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Review
Evaluating the mitochondrial timescale
of human evolution
Phillip Endicott1, Simon Y.W. Ho2, Mait Metspalu3 and Chris Stringer4
1
Départment Hommes Natures Sociétés, Musée de l’Homme, 75116 Paris, France
Centre for Macroevolution and Macroecology, Research School of Biology, Australian National University,
Canberra ACT 0200, Australia
3
Institute of Molecular and Cell Biology, University of Tartu, and Estonian Biocentre, Estonia
4
Department of Palaeontology, Natural History Museum, London SW7 5BD, United Kingdom
2
Different methodologies and modes of calibration have
produced disparate, sometimes irreconcilable, reconstructions of the evolutionary and demographic history
of our species. We discuss how date estimates are
affected by the choice of molecular data and methodology, and evaluate various mitochondrial estimates of
the timescale of human evolution in the context of the
contemporary palaeontological and archaeological evidence for key stages in human prehistory. We contend
that some of the most widely-cited mitochondrial rate
estimates have several significant shortcomings, including a reliance on a human-chimpanzee calibration,
and highlight the pressing need for revised rate estimates.
Estimates of the timescale of human evolution
Current perspectives on the timescale of human evolution
and migration are based on a combination of palaeontological, archaeological, and genetic evidence. In many cases,
the three are in broad agreement, at least with respect to
the temporal order of population divergence events. Following the evolution of modern humans in Africa, recent
genetic diversity has resulted from continuing evolution in
Africa and a migration out-of-Africa. This migration traversed southern Asia and reached Australasia, and perhaps slightly later there was a wave of migration into
western Europe. Modern humans did not arrive in the
Americas until much later.
Despite these similarities in the broad outline of human
prehistory, persistent discrepancies are observed between
absolute date estimates based on palaeoanthropological
(palaeontological + archaeological) and genetic data.
Analyses of the latter have consistently yielded date estimates implying a more protracted timescale for later
events in human evolution than that indicated by the
dating of fossil material and associated artefacts. A welldebated example is the colonisation of the Americas, which
a number of molecular studies have placed prior to the Last
Glacial Maximum [1–3]. In contrast, the oldest wellaccepted archaeological evidence remains less than 15
ka old [4], despite intensive research and improved dating
analyses [5].
This raises the important question of how reliable the
genetic estimates of human evolution might be, and the
Corresponding author: Ho, S.Y.W. ([email protected]).
nature of the molecular clock on which they rely. A revision
of the methods or calibrations used to estimate dates from
molecular data could have widespread implications for the
interpretation of the timescale of human evolution, including the date of divergence from Neanderthals and
the timing of the migration out of Africa.
Date estimates from mitochondrial DNA
Molecular estimates of human evolutionary timeframes
have typically been made by applying one of a number
of published substitution rate estimates to mitochondrial
DNA (mtDNA) sequence data. Human mtDNA exhibits
considerable heterogeneity in substitution rates among
sites, with the result that it is common practice to treat
different portions of the genome separately (Box 1). Some
of the most frequently used and cited estimates of mtDNA
rates are those of Forster et al. [3] for the first hypervariable sequence (HVS1) of the control region, Mishmar et al.
[6] for the coding region, and Kivisild et al. [7] for synonymous changes at protein-coding sites.
The majority of published rate estimates for human
mtDNA, including those of Mishmar and Kivisild, have
been calibrated with reference to the human-chimpanzee
divergence. In the simplest case, the genetic difference
between humans and chimpanzees is divided by the time
since their divergence, to obtain an estimate of the rate per
year. The employment of this calibration typically relies on
two assumptions: (i) that the genetic separation between
humans and chimpanzees occurred about 6 million years
ago; and (ii) that the molecular evolutionary process has
been clocklike since the human-chimpanzee divergence
until the present day.
Both of the assumptions underlying the human-chimpanzee calibration are of contestable validity. First, there
is uncertainty over the exact timing of the human-chimpanzee divergence. A recent review of molecular estimates
suggested a possible age range of 4-8 million years [8],
whereas the fossil record indicates that the split occurred
at least 6 million years ago [9]. Thus, the first assumption
can lead to estimates of molecular rates and associated
chronologies that are inaccurate and artificially precise.
The second assumption is that the molecular evolutionary process along the human and chimpanzee lineages, as
well as among humans, has been relatively homogeneous
and neutral. In practice, this assumption is reflected in the
usage of methods based on a strict molecular clock [6,7].
0169-5347/$ – see front matter ß 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.tree.2009.04.006
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Box 1. Variability of evolutionary rates across the mitochondrial genome
The human mitochondrial genome mutates at a high rate relative to
the nuclear genome and is subject to substantial purifying selection
[7,10–14]. This will lead to an excess of coding-region polymorphisms towards the younger parts of the human tree [20,61–63].
Additionally, the influence of saturation and selection varies along
the length of the molecule, leading to heterogeneity in rates among
sites (Figure I). The magnitude of these effects has resulted in an
analytical separation of the mtDNA molecule into the coding and
control regions, reflected in the two most widely cited mtDNA
substitution rates: (i) 1.7910-7 subs/site/year for 276 bp of the first
hypervariable section (HVS1) of the control region by Forster et al.
[3], and (ii) 1.2610-8 subs/site/year for the coding region by
Mishmar et al. [6]. In addition to these, Kivisild et al. [7] estimated
a rate of 3.510 -8 subs/site/year for synonymous changes in
mitochondrial protein-coding genes.
The HVS1 rate by Forster et al. [3] was obtained using a networkbased approach and calibrated on an intraspecific timescale using an
archaeological horizon. It is substantially slower than a rate calibrated
by a directly-dated fossil human (3.4 - 4.410-7 subs/site/year for
360 bp of HVS1 [64]). These faster rates appear more compatible with
those from human pedigree studies for the control region, which
average 4.7510-7 subs/site/year [19]. Some of this difference might
be due to the use of uncorrected genetic distances, which do not
compensate for sequence saturation, rate heterogeneity among sites,
or departures from a molecular clock, which all affect this section of
the mtDNA genome [17,65]. Demographic factors can also have a
strong influence on network-based approaches for inferring rates and
dates [22,23].
The estimate of the coding-region rate by Mishmar et al. [6] was
obtained using genetic distances assuming the HKY model of
nucleotide substitution, which corrects for multiple hits. The rate
estimate was calibrated by assuming a human-chimpanzee divergence at 6.5 million years ago. Consequently, this rate will be dictated
primarily by the rate of substitutions along the evolutionary branches
connecting humans and chimpanzees.
The synonymous coding-region rate presented by Kivisild et al. [7],
although calibrated by reference to the human-chimpanzee split, is
likely to have improved accuracy over an intraspecific timescale due
to (i) the relaxation of selective constraints operating on synonymous
changes, (ii) lower saturation (compared to the control region), and
(iii) a considerable reduction in the confounding effect of rate
heterogeneity among sites [16].
Figure I. Variation in substitution rates across the human mitochondrial genome
A graphical representation of the variation in nucleotide substitution rate across different regions of the human mitochondrial genome (from the data set of Endicott and
Ho [16]). The Y-axis represents the relative rate and the X-axis the position in each data class. This particular analysis excludes a subset of the molecule (rRNA stems,
tRNA genes, the ND6 gene, and intergenic regions) to simplify the modelling process [16]. Of the four data partitions (control region, rRNA loops, first+second codon
sites, and third codon sites), the control region displays the highest rates and greatest variation across its length. The relative homogeneity of rates at third codon
positions of protein-coding genes is related to the fact that many changes at these sites are silent (synonymous) in nature. Mutations at the first and second codon
positions produce far more non-synonymous changes and are subject to greater selective pressure. Despite exhibiting considerable rate variation among sites, the
highly variable control region, particularly hypervariable sections 1 and 2 (HVS1 and HVS2), remains a valuable source of information because of the substantial amount
of diversity within this short length of the mitochondrial genome.
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There are two lines of evidence that cast doubt on the
legitimacy of these assumptions. First, human mtDNA
appears to be subject to widespread purifying selection
[7,10–14]. Second, studies of human mtDNA have shown
that older calibrations tend to produce slower rate and
older date estimates [15–18]. In particular, the disparity
between pedigree- and phylogeny-based rate estimates is
conspicuous [19–21].
The coding-region rate estimate of Mishmar et al. [6] is
based on genetic distances corrected using the HKY model
of nucleotide substitution, calibrated by assuming that
humans and chimpanzees diverged 6.5 million years
ago. Kivisild et al. [7] employed the same calibration to
estimate the substitution rate for synonymous changes in
protein-coding genes. Numerous other studies of human
mtDNA use the human-chimpanzee calibration directly,
by including a chimpanzee sequence and fixing the age of
their divergence in the dating analysis.
The HVS1 rate of Forster et al. [3] was derived using a
network-based method, calibrated by assuming that the
expansion of human mtDNA haplogroup A2 occurred 11.3
ka ago. This approach yielded a rate estimate of one
transition every 20.3 ka.
Although all three rates were derived using different
methodologies, they share a common reliance on the rho
summary statistic [3], which is a measure of the average
number of polymorphisms along unique lineages deriving
from the ancestral node of a resolved genealogical tree. A
rigorous statistical re-evaluation of the accuracy and utility of this scalar indicates that rho can produce biased date
estimates with large asymmetrical variances [22]. Genetic
dating performed using rho can be particularly distorted if
the sequence data have not evolved with a constant population size through time; for example, due to the presence
of founder events, changes in effective population size and
bottlenecks, all features of human prehistory [22,23]. The
performance of the rho summary statistic will be further
compromised by the effects of natural selection, rate variation among sites, and rate heterogeneity among lineages
[22].
Given these growing concerns, a reconsideration of
published mtDNA rates is warranted. The need for revised
rate estimates is becoming increasingly clear, in view of the
expanding database of whole mitochondrial genomes and
our growing ability to model the molecular evolutionary
process more realistically. Models of nucleotide substitution can accommodate rate heterogeneity among sites,
while correcting for multiple hits. Relaxed molecular-clock
models allow different rates among lineages, which can
ameliorate the confounding impacts of natural selection,
albeit indirectly. Multiple age calibrations derived from
archaeological or palaeontological sources, along with their
associated uncertainty, can be incorporated in a molecular
dating analysis. Recent developments, such as those in
Bayesian phylogenetic methodology, have enabled these
various models and approaches to be implemented within a
single framework [24].
In a significant attempt to address some of these concerns, Soares et al. [14] recently proposed an alternative
method for estimating dates using human mtDNA. Their
approach involves a post-hoc correction formula designed
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to account for the confounding effects of saturation and
purifying selection. Although the formula is calibrated
using a point estimate of the human-chimpanzee divergence, the approach differs substantially from previously
proposed mtDNA clocks because it does not assume rate
constancy across different time periods. However, the
method does not allow for rate variation among contemporaneous lineages, which is a known feature of human
mtDNA evolution.
Implications of different rates for interpretations of
human evolution
The genetic chronology for the Out-of-Africa dispersal
generated by the Mishmar rate has been used to suggest
a modern human presence in South Asia prior to the Toba
eruption 74 ka ago [25]. This is a critical issue because the
archaeological evidence (Jwalapuram in Figure 1) suggests
a cultural continuity of lithic complexes in South Asia
across this well-dated horizon [25]. So a genetic chronology
that puts modern humans in Asia prior to the Toba eruption at 74 ka informs this interpretation of cultural continuity and suggests that they managed to overcome any
adverse conditions associated with this major volcanic
eruption. However, there is currently no mitochondrial
or Y-chromosomal evidence for multiple migrations of
early modern humans from Africa [26], nor are there
human fossils associated with the Jwalapuram lithics.
In fact, the first dated modern human occupations in the
region come from Batadomba lena and Fa Hien in Sri
Lanka at 28-34 ka [27]. So, if the genetic dates for
Out-of-Africa post-date the Toba eruption, then the preToba Jwalapuram tools would instead represent important
archaeological evidence for a previous human migration
from Africa (comparable to Qafzeh and Skhul in the Middle
East at 90-115 ka), for which there is no surviving genetic
evidence; alternatively, this South Asian lithic complex
was made by archaic humans, a conclusion that would
require a further revision of presumed associations between technological complexes and specific hominins [28].
Regardless of any revision to the absolute chronology for
the appearance of modern humans outside of Africa, the
contemporary pattern of human mtDNA confirms a West
to East migration from Africa [26]. It is significant that,
based on mtDNA data, the time between the establishment
of modern humans outside of Africa and their arrival in
Australia appears to have been very short, perhaps as little
as 3 ka [29,30]. Therefore, if modern humans with mtDNA
ancestral to today’s diversity were responsible for the tools
at Jwalapuram, this would imply their subsequent arrival
in Australia by about 70 ka, in contradiction to all the
available palaeoanthropological data. Using the lower
mean for the Out-of-Africa movement (derived from the
dating of macrohaplogroups M and N by either the Mishmar or Soares rate) would place their arrival in Australia
by at least 60 ka. However, the redating of Lake Mungo 3
(LM3) to 40 ka [31] results in a minimum 20 ka gap
between the earliest unambiguous human remains in the
continent and these genetic estimates. The revised dates
for LM3 render disputed evidence for novel mtDNA
sequences [32,33] even more contentious and these are
not considered here, pending ongoing reanalysis.
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Figure 1. Human origins and Out-of-Africa
Illustrative world map showing the locations and dates for the fossil and archaeological complexes associated with anatomically modern humans (AMH) considered in the
text, together with the Siberian fossil from Mal’ta, dated at 28 ka. These are complemented by dated fossil locations for archaic humans outside of Africa during the Late
Pleistocene, together with two key earlier sites, Swanscombe and Atapuerca, which provide age estimates for the first appearance of Neanderthal features [46,59,66–70].
Dates given are best estimates from published data cited in the text. These palaeoanthropological data form the backdrop for the three mtDNA-based reconstructions of the
origin and early migrations of AMH using three different DNA coding-region substitution rates, shown here in colour-coded polygons. These are presented as different
layers and the respective time estimates are given in tabs (see inset top left). The geographic positions of mitochondrial ‘Eve’ and the putative migration routes are meant to
be indicative rather than precise (e.g., Bab el-Mandeb is not established as a route used in the Out-of-Africa dispersals). The coalescence of all haplogroup L3 lineages is
taken as the lower estimate for the Out-of-Africa migration and the average coalescence of haplogroups M and N (which make up the human mtDNA variation outside
Africa) as the upper estimate (n.b. The recent application of the Mishmar rate to a wholly African mtDNA data set produces a younger date for L3, but for the sake of
consistency we restrict the comparative analysis to dates generated by data sets similar to that used in [6]).
There is evidence for slightly earlier human activity in
Australia and neighbouring New Guinea (45 ka) [31],
and lithics might occur marginally earlier than this (but
compare [34] and [31]). An upward revision of the substitution rate for coding-region mtDNA [7,16,35] would lead
to a contraction of the estimated genetic timeframe, substantially reducing this period of invisibility for modern
humans in the archaeological record of Australia. In
Southeast Asia there is a similar pattern, with human
remains in Niah cave dated to 37-38 ka [36] and lithic
evidence slightly earlier [37] (Figure 1). The human
remains from Laibin (38-44 ka) [38] and Tianyuan (3942 ka) [39] in China also fall into this timeframe, consistent with modern humans having reached East Asia
around the same time they first appear in Australia and
New Guinea. The exception is the earlier age (>68 ka)
claimed for the anatomically modern Liujiang skeleton
[40], but given stratigraphic uncertainties [41] and experiences with other ‘‘ancient moderns’’ in China [42], this
requires confirmation by direct dating.
The palaeoanthropological evidence for the arrival of
modern humans into Europe is particularly well studied
and was recently recalibrated using improved radiocarbon
methods [43]. Here too, the earliest direct evidence for
modern humans falls around 40 ka at Oase [44], with
lithics at Kostenki dated at 42-45 ka [45]. These dates fall
squarely within the temporal distribution of early Upper
518
Palaeolithic sites widely believed to be associated with the
dispersal of modern humans [46]. Equivalent sites in the
Near East have slightly earlier chronologies (but also
larger confidence intervals), consistent with an East to
West direction of movement of people and technologies.
The Initial Upper Palaeolithic industries of Üçagzl
(Turkey) and Ksar’Akil (Lebanon), and the early modern
fossil from the latter site, might well map such ancestral
populations at about 40-45 ka [47,48].
Therefore, there is a consistent gap of 20 ka between
the genetic estimates (based on mtDNA) and palaeoanthropological chronologies (based on human skeletal
material and tools) for all regions beyond South Asia using
mtDNA substitution rates equivalent to the magnitude
proposed by Mishmar. The lacuna in South Asia appears to
be even greater because there is sound genetic evidence
that population expansion in modern humans commenced
here substantially before other regions outside of Africa
[35]. Therefore, whether the Jwalapuram tools are attributed to modern humans or not, the South Asian archaeological record demonstrates that it is possible to have
large gaps, presumably influenced by rates of preservation
and recovery. Nevertheless, the consistent absence of modern human remains and/or associated lithic complexes
until the period of 40-50 ka in Europe, the Near East,
Southeast Asia, East Asia, Australia, and Island Melanesia, is striking.
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Figure 2. Comparing different timescales of hominin evolution
Graphical representation of the effect of three human mitochondrial DNA (mtDNA) clock calibrations (synonymous transitions clock [7]; whole coding-region clock [6] (or
equivalent rate of [29] for haplogroup L3); and Bayesian clock with biogeographic calibrations [16]), compared with the palaeoanthropological estimates for the four event
horizons discussed in the main text. The mitochondrial most recent common ancestor (MRCA) of Neanderthals and anatomically modern humans (AMH) is provided for
each substitution rate, with a fourth estimate made from cranial measurements from 2,500 modern humans and 20 Neanderthal fossils [58]. An illustrative indication of
climate fluctuations during the past 500 ka, together with Marine Isotope Stages (MIS) corresponding to the interglacial periods is also provided. Bars on top of the tree
depict the nested structure of mtDNA haplogroups relevant to the current comparison. All subsequent molecular estimates within the human phylogeny come from the
same sources except those for the peopling of the Americas [71]. For the palaeoanthropological estimates of anatomically modern humans outside of Africa we used the
maximum average estimate of reliably dated fossils (see main text for details), and indicate the uncertainty over African ancestral fossils by broken lines. The estimate for
the MRCA of AMHs and Neanderthals based on the Mishmar rate utilised the same 178 genomes (177 human plus one Neanderthal) used for the Bayesian calculation [16],
whilst that using the Kivisild rate compared the revised Cambridge Reference Sequence to the Vindija genome. The molecular date estimates for the MRCA of AMH are
taken from the literature and represent the coalescence time between L0 and L1’L5 lineages. All other details are given in the text.
In this context it is important to remember that the
original ‘Southern Route’ hypothesis for human migrations
Out-of-Africa was predicated upon the gap between
archaeological evidence for human settlement of Europe
at 45 ka and the dates from Australia, which at that time
suggested settlement as early as 65 ka [49]. This 20 ka
gap, which has largely disappeared with the re-evaluation
of sites such as LM3 [31,34], might have influenced
acceptance of the scale of the absolute genetic chronology
generated by the Mishmar rate [29,50]. It should be
acknowledged that dates for the population divergence
between African and non-African populations, based on
the coalescence of mtDNA lineages, will depend on the
effective population size [23]. Our primary focus here,
however, is on the causes of the difference in relative
chronology between the three different substitution rates
used to date the migration Out-of-Africa rather than evaluation of the demographic assumptions underlying their
interpretations of human prehistory.
The early African palaeoanthropological record is difficult to interpret because of the great variability in conditions of preservation and the issue of determining which
fossils represent the earliest examples of ‘‘modern’’ Homo
sapiens. This depends on the diagnostic characteristics
used [51], but the Ethiopian specimens Omo Kibish 1
(98-192 ka), Herto 16/1, and Herto 16/5 (150-161 ka) do
appear to fall into the modern human pattern of cranial
shape [51,52] (Figures 1 and 2). These early examples are
followed by a relative proliferation of well-dated African
specimens after 100 ka, including the Border Cave fossils
(e.g. BC5 61-91 ka ago [52,53]), and those from sites such
as Aduma, Dar-es-Soltane 2, and Klasies River Mouth
Caves, 64-104 ka ago [52,54,55]. This general pattern
is consistent with a geographical expansion of modern
humans within Africa and into the Near East (Qafzeh
and Skhul [52]) during the climatic amelioration associated with Marine Isotope Stage 5 (MIS5) (Figure 2).
The preceding MIS6 was the longest and most severe
glacial period of the last 200 ka, and a prolonged genetic
bottleneck might have affected both modern human populations and Neanderthals at this time. This effect might
have produced a genetic most recent common ancestor
(MRCA) for humans the same age or younger than the
earliest morphological evidence [7,16]. However, it should
be noted that, without various demographic assumptions,
the mtDNA MRCA might tell us more about the long-term
effective population size than it does about the origin and
demographic history of humans [23].
The mitochondrial genome of the Vindija Neanderthal
[56] allows us to perform a comparative exercise estimating the mitochondrial MCRA dates for modern humans
and Neanderthals using the rates of Kivisild (366 ka,
including a correction for saturation by the Jukes-Cantor
model) and Mishmar (450 ka) (Figure 2). Our own estimate was performed using only third codon sites in a
Bayesian phylogenetic framework, correcting for rate
heterogeneity and employing a relaxed clock calibrated
by the age of the directly-dated Vindija Neanderthal
(assigned a calendar date of 42 ka [57]) and by three
nodes within the L3 portion of the human mtDNA tree
[16]. This produced a younger date centred on 301 ka (95%
highest posterior density: 231-383 ka), although this is
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probably an underestimate resulting from our use of
relatively young calibrations. By comparison, the
palaeoanthropological date depicted in Figure 2, based
on cranial measurements of 2,500 modern humans and
20 Neanderthal fossils [58], is the average of two means
with a combined 95% credible interval of 182-592 ka.
All of these estimates for the genetic MRCA differ
significantly from the Bayesian estimate of 660 ka made
by Green et al. [56], which was calibrated on the divergence
of humans and chimpanzees. In contrast, the consensus of
somewhat younger dates envisaged by alternative substitution rates and methodologies used here suggests an
upper bound for a mitochondrial MRCA of humans and
Neanderthals of around 450 ka, whereas the correctionformula method of Soares et al. [14] yields a mean value of
550 ka. When considering the implications of these competing chronologies it needs to be remembered that genetic
divergence should precede the accumulation of sufficient
morphological characters to allow the recognition of
species divergence in the paleoanthropological record.
The apparent presence of morphological features in Europe
indicating ancestry to Neanderthals prior to the majority of
these dates [59] suggests that the palaeoanthropological
record of this important period of human prehistory might
require further calibration and evaluation; refining this
chronology should help to elucidate hominin evolution in
general.
Concluding Remarks
Further research is needed to improve our confidence in
molecular estimates of human evolutionary timescales.
First, the most reliable calibrations within the human tree
need to be identified. For mitochondrial DNA, this depends
on finding well-defined haplogroups that can be precisely
associated with dated palaeoanthropological evidence [17].
Second, the variation in observed rates across different
timescales needs to be accurately quantified [16–18].
Third, these patterns of rate variation need to be investigated for nuclear data, including the Y-chromosome and
short tandem repeats.
The chief recommendation arising from the current
state of knowledge in the field is for a movement away
from reliance on the human-chimpanzee calibration;
instead, calibrations within the human tree are preferred
(but see [14]). There are several recent examples of estimates made using archaeological calibrations [15–17,35],
extending the efforts of earlier authors [3,60]. Considering
recent advances in phylogenetic methodology, there is now
a compelling motivation to employ statistical models that
take into account rate heterogeneity among sites and
among lineages, that correct for multiple substitutions
(saturation), and that incorporate directly the uncertainty
in the ages of calibrations used. Some methods also allow
the statistical evaluation of competing demographic
models, which can have an important influence on estimates of rates and timescales [17,23].
Acknowledgements
We are grateful to Juan Sanchez, George Weber, Evelyne Heyer, Katrina
Lythgoe, and four reviewers for suggestions to improve this manuscript.
The map in Figure 1 was kindly provided by Nobuyuki Yamaguchi. We
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also would like to thank Svante Pääbo, Ed Green, and co-authors for
permission to use the complete sequence of the Neanderthal mtDNA prior
to its publication. Support was provided by the Australian Research
Council (SYWH) and by EC grant ECOGENE to the Estonian Biocentre
(PE and MM). CS is a member of the Ancient Human Occupation of
Britain Project, funded by the Leverhulme Trust.
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