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The genetic history of France

A Correction to this article was published on 11 March 2020

This article has been updated


The study of the genetic structure of different countries within Europe has provided significant insights into their demographic history and population structure. Although France occupies a particular location at the western part of Europe and at the crossroads of migration routes, few population genetic studies have been conducted so far with genome-wide data. In this study, we analyzed SNP-chip genetic data from 2184 individuals born in France who were enrolled in two independent population cohorts. Using FineSTRUCTURE, six different genetic clusters of individuals were found that were very consistent between the two cohorts. These clusters correspond closely to geographic, historical, and linguistic divisions of France, and contain different proportions of ancestry from Stone and Bronze Age populations. By modeling the relationship between genetics and geography using EEMS, we were able to detect gene flow barriers that are similar across the two cohorts and correspond to major rivers and mountain ranges. Estimations of effective population sizes also revealed very similar patterns in both cohorts with a rapid increase of effective population sizes over the last 150 generations similar to other European countries. A marked bottleneck is also consistently seen in the two datasets starting in the 14th century when the Black Death raged in Europe. In conclusion, by performing the first exhaustive study of the genetic structure of France, we fill a gap in genetic studies of Europe that will be useful to medical geneticists, historians, and archeologists.

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Fig. 1: Clustering of the French individuals into six or seven clusters as inferred by FineSTRUCTURE analysis.
Fig. 2: Estimated effective migration surfaces of France obtained from EEMS.
Fig. 3: Ancestry profiles from the three neighboring European populations inferred by SOURCEFIND.
Fig. 4: Relationship between French clusters and three ancient populations: western hunter-gatherers (WHG), early Neolithic farmers (EF), and Steppe pastoralists (SP).

Change history

  • 05 March 2020

    An amendment to this article has been published and can be accessed via a link at the top of the article.

  • 11 March 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.


  1. 1.

    Caesar CJ. De bello Gallico Commentarius Primus. p. 58–60 BCE.

  2. 2.

    Lazaridis I. The evolutionary history of human populations in Europe. Curr Opin Genet Dev. 2018;53:21–7.

    CAS  PubMed  Google Scholar 

  3. 3.

    Lazaridis I, Patterson N, Mittnik A, Renaud G, Mallick S, Kirsanow K, et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature. 2014;513:409–13.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Cornette J. Collection Histoire de France. Paris, France: Belin; 2009–12.

  5. 5.

    Cornette J. Atlas Histoire de France (481–2005). Paris, France: Belin; 2016.

  6. 6.

    Marchini J, Cardon LR, Phillips MS, Donnelly P. The effects of human population structure on large genetic association studies. Nat Genet. 2004;36:512–7.

    CAS  PubMed  Google Scholar 

  7. 7.

    Rosenberg NA, Pritchard JK, Weber JL, Cann HM, Kidd KK, Zhivotovsky LA, et al. Genetic structure of human populations. Science. 2002;298:2381–5.

    CAS  PubMed  Google Scholar 

  8. 8.

    Jorde LB, Watkins WS, Bamshad MJ, Dixon ME, Ricker CE, Seielstad MT, et al. The distribution of human genetic diversity: a comparison of mitochondrial, autosomal, and Y-chromosome data. Am J Hum Genet. 2000;66:979–88.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    David A, Peter D. The International HapMap Consortium. A haplotype map of the human genome. Nature 2005;437:1299–320.

  10. 10.

    Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, Auton A, et al. Genes mirror geography within Europe. Nature. 2008;456:98–101.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Heath SC, Gut IG, Brennan P, McKay JD, Bencko V, Fabianova E, et al. Investigation of the fine structure of European populations with applications to disease association studies. Eur J Hum Genet. 2008;16:1413–29.

    CAS  PubMed  Google Scholar 

  12. 12.

    Humphreys K, Grankvist A, Leu M, Hall P, Liu J, Ripatti S, et al. The genetic structure of the Swedish population. PLoS ONE. 2011;6:e22547.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Abdellaoui A, Hottenga JJ, de Knijff P, Nivard MG, Xiao X, Scheet P, et al. Population structure, migration, and diversifying selection in the Netherlands. Eur J Hum Genet. 2013;21:1277–85.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Gilbert E, O’Reilly S, Merrigan M, McGettigan D, Molloy AM, Brody LC, et al. Author correction: the Irish DNA atlas: revealing fine-scale population structure and history within Ireland. Sci Rep. 2018;8:7208.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Leslie S, Winney B, Hellenthal G, Davison D, Boumertit A, Day T, et al. The fine-scale genetic structure of the British population. Nature. 2015;519:309–14.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Bycroft C, Fernandez-Rozadilla C, Ruiz-Ponte C, Quintela I, Carracedo A, Donnelly P, et al. Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula. Nat Commun. 2019;10:551.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Karakachoff M, Duforet-Frebourg N, Simonet F, Le Scouarnec S, Pellen N, Lecointe S, et al. Fine-scale human genetic structure in Western France. Eur J Hum Genet. 2015;23:831–6.

    CAS  PubMed  Google Scholar 

  18. 18.

    Hercberg S, Galan P, Preziosi P, Bertrais S, Mennen L, Malvy D, et al. The SU.VI.MAX Study: a randomized, placebo-controlled trial of the health effects of antioxidant vitamins and minerals. Arch Intern Med. 2004;164:2335–42.

    CAS  PubMed  Google Scholar 

  19. 19.

    3C Study Group. Vascular factors and risk of dementia: design of the Three-City Study and baseline characteristics of the study population. Neuroepidemiology 2003;22:316–25.

  20. 20.

    Lambert JC, Heath S, Even G, Campion D, Sleegers K, Hiltunen M, et al. Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nat Genet. 2009;41:1094–9.

    CAS  PubMed  Google Scholar 

  21. 21.

    Haworth S, Mitchell R, Corbin L, Wade KH, Dudding T, Budu-Aggrey A, et al. Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis. Nat Commun. 2019;10:333.

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Anderson CA, Pettersson FH, Clarke GM, Cardon LR, Morris AP, Zondervan KT. Data quality control in genetic case-control association studies. Nat Protoc. 2010;5:1564–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.

    CAS  Article  Google Scholar 

  26. 26.

    Lawson DJ, Hellenthal G, Myers S, Falush D. Inference of population structure using dense haplotype data. PLoS Genet. 2012;8:e1002453.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Delaneau O, Marchini J, Zagury JF. A linear complexity phasing method for thousands of genomes. Nat Methods. 2011;9:179–81.

    PubMed  Google Scholar 

  28. 28.

    Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, et al. A global reference for human genetic variation. Nature. 2015;526:68–74.

    PubMed  Google Scholar 

  29. 29.

    Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009;19:1655–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Petkova D, Novembre J, Stephens M. Visualizing spatial population structure with estimated effective migration surfaces. Nat Genet. 2016;48:94–100.

    CAS  PubMed  Google Scholar 

  31. 31.

    Browning SR, Browning BL. Accurate non-parametric estimation of recent effective population size from segments of identity by descent. Am J Hum Genet. 2015;97:404–18.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Browning BL, Browning SR. Detecting identity by descent and estimating genotype error rates in sequence data. Am J Hum Genet. 2013;93:840–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Price AL, Weale ME, Patterson N, Myers SR, Need AC, Shianna KV, et al. Long-range LD can confound genome scans in admixed populations. Am J Hum Genet. 2008;83:132–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, Ramachandran S, et al. Worldwide human relationships inferred from genome-wide patterns of variation. Science. 2008;319:1100–4.

    CAS  PubMed  Google Scholar 

  35. 35.

    Gazal S, Sahbatou M, Babron MC, Genin E, Leutenegger AL. High level of inbreeding in final phase of 1000 Genomes Project. Sci Rep. 2015;5:17453.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Chacon-Duque JC, Adhikari K, Fuentes-Guajardo M, Mendoza-Revilla J, Acuna-Alonzo V, Barquera R, et al. Latin Americans show wide-spread Converso ancestry and imprint of local Native ancestry on physical appearance. Nat Commun. 2018;9:5388.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Mathieson I, Lazaridis I, Rohland N, Mallick S, Patterson N, Roodenberg SA, et al. Genome-wide patterns of selection in 230 ancient Eurasians. Nature. 2015;528:499–503.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Mathieson I, Reich D. Differences in the rare variant spectrum among human populations. PLoS Genet. 2017;13:e1006581.

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Olalde I, Mallick S, Patterson N, Rohland N, Villalba-Mouco V, Silva M, et al. The genomic history of the Iberian Peninsula over the past 8000 years. Science. 2019;363:1230–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Mathieson I, Alpaslan-Roodenberg S, Posth C, Szecsenyi-Nagy A, Rohland N, Mallick S, et al. The genomic history of southeastern Europe. Nature. 2018;555:197–203.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Anthony DW. The Horse, the Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World. Princeton, USA: Princeton University Press; 2007.

  42. 42.

    Lazaridis I, Nadel D, Rollefson G, Merrett DC, Rohland N, Mallick S, et al. Genomic insights into the origin of farming in the ancient Near East. Nature. 2016;536:419–24.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Patterson N, Moorjani P, Luo Y, Mallick S, Rohland N, Zhan Y, et al. Ancient admixture in human history. Genetics. 2012;192:1065–93.

    PubMed  PubMed Central  Google Scholar 

  44. 44.

    Haak W, Lazaridis I, Patterson N, Rohland N, Mallick S, Llamas B, et al. Massive migration from the Steppe was a source for Indo-European languages in Europe. Nature. 2015;522:207–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Keinan A, Clark AG. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science. 2012;336:740–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Chiang CWK, Marcus JH, Sidore C, Biddanda A, Al-Asadi H, Zoledziewska M, et al. Genomic history of the Sardinian population. Nat Genet. 2018;50:1426–34.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Wartburg W von. Les origines des peuples romans. Paris, France: Presses Universitaires de France; 1941.

  48. 48.

    Chaurand J. Nouvelle histoire de la langue française. Paris, France: Seuil; 2012.

  49. 49.

    Leprohon R. Vie et mort des Bretons sous Louis XIV. Brasparts, France: Beltan; 1984.

  50. 50.

    Lasserre F. Strabon, Geographie. Paris, France: Belles Lettres; 1974.

  51. 51.

    Fleuriot L. Les Origines de la Bretagne: L'émigration. Lausanne, Switzerland: Payot; 1999.

  52. 52.

    Lévy ML. La transition démographique en Occident. Institut National des Études Démographiques 1979.

  53. 53.

    Cornette J. Absolutisme et Lumières 1652-783. Paris, France: Hachette; 2008.

  54. 54.

    Dupâquier J. Collection Histoire de la population française. Presses Universitaires de France: Paris, France; 1995.

  55. 55.

    Biget JL, Bove B, Cornette J. Le temps de la Guerre de Cent ans (1328-453). Belin: Paris, France; 2009.

  56. 56.

    Lawson DJ, van Dorp L, Falush D. A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots. Nat Commun. 2018;9:3258.

    PubMed  PubMed Central  Google Scholar 

  57. 57.

    Persyn E, Redon R, Bellanger L, Dina C. The impact of a fine-scale population stratification on rare variant association test results. PLoS ONE. 2018;13:e0207677.

    PubMed  PubMed Central  Google Scholar 

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Part of this work was supported by the French National Research Agency (FROGH: ANR-16-CE12–0033) and the European Union via the Marie Skłodowska-Curie actions (PRESTIGE-2017–4–0018). We are most grateful to the Bioinformatics Core Facility of Nantes (BiRD, Biogenouest) for its technical support.

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Correspondence to Aude Saint Pierre or Christian Dina.

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On behalf of the 3C study: Philippe Amouyel, Jean-François Dartigues, Christophe Tzourio

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Saint Pierre, A., Giemza, J., Alves, I. et al. The genetic history of France. Eur J Hum Genet 28, 853–865 (2020).

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