Global population structure and migration patterns suggest significant population differentiation among isolates of Pyrenophora tritici-repentis

Abstract The analysis of multiple population structures (biodemographic, genetic and socio-cultural) and their inter-relations contribute to a deeper understanding of population structure and population dynamics. Genetically, the population structure corresponds to the deviation of random mating conditioned by a limited number of ancestors, by restricted migration in the social or geographic space, or by preference for certain consanguineous unions. Through the isonymic method, surname frequency and distribution across the population can supply quantitative information on the structure of a human population, as they constitute universal socio-cultural variables. Using documentary sources to undertake the Doctrine of Belén’s (Altos de Arica, Chile) historical demography reconstruction between 1763 and 1820, this study identified an indigenous population with stable patronymics. The availability of complete marriage, baptism and death records, low rates of migration and the significant percentage of individuals registered and constantly present in this population favoured the application of the isonymic method. The aim of this work was to use given names and surnames recorded in these documentary sources to reconstruct the population structure and migration pattern of the Doctrine of Belén between 1750 and 1813 through the isonymic method. The results of the study were consistent with the ethno-historical data of this ethnic space, where social cohesion was, in multiple ways, related to the regulation of daily life in colonial Andean societies.

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Spatial and space-time correlations in systems of subpopulations with genetic drift and migration.

Genetics ◽

10.1093/genetics/133.3.711 ◽

1993 ◽

Vol 133 (3) ◽

pp. 711-727

Author(s):

B K Epperson

Keyword(s):

Population Genetics ◽

Time Correlation ◽

Space Time ◽

Spatial Correlations ◽

Gene Frequencies ◽

Migration Patterns ◽

Migration Rates ◽

Space And Time ◽

Time Correlations ◽

And Migration

Abstract The geographic distribution of genetic variation is an important theoretical and experimental component of population genetics. Previous characterizations of genetic structure of populations have used measures of spatial variance and spatial correlations. Yet a full understanding of the causes and consequences of spatial structure requires complete characterization of the underlying space-time system. This paper examines important interactions between processes and spatial structure in systems of subpopulations with migration and drift, by analyzing correlations of gene frequencies over space and time. We develop methods for studying important features of the complete set of space-time correlations of gene frequencies for the first time in population genetics. These methods also provide a new alternative for studying the purely spatial correlations and the variance, for models with general spatial dimensionalities and migration patterns. These results are obtained by employing theorems, previously unused in population genetics, for space-time autoregressive (STAR) stochastic spatial time series. We include results on systems with subpopulation interactions that have time delay lags (temporal orders) greater than one. We use the space-time correlation structure to develop novel estimators for migration rates that are based on space-time data (samples collected over space and time) rather than on purely spatial data, for real systems. We examine the space-time and spatial correlations for some specific stepping stone migration models. One focus is on the effects of anisotropic migration rates. Partial space-time correlation coefficients can be used for identifying migration patterns. Using STAR models, the spatial, space-time, and partial space-time correlations together provide a framework with an unprecedented level of detail for characterizing, predicting and contrasting space-time theoretical distributions of gene frequencies, and for identifying features such as the pattern of migration and estimating migration rates in experimental studies of genetic variation over space and time.

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