Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Beyond broad strokes: sociocultural insights from the study of ancient genomes

Abstract

In the field of human history, ancient DNA has provided answers to long-standing debates about major movements of people and has begun to inform on other important facets of the human experience. The field is now moving from mostly large-scale supraregional studies to a more local perspective, shedding light on socioeconomic processes, inheritance rules, marriage practices and technological diffusion. In this Review, we summarize recent studies showcasing these types of insights, focusing on methods used to infer sociocultural aspects of human behaviour. This approach often involves working across disciplines — such as anthropology, archaeology, linguistics and genetics — that have until recently evolved in separation. Multidisciplinary dialogue is important for an integrated reconstruction of human history, which can yield extraordinary insights about past societies, reproductive behaviours and even lifestyle habits that would not be possible to obtain otherwise.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: The spread of farming and ‘farming ancestry’ during the Neolithic period.
Fig. 2: Homozygosity by descent in present-day and ancient humans.
Fig. 3: Changes in patterns of mobility through time.

References

  1. Ammerman, A. J. & Cavalli-Sforza, L. L. The Neolithic Transition and the Genetics of Populations in Europe (Princeton University Press, 1984)

  2. Hakenbeck, S. Migration in archaeology: are we nearly there yet? Archaeol. Rev. Camb. 23, 9–26 (2008).

    Google Scholar 

  3. Hofreiter, M., Serre, D., Poinar, H. N., Kuch, M. & Pääbo, S. Ancient DNA. Nat. Rev. Genet. 2, 353–359 (2001).

    CAS  PubMed  Google Scholar 

  4. Willerslev, E. & Cooper, A. Ancient DNA. Proc. Biol. Sci. 272, 3–16 (2005).

    CAS  PubMed  Google Scholar 

  5. Damgaard, P. B. et al. Improving access to endogenous DNA in ancient bones and teeth. Sci. Rep. 5, 11184 (2015).

    PubMed  PubMed Central  Google Scholar 

  6. Pinhasi, R. et al. Optimal ancient DNA yields from the inner ear part of the human petrous bone. PLoS One 10, e0129102 (2015).

    PubMed  PubMed Central  Google Scholar 

  7. Sirak, K. A. et al. A minimally-invasive method for sampling human petrous bones from the cranial base for ancient DNA analysis. Biotechniques 62, 283–289 (2017).

    CAS  PubMed  Google Scholar 

  8. Cruz-Dávalos, D. I. et al. Experimental conditions improving in-solution target enrichment for ancient DNA. Mol. Ecol. Resour. 17, 508–522 (2017).

    PubMed  Google Scholar 

  9. Dabney, J. & Meyer, M. Length and GC-biases during sequencing library amplification: a comparison of various polymerase-buffer systems with ancient and modern DNA sequencing libraries. Biotechniques 52, 87–94 (2012).

    CAS  PubMed  Google Scholar 

  10. Gansauge, M.-T. & Meyer, M. Single-stranded DNA library preparation for the sequencing of ancient or damaged DNA. Nat. Protoc. 8, 737–748 (2013).

    PubMed  Google Scholar 

  11. Meyer, M. et al. A high-coverage genome sequence from an archaic Denisovan individual. Science 338, 222–226 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2012).

    CAS  PubMed  Google Scholar 

  13. Barnett, R. & Larson, G. A phenol-chloroform protocol for extracting DNA from ancient samples. Methods Mol. Biol. 840, 13–19 (2012).

    CAS  PubMed  Google Scholar 

  14. Carpenter, M. L. et al. Pulling out the 1%: whole-genome capture for the targeted enrichment of ancient DNA sequencing libraries. Am. J. Hum. Genet. 93, 852–864 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Slatkin, M. & Racimo, F. Ancient DNA and human history. Proc. Natl Acad. Sci. USA 113, 6380–6387 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Marciniak, S. & Perry, G. H. Harnessing ancient genomes to study the history of human adaptation. Nat. Rev. Genet. 18, 659–674 (2017).

    CAS  PubMed  Google Scholar 

  17. Skoglund, P. & Mathieson, I. Ancient genomics of modern humans: the first decade. Annu. Rev. Genomics Hum. Genet. 19, 381–404 (2018).

    CAS  PubMed  Google Scholar 

  18. Pickrell, J. & Reich, D. Towards a new history and geography of human genes informed by ancient DNA. Trends. Genet. 30, 377–389 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Gerstenberger, J., Hummel, S. & Herrmann, B. Reconstruction of residence patterns through genetic typing of skeletal remains of an early medieval population. Anc. Biomol. 4, 25–32 (2002).

    CAS  Google Scholar 

  20. Gerstenberger, J., Hummel, S., Schultes, T., Häck, B. & Herrmann, B. Reconstruction of a historical genealogy by means of STR analysis and Y-haplotyping of ancient DNA. Eur. J. Hum. Genet. 7, 469–477 (1999).

    CAS  PubMed  Google Scholar 

  21. Haak, W. et al. Ancient DNA, strontium isotopes, and osteological analyses shed light on social and kinship organization of the later Stone Age. Proc. Natl Acad. Sci. USA 105, 18226–18231 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Gamba, C. et al. Genome flux and stasis in a five millennium transect of European prehistory. Nat. Commun. 5, 5257 (2014).

    CAS  PubMed  Google Scholar 

  23. Lindo, J. et al. A time transect of exomes from a Native American population before and after European contact. Nat. Commun. 7, 13175 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Irving-Pease, E. K. et al. Paleogenomics of animal domestication. Popul. Genomics. https://doi.org/10.1007/13836_2018_55 (2018).

    Article  Google Scholar 

  25. Estrada, O., Breen, J., Richards, S. M. & Cooper, A. Ancient plant DNA in the genomic era. Nat. Plants 4, 394–396 (2018).

    CAS  PubMed  Google Scholar 

  26. Gutaker, R. M. & Burbano, H. A. Reinforcing plant evolutionary genomics using ancient DNA. Curr. Opin. Plant. Biol. 36, 38–45 (2017).

    CAS  PubMed  Google Scholar 

  27. MacHugh, D. E., Larson, G. & Orlando, L. Taming the past: ancient DNA and the study of animal domestication. Annu. Rev. Anim. Biosci. 5, 329–351 (2017).

    CAS  PubMed  Google Scholar 

  28. Houldcroft, C. J., Rifkin, R. F. & Underdown, S. J. Human biology and ancient DNA: exploring disease, domestication and movement. Ann. Hum. Biol. 46, 95–98 (2019).

    PubMed  Google Scholar 

  29. McHugo, G. P., Dover, M. J. & MacHugh, D. E. Unlocking the origins and biology of domestic animals using ancient DNA and paleogenomics. BMC Biol. 17, 98 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Bocquet-Appel, J.-P., Naji, S., Linden, M. V. & Kozlowski, J. K. Detection of diffusion and contact zones of early farming in Europe from the space-time distribution of 14C dates. J. Arch. Sci. 36, 807–820 (2009).

    Google Scholar 

  31. Silva, F. & Steele, J. New methods for reconstructing geographical effects on dispersal rates and routes from large-scale radiocarbon databases. J. Arch. Sci. 52, 609–620 (2014).

    Google Scholar 

  32. Fort, J. Demic and cultural diffusion propagated the Neolithic transition across different regions of Europe. J. R. Soc. Interface https://doi.org/10.1098/rsif.2015.0166 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Silva, F. & Linden, M. V. Amplitude of travelling front as inferred from 14C predicts levels of genetic admixture among European early farmers. Sci. Rep. 7, 11985 (2017).

    PubMed  PubMed Central  Google Scholar 

  34. Fort, J. in Diffusive Spreading in Nature, Technology and Society (eds Bunde, A., Caro, J., Kärger, J. & Vogl, G.) 313–331 (Springer, 2018).

  35. Lemmen, C. & Gronenborn, D. in Diffusive Spreading in Nature, Technology and Society (eds Bunde, A., Caro, J., Kärger, J. & Vogl, G.) 333–349 (Springer, 2018)

  36. Mathieson, I. et al. Genome-wide patterns of selection in 230 ancient Eurasians. Nature 528, 499–503 (2015). The authors perform a genome-wide selection analysis in a large data set of ancient European genomes and are able to describe temporal changes in adaptive alleles. This work paved the way for future large screenings to detect selective events.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Lazaridis, I. et al. Genomic insights into the origin of farming in the ancient Near East. Nature 536, 419–424 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Skoglund, P. et al. Origins and genetic legacy of Neolithic farmers and hunter-gatherers in Europe. Science 336, 466–469 (2012).

    CAS  PubMed  Google Scholar 

  39. Skoglund, P. et al. Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmers. Science 344, 747–750 (2014).

    CAS  PubMed  Google Scholar 

  40. Haak, W. et al. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature 522, 207–211 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Mathieson, I. et al. The genomic history of southeastern Europe. Nature 555, 197–203 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Broushaki, F. et al. Early Neolithic genomes from the eastern Fertile Crescent. Science 353, 499–503 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Racimo, F. et al. A geostatistical approach to modelling human Holocene migrations in Europe using ancient DNA. Preprint at bioRxiv https://doi.org/10.1101/826149 (2019).

    Article  Google Scholar 

  44. Lazaridis, I. et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Lipson, M. et al. Parallel palaeogenomic transects reveal complex genetic history of early European farmers. Nature 551, 368–372 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Hofmanová, Z. et al. Early farmers from across Europe directly descended from Neolithic Aegeans. Proc. Natl Acad. Sci. USA 113, 6886–6891 (2016).

    PubMed  PubMed Central  Google Scholar 

  47. Sikora, M. et al. Population genomic analysis of ancient and modern genomes yields new insights into the genetic ancestry of the Tyrolean Iceman and the genetic structure of Europe. PLoS Genet. 10, e1004353 (2014).

    PubMed  PubMed Central  Google Scholar 

  48. Allentoft, M. E. et al. Population genomics of Bronze Age Eurasia. Nature 522, 167–172 (2015). Haak et al. (2015) and Allentoft et al. (2015) are two key articles that independently identify signals for migration from the Eurasian Steppe in the third millennium BCE in Europe.

    CAS  PubMed  Google Scholar 

  49. Narasimhan, V. M. et al. The formation of human populations in South and Central Asia. Science 365, eaat7478 (2019). This work explores the movements of people in the past thousands of years and the formation of a male-biased genetic cline from Central Asia into South Asia, which may be associated with the spread of Indo-European languages and other social transformation events.

    Google Scholar 

  50. Lipson, M. et al. Ancient genomes document multiple waves of migration in Southeast Asian prehistory. Science 361, 92–95 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. McColl, H. et al. The prehistoric peopling of Southeast Asia. Science 361, 88–92 (2018).

    CAS  PubMed  Google Scholar 

  52. Prendergast, M. E. et al. Ancient DNA reveals a multistep spread of the first herders into sub-Saharan Africa. Science https://doi.org/10.1126/science.aaw6275 (2019).

  53. Ye, K., Gao, F., Wang, D., Bar-Yosef, O. & Keinan, A. Dietary adaptation of FADS genes in Europe varied across time and geography. Nat. Ecol. Evolution 1, 0167 (2017).

    Google Scholar 

  54. Buckley, M. T. et al. Selection in Europeans on fatty acid desaturases associated with dietary changes. Mol. Biol. Evol. 34, 1307–1318 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Mathieson, S. & Mathieson, I. FADS1 and the timing of human adaptation to agriculture. Mol. Biol. Evol. 35, 2957–2970 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Bevan, A. et al. Holocene fluctuations in human population demonstrate repeated links to food production and climate. Proc. Natl Acad. Sci. USA 114, E10524–E10531 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Capuzzo, G., Zanon, M., Dal Corso, M., Kirleis, W. & Barceló, J. A. Highly diverse Bronze Age population dynamics in central-southern Europe and their response to regional climatic patterns. PLoS One 13, e0200709 (2018).

    PubMed  PubMed Central  Google Scholar 

  58. Czebreszuk, J. Similar but Different: Bell Beakers in Europe (Sidestone Press, 2014).

  59. Fokkens, H. & Nicolis, F. Background to Beakers: Inquiries into the Regional Cultural Background to the Bell Beaker Complex. (Sidestone Press, 2012).

  60. Shennan, S. J. Settlement and social change in central Europe, 3500-1500 BC. J. World Prehist. 7, 121–161 (1993).

    Google Scholar 

  61. Linden, M. V. What linked the Bell Beakers in third millennium BC Europe? Antiquity 81, 343–352 (2007).

    Google Scholar 

  62. Olalde, I. et al. The Beaker phenomenon and the genomic transformation of northwest Europe. Nature 555, 190–196 (2018). This continental-scale analysis on the Bell Beaker archaeological phenomenon unveiled first a diffusion of ideas and a subsequent population movement that replaced the previous Neolithic population from the British Isles.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Outram, A. K. et al. The earliest horse harnessing and milking. Science 323, 1332–1335 (2009).

    CAS  PubMed  Google Scholar 

  64. de Barros Damgaard, P. et al. The first horse herders and the impact of early Bronze Age steppe expansions into Asia. Science 360, eaa7711 (2018).

    Google Scholar 

  65. Gaunitz, C. et al. Ancient genomes revisit the ancestry of domestic and Przewalski’s horses. Science 360, 111–114 (2018).

    CAS  PubMed  Google Scholar 

  66. Fages, A. et al. Tracking five millennia of horse management with extensive ancient genome time series. Cell 177, 1419–1435 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Sánchez-Quinto, F. et al. Megalithic tombs in western and northern Neolithic Europe were linked to a kindred society. Proc. Natl Acad. Sci. USA 116, 9469–9474 (2019).

    PubMed  PubMed Central  Google Scholar 

  68. Scarre, C. J. Archaeology: kin-groups in Megalithic burials. Nature 311, 512–513 (1984).

    Google Scholar 

  69. Schroeder, H. et al. Unraveling ancestry, kinship, and violence in a Late Neolithic mass grave. Proc. Natl Acad. Sci. USA 116, 10705–10710 (2019). The genetic analysis of a Late Neolithic Polish mass grave with 15 bodies exposed the kinship links among the people buried in this dramatic episode at the time of the arrival of the Eurasian Steppe nomads.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Knipper, C. et al. Female exogamy and gene pool diversification at the transition from the Final Neolithic to the Early Bronze Age in central Europe. Proc. Natl Acad. Sci. USA 114, 10083–10088 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Kennett, D. J. et al. Archaeogenomic evidence reveals prehistoric matrilineal dynasty. Nat. Commun. 8, 14115 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Margaryan, A. et al. Eight millennia of matrilineal genetic continuity in the south Caucasus. Curr. Biol. 27, 2023–2028 (2017).

    CAS  PubMed  Google Scholar 

  73. Degnan, J. H. & Rosenberg, N. A. Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol. Evol. 24, 332–340 (2009).

    PubMed  Google Scholar 

  74. Peletz, M. G. Kinship studies in late twentieth-century anthropology. Annu. Rev. Anthropol. 24, 343–372 (1995).

    Google Scholar 

  75. Mittnik, A. et al. Kinship-based social inequality in Bronze Age Europe. Science 366, 731–734 (2019). The genetic analysis of several Bronze Age settlements in southern Germany helped to understand the patrilineal social structure underlying genetic transformation in that period.

    CAS  PubMed  Google Scholar 

  76. Amorim, C. E. G. et al. Understanding 6th-century barbarian social organization and migration through paleogenomics. Nat. Commun. 9, 3547 (2018). This is another example of integration of ancient DNA and several other sources of evidence for past behaviour at an individual site.

    PubMed  PubMed Central  Google Scholar 

  77. Goldberg, A., Günther, T., Rosenberg, N. A. & Jakobsson, M. Ancient X chromosomes reveal contrasting sex bias in Neolithic and Bronze Age Eurasian migrations. Proc. Natl Acad. Sci. USA 114, 2657–2662 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Lazaridis, I. & Reich, D. Failure to replicate a genetic signal for sex bias in the steppe migration into central Europe. Proc. Natl Acad. Sci. USA 114, E3873–E3874 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Goldberg, A., Günther, T., Rosenberg, N. A. & Jakobsson, M. Reply to Lazaridis and Reich: robust model-based inference of male-biased admixture during Bronze Age migration from the Pontic-Caspian Steppe. Proc. Natl Acad. Sci. USA 114, E3875–E3877 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Olalde, I. et al. The genomic history of the Iberian Peninsula over the past 8000 years. Science 363, 1230–1234 (2019). This work is an example of the large amount of information that can be generated from a single temporal transect in a specific geographical region. The researchers uncovered a male-biased population turnover during the Bronze Age in the Iberian Peninsula.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Martiniano, R. et al. The population genomics of archaeological transition in west Iberia: investigation of ancient substructure using imputation and haplotype-based methods. PLoS Genet. 13, e1006852 (2017).

    PubMed  PubMed Central  Google Scholar 

  82. Saag, L. et al. Extensive farming in Estonia started through a sex-biased migration from the steppe. Curr. Biol. 27, 2185–2193 (2017).

    CAS  PubMed  Google Scholar 

  83. Sandoval-Velasco, M. et al. The genetic origins of Saint Helena’s liberated Africans. Preprint at bioRxiv https://doi.org/10.1101/787515 (2019).

    Article  Google Scholar 

  84. Ginzburg, C. Microhistory: two or three things that I know about it. Crit. Inq. 20, 10–35 (1993).

    Google Scholar 

  85. González-Fortes, G. et al. A western route of prehistoric human migration from Africa into the Iberian Peninsula. Proc. Biol. Sci. 286, 20182288 (2019).

    PubMed  PubMed Central  Google Scholar 

  86. Schuhmacher, T. X., Cardoso, J. L. & Banerjee, A. Sourcing African ivory in Chalcolithic Portugal. Antiquity 83, 983–997 (2009).

    Google Scholar 

  87. Margaryan, A., Lawson, D., Sikora, M. & Racimo, F. Population genomics of the Viking world. Preprint at bioRxiv https://doi.org/10.1101/703405 (2019).

    Article  Google Scholar 

  88. Harney, É. et al. Ancient DNA from the skeletons of Roopkund Lake reveals Mediterranean migrants in India. Nat. Commun. 10, 3670 (2019).

    PubMed  PubMed Central  Google Scholar 

  89. Loog, L. et al. Estimating mobility using sparse data: application to human genetic variation. Proc. Natl Acad. Sci. USA 114, 12213–12218 (2017). This report presents a statistical method that can estimate how much mobility existed among peoples in a given region during periods for which several ancient genomes are available.

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Knapp, A. B. & van Dommelen, P. Past practices: rethinking individuals and agents in archaeology. Camb. Archaeol. J. 18, 15–34 (2008).

    Google Scholar 

  91. Jensen, T. Z. T., Niemann, J., Iversen, K. H. & Fotakis, A. K. Stone Age ‘chewing gum’ yields 5,700 year-old human genome and oral microbiome. Nat. Commun. 10, 5520 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Kashuba, N. et al. Ancient DNA from mastics solidifies connection between material culture and genetics of Mesolithic hunter–gatherers in Scandinavia. Commun Biol. 2, 185 (2019). Jensen et al. (2019) and Kashuba et al. (2019). Two seminal studies demonstrating the potential of chewed birch pitch for recovery of ancient DNA.

    PubMed  PubMed Central  Google Scholar 

  93. Schablitsky, J. M. et al. Ancient DNA analysis of a nineteenth century tobacco pipe from a Maryland slave quarter. J. Archaeol. Sci. 105, 11–18 (2019).

    CAS  Google Scholar 

  94. Lalueza-Fox, C. Agreements and misunderstandings among three scientific fields. Curr. Anthropol. 54, S214–S220 (2013).

    Google Scholar 

  95. Furholt, M. Massive migrations? The impact of recent aDNA studies on our view of third millennium Europe. European. J. Archaeol. 21, 159–191 (2018).

    Google Scholar 

  96. Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. Patterson, N. et al. Ancient admixture in human history. Genetics 192, 1065–1093 (2012).

    PubMed  PubMed Central  Google Scholar 

  98. Lake, M. W. Trends in archaeological simulation. J. Archaeol. Method Theory 21, 258–287 (2014).

    Google Scholar 

  99. Bradburd, G. S. & Ralph, P. L. Spatial population genetics: it’s about time. Annu. Rev. Ecol. Evol. Syst. 50, 427–449 (2019).

    Google Scholar 

  100. Prendergast, M. E. & Sawchuk, E. Boots on the ground in Africa’s ancient DNA ‘revolution’: archaeological perspectives on ethics and best practices. Antiquity 92, 803–815 (2018).

    Google Scholar 

  101. Fox, K. & Hawks, J. Use ancient remains more wisely. Nature 572, 581–583 (2019).

    CAS  PubMed  Google Scholar 

  102. Cotterman, C. W. A Calculus for Statistico-genetics https://etd.ohiolink.edu/!etd.send_file?accession=osu1298297334&disposition=inline (Ohio State University, Columbus, 1940).

  103. Choi, Y., Wijsman, E. M. & Weir, B. S. Case-control association testing in the presence of unknown relationships. Genet. Epidemiol. 33, 668–678 (2009).

    PubMed  PubMed Central  Google Scholar 

  104. Thompson, E. A. The estimation of pairwise relationships. Ann. Hum. Genet. 39,173–188 (1975).

    CAS  PubMed  Google Scholar 

  105. Gusev, A. et al. Whole population, genome-wide mapping of hidden relatedness. Genome Res. 19, 318–326 (2008).

    PubMed  Google Scholar 

  106. Browning, B. L. & Browning, S. R. Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194, 459–471 (2013).

    PubMed  PubMed Central  Google Scholar 

  107. Manichaikul, A. et al. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867–2873 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Albrechtsen, A., Moltke, I. & Nielsen, R. Natural selection and the distribution of identity-by-descent in the human genome. Genetics 186, 295–308 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Korneliussen, T. S. & Moltke, I. NgsRelate: a software tool for estimating pairwise relatedness from next-generation sequencing data. Bioinformatics 31, 4009–4011 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. Martin, M. D., Jay, F., Castellano, S. & Slatkin, M. Determination of genetic relatedness from low-coverage human genome sequences using pedigree simulations. Mol. Ecol. 26, 4145–4157 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Theunert, C., Racimo, F. & Slatkin, M. Joint estimation of relatedness coefficients and allele frequencies from ancient samples. Genetics 206, 1025–1035 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Kuhn, J. M. M., Jakobsson, M. & Günther, T. Estimating genetic kin relationships in prehistoric populations. PLoS One 13, e0195491 (2018).

    Google Scholar 

  113. Waples, R. K., Albrechtsen, A. & Moltke, I. Allele frequency-free inference of close familial relationships from genotypes or low-depth sequencing data. Mol. Ecol. 28, 35–48 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Thompson, E. A. Identity by descent: variation in meiosis, across genomes, and in populations. Genetics 194, 301–326 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  115. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Narasimhan, V. et al. BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data. Bioinformatics 32, 1749–1751 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Su, S.-Y. et al. Detection of identity by descent using next-generation whole genome sequencing data. BMC Bioinformatics 13, 121 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  118. Bertrand, A. R., Kadri, N. K., Flori, L., Gautier, M. & Druet, T. RZooRoH: an R package to characterize individual genomic autozygosity and identify homozygous-by-descent segments. Methods Ecol. Evol. 10, 860–866 (2019).

    Google Scholar 

  119. Vieira, F. G., Albrechtsen, A. & Nielsen, R. Estimating IBD tracts from low coverage NGS data. Bioinformatics 32, 2096–2102 (2016).

    CAS  PubMed  Google Scholar 

  120. Prüfer, K. et al. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature 505, 43–49 (2014).

    PubMed  Google Scholar 

  121. Prüfer, K. et al. A high-coverage Neandertal genome from Vindija Cave in Croatia. Science 358, 655–658 (2017).

    PubMed  PubMed Central  Google Scholar 

  122. Prüfer, K. snpAD: an ancient DNA genotype caller. Bioinformatics 34, 4165–4171 (2018).

    PubMed  PubMed Central  Google Scholar 

  123. Sikora, M. et al. Ancient genomes show social and reproductive behavior of early Upper Paleolithic foragers. Science 358, 659–662 (2017). This is a seminal study inferring social and reproductive behaviour among early Late Palaeolithic foragers from ancient genomes.

    CAS  PubMed  Google Scholar 

  124. Palamara, P. F., Lencz, T., Darvasi, A. & Pe’er, I. Length distributions of identity by descent reveal fine-scale demographic history. Am. J. Hum. Genet. 91, 809–822 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. Linden, M. V. & Silva, F. Comparing and modeling the spread of early farming across Europe. Past. Glob. Change Mag. 26, 28–29 (2018).

    Google Scholar 

  126. Sikora, M. et al. The population history of northeastern Siberia since the Pleistocene. Nature 570, 182–188 (2019).

    CAS  PubMed  Google Scholar 

  127. Browning, B. L. & Browning, S. R. Detecting identity by descent and estimating genotype error rates in sequence data. Am. J. Hum. Genet. 93, 840–851 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  128. Wang, C.-C. et al. Ancient human genome-wide data from a 3000-year interval in the Caucasus corresponds with eco-geographic regions. Nat. Commun. 10, 590 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank F. Silva for providing raw data for reproduction of agricultural spread patterns featured in a previous article by him. F.R. was funded by a Villum Fonden Young Investigator award (project no. 00025300). H.S. was supported by the Humanities in the European Research Area (HERA) Joint Research Programme “Uses of the Past” (CitiGen) and the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 649307. M.V.L. was supported by the European Research Council, funded under the European Union’s Seventh Framework Programme (FP/20072013; European Research Council grant agreement no. 313716). C.L.-F. was supported by a grant from Obra Social “La Caixa” (GRC2017-SGR880, Generalitat de Catalunya) and a grant from FEDER-MCIU-AEI (PGC2018-095931-B-100) of Spain.

Author information

Authors and Affiliations

Authors

Contributions

F.R., M.S., M.V.L. and H.S. researched the literature. All authors provided substantial contributions to discussions of the content, wrote the article, and reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Fernando Racimo or Carles Lalueza-Fox.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Genetics thanks G. H. Perry, W. Haak and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

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

Supplementary information

Glossary

Population admixture

The introduction of genetic lineages from one population into another population that is genetically differentiated from it, because of interbreeding between them at some point in the past.

Eurasian Steppe

Large region of Eurasia extending from eastern Europe through Russia to Mongolia, which served as a major transit and connection route for many cultures throughout history and prehistory; characterized by temperate grasslands, shrub lands and savannahs.

Cultural diffusion

The spread of technologies or cultures from one region to another via the exchange of ideas between populations, with limited associated movements of people. By contrast, demic diffusion is the spread of technologies or cultures via movement of people, often prompted by population growth and expansion.

Megalithic

Pertaining to large stone structures, tombs or monuments. In Europe, the practice of megalith construction took off mainly in the Neolithic period, reached an apogee during the Chalcolithic period and continued into the Bronze Age.

Patrilineal

A term to describe a kinship system in which a person’s social status, family membership and/or property rights are determined through that person’s paternal lineage. By contrast, in a matrilineal system, these factors are determined through the maternal lineage.

Exogamy

The cultural practice by which individuals tend to marry outside their immediate kin group.

Identical by descent

(IBD). Two segments from two different genomes are IBD if they were both inherited from a recent ancestor shared between the two genomes.

Homozygous by descent

(HBD). Genomic segments shared identical by descent within the same individual, resulting in continuous stretches of homozygous genotypes termed ‘runs of homozygosity’.

Endogamy

The cultural practice by which individuals tend to marry within their own kin group or social group.

Uniparentally inherited markers

Sequences of DNA that are — barring rare exceptions — inherited from only one or another of a person’s parents. Examples include the mitochondrial DNA genome (transmitted from the mother alone) and the Y chromosome genome (transmitted from fathers to sons).

Agent-based models

Computational models designed for simulating and studying the behaviour of multiple autonomous agents that may interact with each other so as to study their collective effects on a system.

Isotope analysis

The study of the concentrations of different varieties of a chemical element — such as carbon, nitrogen or strontium — that have different numbers of neutrons in biological samples. They can indicate the relative abundance of vegetation types or dietary items or identify non-local individuals.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Racimo, F., Sikora, M., Vander Linden, M. et al. Beyond broad strokes: sociocultural insights from the study of ancient genomes. Nat Rev Genet 21, 355–366 (2020). https://doi.org/10.1038/s41576-020-0218-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41576-020-0218-z

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing