Estimation of effective population size and migration rate from one- and two-locus identity measures

Development and characterization of microsatellite markers for population genetics of the cocoa pod borer Conopomorpha cramerella (Snellen) (Lepidoptera: Gracillaridae)

The cocoa pod borer (CPB) Conopomorpha cramerella (Snellen) (Lepidoptera: Gracillaridae) is one of the major constraints for cocoa production in South East Asia. In addition to cultural and chemical control methods, autocidal control tactics such as the Sterile Insect Technique (SIT) could be an efficient addition to the currently control strategy, however SIT implementation will depend on the population genetics of the targeted pest. The aim of the present work was to search for suitable microsatellite loci in the genome of CPB that is partially sequenced. Twelve microsatellites were initially selected and used to analyze moths collected from Indonesia, Malaysia, and the Philippines. A quality control verification process was carried out and seven microsatellites found to be suitable and efficient to distinguish differences between CPB populations from different locations. The selected microsatellites were also tested against a closely related species, i.e. the lychee fruit borer Conopomorpha sinensis (LFB) from Vietnam and eight loci were found to be suitable. The availability of these novel microsatellite loci will provide useful tools for the analysis of the population genetics and gene flow of these pests, to select suitable CPB strains to implement the SIT.

Relatedness coefficients and their applications for triplets and quartets of genetic markers

Relatedness coefficients which seek the identity-by-descent of genetic markers are described. The markers are in groups of two, three or four, and if four, can consist of two pairs. It is essential to use cumulants (not moments) for four-marker-gene probabilities, as the covariance of homozygosity, used in four-marker applications, can only be described with cumulants. A covariance of homozygosity between pairs of markers arises when populations follow a mixture distribution. Also, the probability of four markers all identical-by-descent equals the normalized fourth cumulant. In this article, a "genetic marker" generally represents either a gene locus or an allele at a locus. Applications of three marker coefficients mainly involve conditional regression, and applications of four marker coefficients can involve identity disequilibrium. Estimation of relatedness using genetic marker data is discussed. However, three- and four-marker estimators suffer from statistical and numerical problems, including higher statistical variance, complexity of estimation formula, and singularity at some intermediate allele frequencies.

Limited impact of vector control on the population genetic structure of Glossina fuscipes fuscipes from the sleeping sickness focus of Maro, Chad

Tsetse flies (genus Glossina) transmit deadly trypanosomes to human populations and domestic animals in sub-Saharan Africa. Some foci of Human African Trypanosomiasis due to Trypanosoma brucei gambiense (g-HAT) persist in southern Chad, where a program of tsetse control was implemented against the local vector Glossina fuscipes fuscipes in 2018 in Maro. We analyzed the population genetics of G. f. fuscipes from the Maro focus before control (T0), one year (T1), and 18 months (T2) after the beginning of control efforts. Most flies captured displayed a local genetic profile (local survivors), but a few flies displayed outlier genotypes. Moreover, disturbance of isolation by distance signature (increase of genetic distance with geographic distance) and effective population size estimates, absence of any genetic signature of a bottleneck, and an increase of genetic diversity between T0 and T2 strongly suggest gene flows from various origins, and a limited impact of the vector control efforts on this tsetse population. Continuous control and surveillance of g-HAT transmission is thus recommended in Maro. Particular attention will need to be paid to the border with the Central African Republic, a country where the entomological and epidemiological status of g-HAT is unknown.

Development and characterization of microsatellite markers for the tsetse species Glossina brevipalpis and preliminary population genetics analyses

Tsetse flies, the vectors of African trypanosomes are of key medical and economic importance and one of the constraints for the development of Africa. Tsetse fly control is one of the most effective and sustainable strategies used for controlling the disease. Knowledge about population structure and level of gene flow between neighbouring populations of the target vector is of high importance to develop appropriate strategies for implementing effective management programmes. Microsatellites are commonly used to identify population structure and assess dispersal of the target populations and have been developed for several tsetse species but were lacking for Glossina brevipalpis. In this study, we screened the genome of G. brevipalpis to search for suitable microsatellite markers and nine were found to be efficient enough to distinguish between different tsetse populations. The availability of these novel microsatellite loci will help to better understand the population biology of G. brevipalpis and to assess the level of gene flow between different populations. Such information will help with the development of appropriate strategies to implement the sterile insect technique (SIT) in the framework of an area-wide integrated pest management (AW-IPM) approach to manage tsetse populations and ultimately address the trypanosomoses problem in these targeted areas.

Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus

Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but few have examined the demographic processes driving these patterns. In this study, we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of the self-incompatible plant Antirrhinum majus. Excess variance in heterozygosity between individuals is due to identity disequilibrium (ID), which reflects the variance in inbreeding between individuals; it is measured by the statistic g2. We calculated g2 together with FST and pairwise relatedness (Fij) using 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise Fij declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating either selfing or matings between close relatives. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity.

GSpace: an exact coalescence simulator of recombining genomes under isolation by distance

MOTIVATION

Simulation-based inference can bypass the limitations of statistical methods based on analytical approximations, but software allowing simulation of structured population genetic data without the classical n-coalescent approximations (such as those following from assuming large population size) are scarce or slow.

RESULTS

We present GSpace, a simulator for genomic data, based on a generation-by-generation coalescence algorithm taking into account small population size, recombination and isolation by distance.

AVAILABILITY AND IMPLEMENTATION

Freely available at site web INRAe (http://www1.montpellier.inra.fr/CBGP/software/gspace/download.html).

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Altitude and hillside orientation shapes the population structure of the Leishmania infantum vector Phlebotomus ariasi

Despite their role in Leishmania transmission, little is known about the organization of sand fly populations in their environment. Here, we used 11 previously described microsatellite markers to investigate the population genetic structure of Phlebotomus ariasi, the main vector of Leishmania infantum in the region of Montpellier (South of France). From May to October 2011, we captured 1,253 Ph. ariasi specimens using sticky traps in 17 sites in the North of Montpellier along a 14-km transect, and recorded the relevant environmental data (e.g., altitude and hillside). Among the selected microsatellite markers, we removed five loci because of stutter artifacts, absence of polymorphism, or non-neutral evolution. Multiple regression analyses showed the influence of altitude and hillside (51% and 15%, respectively), and the absence of influence of geographic distance on the genetic data. The observed significant isolation by elevation suggested a population structure of Ph. ariasi organized in altitudinal ecotypes with substantial rates of migration and positive assortative mating. This organization has implications on sand fly ecology and pathogen transmission. Indeed, this structure might favor the global temporal and spatial stability of sand fly populations and the spread and increase of L. infantum cases in France. Our results highlight the necessity to consider sand fly populations at small scales to study their ecology and their impact on pathogens they transmit.

Estimating linkage disequilibrium from genotypes under Hardy-Weinberg equilibrium

Background

Measures of linkage disequilibrium (LD) play a key role in a wide range of applications from disease association to demographic history estimation. The true population LD cannot be measured directly and instead can only be inferred from genetic samples, which are unavoidably subject to measurement error. Previous studies of r² (a measure of LD), such as the bias due to finite sample size and its variance, were based on the special case that the true population-wise LD is zero. These results generally do not hold for non-zero \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {r}_{true}^2 $$\end{document}rtrue2 values, which are more common in real genetic data.

Results

This work generalises the estimation of r² to all levels of LD, and for both phased and unphased data. First, we provide new formulae for the effect of finite sample size on the observed r² values. Second, we find a new empirical formula for the variance of the observed r², equals to 2E[r²](1 − E[r²])/n, where n is the diploid sample size. Third, we propose a new routine, Constrained ML, a likelihood-based method to directly estimate haplotype frequencies and r² from diploid genotypes under Hardy-Weinberg Equilibrium. While serving the same purpose as the pre-existing Expectation-Maximisation algorithm, the new routine can have better convergence and is simpler to use. A new likelihood-ratio test is also introduced to test for the absence of a particular haplotype. Extensive simulations are run to support these findings.

Conclusion

Most inferences on LD will benefit from our new findings, from point and interval estimation to hypothesis testing. Genetic analyses utilising r² information will become more accurate as a result.

Conservation Genetic Assessment of Savannah Elephants (Loxodonta africana) in the Greater Kruger Biosphere, South Africa

Savannah elephant populations have been severely reduced and fragmented throughout its remaining range. In general, however, there is limited information regarding their genetic status, which is essential knowledge for conservation. We investigated patterns of genetic variation in savannah elephants from the Greater Kruger Biosphere, with a focus on those in previously unstudied nature reserves adjacent to Kruger National Park, using dung samples from 294 individuals and 18 microsatellites. The results of genetic structure analyses using several different methods of ordination and Bayesian clustering strongly suggest that elephants throughout the Greater Kruger National Park (GKNP) constitute a single population. No evidence of a recent genetic bottleneck was detected using three moment-based approaches and two coalescent likelihood methods. The apparent absence of a recent genetic bottleneck associated with the known early 1900s demographic bottleneck may result from a combination of rapid post-bottleneck population growth, immigration and long generation time. Point estimates of contemporary effective population size (Ne) for the GKNP were ~ 500-700, that is, at the low end of the range of Ne values that have been proposed for maintaining evolutionary potential and the current ratio of Ne to census population size (Nc) may be quite low (<0.1). This study illustrates the difficulties in assessing the impacts on Ne in populations that have suffered demographic crashes but have recovered rapidly and received gene flow, particularly in species with long generation times in which genetic time lags are longer. This work provides a starting point and baseline information for genetic monitoring of the GKNP elephants.

Inbreeding reduces long-term growth of Alpine ibex populations

Many studies document negative inbreeding effects on individuals, and conservation efforts to preserve rare species routinely employ strategies to reduce inbreeding. Despite this, there are few clear examples in nature of inbreeding decreasing the growth rates of populations, and the extent of population-level effects of inbreeding in the wild remains controversial. Here, we take advantage of a long-term dataset of 26 reintroduced Alpine ibex (Capra ibex ibex) populations spanning nearly 100 years to show that inbreeding substantially reduced per capita population growth rates, particularly for populations in harsher environments. Populations with high average inbreeding (F ≈ 0.2) had population growth rates reduced by 71% compared with populations with no inbreeding. Our results show that inbreeding can have long-term demographic consequences even when environmental variation is large and deleterious alleles may have been purged during bottlenecks. Thus, efforts to guard against inbreeding effects in populations of endangered species have not been misplaced.

Population genetics of Glossina palpalis palpalis in sleeping sickness foci of Côte d'Ivoire before and after vector control

Glossina palpalis palpalis remains the major vector of sleeping sickness in Côte d'Ivoire. The disease is still active at low endemic levels in Bonon and Sinfra foci in the western-central part of the country. In this study, we investigated the impact of a control campaign on G. p. palpalis population structure in Bonon and Sinfra foci in order to adapt control strategies. Genetic variation at microsatellite loci was used to examine the population structure of different G. p. palpalis cohorts before and after control campaigns. Isolation by distance was observed in our sampling sites. Before control, effective population size was high (239 individuals) with dispersal at rather short distance (731 m per generation). We found some evidence that some of the flies captured after treatment come from surrounding sites, which increased the genetic variance. One Locus, GPCAG, displayed a 1000% increase of subdivision measure after control while other loci only exhibited a substantial increase in variance of subdivision. Our data suggested a possible trap avoidance behaviour in G. p. palpalis. It is important to take into account and better understand the possible reinvasion from neighboring sites and trap avoidance for the sake of sustainability of control campaigns effects.

Detecting Wahlund effects together with amplification problems: Cryptic species, null alleles and short allele dominance in Glossina pallidipes populations from Tanzania

Population genetics is a convenient tool to study the population biology of non-model and hard to sample species. This is particularly true for parasites and vectors. Heterozygote deficits and/or linkage disequilibrium often occur in such studies and detecting the origin of those (Wahlund effect, reproductive system or amplification problems) is uneasy. We used new tools (correlation between the number of times a locus is found in significant linkage disequilibrium and its genetic diversity, correlations between Wright's F_IS and F_ST , F_IS and number of missing data, F_IT and allele size and standard errors comparisons) for the first time on a real data set of tsetse flies, a vector of dangerous diseases to humans and domestic animals in sub-Saharan Africa. With these new tools, and cleaning data from null allele, temporal heterogeneity and short allele dominance effects, we unveiled the coexistence of two highly divergent cryptic clades in the same sites. These results are in line with other studies suggesting that the biodiversity of many taxa still largely remain undescribed, in particular pathogenic agents and their vectors. Our results also advocate that including individuals from different cohorts tends to bias subdivision measures and that keeping loci with short allele dominance and/or too frequent missing data seriously jeopardize parameter's estimations. Finally, separated analyses of the two clades suggest very small tsetse densities and relatively large dispersal.

Genetic characterization of Benin's wild populations of Sarotherodon melanotheron melanotheron Rüppell, 1852

The Cichlid fish Sarotherodon melanotheron is typically found in West and Central African estuaries and lagoons. It represents a good candidate for promoting tilapia farming in brackish waters. Understanding the genetic diversity in its populations from the hydrographical basins of Southern Benin is primordial before designing selective breeding programs. For this purpose, 202 samples collected from four rivers of Southern Benin and were genotyped using 15 polymorphic microsatellite DNA markers. Each river was split up into three sampling sites. We found significant global linkage disequilibrium across the genome of natural populations of this tilapia species overall the loci. However, when the loci that display aberrant Wright's (F_IS and F_ST) were removed from the data, a linkage disequilibrium was detected for the remaining 11 loci and became compatible with the null hypothesis. Null alleles explained at least 20.58% of F_IS variation. We found a significant isolation by distance across subsamples. Effective population size averaged 210 individuals, with a range from 36 to 517 individuals. Assuming that 79% of heterozygote deficits are explained by sib mating lead to a rough estimate of r_sm = 0.4 of mating rate between full sibs within S. melanotheron subpopulations. The fish size correlated positively and significantly with the observed F_IS (r = 0.58; p value = 0.04806). Reproduction system (endogamy) in S. melanotheron could explain the strong heterozygote deficit observed. Our results provide technical guidance for efficient management of this tilapia species' genetic resources for breeding programs in fresh and brackish waters.

Genetic comparison of Glossina tachinoides populations in three river basins of the Upper West Region of Ghana and implications for tsetse control

Tsetse flies are the cyclical vectors of African animal trypanosomosis (AAT) and human African trypanosomosis (HAT). In March 2010, the Government of Ghana initiated a large scale integrated tsetse eradication campaign in the Upper West Region (UWR) (≈18,000 km(2)) under the umbrella of the Pan-African Tsetse and Trypanosomosis Eradication Campaign (PATTEC). We investigated the structuring of Glossina tachinoides populations within and between the three main river basins of the target area in the UWR. Out of a total sample of 884 flies, a sub-sample of 266 was genotyped at nine microsatellite loci. The significance of the different hierarchical levels was tested using Yang's parameters estimated with Weir and Cockerham's method. A significant effect of traps within groups (pooling traps no more than 3 km distant from each other), of groups within river basins and of river basins within the whole target area was observed. Isolation by distance between traps was highly significant. A local density of 0.48-0.61 flies/m(2) was estimated and a dispersal distance that approximated 11 m per generation [CI 9, 17]. No significant sex-biased dispersal was detected. Dispersal distances of G. tachinoides in the UWR were relatively low, possibly as a result of the fragmentation of the habitat and the seasonality of the Kulpawn and Sissili rivers. Moreover, very high fly population densities were observed in the sample sites, which potentially reduces dispersal at constant habitat saturation, because the probability that migrants can established is reduced (density dependent dispersal). However, the observed spatial dispersal was deemed sufficient for a G. tachinoides-cleared area to be reinvaded from neighboring populations in adjacent river basins. These data corroborate results from other population genetics studies in West Africa, which indicate that G. tachinoides populations from different river basins cannot be considered isolated.

Contemporary effective population and metapopulation size (N e and meta-N e): comparison among three salmonids inhabiting a fragmented system and differing in gene flow and its asymmetries

We estimated local and metapopulation effective sizes ([Formula: see text] and meta-[Formula: see text]) for three coexisting salmonid species (Salmo salar, Salvelinus fontinalis, Salvelinus alpinus) inhabiting a freshwater system comprising seven interconnected lakes. First, we hypothesized that [Formula: see text] might be inversely related to within-species population divergence as reported in an earlier study (i.e., FST: S. salar> S. fontinalis> S. alpinus). Using the approximate Bayesian computation method implemented in ONeSAMP, we found significant differences in [Formula: see text] ([Formula: see text]) between species, consistent with a hierarchy of adult population sizes ([Formula: see text]). Using another method based on a measure of linkage disequilibrium (LDNE: [Formula: see text]), we found more finite [Formula: see text] values for S. salar than for the other two salmonids, in line with the results above that indicate that S. salar exhibits the lowest [Formula: see text] among the three species. Considering subpopulations as open to migration (i.e., removing putative immigrants) led to only marginal and non-significant changes in [Formula: see text], suggesting that migration may be at equilibrium between genetically similar sources. Second, we hypothesized that meta-[Formula: see text] might be significantly smaller than the sum of local [Formula: see text]s (null model) if gene flow is asymmetric, varies among subpopulations, and is driven by common landscape features such as waterfalls. One 'bottom-up' or numerical approach that explicitly incorporates variable and asymmetric migration rates showed this very pattern, while a number of analytical models provided meta-[Formula: see text] estimates that were not significantly different from the null model or from each other. Our study of three species inhabiting a shared environment highlights the importance and utility of differentiating species-specific and landscape effects, not only on dispersal but also in the demography of wild populations as assessed through local [Formula: see text]s and meta-[Formula: see text]s and their relevance in ecology, evolution and conservation.

Inferring recent historic abundance from current genetic diversity

Recent historic abundance is an elusive parameter of great importance for conserving endangered species and understanding the pre-anthropogenic state of the biosphere. The number of studies that have used population genetic theory to estimate recent historic abundance from contemporary levels of genetic diversity has grown rapidly over the last two decades. Such assessments often yield unexpectedly large estimates of historic abundance. We review the underlying theory and common practices of estimating recent historic abundance from contemporary genetic diversity, and critically evaluate the potential issues at various estimation steps. A general issue of mismatched spatio-temporal scales between the estimation itself and the objective of the estimation emerged from our assessment; genetic diversity-based estimates of recent historic abundance represent long-term averages, whereas the objective typically is an estimate of recent abundance for a specific population. Currently, the most promising approach to estimate the difference between recent historic and contemporary abundance requires that genetic data be collected from samples of similar spatial and temporal duration. Novel genome-enabled inference methods may be able to utilize additional information of dense genome-wide distributions of markers, such as of identity-by-descent tracts, to infer recent historic abundance from contemporary samples only.

Balancing selection on MHC class I in wild brown trout Salmo trutta

Evidence is reported for balancing selection acting on variation at major histocompatibility complex (MHC) in wild populations of brown trout Salmo trutta. First, variation at an MHC class I (satr-uba)-linked microsatellite locus (mhc1) is retained in small S. trutta populations isolated above waterfalls although variation is lost at neutral microsatellite markers. Second, populations across several catchments are less differentiated at mhc1 than at neutral markers, as predicted by theory. The population structure of these fish was also elucidated.

Understanding local population genetics of tsetse: the case of an isolated population of Glossina palpalis gambiensis in Burkina Faso

Tsetse flies are the vectors of human and animal trypanosomiases. For tsetse eradication programs, it is crucial to be able to identify and target isolated populations, because they can be targeted for eradication without risk of reinvasion. However, most data that are available on non-isolated populations fail to find how these populations are locally structured, because Wahlund effect (admixture of individuals from genetically different units) always interfere with interpretations. In this paper, we investigated the genetic population structure of a possibly isolated population of Glossina palpalis gambiensis in a sacred wood in South Burkina Faso, using microsatellite DNA markers. We found that genotypic proportions in this population were in agreement with random mating model and that these tsetse were genetically highly differentiated from other populations of the same Mouhoun river basin only a few kilometers away, confirming its genetic isolation. The population also displayed substantial temporal differentiation in a two years period that lead to an estimate of effective population size of ∼100 individuals. The fact that no Wahlund effect was identified allowed us to accurately measure the basic genetic parameters of this isolated population. Identifying such isolated and small populations is crucial for eradication programs and should be implemented more often.

Estimating contemporary effective population size on the basis of linkage disequilibrium in the face of migration

Effective population size (Ne) is an important genetic parameter because of its relationship to loss of genetic variation, increases in inbreeding, accumulation of mutations, and effectiveness of selection. Like most other genetic approaches that estimate contemporary Ne, the method based on linkage disequilibrium (LD) assumes a closed population and (in the most common applications) randomly recombining loci. We used analytical and numerical methods to evaluate the absolute and relative consequences of two potential violations of the closed-population assumption: (1) mixture LD caused by occurrence of more than one gene pool, which would downwardly bias Ne and (2) reductions in drift LD (and hence upward bias in Ne) caused by an increase in the number of parents responsible for local samples. The LD method is surprisingly robust to equilibrium migration. Effects of mixture LD are small for all values of migration rate (m), and effects of additional parents are also small unless m is high in genetic terms. LD estimates of Ne therefore accurately reflect local (subpopulation) Ne unless m>∼5-10%. With higher m, Ne converges on the global (metapopulation) Ne. Two general exceptions were observed. First, equilibrium migration that is rare and hence episodic can occasionally lead to substantial mixture LD, especially when sample size is small. Second, nonequilibrium, pulse migration of strongly divergent individuals can also create strong mixture LD and depress estimates of local Ne. In both cases, assignment tests, Bayesian clustering, and other methods often will allow identification of recent immigrants that strongly influence results. In simulations involving equilibrium migration, the standard LD method performed better than a method designed to jointly estimate Ne and m. The above results assume loci are not physically linked; for tightly linked loci, the LD signal from past migration events can persist for many generations, with consequences for Ne estimates that remain to be evaluated.

Effect of parasitic sex-ratio distorters on host gene frequencies in a mainland-island context

It was previously argued that infection by parasitic sex-ratio distorters can enhance both random genetic drift and genetic influx from outside the population. However, these two enhancement effects have been studied independently. Here, we study the equilibrium frequencies of alleles (neutral and selected) in a mainland-island scenario where both genetic drift and genetic influx are enhanced due to infection by a cytoplasmic feminizing element. Interestingly, our model reveals that at neutral loci, the two effects almost exactly cancel each other out, such that infection has only a very minor effect on the equilibrium frequency distributions of alleles. At selected loci, in contrast, the two effects are unbalanced and infection has conspicuous effects. Despite the cryptic effects of infection at neutral loci, we demonstrate that temporally spaced data can be used to evaluate the effect of infection on genetic drift and that on gene flow separately.

The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating "spurious" bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.

Early detection of population declines: high power of genetic monitoring using effective population size estimators

Early detection of population declines is essential to prevent extinctions and to ensure sustainable harvest. We evaluated the performance of two N_e estimators to detect population declines: the two-sample temporal method and a one-sample method based on linkage disequilibrium (LD). We used simulated data representing a wide range of population sizes, sample sizes and number of loci. Both methods usually detect a population decline only one generation after it occurs if N_e drops to less than approximately 100, and 40 microsatellite loci and 50 individuals are sampled. However, the LD method often out performed the temporal method by allowing earlier detection of less severe population declines (N_e approximately 200). Power for early detection increased more rapidly with the number of individuals sampled than with the number of loci genotyped, primarily for the LD method. The number of samples available is therefore an important criterion when choosing between the LD and temporal methods. We provide guidelines regarding design of studies targeted at monitoring for population declines. We also report that 40 single nucleotide polymorphism (SNP) markers give slightly lower precision than 10 microsatellite markers. Our results suggest that conservation management and monitoring strategies can reliably use genetic based methods for early detection of population declines.

Small variance in growth rates in annual plants has large effects on genetic drift

PREMISE OF THE STUDY

Effective population size (N(e)) is a critical index of the evolutionary capacity of populations. Low N(e) indicates that standing genetic diversity is susceptible to loss via stochastic processes (and inbreeding) and is, therefore, unavailable for natural selection to act upon. Reported N(e) in plant populations is often quite low. What biological and ecological factors might produce such low N(e) •

METHODS

We conducted a simulation model to test the effect of randomly assigned and autocorrelated growth rates of annual plants on plant-size distributions at the end of the growing season. Because plant size is directly correlated with reproductive output in annual plants, variation in plant size reflects variation in reproduction, and thus our modeled size distributions can be used to estimate N(e). •

KEY RESULTS

Randomly assigned growth rates had a negligble effect on N(e)/N. Autocorrelated growth rates decreased N(e)/N as the length of the growing season increased. This was the case even when the variance in growth rates was as low as 0.1% of the mean. •

CONCLUSIONS

While intrinsic plant biology can affect the degree of growth autocorrelation, ecological factors such as competition, herbivory, and abiotic stress can increase or decrease levels of growth autocorrelation. Ecological factors that increase growth autocorrelation can have significant effects on genetic drift within populations.

Spurious correlations and inference in landscape genetics

Reliable interpretation of landscape genetic analyses depends on statistical methods that have high power to identify the correct process driving gene flow while rejecting incorrect alternative hypotheses. Little is known about statistical power and inference in individual-based landscape genetics. Our objective was to evaluate the power of causal-modelling with partial Mantel tests in individual-based landscape genetic analysis. We used a spatially explicit simulation model to generate genetic data across a spatially distributed population as functions of several alternative gene flow processes. This allowed us to stipulate the actual process that is in action, enabling formal evaluation of the strength of spurious correlations with incorrect models. We evaluated the degree to which naïve correlational approaches can lead to incorrect attribution of the driver of observed genetic structure. Second, we evaluated the power of causal modelling with partial Mantel tests on resistance gradients to correctly identify the explanatory model and reject incorrect alternative models. Third, we evaluated how rapidly after the landscape genetic process is initiated that we are able to reliably detect the effect of the correct model and reject the incorrect models. Our analyses suggest that simple correlational analyses between genetic data and proposed explanatory models produce strong spurious correlations, which lead to incorrect inferences. We found that causal modelling was extremely effective at rejecting incorrect explanations and correctly identifying the true causal process. We propose a generalized framework for landscape genetics based on analysis of the spatial genetic relationships among individual organisms relative to alternative hypotheses that define functional relationships between landscape features and spatial population processes.

Population structure of Glossina palpalis gambiensis (Diptera: Glossinidae) between river basins in Burkina Faso: consequences for area-wide integrated pest management

African animal trypanosomosis is a major obstacle to the development of more efficient and sustainable livestock production systems in West Africa. Riverine tsetse species such as Glossina palpalis gambiensis Vanderplank are their major vectors. A wide variety of control tactics is available to manage these vectors, but their elimination will only be sustainable if control is exercised following area-wide integrated pest management (AW-IPM) principles, i.e. the control effort is targeting an entire tsetse population within a circumscribed area. In the present study, genetic variation at microsatellite DNA loci was used to examine the population structure of G. p. gambiensis inhabiting two adjacent river basins, i.e. the Comoé and the Mouhoun River basins in Burkina Faso. A remote sensing analysis revealed that the woodland savannah habitats between the river basins have remained unchanged during the last two decades. In addition, genetic variation was studied in two populations that were separated by a man-made lake originating from a dam built in 1991 on the Comoé. Low genetic differentiation was observed between the samples from the Mouhoun and the Comoé River basins and no differentiation was found between the samples separated by the dam. The data presented indicate that the overall genetic differentiation of G. p. gambiensis populations inhabiting two adjacent river basins in Burkina Faso is low (F(ST)=0.016). The results of this study suggest that either G. p. gambiensis populations from the Mouhoun are not isolated from those of the Comoé, or that the isolation is too recent to be detected. If elimination of the G. p. gambiensis population from the Mouhoun River basin is the selected control strategy, re-invasion from adjacent river basins may need to be prevented by establishing a buffer zone between the Mouhoun and the other river basin(s).

Linkage disequilibrium estimates of contemporary N e using highly variable genetic markers: a largely untapped resource for applied conservation and evolution

Genetic methods are routinely used to estimate contemporary effective population size (N_e) in natural populations, but the vast majority of applications have used only the temporal (two-sample) method. We use simulated data to evaluate how highly polymorphic molecular markers affect precision and bias in the single-sample method based on linkage disequilibrium (LD). Results of this study are as follows: (1) Low-frequency alleles upwardly bias , but a simple rule can reduce bias to <about 10% without sacrificing much precision. (2) With datasets routinely available today (10–20 loci with 10 alleles; 50 individuals), precise estimates can be obtained for relatively small populations (N_e < 200), and small populations are not likely to be mistaken for large ones. However, it is very difficult to obtain reliable estimates for large populations. (3) With ‘microsatellite’ data, the LD method has greater precision than the temporal method, unless the latter is based on samples taken many generations apart. Our results indicate the LD method has widespread applicability to conservation (which typically focuses on small populations) and the study of evolutionary processes in local populations. Considerable opportunity exists to extract more information about N_e in nature by wider use of single-sample estimators and by combining estimates from different methods.

Correlation measures for linkage disequilibrium within and between populations

Correlation statistics can be used to measure the amount of linkage disequilibrium (LD) between two loci in subdivided populations. Within populations, the square of the correlation of gene frequencies, r2, is a convenient measure of LD. Between populations, the statistic rirj, for populations i and j, measures the relatedness of LD. Recurrence relationships for these two parameters are derived for the island model of population subdivision, under the assumptions of the linked identity-by-descent (LIBD) model in which correlation measures are equated to probability measures. The recurrence relationships closely predict the build-up of r2 and rirj following population subdivision in computer simulations. The LIBD model predicts that a steady state will be reached with r2 equal to 1/[1+4Nec(1+(k-1)rho)], where k is the number of island populations, Ne is the effective local population (island) size, and rho measures the ratio of migration (m) to recombination (c) and is equal to m/[c(k-1)+m]. For low values of m/c, rho=0, and E(r2) is equal to 1/(1+4Nec). For high values of m/c, rho=1, and E(r2) is equal to 1/(1+4kNec). The value of rirj following separation eventually settles down to a steady state whose expectation, E(rirj), is equal to E(r2) multiplied by rho. Equations predicting the change in rirj values are applied to the separation of African (Yoruba - YRI) and non-African (European - CEU) populations, using data from Hapmap. The primary data lead to an estimate of separation time of less than 1000 generations if there has been no migration, which is around one-third of minimum current estimates. Ancient rather than recent migration can explain the form of the data.

Extreme inbreeding in Leishmania braziliensis

Leishmania species of the subgenus Viannia and especially Leishmania braziliensis are responsible for a large proportion of New World leishmaniasis cases. The reproductive mode of Leishmania species has often been assumed to be predominantly clonal, but remains unsettled. We have investigated the genetic polymorphism at 12 microsatellite loci on 124 human strains of Leishmania braziliensis from 2 countries, Peru and Bolivia. There is substantial genetic diversity, with an average of 12.4 +/- 4.4 alleles per locus. There is linkage disequilibrium at a genome-wide scale, as well as a substantial heterozygote deficit (more than 50% the expected value from Hardy-Weinberg equilibrium), which indicates high levels of inbreeding. These observations are inconsistent with a strictly clonal model of reproduction, which implies excess heterozygosity. Moreover, there is large genetic heterogeneity between populations within countries (Wahlund effect), which evinces a strong population structure at a microgeographic scale. Our findings are compatible with the existence of population foci at a microgeographic scale, where clonality alternates with sexuality of an endogamic nature, with possible occasional recombination events between individuals of different genotypes. These findings provide key clues on the ecology and transmission patterns of Leishmania parasites.

Population sizes and dispersal pattern of tsetse flies: rolling on the river?

The West African trypanosomoses are mostly transmitted by riverine species of tsetse fly. In this study, we estimate the dispersal and population size of tsetse populations located along the Mouhoun river in Burkina Faso where tsetse habitats are experiencing increasing fragmentation caused by human encroachment. Dispersal estimated through direct (mark and recapture) and indirect (genetic isolation by distance) methods appeared consistent with one another. In these fragmented landscapes, tsetse flies displayed localized, small subpopulations with relatively short effective dispersal. We discuss how such information is crucial for designing optimal strategies for eliminating this threat. To estimate ecological parameters of wild animal populations, the genetic measures are both a cost- and time-effective alternative to mark-release-recapture. They can be applied to other vector-borne diseases of medical and/or economic importance.

The population structure of Glossina palpalis gambiensis from island and continental locations in Coastal Guinea

Background

We undertook a population genetics analysis of the tsetse fly Glossina palpalis gambiensis, a major vector of sleeping sickness in West Africa, using microsatellite and mitochondrial DNA markers. Our aims were to estimate effective population size and the degree of isolation between coastal sites on the mainland of Guinea and Loos Islands. The sampling locations encompassed Dubréka, the area with the highest Human African Trypanosomosis (HAT) prevalence in West Africa, mangrove and savannah sites on the mainland, and two islands, Fotoba and Kassa, within the Loos archipelago. These data are discussed with respect to the feasibility and sustainability of control strategies in those sites currently experiencing, or at risk of, sleeping sickness.

Principal Findings

We found very low migration rates between sites except between those sampled around the Dubréka area that seems to contain a widely dispersed and panmictic population. In the Kassa island samples, various effective population size estimates all converged on surprisingly small values (10<N_e<30) that suggest either a recent bottleneck, and/or other biological or ecological factors such as strong variance in the reproductive success of individuals.

Conclusion/Significance

Whatever their origin, the small effective population sizes suggest high levels of inbreeding in tsetse flies within the island samples in marked contrast to the large diffuse deme in Dubréka zones. We discuss how these genetic results suggest that different tsetse control strategies should be applied on the mainland and islands.

Guinea is the country with the highest prevalence of sleeping sickness in West Africa, and we undertook a population genetics analysis there of the most dangerous tsetse fly species of West Africa, Glossina palpalis gambiensis. Our aims were to estimate effective population size and the degree of isolation between coastal sites on the mainland of Guinea (including Dubréka, a highly prevalent sleeping sickness focus) and Loos Islands in order to get the most possible accurate vision of feasibility and sustainability of anti-tsetse strategies of these sites. We found very low migration rates of tsetse between sites except between those situated in the Dubréka area, which seems to contain a widely distributed panmictic tsetse population (i.e. a population where mating occurs at random). Effective population sizes on Loos islands estimated with various techniques all converged to surprisingly small values. These values might be explained by a recent decrease in tsetse numbers on Kassa Island due to bauxite mining activities. But on the other sites, other explanations have to be found, including possible variance in reproductive success. Our genetic results suggest that different control strategies should be advised on the mainland (reduction in tsetse densities, no elimination) compared to the islands (total elimination feasible). This approach could be extended to many areas where vector control of Human and Animal Trypanosomoses is contemplated.

The joint effects of selection and dominance on the QST - FST contrast

Q(ST) measures the differentiation of quantitative traits between populations. It is often compared to F(ST), which measures population differentiation at neutral marker loci due to drift, migration, and mutation. When Q(ST) is different from F(ST), it is usually taken as evidence that selection has either restrained or accelerated the differentiation of the quantitative trait relative to neutral markers. However, a number of other factors such as inbreeding, dominance, and epistasis may also affect the Q(ST) - F(ST) contrast. In this study, we examine the effects of dominance, selection, and inbreeding on Q(ST) - F(ST). We compare Q(ST) with F(ST) at selected and neutral loci for populations at equilibrium between selection, drift, mutation, and migration using both analytic and simulation approaches. Interestingly, when divergent selection is acting on a locus, inbreeding and dominance generally inflate Q(ST) relative to F(ST) when they are both measured at the quantitative locus at equilibrium. As a consequence, dominance is unlikely to hide the signature of divergent selection on the Q(ST) - F(ST) contrast. However, although in theory dominance and inbreeding affect the expectation for Q(ST) - F(ST), of most concern is the very large variance in both Q(ST) and F(ST), suggesting that we should be cautious in attributing small differences between Q(ST) and F(ST) to selection.

Comparative estimation of effective population sizes and temporal gene flow in two contrasting population systems

Estimation of effective population sizes (N(e)) and temporal gene flow (N(e)m, m) has many implications for understanding population structure in evolutionary and conservation biology. However, comparative studies that gauge the relative performance of N(e), N(e)m or m methods are few. Using temporal genetic data from two salmonid fish population systems with disparate population structure, we (i) evaluated the congruence in estimates and precision of long- and short-term N(e), N(e)m and m from six methods; (ii) explored the effects of metapopulation structure on N(e) estimation in one system with spatiotemporally linked subpopulations, using three approaches; and (iii) determined to what degree interpopulation gene flow was asymmetric over time. We found that long-term N(e) estimates exceeded short-term N(e) within populations by 2-10 times; the two were correlated in the system with temporally stable structure (Atlantic salmon, Salmo salar) but not in the highly dynamic system (brown trout, Salmo trutta). Four temporal methods yielded short-term N(e) estimates within populations that were strongly correlated, and these were higher but more variable within salmon populations than within trout populations. In trout populations, however, these short-term N(e) estimates were always lower when assuming gene flow than when assuming no gene flow. Linkage disequilibrium data generally yielded short-term N(e) estimates of the same magnitude as temporal methods in both systems, but the two were uncorrelated. Correlations between long- and short-term geneflow estimates were inconsistent between methods, and their relative size varied up to eightfold within systems. While asymmetries in gene flow were common in both systems (58-63% of population-pair comparisons), they were only temporally stable in direction within certain salmon population pairs, suggesting that gene flow between particular populations is often intermittent and/or variable. Exploratory metapopulation N(e) analyses in trout demonstrated both the importance of spatial scale in estimating N(e) and the role of gene flow in maintaining genetic variability within subpopulations. Collectively, our results illustrate the utility of comparatively applying N(e), N(e)m and m to (i) tease apart processes implicated in population structure, (ii) assess the degree of continuity in patterns of connectivity between population pairs and (iii) gauge the relative performance of different approaches, such as the influence of population subdivision and gene flow on N(e) estimation. They further reiterate the importance of temporal sampling replication in population genetics, the value of interpreting N(e)or m in light of species biology, and the need to address long-standing assumptions of current N(e), N(e)m or m models more explicitly in future research.

Effective population sizes and migration rates in fragmented populations of an endangered insect (Coenagrion mercuriale: Odonata)

1. Effective population sizes (N(e)) and migration rates (m) are critical evolutionary parameters that impact on population survival and determine the relative influence of selection and genetic drift. While the parameter m is well-studied in animal populations, N(e) remains challenging to measure and consequently is only rarely estimated, particularly in insect taxa. 2. We used demographic and genetic methods to estimate N(e) and m in a fragmented population of the endangered damselfly Coenagrion mercuriale to better understand the contrast between genetic and field estimates of these parameters and also to identify the spatial scale over which populations may become locally adapted. 3. We found a contrast between demographic- and genetic-based estimates of these parameters, with the former apparently providing overestimates of N(e), owing to substantial underestimation of the variance in reproductive success, and the latter overestimating m, because spatial genetic structure is weak. 4. The overall N(e) of sites within the population network at Beaulieu Heath, the largest C. mercuriale site in the UK, was estimated to vary between approximately 60 and 2700. 5. While N(e) was not correlated with either the total numbers of adults (N) or the area of habitat, this parameter was always less than N, because of substantial variance in reproductive success. The ratio N(e)/N varied between 0.006 and 0.42 and was generally larger in smaller populations, possibly representing some 'genetic compensation'. 6. From a simple genetic model and these data on N(e) and m, it seems that populations of C. mercuriale have the potential to respond to localized spatial variation in selection and this would need to be considered for future genetic management of this endangered species.

Steady state of homozygosity and for the island model

We examine homozygosity and G(st) for a subdivided population governed by the finite island model. Assuming an infinite allele model and strong mutation we show that the steady state distributions of G(st) and homozygosity have asymptotic expansions in the mutation rate. We use this observation to derive asymptotic expansions for various moments of homozygosity and to derive rigorous formulas for the mean and variance of G(st). We show that G(st) approximately 1/(1+2Nm), similarly to the well known formula of Wright for the infinite island model, and that the variance of G(st) goes to zero as mutation increases.

Joint estimation of migration rate and effective population size using the island model

Using the island model of population demography, I report that the demographic parameters migration rate and effective population size can be jointly estimated with equilibrium probabilities of identity in state calculated using a sample of genotypes collected at a single point in time from a single generation. The method, which uses moment-type estimators, applies to dioecious populations in which females and males have identical demography and monoecious populations with no selfing and requires that offspring genotypes are sampled following reproduction and prior to migration. I illustrate the estimation procedure using the infinite-island model with no mutation and the finite-island model with three kinds of mutation models. In the infinite-island model with no mutation, the estimators can be expressed as simple functions of estimates of the F-statistic parameters F(IT) and F(ST). In the finite-island model with mutation among k alleles, mutation rate, migration rate, and effective population size can be simultaneously estimated. The estimates of migration rate and effective population size are somewhat robust to violations in assumptions that may arise in empirical applications such as different kinds of mutation models and deviations from temporal equilibrium.

Constraints on the origin and maintenance of genetic kin recognition

Kin-recognition mechanisms allow helping behaviors to be directed preferentially toward related individuals, and could be expected to evolve in many cases. However, genetic kin recognition requires a genetic polymorphism on which recognition is based, and kin discriminating behaviors will affect the evolution of such polymorphism. It is unclear whether genetic polymorphisms used in kin recognition should be maintained by extrinsic selection pressures or not, as opposite conclusions have been reached by analytical one-locus models and simulations exploring different population structures. We analyze a two-locus model in a spatially subdivided population following the island model of dispersal between demes of finite size. We find that in the absence of mutation, selection eliminates polymorphism in most cases, except with extreme spatial structure and low recombination. With mutation, the population may reach a stable limit cycle over which both loci are polymorphic; however, the average frequency of conditional helping can be high only under strong structure and low recombination. Finally, we review evidence for extrinsic selection maintaining polymorphism on which kin recognition is based.

Beyond the point of no return? A comparison of genetic diversity in captive and wild populations of two nearly extinct species of Goodeid fish reveals that one is inbred in the wild

The relative importance of genetic and non-genetic factors in extinction liability has been extensively debated. Here, we examine the levels of genetic variability at 13 (seven informative) loci in wild and captive populations of two endangered species of Mexican Goodeid fish, Ameca splendens and Zoogoneticus tequila. Allelic diversity was higher in the wild populations, and F(IS) lower. Values of theta (=4Nemu) were estimated using a coalescent approach. These implied that the effective population size of all captive populations of A. splendens were smaller than that of the wild population; qualitatively similar results were obtained using an analytical method based on within-population gene identity disequilibrium. However, the wild population of Z. tequila did not show a significantly greater estimate of theta. We used the Beaumont approach to infer population declines, and found that both species showed clear evidence of a decline in effective population size, although this was stronger and probably occurred over a longer period of time in Z. tequila than in A. splendens. The decline in Z. tequila probably occurred before captive populations were established. We discuss implications for the conservation of critically endangered populations.