Measurement of genetic structure within populations using Moran's spatial autocorrelation statistics.

Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, can be analyzed in detail by using spatial autocorrelation statistics. This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesis tests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

Geographical structuring in the mtDNA of Italians.

Geographical patterns of mtDNA variation were studied in 12 Italian samples (1072 individuals) by two different spatial autocorrelation methods. Separate analyses of the frequencies of 12 restriction morphs show North-South clines, differences between Sardinia and the mainland populations, and the effects of isolation by distance. A recently developed autocorrelation statistic summarizing molecular similarity at all sites (AIDA; autocorrelation index for DNA analysis) confirms the presence of a clinical pattern; differences between random pairs of haplotypes tend to increase with their geographical distance. The partition of gene diversity, however, reveals that most variability occurs within populations, whereas differences between populations are minor (GST = 0.057). When the data from the 12 samples are pooled, two descriptors of genetic variability (number of polymorphic sites and average sequence difference between pairs of individuals) do not behave as expected under neutrality. The presence of clinal patterns, Tajima's tests, and a simulation experiment agree in suggesting that population sizes increased rapidly in Italy and Sicily but not necessarily so in Sardinia. The distribution of pairwise sequence differences in the Italian peninsula (excluding Sardinia) permits a tentative location of the demographic increase between 8000 and 20,500 years ago. These dates are consistent with archaeological estimates of two distinct expansion processes, occurring, respectively, in the Neolithic and after the last glacial maximum in the Paleolithic. Conversely, there is no genetic evidence that such processes have had a major impact on the Sardinian population.

Genetics and the origin of European languages.

A new set of European genetic data has been analyzed to dissect independent patterns of geographic variation. The most important cause of European genetic variation has been confirmed to correspond to the migration of Neolithic farmers from the area of origin of agriculture in the Middle East. The next most important component of genetic variation is apparently associated with a north-south gradient possibly due to adaptation to cold climates but also to the differentiation of the Uralic and the Indo-European language-speaking people; however, the relevant correlations are not significantly different from zero after elimination of the spatial autocorrelation. The third component is highly correlated with the infiltration of the Yamna ("Kurgan") people, nomadic pastoralists who domesticated the horse and who have been claimed to have spread Indo-European languages to Europe; this association, which is statistically significant even when taking spatial autocorrelations into account, does not completely exclude the hypothesis of Indo-European as the language of Neolithic farmers. It is possible that both expansions were responsible for the spread of different subfamilies of Indo-European languages, but our genetic data cannot resolve their relative importance.