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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1988 Mar;85(5):1722–1726. doi: 10.1073/pnas.85.5.1722

Genetic, geographic, and linguistic distances in Europe.

R R Sokal 1
PMCID: PMC279847  PMID: 3422760

Abstract

Genetic and taxonomic distances were computed for 3466 samples of human populations in Europe based on 97 allele frequencies and 10 cranial variables. Since the actual samples employed differed among the genetic systems studied, the genetic distances were computed separately for each system, as were matrices of geographic distances and of linguistic distances based on membership in the same language family or phylum. Significant matrix correlations between genetics and geography were found for the majority of systems; somewhat less frequent are significant correlations between genetics and language. The effects of the two factors can be separated by means of partial matrix correlations. These show significant values for both genetics and geography, language kept constant, and genetics and language, geography kept constant, with a tendency for the former to be higher. These findings demonstrate that speakers of different language families in Europe differ genetically and that this difference remains even after geographic differentiation is allowed for. The greater effect of geography than of language may be due to the several factors that bring about spatial differentiation in human populations.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Dow M. M., Cheverud J. M. Comparison of distance matrices in studies of population structure and genetic microdifferentiation: quadratic assignment. Am J Phys Anthropol. 1985 Nov;68(3):367–373. doi: 10.1002/ajpa.1330680307. [DOI] [PubMed] [Google Scholar]
  2. Dow M. M., Cheverud J. M., Friedlaender J. S. Partial correlation of distance matrices in studies of population structure. Am J Phys Anthropol. 1987 Mar;72(3):343–352. doi: 10.1002/ajpa.1330720307. [DOI] [PubMed] [Google Scholar]
  3. Kimura M, Weiss G H. The Stepping Stone Model of Population Structure and the Decrease of Genetic Correlation with Distance. Genetics. 1964 Apr;49(4):561–576. doi: 10.1093/genetics/49.4.561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Mantel N. The detection of disease clustering and a generalized regression approach. Cancer Res. 1967 Feb;27(2):209–220. [PubMed] [Google Scholar]
  5. Sokal R. R., Smouse P. E., Neel J. V. The genetic structure of a tribal population, the Yanomama Indians. XV. Patterns inferred by autocorrelation analysis. Genetics. 1986 Sep;114(1):259–287. doi: 10.1093/genetics/114.1.259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Sokal R. R., Uytterschaut H. Cranial variation in European populations: a spatial autocorrelation study at three time periods. Am J Phys Anthropol. 1987 Sep;74(1):21–38. doi: 10.1002/ajpa.1330740103. [DOI] [PubMed] [Google Scholar]
  7. Sokal R. R., Uytterschaut H., Rösing F. W., Schwidetzky I. A classification of European skulls from three time periods. Am J Phys Anthropol. 1987 Sep;74(1):1–20. doi: 10.1002/ajpa.1330740102. [DOI] [PubMed] [Google Scholar]
  8. Sokal R. R., Wartenberg D. E. A Test of Spatial Autocorrelation Analysis Using an Isolation-by-Distance Model. Genetics. 1983 Sep;105(1):219–237. doi: 10.1093/genetics/105.1.219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Sokal R. R., Winkler E. M. Spatial variation among Kenyan tribes and subtribes. Hum Biol. 1987 Feb;59(1):147–164. [PubMed] [Google Scholar]

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