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

The mean, variance and limiting distribution of two statistics sensitive to phylogenetic tree balance

For two decades, the Colless index has been the most frequently used statistic for assessing the balance of phylogenetic trees. In this article, this statistic is studied under the Yule and uniform model of phylogenetic trees. The main tool of analysis is a coupling argument with another well-known index called the Sackin statistic. Asymptotics for the mean, variance and covariance of these two statistics are obtained, as well as their limiting joint distribution for large phylogenies. Under the Yule model, the limiting distribution arises as a solution of a functional fixed point equation. Under the uniform model, the limiting distribution is the Airy distribution. The cornerstone of this study is the fact that the probabilistic models for phylogenetic trees are strongly related to the random permutation and the Catalan models for binary search trees.Comment: Published at http://dx.doi.org/10.1214/105051606000000547 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Predictions of Native American Population Structure Using Linguistic Covariates in a Hidden Regression Framework

International audienceBACKGROUND: The mainland of the Americas is home to a remarkable diversity of languages, and the relationships between genes and languages have attracted considerable attention in the past. Here we investigate to which extent geography and languages can predict the genetic structure of Native American populations. METHODOLOGY/PRINCIPAL FINDINGS: Our approach is based on a Bayesian latent cluster regression model in which cluster membership is explained by geographic and linguistic covariates. After correcting for geographic effects, we find that the inclusion of linguistic information improves the prediction of individual membership to genetic clusters. We further compare the predictive power of Greenberg's and The Ethnologue classifications of Amerindian languages. We report that The Ethnologue classification provides a better genetic proxy than Greenberg's classification at the stock and at the group levels. Although high predictive values can be achieved from The Ethnologue classification, we nevertheless emphasize that Choco, Chibchan and Tupi linguistic families do not exhibit a univocal correspondence with genetic clusters. CONCLUSIONS/SIGNIFICANCE: The Bayesian latent class regression model described here is efficient at predicting population genetic structure using geographic and linguistic information in Native American populations

End states, ladder compounds, and domain wall fermions

A magnetic field applied to a cross linked ladder compound can generate isolated electronic states bound to the ends of the chain. After exploring the interference phenomena responsible, I discuss a connection to the domain wall approach to chiral fermions in lattice gauge theory. The robust nature of the states under small variations of the bond strengths is tied to chiral symmetry and the multiplicative renormalization of fermion masses.Comment: 10 pages, 4 figures; final version for Phys. Rev. Let

POPS: A Software for Prediction of Population Genetic Structure Using Latent Regression Models

The software POPS performs inference of population genetic structure using multilocus genotypic data. Based on a hierarchical Bayesian framework for latent regression models, POPS implements algorithms that improve estimation of individual admixture proportions and cluster membership probabilities by using geographic and environmental information. In addition, POPS defines ancestry distribution models allowing its users to forecast admixture proportion and cluster membership geographic variation under changing environmental conditions. We illustrate a typical use of POPS using data for an alpine plant species, for which POPS predicts changes in spatial population structure assuming a particular scenario of climate change

Matrilineal Fertility Inheritance Detected in Hunter–Gatherer Populations Using the Imbalance of Gene Genealogies

Fertility inheritance, a phenomenon in which an individual's number of offspring is positively correlated with his or her number of siblings, is a cultural process that can have a strong impact on genetic diversity. Until now, fertility inheritance has been detected primarily using genealogical databases. In this study, we develop a new method to infer fertility inheritance from genetic data in human populations. The method is based on the reconstruction of the gene genealogy of a sample of sequences from a given population and on the computation of the degree of imbalance in this genealogy. We show indeed that this level of imbalance increases with the level of fertility inheritance, and that other phenomena such as hidden population structure are unlikely to generate a signal of imbalance in the genealogy that would be confounded with fertility inheritance. By applying our method to mtDNA samples from 37 human populations, we show that matrilineal fertility inheritance is more frequent in hunter–gatherer populations than in food-producer populations. One possible explanation for this result is that in hunter–gatherer populations, individuals belonging to large kin networks may benefit from stronger social support and may be more likely to have a large number of offspring

Approximate Bayesian Computation: a nonparametric perspective

Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter theta. The posterior distribution is then approximated by an estimator of the conditional density g(theta|s_obs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better performance when there is a nearly homoscedastic relationship between the summary statistics and the parameter of interest. To make this relationship as homoscedastic as possible, we propose to use transformations of the summary statistics. In different examples borrowed from the population genetics and epidemiological literature, we show the potential of the methods with adjustment and of the transformations of the summary statistics. Supplemental materials containing the details of the proofs are available online

On theories of enhanced CP violation in B_s,d meson mixing

The DO collaboration has measured a deviation from the standard model (SM) prediction in the like sign dimuon asymmetry in semileptonic b decay with a significance of 3.2 sigma. We discuss how minimal flavour violating (MFV) models with multiple scalar representations can lead to this deviation through tree level exchanges of new MFV scalars. We review how the two scalar doublet model can accommodate this result and discuss some of its phenomenology. Limits on electric dipole moments suggest that in this model the coupling of the charged scalar to the right handed u-type quarks is suppressed while its coupling to the d-type right handed quarks must be enhanced. We construct an extension of the MFV two scalar doublet model where this occurs naturally.Comment: 10 pages, 7 figures, v3 final JHEP versio

Continuous selections of multivalued mappings

This survey covers in our opinion the most important results in the theory of continuous selections of multivalued mappings (approximately) from 2002 through 2012. It extends and continues our previous such survey which appeared in Recent Progress in General Topology, II, which was published in 2002. In comparison, our present survey considers more restricted and specific areas of mathematics. Note that we do not consider the theory of selectors (i.e. continuous choices of elements from subsets of topological spaces) since this topics is covered by another survey in this volume