137 ancient human genomes from across the Eurasian steppes

Abstract

For thousands of years the Eurasian steppes have been a centre of human migrations and cultural change. Here we sequence the genomes of 137 ancient humans (about 1× average coverage), covering a period of 4,000 years, to understand the population history of the Eurasian steppes after the Bronze Age migrations. We find that the genetics of the Scythian groups that dominated the Eurasian steppes throughout the Iron Age were highly structured, with diverse origins comprising Late Bronze Age herders, European farmers and southern Siberian hunter-gatherers. Later, Scythians admixed with the eastern steppe nomads who formed the Xiongnu confederations, and moved westward in about the second or third century bc, forming the Hun traditions in the fourth–fifth century ad, and carrying with them plague that was basal to the Justinian plague. These nomads were further admixed with East Asian groups during several short- term khanates in the Medieval period. These historical events transformed the Eurasian steppes from being inhabited by Indo-European speakers of largely West Eurasian ancestry to the mostly Turkic-speaking groups of the present day, who are primarily of East Asian ancestry.

Full text

ARTICLE https://doi.org/10.1038/s41586-018-0094-2
137 ancient human genomes from across
the Eurasian steppes
Peter de Barros Damgaard1, Nina Marchi2, Simon Rasmussen3, Michaël Peyrot4, Gabriel Renaud1, Thorfinn Korneliussen1,5,
J. Víctor Moreno-Mayar1, Mikkel Winther Pedersen5, Amy Goldberg6, Emma Usmanova7, Nurbol Baimukhanov8,
Valeriy Loman7, Lotte Hedeager9, Anders Gorm Pedersen3, Kasper Nielsen3,50, Gennady Afanasiev10, Kunbolot Akmatov11,
Almaz Aldashev12, Ashyk Alpaslan11, Gabit Baimbetov8, Vladimir I. Bazaliiskii13, Arman Beisenov14, Bazartseren Boldbaatar15,
Bazartseren Boldgiv16, Choduraa Dorzhu17, Sturla Ellingvag18, Diimaajav Erdenebaatar19, Rana Dajani20,21, Evgeniy Dmitriev7,
Valeriy Evdokimov7, Karin M. Frei22, Andrey Gromov23, Alexander Goryachev24, Hakon Hakonarson25, Tatyana Hegay26,
Zaruhi Khachatryan27, Ruslan Khaskhanov28, Egor Kitov14,29, Alina Kolbina30, Tabaldiev Kubatbek11, Alexey Kukushkin7,
Igor Kukushkin7, Nina Lau31, Ashot Margaryan1,32, Inga Merkyte33, Ilya V. Mertz34, Viktor K. Mertz34, Enkhbayar Mijiddorj19,
Vyacheslav Moiyesev23, Gulmira Mukhtarova35, Bekmukhanbet Nurmukhanbetov35, Z. Orozbekova36, Irina Panyushkina37,
Karol Pieta38, Václav Smrčka39, Irina Shevnina40, Andrey Logvin40, Karl-Göran Sjögren41, Tereza Štolcová38,
Kadicha Tashbaeva42, Alexander Tkachev43, Turaly Tulegenov35, Dmitriy Voyakin24, Levon Yepiskoposyan27,
Sainbileg Undrakhbold16, Victor Varfolomeev7, Andrzej Weber44, Nikolay Kradin45,46, Morten E. Allentoft1, Ludovic Orlando1,47,
Rasmus Nielsen1,48, Martin Sikora1, Evelyne Heyer2, Kristian Kristiansen41 & Eske Willerslev1,5,49*
For thousands of years the Eurasian steppes have been a centre of human migrations and cultural change. Here we
sequence the genomes of 137 ancient humans (about 1× average coverage), covering a period of 4,000 years, to understand
the population history of the Eurasian steppes after the Bronze Age migrations. We find that the genetics of the Scythian
groups that dominated the Eurasian steppes throughout the Iron Age were highly structured, with diverse origins
comprising Late Bronze Age herders, European farmers and southern Siberian hunter-gatherers. Later, Scythians
admixed with the eastern steppe nomads who formed the Xiongnu confederations, and moved westward in about the
second or third century , forming the Hun traditions in the fourth–fifth century , and carrying with them plague
that was basal to the Justinian plague. These nomads were further admixed with East Asian groups during several short-
term khanates in the Medieval period. These historical events transformed the Eurasian steppes from being inhabited
by Indo-European speakers of largely West Eurasian ancestry to the mostly Turkic-speaking groups of the present day,
who are primarily of East Asian ancestry.
The Eurasian steppes stretch about 8,000km from Hungary and
Romania in the west to Mongolia and northeastern China in the east.
These regions have, in the past four to five millennia, been domi-
nated first by Iranian- and later by Turkic- and Mongolic-speaking
nomadic groups with herding and warrior economies. To understand
the population genetic processes associated with the linguistic and
cultural changes of the steppes after the Bronze Age migrations1–3,
we sequenced 137 ancient genomes—to about 1× average depth (see
Supplementary Tables1, 2)—from Europe to Mongolia and the Altai
to Tian Shan mountains; these genomes covered approximately 4,000
years (about 2500–1500) (Fig.1). A list of the population labels
used throughout this Article can be found in Supplementary Table3.
1Center for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark. 2Eco-anthropologie et Ethnobiologie, Muséum national d’Histoire naturelle,
CNRS, Université Paris Diderot, Paris, France. 3Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark. 4Leiden University Centre for Linguistics, Leiden
University, Leiden, The Netherlands. 5Department of Zoology, University of Cambridge, Cambridge, UK. 6Department of Biology, Stanford University, Stanford, CA, USA. 7Buketov Karaganda State
University, Saryarka Archaeological Institute, Karaganda, Kazakhstan. 8Shejire DNA, Almaty, Kazakhstan. 9Department of Archaeology, Conservation and History, University of Oslo, Oslo, Norway.
10Department of Theory and Methods, Institute of Archaeology Russian Academy of Sciences, Moscow, Russia. 11Department of History, Kyrgyzstan-Turkey Manas University, Bishkek, Kyrgyzstan.
12National Academy of Sciences of Kyrgyzstan, Bishkek, Kyrgyzstan. 13Department of History, Irkutsk State University, Irkutsk, Russia. 14A. Kh. Margulan Institute of Archaeology, Almaty,
Kazakhstan. 15Laboratory of Virology, Institute of Veterinary Medicine, Mongolian University of Life Sciences, Ulaanbaatar, Mongolia. 16Department of Biology, School of Arts and Sciences, National
University of Mongolia, Ulaanbaatar, Mongolia. 17Departament of Biology and Ecology, Tuvan State University, Kyzyl, Russia. 18The Explico Foundation, Floro, Norway. 19Department of Archaeology,
Ulaanbaatar State University, Ulaanbaatar, Mongolia. 20Department of Biology and Biotechnology, Hashemite University, Zarqa, Jordan. 21Radcliffe Institute for Advanced Study, Harvard University,
Cambridge, MA, USA. 22Unit for Environmental Archaeology and Materials Science, National Museum of Denmark, Copenhagen, Denmark. 23Peter the Great Museum of Anthropology and
Ethnography (Kunstkamera) RAS, St. Petersburg, Russia. 24Archaeological Expertise LLC, Almaty, Kazakhstan. 25Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia,
PA, USA. 26Republican Scientific Center of Immunology, Ministry of Public Health, Tashkent, Uzbekistan. 27Department of Bioengineering, Bioinformatics and Molecular Biology, Russian-Armenian
University, Yerevan, Armenia. 28Complex Research Institute of the Russian Academy of Sciences, Grozny, Russia. 29Institute of Ethnology and Anthropology, Russian Academy of Science, Moscow,
Russia. 30Kostanay Regional Local History Museum, Kostanay, Kazakhstan. 31Centre for Baltic and Scandinavian Archaeology, Schleswig, Germany. 32Laboratory of Ethnogenomics, Institute of
Molecular Biology, National Academy of Sciences of Armenia, Yerevan, Armenia. 33Saxo-Institute, University of Copenhagen, Copenhagen, Denmark. 34Center for Archaeological Research, S.
Toraighyrov Pavlodar State University, Pavlodar, Kazakhstan. 35The State Historical and Cultural Reserve-Museum (ISSYK), Almaty, Kazakhstan. 36Institute of Archeology and Ethnography of the
Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. 37University of Arizona, Laboratory of Tree-Ring Research, Tucson, AZ, USA. 38Institute of Archaeology of the Slovak
Academy of Sciences, Nitra, Slovakia. 39Institute for History of Medicine and Foreign Languages, First Faculty of Medicine, Charles University, Prague, Czech Republic. 40Archaeological Laboratory,
Kostanay State University, Kostanay, Kazakhstan. 41Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden. 42Institute of History and Cultural Heritage of National
Academy of Sciences, Bishkek, Kyrgyzstan. 43Institute of Problems Development of the North Siberian Branch of the Russian Academy of Sciences, Tyumen, Russia. 44Department of Anthropology,
University of Alberta, Edmonton, Alberta, Canada. 45Institute of History, Archaeology and Ethnology, Far-Eastern Branch of the Russian Academy of Sciences, Ulan-Ude, Russia. 46Institute of
Mongolian, Buddhist, and Tibetan Studies, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude, Russia. 47Laboratoire d’Anthropobiologie Moléculaire et d’Imagerie de Synthèse,
Université de Toulouse, Université Paul Sabatier, Toulouse, France. 48Departments of Integrative Biology and Statistics, University of Berkeley, Berkeley, CA, USA. 49Wellcome Trust Sanger Institute,
Hinxton, UK. 50Present address: Carlsberg Research Laboratory, Copenhagen, Denmark. *e-mail: ewillerslev@snm.ku.dk
17 MAY 2018 | VOL 557 | NATURE | 369
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Article
reSeArcH
Furthermore, we genotyped 502 individuals of 16 self-reported eth-
nicities from across Central Asia, Altai, Siberia and the Caucasus
(Supplementary Table4 and Supplementary Information section5).
In the process, we tested differential ancient DNA preservation in
organic contrasted mineral substrate (Supplementary Information
section6), and generated 83 new accelerator mass spectrometry dates
(Supplementary Information section11).
The genomic origins of the Scythian confederations
Between about 800 and 200, the Eurasian steppes became dominated
by the Iranian-speaking Scythians. This confederation was divided into
geographically distinct groups, but was united by similarities in cul-
tural expression
4
. However, the origins and population structure of the
Scythians remain contested, as can be summarized in three competing
models: (1) the Scythians deriving from a single source originating in
the northern Caucasus or steppe region
5–7
; (2) an origin in southern
Siberia or east-central Asia, moving westwards
8,9
; and finally (3) the
Scythians being a product of multiple transitions taking place locally,
involving social and cultural borrowing in combination with gradual,
small-scale human movements10–13.
Using principal component analysis (PCA) and ADMIXTURE analyses
(Fig.2 and Extended Data Fig.1), we observe a clear separation between
two groups of Iron Age Scythians: the Hungarian Scythians and the Inner
Asian Sakas. Furthermore, we find fine-scaled structure within the Inner
Asian Sakas that separates (1) the populations associated with the ‘Tagar’
culture of southern Siberia, (2) the ‘Central Sakas’ of the central steppe—
most of whom have been described as belonging to the Tasmola culture
(Supplementary Information section3)—and (3) the ‘Tian Shan Sakas’
of the Tian Shan mountain range (see map in Fig.1). These differences
reflect the confederal nature of the Scythian organization.
Recent genetic models suggested the presence of Yamnaya and/or
Afanasievo ancestry in Scythians
11
, which we assessed here using a new
set of outgroups that enabled us to distinguish between Early and Late
Bronze Age steppe ancestry (Supplementary Information section3.6).
We find that the Late Bronze Age herders are a better genetic source
for the West Eurasian ancestry in Scythians than are Early Bronze Age
Yamnaya or Afanasievo, the key difference being their European farmer
ancestry (Supplementary Table5). Using ADMIXTURE models
14
we
also illustrate the shared ancestry between Neolithic farmers (from
Anatolia or Europe), Late Bronze Age herders and Iron Age steppe
nomads that is not shared with Yamnaya herders (Extended Data
Fig.2 and Supplementary Fig.163). These findings are consistent with
archaeological models.
Using D-statistics (Supplementary Information section3.7), we
then characterized the sources of admixture into the various Scythian
groups relative to the Late Bronze Age steppe herders. We find that
Hungarian Scythians had relatively increased European farmer ances-
try (Extended Data Fig.3) and show no signs of gene flow from Inner
Asian groups. Conversely, Inner Asian Sakas show relatively increased
southern Siberian hunter-gatherer ancestry with the strongest gene
flow observed into the Central Sakas. This East Asian admixture is also
reflected in the negative admixture f3 values, indicating that Late Bronze
Age pastoralists and southern Siberian hunter-gatherers are excellent
proxies for the admixing populations (Extended Data Fig.4). We con-
firm the differences between these Iron Age steppe groups through
D-statistics (Supplementary Information section3.7). The increase in
Neolithic Iranian ancestry in the Tian Shan Sakas is significant when
compared to Central Sakas; the Tagar display increased eastern hunter-
gatherer (EHG) ancestry compared to all other Scythians. Lastly, the
high genetic differentiation between western and eastern Scythians is
emphasized by observing higher fixation index (F
ST
) values between
Hungarian Scythians and all Inner Asian Sakas (FST ranges from 0.24
to 0.3) than observed among the different Inner Asian Sakas groups
(FST ranges from 0.15 to 0.2) (Supplementary Table6).
b
2
1
20° E
M
e
d
i
t
e
r
r
a
n
e
a
n
S
e
a
30° E
40° E
50° E 60° E 70° E 80° E
90° E
100° E
110° E
60° N
50° N
40° N
Euro
Euro
Eur
pe
Alta
Alta
Alta
Alta
Alta
A
i
i
i
Moun
Moun
oun
Moun
o
tai
ta
tai
t
Mo
M
Mo
Mo
o
o
M
ai
in
in
in
n
n
s
s
s
s
s
i
CS
ES
PS
a
02,0003,0004,000
Years before present
1,000
A
r
c
t
i
c
O
c
e
a
n
Tian
Tian
Tian
Tian
Tian
S
Sha
S
Sha
a
n
n
n
PS
C
Central steppe
Europe
Tian Shan
02,0003,0004,000
Years before present
1,000
STE
4,700
HP
Issyk-Kul
2
40° N
80°
E
80° E
50° N
1
Hallstatt–Bylany
North Lithuania
Poprad
Hungarian Scythian
West Sarmatian
Medieval nomad
Saltovo-Mayaki
Lchashen Metsamor
Alan
Medieval nomad
Historical nomad
Andronovo
Turk
Tian Shan Hun
Tian Shan Saka
Wusun
Karluk
Kangju
Iron Age nomad
Central Saka
Iron Age nomad
Hun period nomad
Hun–Sarmatian
Kipchak
Sarmatian
Golden Horde
Kimak
Turk
Kangju
Karakhanid
Historical Kazakh
Andronovo
Tagar
Western Xiongnu
Xiongnu
Glazkovo
Caucasus
Fig. 1 | Cultural and geographical presentation of the ancient samples.
a, Geographical distribution of samples. Symbols correspond to samples
of a specific age: circle, Bronze Age; square, Iron Age; diamond, Hun
period; triangle upwards, Turk period; triangle downwards, Medieval
period. b,Each symbol has been sorted according to geographical region
highlighted on the map in a, and given in the grey boxes in b. C, Caucasus;
CS, central steppe; ES, eastern steppe; HP, Hungarian plains; PS, Pontic
steppe; STE, Siberia, Tungus and eastern steppe (STE is not marked on the
map in a, but includes steppe and non-steppe areas).
370 | NATURE | VOL 557 | 17 MAY 2018
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Article reSeArcH
The qpAdm modelling1 of this ancient genomic dataset is consistent
with these findings. The Central Sakas can be modelled as a simple
two-way mixture of Late Bronze Age pastoralists and southern Siberian
hunter-gatherers, with almost equal proportions of Bronze Age herder
(56%) and southern Siberian hunter-gatherer ancestry (44%). The
southern Siberian Tagar show unequal ancestry contributions from
Bronze Age herders (83.5%) and southern Siberian hunter-gatherers
(7.5%), as well as an additional contribution of Mal’ta (MA1 individual)-
like ancestry (9%), indicating differences in the sources of hunter-gatherer
admixture across the Sakas. The Saka population of the Tian Shan
mountains displays a high proportion of Late Bronze Age steppe
herder ancestry (70%) followed by southern Siberian hunter-gatherer
ancestry (25%), and also an additional 5% ancestry coming from a
source related to a Neolithic population from Iran. Taken together,
our data do not support the recent mtDNA-based claim of extensive
gene flow between the different Scythian groups11, but instead indicate
admixture between populations of Late Bronze Age herder descent and
various local groups, consistent with the multiple origins model
(model 3 described above).
Our data show that the culturally similar Scythians represented
genetically structured groups within the Eurasian steppes. In particular,
the Siberian Tagar, Central Sakas and the Tian Shan Sakas were
Scythian groups that arose through admixture between Late Bronze
Age pastoral groups and Inner Asian hunter-gatherers, in contrast to
the Hungarian Scythians who received gene flow from farming groups
within Europe. The additional gene flow from a source related to the
Neolithic Iranians detected in the Tian Shan Sakas suggests that south-
ern steppe nomads also interacted with the civilization of the Bactria–
Margiana archaeological complex of present-day eastern Turkmenistan.
The Xiongnu and the Hunnic expansions
Turkic language elements arguably first emerged among the Xiongnu
nomads
15
, a confederation of several nomadic tribes who occupied the
eastern steppe from the third century . They are believed to be of East
Asian ancestry16,17, although ancient Y-chromosomal data have indi-
cated a possibly heterogeneous population admixed with central steppe
nomads
18
. Huns (third–fifth century ) have previously been argued
to derive directly from the Xiongnu
19
, although others have claimed
that there is no evidence connecting the two groups20. It is com-
monly believed that the Huns spread westward, disseminating Turkic
languages throughout Central Asia at the cost of Iranian languages.
It is known that the expansion of the Xiongnu nomads affected the
movements of other cultural groups from the south-eastern side of the
Tian Shan Mountains, such as the Wusun and Kangju, whose genetic
ancestries have so far remained unknown. It has tentatively been sug-
gested on the basis of the archaeological record that they belonged to
the Iranian-speaking branch of the Indo-European language family21.
Principal component analyses and D-statistics suggest that the
Xiongnu individuals belong to two distinct groups, one being of East
Asian origin and the other presenting considerable admixture lev-
els with West Eurasian sources (Fig.2 and Extended Data Figs.1, 5;
in Fig.2 these are labelled ‘Xiongnu’ and ‘westernXiongnu’, respec-
tively). We find that Central Sakas are accepted as a source for these
‘western-admixed’ Xiongnu in a single-wave model. Consistent with
this finding, no East Asian gene flow is detected compared to Central
Sakas as these form a clade with respect to the East Asian Xiongnu in a
D-statistic, and cluster closely together in the PCA (Fig.2).
We used D-statistics (Supplementary Information section3.7) to
investigate the genetic relationship between Iron Age nomads, the East
Asian Xiongnu and the early Huns of the Tian Shan. We find that the
Huns have increased shared drift with West Eurasians compared to
the Xiongnu (Extended Data Fig.6). We tested for patterns of shared
drift between the Xiongnu and the Wusun, the preceding Sakas and
the slightly later Huns (second century ). We find that both the ear-
lier Sakas and the later Huns have more East Asian ancestry than the
Wusun. This is also apparent from model-based clustering and PCA
(Extended Data Fig.7). Similar results are seen with the contemporane-
ous and later Kangju groups that—as did the Wusun—re-emerged into
the central steppe from south-east of the Tian Shan mountains. In addi-
tion, both groups require a Neolithic Iranian-related source for model-
ling ancestral proportions in the qpAdm framework (Supplementary
Table7), together with Late Bronze Age pastoralists and the southern
Siberian hunter-gatherers. We therefore suspect that the Wusun and
Kangju groups are descendants of Bronze Age pastoralists that inter-
acted with the civilization of the Bactria–Margiana archaeological com-
plex in southern Uzbekistan and eastern Turkmenistan, yet remained
much less admixed with East Asians than did the Iron Age steppe Sakas.
Overall, our data show that the Xiongnu confederation was genet-
ically heterogeneous, and that the Huns emerged following minor
male-driven East Asian gene flow into the preceding Sakas that they
invaded (see Supplementary Information section3.6 for sex-biased
admixture rates). As such our results support the contention that the
–0.04 –0.02 0 0.02 0.04 0.06
Principal component 2
Principal component 1
–0.04 –0.02 0 0.02 0.04
0.06
–0.15
–0.10
–0.05
0
0.05
0.10
–0.15
–0.10
–0.05
0
0.05
0.10
Principal component 1
Principal component 2
Early Bronze Age steppe
Middle Bronze Age steppe
Iron Age steppe
‘Medieval’ steppe
Kazakhs
SHG
Steppe EMBA
Post-BA
Europe
Iron Age to Medieval steppe breadth
Altai/Siberian
Xiongnu
Western Xiongnu
Alan
Turk
Golden Horde Asian
Golden Horde European
Karakhanid
Karluk
Historical Kazakh
Kimak
Kipchak
Historical nomad
Medieval nomad
Saltovo-Mayaki
East Asia
Glazkovo
Andronovo
Central Saka
Hun−Sarmatian nomad
Hallstatt–Bylany
Hungarian Scythian
Lchashen Metsamor
Iron Age nomad
Sarmatian
Tagar
Tian Shan Saka
Hungarian plains nomad
Northern Lithuania
Kangju
Poprad
Tian Shan Hun
Wusun
South Central Asia
Near East/
Caucasus
Anatolia/
Europe Neolithic
Levant Neolithic
Natuan
EHG
Fig. 2 | Principal component analyses. The principal components 1
and 2 were plotted for the ancient data analysed with the present-day
data (no projection bias) using 502 individuals at 242,406 autosomal
SNP positions. Dimension 1 explains 3% of the variance and represents a
gradient stretching from Europe to East Asia. Dimension 2 explains 0.6%
of the variance, and is a gradient mainly represented by ancient DNA
starting from a ‘basal-rich’ cluster of Natufian hunter-gatherers and ending
with EHGs. BA, Bronze Age; EMBA, Early-to-Middle Bronze Age; SHG,
Scandinavian hunter-gatherers.
17 MAY 2018 | VOL 557 | NATURE | 371
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ArticlereSeArcH
disappearance of the Inner Asian Scythians and Sakas around two
thousand years ago was a cultural transition that coincided with the
westward migration of the Xiongnu. This Xiongnu invasion also led to
the displacement of isolated remnant groups—related to Late Bronze
Age pastoralists—that had remained on the south-eastern side of the
Tian Shan mountains.
Repeated conquests and waves of East Asian impact
In the sixth century , the Hunnic Empire had been broken up and
dispersed as the Turkic Khaganate assumed the military and political
domination of the steppes22,23. Khaganates were steppe nomad politi-
cal organizations that varied in size and became dominant during this
period; they can be contrasted to the previous stateless organizations
of the Iron Age
24
. The Turkic Khaganate was eventually replaced by a
number of short-lived steppe cultures25. These included the Kipchak
and the Tungusic Kimak populations, which spread southwards
towards the Tian Shan mountains and westward towards the Ural
mountains to form the Kimak Khaganate of the central steppe during
the eighth to eleventh centuries 
26
. During the eleventh century, the
Kimak Khaganate was overthrown by local Kipchak groups, who in
turn allied themselves with the Cuman of West Eurasia. Eventually the
short-lived khaganates were overtaken by the Mongol Empire, which
emerged through the unification of East Mongolian and Transbaikalian
tribes and which expanded considerably during the rule of Genghis
Khan in the thirteenth century 
26,27
(Supplementary Information
section1).
We find evidence that elite soldiers associated with the Turkic
Khaganate are genetically closer to East Asians than are the preceding
Huns of the Tian Shan mountains (Supplementary Information sec-
tion3.7). We also find that one Turkic Khaganate-period nomad was
a genetic outlier with pronounced European ancestries, indicating the
presence of ongoing contact with Europe. Only one sample here repre-
sents Kimak nomads, and it does not show elevated East Asian ancestry
(Supplementary Information section3.7). During the Kipchak period
in the eleventh century , the domination of the central steppe was
allegedly assumed by another group originating from the geographical
area of Tuva. We present genomic data from two individuals from this
period, one of whom shows increased East Asian ancestry, whereas the
other has pronounced European ancestry (samples DA23 and DA179,
respectively, in Supplementary Information section4). These individ-
uals date to the Cuman–Kipchak alliance, which incorporated both
the western and eastern steppe. For the period in which the region
became incorporated into the Karakhanid Khanate—which encom-
passed present-day regions of Uzbekistan, Tajikistan, Kazakhstan and
Kyrgyzstan—D-statistics identify a small influx of East Asian ancestry
compared to the earlier Turk period. Consistent with this, nomads
in the Karakhanid period are shifted towards East Asians compared
to earlier Turks in the PCA plot (Fig.2 and Extended Data Fig.8).
Additionally, we analysed ten culturally unaffiliated Medieval-period
nomads, most of whom showed pronounced East Asian ancestry, albeit
in very different proportions (Extended Data Fig.8). We also find the
presence of an individual of West Eurasian descent buried together
with members of Jochi Khan’s Golden Horde army from the Ulytau
mountains (see Supplementary Information section4: DA28 is East
Asian and DA29 is European). This could suggest assimilation of dis-
tinct groups into the Medieval Golden Horde, but this individual may
also represent a slave or a servant of West Eurasian descent attached to
the service of the Golden Horde members.
These results suggest that Turkic cultural customs were imposed by
an East Asian minority elite onto central steppe nomad populations,
resulting in a small detectable increase in East Asian ancestry. However,
we also find that steppe nomad ancestry in this period was extremely
heterogeneous, with several individuals being genetically distributed
at the extremes of the first principal component (Fig.2) separating
Eastern and Western descent. On the basis of this notable heterogeneity,
we suggest that during the Medieval period steppe populations were
exposed to gradual admixture from the east, while interacting with
incoming West Eurasians. The strong variation is a direct window into
ongoing admixture processes and the multi-ethnic cultural organiza-
tion of this period.
Origins and spread of the Justinian plague
A few decades after the period of Hunnic-driven mobility across the
Eurasian steppes, large areas of Europe were depopulated owing to the
Justinian plague pandemic28. Although the first reports of the pan-
demic point to an outbreak in Egypt from where it is thought to have
spread into Europe29, the primordial origins of the Justinian plague
remain unknown. The most basal strains of present-day plague (0.PE7
clade) have been found in Qinghai, south-east of the Tian Shan moun-
tains
30
, and the clade basal to the Justinian plague (0.ANT1) was found
in Xinjiang in China, thus pointing to a possible Inner Asian origin of
the Justinian plague.
Central steppePontian steppe Tian Shan, Altai and eastern steppe
40° N
50° N
60° E
A
Alta
AltaAlta
lta
A
i Moi Moi Mo
i Mo
unta
unta
unta
unta
a
a
insinsins
ns
TianTian
Tian
Tian
Sha
Sha
Sha
Sha
n
n
n
n
70° E 80° E90° E
Caspian
Sea
Present day
Middle-to-Late
Bronze Age
Medieval period
Hun period
Iron Age
Early
Bronze Age
East Asian
Eastern
hunter-gathere
r
Natuan
Western
hunter-gatherer
Europe
Fig. 3 | QpAdm results depicting the changes in ancestry across time
in Central Asia. The changes reflect a gradual increase in East Asian
ancestry in the central steppe nomads coupled to a decrease in ancestry
associated with EHGs, starting at a high level in Yamnaya and finishing
at a low level in present-day Kazakh and Kyrgyz individuals. The set of
outgroups used is: Mbuti, Ust’Ishim, Clovis, Kostenki14 and Scandinavian
hunter-gatherers.
372 | NATURE | VOL 557 | 17 MAY 2018
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Article reSeArcH
We find that two individuals, DA101 and DA147 (see Supplementary
Information section7), show detectable levels of Yersinia pestis DNA,
compatible with the characterization of the full genome sequence
at 8.7× and 0.24× coverage. The first individual (DA101) is a Hun
from the Tian Shan mountains and dates to approximately 180,
and the second individual (DA147) is from the Alan culture from
North Ossetia and is estimated archaeologically to date to the sixth–
ninth century . The genome ofthe Y. p es ti s strain DA101, which we
name 0.ANT5, branches off from the main plague lineage just basal
to the Justinian plague strain 0.ANT4, identified from an individ-
ual in Aschheim (Germany) and dated to about 530
29
(Extended
Data Fig.9). As expected, the Tian Shan strain contained the ymt
gene reported to be missing in the more-ancestral Bronze Age plague
strains
31
. The strain also displayed the loss of function mutations in
pde2, pde3, rcsA and ureD that are required for flea transmission in
the traditional ‘blocked flea’ model32 (Extended Data Fig.9). This,
coupled with a fully functional plasminogen activator gene, indicates
that the ‘Hunnic’ plague strain had full bubonic capability and flea
transmissibility.
The fact that we find a higher number of strain-specific variants
in the Aschheim strain is consistent with the difference in sampling
time (approximately 180 versus approximately 530) and the
potentially multiple replication cycles associated with pandemics30.
This is supported by the substitution rate on the branch leading to the
Aschheim strain being higher. Mutation rates in pathogens have been
hypothesized to be affected by epidemics, not only because of natural
selection but also owing to an increase in replication rate30. Therefore,
our observation of an accelerated mutation rate is consistent with this
hypothesis and supports the idea that the Ascheim strain was respon-
sible for a major outbreak—the Justinian plague.
Given that the most basal strains of present-day plague (0.PE7 clade)
originate in Qinghai30 and the clade basal to the Justinian plague
(0.ANT1) is from Xinjiang (China), two areas close to the Tian Shan
mountains, we find provisional support for the hypothesis that the pan-
demic was brought to Europe towards the end of the Hunnic period
through the Silk Road along the southern fringes of the steppes.
Discussion
The overall population history that formed the genetic composition
of present-day steppe populations is illustrated in Fig.3, in which we
model the entire known ancient and present-day diversity of Inner Asia
using the key ancestral groups. We also identify sex-specific admixture
proportions in the Iron Age (Extended Data Fig.10 and Supplementary
Information section3.6). In Fig.4, we presentthe main migratory pat-
terns. Our findings fit well with current insights from the historical
linguistics of this region (Supplementary Information section2). The
steppes were probably largely Iranian-speaking in the first and second
millennia . This is supported by the split of the Indo-Iranian linguis-
tic branch into Iranian and Indian
33
, the distribution of the Iranian lan-
guages, and the preservation of Old Iranian loanwords in Tocharian
34
.
The wide distribution of the Turkic languages from Northwest China,
Mongolia and Siberia in the east to Turkey and Bulgaria in the west
implies large-scale migrations out of the homeland in Mongolia since
about 2,000 years ago
35
. The diversification within the Turkic languages
suggests that several waves of migration occurred
36
and, on the basis of
the effect of local languages, gradual assimilation to local populations
had previously been assumed
37
. The East Asian migration starting with
the Xiongnu accords well with the hypothesis that early Turkic was the
major language of Xiongnu groups
38
. Further migrations of East Asians
westwards find a good linguistic correlate in the influence of Mongolian
b2100–1200 BC c1200–200 BC3000–2100 BC
a
110° E
100° E
70° E
60° E
50° E
40° E
30° E
20° E
70° N
60° N
50° N
40° N
CS
ES
PS
CS
ES
PS
ES
PS
d200 BC–AD 600 eAD 600–1500
CS
ES
PS
CS
ES
PS
CS
90° E
A
r
c
t
i
c
O
c
e
a
n
M
e
d
i
t
e
r
r
a
n
e
a
n
S
e
a
Yamnaya and Afanasievo expansion
Sintashta, Srubnaya and
Andronovo expansion
Scythian expansion
Late Bronze Age admixture
Xiongnu–Hunnic expansion
Asian Medieval impact
Fig. 4 | Summary map. Depictions of the five main migratory events
associated with the genomic history of the steppe pastoralists from
3000 to the present. a, Depiction of Early Bronze Age migrations
related to the expansion of Yamnaya and Afanasievo culture. b, Depiction
of Late Bronze Age migrations related to the Sintashta and Andronovo
horizons. c, Depiction of Iron Age migrations and sources of admixture.
d, Depiction of Hun-period migrations and sources of admixture.
e,Depiction of Medieval migrations across the steppes.
17 MAY 2018 | VOL 557 | NATURE | 373
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
on Turkic and Iranian in the last millennium39. As such, the genomic
history of the Eurasian steppes is the story of a gradual transition from
Bronze Age pastoralists of West Eurasian ancestry towards mounted
warriors of increased East Asian ancestry—a process that continued
well into historical times.
Data availability
Sequence data were deposited in the European Nucleotide Archive (ENA) under
accession number PRJEB20658 (ERP022829). Single nucleotide polymorphism
data for present-day populations are available, after ethical validation, from
the European Genome-Phenome Archive (EGA, https://www.ebi.ac.uk/ega/)
under accession number EGAS00001002926. Plague reads were deposited in the
European Nucleotide Archive (ENA) under accession number PRJEB25891.
Online content
Any Methods, including any statements of data availability and Nature Research
reporting summaries, along with any additional references and Source Data files,
are available in the online version of the paper at https://doi.org/10.1038/s41586-
018-0094-2.
Received: 18 April 2017; Accepted: 3 April 2018;
Published online 9 May 2018.
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Acknowledgements We thank K. Magnussen, L. Petersen, C. Mortensen and
A. Seguin-Orlando at the Danish National Sequencing Centre for producing
the analysed sequences; P. Reimer and S. Hoper at the 14Chrono Center
Belfast for providing accelerator mass spectrometry dating; S. Hackenbeck for
discussing palaeodietary reconstructions; D. Christiansen Appelt, B. Heyerdahl,
the Explico Foundation team, J. Isakova, B. Daulet, A. Tairov, N. Abduov,
B.Tudiyarov, V. Volkov, M. Akchurin, I. Baimukhan, N. Namdakov, Y. Yusupov, E.
Ramankulov, A. Nurgaziyev and A. Kusaev for important assistance in fieldwork;
J. Stenderup, P. V. Olsen and T. Brand for technical assistance in the laboratory;
all involved archaeologists, historians and geographers from Kazakhstan: A.
Suslov, I. Erofeeva, E. Nurmaganbetov, B. Kozhakhmetov, N.Loman, Y. Parshin,
S. Ladunskiy, M. Bedelbaeva, A. Marcsik, O. Gábor, M.Půlpán, Y. Kubeev, R.
Zhumashev, K. Omarov, S. Kasymov and U.Akimbayeva; P.Rodzianko for
creating the initial contact between P.d.B.D., S.E. and E.U.; and S. Jacobsen and
J. O’Brien for translating and proofreading Russian contributions. E.W. thanks
St. John’s College, Cambridge for support and for providing an environment
facilitating scientific discussions.B.Boldg. thanks the Taylor Family-Asia
Foundation Endowed Chair in Ecology and Conservation Biology. The project
was funded by the Danish National Research Foundation (E.W.), the Lundbeck
Foundation (E.W.) and KU2016 (E.W.).
Reviewer information Nature thanks T. Higham, D. Anthony, B. Shapiro, R.
Dennell and the other anonymous reviewer(s) for their contribution to the peer
review of this work.
Author contributions E.W. initiated and led the study. P.d.B.D., E.W., E.U. and
E.H. designed the study. P.d.B.D. and N.M. produced the data. P.d.B.D., N.M., S.R.,
M.S., G.R., T.Ko., A.Gol., M.W.P., A.G.P. and K.N. analysed or assisted in analysis
of data. P.d.B.D., E.W. and K.K. interpreted results with considerable input from
M.S., R.N., M.P., N.K., S.R., L.O., M.E.A. and J.V.M.-M. P.d.B.D., E.W., K.K., M.P. and
S.R. wrote the manuscript with considerable input from N.K., L.H., M.S., R.N.,
M.E.A., L.O. and J.V.M.-M., with contributions from all authors. P.d.B.D., M.E.A.,
L.O., E.U., N.B., V.L., G.A., K.A., A.Ald., A.Alp., G.B., V.I.B., A.B., B.Boldb., B.Boldg.,
C.D., S.E., D.E., R.D., E.D., V.E., K.M.F., A.Gor., A.Gr., H.H., T.H., Z.K., R.K., E.K., A.Ko.,
T.Ku., A.Ku., I.K., N.L., A.M., V.K.M., I.V.M., I.M., E.M., V.M., G.M., B.N., Z.O., I.P., K.P.,
V.S., I.S., A.L., K.-G.S., T.S., K.T., A.T., T.T., D.V., L.Y., S.U., V.V., A.W. and E.H. excavated,
curated, sampled and/or described analysed skeletons; all authors contributed
to final interpretation of data.
Competing interests The authors declare no competing interests.
Additional information
Extended data is available for this paper at https://doi.org/10.1038/s41586-
018-0094-2.
Supplementary information is available for this paper at https://doi.
org/10.1038/s41586-018-0094-2.
Reprints and permissions information is available at http://www.nature.com/
reprints.
Correspondence and requests for materials should be addressed to E.W.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
374 | NATURE | VOL 557 | 17 MAY 2018
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Article reSeArcH
Extended Data Fig. 1 | Analyses of Iron Age clusters. a, PCA of Iron
Age nomads and ancestral sources, explaining the diversity between
them using 74 individuals at 242,406 autosomal single nucleotide
polymorphism (SNP) positions. b, PCA of Iron Age nomads alone using
29 individuals at 242,406 autosomal SNP positions. c, PCA of Xiongnu,
‘Western’ Xiongnu, Tian Shan Huns, Nomads Hun Period, and Tian
Shan Sakas, using 39 individuals at 242,406 autosomal SNP positions.
d, Model-based clustering at K=7 illustrating differences in ancestral
proportions. Labelled individuals: A, Andronovo; B, Neolithic European
(Europe_EN, in a); C, Baikal hunter-gatherers; D, Neolithic Iranian
(Iran_N, in a). Here we illustrate the admixture analyses with K=7 as it
approximately identifies the major component of relevance (Anatolian/
European farmer component, Caucasian ancestry, EHG-related ancestry
and East Asian ancestry). The asterisk indicates an individual flagged as a
genetic outlier. d,e,Results for model-based clustering analysis at K=7.
Here we illustrate the admixture analyses with K=7 as it approximately
identifies the major component of relevance (Anatolian/European farmer
component, Caucasian ancestry, EHG-related ancestry and East Asian
ancestry). Panel d is focused on the Iron Age, while e is focused on the
transition to the Hun period.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
Extended Data Fig. 2 | Illustration of shared ancestry between Neolithic
farmers and Iron Age nomads. Results for model-based clustering
analysis at K=7, plotting only one individual from relevant groups, to
illustrate shared ancestry between Neolithic farmers from Europe, Late
Bronze Age nomads and Iron Age nomads, not shared with Early Bronze
Age nomads. MBLA, Middle-to-Late Bronze Age; Neo, Neolithic.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Article reSeArcH
Extended Data Fig. 3 | Illustration of gene flow into Hungarian
Scythians. We represent all D(Test, Mbuti; Andronovo, Hungarian
Scythians) that deviate significantly from 0 (that is, higher than 3× the
standard errors). The reported numbers are the D-statistics and the
3standard errors were plotted as error bars. The number of individuals per
population can be found in Supplementary Tables3, 4.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
Extended Data Fig. 4 | Illustration of negative admixture f3 statistics
for Iron Age populations. Plot shows f3(Bronze Age Test 1, Bronze Age
Test 2; Iron Age Test). The reported numbers are of the f3 statistics, and the
3standard errors were plotted as errors bars. The number of individuals
per population can be found in Supplementary Table3.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Article reSeArcH
Extended Data Fig. 5 | Illustration of West Eurasian gene flow into
groups forming the Xiongnu culture. We represent all D(Test, Mbuti;
‘Western’ Xiongnu, Xiongnu) that deviate significantly from 0 (that is,
higher than 3× the standard errors). The reported numbers are the D-
statistics and the 3 standard errors were plotted as error bars. The number
of individuals per population can be found in Supplementary Tables3, 4.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
Extended Data Fig. 6 | Illustration of West Eurasian ancestry in early
Tian Shan Huns. We represent all D(Test, Mbuti; Tian Shan Huns,
Xiongnu) that deviate significantly from 0 (that is, higher than 3× the
standard errors). The reported numbers are the D-statistics and the
3standard errors were plotted as error bars. The number of individuals per
population can be found in Supplementary Tables3, 4.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Article reSeArcH
Extended Data Fig. 7 | Analyses of Xiongnu and Hun period population
clusters. a, PCA of Xiongnu, ‘Western’ Xiongnu, Tian Shan Huns,
Hun-period nomads, Tian Shan Sakas, Kangju and Wusun, including
49individualsanalysed at 242,406 autosomal SNP positions. b, Results for
model-based clustering analysis at K=7. Here we illustrate the admixture
analyses with K=7 as it approximately identifies the major component of
relevance (Anatolian/European farmer component, Caucasian ancestry,
EHG-related ancestry and East Asian ancestry). Individual A is a southern
Siberian individual associated with the Andronovo culture.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
Extended Data Fig. 8 | Analyses of Turk- and Medieval-period
population clusters. a, PCA of Tian Shan Hun, Turk, Kimak, Kipchack,
Karakhanid and Golden Horde, including 28 individualsanalysed at
242,406 autosomal SNP positions. b, Results for model-based clustering
analysis at K=7. Here we illustrate the admixture analyses with K=7 as
it approximately identifies the major component of relevance (Anatolian/
European farmer component, Caucasian ancestry, EHG-related ancestry
and East Asian ancestry).
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Article reSeArcH
Extended Data Fig. 9 | Maximum likelihood phylogenetic
reconstruction of Y. pestis. This tree reveals the basal position of the Tian
Shan sample (0.ANT5, DA101, 186) compared to the Justinian plague
sample (0.ANT4, A120, 536). These two samples are shown in orange
italics. Other ancient plague samples included in the tree are Bronze
Age samples (0.PRE1 and 0.PRE2) and a Black Death sample (1.PRE1).
Numbers on nodes indicate bootstrap support (not all of which are shown,
for clarity) and certain branches have been collapsed for clarity. Branch
lengths are substitutions per site.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

ArticlereSeArcH
Extended Data Fig. 10 | Analyses of sex-specific contributions to
Iron Age populations. Estimates of the male and female contributions
from each source populations (left column) to each of the four admixed
populations (right column) using a previously published method40. For
each admixed population, we compared the observed mean autosomal
and X-chromosomal ancestry, estimated in qpAdm, to that calculated
under a constant admixture model on a grid of sex-specific contribution
parameters ranging from 0 to 1 in 0.025 increments using a Euclidean
distance. The logarithms of the ratio of male to female contribution
parameters that produce the smallest 0.1% of distances from the data are
plotted, with the full range of parameter values in grey, the middle 50% in
black, and the median value in red. The dashed line indicates equal male
and female contributions.
© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

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of software and respective versions:
CASAVA v1.8.2
AdapterRemoval v2.1.3
bwa v0.7.10
bwa mem 0.7.10
picard tools v1.127
bamUtil v1.0.14
samtools v1.3.1
GATK v3.3.0 and v 3.6*
pysam 0.7.4 (python module)
bedtools 2.27.1
mapDamage2.0
contamMix v1.0-5
SHRiMP 2.2.3
YFitter v0.2
Haplogrep 2.0

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nature research | reporting summary March 2018
ANGSD v0.915
PRANK v.150803
BEASTv1.8.2
schmutzi
admixtools v4.1
NGSrelate
plink v1.07* and v1.9
ADMIXTURE v1.3
RAxML-8.1.15
SnpEff
SPAdes-3.9.0
R 3.2.3
python 2.7.12
perl v5.22.1
CALIB
NOTE: Versions marked with * were used for Y chromosome analyses.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers
upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.
Data
Policy information about availability of data
All manuscripts must include a data availability statement. This statement should provide the following information, where applicable:
- Accession codes, unique identifiers, or web links for publicly available datasets
- A list of figures that have associated raw data
- A description of any restrictions on data availability
Sequence data were deposited in the European Nucleotide Archive (ENA) under accession PRJEB20658. SNP data for present-day populations are available after
ethical validation in the European Genome-Phenome Archive (EGA) under accession: EGAS00001002926.
Field-specific reporting
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Life sciences Behavioural & social sciences
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Life sciences
Study design
All studies must disclose on these points even when the disclosure is negative.
Sample size We did not rely on statistical methods to predetermine sample sizes. Sample sizes in ancient population genetic studies are limited by the
number of samples yielding endogenous DNA proportions amenable to whole genome sequencing.
Data exclusions We selected 137 samples for whole-genome sequencing, out of all screened samples, based on their endogenous content and low
contamination estimates. These criteria are described in detail in Supplementary Section 3.1. Furthermore, closely related individuals were
excluded from analyses requiring population allele frequencies.
Replication We did not attempt to specifically replicate experimental findings. But we note that samples from the same population carry similar genetic
signatures. Moreover, genome-wide data allows for the analysis of multiple realisations of the sample history, by studying hundreds of
thousands of SNP sites.
Randomization No experimental groups or effect sizes were measured in this study, thus we did not implement any random group assignment.
Blinding No blinding techniques were implemented, as exprimental group assignment is not relevant for popluation genetic history studies of this kind.

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nature research | reporting summary March 2018
Materials & experimental systems
Policy information about availability of materials
n/a Involved in the study
Unique materials
Antibodies
Eukaryotic cell lines
Research animals
Human research participants
Human research participants
Policy information about studies involving human research participants
Population characteristics No experimental procedures were carried out on human participants. We genotyped 502 individuals from 16 self-reported
ethnicities from Altai, Central Asia, Siberia and the Caucasus. Sampling procedures are detailed in Supplementary Section 5.
Method-specific reporting
n/a Involved in the study
ChIP-seq
Flow cytometry
Magnetic resonance imaging