Skip to content

Advertisement

Open Access

Bronze Age meat industry: ancient mitochondrial DNA analyses of pig bones from the prehistoric salt mines of Hallstatt (Austria)

  • Sabine E. Hammer1Email author,
  • Barbara Tautscher2,
  • Erich Pucher3,
  • Kerstin Kowarik4,
  • Hans Reschreiter4,
  • Anton Kern4 and
  • Elisabeth Haring2, 5
BMC Research Notes201811:243

https://doi.org/10.1186/s13104-018-3340-7

Received: 14 February 2018

Accepted: 30 March 2018

Published: 13 April 2018

Abstract

Objective

In the Bronze Age Hallstatt metropolis (‘Salzkammergut’ region, Upper Austria), salt richness enabled the preservation of pork meat to sustain people’s livelihood suggesting an organized meat production industry on a yearly basis of hundreds of pigs. To pattern the geographic and temporal framework of the early management of pig populations in the surrounding areas of Hallstatt, we want to gain insights into the phylogeographic network based on DNA sequence variation among modern pigs, wild boars and prehistoric (likely) domestic pigs.

Results

In this pilot study, we successfully adapted ancient DNA extraction and sequencing approaches for the analysis of mitochondrial DNA sequence variation in ten prehistoric porcine teeth specimens. Minimum-spanning network analyses revealed unique mitochondrial control region DNA haplotypes ranging within the variation of modern domestic pig and wild boar lineages and even shared haplotypes between prehistoric and modern domestic pigs and wild boars were observed.

Keywords

HallstattBronze Age Sus scrofa Ancient DNAMitochondrial DNAPhylogeographic network

Introduction

The UNESCO World Heritage Hallstatt-Dachstein/Salzkammergut, located in the eastern Austrian alps, represents one of the most important prehistoric production centres in Europe. Underground salt mining at depths of up to 170 m is attested as far back as 1500 years BC [1, 2]. Due to the high salt concentrations inside the prehistoric mining galleries, the remains of the extraction activity have been perfectly preserved [3, 4]. The size of the mining areas and the amount of mining waste evidence production on a large scale as well as a highly structured and technologically well-developed organization [1, 2]. Set in an alpine environment, with the production and settlement areas located in a narrow valley at an elevation of 1000 m above sea level (MASL), the prehistoric mining community was nonetheless able to meet the exacting demands of the large scale production activity. In Bronze Age, economic activity encompassed not only salt extraction, but also the production of cured meat, mainly from pig, on a very large scale. A special butchering technique, documented through thousands of pig bones, as well as facilities for curing the meat, 8 log basins with the capacity to hold up to 200 butchered pigs, attest to the developed organization and scale of this meat production industry. Currently archaeological data indicates that the meat of several hundred pigs was annually processed and cured in the Hallstatt High Valley [57]. The archaeozoological analysis of the bone inventory evidences a well organised system based on the breeding of animals for the “meat industry” and the transport of meat from the animal breeders to the Hallstatt High Valley. Morphological differences point to different areas of the pigs’ origin, to the North along the Traun river and to the Southeast towards the Styrian Salzkammergut [8].

The large scope of the project should delineate the geographic and temporal framework of the early management of pig populations in the surrounding areas of Hallstatt and allow to estimate the spatial extent of the catchment areas. These attempts should help to answer the questions which husbandries delivered pigs to Hallstatt and whether or not a natural pig breeding monopoly existed during the Hallstatt period. Ancient DNA elucidates phylogenetic relationships of pigs allowing insights into prehistoric farming practices as well as adaptation and domestication of pigs [913]. The high abundance of porcine teeth remnants at the Hallstatt High Valley initiated this pilot study to assess the suitability of this material for molecular genetic analyses. The study gained first insights into genetic variation in a neutral DNA marker sequence, the mitochondrial (mt) control region (CR) and thus will pave the way for deeper molecular analyses by nuclear marker assessment.

Main text

Methods

Animals and sample collection

The studied material comprises 10 mandibular cuspids (fangs), mainly from castrated males, excavated in 1939 and 1993/94 in the Hallstatt High Valley (‘Salzkammergut’ region, Upper Austria) (Table 1). The town of Hallstatt is situated at 47.56° North latitude, 13.65° East longitude and 514 MASL. The analysed specimens derived from an thick layer of animal bone assemblage being radiocarbon dated to the 13th/12th century BC, the Late Bronze Age [1, 2]. These animal bones are part of the Archaeozoological Collection at the Natural History Museum Vienna (NHMW), Austria. Detailed information on prehistoric pig specimens as well as modern Sus scrofa and Suinae taxa of the present study is given in Table 1.
Table 1

List of mitochondrial DNA sequences of prehistoric and modern domestic pigs, wild boars and Suinae obtained in the present study or downloaded from GenBank

Accession no

Tree/network label

Location

Species

Status

Breed

Source

MG926393

H45-1 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926394

HoN-4 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926395

H405-5 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926396

H124-6 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926397

H288-7 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926398

H51-1 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926393

H117-21 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

MG926393

H136-3 (AT)

Austria

Sus scrofa f. domestica

Prehistoric domestic

This study

DQ379225

Saddleback (DE)

Germany

Sus scrofa f. domestica

Domestic

Angeln Saddleback

[29]

AY884775

Landrace-01 (FI)

Finland

Sus scrofa f. domestica

Domestic

Landrace

[9]

AY884748

Landrace-02 (NO)

Norway

Sus scrofa f. domestica

Domestic

Landrace

[9]

AY884746

Duroc (GB)

United Kingdom

Sus scrofa f. domestica

Domestic

Duroc

[9]

AY884779

Creole (FR)

France

Sus scrofa f. domestica

Domestic

Creole

[9]

DQ152846

Large White (EU)

Europe

Sus scrofa f. domestica

Domestic

Large White

[29]

AY884763

Large White (FR)

France

Sus scrofa f. domestica

Domestic

Large White

[9]

AY884785

Large White (DE)

Germany

Sus scrofa f. domestica

Domestic

Large White

[9]

AY884751

Linderodssvin (SE)

Sweden

Sus scrofa f. domestica

Domestic

Linderodssvin

[9]

AY884769

Piétrain (DE)

Germany

Sus scrofa f. domestica

Domestic

Piétrain

[9]

AY884764

Mangalica (HU)

Hungaria

Sus scrofa f. domestica

Domestic

Mangalica

[9]

DQ152879

Bamei (CN)

China

Sus scrofa f. domestica

Domestic

Bamei

[29]

DQ152886

Huzhu (CN)

China

Sus scrofa f. domestica

Domestic

Huzhu

[29]

DQ379162

Meishan (CN)

China

Sus scrofa f. domestica

Domestic

Meishan

[29]

DQ152868

Zang (CN)

China

Sus scrofa f. domestica

Domestic

Zang

[29]

HM747197

Wild boar (AT)

Austria

Sus scrofa

Wild

[29]

AY884664

Wild boar (DE)

Germany

Sus scrofa

Wild

[9]

DQ379236

Wild boar (BE)

Belgium

Sus scrofa

Wild

[29]

DQ379253

Wild boar-1 (FR)

France

Sus scrofa

Wild

[29]

DQ379244

Wild boar-2 (FR)

France

Sus scrofa

Wild

[29]

FJ236998

Wild boar (ES)

Spain

Sus scrofa

Wild

Fernandez AI (26-SEP-2008)

AY884672

Wild boar (NO)

Norway

Sus scrofa

Wild

[9]

AY884670

Wild boar (MK)

Mecedonia

Sus scrofa

Wild

[9]

AY884726

Wild boar (AM)

Armenia

Sus scrofa

Wild

[9]

DQ872938

Wild boar-1 (IR)

Iran

Sus scrofa

Wild

[9]

DQ872956

Wild boar-2 (IR)

Iran

Sus scrofa

Wild

[9]

AY884612

Wild boar (IN)

India

Sus scrofa

Wild

[9]

AY884661

Wild boar (ID)

Indonesia

Sus scrofa

Wild

[9]

DQ379262

Wild boar-1 (CN)

China

Sus scrofa

Wild

[29]

DQ379266

Wild boar-2 (CN)

China

Sus scrofa

Wild

[29]

AY884702

S. scrofa papuensis

Papua New Guinea

Sus scrofa papuensis

Wild

[9]

AY884708

S. scrofa taiwanensis

Taiwan

Sus scrofa taiwanensis

Wild

[9]

AY884705

S. scrofa andamensis

Andaman Islands (India)

Sus scrofa andamensis

Wild

[9]

KF952600

Sus cebifrons

Philippines

Sus cebifrons

Wild

Si T (10-DEC-2013)

KP789021

Sus barbatus

Southeast Asia

Sus barbatus

Wild

Zhang S (13-FEB-2015)

KF926379

Sus verrucosus

Indonesian

Sus verrucosus

Wild

Fan J (03-DEC-2013)

Specimens from Hallstatt are written in Italic underline. In column ‘Tree/Network label’, the ISO 3166 Countries Codes are given in brackets

DNA extraction

DNA extractions were performed in a clean room by obeying all standard routines for working with aDNA [14, 15] (For details see Additional file 1). Cleaning and decontamination of grinding bowls and balls was performed with DNA-Away1 after an ultrasonic bath followed by subsequent UV radiation. All post-PCR work was carried out in a separate laboratory. Extraction controls (buffers without sample) were performed to screen for contaminated extraction reagents. For each specimen, at least two independent DNA extractions were performed. The detailed protocol for DNA extraction is given in Additional file 1. Briefly, prior to the DNA extraction, the surface of each tooth was treated with 3% sodium hypochlorite and rinsed in nuclease free water2 for decontamination [16]. The dried teeth were crushed into small pieces and pulverized with a Retsch MM400 grinding mill.3 Next, 1 g tooth powder was decalcified three times by adding 4.5 ml Decalcifier soft4 (containing 25% EDTA) and rotating overnight incubation at 4 °C. Following centrifugation (Eppendorf Centrifuge 54305), the supernatant was discarded and replaced by 4.5 ml fresh decalcifying solution. After decalcification, the powder was washed three times by adding 4.5 ml nuclease free water to remove all remains of EDTA. The rinsed powder was subjected to DNA extraction with the Gen-ial All Tissue Kit6 according to the manufacturer’s instructions for DNA extraction from bone to teeth. Finally, the DNA was dissolved in 30 µl nuclease free water (see footnote 2) and after concentration measurement (BioPhotometer D30, µCuvette G1.0) (see footnote 5), the DNA solutions were immediately aliquoted (5–10 µl) and stored at 4 °C (short term) or at − 20 °C for long term.

PCR amplification of the mitochondrial control region

A 721-basepair-long section of the mitochondrial control region was amplified using three PCR primer pairs that produce three overlapping amplicons, ranging from 343 to 401 base pairs (bp) in length (Additional files 2, 3 and 4). PCR was performed with Amplitaq Gold® 360 DNA-Polymerase7 and PCR reactions were run on a Mastercycler Nexus (See footnote 5) by applying conventional thermal cycling conditions and touch-down protocols (Additional file 1). Failed PCR reactions were repeated with varying amounts of template DNA. Control PCR reactions were performed to screen for contaminated reagents: extraction control (buffers without sample) and non-template control with nuclease-free water instead of template. Finally, PCR products were purified with the QIAquick PCR Purification Kit (see footnote 2) and sequenced (both directions using the PCR primers) at Microsynth AG8 and LGC Genomics.9

DNA sequence analysis and phylogenetic reconstruction

BioEdit Sequence Alignment Editor (v7.2.5) was used for nucleotide sequence alignment and sequence editing [17]. The final dataset including previously published sequences (GenBank) had a length of 637 sites and comprised 42 sequences. Trees were calculated by the Neighbor-Joining (NJ) method [18], by Maximum-Likelihood (ML) as well as Bayesian inference (BI) using the software MEGA7 [19] for NJ and ML trees and MrBayes v3.2 [20] for BI trees. For the NJ analysis, the evolutionary distances were computed using the p-distance method [21] and are in the units of the number of base differences per site. The ML method was based on the Tamura 3-parameter model [22] with a discrete Gamma distribution to model evolutionary rate differences among sites (two categories: G = 0.58, I = 0.75). Parameters for BI analysis were as follows: lset nst = 2 rates = gamma [20]. FigTree v1.4.3 [23] was used to annotate the consensus tree produced by MrBayes. The unrooted phylogenetic network was constructed with PopART [24, 25] by applying the minimum spanning option.

Results and discussion

Out of the ten samples analysed, seven allowed to determine the complete CR marker sequence (637 bp), whereas two were unsuccessful and one allowed to amplify fragment B (342 bp), only. Sequences obtained in the present study are deposited in GenBank (Accession no’s MG926393–MG926400, Table 1).

As can be seen in Additional file 5, PCR success is not strictly correlated with DNA concentrations e.g., one of the unsuccessful samples, H188-7 proved to have the highest DNA concentrations, while the sample with the lowest concentration H117-21 allowed to amplify all fragments. Unfortunately, the overall amount of DNA that could be extracted from each tooth was limited and thus only a few PCR trials were possible until the DNA was completely used up. Since DNA concentration seems to be not a reliable predictor of fragmentation it appears reasonable to further reduce the amplicon size. This will of course increase the effort necessary to obtain complete sequences, but, on the other hand, will allow to determine the sequence from a higher number of samples. Three samples (H45-1, H117-21, HoN-4) delivered sequences without any ambiguities, while in samples H405-5, H288-7, H51-1, and H124-6 several ambiguous sites were found, which could be interpreted as derived from post-mortem modifications. Almost all of them could be determined by repetition of PCR and subsequent sequencing as well as with the information from overlapping regions. Only in sample H124-6 two C/T ambiguities could not be resolved and are coded as Y in the alignment. The final alignment (637 bp) comprising 42 sequences of prehistoric and modern domestic pigs, wild boars and Suinae (Table 1) had 567 conserved and 35 parsimony informative sites. The p-distances among prehistoric domestic pigs ranged from 0.2 to 3.2% (average 1.1%), while distances within the in-group were up to 3.9% (average 1.6%) and between S. scrofa and the outgroup taxa distances ranged from 2.4 to 5.7% (average 3.7%) (Additional file 6). A minimum spanning network based on this alignment is roughly divided into two groups (Fig. 1). Interestingly, the “Asian” group includes sequences of Asian as well as European origin, as well as the outgroup taxa. In contrast, the “European” group exclusively consists of sequences derived from European breeds as well as prehistoric pigs from Hallstatt. One sequence from Hallstatt (HoN4) has an intermediate position between the two haplogroups. The inclusion of the outgroup sequences into the network illustrates that distances within S. scrofa are almost in the same range as between S. scrofa and the outgroup (see also Additional files 6, 7). A rooted NJ tree is given in Additional file 8 to alternatively illustrate the distances between sequences and shows the same overall topology as the ML and BI trees (support values of all analyses are included in the NJ tree in Additional files 8, 9). As the separation into two haplogroups is not well supported in this NJ tree, future analyses of additional markers should help to support this geographic pattern. Concerning the distribution of prehistoric samples in the network, there are two shared haplotypes harboured by prehistoric as well as modern pigs: H288-7 was identical with a Wild boar specimen from Norway to H45-1 and H405-5 shared the same haplotype with a British Duroc and the French Wild boar-1.
Fig. 1

Minimum Spanning network illustrating the diversity of haplotypes of the mitochondrial control region of 35 modern wild and domestic Sus taxa and seven prehistoric domestic pigs (in red). The network is based on the 637 bp-alignment. The size of the circles is proportional to the number of individuals sharing the haplotype and the numbers are shown in the circles. Colour-coded connecting lines illustrate the number of nucleotide differences between haplotypes: 1 = blue, 2 = green and 3 = purple. Nucleotide differences between haplotypes greater than 3 are indicated by the boxed digits placed on the connecting lines. Detailed information on taxa and samples is given in Table 1 by defining the specimens’ status as domestic or wild and indicating the pig breed, if applicable. For information on shared haplotypes see main text

Conclusions

There are three major outcomes: (1) The results indicate that the teeth are suitable material to obtain genetic information from prehistoric Sus domestica (S. scrofa f. domestica) from Hallstatt. Next steps are to test nuclear markers (e.g., nuclear DNA sequences of mitochondrial origin (numts) [26]; Y chromosome, MCR1 [27]; SLA-DRB1 [28]) with the tooth material as well as bones to assess the potential success of genomic analyses. (2) The variety found in the mitochondrial marker sequence of prehistoric pigs is almost as high as found among present day S. scrofa (Wild boar and breeds). Although the data presented here can be considered only as first hints, they are in favour for the assumption that the Hallstatt pigs were derived from large herds and/or various husbandries. However, the placement of prehistoric pigs in the haplotype network and the phylogenetic tree do not allow to draw conclusions about their geographical origin and status (wild vs. domesticated). The results are in accordance with earlier findings implying repeated gene flow between wild boar and domestic breeds [9, 29, 30]. (3) With the exception of the intermediate haplotype, all prehistoric pigs from Hallstatt resemble haplotypes of the “European” group. Shared haplotypes between prehistoric and modern S. scrofa indicate that Hallstatt pigs did not represent an independent lineage, but seem to range within the variation of extant S. scrofa.

Limitations

Limitations of this study were mainly due to the low number of prehistoric pigs that have been analysed and the fact that DNA sequence analyses in this pilot study are based on a single mitochondrial marker system. Moreover, the suitability of other bony material for obtaining genetic information from prehistoric pig specimens has to be proven in subsequent experiments. Future nuclear marker assessments will assist in drawing a clearer picture of prehistoric Hallstatt’s meat production and surrounding husbandries. However, any signal could be blurred by a substantial amount of gene flow between geographic regions as well as between wild boars and domesticated pigs.

Footnotes
1

Molecular BioProducts (San Diego, CA).

 
2

Qiagen (Hilden, Germany).

 
3

Retsch GmbH (Haan, Germany).

 
4

Carl Roth (Karlsruhe, Germany).

 
5

Eppendorf AG (Hamburg, Germany).

 
6

GEN-IAL (Troisdorf, Germany).

 
7

Thermo Fisher Scientific (Waltham, MA).

 
8

Microsynth AG (Balgach, Switzerland).

 
9

LGC Genomics (Berlin, Germany).

 

Abbreviations

UNESCO: 

United Nations Educational, Scientific and Cultural Organization

BC: 

before Christ

MASL: 

meters above sea level

mt: 

mitochondrial

CR: 

control region

NHMW: 

Natural History Museum Vienna

EDTA: 

ethylene diamine tetraacetic acid

PCR: 

polymerase chain reaction

bp: 

base pairs

NJ: 

Neighbor-Joining

ML: 

Maximum-Likelihood

BI: 

Bayesian inference

MEGA: 

molecular evolutionary genetics analysis

numts: 

nuclear DNA sequences of mitochondrial origin

MCR1: 

melanocortin receptor 1

Declarations

Authors’ contributions

SEH, EH and HR conceived and designed the study. SEH and EH designed and performed experiments, supervised research and wrote the manuscript with input from all authors. BT designed and performed experiments. SEH and EH interpreted the results and drafted the manuscript. BT, KK and HR helped prepare the manuscript. KK and AK initiated the study and provided specimen-specific information. EP provided access to the collection and specimen-specific information. All authors read and approved the final manuscript.

Acknowledgements

The authors would like to thank Wilhelm Pinsker for critical reading of the manuscript.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

Not applicable.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Institute of Immunology, Department of Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
(2)
Central Research Laboratories, Museum of Natural History Vienna, Vienna, Austria
(3)
1st Zoological Department, Archaeozoological Collection, Museum of Natural History Vienna, Vienna, Austria
(4)
Prehistoric Department, Museum of Natural History Vienna, Vienna, Austria
(5)
Department of Integrative Zoology, University of Vienna, Vienna, Austria

References

  1. Kern A, Kowarik K, Rausch AW, Reschreiter H. Kingdom of Salt. 7000 years of Hallstatt. 3rd ed. Vienna: Department of Prehistory (VPA), Natural History Museum; 2009.Google Scholar
  2. Reschreiter H. In: Grömer K, Kern A, Reschreiter H, Rösl-Mautendorfer H, editors. The prehistoric salt-mines of Hallstatt/Das Salzbergwerk Hallstatt. Budapest: Textiles from Hallstatt; 2013. p. 13–32.Google Scholar
  3. Reschreiter H, Miller Dv, Gengler C, Kalabis S, Zangerl N, Fürhacker R, et al. Aus dem Salz ins Depot - Organische Funde aus den prähistorischen Salzbergwerken von Hallstatt. Wien: Österreichische Zeitschrift für Kunst- und Denkmalpflege; 2014. p. 354–67.Google Scholar
  4. Piñar G, Dalnodar D, Voitl C, Reschreiter H, Sterflinger K. Biodeterioration risk threatens the 3100 year old staircase of Hallstatt (Austria): possible involvement of halophilic microorganisms. PLoS ONE. 2016;11:e0148279.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Pucher E. Hallstatt and Dürrnberg - two salt-mining sites, two different meat supply strategies. In: Anreiter P et al. (ed.) Mining in European history and its impact on environment and human societies. 2010. Proceedings for the 1st mining in european history-conference of the SFB-HIMAT, 12–15. November 2009, Innsbruck. pp. 193–197, Innsbruck: Innsbruck University Press.Google Scholar
  6. Pucher E, Barth FE, Seemann R, Brandstätter F. Bronzezeitliche Fleischverarbeitung im Salzbergtal bei Hallstatt. In: Pucher E, Barth FE, Seemann R, Brandstätter F, editors. Bronzezeitliche Fleischverarbeitung im Salzbergtal bei Hallstatt. 80th ed. Vienna: Mitteilungen der Prähistorischen Kommission, Österreichische Akademie der Wissenschaften, Philosophisch-historische Klasse; 2013. p. 11–134.View ArticleGoogle Scholar
  7. Barth FE. Die Blockwandbauten des Salzbergtales bei Hallstatt und ihre Verwendung. In: Pucher E, Barth FE, Seemann R, Brandstätter F, editors. Bronzezeitliche Fleischverarbeitung im Salzbergtal bei Hallstatt. 80th ed. Vienna: Mitteilungen der Prähistorischen Kommission, Österreichische Akademie der Wissenschaften, Philosophisch-historische Klasse; 2013. p. 93–134.Google Scholar
  8. Pucher E. Neue Aspekte zur Versorgungslogistik Hallstatts: Tierknochenfundkomplexe aus Pichl, Steiermark. Fundberichte aus Österreich. 2014;52:65–93.Google Scholar
  9. Larson G, Dobney K, Albarella U, Fang M, Matisoo-Smith E, Robins J, Lowden S, Finlayson H, Brand T, Willerslev E, Rowley-Conwy P, Andersson L, Cooper A. Worldwide phylogeography of wild boar reveals multiple centers of pig domestication. Science. 2005;307:1618–21.View ArticlePubMedGoogle Scholar
  10. Larson G, Liuc R, Zhaoc X, Yuan J, Fuller D, Barton L, Dobney K, Fan Q, Gu Z, Liu X-H, Luo Y, Lv P, Andersson L, Li N. Patterns of East Asian pig domestication, migration, and turnover revealed by modern and ancient DNA. Proc Natl Acad Sci USA. 2010;107:7687.Google Scholar
  11. Hammer SE, Däubl B, Pucher E, Barth F-E, Kern A, Haring E, Reschreiter H. Ancient mitochondrial DNA analyses of Bronze Age pigs from Hallstatt—results from a pilot study. Mammal Biol. 2016;81(Suppl. 1):7.Google Scholar
  12. Zhang J, Jiao T, Zhao S. Genetic diversity in the mitochondrial DNA D-loop region of global swine (Sus scrofa) populations. Biochem Biophys Res Commun. 2016;473:814–20.View ArticlePubMedGoogle Scholar
  13. Caliebe A, Nebel A, Makarewicz C, Krawczak M, Krause-Kyora B. Insights into early pig domestication provided by ancient DNA analysis. Sci Rep. 2017;7:44550.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Cooper A, Poinar HN. Ancient DNA: do it right or not at all. Science. 2000;289:1139.View ArticlePubMedGoogle Scholar
  15. Haring E, Voyta LL, Däubl B, Tiunov MP. Comparison of genetic and morphological characters in fossil teeth of grey voles from the Russian Far East (Rodentia: Cricetidae: Alexandromys). Mammal Biol. 2015;80:496–504.View ArticleGoogle Scholar
  16. Watt KA (2005). Decontamination techniques in ancient DNA analysis. Master thesis, Simon Fraser University, Burnaby, BC, Canada.Google Scholar
  17. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucl Acids Symp Ser. 1999;41:95–8.Google Scholar
  18. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987;4:406–25.PubMedGoogle Scholar
  19. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.View ArticlePubMedGoogle Scholar
  20. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012;61:539–42.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Nei M, Kumar S. Molecular evolution and phylogenetics. New York: Oxford University Press; 2000.Google Scholar
  22. Tamura K. Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G + C-content biases. Mol Biol Evol. 1992;9:678–87.PubMedGoogle Scholar
  23. Rambaut A (2006–2016) FigTree—a tree figure drawing tool, v1.4.3. http://tree.bio.ed.ac.uk/software/figtree/. Accessed 10 August 2017.
  24. Bandelt H, Forster P, Röhl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16:37–48.View ArticlePubMedGoogle Scholar
  25. Leigh JW, Bryant D. PopART: full-feature software for haplotype network construction. Methods Ecol Evol. 2015;6:1110–6.View ArticleGoogle Scholar
  26. Schiavo G, Hoffmann OI, Ribani A, Utzeri VJ, Ghionda MC, Bertolini F, Geraci C, Bovo S, Fontanesi L. A genomic landscape of mitochondrial DNA insertions in the pig nuclear genome provides evolutionary signatures of interspecies admixture. DNA Res. 2017;24:487–98.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Adeola AC, et al. Analysis of the genetic variation in mitochondrial DNA, Y-chromosome sequences, and MC1R sheds light on the ancestry of Nigerian indigenous pigs. Genet Sel Evol. 2017;49:52.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Moutou KA, Koutsogiannouli EA, Stamatis C, Billinis C, Kalbe C, Scandura M, Mamuris Z. Domestication does not narrow MHC diversity in Sus scrofa. Immunogenetics. 2013;65:195–209.View ArticlePubMedGoogle Scholar
  29. Fang M, Andersson L. Mitochondrial diversity in European and Chinese pigs is consistent with population expansions that occurred prior to domestication. Proc Biol Sci USA. 2006;273:1803–10.View ArticleGoogle Scholar
  30. Alves PC, Pinheiro I, Godinho R, Vicente J, Gortazar C, Scandura M. Genetic diversity of wild boar populations and domestic pig breeds (Sus scrofa) in South-western Europe. Biol J Linn Soc Lond. 2010;101:797–822.View ArticleGoogle Scholar

Copyright

© The Author(s) 2018

Advertisement