Here, we analyzed both nuclear (20 noncoding regions) and mitochondrial (HVS-I) resequencing data to infer the demographic history of 66 African and Eurasian human populations presenting contrasting lifestyles (nomadic hunter-gatherers,… Show more

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Cited by 41 publications
(40 citation statements)
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“…This suggests that strong Paleolithic expansions may have ultimately favored the emergence of agriculture in some populations. 17 However, as ancient expansions could have masked potential signals of more recent expansions, these findings do not preclude the possibility of a second expansion event resulting from the Neolithic transition. Indeed, strong ancient demographic events are more easily detected with coalescent-based methods, and, in some cases, they can mask the signals of more recent events, especially if the population has not yet reached genetic equilibrium.…”
Section: Introductionmentioning
confidence: 87%
See 1 more Smart Citation
“…This suggests that strong Paleolithic expansions may have ultimately favored the emergence of agriculture in some populations. 17 However, as ancient expansions could have masked potential signals of more recent expansions, these findings do not preclude the possibility of a second expansion event resulting from the Neolithic transition. Indeed, strong ancient demographic events are more easily detected with coalescent-based methods, and, in some cases, they can mask the signals of more recent events, especially if the population has not yet reached genetic equilibrium.…”
Section: Introductionmentioning
confidence: 87%
“…16 Similarly, our previous work on HVS-1 data demonstrated strong signals of expansion in both African and Eurasian sedentary farmer populations, weaker expansion signals in Eurasian herders and no signal in African hunter-gatherers. 17 All these studies reported expansions that started during the Paleolithic. Here, using autosomal microsatellite data, although confidence intervals were quite large, we inferred modal estimates for the expansion onsets during or after the Neolithic transition for all farmer populations in Africa and Eurasia, as well as for herder populations in Central Asia.…”
Section: Contrasted Demographic Histories Associated With Different Lmentioning
confidence: 99%
“…We show that the effective population size of RHG is B30% lower than that of AGR, at least in Western Central Africa, as a result of a bottleneck and an expansion occurring earlier than 7,000 YBP in the ancestors of RHG and AGR, respectively. Previous studies have indeed estimated that the ancestors of African farmers started to expand B10,000-30,000 YBP using other aspects of the data such as the allele frequency spectrum [58][59][60] . Our analyses of LD levels thus reinforce these findings, and support the notion that the expansions of Bantu-speaking peoples 3,000-5,000 YBP are not sufficient to explain the signal of population growth observed in present-day AGR.…”
Section: Discussionmentioning
confidence: 99%
“…Using Simcoal version 2.1.2, 26 we simulated here both DNA sequences (mitochondrial or autosomal) and microsatellite (autosomal or from the Y chromosome) data sets under several scenarios involving either one or two successive expansion events, starting at different points in time, consistent with either a Paleolithic or a Neolithic expansion. These data sets were similar to those used in Aimé et al 4,20,25 in terms of numbers of loci.…”
Section: Introductionmentioning
confidence: 87%
“…For the autosomal sequences, we simulated 20 unlinked diploid sequences of 1300 base pairs (bp) to be consistent with existing short neutral sequence marker sets, such as the one developed by Patin et al 28 used in Aimé et al 20 We assumed a mutation rate of 2.5 × 10 − 8 per generation and per site. 29 For the mitochondrial sequences, we simulated a haploid sequence of 400 bp, corresponding to the HVS-I region, assuming a mutation rate of 10 − 5 per generation per site.…”
Section: Data Simulationmentioning
confidence: 99%