Article

Resequencing data provide no evidence for a human bottleneck in Africa during the penultimate glacial period.

Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.
Molecular Biology and Evolution (Impact Factor: 14.31). 02/2012; 29(7):1851-60. DOI: 10.1093/molbev/mss061
Source: PubMed

ABSTRACT Based on the accumulation of genetic, climatic, and fossil evidence, a central theory in paleoanthropology stipulates that a demographic bottleneck coincided with the origin of our species Homo Sapiens. This theory proposes that anatomically modern humans--which were only present in Africa at the time--experienced a drastic bottleneck during the penultimate glacial age (130-190 kya) when a cold and dry climate prevailed. Two scenarios have been proposed to describe the bottleneck, which involve either a fragmentation of the range occupied by humans or the survival of one small group of humans. Here, we analyze DNA sequence data from 61 nuclear loci sequenced in three African populations using Approximate Bayesian Computation and numerical simulations. In contrast to the bottleneck theory, we show that a simple model without any bottleneck during the penultimate ice age has the greatest statistical support compared with bottleneck models. Although the proposed bottleneck is ancient, occurring at least 130 kya, we can discard the possibility that it did not leave detectable footprints in the DNA sequence data except if the bottleneck involves a less than a 3-fold reduction in population size. Finally, we confirm that a simple model without a bottleneck is able to reproduce the main features of the observed patterns of genetic variation. We conclude that models of Pleistocene refugium for modern human origins now require substantial revision.

0 Bookmarks
 · 
114 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The majority of sub-Saharan Africans today speak a number of closely related languages collectively referred to as ‘Bantu’ languages. The current distribution of Bantu-speaking populations has been found to largely be a consequence of the movement of people rather than a diffusion of language alone. Linguistic and single marker genetic studies have generated various hypotheses regarding the timing and the routes of the Bantu expansion, but these hypotheses have not been thoroughly investigated. In this study, we re-analysed microsatellite markers typed for large number of African populations that—owing to their fast mutation rates—capture signatures of recent population history. We confirm the spread of west African people across most of sub-Saharan Africa and estimated the expansion of Bantu-speaking groups, using a Bayesian approach, to around 5600 years ago. We tested four different divergence models for Bantu-speaking populations with a distribution comprising three geographical regions in Africa. We found that the most likely model for the movement of the eastern branch of Bantu-speakers involves migration of Bantu-speaking groups to the east followed by migration to the south. This model, however, is only marginally more likely than other models, which might indicate direct movement from the west and/or significant gene flow with the western Branch of Bantu-speakers. Our study use multi-loci genetic data to explicitly investigate the timing and mode of the Bantu expansion and it demonstrates that west African groups rapidly expanded both in numbers and over a large geographical area, affirming the fact that the Bantu expansion was one of the most dramatic demographic events in human history.
    Proceedings of the Royal Society B: Biological Sciences 09/2014; 281(1793). · 5.29 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Elucidating the history of Homo sapiens has been a passion shared by many researchers spanning several decades. There are now overwhelming lines of evidence from genetic, archaeological, palaeoanthropological and, to some extent, palaeoenvironmental research, that place Africa as the region of origin of our species. The different fields of study use diverse types of data, and methods are subject to variances introduced by mutation rates, time estimates and/or sampling biases. All of these approaches have their respective shortcomings and error ranges and are accompanied by intense debate. Yet, it is timeous to review the most recent and salient highlights that the different approaches are contributing towards explaining our deep history and ancestry. It is, after all, one history, and consequently, there ought to be several convergent patterns between data sets. Our focus is to present an updated regional synthesis from each discipline for a specific window in time within the southern African context, namely between ~160 ka and 85 ka, and to speculate about possible connections between data sets for this period. Even though our focus is specific in time and space, it is not intended to consider southern Africa in isolation from the rest of Africa or to suggest a singular ‘origins’ locale for modern Homo sapiens. We hope that this integrated approach will stimulate discussions to include broader time periods within Africa and between continents.
    South African Journal of Science 01/2013; 109(11/12). · 0.84 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Inference of population demographic history has vastly improved in recent years due to a number of technological and theoretical advances including the use of ancient DNA. Approximate Bayesian computation (ABC) stands among the most promising methods due to its simple theoretical fundament and exceptional flexibility. However, limited availability of user-friendly programs that perform ABC analysis renders it difficult to implement, and hence programming skills are frequently required. In addition, there is limited availability of programs able to deal with heterochronous data. Here we present the software BaySICS: Bayesian Statistical Inference of Coalescent Simulations. BaySICS provides an integrated and user-friendly platform that performs ABC analyses by means of coalescent simulations from DNA sequence data. It estimates historical demographic population parameters and performs hypothesis testing by means of Bayes factors obtained from model comparisons. Although providing specific features that improve inference from datasets with heterochronous data, BaySICS also has several capabilities making it a suitable tool for analysing contemporary genetic datasets. Those capabilities include joint analysis of independent tables, a graphical interface and the implementation of Markov-chain Monte Carlo without likelihoods.
    PLoS ONE 01/2014; 9(5):e98011. · 3.53 Impact Factor

Full-text (2 Sources)

Download
13 Downloads
Available from
Jun 10, 2014