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

Directional genetic differentiation and asymmetric migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. Since information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this paper. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.Comment: 25 pages, 8 (+3) figures, 1 tabl

Wildlife friendly agriculture: which factors do really matter? A genetic study on field vole

The distribution of genetic differentiation and the directions of gene flow were determined mainly by landscape factors: thus the expectation that organic fields act as genetic reservoir was not met. The fact that agricultural area presented more sub-populations than the undisturbed one, together with the importance of connectivity and habitat size in shaping gene flow and genetic differentiation, shows that switching to organic farming might not be enough to ensure the conservation of species in the agricultural environment. These results emphasise the need to include landscape structure in management policies

Demographic history and genetic differentiation in apes

SummaryComparisons of genetic variation between humans and great apes are hampered by the fact that we still know little about the demographics and evolutionary history of the latter species [1–4]. In addition, characterizing ape genetic variation is important because they are threatened with extinction, and knowledge about genetic differentiation among groups may guide conservation efforts [5]. We sequenced multiple intergenic autosomal regions totaling 22,400 base pairs (bp) in ten individuals each from western, central, and eastern chimpanzee groups and in nine bonobos, and 16,000 bp in ten Bornean and six Sumatran orangutans. These regions are analyzed together with homologous information from three human populations and gorillas. We find that whereas orangutans have the highest diversity, western chimpanzees have the lowest, and that the demographic histories of most groups differ drastically. Special attention should therefore be paid to sampling strategies and the statistics chosen when comparing levels of variation within and among groups. Finally, we find that the extent of genetic differentiation among “subspecies” of chimpanzees and orangutans is comparable to that seen among human populations, calling the validity of the “subspecies” concept in apes into question

Genomic variation and population structure detected by single nucleotide polymorphism arrays in Corriedale, Merino and Creole sheep.

THE AIM OF THIS STUDY WAS TO INVESTIGATE THE GENETIC DIVERSITY WITHIN AND AMONG THREE BREEDS OF SHEEP: Corriedale, Merino and Creole. Sheep from the three breeds (Merino n = 110, Corriedale n = 108 and Creole n = 10) were genotyped using the Illumina Ovine SNP50 beadchip(®). Genetic diversity was evaluated by comparing the minor allele frequency (MAF) among breeds. Population structure and genetic differentiation were assessed using STRUCTURE software, principal component analysis (PCA) and fixation index (FST). Fixed markers (MAF = 0) that were different among breeds were identified as specific breed markers. Using a subset of 18,181 single nucleotide polymorphisms (SNPs), PCA and STUCTURE analysis were able to explain population stratification within breeds. Merino and Corriedale divergent lines showed high levels of polymorphism (89.4% and 86% of polymorphic SNPs, respectively) and moderate genetic differentiation (FST = 0.08) between them. In contrast, Creole had only 69% polymorphic SNPs and showed greater genetic differentiation from the other two breeds (FST = 0.17 for both breeds). Hence, a subset of molecular markers present in the OvineSNP50 is informative enough for breed assignment and population structure analysis of commercial and Creole breeds

Estimates of genetic differentiation measured by FST do not necessarily require large sample sizes when using many SNP markers

Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. FST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer FST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating FST. We tested the behavior of three different estimators that infer FST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k.1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing

Assessing Landscape Effects on Genetics and Dispersal of the Rocky Mountain Apollo Butterfly Parnassius smintheus using a Resistance Mapping Approach

Landscape variables that best explain genetic differentiation may not also best explain dispersal patterns, but many studies use genetic differentiation as a proxy for dispersal. I tested the effects of landscape on both genetic differentiation and dispersal in parallel, to explore whether landscape effects on genetic differentiation between populations and landscape effects on dispersal would be comparable in such contexts. I used circuit theory (Circuitscape) and least cost transect analysis to evaluate the effects of landscape on both movement and genetic differentiation of the butterfly, Parnassius smintheus, in the Jumpingpound Ridge study system. Circuit theory and least cost transect analyses did not identify the same best predictors to explain genetic differentiation and dispersal data. Circuit theory produced more accurate results with higher precision. Genetic differentiation should not be used as a sole proxy for dispersal in studies of landscape effects, but should be supplemented by more direct measures of dispersal

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

Population Differentiation In Daphnia Alters Community Assembly In Experimental Ponds

Most studies of community assembly ignore how genetic differentiation within species affects their colonization and extinction. However, genetic differentiation in ecologically relevant traits may be substantial enough to alter the colonization and extinction processes that drive community assembly. We measured significant molecular genetic and quantitative trait differentiation among three Daphnia pulex X pulicaria populations in southwestern Michigan ponds and investigated whether this differentiation could alter the assembly of pond zooplankton communities in experimental mesocosms. In this study, we monitored the invasion success of different D. pulex x pulicaria populations after their introduction into an established zooplankton community. We also monitored the invasion success of a diverse array of zooplankton species into different D. pulex x pulicaria populations. Zooplankton community composition depended on the D. pulex X pulicaria source population. Daphnia pulex X pulicaria from one population failed to invade zooplankton communities, while those from other populations successfully invaded similar communities. If population differentiation in other species plays a role in community assembly similar to that demonstrated in our study, assembly may be more sensitive to evolutionary processes than has been previously generally considered.Integrative Biolog

Inferring genetic connectivity in real populations, exemplified by coastal and oceanic atlantic cod

Genetic data are commonly used to estimate connectivity between putative populations, but translating them to demographic dispersal rates is complicated. Theoretical equations that infer a migration rate based on the genetic estimator FST, such as Wright’s equation, FST ≈ 1/(4Nem + 1), make assumptions that do not apply to most real populations. How complexities inherent to real populations affect migration was exemplified by Atlantic cod in the North Sea and Skagerrak and was examined within an age-structured model that incorporated genetic markers. Migration was determined under various scenarios by varying the number of simulated migrants until the mean simulated level of genetic differentiation matched a fixed level of genetic differentiation equal to empirical estimates. Parameters that decreased the Ne/Nt ratio (where Ne is the effective and Nt is the total population size), such as high fishing mortality and high fishing gear selectivity, increased the number of migrants required to achieve empirical levels of genetic differentiation. Higher maturity-at-age and lower selectivity increased Ne/Nt and decreased migration when genetic differentiation was fixed. Changes in natural mortality, fishing gear selectivity, and maturity-at-age within expected limits had a moderate effect on migration when genetic differentiation was held constant. Changes in population size had the greatest effect on the number of migrants to achieve fixed levels of FST, particularly when genetic differentiation was low, FST ≈ 10−3. Highly variable migration patterns, compared with constant migration, resulted in higher variance in genetic differentiation and higher extreme values. Results are compared with and provide insight into the use of theoretical equations to estimate migration among real populations.publishedVersio