An empirical assessment of individual-based population genetic statistical techniques: application to British pig breeds

Recently developed Bayesian genotypic clustering methods for analysing genetic data offer a powerful tool to evaluate the genetic structure of domestic farm animal breeds. The unit of study with these approaches is the individual instead of the population. We aimed to empirically evaluate various individual-based population genetic statistical methods for characterization of genetic diversity and structure of livestock breeds. Eighteen British pig populations, comprising 819 individuals, were genotyped at 46 microsatellite markers. Three Bayesian genotypic clustering approaches, principle component analysis (PCA) and phylogenetic reconstruction were applied to individual multilocus genotypes to infer the genetic structure and diversity of the British pig breeds. Comparisons of the three Bayesian genotypic clustering methods (, and ) revealed some broad similarities but also some notable differences. Overall, the methods agreed that majority of the British pig breeds are independent genetic units with little evidence of admixture. The three Bayesian genotypic clustering methods provided complementary, biologically credible clustering solutions but at different levels of resolution. detected finer genetic differentiation and in some cases, populations within breeds. Consequently, it estimated a greater number of underlying genetic populations (K, in the notation of Bayesian clustering methods). Two of the Bayesian methods ( and ) and phylogenetic reconstruction provided similar success in assignment of individuals, supporting the use of these methods for breed assignment.     

Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study

On the basis of simulated data, this study compares the relative performances of the Bayesian clustering computer programs structure , geneland , geneclust and a new program named tess . While these four programs can detect population genetic structure from multilocus genotypes, only the last three ones include simultaneous analysis from geographical data. The programs are compared with respect to their abilities to infer the number of populations, to estimate membership probabilities, and to detect genetic discontinuities and clinal variation. The results suggest that combining analyses using tess and structure offers a convenient way to address inference of spatial population structure.     

Influence of habitat fragmentation on population structure of red deer in Croatia

The genetic structure of red deer populations is under strong influence of human activities such as game management and habitat fragmentation. Using multilocus genotypes from 193 geo-referenced individuals, we evaluated the population genetic structure of three red deer populations in Croatia. The effect of habitat fragmentation on genetic structure was tested using Bayesian non-spatial and spatial clustering methods. Our results indicate levels of genetic diversity similar to the ones previously reported by other authors for stable and appropriately managed populations within all populations analyzed. The spatial clustering model was able to detect the effect of habitat fragmentation on population differentiation, supporting the use of spatially explicit methods in landscape genetics, and giving important guidelines for future road planning.     

Genetic clustering methods reveal bull trout (<Emphasis Type="Italic">Salvelinus confluentus</Emphasis>) fine-scale population structure as a spatially nested hierarchy

Many conservation genetics studies in fishes define populations based on capture location. In salmonid fishes, this traditional a priori designation is made by spawning stream, with subsequent post hoc approaches used to define units of conservation. In this study of bull trout from southwestern Alberta, we provide evidence that a model-based Bayesian genetic clustering method may provide a more parsimonious alternative to designating population structure and units of conservation in comparison to traditional methods. The clustering method captured a hierarchical model of population structure, in which seven local populations were nested within three genetic archipelagos. This was in contrast to using simple F _ST based approaches between thirteen a priori designated populations, which found significant differences for nearly every pairwise comparison. In addition, assignment tests results from Bayesian clustering revealed that movement may be common between sampling locations. These clustering methods are easy to use, intuitive and provide substantial information on populations of fish; this study provides an example of their utility for local fisheries management and conservation.     

Empirical evaluation of genetic clustering methods using multilocus genotypes from 20 chicken breeds

We tested the utility of genetic cluster analysis in ascertaining population structure of a large data set for which population structure was previously known. Each of 600 individuals representing 20 distinct chicken breeds was genotyped for 27 microsatellite loci, and individual multilocus genotypes were used to infer genetic clusters. Individuals from each breed were inferred to belong mostly to the same cluster. The clustering success rate, measuring the fraction of individuals that were properly inferred to belong to their correct breeds, was consistently approximately 98%. When markers of highest expected heterozygosity were used, genotypes that included at least 8-10 highly variable markers from among the 27 markers genotyped also achieved >95% clustering success. When 12-15 highly variable markers and only 15-20 of the 30 individuals per breed were used, clustering success was at least 90%. We suggest that in species for which population structure is of interest, databases of multilocus genotypes at highly variable markers should be compiled. These genotypes could then be used as training samples for genetic cluster analysis and to facilitate assignments of individuals of unknown origin to populations. The clustering algorithm has potential applications in defining the within-species genetic units that are useful in problems of conservation.     

Specialist and generalist symbionts show counterintuitive levels of genetic diversity and discordant demographic histories along the Florida Reef Tract

Specialist and generalist life histories are expected to result in contrasting levels of genetic diversity at the population level, and symbioses are expected to lead to patterns that reflect a shared biogeographic history and co-diversification. We test these assumptions using mtDNA sequencing and a comparative phylogeographic approach for six co-occurring crustacean species that are symbiotic with sea anemones on western Atlantic coral reefs, yet vary in their host specificities: four are host specialists and two are host generalists. We first conducted species discovery analyses to delimit cryptic lineages, followed by classic population genetic diversity analyses for each delimited taxon, and then reconstructed the demographic history for each taxon using traditional summary statistics, Bayesian skyline plots, and approximate Bayesian computation to test for signatures of recent and concerted population expansion. The genetic diversity values recovered here contravene the expectations of the specialist–generalist variation hypothesis and classic population genetics theory; all specialist lineages had greater genetic diversity than generalists. Demography suggests recent population expansions in all taxa, although Bayesian skyline plots and approximate Bayesian computation suggest the timing and magnitude of these events were idiosyncratic. These results do not meet the a priori expectation of concordance among symbiotic taxa and suggest that intrinsic aspects of species biology may contribute more to phylogeographic history than extrinsic forces that shape whole communities. The recovery of two cryptic specialist lineages adds an additional layer of biodiversity to this symbiosis and contributes to an emerging pattern of cryptic speciation in the specialist taxa. Our results underscore the differences in the evolutionary processes acting on marine systems from the terrestrial processes that often drive theory. Finally, we continue to highlight the Florida Reef Tract as an important biodiversity hotspot.

     

Spatial genetic analysis reveals high connectivity of tiger (Panthera tigris) populations in the Satpura–Maikal landscape of Central India

We investigated the spatial genetic structure of the tiger meta‐population in the Satpura–Maikal landscape of central India using population‐ and individual‐based genetic clustering methods on multilocus genotypic data from 273 individuals. The Satpura–Maikal landscape is classified as a global‐priority Tiger Conservation Landscape (TCL) due to its potential for providing sufficient habitat that will allow the long‐term persistence of tigers. We found that the tiger meta‐population in the Satpura–Maikal landscape has high genetic variation and very low genetic subdivision. Individual‐based Bayesian clustering algorithms reveal two highly admixed genetic populations. We attribute this to forest connectivity and high gene flow in this landscape. However, deforestation, road widening, and mining may sever this connectivity, impede gene exchange, and further exacerbate the genetic division of tigers in central India.     

Microsatellite population genetics of the emerald ash borer (Agrilus planipennis Fairmaire): comparisons between Asian and North American populations

The emerald ash borer (EAB) (Agrilus planipennis Fairmaire) (Coleoptera; Buprestidae), is an invasive wood-boring beetle native to northeast Asia. This species was first detected in Michigan USA in 2002, and is a significant threat to native and ornamental ash tree species (Fraxinus spp.) throughout North America. We characterized seven polymorphic microsatellite markers for EAB and used these to investigate EAB population structure in the early invasive populations within North America and in comparison with Asia. We found 2–9 alleles per microsatellite locus, no evidence of linkage disequilibrium, and no association with known coding sequences, suggesting that these markers are suitable for population genetic analysis. Microsatellite population genetic structure was examined in 48 EAB populations sampled between 2003 and 2008 from five regions, three in the introduced range, Michigan (US) and Ontario and Quebec (Canada) and two Asian regions, China and South Korea, where EAB is native. We found significant genetic variation geographically but not temporally in EAB populations. Bayesian clustering analyses of individual microsatellite genotypes showed strong clustering among multiple North American populations and populations in both China and South Korea. Finally, allelic richness and expected heterozygosity were higher in the native range of EAB, but there was no difference in observed heterozygosity, suggesting a significant loss of alleles upon introduction but no significant change in the distribution of alleles within and among individuals.     

Origin,Migration Routes and Worldwide Population Genetic Structure of the Wheat Yellow Rust Pathogen Puccinia striiformis f.sp. tritici

Analyses of large-scale population structure of pathogens enable the identification of migration patterns, diversity reservoirs or longevity of populations, the understanding of current evolutionary trajectories and the anticipation of future ones. This is particularly important for long-distance migrating fungal pathogens such as Puccinia striiformis f.sp. tritici (PST), capable of rapid spread to new regions and crop varieties. Although a range of recent PST invasions at continental scales are well documented, the worldwide population structure and the center of origin of the pathogen were still unknown. In this study, we used multilocus microsatellite genotyping to infer worldwide population structure of PST and the origin of new invasions based on 409 isolates representative of distribution of the fungus on six continents. Bayesian and multivariate clustering methods partitioned the set of multilocus genotypes into six distinct genetic groups associated with their geographical origin. Analyses of linkage disequilibrium and genotypic diversity indicated a strong regional heterogeneity in levels of recombination, with clear signatures of recombination in the Himalayan (Nepal and Pakistan) and near-Himalayan regions (China) and a predominant clonal population structure in other regions. The higher genotypic diversity, recombinant population structure and high sexual reproduction ability in the Himalayan and neighboring regions suggests this area as the putative center of origin of PST. We used clustering methods and approximate Bayesian computation (ABC) to compare different competing scenarios describing ancestral relationship among ancestral populations and more recently founded populations. Our analyses confirmed the Middle East-East Africa as the most likely source of newly spreading, high-temperature-adapted strains; Europe as the source of South American, North American and Australian populations; and Mediterranean-Central Asian populations as the origin of South African populations. Although most geographic populations are not markedly affected by recent dispersal events, this study emphasizes the influence of human activities on recent long-distance spread of the pathogen.     

Why sampling scheme matters: the effect of sampling scheme on landscape genetic results

There has been a recent trend in genetic studies of wild populations where researchers have changed their sampling schemes from sampling pre-defined populations to sampling individuals uniformly across landscapes. This reflects the fact that many species under study are continuously distributed rather than clumped into obvious “populations”. Once individual samples are collected, many landscape genetic studies use clustering algorithms and multilocus genetic data to group samples into subpopulations. After clusters are derived, landscape features that may be acting as barriers are examined and described. In theory, if populations were evenly sampled, this course of action should reliably identify population structure. However, genetic gradients and irregularly collected samples may impact the composition and location of clusters. We built genetic models where individual genotypes were either randomly distributed across a landscape or contained gradients created by neighbor mating for multiple generations. We investigated the influence of six different sampling protocols on population clustering using program STRUCTURE, the most commonly used model-based clustering method for multilocus genotype data. For models where individuals (and their alleles) were randomly distributed across a landscape, STRUCTURE correctly predicted that only one population was being sampled. However, when gradients created by neighbor mating existed, STRUCTURE detected multiple, but different numbers of clusters, depending on sampling protocols. We recommend testing for fine scale autocorrelation patterns prior to sample clustering, as the scale of the autocorrelation appears to influence the results. Further, we recommend that researchers pay attention to the impacts that sampling may have on subsequent population and landscape genetic results. The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

Bayesian identification of admixture events using multilocus molecular markers

Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically divergent groups, whereas admixture models target at separating the ancestral sources of the alleles observed in different individuals. We discuss the difficulties involved in the simultaneous estimation of the number of ancestral populations and the levels of admixture in studied individuals' genomes. To resolve this issue, we introduce a computationally efficient method for the identification of admixture events in the population history. Our approach is illustrated by analyses of several challenging real and simulated data sets. The software (baps), implementing the methods introduced here, is freely available at http://www.rni.helsinki.fi/~jic/bapspage.html.     

Forensic characteristic and population structure dissection of Shaanxi Han population in the light of diallelic deletion/insertion polymorphism data

The genetic polymorphisms of diallelic deletion/insertion polymorphic (DIP) loci in the Shaanxi Han population are still not clearly characterized. Herein, allele frequencies and forensic application efficiencies for 30 diallelic DIP loci were investigated in 506 unrelated healthy Han individuals from Chinese Shaanxi province. Based on population data of the same 30 diallelic DIP loci, the genetic differentiations, hierarchical clustering relationships and population architectures among Shaanxi Han and other 50 populations were further dissected through genetic and bioinformatics analyses. Results indicated that most of the 30 diallelic DIP loci were relatively high polymorphisms in the Shaanxi Han population; and there were the genetically intimate relationships between Shaanxi Han and the East Asian populations. In summary, this study provided significant insights into genetic background of Shaanxi Han population, and the multiplex amplification of these 30 diallelic DIP loci was appropriate for forensic individual identification and population genetic research in Shaanxi Han population.     

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.     

Population structure, effective population size and adverse effects of stocking in the endangered Australian eastern freshwater cod Maccullochella ikei

Microsatellite markers were used to examine spatio-temporal genetic variation in the endangered eastern freshwater cod Maccullochella ikei in the Clarence River system, eastern Australia. High levels of population structure were detected. A model-based clustering analysis of multilocus genotypes identified four populations that were highly differentiated by F-statistics (F(ST) = 0·09 - 0·49; P < 0·05), suggesting fragmentation and restricted dispersal particularly among upstream sites. Hatchery breeding programmes were used to re-establish locally extirpated populations and to supplement remnant populations. Bayesian and frequency-based analyses of hatchery fingerling samples provided evidence for population admixture in the hatchery, with the majority of parental stock sourced from distinct upstream sites. Comparison between historical and contemporary wild-caught samples showed a significant loss of heterozygosity (21%) and allelic richness (24%) in the Mann and Nymboida Rivers since the commencement of stocking. Fragmentation may have been a causative factor; however, temporal shifts in allele frequencies suggest swamping with hatchery-produced M. ikei has contributed to the genetic decline in the largest wild population. This study demonstrates the importance of using information on genetic variation and population structure in the management of breeding and stocking programmes, particularly for threatened species.     

Genetic diversity and differentiation of the Korean starry flounder (Platichthys stellatus) between and within cultured stocks and wild populations inferred from microsatellite DNA analysis

The Korean starry flounder, Platichthys stellatus, is economically valuable coastal resident fish species. However, the annual catch of this fish has fluctuated and suffered major declines in Korea. We examined the genetic diversity and population structure for four wild populations and three hatchery stocks of Korean starry flounder to protect its genetic integrity using nine microsatellites. A group of 339 genotypes belonging to seven populations were screened. High degrees of polymorphism at the microsatellite loci were observed within both the wild and hatchery populations. Compared to the wild populations, genetic changes, including reduced genetic diversity and highly significant differentiation, have occurred in cultured stocks. Significant population differentiation was also observed in wild starry flounder populations. Similar degrees of inbreeding and significant Hardy–Weinberg equilibrium deviations were detected in both the wild and the hatchery populations. The genetic connectivity pattern identified four distinct metapopulations of starry flounder in Korea by clustering in the phylogenetic tree, Bayesian analyses, molecular variance analysis, PCA and multidimensional scaling analysis. A pattern of isolation-by-distance was not significant. This genetic differentiation may be the result of the co-effects of various factors, such as historic dispersal, local environment or anthropogenic activities. These results provide useful information for the genetic monitoring of P. stellatus hatchery stocks, for the genetic improvement of this species by selective breeding and for designing suitable management guidelines for the conservation of this species.     

Integration of genetic and demographic data to assess population risk in a continuously distributed species

The identification and demographic assessment of biologically meaningful populations is fundamental to species’ ecology and management. Although genetic tools are used frequently to identify populations, studies often do not incorporate demographic data to understand their respective population trends. We used genetic data to define subpopulations in a continuously distributed species. We assessed demographic independence and variation in population trends across the distribution. Additionally, we identified potential barriers to gene flow among subpopulations. We sampled greater sage-grouse (Centrocercus urophasianus) leks from across their range (≈175,000 Km²) in Wyoming and amplified DNA at 14 microsatellite loci for 1761 samples. Subsequently, we assessed population structure in unrelated individuals (n = 872) by integrating results from multiple Bayesian clustering approaches and used the boundaries to inform our assessment of long-term population trends and lek activity over the period of 1995–2013. We identified four genetic clusters of which two northern ones showed demographic independence from the others. Trends in population size for the northwest subpopulation were statistically different from the other three genetic clusters and the northeast and southwest subpopulations demonstrated a general trend of increasing proportion of inactive leks over time. Population change from 1996 to 2012 suggested population growth in the southern subpopulations and decline, or neutral, change in the northern subpopulations. We suggest that sage-grouse subpopulations in northern Wyoming are at greater risk of extirpation than the southern subpopulations due to smaller census and effective population sizes and higher variability within subpopulations. Our research is an example of incorporating genetic and demographic data and provides guidance on the identification of subpopulations of conservation concern.     

Congruent population structure inferred from dispersal behaviour and intensive genetic surveys of the threatened Florida scrub-jay (Aphelocoma coerulescens)

The delimitation of populations, defined as groups of individuals linked by gene flow, is possible by the analysis of genetic markers and also by spatial models based on dispersal probabilities across a landscape. We combined these two complimentary methods to define the spatial pattern of genetic structure among remaining populations of the threatened Florida scrub-jay, a species for which dispersal ability is unusually well-characterized. The range-wide population was intensively censused in the 1990s, and a metapopulation model defined population boundaries based on predicted dispersal-mediated demographic connectivity. We subjected genotypes from more than 1000 individual jays screened at 20 microsatellite loci to two Bayesian clustering methods. We describe a consensus method for identifying common features across many replicated clustering runs. Ten genetically differentiated groups exist across the present-day range of the Florida scrub-jay. These groups are largely consistent with the dispersal-defined metapopulations, which assume very limited dispersal ability. Some genetic groups comprise more than one metapopulation, likely because these genetically similar metapopulations were sundered only recently by habitat alteration. The combined reconstructions of population structure based on genetics and dispersal-mediated demographic connectivity provide a robust depiction of the current genetic and demographic organization of this species, reflecting past and present levels of dispersal among occupied habitat patches. The differentiation of populations into 10 genetic groups adds urgency to management efforts aimed at preserving what remains of genetic variation in this dwindling species, by maintaining viable populations of all genetically differentiated and geographically isolated populations.     

Forensic DNA Analysis of Pacific Salmonid Samples for Species and Stock Identification

Identification of salmonid tissue samples to species or population of origin has been conducted for over 20 forensic cases in British Columbia. Species identification is based on published sequence variation in exon and intron regions of coding genes. Identification of source populations or regions is carried out using microsatellite and major histocompatibility complex allele frequency data collected from populations throughout the species range and with standard genetic stock identification (GSI) methods. Regional contributions to mixture samples are estimated using maximum likelihood mixture analysis and classification of individual genotypes is carried out with Bayesian methods. DNA has been obtained successfully from salmon scale samples, fresh, frozen and canned tissue samples and bloodstains in clothing. Results from DNA analyses have been instrumental in a number of convictions. A major benefit has been cost savings resulting from the number of guilty pleas entered after disclosure to the defendant of results from genetic testing. In two cases, GSI analysis resulted in exoneration of suspects under investigation for possible illegal sales of Fraser River sockeye salmon by substantiating their claim that the fish originated from the Skeena River watershed. DNA analysis has generally corroborated the species and stock identification carried out by fishery officers, but has revealed that species identification of samples from sources such as restaurants and fish plants can be erroneous. Forensic DNA analysis has facilitated the conviction of those who purchase fish not caught under the authority of licence, thus bringing those who buy fish illegally as well as those involved in illegal harvest and sales within the scope of law enforcement.     

Geographic patterns of genetic variation in native pecans

A structured collection of 80 seedling pecan trees [Carya illinoinensis (Wangenh.) K. Koch], representing 19 putatively native pecan populations across the species range, was evaluated at three plastid and 14 nuclear microsatellite (simple sequence repeat, SSR) loci. Data were analyzed using a priori population designations and also within a Bayesian framework, in which individuals were assigned to clusters regardless of population of origin. Population genetic analyses using a priori populations, clusters based on chloroplast microsatellite data (cpSSR), and clusters based on nuclear microsatellite data (nSSR) yielded consistent results. For all groupings, cpSSR variation exhibited more geographic structure than the nSSR data. Furthermore, cpSSR microsatellite diversity decreased with increasing latitude, but this pattern was not observed with the nuclear data. Contrasting patterns in plastid and nuclear genetic diversity demonstrate unique aspects of postglacial recolonization reflected in the movement of seeds versus pollen. These data suggest that plastid SSRs are useful tools for identifying population structure in pecan and hold promise for ongoing efforts to identify and conserve representative germplasm in ex situ collections.     

Unexpected cryptic species diversity in the widespread coral Seriatopora hystrix masks spatial‐genetic patterns of connectivity

Mounting evidence of cryptic species in a wide range of taxa highlights the need for careful analyses of population genetic data sets to unravel within‐species diversity from potential interspecies relationships. Here, we use microsatellite loci and hierarchical clustering analysis to investigate cryptic diversity in sympatric and allopatric (separated by 450 km) populations of the widespread coral Seriatopora hystrix on the Great Barrier Reef. Structure analyses delimited unique genetic clusters that were confirmed by phylogenetic and extensive population‐level analyses. Each of four sympatric yet distinct genetic clusters detected within S. hystrix demonstrated greater genetic cohesion across regional scales than between genetic clusters within regions (<10 km). Moreover, the magnitude of genetic differentiation between different clusters (>0.620 G”_ST) was similar to the difference between S. hystrix clusters and the congener S. caliendrum (mean G”_ST 0.720). Multiple lines of evidence, including differences in habitat specificity, mitochondrial identity, Symbiodinium associations and morphology, corroborate the nuclear genetic evidence that these distinct clusters constitute different species. Hierarchical clustering analysis combined with more traditional population genetic methods provides a powerful approach for delimiting species and should be regularly applied to ensure that ecological and evolutionary patterns interpreted for single species are not confounded by the presence of cryptic species.