Likelihood-based estimation of the effective population size using temporal changes in allele frequencies: a genealogical approach

MLNe: Simulating and Estimating Effective Size and Migration Rate from Temporal Changes in Allele Frequencies

In studies of molecular ecology, conservation biology and evolutionary biology, the current or recent effective size (Ne) of a population is frequently estimated from the marker genotype data of two or more temporally spaced samples of individuals taken from the population. Despite the developments of numerous Bayesian, likelihood and moment estimators, only a couple of them can use both temporally and spatially spaced samples of individuals to estimate jointly the effective size (Ne) of and the migration rate (m) into a population. In this note I describe new implementations of these joint estimators of Ne and m in software MLNe which runs on multiple platforms (Windows, Mac, Linux) with or without a graphical user interface (GUI), has an integrated simulation module to simulate genotype data for investigating the impacts of various factors (such as sample size and sampling interval) on estimation precision and accuracy, exploits both Message Passing Interface (MPI) and openMP for parallel computations using multiple cores and nodes to speed up analysis. The program does not require data pre-processing and accepts multiple formats of a file of original genotype data and a file of parameters as input. The GUI facilitates data and parameter inputs and produces publication-quality output graphs, while the non-GUI version of software is convenient for batch analysis of multiple datasets as in simulations. MLNe will help advance the analysis of temporal genetic marker data for estimating Ne of and m between populations, which are important parameters that will help biologists for the conservation management of natural and managed populations. MLNe can be downloaded free from the website http://www.zsl.org/science/research/software/.

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.

Genetic substructure and admixture as important factors in linkage disequilibrium-based estimation of effective number of breeders in recovering wildlife populations

The number of effective breeders (Nb ) and effective population size (Ne ) are population parameters reflective of evolutionary potential, susceptibility to stochasticity, and viability. We have estimated these parameters using the linkage disequilibrium-based approach with LDNE through the latest phase of population recovery of the brown bears (Ursus arctos) in Finland (1993-2010; N = 621). This phase of the recovery was recently documented to be associated with major changes in genetic composition. In particular, differentiation between the northern and the southern genetic cluster declined rapidly within 1.5 generations. Based on this, we have studied effects of the changing genetic structure on Nb and Ne , by comparing estimates for whole Finland with the estimates for the two genetic clusters. We expected a potentially strong relationship between estimate sizes and genetic differentiation, which should disappear as the population recovers and clusters merge. Consistent with this, our estimates for whole Finland were lower than the sum of the estimates of the two genetic clusters and both approaches produced similar estimates in the end. Notably, we also found that admixed genotypes strongly increased the estimates. In all analyses, our estimates for Ne were larger than Nb and likely reflective for brown bears of the larger region of Finland and northwestern Russia. Conclusively, we find that neglecting genetic substructure may lead to a massive underestimation of Nb and Ne . Our results also suggest the need for further empirical analysis focusing on individuals with admixed genotypes and their potential high influence on Nb and Ne .

Estimating virus effective population size and selection without neutral markers

By combining high-throughput sequencing (HTS) with experimental evolution, we can observe the within-host dynamics of pathogen variants of biomedical or ecological interest. We studied the evolutionary dynamics of five variants of Potato virus Y (PVY) in 15 doubled-haploid lines of pepper. All plants were inoculated with the same mixture of virus variants and variant frequencies were determined by HTS in eight plants of each pepper line at each of six sampling dates. We developed a method for estimating the intensities of selection and genetic drift in a multi-allelic Wright-Fisher model, applicable whether these forces are strong or weak, and in the absence of neutral markers. This method requires variant frequency determination at several time points, in independent hosts. The parameters are the selection coefficients for each PVY variant and four effective population sizes N_e at different time-points of the experiment. Numerical simulations of asexual haploid Wright-Fisher populations subjected to contrasting genetic drift (N_e ∈ [10, 2000]) and selection (|s| ∈ [0, 0.15]) regimes were used to validate the method proposed. The experiment in closely related pepper host genotypes revealed that viruses experienced a considerable diversity of selection and genetic drift regimes. The resulting variant dynamics were accurately described by Wright-Fisher models. The fitness ranks of the variants were almost identical between host genotypes. By contrast, the dynamics of N_e were highly variable, although a bottleneck was often identified during the systemic movement of the virus. We demonstrated that, for a fixed initial PVY population, virus effective population size is a heritable trait in plants. These findings pave the way for the breeding of plant varieties exposing viruses to stronger genetic drift, thereby slowing virus adaptation.

A growing number of experimental evolution studies are using an “evolve-and-resequence” approach to observe the within-host dynamics of pathogen variants of biomedical or ecological interest. The resulting data are particularly appropriate for studying the effects of evolutionary forces, such as selection and genetic drift, on the emergence of new pathogen variants. However, it remains challenging to unravel the effects of selection and genetic drift in the absence of neutral markers, a situation frequently encountered for microbes, such as viruses, due to their small constrained genomes. Using such an approach on a plant virus, we observed that the same set of virus variants displayed highly diverse dynamics in closely related plant genotypes. We developed and validated a method that does not require neutral markers, for estimating selection coefficients and effective population sizes from these experimental evolution data. We found that the viruses experienced considerable diversity in genetic drift regimes, depending on host genotype. Importantly, genetic drift experienced by virus populations was shown to be a heritable plant trait. These findings pave the way for the breeding of plant varieties exposing viruses to strong genetic drift, thereby slowing virus adaptation.

Determining causes of genetic isolation in a large carnivore (Ursus americanus) population to direct contemporary conservation measures

The processes leading to genetic isolation influence a population’s local extinction risk, and should thus be identified before conservation actions are implemented. Natural or human-induced circumstances can result in historical or contemporary barriers to gene flow and/or demographic bottlenecks. Distinguishing between these hypotheses can be achieved by comparing genetic diversity and differentiation in isolated vs. continuous neighboring populations. In Ontario, American black bears (Ursus americanus) are continuously distributed, genetically diverse, and exhibit an isolation-by-distance structuring pattern, except on the Bruce Peninsula (BP). To identify the processes that led to the genetic isolation of BP black bears, we modelled various levels of historical and contemporary migration and population size reductions using forward simulations. We compared simulation results with empirical genetic indices from Ontario black bear populations under different levels of geographic isolation, and conducted additional simulations to determine if translocations could help achieve genetic restoration. From a genetic standpoint, conservation concerns for BP black bears are warranted because our results show that: i) a recent demographic bottleneck associated with recently reduced migration best explains the low genetic diversity on the BP; and ii) under sustained isolation, BP black bears could lose between 70% and 80% of their rare alleles within 100 years. Although restoring migration corridors would be the most effective method to enhance long-term genetic diversity and prevent inbreeding, it is unrealistic to expect connectivity to be re-established. Current levels of genetic diversity could be maintained by successfully translocating 10 bears onto the peninsula every 5 years. Such regular translocations may be more practical than landscape restoration, because areas connecting the peninsula to nearby mainland black bear populations have been irreversibly modified by humans, and form strong barriers to movement.

Prediction and estimation of effective population size

Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces, such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating Ne for future research.

A longitudinal genetic survey identifies temporal shifts in the population structure of Dutch house sparrows

Dutch house sparrow (Passer domesticus) densities dropped by nearly 50% since the early 1980s, and similar collapses in population sizes have been reported across Europe. Whether, and to what extent, such relatively recent demographic changes are accompanied by concomitant shifts in the genetic population structure of this species needs further investigation. Therefore, we here explore temporal shifts in genetic diversity, genetic structure and effective sizes of seven Dutch house sparrow populations. To allow the most powerful statistical inference, historical populations were resampled at identical locations and each individual bird was genotyped using nine polymorphic microsatellites. Although the demographic history was not reflected by a reduction in genetic diversity, levels of genetic differentiation increased over time, and the original, panmictic population (inferred from the museum samples) diverged into two distinct genetic clusters. Reductions in census size were supported by a substantial reduction in effective population size, although to a smaller extent. As most studies of contemporary house sparrow populations have been unable to identify genetic signatures of recent population declines, results of this study underpin the importance of longitudinal genetic surveys to unravel cryptic genetic patterns.

Moderate genetic drift is driven by extreme recruitment events in the invasive mollusk Crepidula fornicata

Effective population size (Ne) is a measure of genetic drift and is thus a central parameter in evolution, conservation genetics and invasion biology. Interestingly, in native marine species, Ne is typically several orders of magnitude lower than the census size. This pattern has often been explained by high fecundity, variation in reproductive success and pronounced early mortality, resulting in genetic drift across generations. Data documenting genetic drift and/or Ne in marine invasive species are, however, still scarce. We examined the importance of genetic drift in the invasive species Crepidula fornicata by genotyping 681 juveniles sampled during each annual recruitment peak over nine consecutive years in the Bay of Morlaix (Brittany, France). Observed variations in genetic diversity were partially explained by variation in recruitment intensity. In addition, substantial temporal genetic differentiation was documented (that is, genetic drift), and was attributed to nonrandom variance in the reproductive success of different breeding groups across years in the study species. Using a set of single-sample and temporal estimators for Ne, we estimated Ne to be three or four orders of magnitude smaller than the census size (Nc). On one hand, this reduction in Ne relative to Nc appeared congruent with, although slight higher than, values commonly observed in native marine species. Particular life-history traits of this invasive species may play an important role in buffering genetic drift. On the other hand, Ne still remained far below Nc, hence, possibly reducing the efficiency of selection effects.

Temporal trends in genetic data and effective population size support efficacy of management practices in critically endangered dusky gopher frogs (Lithobates sevosus)

Monitoring temporal changes in population genetic diversity and effective population size can provide vital information on future viability. The dusky gopher frog, Lithobates sevosus, is a critically endangered species found only in coastal Mississippi, with low genetic variability as a consequence of isolation and population size reduction. Conservation management practices have been implemented, but their efficacy has not been addressed. We genotyped individuals collected 1997-2014 to determine temporal trends in population genetic variation, structure, and effective size. Observed and expected heterozygosity and allelic richness revealed temporally stable, but low, levels of genetic variation. Positive levels of inbreeding were found in each year. There was weak genetic structure among years, which can be attributed to increased effects of genetic drift and inbreeding in small populations. L. sevosus exhibited an increase in effective population size, and currently has an estimated effective size of 33.0-58.6 individuals, which is approximately half the census size. This large ratio could possibly be explained by genetic compensation. We found that management practices have been effective at maintaining and improving effective size and genetic diversity, but that additional strategies need to be implemented to enhance viability of the species.

Tracking changes in chromosomal arrangements and their genetic content during adaptation

There is considerable evidence for an adaptive role of inversions, but how their genetic content evolves and affects the subsequent evolution of chromosomal polymorphism remains controversial. Here, we track how life-history traits, chromosomal arrangements and 22 microsatellites, within and outside inversions, change in three replicated populations of Drosophila subobscura for 30 generations of laboratory evolution since founding from the wild. The dynamics of fitness-related traits indicated adaptation to the new environment concomitant with directional evolution of chromosomal polymorphism. Evidence of selective changes in frequency of inversions was obtained for seven of 23 chromosomal arrangements, corroborating a role for inversions in adaptation. The evolution of linkage disequilibrium between some microsatellites and chromosomes suggested that adaptive changes in arrangements involved changes in their genetic content. Several microsatellite alleles increased in frequency more than expected by drift in targeted inversions in all replicate populations. In particular, there were signs of selection in the O3+4 arrangement favouring a combination of alleles in two loci linked to the inversion and changing along with it, although the lack of linkage disequilibrium between these loci precludes epistatic selection. Seven other alleles increased in frequency within inversions more than expected by drift, but were not in linkage disequilibrium with them. Possibly these alleles were hitchhiking along with alleles under selection that were not specific to those inversions. Overall, the selection detected on the genetic content of inversions, despite limited coverage of the genome, suggests that genetic changes within inversions play an important role in adaptation.

Coupling Demographic and Genetic Variability from Archived Collections of European Anchovy (Engraulis encrasicolus)

It is well known that temporal fluctuations in small populations deeply influence evolutionary potential. Less well known is whether fluctuations can influence the evolutionary potentials of species with large census sizes. Here, we estimated genetic population parameters from as survey of polymorphic microsatellite DNA loci in archived otoliths from Adriatic European anchovy (Engraulis encrasicolus), a fish with large census sizes that supports numerous local fisheries. Stocks have fluctuated greatly over the past few decades, and the Adriatic fishery collapsed in 1987. Our results show a significant reduction of mean genetic parameters as a consequence of the population collapse. In addition, estimates of effective population size (Ne) are much smaller than those expected in a fishes with large population census sizes (Nc). Estimates of Ne indicate low effective population sizes, even before the population collapse. The ratio Ne/Ne ranged between 10-6 and 10-8, indicating a large discrepancy between the anchovy gene pool and population census size. Therefore, anchovy populations may be more vulnerable to fishery effort and environmental change than previously thought.

The conservation status of the Galápagos marine iguanas, Amblyrhynchus cristatus: a molecular perspective

Traditionally, conservation management focuses efforts on taxonomic units. However, when the taxa used do not reflect biologically meaningful units, such methods should be reconsidered to avoid the loss of irreplaceable biodiversity. The Galápagos marine iguana (Amblyrhynchus cristatus) is listed as Vulnerable on the IUCN Red List of Threatened Species and is facing growing anthropogenic threats. Currently, management is based on a taxonomy which is questionable in the light of recent molecular data. As such, there is a danger that evolutionarily significant populations may be left vulnerable to extirpation. Herein, we apply molecular data to elucidate the population structure of this species across the Galápagos archipelago, and thus advise conservation management in the absence of a revised taxonomy. Applying a wealth of molecular data including 12 microsatellite loci and 1181 bp of the mitochondrial control region in over 1200 individuals, we delineate distinct populations and prioritize their management. Bayesian population structure analysis revealed 10 distinct population clusters, which we propose as management units (MUs). All MUs are significantly differentiated, with one unit on San Cristóbal Island being particularly distinct in terms of both microsatellite loci and mitochondrial data. Based on estimates of the genetic effective population size (Ne), we find the MUs comprised of populations occurring on Floreana, Española, Marchena, and San Cristóbal to be alarmingly small. In consideration of both Neand anthropogenic threats, we recommend that conservation practitioners focus efforts on Floreana and San Cristóbal islands, and argue that better census size estimates of populations are urgently needed.

Temporal stability of genetic variability and differentiation in the three-spined stickleback (Gasterosteus aculeatus)

Temporal variation in allele frequencies, whether caused by deterministic or stochastic forces, can inform us about interesting demographic and evolutionary phenomena occurring in wild populations. In spite of the continued surge of interest in the genetics of three-spined stickleback (Gasterosteus aculeatus) populations, little attention has been paid towards the temporal stability of allele frequency distributions, and whether there are consistent differences in effective size (Ne) of local populations. We investigated temporal stability of genetic variability and differentiation in 15 microsatellite loci within and among eight collection sites of varying habitat type, surveyed twice over a six-year time period. In addition, Nes were estimated with the expectation that they would be lowest in isolated ponds, intermediate in larger lakes and largest in open marine sites. In spite of the marked differences in genetic variability and differentiation among the study sites, the temporal differences in allele frequencies, as well as measures of genetic diversity and differentiation, were negligible. Accordingly, the Ne estimates were temporally stable, but tended to be lower in ponds than in lake or marine habitats. Hence, we conclude that allele frequencies in putatively neutral markers in three-spined sticklebacks seem to be temporally stable - at least over periods of few generations - across a wide range of habitat types differing markedly in levels of genetic variability, effective population size and gene flow.

Estimating effective population size from temporally spaced samples with a novel, efficient maximum-likelihood algorithm

The effective population size Ne is a key parameter in population genetics and evolutionary biology, as it quantifies the expected distribution of changes in allele frequency due to genetic drift. Several methods of estimating Ne have been described, the most direct of which uses allele frequencies measured at two or more time points. A new likelihood-based estimator NB^ for contemporary effective population size using temporal data is developed in this article. The existing likelihood methods are computationally intensive and unable to handle the case when the underlying Ne is large. This article tries to work around this problem by using a hidden Markov algorithm and applying continuous approximations to allele frequencies and transition probabilities. Extensive simulations are run to evaluate the performance of the proposed estimator NB^, and the results show that it is more accurate and has lower variance than previous methods. The new estimator also reduces the computational time by at least 1000-fold and relaxes the upper bound of Ne to several million, hence allowing the estimation of larger Ne. Finally, we demonstrate how this algorithm can cope with nonconstant Ne scenarios and be used as a likelihood-ratio test to test for the equality of Ne throughout the sampling horizon. An R package “NB” is now available for download to implement the method described in this article.

Population genetics inference for longitudinally-sampled mutants under strong selection

Longitudinal allele frequency data are becoming increasingly prevalent. Such samples permit statistical inference of the population genetics parameters that influence the fate of mutant variants. To infer these parameters by maximum likelihood, the mutant frequency is often assumed to evolve according to the Wright–Fisher model. For computational reasons, this discrete model is commonly approximated by a diffusion process that requires the assumption that the forces of natural selection and mutation are weak. This assumption is not always appropriate. For example, mutations that impart drug resistance in pathogens may evolve under strong selective pressure. Here, we present an alternative approximation to the mutant-frequency distribution that does not make any assumptions about the magnitude of selection or mutation and is much more computationally efficient than the standard diffusion approximation. Simulation studies are used to compare the performance of our method to that of the Wright–Fisher and Gaussian diffusion approximations. For large populations, our method is found to provide a much better approximation to the mutant-frequency distribution when selection is strong, while all three methods perform comparably when selection is weak. Importantly, maximum-likelihood estimates of the selection coefficient are severely attenuated when selection is strong under the two diffusion models, but not when our method is used. This is further demonstrated with an application to mutant-frequency data from an experimental study of bacteriophage evolution. We therefore recommend our method for estimating the selection coefficient when the effective population size is too large to utilize the discrete Wright–Fisher model.

Investigating population history using temporal genetic differentiation

The rapid advance of sequencing technology, coupled with improvements in molecular methods for obtaining genetic data from ancient sources, holds the promise of producing a wealth of genomic data from time-separated individuals. However, the population-genetic properties of time-structured samples have not been extensively explored. Here, we consider the implications of temporal sampling for analyses of genetic differentiation and use a temporal coalescent framework to show that complex historical events such as size reductions, population replacements, and transient genetic barriers between populations leave a footprint of genetic differentiation that can be traced through history using temporal samples. Our results emphasize explicit consideration of the temporal structure when making inferences and indicate that genomic data from ancient individuals will greatly increase our ability to reconstruct population history.

WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data

With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (N(e)), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)-based method that is able to correctly infer genomewide average N(e) from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).

Assessing the maximum contribution from ancient populations

Ancestral relationships between populations separated by time represent an often neglected dimension in population genetics, a field which historically has focused on analysis of spatially distributed samples from the same point in time. Models are usually straightforward when two time-separated populations are assumed to be completely isolated from all other populations. However, this is usually an unrealistically stringent assumption when there is gene flow with other populations. Here, we investigate continuity in the presence of gene flow from unknown populations. This setup allows a more nuanced treatment of questions regarding population continuity in terms of "level of contribution" from a particular ancient population to a more recent population. We propose a statistical framework which makes use of a biallelic marker sampled at two different points in time to assess population contribution, and present two different interpretations of the concept. We apply the approach to published data from a prehistoric human population in Scandinavia (Malmström H, Gilbert MTP, Thomas MG, Brandström M, Storå J, Molnar P, Andersen PK, Bendixen C, Holmlund G, Götherström A, et al. 2009. Ancient DNA reveals lack of continuity between Neolithic hunter-gatherers and contemporary Scandinavians. Curr Biol. 19:1758-1762) and Pleistocene woolly mammoth (Barnes I, Shapiro B, Lister A, Kuznetsova T, Sher A, Guthrie D, Thomas MG. 2007. Genetic structure and extinction of the woolly mammoth, Mammuthus primigenius. Curr Biol. 17:1072-1075; Debruyne R, Chu G, King CE, Bos K, Kuch M, Schwarz C, Szpak P, Gröcke DR, Matheus P, Zazula G, et al. 2008. Out of America: ancient DNA evidence for a new world origin of late quaternary woolly mammoths. Curr Biol. 18:1320-1326).

Influenza virus drug resistance: a time-sampled population genetics perspective

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

Can genetic estimators provide robust estimates of the effective number of breeders in small populations?

The effective population size (N(e)) is proportional to the loss of genetic diversity and the rate of inbreeding, and its accurate estimation is crucial for the monitoring of small populations. Here, we integrate temporal studies of the gecko Oedura reticulata, to compare genetic and demographic estimators of N(e). Because geckos have overlapping generations, our goal was to demographically estimate N(bI), the inbreeding effective number of breeders and to calculate the N(bI)/N(a) ratio (N(a) =number of adults) for four populations. Demographically estimated N(bI) ranged from 1 to 65 individuals. The mean reduction in the effective number of breeders relative to census size (N(bI)/N(a)) was 0.1 to 1.1. We identified the variance in reproductive success as the most important variable contributing to reduction of this ratio. We used four methods to estimate the genetic based inbreeding effective number of breeders N(bI(gen)) and the variance effective populations size N(eV(gen)) estimates from the genotype data. Two of these methods - a temporal moment-based (MBT) and a likelihood-based approach (TM3) require at least two samples in time, while the other two were single-sample estimators - the linkage disequilibrium method with bias correction LDNe and the program ONeSAMP. The genetic based estimates were fairly similar across methods and also similar to the demographic estimates excluding those estimates, in which upper confidence interval boundaries were uninformative. For example, LDNe and ONeSAMP estimates ranged from 14-55 and 24-48 individuals, respectively. However, temporal methods suffered from a large variation in confidence intervals and concerns about the prior information. We conclude that the single-sample estimators are an acceptable short-cut to estimate N(bI) for species such as geckos and will be of great importance for the monitoring of species in fragmented landscapes.

From nature to the laboratory: the impact of founder effects on adaptation

Most founding events entail a reduction in population size, which in turn leads to genetic drift effects that can deplete alleles. Besides reducing neutral genetic variability, founder effects can in principle shift additive genetic variance for phenotypes that underlie fitness. This could then lead to different rates of adaptation among populations that have undergone a population size bottleneck as well as an environmental change, even when these populations have a common evolutionary history. Thus, theory suggests that there should be an association between observable genetic variability for both neutral markers and phenotypes related to fitness. Here, we test this scenario by monitoring the early evolutionary dynamics of six laboratory foundations derived from founders taken from the same source natural population of Drosophila subobscura. Each foundation was in turn three-fold replicated. During their first few generations, these six foundations showed an abrupt increase in their genetic differentiation, within and between foundations. The eighteen populations that were monitored also differed in their patterns of phenotypic adaptation according to their immediately ancestral founding sample. Differences in early genetic variability and in effective population size were found to predict differences in the rate of adaptation during the first 21 generations of laboratory evolution. We show that evolution in a novel environment is strongly contingent not only on the initial composition of a newly founded population but also on the stochastic changes that occur during the first generations of colonization. Such effects make laboratory populations poor guides to the evolutionary genetic properties of their ancestral wild populations.

The population structure of Glossina fuscipes fuscipes in the Lake Victoria basin in Uganda: implications for vector control

Background

Glossina fuscipes fuscipes is the primary vector of trypanosomiasis in humans and livestock in Uganda. The Lake Victoria basin has been targeted for tsetse eradication using a rolling carpet initiative, from west to east, with four operational blocks (3 in Uganda and 1 in Kenya), under a Pan-African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). We screened tsetse flies from the three Ugandan PATTEC blocks for genetic diversity at 15 microsatellite loci from continental and offshore populations to provide empirical data to support this initiative.

Methods

We collected tsetse samples from 11 sites across the Lake Victoria basin in Uganda. We performed genetic analyses on 409 of the collected tsetse flies and added data collected for 278 individuals in a previous study. The flies were screened across 15 microsatellite loci and the resulting data were used to assess the temporal stability of populations, to analyze patterns of genetic exchange and structuring, to estimate dispersal rates and evaluate the sex bias in dispersal, as well as to estimate demographic parameters (N_E and N_C).

Results

We found that tsetse populations in this region were stable over 4-16 generations and belong to 4 genetic clusters. Two genetic clusters (1 and 2) corresponded approximately to PATTEC blocks 1 and 2, while the other two (3 and 4) fell within PATTEC block 3. Island populations grouped into the same genetic clusters as neighboring mainland sites, suggesting presence of gene flow between these sites. There was no evidence of the stretch of water separating islands from the mainland forming a significant barrier to dispersal. Dispersal rates ranged from 2.5 km per generation in cluster 1 to 14 km per generation in clusters 3 and 4. We found evidence of male-biased dispersal. Few breeders are successfully dispersing over large distances. Effective population size estimates were low (33–310 individuals), while census size estimates ranged from 1200 (cluster 1) to 4100 (clusters 3 and 4). We present here a novel technique that adapts an existing census size estimation method to sampling without replacement, the scheme used in sampling tsetse flies.

Conclusion

Our study suggests that different control strategies should be implemented for the three PATTEC blocks and that, given the high potential for re-invasion from island sites, mainland and offshore sites in each block should be targeted at the same time.

Demographic history of an elusive carnivore: using museums to inform management

Elusive carnivores present a challenge to managers because traditional survey methods are not suitable. We applied a genetic approach using museum specimens to examine how historical and recent conditions influenced the demographic history of Puma concolor in western and southern Texas, USA. We used 10 microsatellite loci and indexed population trends by estimating historical and recent genetic diversity, genetic differentiation and effective population size. Mountain lions in southern Texas exhibited a 9% decline in genetic diversity, whereas diversity remained stable in western Texas. Genetic differentiation between western and southern Texas was minimal historically (F(ST) = 0.04, P < 0.01), but increased 2-2.5 times in our recent sample. An index of genetic drift for southern Texas was seven to eight times that of western Texas, presumably contributing to the current differentiation between western and southern Texas. Furthermore, southern Texas exhibited a >50% temporal decline in effective population size, whereas western Texas showed no change. Our results illustrate that population declines and genetic drift have occurred in southern Texas, likely because of contemporary habitat loss and predator control. Population monitoring may be needed to ensure the persistence of mountain lions in the southern Texas region. This study highlights the utility of sampling museum collections to examine demographic histories and inform wildlife management.

Ancient DNA reveals genetic stability despite demographic decline: 3,000 years of population history in the endemic Hawaiian petrel

In the Hawaiian Islands, human colonization, which began approximately 1,200 to 800 years ago, marks the beginning of a period in which nearly 75% of the endemic avifauna became extinct and the population size and range of many additional species declined. It remains unclear why some species persisted whereas others did not. The endemic Hawaiian petrel (Pterodroma sandwichensis) has escaped extinction, but colonies on two islands have been extirpated and populations on remaining islands have contracted. We obtained mitochondrial DNA sequences from 100 subfossil bones, 28 museum specimens, and 289 modern samples to investigate patterns of gene flow and temporal changes in the genetic diversity of this endangered species over the last 3,000 years, as Polynesians and then Europeans colonized the Hawaiian Islands. Genetic differentiation was found to be high between both modern and ancient petrel populations. However, gene flow was substantial between the extirpated colonies on Oahu and Molokai and modern birds from the island of Lanai. No significant reductions in genetic diversity occurred over this period, despite fears in the mid-1900s that this species may have been extinct. Simulations show that even a decline to a stable effective population size of 100 individuals would result in the loss of only 5% of the expected heterozygosity. Simulations also show that high levels of genetic diversity may be retained due to the long generation time of this species. Such decoupling between population size and genetic diversity in long-lived species can have important conservation implications. It appears that a pattern of dispersal from declining colonies, in addition to long generation time, may have allowed the Hawaiian petrel to escape a severe genetic bottleneck, and the associated extinction vortex, and persist despite a large population decline after human colonization.

Short-term genetic changes: evaluating effective population size estimates in a comprehensively described brown trout (Salmo trutta) population

The effective population size (N(e)) is notoriously difficult to accurately estimate in wild populations as it is influenced by a number of parameters that are difficult to delineate in natural systems. The different methods that are used to estimate N(e) are affected variously by different processes at the population level, such as the life-history characteristics of the organism, gene flow, and population substructure, as well as by the frequency patterns of genetic markers used and the sampling design. Here, we compare N(e) estimates obtained by different genetic methods and from demographic data and elucidate how the estimates are affected by various factors in an exhaustively sampled and comprehensively described natural brown trout (Salmo trutta) system. In general, the methods yielded rather congruent estimates, and we ascribe that to the adequate genotyping and exhaustive sampling. Effects of violating the assumptions of the different methods were nevertheless apparent. In accordance with theoretical studies, skewed allele frequencies would underestimate temporal allele frequency changes and thereby upwardly bias N(e) if not accounted for. Overlapping generations and iteroparity would also upwardly bias N(e) when applied to temporal samples taken over short time spans. Gene flow from a genetically not very dissimilar source population decreases temporal allele frequency changes and thereby acts to increase estimates of N(e). Our study reiterates the importance of adequate sampling, quantification of life-history parameters and gene flow, and incorporating these data into the N(e) estimation.

Microsatellite genotyping reveals end-Pleistocene decline in mammoth autosomal genetic variation

The last glaciation was a dynamic period with strong impact on the demography of many species and populations. In recent years, mitochondrial DNA sequences retrieved from radiocarbon-dated remains have provided novel insights into the history of Late Pleistocene populations. However, genotyping of loci from the nuclear genome may provide enhanced resolution of population-level changes. Here, we use four autosomal microsatellite DNA markers to investigate the demographic history of woolly mammoths (Mammuthus primigenius) in north-eastern Siberia from before 60 000 years ago up until the species' final disappearance c.4000 years ago. We identified two genetic groups, implying a marked temporal genetic differentiation between samples with radiocarbon ages older than 12 thousand radiocarbon years before present (ka) and those younger than 9ka. Simulation-based analysis indicates that this dramatic change in genetic composition, which included a decrease in individual heterozygosity of approximately 30%, was due to a multifold reduction in effective population size. A corresponding reduction in genetic variation was also detected in the mitochondrial DNA, where about 65% of the diversity was lost. We observed no further loss in genetic variation during the Holocene, which suggests a rapid final extinction event.

Understanding and estimating effective population size for practical application in marine species management

Effective population size (N(e)) determines the strength of genetic drift in a population and has long been recognized as an important parameter for evaluating conservation status and threats to genetic health of populations. Specifically, an estimate of N(e) is crucial to management because it integrates genetic effects with the life history of the species, allowing for predictions of a population's current and future viability. Nevertheless, compared with ecological and demographic parameters, N(e) has had limited influence on species management, beyond its application in very small populations. Recent developments have substantially improved N(e) estimation; however, some obstacles remain for the practical application of N(e) estimates. For example, the need to define the spatial and temporal scale of measurement makes the concept complex and sometimes difficult to interpret. We reviewed approaches to estimation of N(e) over both long-term and contemporary time frames, clarifying their interpretations with respect to local populations and the global metapopulation. We describe multiple experimental factors affecting robustness of contemporary N(e) estimates and suggest that different sampling designs can be combined to compare largely independent measures of N(e) for improved confidence in the result. Large populations with moderate gene flow pose the greatest challenges to robust estimation of contemporary N(e) and require careful consideration of sampling and analysis to minimize estimator bias. We emphasize the practical utility of estimating N(e) by highlighting its relevance to the adaptive potential of a population and describing applications in management of marine populations, where the focus is not always on critically endangered populations. Two cases discussed include the mechanisms generating N(e) estimates many orders of magnitude lower than census N in harvested marine fishes and the predicted reduction in N(e) from hatchery-based population supplementation.

Historical sampling reveals dramatic demographic changes in western gorilla populations

BACKGROUND

Today many large mammals live in small, fragmented populations, but it is often unclear whether this subdivision is the result of long-term or recent events. Demographic modeling using genetic data can estimate changes in long-term population sizes while temporal sampling provides a way to compare genetic variation present today with that sampled in the past. In order to better understand the dynamics associated with the divergences of great ape populations, these analytical approaches were applied to western gorillas (Gorilla gorilla) and in particular to the isolated and Critically Endangered Cross River gorilla subspecies (G. g. diehli).

RESULTS

We used microsatellite genotypes from museum specimens and contemporary samples of Cross River gorillas to infer both the long-term and recent population history. We find that Cross River gorillas diverged from the ancestral western gorilla population ~17,800 years ago (95% HDI: 760, 63,245 years). However, gene flow ceased only ~420 years ago (95% HDI: 200, 16,256 years), followed by a bottleneck beginning ~320 years ago (95% HDI: 200, 2,825 years) that caused a 60-fold decrease in the effective population size of Cross River gorillas. Direct comparison of heterozygosity estimates from museum and contemporary samples suggests a loss of genetic variation over the last 100 years.

CONCLUSIONS

The composite history of western gorillas could plausibly be explained by climatic oscillations inducing environmental changes in western equatorial Africa that would have allowed gorilla populations to expand over time but ultimately isolate the Cross River gorillas, which thereafter exhibited a dramatic population size reduction. The recent decrease in the Cross River population is accordingly most likely attributable to increasing anthropogenic pressure over the last several hundred years. Isolation of diverging populations with prolonged concomitant gene flow, but not secondary admixture, appears to be a typical characteristic of the population histories of African great apes, including gorillas, chimpanzees and bonobos.