Assessing population genetic structure and variability with RAPD data: Application to Vaccinium macrocarpon (American Cranberry)

A method for estimating and comparing population genetic variation using random amplified polymorphic DNA (RAPD) profiling is presented. An analysis of molecular variance (AMOVA) is extended to accomodate phenotypic molecular data in diploid populations in Hardy-Weinberg equilibrium or with an assumed degree of selfing. We present a two step strategy: 1) Estimate RAPD site frequencies without preliminary assumptions on the unknown population structure, then perform significance testing for population substructuring. 2) If population structure is evident from the first step, use this data to calculate better estimates for RAPD site frequencies and sub-population variance components. A nonparametric test for the homogeneity of molecular variance (HOMOVA) is also presented. This test was designed to statistically test for differences in intrapopulational molecular variances (heteroscedasticity among populations). These theoretical developments are applied to a RAPD data set in Vaccinium macrocarpon (American cranberry) using small sample sizes, where a gradient of molecular diversity is found between central and marginal populations. The AMOVA and HOMOVA methods provide flexible population analysis tools when using data from RAPD or other DNA methods that provide many polymorphic markers with or without direct allelic data.     

Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations

Thanks to genome‐scale diversity data, present‐day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up‐to‐date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self‐fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotype–environment correlations and five designed to detect adaptive differentiation (based on F_ST or similar measures). We show that genotype–environment correlation methods have substantially more power to detect selection than differentiation‐based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotype–environment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations.     

Genetic analyses of the Asian longhorned beetle (Coleoptera,Cerambycidae, <Emphasis Type="Italic">Anoplophora glabripennis</Emphasis>), in North America,Europe and Asia

The Asian longhorned beetle, (Coleoptera, Cerambycidae, Anoplophora glabripennis (Motschulsky)), is endemic to China and Korea and an important invasive insect in North America and Europe. We analyzed mitochondrial DNA sequence data of invasive populations of A. glabripennis in North America and Europe, and microsatellite allele frequency data of beetles from North America. We show that populations in New York City and Long Island NY; New Jersey, Chicago, IL, and Toronto, Canada have limited genetic diversity compared to populations in China. In addition, the data suggest that separate introduction events were responsible for many of the populations in North America and for European populations in Austria, France, Germany and Italy. Populations on Long Island, NY are suspected to have been initiated by the transport of cut wood from New York City. A. glabripennis beetles found in Jersey City, NJ appear to be derived from an expansion of the New York City, NY population, whereas beetles found in Linden, NJ are an expansion from the Carteret, NJ population. Limited genetic diversity did not stop this invasive insect from establishing damaging populations in North America. Founders of introduced A. glabripennis populations in North America and Europe are likely derived from populations in China that are themselves invasive, rendering difficult the identification of source populations. Invasiveness in an insect’s natural range could be an important predictor of potential pest status of introduced populations.     

Development of Genotyping Methods for Single Nucleotide Polymorphism in the Human Pancreatic Ribonuclease Gene (RNASE1) and Their Application to Population Studies

Two potential single nucleotide polymorphisms [SNPs; rs1804215 (G979T) and rs11545379 (G1169T)] have been identified in the human pancreatic ribonuclease, RNase 1, gene (RNASE1) that could give rise to an amino acid substitution in the protein, but relevant population data are not available. We have developed genotyping methods for each SNP using the mismatched PCR-restriction fragment length polymorphism technique. These methods are advantageous in comparison with other SNP genotyping methods because they are technically simpler and do not require specialized instruments. We applied these genotyping methods to examine the genotype distribution of each SNP in four populations, including Japanese populations living in two prefectures, an Ovambo population, and a Turkish population. In all the populations studied, however, only a single genotype for each SNP was found. Therefore, irrespective of differences in ethnic groups, RNASE1 might show markedly low heterogeneity in its genetic structure with regard to these SNPs.     

Population Differentiation in a Complex Bird Sound: A Comparison of Three Bioacoustical Analysis Procedures

We examined three bioacoustical analysis methods for comparing complex sounds among different populations. We chose the D‐syllable of the chick‐a‐dee call of the black‐capped chickadee (Poecile atricapilla) because it is a broadband sound representative of a class of vocalizations, common in many animals, that resists simple subjective classification for comparative studies. We examined the properties of the D‐syllable in field‐recorded samples from three different populations. The first method of data extraction sampled the amplitude values of a spectrum obtained in a single fast Fourier transform (SFFT) taken at the midpoint of each D‐syllable using multi‐speech software. The second method employed spectrogram cross‐correlation (SPCC) to obtain a matrix of similarity values between D‐syllables in the samples using canary software. The third method calculated similarity values obtained from the evaluation of four acoustic features of the D‐syllables derived from multi‐taper spectral analysis (MTSA) using sound analysis software. Following data extraction by these three techniques, we used multivariate statistical procedures to reduce the data for examination of differences among populations and to represent in scatter‐plots the patterns of clustering of the sounds. We found that the SFFT in the middle of the D‐syllable provided the poorest population discrimination following statistical processing, the SPCC method produced the next clearest population separation, and the MTSA method resulted in the most distinct separation of the three populations of D‐syllables. In carrying out these comparisons, we discovered that the characteristic environmental noise of a recording area can influence the signal properties of broadband sounds being compared by automated procedures, and could lead to faulty conclusions unless appropriate care is taken to mitigate the noise in which the signals of interest are embedded. Consequently we re‐analyzed our data following noise reduction and found less discrete population separation overall. However, the methods of SPCC and MTSA retained the ability to separate populations, with MTSA providing the sharpest discrimination among groups.     

Genomic inference accurately predicts the timing and severity of a recent bottleneck in a nonmodel insect population

The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all‐in‐one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.     

Modelling urban populations of the Australian White Ibis (Threskiornis molucca) to inform management

Since the 1970s, populations of the Australian White Ibis (Threskiornis molucca) have dramatically increased in many Australian urban centres. Managers of ibis are currently focusing on limiting this bird's reproductive success in order to reduce population sizes or at least halt further increases in urban areas. Here we use data on nesting success and survival for three populations of ibis around greater Sydney to develop an age-structured population model. The estimated growth rate for all populations combined was about 1.5 % per year and for individual sites were more variable at −1, −7, and 9 %. For all populations, growth rates were most sensitive (based on elasticity analyses) to the survival of adults and least sensitive to fecundity, especially of 3 year olds. Further exploration of the importance of fecundity rates, which are relatively poorly known for these populations, suggests that rates of <0.4 fledglings per nest per year is very likely to lead to a population decline (λ less than lower bound of 95 % CI). Conversely, positive population growth is nearly assured (λ greater than upper bound of 95 % CI) for fecundities of >0.7 fledgling per nest per year. The results suggest that ibis from other locations (probably their traditional breeding areas in inland Australia) have immigrated into urban environments as estimated growth rates cannot account for current population sizes. Management strategies must take these findings into account and also consider that ibis are declining in their traditional habitats to avoid exacerbating their decline at a regional scale.     

QUANTIFYING THE PLEISTOCENE HISTORY OF THE OAK GALL PARASITOID CECIDOSTIBA FUNGOSA USING TWENTY INTRON LOCI

The longitudinal spread of temperate organisms into refugial populations in Southern Europe is generally assumed to predate the last interglacial. However, few studies have attempted to quantify this process in nonmodel organisms using explicit models and multilocus data. We used sequence data for 20 intron‐spanning loci (12 kb per individual) to resolve the history of refugial populations of a widespread western Palaearctic oak gall parasitoid Cecidostiba fungosa (Pteromalidae). Using maximum likelihood and Bayesian methods we assess alternative population tree topologies and estimate divergence times and ancestral population sizes under a model of divergence between three refugia (Middle East, Balkans and Iberia). Both methods support an “Out of the East” history for C. fungosa, matching the pattern previously inferred for their gallwasp hosts. However, coalescent‐based estimates of the ages of population divides are much more recent (coinciding with the Eemian interglacial) than nodal ages of single gene trees for C. fungosa and other species. We also find that increasing the sample size from one haploid sequence per refugial population to three only marginally improves parameter estimates. Our results suggest that there is significant information in the minimal samples currently analyzable with maximum likelihood methods, and that similar methods could be applied to multiple species to test alternative models of assemblage evolution.     

Association Tests for a Censored Quantitative Trait and Candidate Genes in Structured Populations with Multilevel Genetic Relatedness

Summary Several statistical methods for detecting associations between quantitative traits and candidate genes in structured populations have been developed for fully observed phenotypes. However, many experiments are concerned with failure‐time phenotypes, which are usually subject to censoring. In this article, we propose statistical methods for detecting associations between a censored quantitative trait and candidate genes in structured populations with complex multiple levels of genetic relatedness among sampled individuals. The proposed methods correct for continuous population stratification using both population structure variables as covariates and the frailty terms attributable to kinship. The relationship between the time‐at‐onset data and genotypic scores at a candidate marker is modeled via a parametric Weibull frailty accelerated failure time (AFT) model as well as a semiparametric frailty AFT model, where the baseline survival function is flexibly modeled as a mixture of Polya trees centered around a family of Weibull distributions. For both parametric and semiparametric models, the frailties are modeled via an intrinsic Gaussian conditional autoregressive prior distribution with the kinship matrix being the adjacency matrix connecting subjects. Simulation studies and applications to the Arabidopsis thaliana line flowering time data sets demonstrated the advantage of the new proposals over existing approaches.     

Second-order feedback and climatic effects determine the dynamics of a small rodent population in a temperate forest of South America

 The multiannual cyclic fluctuations exhibited by arvicoline rodents in the Northern Hemisphere have attracted the attention of population ecologists. However, despite the abundant information on small rodent dynamics in South America, there are no studies reporting cyclic population dynamics. Here, we report evidence of cyclic population dynamics in a South American small rodent, the longhaired field mouse (Abrothrix longipilis) from southern temperate forests in Chile. The time-series analyses showed that longhaired field mice dynamics are better represented by a second-order autoregressive model characterized by 3-year cyclic dynamics. The 3-year cycles are clearly shown in the autocorrelation factor (ACF) pattern and in the dominant frequency of the spectral analysis. In addition, we determined nonlinear effects of the Antarctic Oscillation Index (AAOI). The results shown here pointed out that we need the integration of studies about cyclic small rodent populations from the different continents and beyond the Northern Hemisphere to resolve the enigma underlying the cyclic population dynamics exhibited by many small rodent species. Received: September 19, 2002 / Accepted: February 4, 2003     

Evaluating methods for estimating local effective population size with and without migration

Effective population size is a fundamental parameter in population genetics, evolutionary biology, and conservation biology, yet its estimation can be fraught with difficulties. Several methods to estimate N_e from genetic data have been developed that take advantage of various approaches for inferring N_e. The ability of these methods to accurately estimate N_e, however, has not been comprehensively examined. In this study, we employ seven of the most cited methods for estimating N_e from genetic data (Colony2, CoNe, Estim, MLNe, ONeSAMP, TMVP, and NeEstimator including LDNe) across simulated datasets with populations experiencing migration or no migration. The simulated population demographies are an isolated population with no immigration, an island model metapopulation with a sink population receiving immigrants, and an isolation by distance stepping stone model of populations. We find considerable variance in performance of these methods, both within and across demographic scenarios, with some methods performing very poorly. The most accurate estimates of N_e can be obtained by using LDNe, MLNe, or TMVP; however each of these approaches is outperformed by another in a differing demographic scenario. Knowledge of the approximate demography of population as well as the availability of temporal data largely improves N_e estimates.     

Simultaneous Selection of Extreme Populations: A Subset Selection Approach

The problem of selecting a “best” (largest mean, or smallest mean) population from a collection of k independent populations was formulated and solved by Bechhofer (1954). Gupta (1965) solved another important problem, that of selecting a subset of populations containing the “best” population from the original collection of populations. Since then many variations of the problem have been considered. Tong (1969) and Lewis (1980) have investigated the problem of selecting extreme populations (populations with a largest, and populations with a smallest, mean) with respect to one and two standard populations, respectively. In this paper we study the selection of extreme populations in absence of any standard population. We formulate subset-selection procedures when variances are known and equal, and also in the most general case when they are unknown and unequal. Nonexistence of a single-stage procedure is noted for this latter case (even if variances are equal). A two-stage procedure and some of its associated properties are discussed. Tables needed for application are provided, as is a worked example.     

Genetic Structure of Przewalski’s Rock Partridge (Alectoris magna) Populations in the Longzhong Loess Plateau, China

In this paper, we have analyzed the nuclear DNA of Alectoris magna samples, collected from the Longzhong Loess Plateau. We used allelic variation at eight microsatellite markers to describe the genetic structure of A. magna populations. The primary goal of this study was to examine the population genetic structure and determine the extent of population differentiation among populations of A. magna. The average value of H _E (0.455) was smaller than H _O (0.477), and there was a heterozygote deficit at the MCW135 locus in the Lanzhou population and the Beidao population. The AB063167 locus in each population (except that of Jingyuan) was not in equilibrium (P < 0.05). The Lixian edge population had a lower proportion of genetic diversity than the central geographic populations; the Haiyuan and Jingyuan populations had higher genetic diversity than the central geographic populations. Analysis of population structure revealed clear differentiation among the eight populations of A. magna, suggesting strong isolation of these populations and correspondingly low levels of migration or gene flow. The A. magna populations of Longzhong Loess Plateau are separated into eastern and western populations by a clustering chart. Genetic data indeed suggest that patterns of speciation and population diversification of A. magna in the Longzhong Plateau have been affected by the stability of the climate, natural selection, and human intervention.     

Genome‐wide single nucleotide polymorphisms reveal population history and adaptive divergence in wild guppies

Adaptation of guppies (Poecilia reticulata) to contrasting upland and lowland habitats has been extensively studied with respect to behaviour, morphology and life history traits. Yet population history has not been studied at the whole‐genome level. Although single nucleotide polymorphisms (SNPs) are the most abundant form of variation in many genomes and consequently very informative for a genome‐wide picture of standing natural variation in populations, genome‐wide SNP data are rarely available for wild vertebrates. Here we use genetically mapped SNP markers to comprehensively survey genetic variation within and among naturally occurring guppy populations from a wide geographic range in Trinidad and Venezuela. Results from three different clustering methods, Neighbor‐net, principal component analysis (PCA) and Bayesian analysis show that the population substructure agrees with geographic separation and largely with previously hypothesized patterns of historical colonization. Within major drainages (Caroni, Oropouche and Northern), populations are genetically similar, but those in different geographic regions are highly divergent from one another, with some indications of ancient shared polymorphisms. Clear genomic signatures of a previous introduction experiment were seen, and we detected additional potential admixture events. Headwater populations were significantly less heterozygous than downstream populations. Pairwise F_ST values revealed marked differences in allele frequencies among populations from different regions, and also among populations within the same region. F_ST outlier methods indicated some regions of the genome as being under directional selection. Overall, this study demonstrates the power of a genome‐wide SNP data set to inform for studies on natural variation, adaptation and evolution of wild populations     

Variation between laboratory populations in the performance of the parasitoid Encarsia formosa on two host species, Bemisia tabaci and Trialeurodes vaporariorum

We tested the hypothesis that populations of the parthenogenetic parasitic wasp Encarsia formosa Gahan (Hymenoptera: Aphelinidae) differed in their ability to use two different host species, Bemisia tabaci Gennadius (Homoptera: Aleyrodidae) and Trialeurodes vaporariorum Westwood (Homoptera: Aleyrodidae). Of the three wasp populations tested, two populations had been reared for many generations on B. tabaci and one population had been reared for many years on T. vaporariorum. Performance was measured by the number of whitefly nymphs that were successfully parasitized by individual wasps, and performance on either host was measured in separate experiments. There was variation between wasp populations in their performance on the host B. tabaci, with one wasp population reared for many years on this host performing considerably better than the other two populations. There were no significant differences between populations in their use of the preferred host, T. vaporariorum. The experiments were conducted in such a way that we could distinguish heritable differences between populations from environmentally-induced conditioning differences due to the immediate host from which an individual wasp enclosed. In either experiment there were no significant effects of conditioning, although there was a trend within each population for wasps conditioned on T. vaporariorum to have higher performance than those conditioned on B. tabaci. Thirdly, we conducted a selection experiment, initiated with wasps from a single population historically reared on T. vaporariorum, to measure the effect of laboratory rearing on different hosts for 17 generations. We did not see any difference in the performance of wasps on B. tabaci after this period of rearing on either of the two hosts. In summary, populations of E. formosa do differ in their relative performance on B. tabaci. The one population that was tested further did not show any response to selection by rearing, but the ability to respond to selection on performance may not be equal for all populations. The possibility that wasp populations have differential performance on particular hosts may affect the use of this species as a biological control agent.     

Estimation of migration rates from marker‐based parentage analysis

Coupled with rapid developments of efficient genetic markers, powerful population genetic methods were proposed to estimate migration rates (m) in natural populations in much broader spatial and temporal scales than the traditional mark‐release‐recapture (MRR) methods. Highly polymorphic (e.g. microsatellites) and genomic‐wide (e.g. SNPs) markers provide sufficient information to assign individuals to their populations or parents of origin and thereby to estimate directly m in a way similar to MRR. Such direct estimates of current migration rates are particularly useful in understanding the ecology and microevolution of wild populations and in managing the populations in the future. In this study, I proposed and implemented, in the software MigEst, a likelihood method to use marker‐based parentage assignments in jointly estimating m and candidate parent sampling proportions (x) in a subset of populations, investigated its power and accuracy using data simulated in various scenarios of population properties (e.g. the actual m, number, size and differentiation of populations) and sampling properties (e.g. the numbers of sampled parent candidates, offspring and markers), compared it with the population assignment approach implemented in the software BayesAss and demonstrated its usefulness by analysing a microsatellite data set from three natural populations of Brazilian bats. Simulations showed that MigEst provides unbiased and accurate estimates of m and performs better than BayesAss except when populations are highly differentiated with very small and ecologically insignificant migration rates. A valuable property of MigEst is that in the presence of unsampled populations, it gives good estimates of the rate of migration among sampled populations as well as of the rate of migration into each sampled population from the pooled unsampled populations.     

Zinc tolerance in populations ofDeschampsia cespitosa (Gramineae) beneath electricity pylons

Patterns of zinc tolerance were examined in eightDeschampsia cespitosa (L.)Beauv. populations from normal and zinc-contaminated soils, using solution culture methods. Zinc-tolerant populations have evolved beneath pylons, and their tolerance patterns (degree, variance, heritability) vary. Tolerance is genetically based in all of them. In contrast to the cases of other species previously reported, some within-population differences are considerable, and may be due to both heterogeneity of the soils zinc contents, various gene combinations and gene recombinations between genotypes. One control population contains many tolerant plants, an original result which is discussed.     

Advertisement calls of the midwife toads Alytes (Amphibia, Anura, Discoglossidae) in continental Spain

The advertisement calls of six Spanish populations of midwife toads (genus Alytes) are described presenting characteristic audiospectrograms and oscillograms of the calls. Numerical data concerning the spectral and temporal features of the calls in relation to caller size (SVL) and temperature are also compared. The regression temperature vs. call duration groups the different populations according to the extant recognized phylogeny of the genus. Based on this character, the montane population of A. obstetricans from Penalara (Madrid) appears to be more closely related to the Pyrenean populations of A. o. almogavarü than to the more western populations of A. oboscai in Central Spain, which are closer geographically.     

POLYPHYLETIC ORIGINS OF ASEXUALITY IN DAPHNIA PULEX. II. MITOCHONDRIAL-DNA VARIATION

Allozyme studies of the cladoceran Daphnia pulex have shown that most populations reproduce by obligate parthenogenesis, although some cyclically parthenogenetic populations remain throughout the southern portion of its range. Clonal diversity within the obligate parthenogens is extremely high and has been attributed to the polyphyletic origin of asexuality. Specifically, it has been proposed that the clonal diversity in the obligate parthenogens was generated via the spread of a sex-limited meiosis suppressor through populations of a cyclically parthenogenetic ancestor. In this study, analysis of polymorphism of restriction-endonuclease sites in the mitochondrial genome, in conjunction with allozyme analysis, was used to determine whether obligate parthenogenesis has a monophyletic or polyphyletic origin in D. pulex. An allozyme survey of 77 populations from Ontario and Michigan was first conducted to determine breeding systems and levels of clonal diversity (Hebert et al., 1989). Mitochondrial-DNA variation was then surveyed in one isolate of each clone from each population reproducing by obligate parthenogenesis and in 2–4 isolates from each population reproducing by cyclic parthenogenesis. Seventeen restriction enzymes were used in this analysis. Thirty-five mitochondrial genotypes were found among the 36 obligate clones (as identified by allozyme analysis), while 17 mitochondrial genotypes were identified among 40 cyclic isolates from 14 populations. Five mitochondrial genotypes were found in both groups. Parsimony and phenetic-clustering methods were used to construct trees showing the genetic relationship among mitochondrial genotypes. The results clearly show that obligate parthenogenesis had a polyphyletic origin in this species. The close relationship between cyclic and obligate parthenogens in the Great Lakes region suggests that many obligate clones have recently been derived from cyclic populations and that the generation of clones is still occurring in this area. Patterns of clonal diversity based on the joint consideration of allozyme and mitochondrial-DNA data are discussed.     

Evaluation of model fit of inferred admixture proportions

Model based methods for genetic clustering of individuals, such as those implemented in structure or ADMIXTURE, allow the user to infer individual ancestries and study population structure. The underlying model makes several assumptions about the demographic history that shaped the analysed genetic data. One assumption is that all individuals are a result of K homogeneous ancestral populations that are all well represented in the data, while another assumption is that no drift happened after the admixture event. The histories of many real world populations do not conform to that model, and in that case taking the inferred admixture proportions at face value might be misleading. We propose a method to evaluate the fit of admixture models based on estimating the correlation of the residual difference between the true genotypes and the genotypes predicted by the model. When the model assumptions are not violated, the residuals from a pair of individuals are not correlated. In the case of a bad fitting admixture model, individuals with similar demographic histories have a positive correlation of their residuals. Using simulated and real data, we show how the method is able to detect a bad fit of inferred admixture proportions due to using an insufficient number of clusters K or to demographic histories that deviate significantly from the admixture model assumptions, such as admixture from ghost populations, drift after admixture events and nondiscrete ancestral populations. We have implemented the method as an open source software that can be applied to both unphased genotypes and low depth sequencing data.