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00 MONTH 2018 | VOL 000 | N A T URE | 1
ARTICLE doi:10.1038/nature25738
The Beaker phenomenon and the genomic
transformation of northwest Europe
A list of authors and their affiliations appears at the end of the paper.
During the third millennium bc, two new archaeological pottery styles
expanded across Europe and replaced many of the more localized styles
that had preceded them1. The expansion of the ‘Corded Ware com-
plex’ in north-central and northeastern Europe was associated with
people who derived most of their ancestry from populations related
to Early Bronze Age Yamnaya pastoralists from the Eurasian steppe
2–4
(henceforth referred to as ‘steppe’). In western Europe there was the
equally expansive ‘Bell Beaker complex’, defined by assemblages of
grave goods that included stylized bell-shaped pots, copper daggers,
arrowheads, stone wristguards and V-perforated buttons
5
(Extended
Data Fig. 1). The oldest radiocarbon dates associated with Beaker pot-
tery are from around 2750bc in Atlantic Iber ia
6
, which has been inter-
preted as evidence that the Beaker complex originated in this region.
However, the geographic origins of this complex are still debated7
and other scenarios—including an origin in the Lower Rhine area,
or even multiple independent origins—are possible (Supplementary
Information section 1). Regardless of geographic origin, by 2500bc the
Beaker complex had spread throughout western Europe and northwest
Africa and had reached southern and Atlantic France, Italy and central
Europe5, where it overlapped geographically with the Corded Ware
complex. Within another hundred years, it had expanded to Britain
and Ireland
8
. A major debate in archaeology has revolved around the
question of whether the spread of the Beaker complex was mediated by
the movement of people, culture or a combination of both9. Genome-
wide data have revealed high proportions of steppe-related ancestry in
Beaker-complex-associated individuals from Germany and the Czech
Republic2–4, which shows that these individuals derived from mixtures
of populations from the steppe and the preceding Neolithic farmers of
Europe. However, a deeper understanding of the ancestry of people
associated with the Beaker complex requires genomic characterization
of individuals across the geographic range and temporal duration of
this archaeological phenomenon.
Ancient DNA data
To understand the genetic structure of ancient people associated with
the Beaker complex and their relationship to preceding, subsequent and
contemporary peoples, we used hybridization DNA capture4,10 to enrich
From around 2750 to 2500 BC, Bell Beaker pottery became widespread across western and central Europe, before
it disappeared between 2200 and 1800 BC. The forces that propelled its expansion are a matter of long-standing
debate, and there is support for both cultural diffusion and migration having a role in this process. Here we present
genome-wide data from 400 Neolithic, Copper Age and Bronze Age Europeans, including 226 individuals associated with
Beaker-complex artefacts. We detected limited genetic affinity between Beaker-complex-associated individuals from
Iberia and central Europe, and thus exclude migration as an important mechanism of spread between these two regions.
However, migration had a key role in the further dissemination of the Beaker complex. We document this phenomenon
most clearly in Britain, where the spread of the Beaker complex introduced high levels of steppe-related ancestry and
was associated with the replacement of approximately 90% of Britain’s gene pool within a few hundred years, continuing
the east-to-west expansion that had brought steppe-related ancestry into central and northern Europe over the
previous centuries.
ancient DNA libraries for sequences overlapping 1,233,013 single
nucleotide polymorphisms (SNPs), and generated new sequence
data from 400 ancient Europeans dated to between approximately
4700 and 800bc, excavated from 136 different sites (Extended Data
Ta bl es 1, 2; Supplementary Table 1; Supplementary Information
section 2). This dataset includes 226 Beaker-complex-associated
individuals from Iberia (n = 37), southern France (n = 4), northern
Italy (n = 3), Sicily (n = 3), central Europe (n = 133), the Netherlands
(n = 9) and Britain (n = 37), and 174 individuals from other ancient
populations, including 118 individuals from Britain who lived both
before (n = 51) and after (n = 67) the arrival of the Beaker complex
(Fig. 1a, b). For genome-wide analyses, we filtered out first-degree
relatives and individuals with low coverage (fewer than 10,000 SNPs)
or evidence of DNA contamination (Methods) and combined our
data with previously published ancient DNA data (Extended Data
Fig. 2) to form a dataset of 683 ancient samples (Supplementary
Table 1). We merged these data with those from 2,572 present-day
individuals genotyped on the Affymetrix Human Origins array11,12
as well as with 300 high-coverage genomes13. To facilitate the inter-
pretation of our genetic results, we also generated 111 direct radio-
carbon dates (Extended Data Table 3; Supplementary Information
section 3).
Y- chr om os om e an al ys is
The Y-chromosome composition of Beaker-complex-associated males
was dominated by R1b-M269 (Supplementary Table 4), which is a lineage
associated with the arrival of steppe migrants in central Europe after
3000bc2,3. Outside Iberia, this lineage was present in 84 out of 90 ana-
lysed males. For individuals for whom we determined the R1b-M269
subtype (n = 60), we found that all but two had the derived allele for the
R1b-S116/P312 polymorphism, which defines the dominant subtype
in western Europe today
14
. By contrast, Beaker-complex-associated
individuals from the Iberian Peninsula carried a higher proportion of
Y haplogroups known to be common across Europe during the earlier
Neolithic period
2,4,15,16
, such as I (n = 5) and G2 (n = 1); R1b-M269 was
found in four individuals with a genome-wide signal of steppe-related
ancestry, and of these, the two with higher coverage could be classified
A list of authors and their affiliations appears at the end of the paper.
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as R1b-S116/P312. The widespread presence of the R1b-S116/P312
polymorphism in ancient individuals from central and western Europe
suggests that people associated with the Beaker complex may have had
an important role in the dissemination of this lineage throughout most
of its present-day distribution.
Spread of people associated with the Beaker complex
We performed principal component analysis by projecting the ancient
samples onto the genetic variation in a set of west Eurasian present-day
populations. We replicated previous findings
11
of two parallel clines,
with present-day Europeans on one side and present-day Near
Eastern populations on the other (Extended Data Fig. 3a). Individuals
associated with the Beaker complex are notably heterogeneous
within the European cline along an axis of variation defined by Early
Bronze Age Yamnaya individuals from the steppe at one extreme and
Middle Neolithic and Copper Age Europeans at the other extreme
(Fig. 1c; Extended Data Fig. 3a). This suggests that genetic differenti-
ation among Beaker-complex-associated individuals may be related
to variable amounts of steppe-related ancestry. We obtained quali-
tatively consistent inferences using ADMIXTURE model-based
clustering17. Beaker-complex-associated individuals harboured three
main genetic components: one characteristic of European Mesolithic
hunter-gatherers, one maximized in Neolithic individuals from the
Levant and Anatolia, and one maximized in Neolithic individuals from
Iran and present in admixed form in steppe populations (Extended
Data Fig. 3b).
Both principal component analysis and ADMIXTURE are powerful
tools for visualizing genetic structure, but they do not provide formal
tests of admixture between populations. We grouped Beaker-complex-
associated individuals on the basis of geographic proximity and genetic
similarity (Supplementary Information section 6), and used qpAdm
2
to
directly test admixture models and estimate mixture proportions. We
modelled their ancestry as a mixture of Mesolithic western European
hunter-gatherers, northwestern Anatolian Neolithic farmers and Early
Bronze Age steppe populations; the first two of these contributed to the
ancestry of earlier Neolithic Europeans. We find that in areas outside
of Iberia, with the exception of Sicily, a large majority of the Beaker-
complex-associated individuals that we sampled derive a considerable
portion of their ancestry from steppe populations (Fig. 2a). By contrast,
in Iberia such ancestry is present in only 8 of the 32 individuals that we
analysed; these individuals represent the earliest detection of steppe-
related genomic affinities in this region. We observed differences in
ancestry not only at a pan-European scale, but also within regions and
even within sites. For instance, at Szigetszentmiklós in Hungary, we
−0.03−0.02 −0.010 0.01
–0.06
–0.04
–0.02
0
0.02
0.04
Principal component 1
Principal component 2
Steppe
Early Bronze Age
Europe
Middle Neolithic and
Copper Age
Europe
Early Neolithic
Anatolia Neolithic
Corded Ware
−10° −5° 0° 5° 10° 15° 20° 25°
35°
40°
45°
50°
55°
60°
England_LBA
Scotland_LBA
Scotland_MBA
Wales_MBA
England_MBA
Wales_CA_EBA
Netherlands_BA
Czech_EBA
Poland_BA
Scotland_CA_EBA
England_CA_EBA
Beaker-associated (published)
Beaker-associated
Corded_Ware_Czech
Hungary_BA
Iberia_CA
Hungary_LCA
England_N
Scotland_N
Wales_N
France_MLN
1
5
4
2
20
1
2
16
3
9
25
10
226
3
4
18
4
14
35
2
4
Czech_MN 2
5000 4500 4000 3500 3000 2500 2000 1500 1000
Date (years
BC
)
ac
b
Britain
Southern France
Northern Italy
Iberia
Central Europe
The Netherlands
Sicily
Beaker-associated
Figure 1 | Spatial, temporal and genetic structure of individuals in
this study. a, Geographic distribution of samples with new genome-wide
data. Random jitter was added for sites with multiple individuals. Map
data from the R package ‘maps’. b, Approximate time ranges for samples
with new genome-wide data. Sample sizes are given next to each bar.
c,Principal component analysis of 990 present-day west Eurasian
individuals (grey dots), with previously published (pale yellow) and
new ancient samples projected onto the first two principal components.
This figure is a close-up of Extended Data Fig. 3a. See Methods for
abbreviations of population names.
00 MONTH 2018 | VOL 000 | N A T URE | 3
ARTICLE RESEARCH
found roughly contemporary Beaker-complex-associated individuals
with very different proportions (from 0% to 75%) of steppe-related
ancestry. This genetic heterogeneity is consistent with early stages of
mixture between previously established European Neolithic popula
-
tions and migrants with steppe-related ancestry. One implication of
this is that even at local scales, the Beaker complex was associated with
people of diverse ancestries.
Although the steppe-related ancestry in Beaker-complex-associated
individuals had a recent origin in the east2,3, the other ancestry
component—from previously established European populations—
could potentially be derived from several parts of Europe, because
groups that were genetically closely related were widely distributed
during the Neolithic and Copper Ages
2,4,11,16,18–23
. To obtain insight
into the origin of this ancestry component in Beaker-complex-
associated individuals, we looked for regional patterns of genetic
differentiation within Europe during the Neolithic and Copper Age.
We examined whether populations pre-dating the emergence of the
Beaker complex shared more alleles with Iberian (Iberia_EN) or
central European Linearbandkeramik (LBK_EN) Early Neolithic
popu lations (Fig. 2b). As previously described2, Iberian Middle
Neolithic and Copper Age populations, but not central and northern
European populations, had genetic affinities with Iberian Early
Neolithic farmers (Fig. 2b). These regional patterns could partially
be explained by differential genetic affinities to pre-Neolithic hunter-
gatherer individuals from different regions
22
(Extended Data Fig. 4).
Neolithic individuals from southern France and Britain are also
significantly closer to Iberian Early Neolithic farmers than they are
to central European Early Neolithic farmers (Fig. 2b), consistent
with a previous analysis of a Neolithic genome from Ireland23. By
modelling Neolithic populations and Mesolithic western European
hunter-gatherers in an admixture graph framework, we replicate these
results and show that they are not driven by different proportions of
hunter-gatherer admixture (Extended Data Fig. 5; Supplementary
Information section 7). Our results suggest that a portion of the
ancestry of the Neolithic populations of Britain was derived from
migrants who spread along the Atlantic coast. Megalithic tombs docu-
ment substantial interaction along the Atlantic façade of Europe24,
and our results are consistent with such interactions reflecting south-
to-north movements of people. More data from southern Britain and
Ireland and nearby regions in continental Europe will be needed to
fully understand the complex interactions between Britain, Ireland
and the continent during the Neolithic24.
The distinctive genetic signatures found in the Iberian populations
who preceded the arrival of Beaker complex, when compared to con-
temporary central European populations, enable us to formally test
for the origin of the Neolithic-related ancestry in Beaker-complex-
associated individuals. We grouped individuals from Iberia (n = 32)
and from outside Iberia (n = 172) to increase power and evaluated
the fit of different Neolithic and Copper Age groups with qpAdm2
under the model: ‘Steppe_EBA+Neolithic/Copper Age’. For Be aker-
complex-associated individuals from Iberia, the best fit was obtained
when Middle Neolithic and Copper Age populations from the same
region were used as the source for their Neolithic-related ancestry; we
could exclude central and northern European populations as sources
of this ancestry (P < 0.0063) (Fig. 2c). Conversely, the Neolithic-
related ancestry in Beaker-complex-associated individuals outside
of Iberia was most closely related to central and northern European
Neolithic populations with relatively high hunter-gatherer admixture
(for example, Poland_LN, P = 0.18 and Sweden_MN, P = 0.25), and
we could significantly exclude Iberian sources (P < 0.0104) (Fig. 2c).
Ireland_MN (1)
Wales_N (2)
Scotland_N (34)
England_N (14)
Sweden_MN (4)
Hungary_LCA (19)
Germany_MN (7)
Poland_LN (6)
France_MLN (4)
SW_Iberia_CA (1)
SE_Iberia_CA (4)
N_Iberia_CA (14)
C_Iberia_CA (25)
Iberia_MN (4)
–0.0015 –0.0010 –0.0005 0 0.0005
f4(Mbuti, test; Iberia_EN, LBK_EN)
Iberia
Central
Europe
Britain and
Ireland
Southern France
Northern Europe
Iberia_MN C_Iberia_CA N_Iberia_CA SE_Iberia_CA SW_Iberia_CA Germany_MNPoland_LN Hungary_LCA Sweden_MNFrance_MLN
Beaker complex Iberia
combined 1.66 × 10–1*7.23 × 10–1*1.76 × 10–5 1.15 × 10–1*6.11 × 10–1*8.17 × 10–11 3.36 × 10–6 2.72 × 10–59 6.28 × 10–3 4.53 × 10–2
Beaker complex outside
Iberia combined 1.11 × 10–12 7.48 × 10–10 2.18 × 10–10 9.93 × 10–3 1.04 × 10–2 2.51 × 10–13 1.84 × 10–1*6.05 × 10–55 2.45 × 10–1*4.61 × 10–4
Test
population
Neolithic/Copper Age source population
a
c
b
36
5
3
2
2
45
9
44
9
53
5
2
2
3
10
74
3
27
Figure 2 | Investigating the genetic makeup of Beaker-complex-
associated individuals. a, Proportion of steppe-related ancestry (in black)
in Beaker-complex-associated groups computed with qpAdm2 under the
model ‘Steppe_EBA+Anatolia_N+WHG’ (WHG, Mesolithic western
European hunter-gatherers). The area of the pie is proportional to the
number of individuals (number shown if more than one). Map data from
the R package ‘maps’. b, f-statistics of the form f4(Mbuti, test; Iberia_EN,
LBK_EN) computed for European populations (number of individuals for
each group is given in parentheses) before the emergence of the Beaker
complex (Supplementary Information section 7). Error bars represent ± 1
standard errors. c, Testing different populations as a source for the
Neolithic ancestry component in Beaker-complex-associated individuals.
The table shows P values (* indicates values > 0.05) for the fit of the
model: ‘Steppe_EBA+Neolithic/Copper Age’ source population.
4 | N A T URE | VOL 000 | 00 MONTH 2018
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These results support mostly different origins for Beaker-complex-
associated individuals, with no discernible Iberia-related ancestry
outside of Iberia.
Nearly complete turnover of ancestry in Britain
The genetic profile of British Beaker-complex-associated individ-
uals (n = 37) shows strong similarities to that of central European
Beaker-complex-associated individuals (Extended Data Fig. 3). This
observation is not restricted to British individuals associated with the
‘All-Over-Cord’ Beaker pottery style that is shared between Britain and
central Europe: we also find this genetic signal in British individu-
als associated with Beaker pottery styles derived from the ‘Maritime’
forms, which were predominant earlier in Iberia. The presence of
large amounts of steppe-related ancestry in British Beaker-complex-
associated individuals (Fig. 2a) contrasts sharply with Neolithic indi-
viduals from Britain (n = 51), who have no evidence of steppe genetic
affinities and cluster instead with Middle Neolithic and Copper Age
populations from mainland Europe (Extended Data Fig. 3). A previ-
ous study showed that steppe-related ancestry had arrived in Ireland
by the Bronze Age
23
; here we show that, at least in Britain, it arrived
earlier in the Copper Age (which, in Britain, is synonymous with the
Beaker period).
Among the continental Beaker-complex groups analysed in our data-
set, individuals from Oostwoud, the Netherlands, are the most closely
related to the large majority of Beaker-complex-associated individuals
from southern Britain (n = 27). The two groups had almost identical
steppe-related ancestry proportions (Fig. 2a), the highest level of shared
genetic drift (Extended Data Fig. 6b) and were symmetrically related
to most ancient populations (Extended Data Fig. 6a), which shows that
they are likely derived from the same ancestral population with limited
mixture into either group. This does not necessarily imply that the
Oostwoud individuals are direct ancestors of the British individuals,
but it does show that they were closely related genetically to the
population—perhaps yet to be sampled—that moved into Britain from
continental Europe.
We investigated the magnitude of population replacement in
Britain with qpAdm2 by modelling the genome-wide ancestry of
Neolithic, Copper and Bronze Age individuals, including Beaker-
complex-associated individuals, as a mixture of continental Beaker-
complex-associated samples (using the Oostwoud individuals as
a surrogate) and the British Neolithic population (Supplementary
Information section 8). During the first centuries after the initial con-
tact, between approximately 2450 and 2000bc, ancestry proportions
were variable (Fig. 3), which is consistent with migrant communities
just beginning to mix with the previously established British Neolithic
population. After roughly 2000bc, individuals were more homo-
geneous and possessed less variation in ancestry proportions and
a modest increase in Neolithic-related ancestry (Fig. 3). This could
represent admixture with persisting British populations with high
levels of Neolithic-related ancestry or, alternatively, with incoming
continental populations with higher proportions of Neolithic-related
ancestry. In either case, our results imply a minimum of 90 ± 2%
local population turnover by the Middle Bronze Age (approximately
1500–1000bc), with no significant decrease observed in 5 samples
from the Late Bronze Age. Although the exact turnover rate and
its geographic pattern await refinement with more ancient sam-
ples, our results imply that for individuals from Britain during and
after the Beaker period, a very high fraction of their DNA derives
from ancestors who lived in continental Europe before 2450bc. An
independent line of evidence for population turnover comes from
uniparental markers. Whereas Y-chromosome haplogroup R1b was
completely absent in Neolithic individuals (n = 33), it represents more
than 90% of the Y chromosomes in individuals from Copper and
Bronze Age Britain (n = 52) (Fig. 3). The introduction of new mtDNA
haplogroups, such as I, R1a and U4, which were present in Beaker-
complex-associated populations from continental Europe but not in
Neolithic Britain (Supplementary Table 3), suggests that both men
and women were involved in this population turnover.
Our ancient DNA transect-through-time in Britain also enabled us to
track the frequencies of alleles with known phenotypic effects. Derived
alleles at rs16891982 in SLC45A2 and rs12913832 in HERC2/OCA2,
2450
BC
1500
BC
1000
BC
800 BC
4000
BC
2000
BC
3500
BC
3000
BC
I2a R1b
Copper Age and
Early Bronze Ag
e
Middle Bronze
Age
Late Bronze
Age
Neolithic
Y-chromosome
haplogroup
Britain
Neolithic
Continental
Beaker complex
Genome-wide
ancestry components
0% 25% 50% 75% 100%
Figure 3 | Population transformation in Britain associated with the
arrival of the Beaker complex. Modelling Neolithic, Copper and Bronze
Age (including Beaker-complex-associated) individuals from Britain as a
mixture of continental Beaker-complex-associated individuals (red) and
the Neolithic population from Britain (blue). Each bar represents genome-
wide mixture proportions for one individual. Individuals are ordered
chronologically and included in the plot if represented by more than
100,000 SNPs. Circles indicate the Y-chromosome haplogroup for male
individuals.
00 MONTH 2018 | VOL 000 | N A T URE | 5
ARTICLE RESEARCH
which contribute to reduced skin and eye pigmentation in Europeans,
considerably increased in frequency between the Neolithic period and
the Beaker and Bronze Age periods (Extended Data Fig. 7). The arrival
of migrants associated with the Beaker complex therefore markedly
altered the pigmentation phenotypes of British populations. However,
the lactase persistence allele at SNP rs4988235 in LCT remained at very
low frequencies across this transition, both in Britain and continental
Europe, which shows that the major increase in its frequency occurred
within the last 3,500 years3,4,25.
Discussion
The term ‘Bell Beaker’ was introduced by late-nineteenth- and early-
twentieth-century archaeologists to refer to a distinctive pottery style
found across western and central Europe at the end of the Neolithic
that was initially hypothesized to have been spread by a genetically
homogeneous population. This idea of a ‘Beaker Folk’ became unpop-
ular after the 1960s as scepticism grew about the role of migration in
mediating change in archaeological cultures26, although even at the
time
27
it was speculated that the expansion of the Beaker complex into
Britain was an exception—a prediction that has now been borne out
by ancient genomic data.
The expansion of the Beaker complex cannot be described by a sim-
ple one-to-one mapping of an archaeologically defined material culture
to a genetically homogeneous population. This stands in contrast to
other archaeological complexes, notably the Linearbandkeramik farm-
ers of central Europe
2
, the Early Bronze Age Yamnaya of the steppe
2,3
and—to some extent—the Corded Ware complex of central and eastern
Europe2,3. Our results support a model in which cultural transmission
and human migration both had important roles, with the relative bal-
ance of these two processes depending on the region. In Iberia, the
majority of Beaker-complex-associated individuals lacked steppe affini-
ties and were genetically most similar to preceding Iberian populations.
In central Europe, steppe-related ancestry was widespread and we can
exclude a substantial contribution from Iberian Beaker-complex-
associated individuals. However, the presence of steppe-related ancestry
in some Iberian individuals demonstrates that gene flow into Iberia
was not uncommon during this period. These results contradict ini-
tial suggestions of gene flow into central Europe based on analysis of
mtDNA
28
and dental morpholog y
29
. In particular, mtDNA haplogroups
H1 and H3 were proposed as markers for a Beaker-complex expansion
originating in Iberia28, yet H3 is absent among our Iberian Beaker-
complex-associated individuals.
In other parts of Europe, the expansion of the Beaker complex was
driven to a substantial extent by migration. This genomic transforma-
tion is clearest in Britain owing to our densely sampled time transect.
The arrival of people associated with the Beaker complex precipitated
a demographic transformation in Britain, exemplified by the pres-
ence of individuals with large amounts of steppe-related ancestry after
2450bc. We considered the possibility that an uneven geographic
distribution of samples may have caused us to miss a major popula-
tion that lacked steppe-derived ancestry after 2450bc. However, our
British Beaker and Bronze Age samples are dispersed geographically—
extending from the southeastern peninsula of England to the Western
Isles of Scotland—and come from a wide variety of funerary contexts
(rivers, caves, pits, barrows, cists and flat graves) and diverse funerary
traditions (single and multiple burials in variable states of anatomical
articulation), which reduces the likelihood that our sampling missed
major populations. We also considered the possibility that different
burial practices between local and incoming populations (cremation
versus inhumation) during the early stages of interaction could result
in a sampling bias against local individuals. Although it is possible
that such a sampling bias makes the ancestry transition appear more
sudden than it in fact was, the long-term demographic effect was
clearly substantial, as the pervasive steppe-related ancestry observed
during the Beaker period, which was absent in the Neolithic period,
persisted during the Bronze Age—and indeed remains predominant in
Britain today2. These results are notable in light of strontium and
oxygen isotope analyses of British skeletons from the Beaker and
Bronze Age periods
30
, which have provided no evidence for substantial
mobility over individuals’ lifetimes from locations with cooler climates
or from places with geologies atypical of Britain. However, the isotope
data are only sensitive to first-generation migrants and do not rule out
movements from regions such as the lower Rhine area or from other
geologically similar regions for which DNA sampling is still sparse.
Further sampling of regions on the European continent may reveal
additional candidate sources.
By analysing DNA data from ancient individuals, we have been able
to provide constraints on the interpretations of the processes underly-
ing cultural and social changes in Europe during the third millennium
bc. Our results motivate further archaeological research to identify the
changes in social organization, technology, subsistence, climate, pop-
ulation sizes
31
or pathogen exposure
32,33
that could have precipitated
the demographic changes uncovered in this study.
Online Content Methods, along with any additional Extended Data display items and
Source Data, are available in the online version of the paper; references unique to
these sections appear only in the online paper.
Received 8 May 2017; accepted 4 January 2018.
Published online 21 February 2018.
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Supplementary Information is available in the online version of the paper.
Acknowledgements We thank D. Anthony, J. Koch, I. Mathieson and C. Renfrew
for comments; A. Cooper for support from the Australian Centre for Ancient
DNA; the Bristol Radiocarbon Accelerator Mass Spectrometry Facility (BRAMS);
A. C. Sousa, A. M. Cólliga, L. Loe, C. Roth, E. Carmona Ballesteros, M. Kunst,
S.-A. Coupar, M. Giesen, T. Lord, M. Green, A. Chamberlain and G. Drinkall for
assistance with samples; E. Willerslev for supporting several co-authors at the
Centre for GeoGenetics; the Museo Arqueológico Regional de la Comunidad
de Madrid, the Hunterian Museum, University of Glasgow, the Orkney Museum,
the Museu Municipal de Torres Vedras, the Great North Museum: Hancock, the
Society of Antiquaries of Newcastle upon Tyne, the Sunderland Museum, the
National Museum of Wales, the Duckworth Laboratory, the Wiltshire Museum,
the Wells Museum, the Brighton Museum, the Somerset Heritage Museum
and the Museum of London for facilitating sample collection. Support for this
project was provided by Czech Academy of Sciences grant RVO:67985912;
by the Momentum Mobility Research Group of the Hungarian Academy of
Sciences; by the Wellcome Trust (100713/Z/12/Z); by Irish Research Council
grant GOIPG/2013/36 to D.F.; by the Heidelberg Academy of Sciences
(WIN project ‘Times of Upheaval’) to P.W.S., J.K. and A.Mi.; by the Swedish
Foundation for Humanities and Social Sciences grant M16-0455:1 to K.Kr.;
by the National Science Centre, Poland grant DEC-2013/10/E/HS3/00141
to M.Fu.; by a Spanish MINECO grant BFU2015-64699-P to C.L.-F.; by Obra
Social La Caixa and a Spanish MINECO grant HAR2016-77600-P to C.L., P.R.
and C.Bl.; by the NSF Archaeometry program BCS-1460369 to D.J.K.; by the
NFS Archaeology program BCS-1725067 to D.J.K. and T.Ha.; and by an Allen
Discovery Center grant from the Paul Allen Foundation, US National Science
Foundation HOMINID grant BCS-1032255, US National Institutes of Health
grant GM100233, and the Howard Hughes Medical Institute to D.R.
Author Contributions S.B., M.E.A., N.R., A.S.-N., A.Mi., N.B., M.Fe., E.Har., M.Mi.,
J.O., K.S., O.C., D.K., F.C., R.Pi., J.K., W.H., I.B. and D.R. performed or supervised
laboratory work. G.T.C. and D.J.K. undertook the radiocarbon dating of a large
fraction of samples. I.A., K.Kr., A.B., K.W.A., A.A.F., E.B., M.B.-B., D.B., C.Bl., J.V.M.,
R.M.G., C.Bo., L.Bo., T.A., L.Bü., S.C., L.C.N., O.E.C., G.T.C., B.C., A.D., K.E.D., N.D.,
M.E., C.E., M.K., J.F.F., H.F., C.F., M.G., R.G.P., M.H.-U., E.Had., G.H., N.J., T.K., K.Ma.,
S.P., P.L., O.L., A.L., C.H.M., V.G.O., A.B.R., J.L.M., T.M., J.I.M., K.Mc., B.G.M., A.Mo.,
G.K., V.K., A.C., R.Pa., A.E., K.Kö., T.Ha., T.S., J.Da., Z.B., M.H., P.V., M.D., F.B., R.F.F.,
A.-M.H.-C., S.T., E.C., L.L., A.V., A.Z., C.W., G.D., E.G.-D., B.N., M.Br., M.Lu., R.M.,
J.De., M.Be., G.B., M.Fu., A.H., M.Ma., A.R., S.L., I.S., K.T.L., J.L.C., C.L., M.P.P.,
P.W., T.D.P., P.P., P.-J.R., P.R., R.R., M.A.R.G., A.Sc., J.S., A.M.S., V.S., L.V., J.Z., D.C.,
T.Hi., V.H., A.Sh., K.-G.S., P.W.S., R.Pi., J.K., W.H., I.B., C.L.-F. and D.R. assembled
archaeological material. I.O., S.M., T.B., A.Mi., E.A., M.Li., I.L., N.P., Y.D., Z.F., D.F.,
D.J.K., P.d.K., T.K.H., M.G.T. and D.R. analysed data. I.O., C.L.-F. and D.R. wrote the
manuscript with input from all co-authors.
Author Information Reprints and permissions information is available at
www.nature.com/reprints. The authors declare no competing financial
interests. Readers are welcome to comment on the online version of the paper.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations. Correspondence and
requests for materials should be addressed to I.O. (inigo_olalde@hms.harvard.
edu) or D.R. (reich@genetics.med.harvard.edu).
Reviewer Information Nature thanks C. Renfrew, E. Rhodes, M. Richards and
the other anonymous reviewer(s) for their contribution to the peer review of
this work.
IñigoOlalde1, SelinaBrace2, MortenE.Allentoft3, IanArmit4§,
KristianKristiansen5§, ThomasBooth2, NadinRohland1, SwapanMallick1,6,7,
AnnaSzécsényi-Nagy8, AlissaMittnik9,10, EvelineAltena11,
MarkLipson1, IosifLazaridis1,6, ThomasK.Harper12, NickPatterson6,
NasreenBroomandkhoshbacht1,7, YoanDiekmann13, ZuzanaFaltyskova13,
DanielFernandes14,15,16, MatthewFerry1,7, EadaoinHarney1, Peterde Knijff11,
MeganMichel1,7, JonasOppenheimer1,7, KristinStewardson1,7,
AlistairBarclay17, KurtWernerAlt18,19,20, CorinaLiesau21, PatriciaRíos21,
ConcepciónBlasco21, JorgeVegaMiguel22, RobertoMenduiñaGarcía22,
AzucenaAvilésFernández23, EszterBánffy24,25, MariaBernabò-Brea26,
DavidBilloin27, CliveBonsall28, LauraBonsall29, TimAllen30,
LindseyBüster4, SophieCarver31, LauraCastellsNavarro4,
OliverE.Craig32, GordonT.Cook33, BarryCunliffe34, AnthonyDenaire35,
KirstenEggingDinwiddy17, NatashaDodwell36, MichalErnée37,
ChristopherEvans38, MilanKucharˇ ík39, JoanFrancèsFarré40, ChrisFowler41,
MichielGazenbeek42, RafaelGarridoPena21, MaríaHaber-Uriarte23,
Elz˙bietaHaduch43, GillHey30, NickJowett44, TimothyKnowles45,
KenMassy46, SaskiaPfrengle9, PhilippeLefranc47, OlivierLemercier48,
ArnaudLefebvre49,50, CésarHerasMartínez51,52,53, VirginiaGaleraOlmo52,53,
AnaBastidaRamírez51, JoaquínLombaMaurandi23, TonaMajó54,
JacquelineI.McKinley17, KathleenMcSweeney28, BalázsGusztávMende8,
AlessandraMod55, GabriellaKulcsár24, ViktóriaKiss24, AndrásCzene56,
RóbertPatay57, AnnaEndro˝ di58, KittiKöhler24, TamásHajdu59,60,
TamásSzen i c z e y 59, JánosDani61, ZsoltBernert60, MayaHoole62,
OliviaCheronet14,15, DeniseKeating63, PetrVelemínský64, MiroslavDobeš37,
FrancescaCandilio65,66,67, FraserBrown30, RaúlFloresFernández68,
Ana-MercedesHerrero-Corral69, SebastianoTusa70, EmilianoCarnieri71,
LuigiLentini72, AntonellaValenti73, AlessandroZanini74, CliveWaddington75,
GermánDelibes76, ElisaGuerra-Doce76, BenjaminNeil38, MarcusBrittain38,
MikeLuke77, RichardMortimer36, JocelyneDesideri78, MarieBesse78,
GünterBrücken79, MirosławFurmanek80, AgataHałuszko80,
MaksymMackiewicz80, ArturRapin´ ski81, StephanyLeach82, IgnacioSoriano83,
KatinaT.Lillios84, JoãoLuísCardoso85,86, MichaelParkerPearson87,
PiotrWłodarczak88, T.DouglasPrice89, PilarPrieto90, Pierre-JérômeRey91,
RobertoRisch83, ManuelA.Rojo Guerra92, AuroreSchmitt93,
JoëlSerralongue94, AnaMariaSilva95, VáclavSmrcˇ ka96, LucVergnaud97,
JoãoZilhão85,98,99, DavidCaramelli55, ThomasHigham100, MarkG.Thomas13,
DouglasJ.Kennett101, HarryFokkens102, VolkerHeyd31,103, AlisonSheridan104,
Karl-GöranSjögren5, PhilippW.Stockhammer46,105, JohannesKrause105,
RonPinhasi14,15§, WolfgangHaak105,106§, IanBarnes2§, CarlesLalueza-Fox107§ &
DavidReich1,6,7§
1Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.
2Department of Earth Sciences, Natural History Museum, London SW7 5BD, UK. 3Centre for
GeoGenetics, Natural History Museum, University of Copenhagen, Copenhagen 1350, Denmark.
4School of Archaeological and Forensic Sciences, University of Bradford, Bradford BD7 1DP, UK.
5University of Gothenburg, Gothenburg 405 30, Sweden. 6Broad Institute of MIT and Harvard,
Cambridge, Massachusetts 02142, USA. 7Howard Hughes Medical Institute, Harvard Medical
School, Boston, Massachusetts 02115, USA. 8Laboratory of Archaeogenetics, Institute of
Archaeology, Research Centre for the Humanities, Hungarian Academy of Sciences, Budapest
1097, Hungary. 9Institute for Archaeological Sciences, Archaeo- and Palaeogenetics, University
of Tübingen, Tübingen 72070, Germany. 10Department of Archaeogenetics, Max Planck
Institute for the Science of Human History, Jena 07745, Germany. 11Department of Human
Genetics, Leiden University Medical Center, Leiden 2333 ZC, The Netherlands. 12Department of
Anthropology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
13Research Department of Genetics, Evolution and Environment, University College London,
London WC1E 6BT, UK. 14Earth Institute and School of Archaeology, University College Dublin,
Dublin 4, Ireland. 15Department of Anthropology, University of Vienna, Vienna 1090, Austria.
16Research Center for Anthropology and Health, Department of Life Science, University of
Coimbra, Coimbra 3000-456, Portugal. 17Wessex Archaeology, Salisbury SP4 6EB, UK. 18Center
of Natural and Cultural History of Man, Danube Private University, Krems 3500, Austria.
19Department of Biomedical Engineering, Basel University, Basel 4123, Switzerland.
20Integrative Prehistory and Archaeological Science, Basel University, Basel, Switzerland.
21Departamento de Prehistoria y Arqueología, Universidad Autónoma de Madrid, Madrid
28049, Spain. 22ARGEA S.L., Madrid 28011, Spain. 23Área de Prehistoria, Universidad de
Murcia, Murcia 30001, Spain. 24Institute of Archaeology, Research Centre for the Humanities,
Hungarian Academy of Sciences, Budapest 1097, Hungary. 25Romano-Germanic Commission,
German Archaeological Institute, Frankfurt am Main 60325, Germany. 26Museo Archeologico
Nazionale di Parma, Parma 43100, Italy. 27INRAP, Institut National de Recherches
Archéologiques Préventives, Buffard 25440, France. 28School of History, Classics and
Archaeology, University of Edinburgh, Edinburgh EH8 9AG, UK. 2910 Merchiston Gardens,
Edinburgh EH10 5DD, UK. 30Oxford Archaeology, Oxford OX2 0ES, UK. 31Department of
Archaeology and Anthropology, University of Bristol, Bristol BS8 1UU, UK. 32BioArCh,
Department of Archaeology, University of York, York YO10 5DD, UK. 33Scottish Universities
Environmental Research Centre, East Kilbride G75 0QF, UK. 34Institute of Archaeology,
University of Oxford, Oxford OX1 2PG, UK. 35University of Burgundy, Dijon 21000, France.
36Oxford Archaeology East, Cambridge CB23 8SQ, UK. 37Institute of Archaeology, Czech
Academy of Sciences, Prague 118 01, Czech Republic. 38Cambridge Archaeological Unit,
Department of Archaeology, University of Cambridge, Cambridge CB3 0DT, UK. 39Labrys o.p.s.,
Prague 198 00, Czech Republic. 40Museu i Poblat Ibèric de Ca n'Oliver, Cerdanyola del Vallès
08290, Spain. 41School of History, Classics & Archaeology, Newcastle University, Newcastle
upon Tyne NE1 7RU, UK. 42INRAP, Institut National de Recherches Archéologiques Préventives,
Nice 06300, France. 43Institute of Zoology and Biomedical Research, Jagiellonian University,
Kraków 31-007, Poland. 44Great Orme Mines, Great Orme, Llandudno LL30 2XG, UK. 45Bristol
Radiocarbon Accelerator Mass Spectrometry Facility, University of Bristol, Bristol BS8 1UU, UK.
46Institut für Vor- und Frühgeschichtliche Archäologie und Provinzialrömische Archäologie,
00 MONTH 2018 | VOL 000 | N A T URE | 7
ARTICLE RESEARCH
Ludwig-Maximilians-Universität München, Munich 80539, Germany. 47INRAP, Institut National de
Recherches Archéologiques Préventives, Strasbourg 67100, France. 48Université Paul-Valéry -
Montpellier 3, UMR 5140 ASM, Montpellier 34199, France. 49INRAP, Institut National de
Recherches Archéologiques Préventives, Metz 57063, France. 50UMR 5199, Pacea, équipe A3P,
Université de Bordeaux, Talence 33400, France. 51TRÉBEDE, Patrimonio y Cultura SL, Torres de
la Alameda 28813, Spain. 52Departamento de Ciencias de la Vida, Universidad de Alcalá, Alcalá
de Henares 28801, Spain. 53Instituto Universitario de Investigación en Ciencias Policiales
(IUICP), Alcalá de Henares 28801, Spain. 54Archaeom, Departament de Prehistòria, Universitat
Autònoma de Barcelona, Cerdanyola del Vallès 08193, Spain. 55Department of Biology,
University of Florence, Florence 50121, Italy. 56Salisbury Ltd, Budaörs 2040, Hungary.
57Ferenczy Museum Center, Szentendre 2100, Hungary. 58Budapest History Museum,
Budapest 1014, Hungary. 59Department of Biological Anthropology, Eötvös Loránd University,
Budapest 1117, Hungary. 60Hungarian Natural History Museum, Budapest 1083, Hungary.
61Déri Museum, Debrecen 4026, Hungary. 62Historic Environment Scotland, Edinburgh EH9 1SH,
UK. 63Humanities Institute, University College Dublin, Dublin 4, Ireland. 64Department of
Anthropology, National Museum, Prague 115 79, Czech Republic. 65Soprintendenza
Archeologia belle arti e paesaggio per la città metropolitana di Cagliari e per le province di
Oristano e Sud Sardegna, Cagliari 9124, Italy. 66Physical Anthropology Section, University of
Philadelphia Museum of Archaeology and Anthropology, Philadelphia, Pennsylvania 19104,
USA. 67Department of Environmental Biology, Sapienza University of Rome, Rome 00185, Italy.
6846 Cuidad Real Street, Parla 28982, Spain. 69Departamento de Prehistoria, Universidad
Complutense de Madrid, Madrid 28040, Spain. 70Soprintendenza del Mare, Palermo 90133,
Italy. 71Facoltà di Lettere e Filosofia, Università di Palermo, Palermo 90133, Italy.
72Soprintendenza per i beni culturali e ambientali di Trapani, Trapani 91100, Italy. 73Prima
Archeologia del Mediterraneo, Partanna 91028, Italy. 74Università degli Studi di Palermo,
Agrigento 92100, Italy. 75Archaeological Research Services Ltd, Bakewell DE45 1HB, UK.
76Departamento de Prehistoria, Facultad de Filosofía y Letras, Universidad de Valladolid,
Valladolid 47011, Spain. 77Albion Archaeology, Bedford MK42 0AS, UK. 78Laboratory of
Prehistoric Archaeology and Anthropology, Department F.-A. Forel for Environmental and
Aquatic Sciences, University of Geneva, Geneva 4, Switzerland. 79General Department of
Cultural Heritage Rhineland Palatinate, Department of Archaeology, Mainz 55116, Germany.
80Institute of Archaeology, University of Wroclaw, Wrocław 50-137, Poland. 81Institute of
Archaeology, Silesian University in Opava, Opava 746 01, Czech Republic. 82Department of
Archaeology, University of Exeter, Exeter EX4 4QE, UK. 83Departament de Prehistòria,
Universitat Autònoma de Barcelona, Cerdanyola del Vallès 08193, Spain. 84Department of
Anthropology, University of Iowa, Iowa City, Iowa 52240, USA. 85Centro de Arqueologia,
Universidade de Lisboa, Lisboa 1600-214, Portugal. 86Universidade Aberta, Lisboa 1269-001,
Portugal. 87Institute of Archaeology, University College London, London WC1H 0PY, UK.
88Institute of Archaeology and Ethnology, Polish Academy of Sciences, Kraków 31-016, Poland.
89Laboratory for Archaeological Chemistry, University of Wisconsin-Madison, Madison,
Wisconsin 53706, USA. 90University of Santiago de Compostela, Santiago de Compostela
15782, Spain. 91UMR 5204 Laboratoire Edytem, Université Savoie Mont Blanc, Chambéry
73376, France. 92Department of Prehistory and Archaeology, Faculty of Philosophy and Letters,
Valladolid University, Valladolid 47011, Spain. 93UMR 7268 ADES, CNRS, Aix-Marseille Univ,
EFS, Faculté de médecine Nord, Marseille 13015, France. 94Service archéologique, Conseil
Général de la Haute-Savoie, Annecy 74000, France. 95Laboratory of Prehistory, Research Center
for Anthropology and Health, Department of Life Science, University of Coimbra, Coimbra
3000-456, Portugal. 96Institute for History of Medicine and Foreign Languages, First Faculty of
Medicine, Charles University, Prague 121 08, Czech Republic. 97ANTEA Bureau d'étude en
Archéologie, Habsheim 68440, France. 98Institució Catalana de Recerca i Estudis Avançats,
Barcelona 08010, Spain. 99Departament d'Història i Arqueologia, Universitat de Barcelona,
Barcelona 08001, Spain. 100Oxford Radiocarbon Accelerator Unit, RLAHA, University of Oxford,
Oxford OX1 3QY, UK. 101Department of Anthropology & Institute for Energy and the
Environment, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
102Faculty of Archaeology, Leiden University, 2333 CC Leiden, The Netherlands. 103Department
of Philosophy, History, Culture and Art Studies, Section of Archaeology, University of Helsinki,
Helsinki 00014, Finland. 104National Museums Scotland, Edinburgh EH1 1JF, UK. 105Max
Planck Institute for the Science of Human History, Jena 07745, Germany. 106Australian Centre
for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide 5005, South
Australia, Australia. 107Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona 08003, Spain.
§These authors jointly supervised this work.
ARTICLE
RESEARCH
METHODS
No statistical methods were used to predetermine sample size. The experiments
were not randomized and the investigators were not blinded to allocation during
experiments and outcome assessment.
Ancient DNA analysis. We screened skeletal samples for DNA preservation in
dedicated clean rooms. We extracted DNA34–36 and prepared barcoded next-
generation sequencing libraries, the majority of which were treated with uracil-
DNA glycosylase (UDG) to greatly reduce the damage (except at the terminal
nucleotide) that is characteristic of ancient DNA37,38 (Supplementary Information
section 4). We initially enriched libraries for sequences overlapping the mitochon-
drial genome39 and approximately 3,000 nuclear SNPs, using synthesized baits
(CustomArray) that we PCR-amplified. We sequenced the enriched material on
an Illumina NextSeq instrument with 2 × 76 cycles, and 2 × 7 cycles to read out the
two indices
40
. We merged read pairs with the expected barcodes that overlapped by
at least 15 bases, mapped the merged sequences to the human reference genome
hg19 and to the reconstructed mitochondrial DNA consensus sequence
41
using
the ‘samse’ command in bwa v.0.6.1
42
, and then removed duplicated sequences.
We e v al u a te d D N A a ut h e nt i c it y b y e s t im a t in g t h e r a te of mi s m at c h in g t o t h e c o n
-
sensus mitochondrial sequence
43
, and also by requiring that the rate of damage at
the terminal nucleotide was at least 3% for UDG-treated libraries
43
and 10% for
non-UDG-treated libraries44.
For libraries that appeared promising after screening, we enriched in two
consecutive rounds for sequences overlapping 1,233,013 SNPs (‘1,240k SNP cap-
ture’)
2,10
and s equen ced 2 × 76 cycles and 2 × 7 cycles on an Illumina NextSeq500
instrument. We bioinformatically processed the data in the same way as for the
mitochondrial capture data, except that this time we mapped only to hg19 and
merged the data from different libraries of the same individual. We further evalu-
ated authenticity by looking at the ratio of X- to-Y chromosome reads and estimat-
ing X-chromosome contamination in males based on the rate of heterozygosity
45
.
Samples with evidence of contamination were either filtered out or restricted to
sequences with terminal cytosine deamination in order to remove sequences that
derived from modern contaminants. Finally, we filtered out samples with fewer
than 10,000 targeted SNPs covered at least once and samples that were first-degree
relatives of others in the dataset (keeping the sample with the larger number of
covered SNPs) (Supplementary Table 1) from our genome-wide analysis dataset.
Mitochondrial haplogroup determination. We used the mitochondrial capture
.bam files to determine the mitochondrial haplogroup of each sample with new
data, restricting our analysis to sequences with MAPQ ≥ 30 and base quality ≥ 30.
First, we constructed a consensus sequence with samtools and bcftools46, using a
majority rule and requiring a minimum coverage of two. We called haplogroups
with HaploGrep247 based on phylotree48 (mtDNA tree build 17 (accessed
18 February 2016)). Mutational differences, compared to the revised Cambridge
Reference Sequence (GenBank reference sequence: NC_012920.1) and corre-
sponding haplogroups, can be viewed in Supplementary Table 2. We computed
haplogroup frequencies for relevant ancient populations (Supplementary Table 3)
after removing close relatives with the same mtDNA.
Y-c hr om os om e an al ys is . We determined Y-chromosome haplogroups for both
new and published samples (Supplementary Information section 5). We made
use of the sequences mapping to 1,240k Y-chromosome targets, restricting our
analysis to sequences with mapping quality ≥ 30 and bases with quality ≥ 30. We
called haplogroups by determining the most derived mutation for each sample,
using the nomenclature of the International Society of Genetic Genealogy (http://
www.isogg.org) version 11.110 (accessed 21 April 2016). Haplogroups and their
supporting derived mutations can be viewed in Supplementary Table 4.
Merging newly generated data with pu blished dat a. We assembled two data-
sets for genome-wide analyses. The first dataset is HO, which includes 2,572
present-day individuals from worldwide populations genotyped on the Human
Origins Array11,12,49 and 683 ancient individuals. The ancient set includes 211
Beaker-complex-associated individuals (195 newly reported, 7 with shotgun data
3
for which we generated 1,240k capture data and 9 that had previously been pub-
lished3,4), 68 newly reported individuals from relevant ancient populations and 298
individuals that had previously been published
12,18,19,21–23,50–57
(Supplementary
Table 1). We kept 591,642 autosomal SNPs after intersecting autosomal SNPs in the
1,240k capture with the analysis set of 594,924 SNPs from a previous publication11.
The second dataset is HOIll, which includes the same set of ancient samples and
300 present-day individuals from 142 populations sequenced to high coverage as
part of the Simons Genome Diversity Project
13
. For this dataset, we used 1,054,671
autosomal SNPs, excluding SNPs of the 1,240k array located on sex chromosomes
or with known functional effects.
For each individual, we represented the allele at each SNP by randomly sampling
one sequence and discarding the first and the last two nucleotides of each sequence.
Abbrev iati ons. We have used the following abbreviations in population labels:
E, Early; M, Middle; L, Late; N, Neolithic; CA, Copper Age; BA, Bronze Age; BC,
Beaker complex; N_Iberia, northern Iberia; C_Iberia, central Iberia; SE_Iberia,
southeast Iberia; and SW_Iberia, southwest Iberia.
Principal component analysis. We carried out principal component analysis on
the HO dataset using the ‘smartpca’ program in EIGENSOFT58. We computed
principal components on 990 present-day west Eurasians and projected ancient
individuals using lsqproject:YES and shrinkmode:YES.
ADMIXTURE analysis. We performed model-based clustering analysis using
ADMIXTURE
17
on the HO reference dataset, which included 2,572 present-day
individuals from worldwide populations and the ancient individuals. First, we
carried out linkage disequilibrium pruning on the dataset using PLINK59 with
the flag–indep-pairwise 200 25 0.4, leaving 306,393 SNPs. We ran ADMIXTURE
with the cross validation (–cv.) flag specifying from K = 2 to K = 20 clusters, with
20 replicates for each value of K. For each value of K, the replicate with highest log
likelihood was kept. In Extended Data Fig. 3b we show the cluster assignments at
K = 8 of newly reported individuals and other relevant ancient samples for com-
parison. We chose this value of K as it was the lowest one for which components
of ancestry related both to Iranian Neolithic farmers and European Mesolithic
hunter-gatherers were maximized.
f-statistics. We com puted f-statistics on the HOIll dataset using ADMIXTOOLS
49
with default parameters (Supplementar y Information section 6). We used
qpDstat with f4mode:Yes for f
4
-statistics and qp3Pop for outgroup f
3
-statistics. We
computed standard errors using a weighted block jackknife60 over 5- Mb blocks.
Inference of mixture proportions. We estimated ancestry proportions on the
HOIll dataset using qpAdm2 and a basic set of nine outgroups: Mota, Ust_Ishim,
MA1, Villabruna, Mbuti, Papuan, Onge, Han and Karitiana. For some analyses
(Supplementary Information section 8) we added additional outgroups to this
basic set.
Admixture graph modelli ng. We modelled the relationships between pop-
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in ADMIXTOOLS49, using the HOIll dataset and Mbuti as an outgroup
(Supplementary Information section 7).
Allele frequency estimation from read counts. We used allele counts at each
SNP to perform maximum likelihood estimations of allele frequencies in ancient
populations as in ref. 4. In Extended Data Fig. 7, we show derived allele frequency
estimates at three SNPs of functional importance for different ancient populations.
Data availability. All 1, 240k a nd mito chondr ial cap ture se quenci ng data are avai l-
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hms.harvard.edu/datasets.
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Extended Data Figure 1 | Beaker-complex artefacts. a, ‘All-Over-Cord’
Beaker from Bathgate, West Lothian, Scotland. Photograph: © National
Museums Scotland. b, Beaker-complex grave goods from La Sima III
barrow, Soria, Spain61. The set includes Beaker pots of the so-called
‘Maritime style’. Photograph: Junta de Castilla y León, Archivo Museo
Numantino, A lejand ro Plaza.
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Extended Data Figure 2 | Ancient individuals with previously published
genome-wide data used in this study. a, Sampling locations. b, Time
ranges. WHG, western hunter-gatherers; EHG, eastern hunter-gatherers;
SHG, Scandinavian hunter-gatherers; CHG, Caucasus hunter-gatherers;
E, Early; M, Middle; L, Late; N, Neolithic; CA, Copper Age; and
BA,Bronze Age. Map data from the R package ‘maps’.
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Extended Data Figure 3 | Population structure. a, Principal component
analysis of 990 present-day west Eurasian individuals (grey dots), with
previously published (pale yellow) and new ancient samples projected onto
the first two principal components. b, ADMIXTURE clustering analysis
with K = 8 showing ancient individuals. WHG, western hunter-gatherers;
EHG, eastern hunter-gatherers; SHG, Scandinavian hunter-gatherers;
CHG, Caucasus hunter-gatherers; E, Early; M, Middle; L, Late;
N, Neolithic; CA, Copper Age; and BA, Bronze Age.
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Extended Data Figure 4 | Hunter-gatherer affinities in Neolithic
and Copper Age Europe. Differential affinity to hunter-gatherer
individuals (La Braña156 from Spain and KO162 from Hungary) in
European populations before the emergence of the Beaker complex.
See Supplementary Information section 8 for mixture proportions and
standard errors computed with qpAdm2. E, Early; M, Middle; L, Late;
N, Neolithic; CA, Copper Age; BA, Bronze Age; N_Iberia, northern Iberia;
and C_Iberia, central Iberia.
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Extended Data Figure 5 | Modelling the relationships between Neolithic
populations. a, Admixture graph fitting a test population as a mixture
of sources related to both Iberia_EN and Hungary_EN. b, Likelihood
distribution for models with different proportions of the source related
to Iberia_EN (green admixture edge in a) when the test population is
England_N, Scotland_N or France_MLN. E, Early; M, Middle; L, Late;
and N, Neolithic.
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Extended Data Figure 6 | Genetic affinity between Beaker-complex-
associated individuals from southern England and the Netherlands.
a,f-statistics of the form f4(Mbuti, test; BK_Netherlands_Tui, BK_
England_SOU). Negative values indicate that test population is closer to
BK_Netherlands_Tui than to BK_England_SOU; positive values indicate
that the test population is closer to BK_England_SOU than to BK_
Netherlands_Tui. Error bars repres ent ± 3 standard errors. b, Outgroup f3-
statistics of the form f3(Mbuti; BK_England_SOU, test) measuring shared
genetic drift between BK_England_SOU and other Beaker-complex-
associated groups. Error bars represent ± 1 standard errors. Number of
individuals for each group is given in parentheses. BK_Netherlands_Tui,
Beaker-complex-associated individuals from De Tuithoorn (Oostwoud,
the Netherlands); BK_England_SOU, Beaker-complex-associated
individuals from southern England. See Supplementary Table 1 for
individuals associated with each population label.
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Extended Data Figure 7 | Derived allele frequencies at three SNPs of
functional importance. Error bars represent 1.9-log-likelihood support
interval. The red dashed lines show allele frequencies in the 1000 Genomes
Project (http://www.internationalgenome.org/) ‘GBR’ population
(present-day people from Great Britain). Sample sizes are 50, 98 and 117
for Britain Neolithic, Britain Copper Age and Bronze Age, and central
European Beaker-complex-associated individuals, respectively. BC, Beaker
complex; CA, Copper Age; and BA, Bronze Age.
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Extended Data Table 1 | Sites from outside Britain with new genome-wide
data reported in this study
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Extended Data Table 2 | Sites from Britain with new genome-wide data reported in this study
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Extended Data Table 3 | 111 newly reported radiocarbon dates
