Non-stationary patterns of isolation-by-distance: inferring measures of local genetic differentiation with Bayesian kriging

Patterns of isolation-by-distance arise when population differentiation increases with increasing geographic distances. Patterns of isolation-by-distance are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate non-stationary patterns of isolation-by-distance where the rate at which genetic differentiation accumulates varies across space. To characterize non-stationary patterns of isolation-by-distance, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of FST between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with 2 data sets: genome-wide SNP data for human Swedish populations and AFLP markers for alpine plant species. The software LocalDiff implementing the method is available at http://membres-timc.imag.fr/Michael.Blum/LocalDiff.htmlComment: In press, Evolution 201

Disentangling the effects of geographic and ecological isolation on genetic differentiation

Populations can be genetically isolated both by geographic distance and by differences in their ecology or environment that decrease the rate of successful migration. Empirical studies often seek to investigate the relationship between genetic differentiation and some ecological variable(s) while accounting for geographic distance, but common approaches to this problem (such as the partial Mantel test) have a number of drawbacks. In this article, we present a Bayesian method that enables users to quantify the relative contributions of geographic distance and ecological distance to genetic differentiation between sampled populations or individuals. We model the allele frequencies in a set of populations at a set of unlinked loci as spatially correlated Gaussian processes, in which the covariance structure is a decreasing function of both geographic and ecological distance. Parameters of the model are estimated using a Markov chain Monte Carlo algorithm. We call this method Bayesian Estimation of Differentiation in Alleles by Spatial Structure and Local Ecology (BEDASSLE), and have implemented it in a user-friendly format in the statistical platform R. We demonstrate its utility with a simulation study and empirical applications to human and teosinte datasets

War and Relatedness

We develop a theory of interstate conflict in which the degree of genealogical relatedness between populations has a positive effect on their conflict propensities because more closely related populations, on average, tend to interact more and develop more disputes over sets of common issues. We examine the empirical relationship between the occurrence of interstate conflicts and the degree of relatedness between countries, showing that populations that are genetically closer are more prone to go to war with each other, even after controlling for a wide set of measures of geographic distance and other factors that affect conflict, including measures of trade and democracy.conflict, genetic distance, common issues, rival issues

Genetic and phenotypic divergence in an island bird: isolation by distance, by colonization or by adaptation?

Discerning the relative roles of adaptive and nonadaptive processes in generating differences among populations and species, as well as how these processes interact, is a fundamental aim in biology. Both genetic and phenotypic divergence across populations can be the product of limited dispersal and gradual genetic drift across populations (isolation by distance), of colonization history and founder effects (isolation by colonization) or of adaptation to different environments preventing migration between populations (isolation by adaptation). Here, we attempt to differentiate between these processes using island populations of Berthelot's pipit (Anthus berthelotii), a passerine bird endemic to three Atlantic archipelagos. Using microsatellite markers and approximate Bayesian computation, we reveal that the northward colonization of this species ca. 8500years ago resulted in genetic bottlenecks in the colonized archipelagos. We then show that high levels of genetic structure exist across archipelagos and that these are consistent with a pattern of isolation by colonization, but not with isolation by distance or adaptation. Finally, we show that substantial morphological divergence also exists and that this is strongly concordant with patterns of genetic structure and bottleneck history, but not with environmental differences or geographic distance. Overall, our data suggest that founder effects are responsible for both genetic and phenotypic changes across archipelagos. Our findings provide a rare example of how founder effects can persist over evolutionary timescales and suggest that they may play an important role in the early stages of speciation

Sex-Biased Gene Flow Among Elk in the Greater Yellowstone Ecosystem

We quantified patterns of population genetic structure to help understand gene flow among elk populations across the Greater Yellowstone Ecosystem. We sequenced 596 base pairs of the mitochondrial control region of 380 elk from eight populations. Analysis revealed high mitochondrial DNA variation within populations, averaging 13.0 haplotypes with high mean gene diversity (0.85). The genetic differentiation among populations for mitochondrial DNA was relatively high (FST = 0.161; P = 0.001) compared to genetic differentiation for nuclear microsatellite data (FST = 0.002; P = 0.332), which suggested relatively low female gene flow among populations. The estimated ratio of male to female gene flow (mm/mf = 46) was among the highest we have seen reported for large mammals. Genetic distance (for mitochondrial DNA pairwise FST) was not significantly correlated with geographic (Euclidean) distance between populations (Mantel’s r = 0.274, P = 0.168). Large mitochondrial DNA genetic distances (e.g., FST . 0.2) between some of the geographically closest populations (,65 km) suggested behavioral factors and/or landscape features might shape female gene flow patterns. Given the strong sex-biased gene flow, future research and conservation efforts should consider the sexes separately when modeling corridors of gene flow or predicting spread of maternally transmitted diseases. The growing availability of genetic data to compare male vs. female gene flow provides many exciting opportunities to explore the magnitude, causes, and implications of sex-biased gene flow likely to occur in many species

War and relatedness

We examine the empirical relationship between the occurrence of inter-state conflicts and the degree of relatedness between countries, measured by genetic distance. We find that populations that are genetically closer are more prone to go to war with each other, even after controlling for numerous measures of geographic distance and other factors that affect conflict, including measures of trade and democracy. These findings are consistent with a framework in which conflict over rival and excludable goods (such as territory and resources) is more likely among populations that share more similar preferences, and inherit such preferences with variation from their ancestors

War and Relatedness

We develop a theory of interstate conflict in which the degree of genealogical relatedness between populations has a positive effect on their conflict propensities because more closely related populations, on average, tend to interact more and develop more disputes over sets of common issues. We examine the empirical relationship between the occurrence of interstate conflicts and the degree of relatedness between countries, showing that populations that are genetically closer are more than prone to go to war with each other, even after controlling for a wide set of measures of geographic distance and other factors that affect conflict, including measure of trade and democracy.

Classification of Chenopodium Genus Populations and Species Based on Continuous and Categorical Variables

2000 Mathematics Subject Classification: 62P10, 62H30The estimation of statistical distance between populations arises in many multivariate analysis techniques. Whereas distance measures for continuous data are well developed, those for mixed discrete and continuous data are less so because of the lack of a standard model for such data. Such mixture of variables arise frequently in the field of medicine, biometry, psychology, econometrics and only comparatively few models have been developed for evaluating distance between populations. The subject of our study were data in the field of botany. The aim of the presented investigation was to apply methods for analysis of dissimilarity between 44 populations of 13 species of Ghenopodium genus,presented by 15 variables - 10 continuous and 5 categorical. The previously developed by another authors distance measures between populations presented by mixed attributes turned out not appropriate for the available data of Chenopodium genus. F or that reason a specific distance measures were applied. The matrices with distances between populations and species were used as input for Hierarchical Cluster Analysis to explore the taxonomic structure of the Chenopodium genus