A test for deviation from island-model population structure

The neutral island model forms the basis for several estimation models that relate patterns of genetic structure to microevolutionary processes. Estimates of gene flow are often based on this model and may be biased when the model's assumptions are violated. An appropriate test for violations is to compare FST scores for individual loci to a null distribution based on the average FST taken over multiple loci. A parametric bootstrap method is described here based on Wright's beta-distribution to generate null distributions of FST for each locus. These null distributions account for error introduced by sampling populations, individuals and loci, and also biological sources of error, including variable alleles/locus and inbreeding. Confidence limits can be obtained directly from these distributions. Significant deviations from the island model may be the result of selection, deviations from the island model's migration pattern, nonequilibrium conditions, or other deviations from island-model assumptions. Only strong biases are likely to be detected because of the inherently large sampling variation of FST. Nevertheless, a coefficient, Nb, describing bias in the spread of the beta-distribution in units comparable to the gene flow parameter, Nm, can be obtained for each locus. In samples from populations of the butterfly Coenonympha tullia, the loci Idh-1, Mdh-1, Pgi and Pgm showed significantly lower FST than expected.     

The role of temperature variability on insect performance and population dynamics in a warming world

Despite the amount of research on the consequences of global warming on ecological systems, most studies examine the impact of increases in average temperature. However, there are few studies concerning the role of thermal variability on ecological processes. Based on insect thermal and population ecology, we propose a theoretical framework for organizing the study of the role that thermal mean and variability plays in individual performance, and how it may affect population dynamics. Starting with three predictions of global warming scenarios, we develop null models of the expected changes in individual physiological performance and population dynamics. Ecological consequences in each scenario may range from simple changes in performance to drastic changes in population fluctuations and geographic ranges. In particular, our null models show that potential changes in the intrinsic population growth rate (R_m) will depend on the interaction of mean temperature and thermal variability, and that the net effect of the interaction could be synergistic or antagonistic. To evaluate these null models, we fit performance curves to compiled data from the literature on measurements of R_m at several constant and fluctuating temperatures. The fitted models showed that several of the qualitative characteristics predicted by the null model may be found in the fitted curves. We expect that this framework will be useful as a guide to study the influence of thermal changes on the dynamics of natural populations. Synthesis Despite the common assertion that global warming impacts depend on not only the mean temperatures but also on thermal variability, theoretical approaches to explain how the interaction of thermal mean and variability determines fitness are lacking. Here we propose a framework for studying the role of thermal mean and variability on individual performance and population dynamics. We developed null models that show how changes in the intrinsic population growth rate (R_m) will depend on the interaction of mean temperature and thermal variability, and that the net effect could be synergistic or antagonistic. We expect that this framework will be useful to study the influence of thermal changes on natural populations.     

Microsatellite null alleles and estimation of population differentiation

Microsatellite null alleles are commonly encountered in population genetics studies, yet little is known about their impact on the estimation of population differentiation. Computer simulations based on the coalescent were used to investigate the evolutionary dynamics of null alleles, their impact on F(ST) and genetic distances, and the efficiency of estimators of null allele frequency. Further, we explored how the existing method for correcting genotype data for null alleles performed in estimating F(ST) and genetic distances, and we compared this method with a new method proposed here (for F(ST) only). Null alleles were likely to be encountered in populations with a large effective size, with an unusually high mutation rate in the flanking regions, and that have diverged from the population from which the cloned allele state was drawn and the primers designed. When populations were significantly differentiated, F(ST) and genetic distances were overestimated in the presence of null alleles. Frequency of null alleles was estimated precisely with the algorithm presented in Dempster et al. (1977). The conventional method for correcting genotype data for null alleles did not provide an accurate estimate of F(ST) and genetic distances. However, the use of the genetic distance of Cavalli-Sforza and Edwards (1967) corrected by the conventional method gave better estimates than those obtained without correction. F(ST) estimation from corrected genotype frequencies performed well when restricted to visible allele sizes. Both the proposed method and the traditional correction method have been implemented in a program that is available free of charge at http://www.montpellier.inra.fr/URLB/. We used 2 published microsatellite data sets based on original and redesigned pairs of primers to empirically confirm our simulation results.     

Fuzzy subset approach in coupled population dynamics of blowflies

This paper is a study on the population dynamics of blowflies employing a density-dependent, non-linear mathematical model and a coupled population formalism. In this study, we investigated the coupled population dynamics applying fuzzy subsets to model the population trajectory, analyzing demographic parameters such as fecundity, survival, and migration. The main results suggest different possibilities in terms of dynamic behavior produced by migration in coupled populations between distinct environments and the rescue effect generated by the connection between populations. It was possible to conclude that environmental heterogeneity can play an important role in blowfly metapopulation systems. The implications of these results for population dynamics of blowflies are discussed.     

DNA fingerprinting data and the analysis of population genetic structure by comparing band-sharing patterns

Genetic isolation among populations can be effectively investigated by multilocus DNA fingerprinting. If populations have diverged, it is expected that the mean proportion of bands shared by individuals from the same population, Bw, exceeds the corresponding mean, Bb, calculated from pairs of individuals from distinct populations. A problem arises in deciding whether any difference between Bw and Bb is statistically significant. In fact, any two band-sharing data (bij), contributing to Bw or Bb, are not independent if they share a common individual (like bij and bjl). This prevents a correct application of parametric tests, such as the Student's t-test. Recently, a modification of this test has been proposed that should avoid the independence problem. Using a large number of samples of fingerprints, simulated from an appropriate 'genetic' model, under a wide range of conditions, we compared the performances of the Student's t-test, the modified t-test and five new permutation tests, where individuals, rather than bij values, are permuted. We found that: (i) the Student's t-test can be very permissive, rejecting too often the null hypothesis when true, but is correct or conservative in certain cases; (ii) the modified t-test is extremely conservative when the null hypothesis is true and very inefficient otherwise; (iii) all five permutation tests are strictly correct, provided that individuals are ordered randomly on gels; and (iv) in this case, the permutation tests are equally efficient, and are not inferior to the Student's t-test when the latter is approximately correct and provides a fair benchmark.     

Comparing relative rates of pollen and seed gene flow in the island model using nuclear and organelle measures of population structure

We describe a method for comparing nuclear and organelle population differentiation (F(ST)) in seed plants to test the hypothesis that pollen and seed gene flow rates are equal. Wright's infinite island model is used, with arbitrary levels of self-fertilization and biparental organelle inheritance. The comparison can also be applied to gene flow in animals. Since effective population sizes are smaller for organelle genomes than for nuclear genomes and organelles are often uniparentally inherited, organelle F(ST) is expected to be higher at equilibrium than nuclear F(ST) even if pollen and seed gene flow rates are equal. To reject the null hypothesis of equal seed and pollen gene flow rates, nuclear and organelle F(ST)'s must differ significantly from their expected values under this hypothesis. Finite island model simulations indicate that infinite island model expectations are not greatly biased by finite numbers of populations (>/=100 subpopulations). The power to distinguish dissimilar rates of pollen and seed gene flow depends on confidence intervals for fixation index estimates, which shrink as more subpopulations and loci are sampled. Using data from the tropical tree Corythophora alta, we rejected the null hypothesis that seed and pollen gene flow rates are equal but cannot reject the alternative hypothesis that pollen gene flow is 200 times greater than seed gene flow.     

Methods of aggregation of variables in population dynamics

In ecology, we are faced with modelling complex systems involving many variables corresponding to interacting populations structured in different compartmental classes, ages and spatial patches. Models that incorporate such a variety of aspects would lead to systems of equations with many variables and parameters. Mathematical analysis of these models would, in general, be impossible. In many real cases, the dynamics of the system corresponds to two or more time scales. For example, individual decisions can be rapid in comparison to growth of the populations. In that case, it is possible to perform aggregation methods that allow one to build a reduced model that governs the dynamics of a lower dimensional system, at a slow time scale. In this article, we present a review of aggregation methods for time continuous systems as well as for discrete models. We also present applications in population dynamics. A first example concerns a continuous time model of a single population distributed on a system of two connected patches (a logistic source and a sink), by fast migration. It is shown that under a certain condition, the total equilibrium population can be larger than the carrying capacity of the logistic source. A second example concerns a discrete model of a population distributed on two patches, still a source and a sink, connected by fast migration. The use of aggregation methods permits us to conclude that density-dependent migration can stabilize the total population.     

Postglacial population expansion drives the evolution of long-distance migration in a songbird

The evolution of long-distance migratory behavior from sedentary populations is a central problem in studies of animal migration. Three crucial issues that remain unresolved are: (1) the biotic and abiotic factors promoting evolution of migratory behavior, (2) the geographic origin of ancestral sedentary populations, and (3) the time scale over which migration evolves. We test the role of postglacial population expansions during the Quaternary in driving the evolution of songbird migration against prevailing views favoring the role of intraspecific competition. In contrast to previous attempts to investigate these questions using interspecific phylogenies, we adopt an intraspecific approach and examine the phylogeography of a North American songbird, the chipping sparrow (Spizella passerina), which exhibits both long-distance migratory behavior in temperate North America and sedentary behavior in Mexico and Central America. We show that migratory populations descend from sedentary populations in southern Mexico and that migration has evolved as a result of a northward population expansion into temperate North America since the last glacial maximum 18,000 years ago. Migration appears to have evolved rapidly in some species as populations colonized areas of high seasonality in the temperate zone. The phylogeography of the yellow-eyed junco (Junco phaeonotus), a strictly sedentary species, provides a null model supporting the view that northward range expansions were driven solely by environmental factors and not by a predisposition to evolve migratory behavior. These results provide the strongest evidence to date that historical climate patterns can drive the rapid evolution of avian migration in natural populations, and they suggest a general mechanism for the repeated evolution of migration within and across bird lineages.     

Seasonally limited host supply generates microparasite population cycles

Cycles in biological populations have been shown to arise from enemy-victim systems, delayed density dependence, andmaternal effects. In an initial effort to model the year-to-year dynamics of natural populations of entomopathogenic nematodes and their insect hosts, we find that a simple, nonlinear, mechanistic model produces large amplitude, period two population cycles. The cycles are generated by seasonal dynamics within semi-isolated populations independently of inter-annual feedback in host population numbers, which differs from previously studied mechanisms. The microparasites compete for a fixed number of host insect larvae. Many nematodes at the beginning of the year quickly eliminate the pool of small hosts, and few nematodes are produced for the subsequent year. Conversely, initially small nematode populations do not over-exploit the host population, so the surviving hosts grow to be large and produce many nematodes that survive to the following year.     

The population genetics of alleles affecting enzyme activity.

It is possible to predict the population genetics of allozymes by assuming that fitness is proportional to flux through a biochemical pathway. The model presented here extends previous work by incorporating two additional features of biological realism. Firstly, that more than one biochemical route may exist between any two metabolites. The major routes have been identified as the classical biochemical pathways but in the event of a mutation blocking a major route, minor routes become significant. These minor routes are named "bypass fluxes" and have profound effects on the population genetics of allozymes. Secondly, recent work has suggested that a metabolic cost is associated with enzyme synthesis; this will constitute an additional selective pressure on alleles which affect the amount of enzyme synthesized. The model generates a fitness curve which predicts the fitness associated with any level of enzyme activity. It can utilize data on null or near-null, structural or regulatory, mutations in the presence or absence of bypass fluxes. When data from natural populations of Drosophila are investigated, it is concluded that selection pressures acting on enzyme variants may be much higher than previously thought.     

Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface

We introduce a new algorithm to account for the presence of null alleles in inferences of populations clusters from individual multilocus genetic data. We show by simulations that the presence of null alleles can affect the accuracy of inferences if not properly accounted for and that our algorithm improve signficantly their accuracy. AVAILABILITY: This new algorithm is implemented in the program Geneland. It is freely available under GNU public license as an R package on the Comprehensive R Archive Network. It now includes a fully clickable graphical interface. Informations on how to get the software are available on folk.uio.no/gillesg/Geneland.html     

RADSeq: next-generation population genetics

Next-generation sequencing technologies are making a substantial impact on many areas of biology, including the analysis of genetic diversity in populations. However, genome-scale population genetic studies have been accessible only to well-funded model systems. Restriction-site associated DNA sequencing, a method that samples at reduced complexity across target genomes, promises to deliver high resolution population genomic data-thousands of sequenced markers across many individuals-for any organism at reasonable costs. It has found application in wild populations and non-traditional study species, and promises to become an important technology for ecological population genomics.     

Rapidly converging numerical algorithms for models of population dynamics

We propose algorithms for the approximation of the age distributions of populations modeled by the McKendrick-von Foerster and the Gurtin-MacCamy systems both in one- and two-sex versions. For the one-sex model methods of second and fourth order are proposed. For the two-sex model a second order method is described. In each case the convergence is demonstrated. Several numerical examples are given.     

The population genetics of nodule bacteria

The data are reviewed on the population structure and evolutionary dynamics of the nodule bacteria (rhizobia) which are among the most intensively studied microorganisms. High level of the population polymorphism was demonstrated for the rhizobia populations using the enzyme electrophoresis (MLEE profiles). The average value of Nei's coefficient of heterogeneity (H = 1 - sigma pi2 [n/(n - 1)]) were: 0.590 for rhizobia (Rhizobium, Bradyrhizobium), 0.368 for enterobacteria (Escherichia, Salmonella, Shigella) and 0.452 for pathogenic bacteria (Bordetella, Borrelia, Erysipelothrix, Haemophilus, Helicobacter, Listeria, Mycobacterium, Neisseria, Staphylococcus) populations. In spite of being devoid of the effective systems for the gene conjugative transfer, many rhizobia populations possess an essentially panmictic structure. However, the enterobacteria populations in which the gene transfer may be facilitated due to the conjugative F- and R-factors, usually display the clonal population structure. The legume host plant is proved to be a key factor that determines the high levels of polymorphism and of panmixis as well as high evolutionary rates of the symbiotic bacteria populations. The host may ensure: a) an increase in mutation and gene transfer frequencies; b) stimulation of the competitive (selective) processes in both symbiotic and free-living rhizobia populations. A "cyclic" model of the rhizobia microevolution is presented which allows to assess the inputs the interstrain competition for the saprophytic growth and for the host nodulation into evolution of a plant-associated rhizobia population. The nodulation competitiveness in the rhizobia populations is responsible for the frequency-dependent selection of the rare genotypes which may arise in the soil bacterial communities as a result of the transfer of symbiotic (sym) genes from virulent rhizobia strains to either avirulent rhizobia or to the other (saprophytic, phytopathogenic) bacteria. Therefore, the nodulation competitiveness may ensure: a) panmictic structure of the natural rhizobia populations; b) high taxonomic diversity of rhizobia which was apparently caused by a broad sym gene expansion in the soil bacterial communities. The kin selection models are presented which explain evolution of the "altruistic" (essential for the host plant, but not for the bacteria themselves) symbiotic traits (e.g., the ability for symbiotic nitrogen fixation and for differentiation into non-viable bacteroids) in the rhizobia populations. These models are based on preferential multiplication of the nitrogen-fixing clones either in planta (due to an elevated supply of the nitrogen-fixing nodules with photosynthates) or ex planta (due to a release of the rhizopines from the nitrogen-fixing nodules). Speaking generally, interactions with the host plants provide a range of mechanisms increasing a genetic heterogeneity and an evolutionary potential in the associated rhizobia populations.     

基于零模型的宁夏荒漠草原优势种群点格局分析

植物种群空间分布格局是多种生态过程综合作用的结果。明确植物优势种群个体的空间分布格局与形成机制有助于认识种群生态适应对策与群落多样性维持机制。以宁夏荒漠草原优势种群蒙古冰草、短花针茅、牛枝子和牛心朴子为研究对象,采用完全空间随机零模型分析其种群空间分布格局特征,并通过异质泊松零模型与泊松聚块零模型探讨生境异质性、扩散限制等因子在其空间分布格局形成过程中的作用。结果显示:(1)完全空间随机零模型下,4个物种在<4 m尺度范围内表现为聚集分布,随尺度增大,逐渐过渡到随机分布和均匀分布。(2)在排除生境异质性的异质泊松零模型下,蒙古冰草种群在整个研究尺度上表现为随机分布;牛枝子、短花针茅和牛心朴子种群仅分别在0—0.2、0.1—0.4 m与0—0.2 m尺度范围内发生偏离,表现为均匀分布与聚集分布,其他尺度均为随机分布。(3)在排除扩散限制的泊松聚块零模型下,所研究种群均表现为随机分布。综上,荒漠草原优势种群在小尺度范围内主要表现为聚集分布;生境异质性与扩散限制均是驱动其空间分布格局形成的重要因子,相对而言,小尺度空间范围内扩散限制的作用更为显著。     

Microarray genotyping resource to determine population stratification in genetic association studies of complex disease

We have developed a robust microarray genotyping chip that will help advance studies in genetic epidemiology. In population-based genetic association studies of complex disease, there could be hidden genetic substructure in the study populations, resulting in false-positive associations. Such population stratification may confound efforts to identify true associations between genotype/haplotype and phenotype. Methods relying on genotyping additional null single nucleotide polymorphism (SNP) markers have been proposed, such as genomic control (GC) and structured association (SA), to correct association tests for population stratification. If there is an association of a disease with null SNPs, this suggests that there is a population subset with different genetic background plus different disease susceptibility. Genotyping over 100 null SNPs in the large numbers of patient and control DNA samples that are required in genetic association studies can be prohibitively expensive. We have therefore developed and tested a resequencing chip based on arrayed primer extension (APEX) from over 2000 DNA probe features that facilitate multiple interrogations of each SNP, providing a powerful, accurate, and economical means to simultaneously determine the genotypes at 110 null SNP loci in any individual. Based on 1141 known genotypes from other research groups, our GC SNP chip has an accuracy of 98.5%, including non-calls.     

The synergistic effects of stochasticity and dispersal on population densities

Using laboratory experiments, simulation models, and analytical techniques, we examined the impact of dispersal on the mean densities of patchily distributed populations. Even when dispersal leads to no net additions or removals of individuals from a population, it may nonetheless increase mean population densities if the net immigration rate is positive when populations are growing and negative when they are declining. As a model system for exploring this phenomenon, we used the yeastlike fungus Aureobasidium pullulans. In a laboratory experiment, we showed that dispersal can both ensure persistence and increase mean population densities even when dispersal among populations causes no direct addition or loss of fungal cells. From the laboratory data, we constructed a plausible model of A. pullulans dynamics among apple leaves within an orchard. This simulation model demonstrated that the effect of dispersal on mean densities is enhanced by three factors: weak density dependence of the dynamics within populations, high environmental variability affecting population growth rates, and lack of synchrony among the fluctuations of populations. Using an analytical model, we showed that the underlying mechanisms for this phenomenon are general, suggesting that a large effect of dispersal on mean population densities is possible in many natural systems.     

Transience in the humpback whale population of New Caledonia and implications for abundance estimation

A phenomenon of transience in the humpback whale population breeding in New Caledonia has been highlighted in recent analyses. We used these data to illustrate the risk of flawed inference when transience is not properly accounted for in abundance estimation of resident populations. Transients are commonly defined as individuals that pass through the sampling area once, i.e., have a null probability of being caught again, and therefore induce heterogeneity in the detection process. The presence of transients can lead to severe bias in the estimation of abundance and we demonstrate how to correct for this feature when estimating abundance of resident populations. In New Caledonia, very different conclusions about the number of resident whales in the southern lagoon between 1999 and 2005 are obtained when the abundance estimate accounts for the transient whales. Without correction, the estimates of the abundance were up to twice as high across all years compared to the estimates of the resident population when a correction for transients had been incorporated. Having reliable population estimates when assessing the status of endangered species is essential in documenting recovery and monitoring of population trends. Therefore, we encourage researchers to account for transients when reporting abundances of resident populations.