Interdisciplinary analyses of Bronze Age communities from Western Hungary reveal complex population histories

Abstract

In this study we report 21 ancient shotgun genomes from present-day Western Hungary (3530 – 1620 cal BCE), from previously understudied Late Copper Age Baden, and Bronze Age Somogyvár-Vinkovci, Kisapostag, and Encrusted Pottery archaeological cultures. Our results indicate the presence of high steppe ancestry in Somogyvár-Vinkovci culture that was replaced by the Kisapostag group having an outstandingly high (up to ∼47%) Mesolithic hunter-gatherer ancestry, despite this component being thought to be highly diluted by the time of the Early Bronze Age. The Kisapostag population was also the genetic basis of the succeeding community of the Encrusted pottery culture. We also found an elevated hunter-gatherer component in a local Baden culture associated individual, but no connections were proven to the Bronze Age individuals. The hunter-gatherer ancestry in Kisapostag is likely derived from two main sources, one from a Funnelbeaker or Globular Amphora culture related population and one from a previously unrecognised source in Eastern Europe. We show that this ancestry not only appeared in various groups in Bronze Age Central Europe, but also made contributions to Baltic populations. The social structure of Kisapostag and Encrusted pottery cultures is patrilocal, similarly to most contemporaneous groups. Furthermore, we developed new methods and method standards for computational analyses of ancient DNA, implemented to our newly developed and freely available bioinformatic package. By analysing clinical traits, we found carriers of aneuploidy and inheritable genetic diseases. Finally, based on genetic and anthropological data, we present here the first female facial reconstruction from the Bronze Age Carpathian Basin.

Significance
The hunter-gatherer ancestry we recovered in this study promotes the rethinking of the survival dynamics of Mesolithic populations, especially in the region of East-Central Europe. Despite strong genetic ties of patrilocal populations recovered at Balatonkeresztúr site toward groups of completely different social structure, high flexibility in social organisation can be assumed during the Bronze Age of the region. The newly presented bioinformatic tools ease the routine analysis of clinical and phenotype traits and help a yet underresearched part of the field. Reconstruction of a mass grave and a burial along with a forensic facial reconstruction bring closer past populations to our understanding of the prehistory.

Full text

Interdisciplinary analyses of Bronze Age communities from Western Hungary reveal
complex population histories
Dániel Gerber1,2,3, Bea Szeifert1,2,3, Orsolya Székely1, Balázs Egyed2, Balázs Gyuris1,2,3, Julia I. Giblin4, Anikó
Horváth5, László Palcsu5, Kitti Köhler6, Gabriella Kulcsár6, Ágnes Kustár7, Vajk Szeverényi8, Szilvia Fábián9,
Balázs Gusztáv Mende1, Mária Bondár6, Eszter Ari2,10,11,*, Viktória Kiss6,*, Anna Szécsényi-Nagy1*
1) Institute of Archaeogenomics, Research Centre for the Humanities, Eötvös Loránd Research Network
(ELKH); Tóth Kálmán utca 4., 1097 Budapest, Hungary 2) Department of Genetics, ELTE Eötvös Loránd
University; Pázmány Péter sétány 1/C, 1117 Budapest, Hungary 3) Doctoral School of Biology, Institute of
Biology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/C. 1117 Budapest, Hungary 4) Department
of Sociology, Criminal Justice and Anthropology, Quinnipiac University; 275 Mount Carmel Avenue, Hamden,
CT 06518, USA 5) Institute for Nuclear Research, ICER Centre; Bem tér 18/C, 4026 Debrecen, Hungary 6)
Institute of Archaeology, Research Centre for the Humanities, Eötvös Loránd Research Network (ELKH);
Tóth Kálmán utca 4., 1097 Budapest, Hungary 7) freelancer anthropologist, 1028 Budapest, Hungary 8) Déri
Museum; Déri tér 1., 4026 Debrecen, Hungary 9) Hungarian National Museum; Múzeum krt. 14-16., 1088
Budapest, Hungary 10) HCEMM-BRC Metabolic Systems Biology Lab; Temesvári krt. 62., 6726 Szeged,
Hungary 11) Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre,
Eötvös Loránd Research Network (ELKH); Temesvári krt. 62, 6726 Szeged, Hungary
*These authors jointly supervised this work.
Correspondence to: Eszter Ari (arieszter@gmail.com), Viktória Kiss (kiss.viktoria@abtk.hu), Anna
Szécsényi-Nagy (szecsenyi-nagy.anna@abtk.hu)
Keywords: mass grave, facial reconstruction, Bronze Age, Central Europe, hunter-gatherers, PAPline
Abstract
In this study we report 20 ancient shotgun genomes from present-day Western Hungary (3530 – 1620 cal
BCE), mainly from previously understudied Baden, Somogyvár-Vinkovci, Kisapostag, and Encrusted Pottery
archaeological cultures. Besides analysing archaeological, anthropological and genetic data, 14C and
strontium isotope measurements complemented reconstructing the dynamics of the communities discovered
at the site Balatonkeresztúr. Our results indicate the appearance of an outstandingly high Mesolithic
hunter-gatherer ancestry in the largest proportion (up to ~46%) among Kisapostag associated individuals,
despite this component being thought to be highly diluted by the Early Bronze Age. We show that
hunter-gatherer ancestry was likely derived from a previously unrecognised source in Eastern Europe that
contributed mostly to prehistoric populations in Central Europe and the Baltic region. We revealed a
patrilocal residence system and local female exogamy for this Kisapostag population that was also the
genetic basis of the succeeding community of the Encrusted Pottery culture, represented by a mass grave
that likely resulted from an epidemic. We also created a bioinformatic pipeline dedicated for archaeogenetic
data processing. By developing and applying analytical methods for analysing genetic variants we found
carriers of aneuploidy and inheritable genetic diseases. Furthermore, based on genetic and anthropological
data, we present here the first female facial reconstruction from the Bronze Age Carpathian Basin.
Significance
Here we present a genomic time transect study from the Carpathian Basin (3530 – 1620 cal BCE), that
sheds light on local and interregional population processes. We not only discovered long-distance mobility to
provide detailed analysis of yet understudied Bronze Age communities, but we also recovered a previously
hidden remnant hunter-gatherer genetic ancestry and its contribution to various populations in Eastern and
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Central Europe. We integrated 14C and strontium isotope measurements to the interdisciplinary interpretation
of a site with 19 individuals analysed, where patrilocal social organisation and several health-related genetic
traits were detected. Furthermore, we developed new methods and method standards for computational
analyses of archaic DNA, implemented to our newly developed and freely available bioinformatic pipeline.
Introduction
A number of studies addressed population historical questions in Prehistoric Europe by recovering major
events connected to the pre-Neolithic hunter-gatherers (HG)1–3, their assimilation to early European farmers
during the Neolithic era2,4–6, and the appearance, expansion and admixture of steppe ancestry during the
Eneolithic / Late Copper Age to the dawn of Early Bronze Age4,7,8. While some of these studies are essential
for understanding the foundation of the European gene pool, studies are sparse in the literature that uncover
regional interactions or social stratification via kinship9–11. Additionally, except for a few well-known markers in
most archaic studies – e.g. basic pigmentation markers or lactose intolerance analysed large-scale in
Mathieson et al. 201512 – no deeper analyses have been made e.g. on clinical variants. Our study aimed to
make a transect analysis on a single site concerning understudied archaeological assemblies, as well as
introducing the PAPline (Performing Archaeogenetic Pipeline, Supplementary Information section 6), a new
bioinformatic pipeline for archaic DNA analysis. We analysed the archaeological finds from
Balatonkeresztúr-Réti-dűlő site in Western Hungary, where - among others - Bronze Age assemblies were
found during roadwork in 2003. Three Bronze Age archaeological horizons can be distinguished, from the
Somogyvár-Vinkovci culture (~2500-2200 BCE), Kisapostag culture (~2200–1900 BCE) and to the Encrusted
pottery culture (~1900–1450 BCE) that were named into Bk-I, II and III phases in this study, respectively
(Table 1, Supplementary Information section 1, and Fig. S.1.2.1). In order to provide additional proxy to
population ancestry of the region one further Late Copper Age individual from a multiple grave of the Baden
culture (3600-2800 BCE) excavated at site Balatonlelle-Rádpuszta, ~30 km away from Balatonkeresztúr was
added to our dataset.
Results
We shotgun sequenced genomes of 20 individuals with 0.008 to 0.17x coverage. We also sequenced reads
of a capture set consisting 3000 nuclear SNPs (single nucleotide polymorphisms), and whole mitochondrial
DNAs (mtDNAs) of all individuals. The shotgun and the capture sequenced samples ultimately resulted in an
average ~104k SNPs/individuals using the 1240k SNP panel for genotype calling12, see Materials and
Methods and Supplementary Tables S4 and S7. We utilised STR analysis of the Y chromosome to recover
paternal kinship patterns. Furthermore, we reconstructed the face of individual S13 (Bk-II), where all known
biological and archaeological details were considered, see Supplementary Information section 4. The
bioarchaeological analyses were completed with radiocarbon and strontium isotope analyses, the latter can
be used to trace individual mobility.
Archaeological and anthropological evaluation of samples
Bk-I contained the remains of a single male individual having a very long (ultradolichocran) skull type which
differentiates it from most individuals found at Bk-II and Bk-III that have a very short (brachycranic) skull
type13 (Table 1). In Bk-II and Bk-III male dominance (~78%) suggest distinctive funeral treatment for males
and females. Bk-II is represented by 3 juveniles (16-19 years olds) and 7 adults (30+ years olds) distributed
into two grave groups of A and B (Table 1, Supplementary Information Fig. S.1.2.1), and one child grave
(individual S10) far from the others. Most of the burials contained no remaining grave goods except for small
copper jewellery in S10 and S13. Radiocarbon dates place these inhumations to ca. 2200-1770 cal BCE,
however, with Bayesian analysis using the OxCal software the timespan of the Bk-II burials can be reduced
to ca. 2120-1900 cal BCE (95.4% CI), with two graves (individuals S10 and S11) possibly being slightly
earlier (Supplementary Information section 1.8). The absence of children from the site is a common
phenomenon that can be traced back to different preservation dynamics or burial practises to adults14, while
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

the reason for the absence of young adults (~20-30 year olds) is unknown. Bk-III is represented by a single
mass grave of 8 skeletal remains of all ages that turned out to be an unusual find in a period when the
cremation practises and single inhumations were common, from ca. 1870-1620 cal BCE (95.4% CI). For
details, see Supplementary Information section 1.
Uniparental genetics and kinship analyses
Both Bk-II and Bk-III show phylogeographic signals for their maternal and paternal lineages. Accordingly,
Bk-II is mostly defined by mtDNA connections to the region of present-day Poland and its surroundings,
whereas Bk-III has more diverse maternal composition, see Supplementary Information section 2.1. Male
lineages in both Bk-II and Bk-III are mostly defined by Y chromosome haplogroup I2a-L1229 (Table 1), for
which network analysis (Supplementary Information section 2.2) narrowed down regional affinities to the
North European plain and shows continuity between these two horizons. Uniparental diversity makeup points
to a patriarchal social structure similar to previously reported Bronze Age findings9,11,15. Results are highly
similar to previous observations on Encrusted Pottery culture at the Jagodnjak site (Croatia)10. The kinship
network of Bk-II follows the distribution of grave groups (Fig. 1) which were likely established along family
relationships and chronology. Individuals buried in the Bk-III mass grave only show a few blood relations, like
a half-brother and father-son and a dizygotic twin, the latter is the most archaic detection to date to our
knowledge. However, Bk-III as an extended family group can not be excluded. For further details, see
Supplementary Information section 2 and Supplementary Tables S1-S3.
Table 1 Summary of the investigated samples. MtDNA and ChrY denote mitochondrial haplogroup and Y
chromosome haplogroup. In column “Kinship” 1st and 2nd mean the degree relations. For the feature, grave
IDs and details on newly reported radiocarbon dates see the Supplementary Table S1.
Group
ID
Grave
group
14C (cal BCE)
2σ (95.4%
CI)
Age
Sex
MtDNA
ChrY
Kinship
Baden
BAD002
3530-3370
8-9
M
K1a4a1
I-M170
None
Bk-I:
Somogyvár -
Vinkovci culture
S9
2560-2290
35-40
M
K1a3a
R1a-V2670
None
Bk-II:
Kisapostag or
Early Encrusted
Pottery culture
S1
A
2120-1880
40+
M
V
I2a-L1229
2nd to S2 & S8
S2
A
2120-1880
30-35
M
U5a2b1a
I2a-L1229
2nd to S1 & S8
S4
B
17-19
M
H10a1
I2a-L1229
1st to S8
S5
A
16-18
M
T1a4
I2a-L1229
1st to S6 & S11
S6
A
2030-1770
17-18
M
T1a4
I2a-L1229
1st to S5 & S11
S7
A
2120-1880
35-50
F
V
2nd to S8
S8
B
30-40
M
T2b
I2a-L1229
1st to S4; 2nd to S1 & S2 & S7
S10
2140-1940
7-8
M
K1a4a1g
I2a-L1229
None
S11
B
2200-1980
34-43
M
T2b
I2a-L1229
1st to S5 & S6
S13
B
2120-1890
35-45
F
J2b1
None
Bk-III:
Transdanubian
Encrusted Pottery
culture
S14
Mass
Grave
B-938
7-8
F
H10a1
None
S15
21-23
M
U4b1b1
I2a-L1229
2nd to S17
S16
1890-1640
35-44
M
T2g2
I2a-L1229
None
S17
1870-1540
26-35
M
U5b1b1+@16192
I2a-L1229
1st to S19; 2nd to S15
S18
3-4
M
U4a2
R1b-Z2103
None
S19
9-10
M
T2b
I2a-L1229
1st to S17
S20
1.5-2
M
K1a+195
R1b-Z2103
1st to S21
S21
1.5-2
F
K1a+195
1st to S20
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Fig. 1 Kinship network at Balatonkeresztúr site based on the biological age of the individuals, and the
results of the uniparental and and the READ/MPMR analyses. Blue colour represents the Bk-II grave
group “A” that consists of descendant individuals, while the green coloured individuals – found in Bk-II
grave group “B”– are mostly the ancestors, which suggests a kinship or chronological based geographical
distribution of graves. In the mass grave Bk-III (orange, east to Bk-II graves, for full site map see
Supplementary Information Fig. S.1.2.1) only a partial kinship network can be observed. Specimens
buried in Bk-II S10 (purple) and S13 (green), and Bk-III S14, S16 and S18 (orange) do not have 1st and 2nd
degree relatives in the uncovered graves.
Genetic disorders and pigmentation
Investigating genetic disorders in archaic datasets is potentially valuable for history of health and medicine,
and also highlights the overall genetic health of past populations. Inherited genetic disorders, if accompanied
with severe phenotypic anomalies, could also explain unusual burial practises, as it was described in cases
of dwarfism16. For detailed results of this topic, see Supplementary Information section 3.
Aneuploidies
The abnormal number of chromosomes result in a few well known diseases which we tested thoroughly. We
found one individual, S10, the only child burial in Bk-II, with XYY gonosomal genotype, described as Jacob’s
syndrome. Although this syndrome remains in most cases silent as it is relatively frequent (~0.1%) in today’s
populations, it occasionally comes with a wide scale of symptoms17, which may be linked to its separate
burial, but due to poor bone preservation for S10 no further assessments could be made.
Mitochondrial DNA diseases
We examined the clinical significances of the polymorphisms that can be found in the mtDNA by using the
mitopathotool software on the AmtDB database18, and found that individual S1 (40+ years old) from Bk-II had
one of the defining mutations (T14484C) of Leber’s hereditary optic neuropathy (LHON) causing complete
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

vision loss in ~10% of females and in ~50% of males between 20-40 years of age, rarely accompanying with
other neuropathies19.
Pigmentation
Pigmentation patterns highly differ between horizons, as Bk-I mostly possess variants for light pigmentation,
blue eyes and blonde hair, while Bk-II is more similar to populations of Neolithic Europe (Fig. 2), although
some variants for lighter pigmentation exist within this group too. Members of Bk-III on the other hand show a
wide range from dark to light tones and even the presence of variants for red hair (Supplementary Table S5,
Supplementary Information section 3.2.1).
Fig. 2 Reconstruction of individual S13. Her mouth was partly open due to maxillary prognathia and her
burial position differs from the others by her unusual arm position. She likely had higher social status for
the rare copper beads she had around her head. Her genomic makeup and pigmentation pattern blends
well to other Bk-II individuals, and while she did not have any blood relatives at the site up to second
degree, according to strontium isotope data she lived in the region, suggesting her origin from a nearby
community of the same population. For more information, see Supplementary Information sections 1 and
4.
Nuclear variants with clinical significance
We also examined the nuclear genomes to find regions with clinical significance. Since a complete panel for
determining disease susceptibility only exists in commercial DNA kits, and detailed description for the 1240k
SNP set is not available, we created our own SNP calling panel (included in PAPline) focusing on various
conditions including amyotrophic lateral sclerosis, Alzheimer disease, autism, Crohn’s disease, diabetes,
lactose intolerance, tumor markers, mental disorders, Parkinson disease, schizophrenia and ulcerative
colitis. For this study we used 3,874 clinically significant SNPs, which were marked as “pathogenic” or “likely
pathogenic” in the ClinVar database20, by ignoring deletion, duplication and copy number variants, as well as
SNPs with questionable (“reported”, “conflicting reports”, etc.) contribution to diseases. From this set we
found ~2,200 SNPs which covered at least one individual, out of these 27 positions showed clinically
relevant substitutions. However, test runs on database data resulted in numerous positive hits for pathogenic
variants most likely related to DNA damage, which highlights the unreliability of low coverage SNP data for
variant identification (Supplementary Information section 3.2.2). To overcome this issue, we considered
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

positions with more than 0.99 genotype likelihood (GL) values calculated using ANGSD v0.93121
(Supplementary Table S6) or when skeletal features supported results. A variant for Lig4 syndrome
(rs10489442122, GL=0.999) in individual S15 was detected, and some of his skeletal features (e.g. congenital
hip dysplasia) show possible onset of symptoms (Supplementary Information section 3.2.2.1). In another
case the physical manifestation of hereditary spastic paraplegia is likely for S11 and S6, father and son but
the genotype likelihood is lower (0.67; see Supplementary Information section 3.2.2.3). Interestingly, a tumor
marker on the BRCA2 gene (rs80358920, GL=0.999) in individual S9 is nowadays only prevalent in Asian
populations22. For further discussions, see Supplementary Information section 3.2.
Whole genome composition and genetic ancestry
Balatonkeresztúr site samples
According to the principal component analysis (PCA) based on 590k nuclear SNPs (Fig. 3 a.) Bk-I is clearly
separated from Bk-II and Bk-III, where Bk-II has a strong shift towards HG samples23 overlapping with only a
fraction of known archaic samples23 and Bk-III. Admixture and qpAdm analyses for assessing genetic
components (Supplementary Tables S9, S12-16; Supplementary Information sections 5.2 and 5.5.2)
revealed ~17% HG, ~40% European farmer, and ~43% steppe ancestry for Bk-I, similar to average Bronze
Age Europeans. Bk-I is most likely derived from a single source that is genetically related to a Poland
Southeast Bell Beaker culture (BBC) associated population (p= 0.784) in line with archaeological
observations24. Bk-II comprises a unique makeup of ~42% HG, ~41% European farmer, and ~17% steppe
ancestries. qpAdm analysis revealed most plausible sources of Neolithic Sweden Funnel Beaker culture
(~32±8%), Poland Southeast BBC (~41±6%) and an extra HG (~29±3%) ancestry of yet unknown origin.
Despite the lower supported models Bk-I can not be excluded as an ancestry component for Bk-II, while the
affinity of Sweden Funnel Beaker culture associated population likely reflects a more closely related group,
such as population related to the Poland Globular Amphora culture, see Supplementary Information section
5.5.2.2 and Supplementary Tables S12 and S15. Bk-III shows a shift in ancestry composition (~29% HG,
~46% European farmer, ~25% steppe). qpAdm analyses revealed that the main ancestry component for
Bk-III is Bk-II (~53±5%), while “dilution” of Bk-II to Bk-III is mostly driven by population events that are yet to
be uncovered.
Genetic outliers from previous studies
Many samples were defined as genetic outliers in their genetic context by previous studies from Bronze Age
Europe. We selected such outlier individuals with high HG ancestry components to assess whether they are
related to Bk-II. Selection was based on previous observations and also by using Dixon’s Q-test25 at 90%
confidence interval on HG component’s upper deviation using results of the Admixture analysis. First, we ran
f4-statistics in the form of f4(W=test outlier, X=corresponding population, Y=Bk-II, Z=Yoruba)26. This test
resulted in positive values for some outliers (W) meaning that these are genetically closer to Bk-II (Y) than its
presumed population (X). However, Z-scores are low in many cases, and false positives may appear solely
by high HG component, not by true relationship (see Supplementary Table S10 and Supplementary
Information section 5.3). To check true relationship between Bk-II and groups/samples with high HG
ancestry, we performed an outgroup f3-statistics in the form of f3(X=Bk-II, Y=test HG-s, Z=Yoruba) for all
relevant archaic populations and outliers23 (Supplementary Table S11) that resulted a table of allele
frequency based distances between test pairs Xs and Ys. Euclidean clustering based on the results of
f3-statistics revealed that a number of samples and even three populations from the Baltic (Fig. 3 b,
Supplementary Information section 5.4) from AADR23 form a cluster with Bk-II and Bk-III, suggesting actual
genetic connection via a common HG ancestry source.
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Fig. 3 a) Principal Component Analysis based on 590k SNPs calculated by the smartpca software. Bk-II
clearly separated from any known archaic Central-Eastern European populations. b) Highlighted genetic
outliers from previous studies (Supplementary Information section 5) that show a similar hunter-gatherer
(HG) ancestry component to Bk-II among ancient datasets. The origin of the HG component likely lies
between the Carpathian mountains and the Dnieper River or the Black Sea, from where it expanded
further North and from where the Bk-II population most likely originated from. Outliers signalise a
westward migration route of this component detected in Bk-II.
Origin of high HG ancestry component in BK-II and the Kisapostag population
f4-statistics in the form of f4(W=Sweden HG, X=Serbia IronGates HG, Y=Bk-II, Z=Yoruba) revealed that
while Pitted Ware culture associated individuals have similarly high HG levels to Bk-II from Scandinavian
HG-s, in Bk-II this type of HG component is significantly negative meaning no or minimal shared ancestry
(Supplementary Information section 5.3). Results of outgroup in f3-statistics in the form of f3(X=Bk-II,
Y=HG-s, Z=Yoruba) showed that HGs fit the best to Bk-II are geographically widely distributed
(Supplementary Table S11), thus we conclude that the true source for this component is yet to be described.
We can take into consideration the outgroup f3-statistics results, chronology, timing of HG admixture
according to Freilich 202110 between ~3400-2400 BCE, qpAdm results and the geographical distribution of
groups and outliers of similar HG makeup. These suggest a dated migration pattern for this undescribed
population with dominant HG genetic ancestry from what is present-day Bulgaria to the Baltic through the
Eastern borders of the Carpathians (Fig. 3 b). Ancestors of Bk-II likely branched off from this migration route
and started to move towards West, by at least around ~2500 BCE, subsequently intermixing with various
groups. Interestingly, the phylogeography of mitochondrial haplogroup U4b1b1 (individual S15) perfectly fits
this scenario. Notably, strontium (87Sr/86Sr ratio) isotope results from molars (Fig. 4, Supplementary
Information section 1.9) indicate that every individual of this study was raised and lived at least close
proximity to Balatonkeresztúr site in their childhood and early adolescence, suggesting that Bk-II group does
not represent the first generation of the Kisapostag culture associated population in Transdanubia (Western
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Hungary). Correspondingly, the high number of supported models in qpAdm results could be the result of
subsequent local admixtures.
Fig. 4. Sr isotope data from the Balatonkeresztúr site. Samples were taken from dental enamel (first, second
and third molars) to evaluate whether individuals were born in the area, or grew up in a geologically distinct
region. All of the samples are consistent with previously published plant and water 87Sr/86Sr ratio (green
diamonds) data collected from the southern portion of Lake Balaton14. For further data see Supplementary
Information section 1.9.
A Late Copper Age outlier individual from Balatonlelle site
We included a Late Copper Age individual from Balatonlelle site to this study for its high HG genomic
ancestry component. Mitogenome of BAD002 (K1a4a1) shows affinity to Iberian BBC associated individuals
(Supplementary Information Fig. S.2.1.1), and his Y chromosomal haplogroup belongs to I-M170. On
genomic PCA this sample groups with Iberian and French Neolithic individuals, due to higher HG component
(~34%) than known Neolithic and Copper Age populations in the Carpathian Basin have, and due to the lack
of steppe related ancestry. qpAdm estimates pointed to a source of Neolithic communities from present-day
(Northwestern) France (87±8%)27 with a minor extra HG component (13±8%) with p=0.948 (Supplementary
Information section 5.5, Supplementary Tables S12 and S13). Pigmentation pattern of BAD002 shows
resemblance to average Neolithic Europeans. The foreign cultural traits of the boy’s jewellery is in line with
his outlier genetic composition in the study region28. Notably, further tests (outgroup f3-statistics, qpAdm)
excluded contribution nor any connection of BAD002 to Bk-II (Supplementary Tables S11, S12 and S13,
Supplementary Information section 5). Therefore we conclude that this individual testifies large-scale
migration in the Copper Age, providing research questions for future studies.
PAPline
We introduce our newly developed, freely available bioinformatic pipeline, named PAPline (Performing
Archaeogenetic Pipeline), written in linux bash, R, and python v3.8.10 programming languages. One can use
this software primarily to analyse next generation sequencing data of archaeogenomic samples,
supplemented by non-pipeline scripts. The main distinguishing feature of the PAPline compared to the
EAGER29 and the Paleomix30 pipelines is its user friendliness, as its installation process is less complicated
and it provides a graphical interface with almost complete automatisation with practical details. For detailed
description visit the github page or see Supplementary Information section 6.
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Discussion
The Carpathian Basin was inhabited by the Baden cultures’ population at the end of the Copper Age, and
their genetic composition was represented by an early farmer and a slightly increased HG genetic
component, compared to the previous Neolithic populations of the region6. Here we demonstrated that in the
early phase of this culture, a group of Western European origin appeared in Transdanubia, diversifying what
we knew about the region’s Late Copper Age substrate up to now.
The Carpathian Basin experienced the influx of steppe-related genetic ancestry at the dawn of the Bronze
Age5,8, and this transformation was already detectable at Balatonkeresztúr-Réti-dűlő site as well, where we
could examine multiple populations. The earliest Bronze Age horizon Bk-I (representative of the
Somogyvár-Vinkovci culture) shows similarities to Poland Southeast BBC associated population with high
steppe ancestry that was replaced by the Kisapostag culture associated Bk-II around the 23-22th century
BCE, while at least some sort of genetic ancestry of Bk-I in this population can not be excluded. According to
our results, the Bk-II population had outstandingly high HG genetic ancestry levels, compared to other
Bronze Age groups of the region, which can be traced back to today’s Ukraine, Belarus, Moldavia or
Romania, pointing to a long standing previously unsampled population with dominant HG ancestry.
Calculated admixture dates10 suggest the presence of a genetically pure or at least highly HG specific
population in Eastern Europe as late as the end of the Copper Age. Part of this group subsequently admixed
with populations of mainly steppe (likely Poland Southeast BBC) and early farmer (most likely a Globular
Amphora culture related) ancestry during their westward migration on a Northern route, leaving genetic
traces in Corded Ware culture, BBC, and other Bronze Age populations. The paternal lineage of BK-II was
likely linked to the farmer component, as I2a-M223 (upstream to I2a-L1229) was a frequent paternal lineage
among Globular Amphora culture and related populations. Looking for the possible source areas of the
Kisapostag culture, a number of archaeological theories need to be considered. The pottery decoration
technique originated either from Corded Ware in the Middle Dnieper region (Ukraine), epi-Corded Ware
groups (northern Carpathians), e.g. Chłopice-Veselé or Nitra groups (Slovakia), the latter two is also
supported by inhumation practises31–36. However, connections with the Litzenkeramik or
Guntramsdorf-Drassburg group (eastern Austria, Slovenia, western Croatia) were also raised37,38. Pottery
forms were connected to local development of communities with eastern (Makó–Kosihy–Čaka) or southern
(Somogyvár–Vinkovci) origins, too39. BBC influence was also mentioned based on connections of pottery
and craniometry data (so called Glockenbecher or brachycran skull type40–42). The results of this study fit best
with the Middle Dnieper area origin of BK-II, especially when we consider individual I4110 from Dereivka I
(Ukraine Eneolithic) as one of the earliest representatives of their genomic makeup.
Strontium isotope (87Sr/86Sr ratio) data, representing through nutrition the bioavailable Sr in the area where
people lived in a certain age interval, shows local values for both sexes in both Bk-II and Bk-III. These results
push back the timing of their arrival a few generations, meaning that local or southern impact of cultural traits
and maybe even genetic admixtures likely occurred during this short period as well, which also could explain
the culture’s archaeological heterogeneity.
The population of Bk-III was the direct descendant of Bk-II, forming not just cultural (Encrusted pottery) but
also genetic continuity for at least ~500 years, even if the radiocarbon sequences allow a few decades of
hiatus at the studied site. Continuous female-biased admixture with various groups occurred during this
period according to our and previous genetic10 and archaeological31,43 evidence, diluting the BK-II genetic
ancestry.
In both periods, the homogeneity of paternal lineages suggest a similar social organisation described in9,10 of
a patrilocal residence system. However, strontium isotope data shows local values for both sexes, which
along with similar genomic makeup of females and males suggest exogamy most probably between villages
of the same population. Two pairs of half-sibling graves in the two periods may indicate polygamy, although
remarriage for high female mortality is more plausible. Notably, almost none of the uniparental markers are
identical even at the haplogroup level with individuals from the Croatian Encrusted Pottery culture Jagodnjak
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

site, despite high similarities in cultural traits, social structure and genomic composition of the communities.
This points to clan-like or patriarchal superfamily structure of Kisapostag and Encrusted Pottery groups. The
relatively limited presence of female and children burials in both Bk-II and Bk-III periods may suggest
distinctive treatment or another (here undiscovered) burial group for women and children at the same site.
Although, in other Bronze Age cemeteries, e.g. Ordacsehi and Bonyhád in Hungary, males, females and
children were buried close to each other, suggesting high variance of burial practises34,35,44.
While low genomic coverage did not allow fine SNP recovery, we did find evidence for malignant variants
within all of our tested groups, and undoubtedly showed the presence of LHON and Jacob’s syndrome within
Bk-II. Additionally, the disease panel we created can be extended and used in future studies, providing
insight into past population health qualities.
Considering the unstructured age and kinship distribution in the mass grave Bk-III compared to Bk-II, the
coetaneous death of eight people at least, the absence of traumatic or ritual events on bones, and
non-cremated nature of the burial all signals a sudden tragic event in the Encrusted pottery period, most
likely an epidemic, as first suggested based on the anthropological analyses45. Interestingly, comparative
strontium isotope analyses on the first and third molar of the individuals in the BK-III mass grave indicate that
subadult males - including a severely disabled individual (S15) with hip dysplasia - left their community for a
while and then returned to their birthplace prior to their death, raising further questions for future studies on
prehistoric lifeways and social organisations.
Materials and Methods
Isotope analyses
Radiocarbon dating was performed at the HEKAL AMS C-14 facility of the Institute for Nuclear Research in
Debrecen, Hungary (see Supplementary Information section 1.8). 87Sr/86Sr isotope measurements were
performed in the ICER Centre, Institute for Nuclear Research Debrecen, Hungary and at Quinnipiac and Yale
University, Connecticut, USA (see Supplementary Information section 1.9).
Ancient DNA laboratory work
Petrous bones and teeth were taken from skulls for genetic investigation (Supplementary Table S1).
Laboratory work was performed in a dedicated ancient DNA laboratory facility (Institute of Archaeogenomics,
Research Centre for the Humanities, Eötvös Loránd Research Network, Budapest, Hungary). Each step was
carried out in separate rooms under sterile conditions, during work protective clothing was used. Irradiated
UV-C light, DNA-ExitusPlus™ (AppliChem) and/or bleach were applied for cleaning after and between work
stages, and also, blank controls were utilised at all times.
Sample surfaces were cleaned by sandblasting and mechanically milled to powder. DNA extraction was
performed according to Dabney et al. 201346 with minor changes according to Lipson et al. 20176. DNA
extraction success was verified by PCR using mtDNA primer pairs (F16209-R06348; F16045-R06240).
Half-UDG treated libraries were used according to Rohland et al. 201547 with minor changes. Unique double
internal barcode combinations were used for each library (Supplementary Table S1). Libraries were amplified
with TwistAmp Basic (Twist DX Ltd) and purified with AMPure XP beads (Agilent). Then, concentration
measurements were taken on Qubit 2.0 fluorometer, fragment sizes were checked on Agilent 4200
TapeStation System (Agilent High Sensitivity D1000 ScreenTape Assay).
Hybridisation capture method for mtDNA and 3k nuclear SNP was used besides whole genome shotgun, as
described by Haak et al. 2015, Lipson et al. 2017 and Csáky et al. 20204,6,48. Bait production was based on
Fu et al. 20161and N. Rohland’s personal communication, the oligos as a pool was ordered from
CustomArray Inc. Both for shotgun and capture libraries, universal iP5 and unique iP7 indexes were used.
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Sequencing was done on Illumina MiSeq and NovaSeq platforms with custom setup and 150, 200 and 300
cycles, respectively.
Additionally, we investigated Y chromosome STR profiles (17 markers) with AmpFISTR® Yfiler® PCR
Amplification Kit (Applied Biosystems), having one blank and one positive control at each reaction
preparation. The workflow followed the recommended protocol except the PCR cycles were increased from
30 to 34 and reactions were halved in volume. Two repeats were done where at least 4 markers yielded
results. Data analyses were carried out in GeneMapper® ID Software v3.2.1 (Applied Biosystems), results
are summarised in Supplementary Table S3.
Bioinformatic analyses
Illumina sequencing reads were processed by the PAPline, for details, see Supplementary Information
section 6. We used the GRCH37.p13 reference sequence for calling pseudohaploid genomes. For kinship
inferences we applied the READ software49 and a custom script (named MPMR, see Supplementary
Information section 2.3 and Supplementary Table S2). MtDNA analyses included phylogenetic analyses
using the MrBayes v3.2.650 and the BEAST v1.10.451 softwares and diversity tests using the Popgenome52 R
package, see Supplementary Information section 2.1. For Y chromosome haplogroup determination the
Yleaf v153 software was applied. For network analysis of STR data we used Network v10.1.0.0 and Network
publisher v2.1.2.554,55, see Supplementary Information section 2.2. Due to low genomic coverages (<10,000
SNPs) we discarded individuals S2, S5 and S17 from the population genetic analyses. PCA was made by
the Eigensoft smartpca software56 using the Human Origins Panel SNP set26, for other analyses the 1240k
array12 was used for SNP call, for results, see Supplementary Table S7. Individuals S4, S5, S6 and S20 were
discarded from further tests for them being first degree relatives of other samples. For investigating ancestry
estimates we used supervised admixture analysis calculated by the ADMIXTURE v1.3.0 software57. The
results were visualised by custom Rscripts. f-statistics and qpAdm were performed using the admixr v0.9.158
and the admixtools v2.0.026 Rpackages.
Data availability
All other study data are included in the article and/or Supplementary Information and tables. Sequencing
data are deposited in the European Nucleotide Archive (ENA) and are available to download under
accession number PRJEB49524. Our new software ‘PAPline’ is freely available at
https://www.github.com/gerberd-workshop/papline.
Acknowledgement
This study was funded by the Hungarian Academy of Sciences through the Momentum Mobility research
project (LP2015-3/2015). This paper and A.S-N. was supported by the János Bolyai Research Scholarship of
the Hungarian Academy of Sciences. E.A. 's work was supported by the National Research, Development
and Innovation Office, Hungary (NKFIH) grant (PD-19/131839). M.B. 's work and the analyses of the
BAD002 sample was supported by a NKFIH grant under project code K-18/128413. We would like to greatly
thank restorer Zsuzsanna Herceg and digital artist Fanni Gerber for the artwork of individual S13. We are
grateful for the radiocarbon dates to István Major and Mihály Molnár at the HEKAL AMS C14 facility of the
Institute for Nuclear Research in Debrecen, Hungary.
Author contribution
D.G, V.K., A.Sz-N. conceived and designed the experiments. D.G. processed the sequencing data, created
the PAPline, and performed downstream bioinformatic analyses. B.Sz. did all molecular laboratory work.
O.Sz. created the mtDNA database for phylogenetic analyses. B.E. obtained Y chromosome STR data.
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

B.Gy. and E.A. optimised genetic analyses. J.I.G., A.H., L.P. performed Sr isotope analysis. G.K., Sz.F., V. K.
and M.B. evaluated the archaeological context. B.G.M., Á.K. and K.K. did the anthropological examination of
the remains. Á.K. made the facial reconstruction. V.Sz. performed radiocarbon calibrations and modelling.
B.G.M. sampled the remains. E.A., V.K. and A.Sz-N. jointly supervised the research and wrote the paper with
D.G. All authors provide critical feedback for this study and contribute to the final manuscript.
Ethics declarations
The authors declare that they had requested and got permission for the destructive bioarchaeological
analyses of the archaeological material in the study from the stakeholders, excavator and processor
archaeologists.
Competing interests
The authors declare no competing interests.
References
1. Fu, Q. et al. The genetic history of Ice Age Europe. Nature 534, 200–205 (2016).
2. Mittnik, A. et al. The genetic prehistory of the Baltic Sea region. Nat. Commun. 9, 442
(2018).
3. Rivollat, M. et al. Ancient genome-wide DNA from France highlights the complexity of
interactions between Mesolithic hunter-gatherers and Neolithic farmers. Sci. Adv. 6,
eaaz5344 (2020).
4. Haak, W. et al. Massive migration from the steppe was a source for Indo-European
languages in Europe. Nature 522, 207–211 (2015).
5. Mathieson, I. et al. The genomic history of southeastern Europe. Nature 555, 197–203
(2018).
6. Lipson, M. et al. Parallel palaeogenomic transects reveal complex genetic history of
early European farmers. Nature 551, 368–372 (2017).
7. Allentoft, M. E. et al. Population genomics of Bronze Age Eurasia. Nature 522,
167–172 (2015).
8. Olalde, I. et al. The Beaker phenomenon and the genomic transformation of northwest
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

Europe. Nature 555, 190–196 (2018).
9. Schroeder, H. et al. Unraveling ancestry, kinship, and violence in a Late Neolithic mass
grave. Proc. Natl. Acad. Sci. 116, 10705–10710 (2019).
10. Freilich, S. et al. Reconstructing genetic histories and social organisation in Neolithic
and Bronze Age Croatia. Sci. Rep. 11, 16729 (2021).
11. Žegarac, A. et al. Ancient genomes provide insights into family structure and the
heredity of social status in the early Bronze Age of southeastern Europe. Sci. Rep. 11,
10072 (2021).
12. Mathieson, I. et al. Genome-wide patterns of selection in 230 ancient Eurasians.
Nature 528, 499–503 (2015).
13. Köhler, K. Anthropological examination of the Late Copper Age human remains. in The
Prehistoric Settlement at BalatonőszödTemetői-dűlő. The Middle Copper Age, Late
Copper Age and EarlyBronze Age Occupation 269–292 (Archaeolingua, 2014).
14. Alt, K. W. et al. Lombards on the Move – An Integrative Study of the Migration Period
Cemetery at Szólád, Hungary. PLoS ONE 9, e110793 (2014).
15. Mittnik, A. et al. Kinship-based social inequality in Bronze Age Europe. Science 366,
731–734 (2019).
16. Slon, V., Nagar, Y., Kuperman, T. & Hershkovitz, I. A Case of Dwarfism from the
Byzantine City Rehovot-in-the-Negev, Israel: Dwarfism and Christianity. Int. J.
Osteoarchaeol. 23, 573–589 (2013).
17. Bardsley, M. Z. et al. 47,XYY Syndrome: Clinical Phenotype and Timing of
Ascertainment. J. Pediatr. 163, 1085–1094 (2013).
18. Ehler, E. et al. AmtDB: a database of ancient human mitochondrial genomes. Nucleic
Acids Res. 47, D29–D32 (2019).
19. Tońska, K., Kodroń, A. & Bartnik, E. Genotype–phenotype correlations in Leber
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

hereditary optic neuropathy. Biochim. Biophys. Acta BBA - Bioenerg. 1797, 1119–1123
(2010).
20. Landrum, M. J. et al. ClinVar: improving access to variant interpretations and
supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018).
21. Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: Analysis of Next
Generation Sequencing Data. BMC Bioinformatics 15, 356 (2014).
22. dbSNP. NCBI https://www.ncbi.nlm.nih.gov/snp/docs/RefSNP_about/ (2021).
23. Reich, D. David Reich Lab: Ancient DNA, Biology, and Disease.
https://reich.hms.harvard.edu/allen-ancient-dna-resource-aadr-downloadable-genotype
s-present-day-and-ancient-dna-data (2021).
24. Buchvaldek, M. Zu den Beziehungen zwischen Böhmen, Mähren und dem
Karpatenbecken in der Frühbronzezeit. Bp. Régiségei 36, 211–221 (2002).
25. Dean, R. B. & Dixon, W. J. Simplified Statistics for Small Numbers of Observations.
Anal. Chem. 23, 636–638 (1951).
26. Patterson, N. et al. Ancient Admixture in Human History. Genetics 192, 1065–1093
(2012).
27. Brunel, S. et al. Ancient genomes from present-day France unveil 7,000 years of its
demographic history. Proc. Natl. Acad. Sci. 117, 12791–12798 (2020).
28. Bondár, M. & Szécsényi-Nagy, A. Skull cult in the Late Copper Age. Ziridava 34,
91–104 (2020).
29. Peltzer, A. et al. EAGER: efficient ancient genome reconstruction. Genome Biol. 17, 60
(2016).
30. Schubert, M. et al. Characterization of ancient and modern genomes by SNP detection
and phylogenomic and metagenomic analysis using PALEOMIX. Nat. Protoc. 9,
1056–1082 (2014).
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

31. Bóna, I. Die mittlere Bronzezeit Ungarns und ihre südöstlichen Beziehungen. Archaeol.
Hung. 49, 73–76, 229–230 (1975).
32. Bóna, I. Geschichte der frühen und mittleren Bronzezeit in Ungarn und im mittleren
Donauraum. in Annales Universitatis Scientiarum Budapestinensis de Rolando Eötvös
nominatae III-IV vol. 3 3–22 (ELTE, 1961).
33. Bándi, G. Die „Kisapostag-Problematik”. Die Kultur der transdanubischen inkrustierten
Keramik. in Kulturen der Frühbronzezeit des Karpatenbeckens und Nordbalkans.
257–281 (1984).
34. Szabó, G. A Dunántúli mészbetétes edények népe kultúrájának kialakulása és belső
időrendje a Bonyhádon feltárt temetőrészlet tükrében. in Wosinsky Mór Megyei
Múzeum Évkönyve vol. 32 101–128 (2010).
35. Hajdu, T. A bronzkori Dunántúli mészbetétes edények népe kultúrájának bonyhádi
temetője feltárása és az embertani leletek vizsgálata során alkalmazott módszerek
tanulságai. in Wosinsky Mór Megyei Múzeum Évkönyve vol. 32 129–140 (2010).
36. Kiss, V. The Bronze Age burial from Balatonakali revisited. in Objects, Ideas and
Travelers. Contacts between the Balkans, the Aegean and Western Anatolia during the
Bronze Age and Early Iron Age. Conference to the Memory of Alexandru Vulpe.
553–568 (Deutsche Nationalbibliothek, 2020).
37. Bóna, I. Bronzezeitliche Tell-Kulturen in Ungarn. in Bronzezeit in Ungarn. Forschungen
in Tell-Siedlungen an Donau und Theiss. 9–42 (Frankfurt am Main, 1992).
38. Črešnar, M. New research on the Urnfield period of Eastern Slovenia. A case study of
Rogoza near Maribor. Arheol. Vestn. 61, 114 (2010).
39. Kiss, V. Recent data on chronology, distribution, and connections of Kisapostag,
Transdanubian Encrusted Pottery and Litzenkeramik. in KEĎ BRONZ VYSTRIEDAL
MEĎ 27–38 (Archaeologica Slovaca Monographiae, 2015).
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

40. Mozsolics, A. A kisapostagi korabronzkori urnatemető (Der frühbronzezeitliche
Urnenfriedhof von Kisapostag). Archaeol. Hung. 26, (1941).
41. K. Zoffmann, Z. Az M7-es autópálya nyomvonalán előkerült őskori embertani leletek
rövid áttekintése. in Gördülő idő. Régészeti feltárások az M7-es autópálya Somogy
megyei szakaszán Zamárdi és Ordacsehi között – Rolling time. Excavationson the M7
motorway in County Somogy between Zamárdi and Ordacsehi. 309–313 (2007).
42. K. Zoffmann, Z. A bronzkori Gáta-Wieselburg kultúra Nagycenk-Laposi rét lelőhelyen
feltárt temetkezéseinek embertani vizsgálata. The anthropologic study of the burials
unearthed at the Nagycenk-Laposi rét site of the Bronze Age Gáta-Wieselburg Culture.
in Múzeumi Közlemények vol. 2 9–34 (2008).
43. Vicze, M. Bronze Age Cemetery at Dunaújváros-Duna-dűlő. Diss. Pannonicae 4,
34–36, 52–53 (2011).
44. Somogyi, K. A kisapostagi kultúra birituális temetője Ordacsehi-Csereföldön – Das
birituelle Gräberfeld der Kisapostag-Kultur on Ordacsehi-Csereföld. in Őskoros Kutatók
III. Összejövetelének konferenciakötete vol. MΩΜΩΣ 349–381 (2004).
45. Köhler K. Õskori tömegsír embertani leletei Balatonkeresztúrról. 17, 8 (2006).
46. Dabney, J. et al. Complete mitochondrial genome sequence of a Middle Pleistocene
cave bear reconstructed from ultrashort DNA fragments. Proc. Natl. Acad. Sci. 110,
15758–15763 (2013).
47. Rohland, N., Harney, E., Mallick, S., Nordenfelt, S. & Reich, D. Partial
uracil–DNA–glycosylase treatment for screening of ancient DNA. Philos. Trans. R. Soc.
B Biol. Sci. 370, 20130624 (2015).
48. Csáky, V. et al. Early medieval genetic data from Ural region evaluated in the light of
archaeological evidence of ancient Hungarians. Sci. Rep. 10, 19137 (2020).
49. Monroy Kuhn, J. M., Jakobsson, M. & Günther, T. Estimating genetic kin relationships
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint

in prehistoric populations. PLOS ONE 13, e0195491 (2018).
50. Ronquist, F. & Huelsenbeck, J. P. MrBayes 3: Bayesian phylogenetic inference under
mixed models. Bioinformatics 19, 1572–1574 (2003).
51. Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using
BEAST 1.10. Virus Evol. 4, (2018).
52. Pfeifer, B., Wittelsbürger, U., Ramos-Onsins, S. E. & Lercher, M. J. PopGenome: An
Efficient Swiss Army Knife for Population Genomic Analyses in R. Mol. Biol. Evol. 31,
1929–1936 (2014).
53. Ralf, A., Montiel González, D., Zhong, K. & Kayser, M. Yleaf: Software for Human
Y-Chromosomal Haplogroup Inference from Next-Generation Sequencing Data. Mol.
Biol. Evol. 35, 1291–1294 (2018).
54. Bandelt, H. J., Forster, P. & Rohl, A. Median-joining networks for inferring intraspecific
phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).
55. Network Software. Fluxus-Engineering
https://www.fluxus-engineering.com/sharepub.htm#a1 (2008).
56. Patterson, N. et al. EIGENSOFT. (2017).
57. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry
in unrelated individuals. Genome Res. 19, 1655–1664 (2009).
58. Petr, M., Vernot, B. & Kelso, J. admixr—R package for reproducible analyses using
ADMIXTOOLS. Bioinformatics 35, 3194–3195 (2019).
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for thisthis version posted February 6, 2022. ; https://doi.org/10.1101/2022.02.03.478968doi: bioRxiv preprint