supplementary materials for...jan 06, 2021 · excavated in 1994 (9).this burial is a...

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Supplementary Materials for

Human population dynamics and Yersinia pestis in ancient northeast Asia

Gülşah Merve Kılınç*, Natalija Kashuba, Dilek Koptekin, Nora Bergfeldt, Handan Melike Dönertaş,

Ricardo Rodríguez-Varela, Dmitrij Shergin, Grigorij Ivanov, Dmitrii Kichigin, Kjunnej Pestereva, Denis Volkov, Pavel Mandryka, Artur Kharinskii, Alexey Tishkin, Evgenij Ineshin, Evgeniy Kovychev, Aleksandr Stepanov, Love Dalén, Torsten Günther, Emrah Kırdök, Mattias Jakobsson, Mehmet Somel, Maja Krzewińska, Jan Storå*, Anders Götherström*

*Corresponding author. Email: [email protected] (A.G.); [email protected] (J.S.);

[email protected] (G.M.K.)

Published 6 January 2021, Sci. Adv. 7, eabc4587 (2021) DOI: 10.1126/sciadv.abc4587

The PDF file includes:

Supplementary Text Figs. S1 to S32 Tables S1 to S24 Legends for data files S1 to S5 References

Other Supplementary Material for this manuscript includes the following: (available at advances.sciencemag.org/cgi/content/full/7/2/eabc4587/DC1)

Data files S1 to S5

Supplementary Text

Archaeological background

General archaeological information about the northeast Asia

The archaeological finds from the Pleistocene, corresponding to the Middle to the Upper

Palaeolithic periods, in the northeast Asia are rather scarce. This has been explained by the volatile

climatic conditions and overall fluctuations and changes of the environment affecting the

conditions for the human groups: the Ice Age cold period, the late Pleistocene temperature

fluctuations and the post-tectonic activity of the Baikal rift zone. During the period corresponding

to the Palaeolithic period, Baikal became a deep lake while the eastern terraces of the Baikal basins

were uplifted and the formation of the Baikal outlet into the Angara River 60,000 years ago

occurred (7 ). There is a correlation between these events and the scarcity of the archaeological

sites in the Pleistocene. The Khaiyrgas cave is one of the few notable sites providing the

opportunity to view the collections of artefacts from several periods, starting from the Upper

Palaeolithic.

A different scenario was seen in the Holocene populations of northeast Asia, represented by a

diversity of cultural complexes, with a continuous presence of human occupation in some of the

ecologically favourable areas up until today. The general chronological outline for the human

groups close to Baikal during the first half of the Holocene is characterized by two main complexes

in the Early Mesolithic-Middle Neolithic and in the Late Neolithic-Bronze Age associated with

the Kitoi and the Glazkovo cultural complexes, respectively. On the territory of the Baikal region

(Angara, Upper Lena, Baikal, Vitim), the late Mesolithic burial complexes were identified - related

to the Khinsky and Schukin burial traditions; Early Neolithic - the Chinese tradition of burials;

Late Neolithic — Isakovskaya, Serovskaya, Late-Serovskaya for Priolkhonya, “burial traditions”

for the Upper Lena “archaic”.

A Mesolithic human occupation has been discovered in both the Cis-Baikal and the Trans-Baikal

areas. Some aspects of the Mesolithic cultures in northeast Asia are considered as pan-Eurasian,

such as the use of red ochre. Red ocher is found in burial complexes of the Early and Late Neolithic

of Pribaikalye. Regional differences are seen in the broad variety of local lithic traditions, use of

different materials (for example nephrite) as well as composite tools, fishery-associated artefacts

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and, finally, the early use of pottery. The complexity of the Mesolithic/Early Neolithic cultures of

the northeast Asia is seen in the variation of the material used by people to make lithic tools and

exceptional in the case is the Dzhylinda burial included in the present study (sample: irk00x,

Dzyhlinda-1). The variation of the cultures in the early Holocene may be explained by the

specialization of regional groups as means of adaptation to different ecological environments,

which vary from alpine and forested areas to lowland steppe and tundra in northeast Asia (7 ). The

Late Neolithic-Bronze Age complex of cultures (Serovo, Isakovo and Galzkovo) show more

homogenous expressions and characteristics than the Mesolithic and Early Neolithic cultural-

complexes, but with a large variation in pottery styles.

There is a period between the two main cultural complexes mentioned above, during which

archaeological finds in the Cis-Baikal area are few. This “hiatus” has been in focus of discussions

and different views and interpretations have been presented, suggesting that it may have lasted

anywhere between 100 and a 1,000 years. Other “hiatus” periods have most often been associated

to unfavourable ecological conditions (7 ).

The development of the human populations and the movements of groups are complicated to

follow and interpret due to the complexity of the archaeological record. Often the burial sites have

several cultural layers associated to different cultural manifestations and the specific chronological

circumstances are not always fully understood. Exemplary in this case is the

Cyclodrom/Lokomotiv, the large necropolis in Irkutsk, which contained burials from the

Mesolithic and up to the Bronze Age. Regarding the movements of people during the first part of

the Holocene, there has been a general consensus of directions of mobility and migrations, which

are linked to the appearance and dispersal of Late Neolithic and Bronze Age culture complexes

through the areas near Baikal and the Lena river valley. The most often identified directions of

mobility in these periods have been from west to east and from south to north.

Archaeological contexts of the studied individuals

In this study, we studied 40 samples from 5 distinct administrative regions in Russian Federation

including: Trans-Baikal, Cis-Baikal, Yakutia, Krasnoyarsk Krai and Amur Oblast.

Chronologically, the samples cover a time period between the Late Upper Paleolithic and the

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Medieval era. The majority of individuals in our study are dated to the Neolithic and Bronze Ages.

A Late Upper Paleolithic individual (yak025, Khaiyrgas-1) included in this study was recovered

in the Khaiyrgas Cave in Yakutia (18). Archaeological information for 38 of the 40 samples (Table

S1) sequenced here was provided in (18). In this study, we report 2 additional individuals including

cta016 which is from the Trans-Baikal region and dated to 8,345 to 8,185 BP and Matta-1 (N2a)

which is from the Yakutia region and dated to 6,845 to 6,665 BP. We provide archaeological

information for these two samples below.

Archaeological periods do not have heuristic meaning, since there are no specific criteria for

distinguishing these periods as in European context while analyzing materials from Asia. For

example, pottery appears in the Late Paleolithic and Mesolithic; Paleolithic traditions of lithic

technologies exist in the Neolithic. Still, archaeological periods for the analyzed individuals have

been determined according to a general chronological frame of the north Asian archaeological

cultural complexes (7 –8 ) (Table S1). In brief, genome sequence data from Yakutia include a

Late Upper Palaeolithic (c.16,900-16,450 BP) individual (0.3X genome coverage); two

Early/Middle Neolithic (c.6,850-6,190 BP) individuals (0.03X to 0.05X); six Late Neolithic

(c.4,780-3,080 BP) individuals (0.2X to 8.9X); and an Early Iron Age (c.2,750-2,490 BP)

individual (0.07X); from Trans-Baikal encompasses two Mesolithic (c.8,515-8,185 BP)

individuals (1.1X to 4.7X), five Neolithic (c.7,460-5,940 BP) individuals (0.1X to 3.8X); and a

Bronze Age (c.3,210-3,000 BP) individual (0.1X); from Cis-Baikal consists of two Mesolithic

(c.8,980-7,855 BP) individuals (2.17X to 3.49X); nine Neolithic (c.6,100-4,600 BP) individuals

(0.4X to 14.5X); eight Bronze Age (c.4,530-3,700 BP) individuals (0.1X to 8.7X); and a Medieval

(c.675-560 BP) individual (0.5X); from Krasnoyarsk Krai encompasses a Bronze Age (c.4,280-

4,085 BP) individual (13.6X); and from Amur Oblast covers an Iron Age (c.1,345-1,270 BP)

individual (0.7X) (fig. S1, table S1). Below we present a short description of the archaeological

contexts of the studied individuals:

Cis-Baikal group

Of the studied 40 individuals, 20 were from the Cis-Baikal area encompassing Angara River

basin, Lena River basin and Lake Baikal region.

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Angara river group (10 individuals)

The sites of Cyclodrome (Lokomotiv) (irk051, Cyclodrome-1) and Glazkovo (irk036) both belong

to the Glazkovo necropolis in Irkutsk (8 , 8 ). The sites were excavated by several researchers

during the 20th century (8 –8 ). The Glazkovo necropolis in Irkutsk contains burials belonging

to both the Kitoi and the Glazkovo cultural-complexes (8 ). The individual from Glazkovo

necropolis (irk036) belongs to the Glazkovo culture, which dates to Early Bronze Age. The Suhaja

Pad’ Buret’ site, burial 2 (irk025) is from the Early Bronze Age (8 –8 ). The Ust’-Dolgoe (Ust’-

Dolgaya) site, burial 3 (irk022) is also a Glazkovo site, based on the burial inventory (8 ). Chastaja

(Chastye) Padi (irk033) is both a burial and a settlement site. The burials belong to Glazkovo

culture while the settlement site had a layer with fragments of pottery with net-imprint (8 ).

Anosovo-1 (irk050) was excavated from an Eneolithic Glazkovo site (8 ). Podostrozhnoe is a term

used for a group of sites, including Kirpichnyj Saraj (irk034), Gorodische site N 1 (irk040) and

Podostrozhnoe site N 3 (irk057). Burial 3 from the Zarubino site (irk032) is a Medieval burial.

Lena river group (7 individuals)

The sites at Zvjozdochka (irk061) were excavated by Okladnikov in 1930 at the left bank of Lena

river. These sites were classified as Glazkovo culture sites. The sites at Korkino (irk030),

Shishkino N1 (irk068) and Makarovo (irk017) are also classified as Glazkovo culture sites. The

Silinskij burial site (irk008) lies on the left bank of Lena River. Popovskij Lug is a collective name

used for a number of Neolithic-Bronze Age sites (8 ). In 2010 an archaeological expedition at

Popovskij Lug II unearthed a single male burial (irk007, Popovskij-1). The burial is the oldest

earliest documented burial in Cis-Baikal with ceramic as grave goods (8 ) and attributed to the

early Neolithic of Baikal region based on the morphology of the burial equipment and the presence

of ceramics. Makrushino (burial 26, mak026) is a burial site containing material from the Early

Neolithic to the Bronze Age in the Kachug District (8 ).

Baikal Lake (3 individuals)

The Mys Uyuga burial 2 (individual 1- irk071) is a double burial situated on the peninsula of Mys

Uyuga ( 9 0, 9 ). The Shamanka 2 site (Iindividual 1, irk076) is a site situated on the southern side

of the cape Shamanka (7 ). The Sokhter site, complex 1 contains a single burial (burial 5, irk075)

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excavated in 1994 (9 ). This burial is a Shumilikhinskaja burial type, and dated to the

Neolithic/Early Bronze Age (7 ).

Trans-Baikal group (8 individuals)

The analysed burials in the Trans-Baikal group are all located east of the Lake Baikal. The sites

are: Izvestkovaja-1 (burial 1-brn008 and burial 2-brn001), Nozhyj lake burial site-2 (burial 6,

skeleton 3, brn012 and one individual from a burial without a number, brn002), Okoshki-1

(irk078), Dvorcy-Dacha burial (brn003) and Dzhylinda (irk00X, Dzhylinda-1). Chronologically

the samples are spread from c.8,514 and and 5,940 cal BP (9 ). The Okoshki-1 Burial 23 (irk078)

is dated to the Bronze Age (9 , 9 ). We include one new individual from the area in this study

(cta016). It is from one of the few known Stone Age burial grounds in Trans-Baikal region. The

site is located 7 kilometers off the Duroy village, on the western side of the Bol’shaja Kanga - 1

mountain (Большая Канга-1) by the Argun river. From 65 burials two were considered to be Stone

Age burials, based on for example appearance of red ochre by the remains of the individual. A

tooth from mandible of the individual 1 was taken for analyses. The bone tools and remaining

inventory from this part of Trans-Baikal suggests a hunter/fisher-gatherer lifestyle (9 ).

Yakutia (Sakha Republic) group (10 individuals)

The samples from Yakutia located geographically in three areas: Southwestern Yakutia (Khaiyrgas

Cave at the Lena river (yak025, Khaiyrgas-1)), central Yakutia (samples=yak030 (N3a), N4a1,

N4b2, N5a (Onnyos-1)) and northeastern Yakutia (yak021-024). The following sites are included

in the present study; Khaiyrgas cave (yak025, Khaiyrgas-1), Onnyos (N5a, Onnyos-1),

Kyordyughen (Kyordyughen 2, N4a1; Kyordyughen 1, burial 1, N4b2), Kamenka 2 (individual 1,

Kamenka-1, yak022; individual 2, Kamenka-2, yak023; and individual 3, yak024, Kamenka-3);

Pomazkino (yak021), and Dyupsya (yak030), (8, 9 ). The Onnyos burial (N5a, Onnyos-1) belongs

to the Belkachi culture complex (9 ). The Kyordyughen site is dated to the Late Neolithic (9 , 9 ).

Kyordyughen 1 is a double burial and we include both individuals (N4b2, Ind 1) and (N4a1, Ind

2) ( ). The Kamenka-II burial contained three juvenile individuals (9 , 10 ) (individual 1-

yak022, individual 2-yak023 and individual 3-yak024) (10 ). From the Pomazkino-III site we

include burial 2 (yak021) (9 ). The Dyupsya burial (yak030, labelled as N3a in (18) is dated to the

Early Iron Age (10 3, 10 ). We include one previously unpublished individual from the area (N2a,

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Matta-1). It is from the Matta burial which was found on the terrace of the Matta Lake which is

located in Megino-Kangalassky ulus (district), 26 km east of the Lena River. The skeleton

belonged to a female and had bones from a metatarsal or metacarpal from a species of the genus

Lepus instead of the left hand of the individual (10 ). The fragments taken for the analyses are

bones from left foot: metatarsale 1, os cuneiforme 2 (10 ).

Krasnoyarsk Krai (1 individual)

The region of Krasnoyarsk Krai is represented by burial 1 (kra001) from the Nefteprovod-2 site.

Amur Oblast (1 individual)

The Blagoveschensky District of Amur Oblast is represented by burial 2 (bla001) from the

Oktyabr’skoe site.

Radiocarbon dating and stable isotope analysis

All samples except yak024 (Kamenka-3) were radiocarbon dated using AMS radiocarbon dating

(table S1) (18). Kamenka-3 could not be dated due too poor quality of the sample but it was found

in the same burial with yak022 (Kamenka-1) and yak023 (Kamenka-2). Calibration of the

conventional radiocarbon ages was performed using Oxcal version 4.3.2 (10 ), and the IntCal13

atmospheric curve (10 ). Calibrated results (BCE) were reported with 95% confidence intervals

(2σ) (figure S1, table S1). The isotopic values for a few samples exhibit elevated δ15N-values

(>+16) (table S1) (7 ). A few of these values were measured on deciduous teeth and probably

exhibit an effect of weaning. Although some level of freshwater reservoir effect (FRE) might affect

the age estimations this does not have major consequences for the present study (7 ).

Evaluation of biological relatedness

In Trans-Baikal group, we found that brn002 was a second or third degree relative of brn012. In

Cis-Baikal group, irk022 was a 3rd-5th degree relative of irk025. Within the Yakutia group,

yak021, yak022 (Kamenka-1), yak023 (Kamenka-2) and yak024 (Kamenka-3) were biologically

related at different degrees from first to third-fifth degree (Table S1). We excluded from the

frequency-based analyses one individual from each pair of related individuals with a k0 values <

0.9. The excluded individuals are brn002, irk022, yak024 (Kamenka-3), yak023 (Kamenka-2),

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yak021 (Table S1). Note that the high genetic diversity within the ancient samples due to their

wide spatial and chronological differences may produce an underestimation of the relatedness

degree between some of the studied individuals.

Uniparental markers

Y haplogroups

All individuals were accredited either to Y macro-haplogroup Q or N. The one possible exception

was individual irk032 (probable carrier of Hg I*), which was dated to the Medieval period. In

short, all of the oldest (Mesolithic and Neolithic) and most eastern (Trans-Baikal and Yakutia)

individuals were carriers of N1c1a1 lineage, while Bronze Age males from Cis-Baikal region were

all carriers of Q1a2a and its variants. The individual from Cis-Baikal region (irk007, Popovskij-1)

may have been a carrier of N1c2b2 lineage associated with present-day Khanty and Komi

populations of western Siberia (14). This pattern is in line with earlier findings suggesting both

lineages were widespread among individuals from Neolithic Lokomotiv and Shamanka cultures

around Lake Baikal (16) (Table S18).

Mitochondrial haplogroups

All individuals carried non-African mitochondrial macrohaplogroups of M, N and R (18) (Table

S1). Individuals from Trans-Baikal group carried east Eurasian haplogroups of A, D, C, G and

their sub-haplogroups. Cis-Baikal group carried A, C, D, F and their sub-haplogroups and also one

Cis-Baikal individual carried R1b mitochondrial haplogroup. Similarly this R1b haplogroup was

also found in Khaiyrgas-1 (yak025), the Late Upper Palaeolithic subadult female from Yakutia.

Other Yakutia individuals carried the A, C, D and F haplogroups (Table S1) (18).

Model-based clustering for modern populations

We run the ADMIXTURE on modern samples and projected the ancient samples on this. At this

point, to decide which K explains the observed pattern better, we examined each K and present the

results for all Ks (fig. S3, table S4).

In brief, at K=2, modern populations separated into African (dark-red) and non-African (navy)

components; ancient Siberians carried non-African component. At K=3, the new component

separated present-day east Asia & Native America populations (dark-green) and west Eurasia

populations (navy); ancient Siberians carried mostly the east Asia component (dark-green) and to

a lesser degree the west Eurasia component (navy). At K=4, the new component separated present-

day east Asia (dark-green) and Native America (purple) populations; ancient Siberians carried

slightly more east Asia (dark-green), and to a lesser degree Native America (purple) and west

Eurasia (navy) components. At K=7, the new component separated present-day southeast Asia

(brown) and east Asia (dark-green) populations; ancient Siberians carried this component at low

levels compared to east Asia (dark-green) component. At K=8, the new component (yellow)

maximized in present-day Far East populations including Itelmen and Koryak (se fig. S4 for

geographical locations of populations); ancient Siberians carried almost equal amount of Far East

(yellow), east Asia (dark-green), and west Eurasia (navy) components and less amount of Native

America (purple) and southeast Asia (brown) components. At K=9, the new component (light-

blue) split up the west Eurasia populations into north (navy) and south (light-blue) components

and also separated the west European Mesolithic hunter-gatherers and Neolithic farmers; this

component present in very low levels in ancient Siberians. At K=13, Siberian ancestry split up into

Far East (pink-orange) and north Siberian (yellow) components; this new Far East (pink-orange)

component was present in ancient Siberian genomes in low amount compared to north Siberian

(yellow) component. Starting from K=14 to K=16 the observed pattern continued, Therefore, we

present the results for K=14 in (Fig. 2 and fig. S4).

Analysis for Yersinia pestis (Y. pestis)

Y. pestis is recently diverged from a less virulent species Y. pseudotuberculosis (10 ). Therefore,

one of the main methodological problems to identify Y. pestis sequences in archaeological samples

is the sequence similarity of these two closely related species. To this end, a hybrid genome

combining Y. pestis and Y. pseudotuberculosis reference genomes was created in (39). In this

study, aDNA reads were aligned to this hybrid genome and the reads that were mapped to Y. pestis

CO92 reference genome were extracted. To judge the taxonomical origin of Y. pestis sequences,

edit distance distribution, length distribution, deamination patterns, and breadth of coverage

information were used. Edit distance is the number of substitutions between the DNA sequence

and its respective reference genome portion. It implies the similarity between the reference genome

and the aligned read and it could be used as a marker to judge the quality of the alignment. Most

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of the reads should be perfectly aligned to the reference genome (that means 0 edit distance).

Deamination patterns at the 5’ and 3’ ends of the DNA sequences prove the authenticity of the

sequences. Right skewed length distribution (with a mean around 50bp) shows that the DNA

sequences are fragmented thus supporting the authenticity. The genome coverage and a

homogenous genome-wide distribution of the alignments is an important factor to prove

authenticity and presence of the microbe (10 ). Generally, reads could stack in multi-locus

repetitive regions that share the sequence homology between bacterial species. Those areas results

with a peak in the coverage and causes misinterpretation. So, a careful examination of the read

distribution is also important.

In this study we analyzed 205 sequence libraries from 40 different samples to detect the Y. pestis

presence. In Anosovo-1 (irk050), Kamenka-1 (yak022) and Kamenka-2 (yak023) we detected

notable amounts of aDNA reads associated with Y. pestis. Specifically, Our 9,523 aDNA reads in

Anosovo-1, 2,480 aDNA reads in Kamenka-1, and 4,176 aDNA reads in Kamenka-2 were ssigned

to Y. pestis CO92 reference genome (Table S20). The Kamenka-2 from Yakutia in eastern Siberia

is to our knowledge the most northeastern findings of Y. pestis to this day (fig. S23).

Identification of Y. pestis aDNA sequences in Anosovo-1

After the mapping to the hybrid genome and filtering processes, we found that 9,395 aDNA reads

specifically mapped to Y. pestis genome in the Anosovo-1 sample. After removing the optical PCR

duplicates, 3,289 of aDNA reads were used for the further analysis. We observed that 1650 aDNA

reads aligned to CO92 reference genome with 0 edit distance followed by 991 aDNA reads with

an edit distance 1,363 aDNA reads with 2 edit distance, and 166 aDNA reads with an edit distance

3 (fig. S24A). Also the fragment length distribution was skewed with a mean of 54.1657 nucleotide

(fig. S24B). Nucleotide misincorporation patterns showed the authentic deamination patterns at

the end of the DNA sequences (fig. S24C). The overall coverage was 1.85% for the whole genome.

Y. pestis CO92 genome has one chromosome and three plasmids so it is possible to check the

coverage for each of them. Table S21 shows the statistics for the individual sequences in Y. pestis

genome. Results show that we covered %3.66 of the Y. pestis CO92 chromosome (table S21).

Reads were also homogeneously distributed among the chromosomes except pPCP1 plasmid (fig.

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S25). These plots should be interpreted with caution since it is not possible to make X axis wide

enough to accomodate all alignments. Still, reads were distributed among the genome

homogeneously. Also, we checked the alignments using IGV. We did not find any spurious

mappings. We observed that more than 90% of the aDNA reads aligned to Y. pestis genome with

less than 3 edit distance.

Identification of Y. pestis aDNA sequences in Kamenka-2 (yak023)

After mapping to the hybrid genome and filtering, we found that 4,176 aDNA reads were

specifically mapped to Y. pestis genome in Kamenka-2. After removing 26% of the clonal

sequences, 3,070 of aDNA reads were used for the further analysis. We observed that 1,784 aDNA


an edit distance 1, 251 aDNA reads with 2 edit distance, and 67 aDNA reads with an edit distance

3 (fig. S26A). Also the fragment length distribution was skewed with a mean 51.36 nucleotide

length (fig. S26B). Nucleotide misincorporation patterns showed the authentic deamination

patterns at the end of the DNA sequences (fig. S26C). The overall coverage was 1.65% for the

whole genome. We checked the coverage for one chromosome and three plasmids of Y. pestis.

Table S22 shows the statistics for the individual sequences in Y. pestis genome. Results show that

we covered %3.16 of the Y. pestis CO92 chromosome (table S22). However we could not find

aDNA reads mapped to plasmid pCP1. Then we analysed the genome coverage (fig. S27). We

observed that more than 90% of the aDNA reads aligned to Y. pestis genome with less than 3 edit

distance. Also we observed a homogenous distribution in coverage.

Identification of Y. pestis aDNA sequences in Kamenka-1 (yak022)

After mapping to the hybrid genome and filtering process, we found that 2,480 aDNA reads were

specifically mapped to Y. pestis genome in Kamenka-1 sample. After removing 34% of the clonal

sequences, 1640 of aDNA reads were used for the further analysis. We observed that 1,403 aDNA


an edit distance of 1, 28 aDNA reads with edit distance of 2, and 6 aDNA reads with an edit

distance of 3 (fig. S28A). Also the fragment length distribution was right-skewed with a mean

46.4207 nucleotide length (fig. S28B). Nucleotide misincorporation patterns did not show the

authentic deamination patterns at the end of the DNA sequences (fig. S28C). The overall coverage

was 0.79% for the whole genome. We checked the coverage for one chromosome and three

plasmids of Y. pestis. Table S23 shows the statistics for the individual sequences in Y. pestis

genome. Results show that we covered %1.56 of the Y. pestis CO92 chromosome (table S23). In

Kamenka-1 sample, we could not find aDNA reads mapped to plasmid pCP1. Then we analysed

genome coverage (fig. S29). We observed that more than 90% of the aDNA reads aligned to Y.

pestis genome with less than 3 edit distance. Therefore, we could not validate the presence of Y.

pestis in this individual.

Overall, in our analysis, deamination rate in Y. pestis reads is relatively higher than the rate in

human reads (table S24) for all there samples.

Functional SNPs

Accelerator phenotype

N-acetylotransferase 2 gene (NAT2) is involved in the metabolism of a wide variety of foreign

chemical substance (xeniobiotics) (11 ). The metabolism can be either fast, intermediate or slow

and the status has been linked to differential response to various drugs and carcinogens (11 ). The

variation in worldwide distribution of different NAT2 phenotypes suggests that the distribution of

the phenotypes correlates with the type of subsistence practice. It has been noted that hunter-

gatherers often have high frequencies of the fast phenotype (>77%), while pastoralists and

agriculturalists have reduced levels of the phenotype (51-54.9%) (11 ) . The favorable selection

of the slow phenotype in modern populations, which is higher in west Eurasians and Africans,

compared to hunter-gatherers, Native Americans and east Asians was hypothesized to be related

to dietary changes accompanying the transition to agriculture (11 , 11 ). Indeed, in modern Asian

populations the distribution of acetylation phenotype has been linked to subsistence strategy with

slow phenotype more common among populations of sedentary agriculturalists than the nomadic

populations (11 )

In order to investigate the status of acetylator phenotype in ancient Siberian individuals we predict

the NAT2 phenotype from seven informative SNPs (rs1801279, rs1801280, rs1799930, rs1799931,

rs1041983, rs1799929, rs1208) using an online NAT2 prediction tool - NAT2PRED

(http://nat2pred. rit. albany.edu) (11 ). To confirm the status we further use a tag SNP (rs1495741)

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and/or a 2-SNP panel (rs1041983 and rs1801280) (11 ) which has been suggested to outperform

the single tag SNP prediction in non-Caucasian populations (11 ), but may result in

overrepresentation of the intermediate phenotype.

We have used the combination of all three methods to predict the acetylation status in 22

individuals sequenced to genomic coverage above 1X (Table S22). We compare the results

obtained from both damage repaired (Table S19) and non-damage repaired libraries (Table S19)

using the latter for finale predictions due to low impact of observed damages coupled with much

higher coverage (especially in irk034) and what follows, increased probability of identification of

heterozygotes. We only accept consensus predictions whenever all three prediction tools yielded

results and when at least two of the predicted phenotypes matched. Using those criteria we were

able to make phenotype predictions in 15 out of 22 tested individuals. We find that a single

Mesolithic individual was a carrier of a rapid phenotype, and so were five Neolithic individuals.

Only one Neolithic individual was a carrier of an intermediated phenotype while Bronze Age

individuals were either intermediate (N=5) or slow acetylators (N=3) (Table S19). Our data

suggests that intermediate phenotypes were uncommon in Siberia during the Mesolithic and

Neolithic with significant frequency increase during the Bronze Age. Thus, our results are in line

with hypothesis suggesting selective pressures associated with transition to agriculture and major

change of lifestyle may have shaped present-day distribution of the NAT2 phenotype in Asia.

Diet-related SNPs

The ability to digest sugars found in milk into the adulthood, so called lactase persistence, is often

regarded as an important cultural adaptation in humans associated with dairy animal

domestication. We have tested 22 individuals sequenced to average genome coverage exceeding

1X for the two SNPs most commonly associated with the trait: LCTa (rs4988235 - "C/T(-13910)",

(1 ) and LCTb (rs182549 - "G/A(-22018)"; (12 ) as well as other variants associated with lactase

persistence which could be more common in individuals of non-European descent: rs41380347 -

"C/T(-13915)" (East Asia), rs41525747 - "C/G(-13907)" (East/North Africa and Middle East) and

rs145946881 - "G/C-14010" (East Africa) (12 ). However, we find no evidence of lactase

persistence in the 22 tested ancient Siberians.

7

8

9 0

1

1

Another variant, potentially associated with the spread of agriculture is the derived status of

ADH1B*47His which among other associations has been linked to alcohol metabolism in East

Asians and the so-called ‘Asian blush’. It has been suggested that prevalence of derived

ADH1B*47His could be explained by the increased alcohol consumption in connection to

Neolithic rice domestication (11 ). None of the tested individuals was a carrier of the derived (A)

allele at position rs1229984. Additionally, the lack of derived alleles (A) at the ALDH2 rs671

suggests absence of Asian flush and reduced hangovers in all 22 individuals. Thus, present-day

distribution of ADH1B*47His and characteristic distribution of alcohol metabolism associated

variants among Asian populations was shaped in more recent times.

Other phenotypic traits

We have tested all individuals for a number of SNPs associated with various phenotypic traits

such as AGT gene, associated with increased risk of hypertension (12 ); KITLG gene, associated

with UV protective tanning in lighter skinned individuals (12 ); CYP3A4 and CYP3A5 associated

with certain cancers and drug metabolism (12 , 12 ); EDAR gene, associated with incisor and hair

shape as well as Asian ancestry (12 ), ABCC1 gene associated with various phenotypic traits as

well as Asian ancestry (12 ), and finally, C282Y and H63D variant in HFE gene associated with

hereditary haemochromatosis.

We only find variation in AGT, KITLG, EDAR, ABCC1 and CYP3A5 genes. While the different

variants and incidence of heterozygotes in AGT and KITLIG is spread out among various groups

and time periods and likely represents population variation, it seems that the increase in

hetergozygosity in ABCC1 and EDAR genes is mostly restricted to Neolithic and Bronze Age

individuals from Cis-Baikal group. On EDAR we observed increased occurrence of (A) on

otherwise widespread (G) variant associated with straight hair and shovel shaped incisors (note

that the phenotypic representation of heterozygotes would be the same), while four individuals

were heterozygous on ABCC1 gene, otherwise all tested individuals were homozygotes for variant

T associated with Asian ancestry. Thus, it seems that on some phenotype encoding SNPs we detect

signal of western admixture in Cis-Baikal during the Neolithic and Bronze Age.

Blood type

4

3

4 5

6

7

2

AB0 and Rh blood group system are a set of genetic markers which has been used in the study of

human genetic variation for decades and presents distinct geographic distribution (11 , 12 ). In

order to investigate blood group variation in our dataset we followed a strategy for blood group

prediction adopted in (1 ) and checked 22 individuals at five SNPs within the ABO gene region:

rs8176719 (G/-), rs7853989 (C;C/G;G), rs8176746 (C;C/A;A), rs8176747 (G;G/C;C) and

rs590787 (C;C/T;T) (13 )

It was possible to make broad blood group inferences in 19 of the tested individuals of which four

were phenotypically carriers of blood group ARh+, while remaining 15 individuals were probable

carriers of 0Rh+. Both phenotypes are common in present-day Asia, especially 0Rh+, however

seeing that we only identify ARh+ in Mesolithic and Neolithic individuals in our dataset and not

among more numerous Bronze Age samples could potentially suggest that ARh+ was more

widespread in earlier periods and declined in frequency sometime during or after the Neolithic.

8

0

29

0

Fig. S1

Radiocarbon dates of the studied samples. Samples excluded from the comparison are yak025

(Khaiyrgas-1), irk032, yak030, and bla001. yak024 (Kamenka-3) could not be dated due too poor

quality of the sample but it was found in the same burial with yak022 (Kamenka-1) and yak023

(Kamenka-2). Full data was presented in Table S1.

Fig. S2

Outgroup f3-statistics for Khaiyrgas-1. Plot showing the f3-statistics in the form of f3(Khaiyrgas-

1, Test_Population, Yoruba) plotted with 2 standard errors (se). Test population is one of the 194

present-day world populations from Human Origins dataset (see table S3).

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●

●●●●

●●

●●

●●●●

●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

WamboBantu_SA_OvamboMandenkaDamaraBantu_SA_S_SothoBantu_SA_HereroBantu_SA_ZuluHimbaTswanaBantu_SA_TswanaBantu_SA_PediBiakaPygmyBantuKenyaLuoKgalagadiMbutiPygmyKhweTaa_EastGanaTshwaXuunDinkaShuaHoanTaa_WestJu_hoan_SouthJu_hoan_NorthTaa_NorthGuiHaiomNaroAA_DenverKikuyuKhomaniHadzaNamaSandaweDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenYemenite_JewPalestinianSaudiSyrianJordanianLibyan_JewLebaneseCanary_IslandersTunisian_JewMoroccan_JewMalteseDruzeIraqi_JewItalian_SouthCypriotTurkish_JewIranian_JewMakraniArmenianAshkenazi_JewSicilianSardinianIranianGeorgian_JewBalochiSpanishTuscanGeorgianBrahuiBergamoGreekTurkishAbkhasianAlbanianBasque_SpanishBasque_FrenchBulgarianCochin_JewChechenFrenchKumykSindhiAustralianEnglishAdygeiFrench_SouthLezginPapuanHungarianCzechOrcadianNorth_OssetianVishwabrahminCroatianBelarusianGujaratiPathanBalkarTiwariKalashIcelandicPunjabiNorwegianLodhiMalaTajik_PomiriOngeScottishEstonianLithuanianBurushoBengaliRussianMordovianFinnishBougainvilleNogaiKhariaTurkmenChuvashUzbekHazaraUygurAleutKusundaThaiCambodianKyrgyzMansiTubalarTlingitKinhLahuDaiChiloteAtayalNaxiEvenKalmykSelkupTuAmiAltaianHanDolganTuvinianHan_NChinaMiaoTujiaYiSheJapaneseXiboMongolaOjibwaCreeAlgonquinHezhenKoreanDaurYukagirYakutIngaOroqenUlchiNganasanQuechua_CoriellChipewyanMayanZapotecKoryakMixtecPiapocoWayuuAymaraEskimoChukchiItelmenPimaKaqchikelQuechua_RuizLinaresSuruiCabecarMixeTicunaKaritianaGuaraniChane

0.004825

0.007333

0.008864

0.010758

0.012843

0.015742

0.018396

0.019987

0.022831

0.024723

0.027358

0.032261

0.035161

0.037986

0.051903

0.061310

0.072540

0.096211

0.098251

0.102076

0.107323

0.118417

0.120093

0.121785

0.124246

0.125982

0.128159

0.129810

0.131763

0.133277

0.134806

0.136384

0.137905

0.139613

0.141374

0.144183

0.146036

0.148790

0.150950

0.152926

0.155165

0.157400

0.159447

0.161010

0.163316

0.165280

0.167470

0.169609

0.171272

0.173071

0.175706

Fig. S3

ADMIXTURE analysis for K=2 to K=16. Final results for each K which was obtained by running

CLUMPP on 30 independent runs per K was plotted in R. Color codes which were used for plotting

are presented in table S4. R library "RColorBrewer” was used to create that color vector (table

S4).

Moroccan_JewSaharawiGambianMandenka

MendeAlgerianMozabiteTunisian

Tunisian_JewLibyan_Jew

EgyptianDinka

Ethiopian_JewOromo

BantuKenyaKikuyuLuhyaLuo

MasaiSomaliDatogHadza

SandaweEsan

YorubaBiakaPygmyMbutiPygmy

KhomaniBantu_SA_PediBantu_SA_Zulu

Bantu_SA_OvamboGanaGui

HoanJu_hoan_South

KgalagadiKhweNaroShua

Taa_EastTaa_NorthTaa_West

TshwaTswana

Bantu_SA_HereroBantu_SA_TswanaBantu_SA_S_Sotho

DamaraHaiomHimba

Ju_hoan_NorthNama

WamboXuunChaneGuaraniAymaraBolivian

Quechua_RuizLinaresKaritiana

SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima

ZapotecAA_DenverAlgonquinChipewyan

CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut

AltaianChukchiDolganEskimoEven

ItelmenKalmykKoryakMansi

NganasanSelkupTlingitTubalarTuvinian

UlchiYakut

YukagirMongola

CambodianDai

DaurHan

Han_NChinaHezhenLahuMiaoNaxi

OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew

GujaratiKhariaLodhiMalaOngeTiwari

VishwabrahminKusundaBalochiBrahui

BurushoHazaraKalashMakraniPathanPunjabiSindhi

AustralianBougainville

PapuanBalkar

ChechenChuvashKumykLezgin

MordovianNogai

North_OssetianRussianAdygeiIranian

Iranian_JewIraqi_Jew

SyrianDruze

PalestinianSaudiYemen

Yemenite_JewBedouin

JordanianLebaneseAbkhasianGeorgian

Georgian_JewArmenianUkrainianBelarusianLithuanian

Ashkenazi_JewTurkish

Turkish_JewGreekCypriot

Basque_FrenchBasque_Spanish

FrenchFrench_SouthItalian_South

SardinianSicilianTuscanMalteseBergamo

Canary_IslandersSpanishAlbanianBulgarianCroatian

HungarianCzech

EstonianFinnish

NorwegianIcelandicEnglish

OrcadianScottish

Dzhylinda−1_(irk00x)cta016brn008brn001brn003brn012brn002irk078bla001

Popovskij−1_(irk007)Cyclodrome−1_(irk051)

Shamanka_DA245_5200_ENShamanka_DA246_5200_ENShamanka_DA247_5200_ENShamanka_DA248_5200_ENShamanka_DA249_5200_ENShamanka_DA250_5200_ENShamanka_DA251_5200_ENShamanka_DA252_5200_ENShamanka_DA253_5200_ENLokomotiv_DA340_4700_ENLokomotiv_DA341_4700_ENLokomotiv_DA357_4700_ENLokomotiv_DA359_4700_EN

irk030irk040irk034irk075irk017irk071irk033irk036

mak026irk068irk025irk061irk022irk057

Anosovo−1_(irk050)irk076irk008

UstIda_LN_DA342UstIda_LN_DA355UstIda_LN_DA344UstIda_LN_DA345

Kurma_EBA_DA354Kurma_EBA_DA358Kurma_EBA_DA360

Shamanka_EBA_DA334Shamanka_EBA_DA335Shamanka_EBA_DA336Shamanka_EBA_DA337Shamanka_EBA_DA338Shamanka_EBA_DA339Shamanka_EBA_DA362

irk032Khaiyrgas−1_(yak025)

Matta−1_(N2a)Onnyos−1_(N5a)

N4a1N4b2

Kamenka−1_(yak022)Kamenka−3_(yak024)Kamenka−2_(yak023)

yak021yak030kra001

Yana_UP_1Yana_UP_2Yana_youngKolyma_M

Devilscave_N_NEO236Devilscave_N_NEO239Devilscave_N_NEO240

Devilsgate1Devilsgate2

UstBelaya_N_NEO229UstBelaya_EBA_NEO230UstBelaya_EBA_NEO231UstBelaya_EBA_NEO232UstBelaya_EBA_NEO298

UstBelaya_MEDMagadan_BA_M0831Magadan_BA_M9984Uelen_IA_NEO233Uelen_IA_NEO234Ekven_IA_NEO241Ekven_IA_NEO242Ekven_IA_NEO243Ekven_IA_NEO246Ekven_IA_NEO247Ekven_IA_NEO248Ekven_IA_NEO249Ekven_IA_NEO250Ekven_IA_NEO251Ekven_IA_NEO253

Saami_IAAnzick1TianyuanSaqqaq

MA1SIII_Sunghir_SIII

K14Ust_Ishim

AfontovaGora3Botai_BOT14Botai_BOT15

Botai_BOT2016CentralSteppe_EMBA_1CentralSteppe_EMBA_2

Okunevo_EMBA_RISE664Okunevo_EMBA_RISE674

SidelkinoEHG_MLTurkmenistan_IA_DA382

Iran_CA_I1661Iran_CA_I1665Iran_N_I1290Iran_N_I1945

Levant_N_I0867Levant_N_I1699

Namazga_CA_DA380Namazga_CA_DA381Namazga_CA_DA383

Natufian_I0861Natufian_I1072

Vietnam_N_I0626_allVietnam_N_I0627_allVietnam_N_I10973Vietnam_N_I1135

Vietnam_N_I1137_allVietnam_N_I1859_allVietnam_N_I2731_all

Vietnam_N_I2947Vietnam_BA_I2497_allVietnam_BA_I2948_all

Myanmar_LN_BA_I4011_allMyanmar_LN_BA_I4012Thailand_BA_I4458_all

Thailand_BA_I8974Thailand_BA_I8977

Thailand_LN_BA_I8978Thailand_IA_I8970

Cambodia_IA_I1680Russia_Afanasievo_RISE507Russia_Afanasievo_RISE509Russia_Afanasievo_RISE510Russia_Afanasievo_RISE511Russia_Andronovo_RISE500Russia_Andronovo_RISE503Russia_Andronovo_RISE505Russia_Andronovo_RISE512Russia_Karasuk_RISE493Russia_Karasuk_RISE494Russia_Karasuk_RISE495Russia_Karasuk_RISE496Russia_Karasuk_RISE497Russia_Karasuk_RISE499Russia_Karasuk_RISE502

Russia_Mezhovskaya_RISE523Russia_Sintashta_RISE392Russia_Sintashta_RISE394Russia_Sintashta_RISE395Yamnaya_Samara_I0231Yamnaya_Samara_I0370Yamnaya_Samara_I0441Yamnaya_Samara_I0444Yamnaya_Samara_I0357Yamnaya_Samara_I0429Yamnaya_Samara_I0439Yamnaya_Samara_I0443Yamnaya_Samara_I0438Yamnaya_Ukraine_I2105Yamnaya_Ukraine_I3141

Yamnaya_DamgaardLatvia_HG_I4432Latvia_HG_I4434Latvia_HG_I4438Latvia_HG_I4439Latvia_HG_I4440Latvia_HG_I4441Latvia_HG_I4550Latvia_HG_I4551Latvia_HG_I4552Latvia_HG_I4553Latvia_HG_I4595Latvia_HG_I4596Latvia_HG_I4626Latvia_HG_I4628Latvia_HG_I4630Latvia_HG_I4632Latvia_MN_I4435Latvia_MN_I4436Latvia_MN_I4437Latvia_MN_I4554Latvia_MN_I4627Latvia_MN_I4629

Ukraine_Mesolithic_I1733Ukraine_Mesolithic_I1737Ukraine_Mesolithic_I1763Ukraine_Mesolithic_I1819Ukraine_Mesolithic_I5876Ukraine_Eneolithic_I6561Ukraine_Eneolithic_I4110Ukraine_Eneolithic_I5882Ukraine_Eneolithic_I5884Ukraine_Neolithic_I5885Ukraine_Neolithic_I3717Ukraine_Neolithic_I3718Ukraine_Neolithic_I4111Ukraine_Neolithic_I4112Ukraine_Neolithic_I4114Ukraine_Neolithic_I5875Ukraine_Neolithic_I5881Ukraine_Neolithic_I5883Ukraine_Neolithic_I5886Ukraine_Neolithic_I5889Ukraine_Neolithic_I5890Ukraine_Neolithic_I5891Ukraine_Neolithic_I5892Ukraine_Neolithic_I5893Ukraine_Neolithic_I1736Ukraine_Neolithic_I3712Ukraine_Neolithic_I3713Ukraine_Neolithic_I3714Ukraine_Neolithic_I3715Ukraine_Neolithic_I3716Ukraine_Neolithic_I5868Ukraine_Neolithic_I5870Ukraine_Neolithic_I5872Ukraine_Neolithic_I5873Ukraine_Neolithic_I5957Ukraine_Neolithic_I6133Ukraine_Neolithic_I1732Ukraine_Neolithic_I1738

Ukraine_Neolithic_StPet12Latvia_MN_ZVEJ26Latvia_MN_ZVEJ31Latvia_LN_ZVEJ28

WHG_BichonWHG_Loschbour

WHG_Iboussieres25−1WHG_Iboussieres31−2

WHG_BerryAuBacWHG_Chaudardes1_m

WHG_FalkensteinWHG_I2158

WHG_RochedaneWHG_I1875

SHG_Motala12SHG_SF12EHG_I0124EHG_I0061

CHG_SatsurbliaCHG_KotiasEEF_I0046EEF_I0048EEF_I0057EEF_I0100EEF_I0659EEF_I0821EEF_I1550EEF_I0795EEF_I0797EEF_I0054EEF_I0022EEF_I0025EEF_I0026

EEF_StuttgartAnatolia_N_Bar8Anatolia_N_Bar31

Anatolia_N_Bon002Anatolia_N_Tep003

Narva_Donkalnis_Donkalnis6Narva_Donkalnis_Donkalnis7

CW_BattlleAxe_Lit_Gyvakarai1Late_BA_Latvia_Kivutkalns153Late_BA_Latvia_Kivutkalns19Late_BA_Latvia_Kivutkalns207Late_BA_Latvia_Kivutkalns209Late_BA_Latvia_Kivutkalns215Narva_Kretuonas_Kretuonas2Narva_Kretuonas_Kretuonas4

CW_Est_Kunila2_WGSCW_BattlleAxe_Lit_Plinkaigalis242

FBC_Saxtorp5158FBC_Saxtorp5164

Narva_Spiginas_Spiginas1Kunda_Spiginas_Spiginas4

CombedWare_Tamula1Trzciniec_BA_Turlojiske3

Narva_Veibri_Veibri4

0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1




EgyptianDinka

Ethiopian_JewOromo



SandaweEsan




HoanJu_hoan_South



TshwaTswana


DamaraHaiomHimba

Ju_hoan_NorthNama



SuruiChilote

Quechua_CoriellInga

PiapocoTicunaWayuu

CabecarKaqchikel

MayanMixe

MixtecPima


CreeOjibwa

Tajik_PomiriKyrgyz

TurkmenUzbekAleut




UlchiYakut

YukagirMongola

CambodianDai

DaurHan


OroqenSheTu

TujiaUygurXiboYi

JapaneseKorean

AmiAtayalThaiKinh

BengaliCochin_Jew





PapuanBalkar


MordovianNogai



SyrianDruze


Yemenite_JewBedouin









HungarianCzech

EstonianFinnish


OrcadianScottish












N4a1N4b2


yak021yak030kra001








K14Ust_Ishim




































0

0.2

0.4

0.6

0.8 1

Fig. S4

ADMIXTURE result for modern populations. (a) ADMIXTURE analysis result for K=14

ancestral clusters for present-day world populations from Human Origins data set. (b)

Approximate geographical positions corresponding to each of the present-day populations plotted

in the fig. S4a (table S4).

●

●

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● ●

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●

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●

●

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●

●

●

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●

● ●

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●

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●

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●

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Moroccan_Jew

Saharawi

GambianMandenka

Mende

Algerian

Mozabite TunisianTunisian_JewLibyan_Jew

Egyptian

DinkaEthiopian_JewOromo

BantuKenyaKikuyu

LuhyaLuoMasaiSomaliDatogHadza

Sandawe

EsanYoruba BiakaPygmy

MbutiPygmy


Bantu_SA_Ovambo

GanaGuiHoanJu_hoan_South

KgalagadiKhweNaroShuaTaa_East

Taa_North

Taa_WestTshwaTswanaBantu_SA_Herero

Bantu_SA_TswanaBantu_SA_S_Sotho

DamaraHaiomHimbaJu_hoan_North

Nama

WamboXuun

Chane

Guarani

AymaraBolivianQuechua_RuizLinares

KaritianaSurui

Chilote

Quechua_Coriell

Inga PiapocoTicuna

WayuuCabecar

KaqchikelMayanMixeMixtec

Pima

Zapotec

AA_Denver

Algonquin

ChipewyanCree

Ojibwa

Tajik_Pomiri

KrgyzTurkmen

Uzbek

Aleut Altaian

Chukchi Dolgan

Eskimo

Even

Itelmen

Kalmyk

KoryakMansi

Nganasan

SelkupTlingit

Tubalar Tuvinian Ulchi

YakutYukagir

Mongola

Cambodian

Dai

Daur

Han

Han_Nchina

Hezhen

LahuMiaoNaxi

Oroqen

She

Tu

Tujia

Uygur

Xibo

Yi

JapaneseKorean

AmiAtayal

ThaiKinh

Bengali

Cochin_Jew

Gujarati Kharia

Lodhi

MalaOnge

Tiwari

Vishwabrahmin

KusundaBalochiBrahui

BurushoHazaraKalash

Makrani

PathanPunjabi

Sindhi

Australian

BougainvillePapuan

BalkarChechen

Chuvash

KumykLezgin

Mordovian

NogaiNorth_Ossetian

Russian

Adygei

IranianIranian_JewIraqi_JewSyrianDruze

Palestinian

Saudi

YemenYemenite_Jew

Bedouin JordanianLebanese

AbkhasianGeorgianGeorgian_JewArmenian

UkrainianBelarusianLithuanian

Ashkenazi_jew

TurkishTurkish_Jew

GreekCypriot

Basque_FrenchBasque_SpanishFrench

French_SouthItalian_SouthSardinianSicilian

Tuscan

Maltese

Bergamo

Canary_Islanders

Spanish AlbanianBulgarian

CroatianHungarian

Czech

Estonian

FinnishNorwegian

Icelandic

English

OrcadianScottish

a

b

Fig. S5.

Admixture graph fitting using Treemix. (a) A maximum likelihood tree for a model which

allows for zero migration and (b) Pairwise residual matrix in which large values imply a poor fit

for the indicated population pairs.

Drift parameter

0.00 0.05 0.10 0.15 0.20 0.25

0.5

0

Anzick-1

Yoruba

Yana1

Khaiyrgas-1

MA1

10 s.e.

irk034

kra001

Tianyuan

Kolyma_M

AfontovaGora3

Migration weight

Yoruba

AfontovaGora3

Afon

tova

Gor

a3

MA1

MA1

Anzick1

Anzi

ck-1

Kolyma_M

Koly

ma_

M

irk034

irk03

4

kra001

kra0

01

Tianyuan

Tian

yuan

yak025

Khaiyrgas-1

Yana1

Yana

1

−3.1 SE

3.1 SE

Yoru

ba

a b

Fig. S6

F4-statistics for f4(Yoruba, Khaiyrgas-1; TestPopx, Kolyma_M). Results were plotted with two

se intervals for the tree like topology of f4(Yoruba, Khaiyrgas-1; TestPopx, Kolyma_M) in which

TestPopx corresponds to one of the ancient groups on the left y-axis (table S6).

−0.02 0.00 0.02 0.04 0.06

●●

●●●

●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●

●

Altai_NeanderthalNatufianLevant_NIran_N

Iran_CANamazga_CA

FBCUst_Ishim

Thailand_LN_BAEEF

Anatolia_NCHG

SIII_SunghirK14

RomanTurkmenistan_IA

Yamnaya_DamgaardTianyuan

Late_BA_LatviaWHG

Thailand_BAUkraine_Eneolithic

Late_IA_HLate_IA_LYana_UP

Russia_SintashtaYamnaya_Ukraine

Latvia_LNSHG

Yamnaya_SamaraRussia_Andronovo

Latvia_HGUkraine_Neolithic

Russia_AfanasievoMyanmar_LN_BA

Trzciniec_BAUkraine_Mesolithic

CombedWareRussia_Mezhovskaya

Latvia_MNVietnam_N

SidelkinoEHG_MLMA1

Saami_IA

Vietnam_BAEHG

Russia_KarasukCentralSteppe_EMBA

Okunevo_EMBADevilscave_NUstBelaya_N

BotaiUstBelaya_MED

Thailand_IAYana_MED

AfontovaGora3Magadan_BA

SaqqaqUstBelaya_EBA

Ekven_IAAnzick1

Uelen_IADevilsgate1Devilsgate2

Kolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_MKolyma_M

Cis-Baikal_6100_3700_BP

Cis-Baikal_7200_6200_BPCis-Baikal_7980_7855_BP

Yakutia_Lena_Kolyma_4780_2490_BPBlagoveshensk_1345_1270_BP

Trans-Baikal_8515_8380_BP



Yakutia_Lena_6850_6190_BP

Trans-Baikal_8515_8380_BP

Fig. S7

F4-statistics for f4(Yoruba, Kolyma_M; TestPopx, Khaiyrgas-1). Result were plotted with two se

intervals for the tree like topology of f4(Yoruba, Kolyma_M; TestPopx, Khaiyrgas-1) in which

TestPopx corresponds to one of the ancient groups on the left y-axis (table S6).

−0.02 0.00 0.02 0.04 0.06

●●

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●●●●●●●●●●●

●●●●●●

●●

Altai_NeanderthalNatufian

Thailand_LN_BALevant_NIran_N

Iran_CAFBC

Namazga_CAEEF

Anatolia_NUst_Ishim

SIII_SunghirCHG

Turkmenistan_IARomanK14

WHGLate_IA_H

Yamnaya_DamgaardLate_BA_Latvia

Russia_SintashtaLate_IA_L

Yamnaya_UkraineUkraine_Eneolithic

Trzciniec_BALatvia_LN

Yamnaya_SamaraLatvia_HG

SHGRussia_AndronovoRussia_Afanasievo

Yana_UPUkraine_MesolithicUkraine_Neolithic

TianyuanRussia_Mezhovskaya

SidelkinoEHG_MLLatvia_MN

MA1Saami_IA

EHGCombedWareVietnam_N

Russia_KarasukAfontovaGora3

Myanmar_LN_BAThailand_IA

BotaiDevilsgate1Vietnam_BA

Okunevo_EMBACentralSteppe_EMBA

UstBelaya_MEDThailand_BAYana_MED

Devilscave_N

UstBelaya_N

UstBelaya_EBA

Anzick1

Ekven_IASaqqaq

Devilsgate2Uelen_IA

Magadan_BA

Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1Khaiyrgas−1

Yakutia_Lena_6850_6190_BPTrans-Baikal_8515_8380_BP

Yakutia_Lena_Kolyma_4780_2490_BPCis-Baikal_6100_3700_BP


Cis-Baikal_7200_6200_BPTrans-Baikal_8515_8380_BP

Blagoveshensk_1345_1270_BPCis-Baikal_7980_7855_BP


Fig. S8

F4-statistics for f4(Yoruba, Anzick-1; Khaiyrgas-1, Kolyma_M) and f4(Yoruba, Saqqaq;

Khaiyrgas-1, Kolyma_M). Result plotted with two se intervals for the tree like topologies in the

form of f4(Yoruba, Anzick-1; Khaiyrgas-1, Kolyma_M) and f4(Yoruba, Saqqaq; Khaiyrgas-1,

Kolyma_M).

0.000 0.005 0.010

●

●

Khaiyrgas−1

Khaiyrgas−1

Kolyma_M

Kolyma_MAnzick

Saqqaq

Fig. S9

F4-statistics to formally test grouping of individuals on PCA. Tests were run for tree-like

topology of f4(Yoruba, indx1..ngroupx; indy1..ngroupy, indx1..ngroupx). Each individual shared more

alleles with individuals from the same group compared to the individuals from other groups

(Z>|3|).

Trans−Baikal−8345−3000 BP Cis−Baikal−7200−6200BP Cis−Baikal−6100−3700BP Yakutia−Lena−6850−6190BP Yakutia−Lena−Kolyma−4780−2490BP

Cis−B

aika

l−72

00−6

200B

P

Cis−B

aika

l−61

00−3

700B

P

Yaku

tia−L

ena−

6850−6

190B

P

Yaku

tia−L

ena−

Koly

ma−

4780−24

90BP

Tran

s−Ba

ikal−8

345−

3000

BP

Cis−B

aika

l−61

00−3

700B

P

Yaku

tia−L

ena−

6850−6

190B

P

Yaku

tia−L

ena−

Koly

ma−

4780−24

90BP

Tran

s−Ba

ikal−8

345−

3000

BP

Cis−B

aika

l−72

00−6

200B

P

Yaku

tia−L

ena−

6850−6

190B

P

Yaku

tia−L

ena−

Koly

ma−

4780−2

490B

P

Tran

s−Ba

ikal−8

345−

3000

BP

Cis−B

aika

l−72

00−6

200B

P

Cis−B

aika

l−61

00−3

700B

P

Yaku

tia−L

ena−

Koly

ma−

4780−24

90BP

Tran

s−Ba

ikal−8

345−

3000

BP

Cis−B

aika

l−72

00−6

200B

P

Cis−B

aika

l−61

00−3

700B

P

Yaku

tia−L

ena−

6850−6

190B

P

−0.08

−0.04

0.00

0.04

0.08

f4 |Z|>3

ns

Fig. S10

Outgroup f3-statistics for Yakutia_Lena_6850_6190_BP. Plot showing the f3-statistics in the

form of f3(Yakutia_Lena_6850_6190_BP, Test_Population, Yoruba) plotted with two se. Test

population is one of the 194 present-day world populations from Human Origins dataset (table

S7).

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●

●●

●●

●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●

●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●

Bantu_SA_S_SothoBantu_SA_OvamboWamboHimbaMandenkaDamaraTswanaBantu_SA_ZuluBantu_SA_HereroBantu_SA_TswanaKgalagadiBantuKenyaBantu_SA_PediBiakaPygmyLuoMbutiPygmyTaa_EastTshwaGanaHoanTaa_WestKhweDinkaXuunShuaTaa_NorthJu_hoan_NorthGuiJu_hoan_SouthHaiomNaroAA_DenverKikuyuKhomaniHadzaNamaSandaweDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenPalestinianSaudiYemenite_JewJordanianLibyan_JewSyrianTunisian_JewLebaneseCanary_IslandersMoroccan_JewDruzeMalteseItalian_SouthIraqi_JewTurkish_JewCypriotIranian_JewMakraniArmenianAshkenazi_JewSardinianSicilianIranianGeorgian_JewGeorgianSpanishBergamoGreekTuscanBasque_SpanishBrahuiAlbanianBasque_FrenchAbkhasianFrench_SouthFrenchTurkishBalochiAdygeiBulgarianEnglishLezginOrcadianCzechHungarianCroatianScottishKumykNorth_OssetianChechenBelarusianLithuanianBalkarCochin_JewIcelandicNorwegianKalashSindhiEstonianPathanTajik_PomiriTiwariGujaratiMordovianFinnishVishwabrahminBurushoRussianLodhiMalaPunjabiPapuanAustralianBengaliNogaiOngeTurkmenChuvashKhariaBougainvilleUzbekAleutHazaraUygurChiloteKusundaTlingitThaiOjibwaTubalarCambodianCreeMansiAlgonquinKyrgyzIngaLahuAmiChipewyanQuechua_CoriellDaiAltaianKinhEvenAtayalMayanKalmykSelkupNaxiYiQuechua_RuizLinaresTuZapotecMixtecHanMiaoTujiaSheTuvinianAymaraHan_NChinaKaqchikelPiapocoPimaXiboMongolaDolganKaritianaChaneWayuuGuaraniJapaneseKoreanMixeTicunaDaurCabecarSuruiYakutYukagirHezhenOroqenUlchiEskimoChukchiNganasanKoryakItelmen

0.003737

0.005856

0.007613

0.009604

0.012406

0.014886

0.016525

0.018255

0.019899

0.021545

0.026606

0.029731

0.032681

0.037163

0.051179

0.059811

0.071693

0.092748

0.096071

0.098892

0.104356

0.114673

0.116267

0.118518

0.120732

0.123319

0.124916

0.126906

0.128847

0.130698

0.132557

0.134353

0.135999

0.138878

0.140492

0.143398

0.145009

0.148527

0.151532

0.154035

0.158378

0.161737

0.163358

0.167466

0.169165

0.171278

0.172927

0.174588

0.176438

0.179487

0.182358

0.184760

0.186766

Fig. S11

Outgroup f3-statistics for Yakutia_Lena_Kolyma_4780_2490_BP. Plot showing the f3-

statistics in the form of f3(Yakutia_Lena_Kolyma_4780_2490_BP,Test_Population, Yoruba)

plotted with two se. Test population is one of the 194 present-day world populations from Human

Origins dataset (table S8).

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●

●●

●●

●●●

●●

●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●

Bantu_SA_OvamboWamboMandenkaHimbaBantu_SA_S_SothoDamaraBantu_SA_ZuluBantu_SA_HereroTswanaBantu_SA_PediBantu_SA_TswanaBantuKenyaKgalagadiBiakaPygmyLuoMbutiPygmyDinkaKhweTshwaShuaGanaTaa_EastHoanXuunTaa_WestHaiomAA_DenverJu_hoan_SouthJu_hoan_NorthTaa_NorthGuiNaroKikuyuHadzaKhomaniSandaweNamaDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenPalestinianYemenite_JewSyrianJordanianSaudiLibyan_JewTunisian_JewLebaneseMoroccan_JewCanary_IslandersDruzeIraqi_JewMalteseTurkish_JewCypriotItalian_SouthIranian_JewMakraniSardinianSicilianArmenianAshkenazi_JewGeorgian_JewIranianSpanishTuscanGreekGeorgianBergamoAlbanianAbkhasianBasque_FrenchBrahuiBasque_SpanishFrench_SouthBulgarianFrenchBalochiEnglishTurkishAdygeiOrcadianCzechCroatianIcelandicHungarianScottishLezginKumykBelarusianChechenLithuanianNorth_OssetianNorwegianEstonianBalkarCochin_JewSindhiKalashPathanTajik_PomiriTiwariGujaratiMordovianRussianVishwabrahminFinnishPunjabiBurushoLodhiMalaBengaliPapuanNogaiAustralianOngeTurkmenChuvashBougainvilleKhariaUzbekAleutChiloteUygurHazaraTlingitOjibwaCreeAlgonquinKusundaTubalarThaiCambodianIngaKyrgyzChipewyanMayanMansiQuechua_CoriellMixtecZapotecAltaianWayuuQuechua_RuizLinaresDaiPiapocoPimaKinhGuaraniAymaraLahuSuruiKaritianaAtayalKaqchikelAmiMixeTuChaneNaxiEvenTicunaSheKalmykHanYiMiaoCabecarTujiaHan_NChinaSelkupTuvinianJapaneseMongolaXiboKoreanDaurHezhenDolganYakutEskimoYukagirOroqenKoryakItelmenChukchiUlchiNganasan

0.006260

0.008564

0.010055

0.011931

0.017860

0.019836

0.021401

0.023028

0.025275

0.028528

0.031985

0.035266

0.046114

0.055419

0.066652

0.084474

0.087723

0.090371

0.094641

0.104681

0.106289

0.108143

0.110509

0.112038

0.113541

0.115066

0.116682

0.118255

0.119888

0.121676

0.123467

0.125693

0.127487

0.129170

0.131783

0.133614

0.136396

0.141223

0.143222

0.145280

0.147035

0.149337

0.151307

0.154161

0.155651

0.157346

0.158856

0.160919

0.162481

0.164235

0.165768

0.168886

0.178918

Fig. S12

Northeast Asia- and Native America-related genetic components. A subset of ADMIXTURE

analysis results for K=14 ancestral clusters for Yakutia individuals compared to Native American

populations (Anzick1, purple component) and Northeast Asia populations (Nganasan, yellow

component).

Nganasan

Anzick1

Khaiyrgas-1

Matta-1

Onnyos-1

N4a1

N4b2

Kamenka-1

KAmenka-3

Kamenka-2

yak021

yak030

kra00

Ancestry

0.00.20.40.60.81.0

Fig. S13

F4-statistics for f4(Yoruba, Devil’s Cave; YakutiaPopX, YakutiaPopY). Result plotted with two

standard se intervals for the tree like topologies in the form of f4(Yoruba, Devil’s Cave;

YakutiaPopX, YakutiaPopY) in which YakutiaPopX, YakutiaPopY corresponds to one of the

ancient Yakutia groups (table S9).

●

●

●

●

●

●

Khaiyrgas-1

Khaiyrgas-1


Yakutia_Lena_Kolyma_4780_2490_BP



Khaiyrgas-1

Khaiyrgas-1





Fig. S14

F4-statistics for f4(Yoruba, Anzick-1; YakutiaPopX, YakutiaPopY). Result plotted with two se

intervals for the tree like topologies in the form of f4(Yoruba, Anzick-1; YakutiaPopX,

YakutiaPopY) which YakutiaPopX, YakutiaPopY corresponds to one of the ancient Yakutia

groups. (table S9).

●

●

●

●

●

●


Khaiyrgas-1

Khaiyrgas-1







Khaiyrgas-1

Khaiyrgas-1


f4(Yoruba,Anzick1,Yakutia_X,Yakutia_X)

Fig. S15

F4-statistics for f4(Yoruba, Yakutia_Lena_6850_6190_B; PopX, Saqqaq). Result plotted with

two se intervals for the tree like topology in the form of f4(Yoruba, Yakutia_Lena_6850_6190_BP;

PopX, Saqqaq) where PopX corresponds to one of the ancient groups (table S10).

−0.04 −0.02 0.00 0.02 0.04 0.06

●●

●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●

●●

●●●●●●

●●●●●●●●●●●●●●●●●●

Altai_NeanderthalNatufianLevant_NIran_CAIran_N

Thailand_IAFBC

CombedWareNamazga_CA

Turkmenistan_IASIII_Sunghir

EEFUst_IshimAnatolia_N

Late_BA_LatviaCHGK14

Trzciniec_BARoman

Yamnaya_UkraineUkraine_Eneolithic

Late_IA_LUkraine_Neolithic

Yamnaya_DamgaardYamnaya_Samara

Latvia_LNWHG

Late_IA_HLatvia_HG

Ukraine_MesolithicRussia_Sintashta

SHGYana_UP

Russia_AfanasievoTianyuan

AfontovaGora3SidelkinoEHG_MLRussia_Andronovo

MA1EHG

Russia_MezhovskayaLatvia_MN

Thailand_BAMyanmar_LN_BA

BotaiSaami_IA

Okunevo_EMBARussia_Karasuk

CentralSteppe_EMBACis−Baikal_673_557_BP

Thailand_LN_BAUstBelaya_MED

Khaiyrgas−1Vietnam_BA

Anzick1Vietnam_NYana_MED

Devilscave_NKolyma_M

Cis−Baikal_7980_7855_BPCis−Baikal_6100_3700_BP

Blagoveshensk_1345_1270_BPMagadan_BA

Uelen_IAUstBelaya_EBA

Trans−Baikal_8345_3000_BPCis−Baikal_7200_6200_BP

Ekven_IACis−Baikal_8980_8640_BP

Devilsgate1UstBelaya_N

Trans−Baikal_8515_8380_BPDevilsgate2


Saqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remappedSaqqaq_remapped

Fig. S16

F4-statistics for f4(Yoruba, Saqqaq; PopX, Yakutia_Lena_6850_6190_BP). Result plotted with

two se intervals for the tree like topology in the form of f4(Yoruba, Saqqaq; PopX,

Yakutia_Lena_6850_6190_BP) where PopX corresponds to one of the ancient groups (table S10).

−0.02 0.00 0.02 0.04 0.06

●●●

●●●

●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●

Altai_NeanderthalThailand_LN_BA

NatufianLevant_NIran_N

Namazga_CAIran_CA

Turkmenistan_IAUst_Ishim

FBCCombedWareAnatolia_N

K14EEF

Yamnaya_DamgaardLate_BA_Latvia

CHGSIII_Sunghir

RomanUkraine_Eneolithic

Late_IA_HWHG

Yamnaya_UkraineLate_IA_LLatvia_LN

SHGYamnaya_Samara

Latvia_HGRussia_Sintashta

Trzciniec_BAUkraine_MesolithicSidelkinoEHG_ML

Yana_UPMA1

Ukraine_NeolithicTianyuan

Russia_AndronovoRussia_Afanasievo

EHGRussia_Mezhovskaya

Latvia_MNBotai

Thailand_BAAfontovaGora3

Okunevo_EMBASaami_IA


Cis−Baikal_673_557_BPMyanmar_LN_BA

Vietnam_NVietnam_BAKhaiyrgas−1

UstBelaya_MEDAnzick1

Devilsgate2Yana_MED

UstBelaya_NDevilscave_N

Kolyma_MCis−Baikal_6100_3700_BPCis−Baikal_7980_7855_BP

Trans−Baikal_8345_3000_BPTrans−Baikal_8515_8380_BP

UstBelaya_EBAYakutia_Lena_Kolyma_4780_2490_BP


Thailand_IABlagoveshensk_1345_1270_BP

Magadan_BADevilsgate1Uelen_IAEkven_IA

Yakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BP

Fig. S17

Outgroup f3-statistics for Dzyhlinda-1. Plot showing the f3-statistics in the form of f3(Dzyhlinda-

1, Test_Population, Yoruba) plotted with two se. Test population is one of the 194 present-day

world populations from Human Origins dataset (table S12).

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●

●●●●

●●

●●

●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●

●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

Bantu_SA_OvamboHimbaWamboMandenkaDamaraBantu_SA_ZuluBantu_SA_TswanaTswanaBantu_SA_PediBantu_SA_S_SothoBantu_SA_HereroKgalagadiBantuKenyaBiakaPygmyLuoTaa_EastMbutiPygmyKhweDinkaGanaTshwaShuaHoanTaa_WestXuunJu_hoan_NorthGuiTaa_NorthJu_hoan_SouthHaiomNaroAA_DenverKikuyuKhomaniHadzaNamaSandaweDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenPalestinianYemenite_JewJordanianSyrianLibyan_JewSaudiTunisian_JewLebaneseMoroccan_JewCanary_IslandersDruzeIraqi_JewMalteseTurkish_JewIranian_JewSardinianAshkenazi_JewItalian_SouthCypriotArmenianMakraniSicilianGeorgian_JewIranianTuscanSpanishGreekGeorgianBergamoBasque_FrenchAbkhasianAlbanianBrahuiBasque_SpanishFrench_SouthBulgarianTurkishFrenchEnglishBalochiAdygeiCroatianLezginCzechOrcadianHungarianKumykBalkarNorwegianNorth_OssetianIcelandicCochin_JewBelarusianChechenLithuanianScottishEstonianSindhiKalashPathanGujaratiTajik_PomiriMordovianPapuanTiwariFinnishVishwabrahminPunjabiRussianMalaLodhiAustralianBurushoBengaliNogaiOngeBougainvilleTurkmenChuvashKhariaUzbekAleutHazaraUygurChiloteKusundaTlingitMansiTubalarCambodianThaiKyrgyzAlgonquinOjibwaAltaianCreeEvenLahuSelkupDaiAtayalAmiKinhTuNaxiSheKalmykYiMiaoHanTujiaChipewyanIngaTuvinianHan_NChinaMayanXiboMongolaQuechua_CoriellDolganJapaneseKoreanMixtecYukagirYakutDaurZapotecHezhenWayuuQuechua_RuizLinaresGuaraniPiapocoPimaAymaraTicunaChaneSuruiMixeKaqchikelOroqenKaritianaCabecarNganasanUlchiKoryakEskimoChukchiItelmen

0.005966

0.007683

0.009527

0.011938

0.017292

0.018855

0.021153

0.022960

0.026424

0.030058

0.031939

0.033991

0.037298

0.048758

0.058872

0.072445

0.091784

0.093833

0.096728

0.102380

0.112531

0.114558

0.116401

0.118945

0.121090

0.122974

0.124545

0.126091

0.127644

0.129189

0.130851

0.132436

0.134098

0.135873

0.138488

0.140486

0.145084

0.150969

0.156122

0.158658

0.160340

0.162404

0.164718

0.166710

0.168649

0.170203

0.172150

0.173770

0.176053

0.177617

0.179280

0.181896

0.183531

Fig. S18

F4-statistics for f4(Yoruba, Dzyhlinda-1; PopX, Yakutia_Lena_6850_6190_BP). Result plotted

with two se intervals for the tree like topology in the form of f4(Yoruba, Dzyhlinda-1; PopX,

Yakutia_Lena_6850_6190_BP) where PopX corresponds to one of the ancient groups (table S13).

−0.02 0.00 0.02 0.04 0.06

●●

●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●

●●●●●

●●●●●●●●●●●●●●●●●

Altai_NeanderthalNatufianLevant_NIran_CAIran_N

Thailand_LN_BAFBC

Namazga_CAEEF

Anatolia_NUst_Ishim

Yamnaya_DamgaardTrzciniec_BASIII_Sunghir

CHGTurkmenistan_IA

RomanWHG

Late_BA_LatviaK14

Ukraine_EneolithicYamnaya_Ukraine

Latvia_LNThailand_BALate_IA_H

Yamnaya_SamaraLate_IA_L

SHGLatvia_HGTianyuanYana_UP

Ukraine_MesolithicRussia_SintashtaUkraine_NeolithicRussia_AndronovoRussia_Afanasievo

CombedWareSidelkinoEHG_ML

Latvia_MNEHG

Russia_MezhovskayaMA1

Myanmar_LN_BAAfontovaGora3

BotaiSaami_IA


Cis−Baikal_673_557_BPVietnam_N

Okunevo_EMBAThailand_IAVietnam_BAKhaiyrgas−1

UstBelaya_MEDDevilsgate2Devilsgate1

Anzick1Yana_MED

Cis−Baikal_7980_7855_BPDevilscave_N

Kolyma_MCis−Baikal_6100_3700_BP

UstBelaya_EBAUstBelaya_N

Cis−Baikal_7200_6200_BPSaqqaq_remapped

Trans−Baikal_8345_3000_BPUelen_IA

Yakutia_Lena_Kolyma_4780_2490_BPBlagoveshensk_1345_1270_BP

Ekven_IACis−Baikal_8980_8640_BP

Magadan_BA

Yakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BPYakutia_Lena_6850_6190_BP

Fig. S19

F4-statistics for f4(Yoruba, Yakutia_Lena_6850_6190_BP; PopX, Dzyhlinda-1). Result plotted

with two se intervals for the tree like topology in the form of f4(Yoruba,

Yakutia_Lena_6850_6190_BP;PopX, Dyhlinda-1) where PopX corresponds to one of the ancient

groups (table S13).

−0.04 −0.02 0.00 0.02 0.04 0.06

●●

●●

●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●

Altai_NeanderthalNatufianLevant_NIran_CAIran_NFBC

Namazga_CAEEF

Ust_IshimAnatolia_N

Turkmenistan_IASIII_SunghirThailand_BA

RomanUkraine_Eneolithic

CHGK14

Yamnaya_UkraineTrzciniec_BA

WHGLate_BA_Latvia

Late_IA_LYamnaya_Damgaard

CombedWareYamnaya_Samara

Late_IA_HLatvia_HG

Ukraine_NeolithicRussia_Sintashta

Latvia_LNSHG

Thailand_IASidelkinoEHG_ML

Yana_UPUkraine_Mesolithic

TianyuanRussia_AfanasievoRussia_Andronovo

EHGMA1

Russia_MezhovskayaLatvia_MN

Myanmar_LN_BAAfontovaGora3Russia_Karasuk

BotaiCis−Baikal_673_557_BP

CentralSteppe_EMBASaami_IA

Vietnam_BAOkunevo_EMBA

Khaiyrgas−1Vietnam_N

Thailand_LN_BAAnzick1

UstBelaya_MEDKolyma_M

Devilscave_NDevilsgate1Yana_MED


UstBelaya_EBAMagadan_BA

Trans−Baikal_8345_3000_BPUelen_IA

Blagoveshensk_1345_1270_BPCis−Baikal_7200_6200_BPCis−Baikal_8980_8640_BP

Ekven_IAUstBelaya_N

Yakutia_Lena_Kolyma_4780_2490_BPSaqqaq_remapped

Devilsgate2

Trans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BPTrans−Baikal_8515_8380_BP

Fig. S20

Outgroup f3-statistics for Trans-Baikal_8345_3000_BP. Plot showing the f3-statistics in the

form of f3(Trans-Baikal_8345_3000_BP;Test_Population,Yoruba) plotted with two se. Test

population is one of the 194 present-day world populations from Human Origins dataset (table

S14).

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●

●●●

●●

●●●

●●

●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

Bantu_SA_OvamboWamboMandenkaBantu_SA_S_SothoHimbaDamaraBantu_SA_ZuluBantu_SA_HereroTswanaBantu_SA_PediBantu_SA_TswanaBantuKenyaKgalagadiLuoBiakaPygmyMbutiPygmyDinkaKhweTshwaShuaGanaTaa_EastHoanXuunTaa_WestAA_DenverHaiomTaa_NorthJu_hoan_NorthGuiJu_hoan_SouthNaroKikuyuHadzaKhomaniNamaSandaweDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenPalestinianYemenite_JewSyrianJordanianSaudiLibyan_JewTunisian_JewLebaneseCanary_IslandersMoroccan_JewDruzeIraqi_JewMalteseTurkish_JewCypriotItalian_SouthIranian_JewArmenianMakraniAshkenazi_JewSicilianGeorgian_JewSardinianIranianSpanishBergamoGeorgianTuscanGreekAbkhasianAlbanianBasque_FrenchBasque_SpanishBulgarianFrench_SouthFrenchBrahuiEnglishOrcadianBalochiScottishCzechCroatianHungarianTurkishLezginIcelandicBelarusianAdygeiKumykLithuanianChechenEstonianNorwegianBalkarNorth_OssetianCochin_JewSindhiKalashPathanTajik_PomiriRussianMordovianTiwariFinnishGujaratiBurushoVishwabrahminLodhiPunjabiMalaBengaliNogaiChuvashPapuanAustralianTurkmenOngeAleutKhariaBougainvilleUzbekChiloteTlingitUygurHazaraOjibwaAlgonquinCreeMansiTubalarIngaChipewyanKusundaMayanQuechua_CoriellKyrgyzThaiCambodianSelkupMixtecQuechua_RuizLinaresZapotecPiapocoAltaianWayuuAymaraKaqchikelPimaGuaraniEvenKaritianaSuruiCabecarMixeTicunaChaneDaiKinhAmiLahuKalmykAtayalTuvinianTuDolganNaxiYukagirSheMiaoHanYiTujiaHan_NChinaMongolaEskimoXiboJapaneseYakutChukchiKoreanKoryakDaurItelmenHezhenOroqenNganasanUlchi

0.005736

0.007301

0.008888

0.010536

0.012252

0.018583

0.021331

0.023326

0.025159

0.028687

0.031722

0.034527

0.045764

0.054623

0.065295

0.083040

0.085795

0.088398

0.092683

0.102177

0.103594

0.105178

0.107371

0.109069

0.110483

0.112007

0.113586

0.115079

0.116913

0.118581

0.120538

0.122143

0.123796

0.125965

0.127808

0.131747

0.133501

0.139002

0.140801

0.143483

0.146612

0.148247

0.149911

0.151536

0.152979

0.154436

0.156983

0.159021

0.160444

0.162285

0.163896

0.166711

0.168202

Fig. S21

Outgroup f3-statistics for bla001. Plot showing the f3-statistics in the form of

f3(bla001,Test_Population,Yoruba) plotted with two standard errors (se). Test population is one of

the 194 present-day world populations from Human Origins dataset (table S16).

●●●●●●●●●●●●●●●

●●●●●●●●●●●●●●●●●

●●●

●●

●●●

●●

●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

●●●●●

●●●●●●●●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

Bantu_SA_OvamboWamboMandenkaBantu_SA_S_SothoHimbaDamaraBantu_SA_ZuluBantu_SA_HereroTswanaBantu_SA_PediBantu_SA_TswanaBantuKenyaKgalagadiLuoBiakaPygmyMbutiPygmyDinkaKhweTshwaShuaGanaTaa_EastHoanXuunTaa_WestAA_DenverHaiomTaa_NorthJu_hoan_NorthGuiJu_hoan_SouthNaroKikuyuHadzaKhomaniNamaSandaweDatogSomaliOromoEthiopian_JewSaharawiMozabiteAlgerianTunisianYemenPalestinianYemenite_JewSyrianJordanianSaudiLibyan_JewTunisian_JewLebaneseCanary_IslandersMoroccan_JewDruzeIraqi_JewMalteseTurkish_JewCypriotItalian_SouthIranian_JewArmenianMakraniAshkenazi_JewSicilianGeorgian_JewSardinianIranianSpanishBergamoGeorgianTuscanGreekAbkhasianAlbanianBasque_FrenchBasque_SpanishBulgarianFrench_SouthFrenchBrahuiEnglishOrcadianBalochiScottishCzechCroatianHungarianTurkishLezginIcelandicBelarusianAdygeiKumykLithuanianChechenEstonianNorwegianBalkarNorth_OssetianCochin_JewSindhiKalashPathanTajik_PomiriRussianMordovianTiwariFinnishGujaratiBurushoVishwabrahminLodhiPunjabiMalaBengaliNogaiChuvashPapuanAustralianTurkmenOngeAleutKhariaBougainvilleUzbekChiloteTlingitUygurHazaraOjibwaAlgonquinCreeMansiTubalarIngaChipewyanKusundaMayanQuechua_CoriellKyrgyzThaiCambodianSelkupMixtecQuechua_RuizLinaresZapotecPiapocoAltaianWayuuAymaraKaqchikelPimaGuaraniEvenKaritianaSuruiCabecarMixeTicunaChaneDaiKinhAmiLahuKalmykAtayalTuvinianTuDolganNaxiYukagirSheMiaoHanYiTujiaHan_NChinaMongolaEskimoXiboJapaneseYakutChukchiKoreanKoryakDaurItelmenHezhenOroqenNganasanUlchi

0.005736

0.007301

0.008888

0.010536

0.012252

0.018583

0.021331

0.023326

0.025159

0.028687

0.031722

0.034527

0.045764

0.054623

0.065295

0.083040

0.085795

0.088398

0.092683

0.102177

0.103594

0.105178

0.107371

0.109069

0.110483

0.112007

0.113586

0.115079

0.116913

0.118581

0.120538

0.122143

0.123796

0.125965

0.127808

0.131747

0.133501

0.139002

0.140801

0.143483

0.146612

0.148247

0.149911

0.151536

0.152979

0.154436

0.156983

0.159021

0.160444

0.162285

0.163896

0.166711

0.168202

Fig. S22

Distribution of long Runs of Homozygosity.

cta016

irk022

irk025

irk030

irk034irk036

irk040

irk061

irk068irk075

kra001

yak022

yak024

100

150

200

4000 5000 6000 7000 8000Age(calBCE)

Tota

l Mb

for s

egm

ents

>=

1.6

Mb

Fig. S23

Overview of the analyzed individuals with Y. pestis. Radiocarbon dates are compiled from (37).

Rise509 and Rise511 contains the oldest Y. pestis genomes in Asia (found in Afanasievo Gora

cultural site). Dates are shown in BCE.

Fig. S24

Summary for Y. pestis analysis in Anosovo-1. (a) The edit distance (less than 10 are shown in

the plot), (b) length distribution observed from the reads that are aligned to Y. pestis CO92

reference genome in the Anosovo-1, (c) Nucleotide misincorporation patterns.

0

500

1000

1500

0.0 2.5 5.0 7.5 10.0Edit Distance

Cou

nta

0

30

60

90

120

50 100 150Length

Cou

nt

b

0.05

0.10

0.15

0.20

0 5 10 15 20 25Distance from 5' end

C>T

tran

sitio

n ra

te

c

0.05

0.10

0.15

0510152025Distance from 3' end

G>A transition rate

Fig. S25

The coverage distribution among the sequences in Y. pestis genome from the Anosovo-1.

Please note that this plot is to demonstrate the distribution of the coverage among the genomes.

Because of the limited space on the X axis, the coverage could be misinterpreted.

Fig. S26

Summary for Y. pestis analysis in Kamenka-2. (a) The edit distance (less than 10 are shown in


reference genome in the Kamenka-2, (c) Nucleotide misincorporation patterns.

0

500

1000

1500

0.0 2.5 5.0 7.5 10.0Edit Distance

Cou

nta

0

30

60

90

120

50 100 150Length

Cou

nt

b

0.05

0.10

0.15

0.20


C>T

tran

sitio

n ra

te

c

0.05

0.10

0.15


G>A transition rate

Fig. S27

The coverage distribution among the sequences in Y. pestis genome from the Kamenka-2.

Please note that this plot is to demonstrate the distribution of the coverage among the genomes.

Because of the limited space on the X axis, the coverage could be misinterpreted.

Fig. S28

Summary for Y. pestis analysis in Kamenka-1. (a) The edit distance (less than 10 are shown in


reference genome in the Kamenka-1, (c) Nucleotide misincorporation patterns.

0

500

1000

0.0 2.5 5.0 7.5 10.0Edit Distance

Cou

nta

0

20

40

60

80

100 200Length

Cou

nt

b

0.00

0.01

0.02

0.03

0.04


C>T

tran

sitio

n ra

te

c

0.00

0.01

0.02

0.03

0.04


G>A transition rate

Fig. S29

The coverage distribution among the sequences in Y. pestis sequences from Kamenka-1.

Please note that this plot is to demonstrate the distribution of the coverage among the references.

Because of the limited space on the X-axis, the coverage could be misinterpreted.

Fig. S30

Comparison of deamination rates and read length distribution between Y. pestis and human

sequences of Ansanovo-1. (a) Deamination patterns of Y.pestis reads, (b) Read length distribution

of Y. pestis reads, (c) Deamination patterns of human reads, (d) Read length distribution of human

reads.

0.05

0.10

0.15

0.20


C>T

tran

sitio

n ra

teAnalysis of Y. pestis reads

0.05

0.10

0.15


G>A transition rate

a

0

30

60

90

120

50 100 150Length

Cou

nt

b

0.04

0.08

0.12

0.16


C>T

tran

sitio

n ra

te

Analysis of human reads

0.04

0.08

0.12


G>A transition rate

c

0

100

200

100 200 300Length

Cou

nt (t

hous

and)

d

Fig. S31


sequences of Kamenka-2. (a) Deamination patterns of Y.pestis reads, (b) Read length distribution


reads.

0.05

0.10


C>T

tran

sitio

n ra


0.00

0.05

0.10


G>A transition rate

a

0

40

80

120

50 100 150 200Length

Cou

nt

b

0.025

0.050

0.075

0.100


C>T

tran

sitio

n ra

te


0.025

0.050

0.075

0.100


G>A transition rate

c

0

100

200

300

400

100 200 300Length

Cou

nt (t

hous

and)

d

Fig. S32


sequences of Kamenka-1. (a) Deamination patterns of Y.pestis reads, (b) Read length distribution


reads.

0.05

0.10


C>T

tran

sitio

n ra


0.00

0.05

0.10


G>A transition rate

a

0

40

80

120

50 100 150 200Length

Cou

nt

b

0.025

0.050

0.075

0.100


C>T

tran

sitio

n ra

te


0.025

0.050

0.075

0.100


G>A transition rate

c

0

100

200

300

400

100 200 300Length

Cou

nt (t

hous

and)

d

Table S20.

Alignment statistics of the aligned Y. pestis reads in different samples. BF: Before read

length and quality filtering, AF: After read length and quality filtering, BD: Before duplication

removal, AD: After duplication removal.

Table S21.

The coverage statistics for the sequences in Y. pestis genome in the Anosovo-1. Coverage

describes the percent covered regions at least one time (breadth of coverage more than 1X).

NCBI_ID Length Coverage Name

NC_003131.1 70305 3.41 plasmid pCD1

NC_003132.1 9612 0.52 plasmid pCP1

NC_003134.1 96210 0.97 plasmid pMT1

NC_003143.1 4653728 3.66 CO92 chromosome

Table S22.

The coverage statistics for the sequences in Y. pestis genome in Kamenka-2. Coverage

describes the percent covered regions at least one time (percent coverage at least 1X).

Sample NO_reads_BF NO_reads_AF Mean_length_BD Mean_coverage_BD Clonality NO_reads_AD Mean_length_AD Mean_coverage_AD

irk050 9523 9395 54.23 0.05 64.99 3289 54.17 0.02

yak022 2503 2480 46.57 0.01 33.87 1640 46.42 0.01

yak023 4227 4176 51.25 0.0 26.48 3070 51.37 0.02

NCBI_ID Length Coverage Name

NC_003131.1 70305 3.60 plasmid pCD1

NC_003134.1 96210 2.13 plasmid pMT1

NC_003143.1 4653728 3.16 CO92 chromosome

Table S23.

The coverage statistics for the sequences in Y. pestis genome in Kamenka-1. Coverage

describes the percent covered regions at least one time (breadth of coverage more than one x).

- Length Coverage Name

NC_003131.1 70305 1.58 plasmid pCD1

NC_003134.1 96210 1.02 plasmid pMT1

NC_003143.1 4653728 1.56 CO92 chromosome

Table S24.

Comparison of single stranded deamination rates of Y.pestis and human DNA reads. Single

stranded deamination rates were calculated using mapDamage software.

Sample Single strand deamination rate for Y. pestis reads

Single strand deamination rate for human reads

irk050 0.51 +- 0.05 0.38 +- 0.001

yak022 0.15 +- 0.06 0.038 +- 0

yak023 0.31 +- 0.05 0.25 +- 0.001

REFERENCES AND NOTES

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(University of California Press, ed. 1, 2003).

2. T. Goebel, M. R. Waters, D. H. O’Rourke, The late Pleistocene dispersal of modern humans in the

Americas. Science 319, 1497–1502 (2008).

3. S. J. Fiedel, Y. V. Kuzmin, Radiocarbon date frequency as an index of intensity of Paleolithic

occupation of Siberia: Did humans react predictably to climate oscillations? Radiocarbon. 49, 741–

756 (2007).

4. V. V. Pitulko, P. A. Nikolsky, E. Y. Girya, A. E. Basilyan, V. E. Tumskoy, S. A. Koulakov, S. N.

Astakhov, E. Y. Pavlova, M. A. Anisimov, The Yana RHS site: Humans in the Arctic before the last

glacial maximum. Science 303, 52–56 (2004).

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