Efficiency of allele frequency‐based bayesian programmes for detecting hybridization between farmed and wild salmon

Large escapes of cultured salmon from net‐pens have become inevitable disasters linked to the growth of aquaculture in coastal areas. Hybridization between farmed and wild salmon has been witnessed; but the extent of eventual genetic introgression is controversial as selection against hybrids can maintain distinct gene pools. Individual assignment tests based on genetic data have been widely used in fisheries, due to the importance of accurate population assignment for a variety of purposes including distinction between individuals of native and stocked origin. However the ability of these Bayesian programs to detect hybrids and subsequent generations between closely related populations has been little investigated. Here we present results regarding the efficiency of two new computer programs, structure and New Hybrids in detecting hybridization between farmed and wild salmon from the river Teno (Northern Europe) based on genetic data obtained from 17 microsatellite loci.     

Fine-scale genetic structure of a long-lived reptile reflects recent habitat modification

Anthropogenic habitat fragmentation — ubiquitous in modern ecosystems — has strong impacts on gene flow and genetic population structure. Reptiles may be particularly susceptible to the effects of fragmentation because of their extreme sensitivity to environmental conditions and limited dispersal. We investigate fine-scale spatial genetic structure, individual relatedness, and sex-biased dispersal in a large population of a long-lived reptile (tuatara, Sphenodon punctatus) on a recently fragmented island. We genotyped individuals from remnant forest, regenerating forest, and grassland pasture sites at seven microsatellite loci and found significant genetic structuring (R_ST = 0.012) across small distances (< 500 m). Isolation by distance was not evident, but rather, genetic distance was weakly correlated with habitat similarity. Only individuals in forest fragments were correctly assignable to their site of origin, and individual pairwise relatedness in one fragment was significantly higher than expected. We did not detect sex-biased dispersal, but natural dispersal patterns may be confounded by fragmentation. Assignment tests showed that reforestation appears to have provided refuges for tuatara from disturbed areas. Our results suggest that fine-scale genetic structuring is driven by recent habitat modification and compounded by the sedentary lifestyle of these long-lived reptiles. Extreme longevity, large population size, simple social structure and random dispersal are not strong enough to counteract the genetic structure caused by a sedentary lifestyle. We suspect that fine-scale spatial genetic structuring could occur in any sedentary species with limited dispersal, making them more susceptible to the effects of fragmentation.     

The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis

The inference of population genetic structures is essential in many research areas in population genetics, conservation biology and evolutionary biology. Recently, unsupervised Bayesian clustering algorithms have been developed to detect a hidden population structure from genotypic data, assuming among others that individuals taken from the population are unrelated. Under this assumption, markers in a sample taken from a subpopulation can be considered to be in Hardy-Weinberg and linkage equilibrium. However, close relatives might be sampled from the same subpopulation, and consequently, might cause Hardy-Weinberg and linkage disequilibrium and thus bias a population genetic structure analysis. In this study, we used simulated and real data to investigate the impact of close relatives in a sample on Bayesian population structure analysis. We also showed that, when close relatives were identified by a pedigree reconstruction approach and removed, the accuracy of a population genetic structure analysis can be greatly improved. The results indicate that unsupervised Bayesian clustering algorithms cannot be used blindly to detect genetic structure in a sample with closely related individuals. Rather, when closely related individuals are suspected to be frequent in a sample, these individuals should be first identified and removed before conducting a population structure analysis.     

Isolation by resistance across a complex coral reef seascape

A detailed understanding of the genetic structure of populations and an accurate interpretation of processes driving contemporary patterns of gene flow are fundamental to successful spatial conservation management. The field of seascape genetics seeks to incorporate environmental variables and processes into analyses of population genetic data to improve our understanding of forces driving genetic divergence in the marine environment. Information about barriers to gene flow (such as ocean currents) is used to define a resistance surface to predict the spatial genetic structure of populations and explain deviations from the widely applied isolation-by-distance model. The majority of seascape approaches to date have been applied to linear coastal systems or at large spatial scales (more than 250 km), with very few applied to complex systems at regional spatial scales (less than 100 km). Here, we apply a seascape genetics approach to a peripheral population of the broadcast-spawning coral Acropora spicifera across the Houtman Abrolhos Islands, a high-latitude complex coral reef system off the central coast of Western Australia. We coupled population genetic data from a panel of microsatellite DNA markers with a biophysical dispersal model to test whether oceanographic processes could explain patterns of genetic divergence. We identified significant variation in allele frequencies over distances of less than 10 km, with significant differentiation occurring between adjacent sites but not between the most geographically distant ones. Recruitment probabilities between sites based on simulated larval dispersal were projected into a measure of resistance to connectivity that was significantly correlated with patterns of genetic divergence, demonstrating that patterns of spatial genetic structure are a function of restrictions to gene flow imposed by oceanographic currents. This study advances our understanding of the role of larval dispersal on the fine-scale genetic structure of coral populations across a complex island system and applies a methodological framework that can be tailored to suit a variety of marine organisms with a range of life-history characteristics.     

Spatial genetic structure of a small rodent in a heterogeneous landscape

Gene flow in natural populations may be strongly influenced by landscape features. The integration of landscape characteristics in population genetic studies may thus improve our understanding of population functioning. In this study, we investigated the population genetic structure and gene flow pattern for the common vole, Microtus arvalis, in a heterogeneous landscape characterised by strong spatial and temporal variation. The studied area is an intensive agricultural zone of approximately 500 km² crossed by a motorway. We used individual-based Bayesian methods to define the number of population units and their spatial borders without prior delimitation of such units. Unexpectedly, we determined a single genetic unit that covered the entire area studied. In particular, the motorway considered as a likely barrier to dispersal was not associated with any spatial genetic discontinuity. Using computer simulations, we demonstrated that recent anthropogenic barriers to effective dispersal are difficult to detect through analysis of genetic variation for species with large effective population sizes. We observed a slight, but significant, pattern of isolation by distance over the whole study site. Spatial autocorrelation analyses detected genetic structuring on a local scale, most probably due to the social organisation of the study species. Overall, our analysis suggests intense small-scale dispersal associated with a large effective population size. High dispersal rates may be imposed by the strong spatio-temporal heterogeneity of habitat quality, which characterises intensive agroecosystems.     

Population structure and eigenanalysis

Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like F_ST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.     

Evaluating the ability of Bayesian clustering methods to detect hybridization and introgression using an empirical red wolf data set

Bayesian clustering methods have emerged as a popular tool for assessing hybridization using genetic markers. Simulation studies have shown these methods perform well under certain conditions; however, these methods have not been evaluated using empirical data sets with individuals of known ancestry. We evaluated the performance of two clustering programs, baps and structure , with genetic data from a reintroduced red wolf (Canis rufus) population in North Carolina, USA. Red wolves hybridize with coyotes (C. latrans), and a single hybridization event resulted in introgression of coyote genes into the red wolf population. A detailed pedigree has been reconstructed for the wild red wolf population that includes individuals of 50–100% red wolf ancestry, providing an ideal case study for evaluating the ability of these methods to estimate admixture. Using 17 microsatellite loci, we tested the programs using different training set compositions and varying numbers of loci. structure was more likely than baps to detect an admixed genotype and correctly estimate an individual's true ancestry composition. However, structure was more likely to misclassify a pure individual as a hybrid. Both programs were outperformed by a maximum‐likelihood‐based test designed specifically for this system, which never misclassified a hybrid (50–75% red wolf) as a red wolf or vice versa. Training set composition and the number of loci both had an impact on accuracy but their relative importance varied depending on the program. Our findings demonstrate the importance of evaluating methods used for detecting admixture in the context of endangered species management.     

Genetic diversity and population structure of Eugenia dysenterica DC. (``cagaiteira' – Myrtaceae) in Central Brazil: Spatial analysis and implications for conservation and management

Studies about the organization of the genetic variability and population structure in natural plant populations are used to support conservation and management programs. Among the Cerrado fruit tree species that possess potential economic importance in agriculture, the “Cagaiteira” (Eugenia dysenterica DC. – Myrtaceae), deserves an special position. We obtained information about allele and genotypic frequencies in 10 local populations, situated up to 250 km apart, from six isozymes that furnished a total of 8 loci. The average within-population fixation index (f) was 0.337, and the out crossing rate was 0.835, suggesting a mixed mating system for this species, which seems to be preferably alogamous. Based on genetic diversity and analysis of variance techniques, a high degree of population differentiation (θ_P = 0.154) was found, in comparison with other tropical tree species. Genetic divergence, analyzed by Nei's genetic distances, clustered with UPGMA and ordinated by non-metric multidimensional scaling, showed spatial patterns of clusters of local populations. Explicit spatial analyses, using Mantel tests and boundary tests, basically confirmed these patterns and revealed a complex pattern of genetic variation in geographic space. The intercept of the multivariate spatial correlograms was around 120 km, an indication of the minimum distance between samples needed to conserve genetic diversity among samples. This spatial scale can be used to define population genetics units for conservation programs or to establish sampling strategies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Genetic structures and linguistic boundaries in Italy: a microregional approach.

The amount of genetic data (sequences, gene frequencies, and isonymy) available for the Province of Ferrara, Italy, makes this area one of the world's best known. In an effort to infer the underlying demographic processes, we studied the province's population structure by comparing geological, palaeoclimatic, archeological, historical, and linguistic data. This multilevel approach allowed us to date some characteristics of the population structure from prehistoric times to the Roman and Middle Ages, and to detect overlapping biological, cultural, and geographic boundaries. To detect linguistic boundaries within this area we turned pronunciation differences into phonetic notation. We then computed pairwise distances by using methods for multiple genetic sequence analysis, in order to obtain a distance matrix of the overall pronunciation variability. This approach enabled us to test the association among linguistic, geographical, and genetic distance matrices using the same statistical tests. Results indicate that demographic phenomena can be traced in an area as small as the Province of Ferrara and that, on a microregional scale, recent events may have influenced important aspects of the overall genetic variation.     

Assumed and inferred spatial structure of populations: the Scandinavian brown bears revisited

We reanalysed the spatial structure of the Scandinavian brown bear (Ursus arctos) population based on multilocus genotypes. We used data from a former study that had presumed a priori a specific population subdivision based on four subpopulations. Using two independent methods (neighbour-joining trees and Bayesian assignment tests), we analysed the data without any prior presumption about the spatial structure. A subdivision of the population into three subpopulations emerged from our study. The genetic pattern of these subpopulations matched the three geographical clusters of individuals present in the population. We recommend considering the Scandinavian brown bear population as consisting of three (instead of four) subpopulations. Our results underline the importance of determining genetic structure from the data, without presupposing a structure, even when there seems to be good reason to do so.     

Genetic structure of the critically endangered endemic Cochlearia polonica (Brassicaceae): efficiency of the last-chance transplantation

Cochlearia polonica , a narrow endemic of southern Poland, is one of the rarest and most endangered species of the European flora. All natural populations are extinct and the species has survived in only one transplanted population derived from 14 original individuals. Using AFLPs, the genetic variation and spatial structure of this population were analysed approximately 30 years after transplantation. The incidence of polymorphic AFLP bands (30.46%) is low compared with data from a natural population of another Cochlearia species, C. tatrae . Principal co-ordinates and spatial autocorrelation analyses demonstrated the presence of significant genetic structure. It is recommended that conservation efforts on C. polonica should preserve the complete population area, because local extinctions may lead to a loss of genetic information. The presence of genetic structure should also be taken into account during the sampling of material (plants or seeds) for ex situ conservation measures.  © 2007 The Linnean Society of London, Botanical Journal of the Linnean Society , 2007, 155 , 527–532.     

人类群体遗传空间结构的"克立格"模型

通过将“克立格”技术应用于人类群体遗传学领域,构建了人类群体遗传空间结构的“克立格”模型,并论述了其原理和计算方法。以HLA-A基因座为例,应用“克立格”模型,定量分析了中国人群HLA-A基因座的空间遗传异质性;对HLA-A基因频率的空间数据矩阵进行了主成分分析,进而定义了人类群体遗传结构的综合遗传测度(SPC),绘制了综合遗传测度和主成分(PC)的“克立格”地图,分析了其群体遗传空间结构特性。与其他空间插值或平滑方法相比,人类群体遗传空间结构的“克立格”模型具有明显优点：1)“克立格”估计以空间遗传变异函数模型为基础,在绘制空间遗传结构地图之前,可利用变异函数模型定量分析所研究基因座(或多基因座)的空间遗传异质性;2)“克立格”插值方法是真正意义上的无偏估计模型,它利用待估区域周围的已知群体遗传调查点数据,并充分考虑调查点的空间影响范围,给出待估区域的最优估计值;3)“克立格”模型允许估计插值误差,这种插值误差既可用于评价空间估计效果,又可通过绘制误差地图指导在误差过高的地点增加新的群体遗传调查样本点,以优化估计效果。然而,人类群体遗传空间结构的“克立格”模型也存在一定缺点：1)若不能用任何理论遗传变异函数模型拟合观察遗传变异函数值,则不能建立“克立格”模型;2)若理论遗传变异函数的拟合优度很低,则据此建立的“克立格”模型的估计标准差在整个空间范围内会很大,此时“克立格”模型不适用于估计群体遗传空间结构。出现上述两种情形时,应选用不考虑空间相关性的空间随机插值方法绘制群体遗传结构地图,如基因绘图软件中的Cavalli-Sforza方法,反向距离加权法和条样函数插值法等。     

Spatial structuring of the population genetics of a European subterranean termite species

In population genetics studies, detecting and quantifying the distribution of genetic variation can help elucidate ecological and evolutionary processes. In social insects, the distribution of population‐level genetic variability is generally linked to colony‐level genetic structure. It is thus especially crucial to conduct complementary analyses on such organisms to examine how spatial and social constraints interact to shape patterns of intraspecific diversity. In this study, we sequenced the mitochondrial COII gene for 52 colonies of the subterranean termite Reticulitermes grassei (Isoptera: Rhinotermitidae), sampled from a population in southwestern France. Three haplotypes were detected, one of which was found exclusively in the southern part of the study area (near the Pyrenees). After genotyping 6 microsatellite loci for 512 individual termites, we detected a significant degree of isolation by distance among individuals over the entire range; however, the cline of genetic differentiation was not continuous, suggesting the existence of differentiated populations. A spatial principal component analysis based on allele frequency data revealed significant spatial autocorrelation among genotypes: the northern and southern groups were strongly differentiated. This finding was corroborated by clustering analyses; depending on the randomized data set, two or three clusters, exhibiting significant degrees of differentiation, were identified. An examination of colony breeding systems showed that colonies containing related neotenic reproductives were prevalent, suggesting that inbreeding may contribute to the high level of homozygosity observed and thus enhance genetic contrasts among colonies. We discuss the effect of evolutionary and environmental factors as well as reproductive and dispersal modes on population genetic structure.     

The use of carcasses for the analysis of cetacean population genetic structure: a comparative study in two dolphin species

Advances in molecular techniques have enabled the study of genetic diversity and population structure in many different contexts. Studies that assess the genetic structure of cetacean populations often use biopsy samples from free-ranging individuals and tissue samples from stranded animals or individuals that became entangled in fishery or aquaculture equipment. This leads to the question of how representative the location of a stranded or entangled animal is with respect to its natural range, and whether similar results would be obtained when comparing carcass samples with samples from free-ranging individuals in studies of population structure. Here we use tissue samples from carcasses of dolphins that stranded or died as a result of bycatch in South Australia to investigate spatial population structure in two species: coastal bottlenose (Tursiops sp.) and short-beaked common dolphins (Delphinus delphis). We compare these results with those previously obtained from biopsy sampled free-ranging dolphins in the same area to test whether carcass samples yield similar patterns of genetic variability and population structure. Data from dolphin carcasses were gathered using seven microsatellite markers and a fragment of the mitochondrial DNA control region. Analyses based on carcass samples alone failed to detect genetic structure in Tursiops sp., a species previously shown to exhibit restricted dispersal and moderate genetic differentiation across a small spatial scale in this region. However, genetic structure was correctly inferred in D. delphis, a species previously shown to have reduced genetic structure over a similar geographic area. We propose that in the absence of corroborating data, and when population structure is assessed over relatively small spatial scales, the sole use of carcasses may lead to an underestimate of genetic differentiation. This can lead to a failure in identifying management units for conservation. Therefore, this risk should be carefully assessed when planning population genetic studies of cetaceans.     

Spatial and demographic population genetic structure in Catasetum viridiflavum across a human-disturbed habitat

Spatial and temporal genetic structures were examined across sites on islands and mainland (continuous forest) populations of an epiphytic orchid, Catasetum viridiflavum, using 17 polymorphic allozyme loci. I tested whether patches on islands or at mainland sites comprised small local populations or a large population. Low among population differentiation was observed across the landscape suggesting that the species-specific pollinator and tiny wind-dispersed seeds maintain interconnections among distant patches. Temporal genetic structure among stage classes, and among breeding individuals are important components of the maintenance of genetic variation in this orchid. The natural history of this species including small breeding populations, probable high frequency of mating among relatives, and the high rates of seed movement among sites contribute to the high FIS. These data show that physically isolated patches in this epiphytic orchid comprise a single larger genetic population, which is independent of the physical distances among sites. Although quite different in ecological and life history characteristics, the genetic structure of this orchid demonstrates a pattern similar to temperate and tropical trees in fragmented landscapes.     

Detecting populations in the 'ambiguous' zone: kinship-based estimation of population structure at low genetic divergence

Identifying population structure is one of the most common and important objectives of spatial analyses using population genetic data. Population structure is detected either by rejecting the null hypothesis of a homogenous distribution of genetic variation, or by estimating low migration rates. Issues arise with most current population genetic inference methods when the genetic divergence is low among putative populations. Low levels of genetic divergence may be as a result of either high ongoing migration or historic high migration but no current, ongoing migration. We direct attention to recent developments in the use of the tempo-spatial distribution of closely related individuals to detect population structure or estimate current migration rates. These 'kinship-based' approaches complement more traditional population-based genetic inference methods by providing a means to detect population structure and estimate current migration rates when genetic divergence is low. However, for kinship-based methods to become widely adopted, formal estimation procedures applicable to a range of species life histories are needed.     

Subpopulation genetic structure of a plant panmictic population of Castanea sequinii as revealed by microsatellite markers

Castanea squinii Dode,an endemic tree widely distributed in China,plays an important role both in chestnut breeding and forest ecosystem function.The spatial genetic structure within and among populations is an important part of the evolutionary and ecological genetic dynamics of natural populations,and can provide insights into effective conservation of genetic resources.In the present study,the spatial genetic structure of a panmictic natural population of C.sequinii in the Dabie Mountain region was investigated using microsatellite markers.Nine prescreened microsatellite loci generated 29-33 alleles each,and were used for spatial autocorrelation analysis.Based on Moran's I coefficient,a panmictic population of C.sequinii in the Dabie Mountain region was found to be lacking a spatial genetic structure.These results suggest that a high pollen-mediated gene flow among subpopulations counteract genetic drift and/or genetic differentiation and plays an important role in maintaining a random and panmictic population structure in C.sequinii populations.Further,a spatial genetic structure was detected in each subpopulation's scale (0.228 km),with all three subpopulations showing significant fine-scale structure.The genetic variation was found to be nonrandomly distributed within 61 m in each subpopulation (Moran's I positive values).Although Moran's I values varied among the different subpopulations,Moran's I in all the three subpopulations reached the expected values with an increase in distances,suggesting a generally patchy distribution in the subpopulations.The fine-scale structure seems to reflect restricted seed dispersal and microenvironment selection in C.sequinii.These results have important implications for understanding the evolutionary history and ecological process of the natural population of C.sequinii and provide baseline data for formulating a conservation strategy of Castanea species.     

Spatially explicit Bayesian clustering models in population genetics

This article reviews recent developments in Bayesian algorithms that explicitly include geographical information in the inference of population structure. Current models substantially differ in their prior distributions and background assumptions, falling into two broad categories: models with or without admixture. To aid users of this new generation of spatially explicit programs, we clarify the assumptions underlying the models, and we test these models in situations where their assumptions are not met. We show that models without admixture are not robust to the inclusion of admixed individuals in the sample, thus providing an incorrect assessment of population genetic structure in many cases. In contrast, admixture models are robust to an absence of admixture in the sample. We also give statistical and conceptual reasons why data should be explored using spatially explicit models that include admixture.     

A comparison of four methods for detecting weak genetic structure from marker data

Genetic structure is ubiquitous in wild populations and is the result of the processes of natural selection, genetic drift, mutation, and gene flow. Genetic drift and divergent selection promotes the generation of genetic structure, while gene flow homogenizes the subpopulations. The ability to detect genetic structure from marker data diminishes rapidly with a decreasing level of differentiation among subpopulations. Weak genetic structure may be unimportant over evolutionary time scales but could have important implications in ecology and conservation biology. In this paper we examine methods for detecting and quantifying weak genetic structures using simulated data. We simulated populations consisting of two putative subpopulations evolving for up to 50 generations with varying degrees of gene flow (migration), and varying amounts of information (allelic diversity). There are a number of techniques available to detect and quantify genetic structure but here we concentrate on four methods: F(ST), population assignment, relatedness, and sibship assignment. Under the simple mating system simulated here, the four methods produce qualitatively similar results. However, the assignment method performed relatively poorly when genetic structure was weak and we therefore caution against using this method when the analytical aim is to detect fine-scale patterns. Further work should examine situations with different mating systems, for example where a few individuals dominate reproductive output of the population. This study will help workers to design their experiments (e.g., sample sizes of markers and individuals), and to decide which methods are likely to be most appropriate for their particular data.     

Fine-scale genetic structure of life history stages in the food-deceptive orchid Orchis purpurea

In natural plant populations, fine-scale spatial genetic structure can result from limited gene flow, selection pressures or historical events, but the role of each factor is in general hard to discern. One way to investigate the origination of spatial genetic structure within a plant population consists of comparing spatial genetic structure among different life history stages. In this study, spatial genetic structure of the food-deceptive orchid Orchis purpurea was determined across life history stages in two populations that were regenerating after many years of population decline. Based on demographic analyses (2001-2004), we distinguished between recruits and adult plants. For both sites, there was no difference in the proportion of polymorphic loci and expected heterozygosity between life history stages. However, spatial autocorrelation analyses showed that spatial genetic structure increased in magnitude with life history stage. Weak or no spatial genetic structure was observed for recruits, whereas adult plants showed a pattern that is consistent with that found in other species with a predominantly outcrossing mating system. The observed differences between seedlings and adults are probably a consequence of changes in management of the two study sites and associated demographic changes in both populations. Our results illustrate that recurrent population crashes and recovery may strongly affect genetic diversity and fine-scale spatial genetic structure of plant populations.