Infer Population Structure Research Articles

Correcting population stratification in genetic association studies using a phylogenetic approach

The rapid development of genotyping technology and extensive cataloguing of single nucleotide polymorphisms (SNPs) across the human genome have made genetic association studies the mainstream for gene mapping of complex human diseases. For many diseases, the most practical approach is the population-based design with unrelated individuals. Although having the advantages of easier sample collection and greater power than family-based designs, unrecognized population stratification in the study samples can lead to both false-positive and false-negative findings and might obscure the true association signals if not appropriately corrected. We report PHYLOSTRAT, a new method that corrects for population stratification by combining phylogeny constructed from SNP genotypes and principal coordinates from multi-dimensional scaling (MDS) analysis. This hybrid approach efficiently captures both discrete and admixed population structures. By extensive simulations, the analysis of a synthetic genome-wide association dataset created using data from the Human Genome Diversity Project, and the analysis of a lactase-height dataset, we show that our method can correct for population stratification more efficiently than several existing population stratification correction methods, including EIGENSTRAT, a hybrid approach based on MDS and clustering, and STRATSCORE , in terms of requiring fewer random SNPs for inference of population structure. By combining the flexibility and hierarchical nature of phylogenetic trees with the advantage of representing admixture using MDS, our hybrid approach can capture the complex population structures in human populations effectively. Codes can be downloaded from http://people.pcbi.upenn.edu/ approximately lswang/phylostrat/ mingyao@upenn.edu; iswang@upenn.edu. Supplementary data are available at Bioinformatics online.

Demographic histories of four spruce (Picea) species of the Qinghai-Tibetan Plateau and neighboring areas inferred from multiple nuclear loci

Nucleotide variation at 12-16 nuclear loci was studied in three spruce species from the Qinghai-Tibetan Plateau (QTP), Picea likiangensis, P. wilsonii, and P. purpurea, and one species from the Tian Shan mountain range, P. schrenkiana. Silent nucleotide diversity was limited in P. schrenkiana and high in the three species from the QTP, with values higher than in boreal spruce species, despite their much more restricted distributions compared with that of the boreal species. In contrast to European boreal species that have experienced severe bottlenecks in the past, coalescent-based analysis suggests that DNA polymorphism in the species from the QTP and adjacent areas is compatible with the standard neutral model (P. likiangensis, P. wilsonii, and P. schrenkiana) or with population growth (P. purpurea). In order to test if P. purpurea is a diploid hybrid of P. likiangensis and P. wilsonii, we used a combination of approaches, including model-based inference of population structure, isolation-with-migration models, and recent theoretical results on the effect of introgression on the geographic distribution of diversity. In contrast to the three other species, each of which was predominantly assigned to a single cluster in the Structure analysis, P. purpurea individuals were scattered over the three main clusters and not, as we had expected, confined to the P. likiangensis and P. wilsonii clusters. Furthermore, the contribution of P. schrenkiana was by far the largest one. In agreement with this, the divergence between P. purpurea and P. schrenkiana was lower than the divergence of either P. likiangensis or P. wilsonii from P. schrenkiana. These results, together with previous ones showing that P. purpurea and P. wilsonii share the same haplotypes at both chloroplast and mitochondrial markers, suggest that P. purpurea has a complex origin, possibly involving additional species.

Laplacian eigenfunctions learn population structure.

Principal components analysis has been used for decades to summarize genetic variation across geographic regions and to infer population migration history. More recently, with the advent of genome-wide association studies of complex traits, it has become a commonly-used tool for detection and correction of confounding due to population structure. However, principal components are generally sensitive to outliers. Recently there has also been concern about its interpretation. Motivated from geometric learning, we describe a method based on spectral graph theory. Regarding each study subject as a node with suitably defined weights for its edges to close neighbors, one can form a weighted graph. We suggest using the spectrum of the associated graph Laplacian operator, namely, Laplacian eigenfunctions, to infer population structure. In simulations and real data on a ring species of birds, Laplacian eigenfunctions reveal more meaningful and less noisy structure of the underlying population, compared with principal components. The proposed approach is simple and computationally fast. It is expected to become a promising and basic method for population genetics and disease association studies.

Genealogical Relationship among Members of Selection and Production Populations of Yellow Cedar (Callitropsis nootkatensis [D. Don] Oerst.) in the Absence of Parental Information

We used DNA fingerprinting and pedigree reconstruction to determine the genetic relationship among members of 3 yellow-cedar (Callitropsis nootkatensis [D. Don] Oerst.) selection populations in the absence of their parental genotypes. Selection population members consisted of the tallest individuals within seedling crops originated from natural stand seed collected from multiple seed donors covering wide areas within 3 distinct locations (phenotypic mass selection). Pairwise relative kinship estimates indicated the presence of extensive coancestry among the selected seedlings, and pedigree reconstruction grouped each selection members into multiple full-sib families of different sizes (1-10) nested within several half-sib families (19-21). The "STRUCTURE" program (Pritchard JK, Stephens M, Donnelly P. 2000. "Inference of population structure using multilocus genotype data." Genetics. 155:945-959.) provided a pictorial classification of the 3 selection populations and grouped their individuals into multiple cohorts (9-10). The STRUCTURE program's results corresponded with that of the pedigree reconstruction, indicating that members of the selection populations originated from a subset of the seed donors forming the natural stand seed collections. The species' silvics, reproductive biology, methods of natural stand seed collection and seedling production, and the high selection intensity applied to form the selection populations contributed to limiting the selection to a subset of the original donor trees. The associated buildup of coancestry in selection and production populations is expected to result in inaccurate estimation of genetic parameters and an unintentional reduction in genetic diversity in reforestation stocks.

Genetic analysis across different spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes

Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.

Assessing population genetic structure via the maximisation of genetic distance

BackgroundThe inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.MethodsIn this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a simulated annealing algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.ResultsThe simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for FST ≥ 0.03, but only STRUCTURE estimates the correct number of clusters for FST as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.ConclusionThis new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.

A nonsynonymous gene variant in the adiponutrin gene is associated with nonalcoholic fatty liver disease severity

We explored the role of the adiponutrin (PNPLA3) nonsynonymous-rs738409 single nucleotide polymorphism (SNP) in genetic susceptibility to nonalcoholic fatty liver disease (NAFLD) and whether this SNP contributes to the severity of histological disease. Two hundred sixty-six individuals were evaluated in a case-control association study, which included 172 patients with features of NAFLD and 94 control subjects. The rs738409 G allele was significantly associated with NAFLD (P < 0.001; OR 2.8 95%, CI 1.5-5.2), independent of age, sex, body mass index (BMI), and Homeostasis Model Assessment (HOMA) index. When we tested the hypothesis of a relation between the SNP and the histological spectrum of NAFLD, a significant association was observed [chi2 19.9, degree of freedom (df): 2, P < 5 x 10(-5), adjusted for HOMA and BMI]. The degree of liver steatosis, as evaluated by liver biopsy, was significantly associated with the rs738409 G allele. Patients with CC genotype showed a lower steatosis score (14.9% +/- 3.9) in comparison with the CG genotype (26.3% +/- 3.5) and GG genotype (33.3% +/- 4.0) (P < 0.005). The proportion of the total variation attributed to rs738409 genotypes was 5.3% (beta 0.23 +/- 0.07; P < 0.002). Our data suggest that the rs738409 G allele is associated not only with fat accumulation in the liver but also with liver injury, possibly triggered by lipotoxicity.

Phylogeography of the flathead mullet Mugil cephalus in the north‐west Pacific as inferred from the mtDNA control region

The population genetic structure and historical demography of the flathead mullet Mugil cephalus were investigated using the mtDNA control region (CR) sequences (909-1015 bp) of 126 individuals collected from seven locations in the north-west Pacific between 2005 and 2007. Haplotype diversity (h = 0.9333-1.000) and nucleotide diversity (pi = 0.0046-0.1467) varied greatly among the sampling locations. Phylogenetic analysis of the CR sequences indicated that M. cephalus in the north-west Pacific belongs to two highly divergent lineages (lineages 1 and 2), with the inferred population structure being closely associated with the distribution of both lineages. Two populations were identified, one from the East China Sea and the other from the South China Sea. The former samples were obtained from Taiwan and Qingdao of north China and associated with lineage 1 haplotypes. The latter samples were collected from the Philippines, Pearl River of South China and two samples from Japan, all of which were associated with lineage 2. Japanese samples from Okinawa and Yokosuka had different degrees of mixing between lineages 1 and 2. Historical demographic variables in both populations indicated that Pleistocene glaciations had a strong impact on M. cephalus in the north-west Pacific, resulting in a recent demographic decline of the East China Sea population but in demographic equilibrium for the South China Sea population. Japan appears to be a contact zone between lineages 1 and 2, but it may also be indicative of coexistence between resident and migratory populations. Further global studies are required to clarify the taxonomic status of this cosmopolitan species.

Effects of Sample Size and Loci Number on Genetic Diversity in Wild Population of Grass Carp Revealed by SSR

Sample collection and marker selection are of primary importance in population genetic studies, and can greatly influence the analysis and interpretation of the data obtained. Microsatellite DNA sequences are the most revealing DNA markers available so far for inferring population structure and have been widely employed in genetic studies of populations．Nevertheless，few studies have specifically examined the effects of sample size and loci number on various genetic diversity measures in population genetic work using these markers．Here，we examined this issue using experimental data from an analysis of genetic diversity of wild populations of grass carp at 45 polymorphic microsatellite loci. The following genetic diversity measures were studied: number of alleles per locus (N_a), effective number of allele per loci (N_e)，observed hererozygosity (H_o) and expected heterozygosity (H_e)．We also tried to infer the theoretical minimum sample size and loci number needed for population genetic studies with microsatellite loci. The results are as follows: (1) N_a and Mean number of allele over loci (MNA) are significantly affected by sample size. It increase according to the raise of the sample size, only when the sample size exceeds 40 it tends to be stable. The significant correlation between sample size and N_a was observed and the correlation curve is Y=3.8403+0.6376, r²=0.967．However, there is no significant correlation between the mean value of N_e, H_o, H_eand the sample size. Mean value of H_o, H_e fluctuate with the raise of the sample size, only when the sample size exceeds 40 it manifest a stable trend. (2) Evaluating of different genetic parameters with the makers of different polymorphism information content, a significantly different result were acquired. When PIC>0.5, N_a, N_e, H_o, H_e were 3.6, 1.5934, 0.2824, 0.3540, While PIC<0.5, N_a, N_e, H_o, H_e were 9.5, 5.9209, 0.8497, 0.8242 respectively. Accordingly, marker selecting strategy has much greater impact on evaluation of genetic diversity. (3) According to the rise of loci number, the value of genetic parameter could be divided into three stages: ① Descending stage: loci number between 0&#8722;5, values of N_a, N_e, H_o, H_e indicated descending trend. ② Loci number between 5&#8722;10, values of N_a, N_e, H_o, H_e demonstrate ascending trend. ③ When loci number exceeded 15 values of N_a, N_e, H_e tend to be stable, while only when loci number exceeded 25 the value of H_o tend to be stable. Analysis above proved that not only the sample size and loci number but also the polymorphism information of microsatellite markers have significant effect on the estimation of population genetic diversity. So, we suggested that when microsatellite markers were used to estimate genetic diversity of population the minimum loci number and sample size are needed to exceed 25 and 40, respectively. Moreover, the conclusion above has been used to evaluate the genetic diversity of wild population of grass carp, values of the parameter were N_a=7.26、N_e =4.21、H_o=0.73、H_e=0.68, which demonstrated that has a relatively high diversity, a totally different conclusion from the former studies. Therefore, further researches are necessary for the evaluation of genetic diversity of geographically different population of grass carp.

Genetic diversity and relationships among indigenous Mozambican cattle breeds

Three indigenous Mozambican cattle breeds, namely the Angone, Landim and Bovino de Tete were characterized using six proteins, 13 autosomal microsatellite loci and one Y-specific microsatellite locus (INRA124). The Mashona breed from Zimbabwe was also studied to elucidate the origin of the Bovino de Tete cattle. Expected mean heterozygosity ranged from 0.46 - 0.50 in the proteins and from 0.66 - 0.69 in the microsatellites. Population genetic variability was relatively high when compared to other African breeds. Only 4.5% of the total genetic variation could be attributed to the differences among the breeds. DA genetic distances and principal component analysis suggest that Mozambican breeds occupy an intermediate position between Indian Zebu and African taurine cattle. The genetic contribution from Indian Zebu, estimated by mR and average percentage of Zebu diagnostic alleles, was highest in the Angone breed and lowest in the Landim breed. The indicine Y-specific allele was fixed in the Angone breed (classified as Zebu), was found in 62% of the Bovino de Tete breed and was absent in the Landim breed (classified as Sanga). The hybrid nature of these breeds was also revealed by using an admixture model to infer population structure. Cluster analysis correctly assigned individuals to their rightful populations with probabilities ranging from 0.96 to 0.98, using prior population information. The results support the hypothesis of the Bovino de Tete cattle being a result of crossbreeding between Sanga and Zebu breeds. This study presents the first extensive information on the genetic diversity and relationships among Mozambican cattle breeds and with other breeds from different continents.

MStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations

Traditional methods for analyzing population structure, such as the Structure program, ignore the influence of the effect of allele mutations between the ancestral and current alleles of genetic markers, which can dramatically influence the accuracy of the structural estimation of current populations. Studying these effects can also reveal additional information about population evolution such as the divergence time and migration history of admixed populations. We propose mStruct, an admixture of population-specific mixtures of inheritance models that addresses the task of structure inference and mutation estimation jointly through a hierarchical Bayesian framework, and a variational algorithm for inference. We validated our method on synthetic data and used it to analyze the Human Genome Diversity Project-Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) cell line panel of microsatellites and HGDP single-nucleotide polymorphism (SNP) data. A comparison of the structural maps of world populations estimated by mStruct and Structure is presented, and we also report potentially interesting mutation patterns in world populations estimated by mStruct.

Landscape genetics of white‐tailed deer in Illinois: a tool for investigating an outbreak of chronic wasting disease

Understanding transmission patterns of wildlife diseases can facilitate predictions of disease spread and allow for identification of risk factors for disease. The objective of this study was to infer population structure and animal movement from genetic information to clarify the relative contribution of direct and environmental components of Chronic Wasting Disease (CWD) transmission. CWD, a cervid transmissible spongiform encephalopathy, was identified in Illinois in 2002 and is currently being managed through disease surveillance and increased population control. Multi‐locus genotypes were compiled for &gt; 1000 white‐tailed deer sampled through CWD surveillance in Illinois. Using ten microsatellites, inter‐individual genetic relatedness values were calculated for CWD positive deer and for negative deer selected to control for gender, age and harvest location. No differences in genetic relatedness were observed between the two groups, suggesting that contact with relatives does not increase the rate of CWD transmission. Genotypes were further evaluated for genetic isolation by distance to infer gene flow and migration, information which could aid in the prediction of CWD spread across the landscape. Within the seven county study area of northern Illinois, female deer exhibited genetic isolation by distance while male deer did not. Research funded by USGS and IDNR.

Physiogenomic Analysis of the Puerto Rican Population

Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.

Accurate Inference of Subtle Population Structure (and Other Genetic Discontinuities) Using Principal Coordinates

BackgroundAccurate inference of genetic discontinuities between populations is an essential component of intraspecific biodiversity and evolution studies, as well as associative genetics. The most widely-used methods to infer population structure are model-based, Bayesian MCMC procedures that minimize Hardy-Weinberg and linkage disequilibrium within subpopulations. These methods are useful, but suffer from large computational requirements and a dependence on modeling assumptions that may not be met in real data sets. Here we describe the development of a new approach, PCO-MC, which couples principal coordinate analysis to a clustering procedure for the inference of population structure from multilocus genotype data.Methodology/Principal FindingsPCO-MC uses data from all principal coordinate axes simultaneously to calculate a multidimensional “density landscape”, from which the number of subpopulations, and the membership within subpopulations, is determined using a valley-seeking algorithm. Using extensive simulations, we show that this approach outperforms a Bayesian MCMC procedure when many loci (e.g. 100) are sampled, but that the Bayesian procedure is marginally superior with few loci (e.g. 10). When presented with sufficient data, PCO-MC accurately delineated subpopulations with population Fst values as low as 0.03 (G'st>0.2), whereas the limit of resolution of the Bayesian approach was Fst = 0.05 (G'st>0.35).Conclusions/SignificanceWe draw a distinction between population structure inference for describing biodiversity as opposed to Type I error control in associative genetics. We suggest that discrete assignments, like those produced by PCO-MC, are appropriate for circumscribing units of biodiversity whereas expression of population structure as a continuous variable is more useful for case-control correction in structured association studies.

Correcting for ascertainment bias in the inference of population structure

The ascertainment process of molecular markers amounts to disregard loci carrying alleles with low frequencies. This can result in strong biases in inferences under population genetics models if not properly taken into account by the inference algorithm. Attempting to model this censoring process in view of making inference of population structure (i.e.identifying clusters of individuals) brings up challenging numerical difficulties. These difficulties are related to the presence of intractable normalizing constants in Metropolis-Hastings acceptance ratios. This can be solved via an Markov chain Monte Carlo (MCMC) algorithm known as single variable exchange algorithm (SVEA). We show how this general solution can be implemented for a class of clustering models of broad interest in population genetics that includes the models underlying the computer programs STRUCTURE, GENELAND and GESTE. We also implement the method proposed for a simple example and show that it allows us to reduce the bias substantially. Further details and a computer program implementing the method are available from http://folk.uio.no/gillesg/AscB/.

PCA-based population structure inference with generic clustering algorithms

BackgroundHandling genotype data typed at hundreds of thousands of loci is very time-consuming and it is no exception for population structure inference. Therefore, we propose to apply PCA to the genotype data of a population, select the significant principal components using the Tracy-Widom distribution, and assign the individuals to one or more subpopulations using generic clustering algorithms.ResultsWe investigated K-means, soft K-means and spectral clustering and made comparison to STRUCTURE, a model-based algorithm specifically designed for population structure inference. Moreover, we investigated methods for predicting the number of subpopulations in a population. The results on four simulated datasets and two real datasets indicate that our approach performs comparably well to STRUCTURE. For the simulated datasets, STRUCTURE and soft K-means with BIC produced identical predictions on the number of subpopulations. We also showed that, for real dataset, BIC is a better index than likelihood in predicting the number of subpopulations.ConclusionOur approach has the advantage of being fast and scalable, while STRUCTURE is very time-consuming because of the nature of MCMC in parameter estimation. Therefore, we suggest choosing the proper algorithm based on the application of population structure inference.

AFLP Analysis of Intraspecific Variation Between Monilinia laxa Isolates from Different Hosts.

We analyzed with an amplified fragment length polymorphism (AFLP) marker system the genetic diversity and relationships among 67 Monilinia laxa isolates obtained from different host plants. From a total of 1,089 amplified bands scored using 20 primer combinations with two selective nucleotides, 354 were polymorphic and further used in genetic diversity analysis. Genetic relationships among isolates were assessed with different phenetic approaches, including unweighted pair group method with arithmetic mean clustering and principal coordinate analysis; the population's differentiation estimate was analyzed by molecular variance; and model-based clustering was employed to infer population structure. All four analyses clearly showed significant differences between isolates from apple trees and isolates from other host plants. No further grouping according to any other host plant was observed. The results indicate host specialization of apple isolates and support the taxonomic grouping of apple isolates.

A semiparametric test to detect associations between quantitative traits and candidate genes in structured populations

Although population-based association mapping may be subject to the bias caused by population stratification, alternative methods that are robust to population stratification such as family-based linkage analysis have lower mapping resolution. Recently, various statistical methods robust to population stratification were proposed for association studies, using unrelated individuals to identify associations between candidate genes and traits of interest. The association between a candidate gene and a quantitative trait is often evaluated via a regression model with inferred population structure variables as covariates, where the residual distribution is customarily assumed to be from a symmetric and unimodal parametric family, such as a Gaussian, although this may be inappropriate for the analysis of many real-life datasets. In this article, we proposed a new structured association (SA) test. Our method corrects for continuous population stratification by first deriving population structure and kinship matrices through a set of random genetic markers and then modeling the relationship between trait values, genotypic scores at a candidate marker and genetic background variables through a semiparametric model, where the error distribution is modeled as a mixture of Polya trees centered around a normal family of distributions. We compared our model to the existing SA tests in terms of model fit, type I error rate, power, precision and accuracy by application to a real dataset as well as simulated datasets.

Genetic structure, migration, and patterns of allelic richness among coho salmon (Oncorhynchus kisutch) populations of the Oregon coast

Genotypic data from eight microsatellite loci are used to infer population structure, effective population size, migration rates, and patterns of allelic richness among wild and hatchery populations of Oregon coastal coho salmon ( Oncorhynchus kisutch ). Corroborating the results of a previous study, we found relatively weak genetic structure among coho from different river basins, although some geographically and ecologically defined clades are supported. Contemporary migration rates among basins appear to be high and asymmetrical. Hatchery populations tended to resemble the wild populations from which they were founded, but presented significantly lower levels of allelic richness. Allelic richness was also low in Oregon coastal lake populations and peaked in the central region of the evolutionarily significant unit among wild river populations. We suggest that the observed patterns may reflect both current source–sink dynamics and post-Pleistocene colonization events.

Genetic diversity of Brazilian Pantaneiro horse and relationships among horse breeds

The objective of this work was to evaluate the genetic diversity of Brazilian Pantaneiro horse by microsatellite markers, investigate the effect of genetic bottlenecks and estimate genetic differentiation among four horse breeds. Genetic variation was estimated through allele frequencies and mean breed heterozygosity. Nei's genetic distances among the breeds Pantaneiro, Thoroughbred, Arabian, Spanish Pure Breed (Andalusian), and Uruguay Creole were calculated, and it was used to construct an UPGMA dendrogram. Clustering at different K values was calculated to infer population structure and assign individuals to populations. Nei's distances showed a minimum distance between Pantaneiro horse and Spanish Pure Breed (0.228), and similar distances from Spanish Pure Breed to Thoroughbred and to Arabian (0.355 and 0.332). It was observed a great level of diversity, clear distance from Pantaneiro horse to other breeds, and genetic uniformity within breed. It was verified a certain level of substructure of Pantaneiro horse showing no influences from the other studied breeds.