Sets of complementary phenotypic relationships across five isolated populations: Traces of expression of different gene complexes?

The aim of this study is to search for certain repeating phenotypic patterns, i.e. sets of complementary relationships across five isolated populations, which may represent the traces of expression of different genes or gene complexes. The study was conducted among isolates of five island populations of eastern Adriatic, Croatia, and the data were collected between 1979 and 1990. Selected phenotypic characteristics included measures of biological distances (e.g. anthropometrical body and head distances, physiological, dermatoglyphic and radiogrammetric bone distances), while other examined traits included sociocultural (linguistic), bio-cultural (migrational kinship) and genetic distances. The sample consisted of 6,286 examinees from 43 villages of five isolate populations. Correlations between distance matrices based on examined traits were analyzed in each of five populations using Mantel's test of matrix correspondence, and factor analysis (rotated principal component) was then performed over obtained correlation matrices. The results showed that there were several consistent and significant correlations between some analyzed traits across all of the studied isolate populations, which might indicate their regulation by the shared gene complexes or genome regions. The analyses identified three main clusters of correlations in all five isolate populations: the first one containing anthropometric measures (body and head measures and physiological properties in both sexes), the second one containing geographic distance-related traits (migrational kinship, linguistic and genetic distances), and the third one containing dermatoglyphic properties and radiogrammetric bone measures in both sexes. The higher order varimax rotation over the matrix of factor correlations revealed that the primary source of variation within all five analyzed populations was not sex-related, but rather variable-specific.     

Applications of pooled DNA samples to the assessment of population affinities: short tandem repeats

Pooled DNA samples have been used in association studies of Mendelian disease genes. This method involves combining equal quantities of DNA from patients and control subjects into separate pools and comparing the pools for distributions of genetic markers. In this study identical quantities of DNA from 300 individuals representing 6 populations were pooled and amplified for 296 loci using the touchdown polymerase chain reaction (PCR) method. The purpose of this study is to test the efficacy of pooled DNA markers in the reconstruction of the genetic structure of human populations. The populations sampled included Chuvash, Buryats, Kizhi, Native Americans, South Africans, and New York City whites. To test the accuracy of the allele-frequency distributions, we genotyped the Buryats and New York samples individually for six microsatellite markers and compared their frequencies to the allele frequencies derived from the electropherogram peak heights for the pooled DNA, producing a correlation of 0.9811 with a variance of less than 0.04. Two-dimensional scaling of genetic distances among the six populations produced clusters that reflected known historical relationships. A distance matrix was created using all 296 loci, and matrices based on individual chromosomes were correlated against the total matrix. As expected, the largest chromosomes had the highest correlations with the total matrix, whereas one of the smallest chromosomes, chromosome 22, had the lowest correlation and differed most from the combined STR distance matrix.     

Patterns of phenotypic covariation and correlation in modern humans as viewed from morphological integration

Proportionality of phenotypic and genetic distance is of crucial importance to adequately focus on population history and structure, and it depends on the proportionality of genetic and phenotypic covariance. Constancy of phenotypic covariances is unlikely without constancy of genetic covariation if the latter is a substantial component of the former. If phenotypic patterns are found to be relatively stable, the most probable explanation is that genetic covariance matrices are also stable. Factors like morphological integration account for such stability. Morphological integration can be studied by analyzing the relationships among morphological traits. We present here a comparison of phenotypic correlation and covariance structure among worldwide human populations. Correlation and covariance matrices between 47 cranial traits were obtained for 28 populations, and compared with design matrices representing functional and developmental constraints. Among-population differences in patterns of correlation and covariation were tested for association with matrices of genetic distances (obtained after an examination of 10 Alu-insertions) and with Mahalanobis distances (computed after craniometrical traits). All matrix correlations were estimated by means of Mantel tests. Results indicate that correlation and covariance structure in our species is stable, and that among-group correlation/covariance similarity is not related to genetic or phenotypic distance. Conversely, genetic and morphological distance matrices were highly correlated. Correlation and covariation patterns were largely associated with functional and developmental factors, which probably account for the stability of covariance patterns.     

Gene flow and functional connectivity in the natterjack toad

Functional connectivity is a key factor for the persistence of many specialist species in fragmented landscapes. However, connectivity estimates have rarely been validated by the observation of dispersal movements. In this study, we estimated functional connectivity of a real landscape by modelling dispersal for the endangered natterjack toad (Bufo calamita) using cost distance. Cost distance allows the evaluation of 'effective distances', which are distances corrected for the costs involved in moving between habitat patches in spatially explicit landscapes. We parameterized cost-distance models using the results of our previous experimental investigation of natterjack's movement behaviour. These model predictions (connectivity estimates from the GIS study) were then confronted to genetic-based dispersal rates between natterjack populations in the same landscape using Mantel tests. Dispersal rates between the populations were inferred from variation at six microsatellite loci. Based on these results, we conclude that matrix structure has a strong effect on dispersal rates. Moreover, we found that cost distances generated by habitat preferences explained dispersal rates better than did the Euclidian distances, or the connectivity estimate based on patch-specific resistances (patch viscosity). This study is a clear example of how landscape genetics can validate operational functional connectivity estimates.     

Phylogenetic Inference with Weighted Codon Evolutionary Distances

We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.     

Phylogeny of Finnish-Ugric populations

Genetic distances of 18 Finnish-Ugric and other populations of Europe, Asia and America by 28 alleles of 12 loci of proteins, enzymes and blood groups were calculated. The data of matrix of genetic distances and dendrogramme constructed by paired clusterisation method suggested that there was the relationship of Finnish-Ugric populations and some Caucasoids and North Mongoloid populations. These data give new approaches to the problem of Finnish-Ugric phylogenesis.     

Testing the "malaria hypothesis" for the case of Thailand: a genetic appraisal

This study provides statistical analyses of allele frequencies for populations of Thailand, with an attempt to trace the roles of differential malarial selection and genetic admixtures on the observed frequency variation of certain red cell genetic abnormalities (the two beta-globin variants--hemoglobin E and beta-thalassemia--and G-6PD deficiency), probably evolving under malarial endemicity. It is found that frequencies of hemoglobin E vary accordingly with those of G-6PD deficiency, and with diverse malarial ecology. The levels of genetic diversity are greater for hemoglobin E and G-6PD deficiency than for most other nonmalarial related genetic markers, suggesting the evolution of these two genetic abnormalities under differential selection. Results of the Mantel's statistical test for correspondence between distance matrices suggest distinctive patterns of allele frequency differentiation between malarial-related and nonmalarial-related genetic loci. Correlations between beta-globin and G-6PD genetic distances, as well as those between both sets of distances and the malarial distances, are statistically significant. On the other hand, a correlation between malarial distances and the genetic distances for nonmalarial-related genetic loci is not significant statistically. A correlation between the beta-globin genetic distances and the genetic distances for nonmalarial-related genetic loci is, however, statistically significant. The latter result could be attributed largely to the clustering of relatively high hemoglobin E frequencies among genetically closely related populations of northeastern Thailand, whose recent homeland was Laos. The consistently low frequencies of beta-thalassemia observed in most studied populations are explained as a result of the replacement of this genetic variant by hemoglobin E, under long-term malarial selection.     

The evolution of the phenotypic covariance matrix: evidence for selection and drift in Melanoplus

Phenotypic variation in trait means is a common observation for geographically separated populations. Such variation is typically retained under common garden conditions, indicating that there has been evolutionary change in the populations, as a result of selection and/or drift. Much less frequently studied is variation in the phenotypic covariance matrix (hereafter, P matrix), although this is an important component of evolutionary change. In this paper, we examine variation in the phenotypic means and P matrices in two species of grasshopper, Melanoplus sanguinipes and M. devastator. Using the P matrices estimated for 14 populations of M. sanguinipes and three populations of M. devastator we find that (1) significant differences between the sexes can be attributed to scaling effects; (2) there is no significant difference between the two species; (3) there are highly significant differences among populations that cannot be accounted for by scaling effects; (4) these differences are a consequence of statistically significant patterns of covariation with geographic and environmental factors, phenotypic variances and covariances increasing with increased temperature but decreasing with increased latitude and altitude. This covariation suggests that selection has been important in the evolution of the P matrix in these populations Finally, we find a significant positive correlation between the average difference between matrices and the genetic distance between the populations, indicating that drift has caused some of the variation in the P matrices.     

Genetic code,hamming distance and stochastic matrices

In this paper we use the Gray code representation of the genetic code C = 00, U = 10, G = 11 and A = 01 (C pairs with G, A pairs with U) to generate a sequence of genetic code-based matrices. In connection with these code-based matrices, we use the Hamming distance to generate a sequence of numerical matrices. We then further investigate the properties of the numerical matrices and show that they are doubly stochastic and symmetric. We determine the frequency distributions of the Hamming distances, building blocks of the matrices, decomposition and iterations of matrices. We present an explicit decomposition formula for the genetic code-based matrix in terms of permutation matrices, which provides a hypercube representation of the genetic code. It is also observed that there is a Hamiltonian cycle in a genetic code-based hypercube.     

Genetic relationships among some new cat populations sampled in Europe: A spatial autocorrelation analysis

The allelic frequencies of nine Mendelizing genetic characteristics that control coat colour, tabby and length and some skeletal abnormalities have been studied in four feral domestic cat populations, two in the north of Catalonia (Girona and Roses & L’Estartit, northeastern Spain) and two Adriatic Italian populations (Rimini and Venice). Using different genetic and multivariate analyses (Nei’s and Cavalli-Sforza and Edwards’s genetic distances, phenograms and cladograms using different algorithms, strict consensus trees, canonical population, principal coordinates and nonmetric multidimensional scaling analyses), I show the genetic relationships between these populations and other Western European cat populations previously studied. In the Western European area comprising Catalonia, Italy, France and Great Britain, I found significant spatial structure for thet ^b, l andW alleles and for the average correlogram for the seven alleles studied as a whole using a spatial autocorrelation analysis. The genetic distance matrices between these European cat populations also showed a significant correlation with the geographical distance between these populations using Mantel’s test. These analyses showed that in each of these countries, local cat populations have characteristic genetic profiles which were different to neighbouring populations in nearby countries. At least in this area of Western Europe, the geographical distances between cat populations (although the gene flow can be relatively high) is an important factor which can explain differences in allele frequencies between these populations.     

Solving alpha‐diversity by morphological markers contributes to arranging the systematic status of a crayfish species complex (Crustacea,Decapoda)

Since innovative molecular approaches in phylogenetics solely based on small gene fragments have often generated widely complicated interpretations of crayfish diversity, we propose a geometric morphometric study integrated with previous molecular data to provide robust estimates of phylogeny and classification of the Austropotamobius pallipes complex, genetically divided into several species and subspecies. We discuss whether cephalothorax shape variation can show phylogenetic signals congruent to those derived from analyses of mitochondrial and nuclear markers. Our results support the hypothesis that carapace form is potentially informative in the reconstruction of crayfish phylogeny. In the phenetic analyses, populations collected within the Italian territory form different unexpected clusters, each involving distant populations of different genetic haplogroups, suggesting a within‐species convergence probably due to a series of local adaptations. The phylogenetic analysis performed using a neighbour‐joining algorithm showed interesting relationships amongst the studied populations. In particular, the geometric morphometric matrices showed a slight congruence with some genetic distances, allowing the discrimination of three major lineages: (1) Istran + Apennine group; (2) Arno group; (3) north‐western group. Finally, our observations support some molecular data with a lighter phylogenetic signal that do not suggest a strong separation of A. pallipes into clades and sub‐clades.     

THE COVARIANCE STRUCTURE OF LIFE-HISTORY CHARACTERS IN DAPHNIA PULEX

The genetic covariance structure for life-history characters in two populations of cyclically parthenogenetic Daphnia pulex indicates considerable positive correlation among important fitness components, apparently at odds with the expectation if antagonistic pleiotropy is the dominant cause of the maintanence of genetic variation. Although there is no genetic correlation between offspring size and offspring number, present growth and present reproduction are both strongly positively correlated genetically with future reproduction, and early maturity is genetically correlated with larger clutch size. Although the ubiquity of antagonistic pleiotropy has been recently questioned, there are peculiarities of cyclical parthenogenesis that could lead to positive life-history covariance even when negative covariance would be expected in a similar sexual species. These include the influence of nonadditive gene action on evolution in clonally reproducing organisms, and the periodic release of hidden genetic variance within populations of cyclical parthenogens. Examination of matrix similarity, using the bootstrap for distribution-free hypothesis testing, reveals no evidence to suggest that the genetic covariance matrices differ between the populations. However, there is considerable evidence that the phenotypic and environmental covariance matrices differ between populations. These results indicate approximate stability of the genetic covariance matrix within species, an important assumption of many phenotypic evolution models, but should caution against the use of phenotypic in place of genetic covariance matrices.     

Similarity in G matrix structure among natural populations of Arabidopsis lyrata

Understanding the stability of the G matrix in natural populations is fundamental for predicting evolutionary trajectories; yet, the extent of its spatial variation and how this impacts responses to selection remain open questions. With a nested paternal half‐sib crossing design and plants grown in a field experiment, we examined differences in the genetic architecture of flowering time, floral display, and plant size among four Scandinavian populations of Arabidopsis lyrata. Using a multivariate Bayesian framework, we compared the size, shape, and orientation of G matrices and assessed their potential to facilitate or constrain trait evolution. Flowering time, floral display and rosette size varied among populations and significant additive genetic variation within populations indicated potential to evolve in response to selection. Yet, some characters, including flowering start and number of flowers, may not evolve independently because of genetic correlations. Using a multivariate framework, we found few differences in the genetic architecture of traits among populations. G matrices varied mostly in size rather than shape or orientation. Differences in multivariate responses to selection predicted from differences in G were small, suggesting overall matrix similarity and shared constraints to trait evolution among populations.     

Forest cover mediates genetic connectivity of northwestern cougars

Population structure, connectivity, and dispersal success of individuals can be challenging to demonstrate for solitary carnivores with low population densities. Though the cougar (Puma concolor) is widely distributed throughout North America and is capable of dispersing long distances, populations can be geographically structured and genetic isolation has been documented in some small populations. We described genetic structure and explored the relationship between landscape resistance and genetic variation in cougars in Washington and southern British Columbia using allele frequencies of 17 microsatellite loci for felids. We evaluated population structure of cougars using the Geneland clustering algorithm and spatial principal components analysis. We then used Circuitscape to estimate the landscape resistance between pairs of individuals based on rescaled GIS layers for forest canopy cover, elevation, human population density and highways. We quantified the effect of landscape resistance on genetic distance using multiple regression on distance matrices and boosted regression tree analysis. Cluster analysis identified four populations in the study area. Multiple regression on distance matrices and boosted regression tree models indicated that only forest canopy cover and geographic distance between individuals had an effect on genetic distance. The boundaries between genetic clusters largely corresponded with breaks in forest cover, showing agreement between population structure and genetic gradient analyses. Our data indicate that forest cover promotes gene flow for cougars in the Pacific Northwest, which provides insight managers can use to preserve or enhance genetic connectivity.     

Structure and Genetic Relationship Among Brazilian Naturalized and Imported Goat Breeds

Fourteen goat populations were studied regarding their genetic relationship and structure. Parameters of genetic diversity (HT, HS and GST) and F statistic (FIS, FIT and FST) were estimated. Undefined breed populations presented high homogeneity, as did imported breed populations. Naturalized breed populations showed high differentiation. The genetic distances separating these 14 goat populations were calculated from gene frequency data for eight blood genetic markers (esterase D, phosphoglucomutase 1, carbonic anhydrase II, peptidase B, amylase, haemoglobin, transferrin, and protein X). Working with the genetic distance matrix of Nei corrected for small samples (DA), we constructed a dendrogram using the unweighted pair group method with arithmetic mean. DA values ranged from 0.0027 to 0.1518. The dendrogram divided the populations into two groups, one consisting of three populations of naturalized breeds, and another including the other populations (imported breeds, undefined breeds and some other naturalized breeds).     

Identifying the environmental factors that determine the genetic structure of populations

The study of population genetic structure is a fundamental problem in population biology because it helps us obtain a deeper understanding of the evolutionary process. One of the issues most assiduously studied in this context is the assessment of the relative importance of environmental factors (geographic distance, language, temperature, altitude, etc.) on the genetic structure of populations. The most widely used method to address this question is the multivariate Mantel test, a nonparametric method that calculates a correlation coefficient between a dependent matrix of pairwise population genetic distances and one or more independent matrices of environmental differences. Here we present a hierarchical Bayesian method that estimates F(ST) values for each local population and relates them to environmental factors using a generalized linear model. The method is demonstrated by applying it to two data sets, a data set for a population of the argan tree and a human data set comprising 51 populations distributed worldwide. We also carry out a simulation study to investigate the performance of the method and find that it can correctly identify the factors that play a role in the structuring of genetic diversity under a wide range of scenarios.     

Genetic affinities of Jewish populations.

Genetic relations between various Jewish (J) and non-Jewish (NJ) populations were assessed using two sets of data. The first set contained 12 pairs of matched J and NJ populations from Europe, the Middle East, and North Africa, for which 10 common polymorphic genetic systems (13 loci) were available. The second set included 22 polymorphic genetic systems (26 loci) with various numbers of populations (ranging from 21 to 51) for each system. Therefore, each system was studied separately. Nei's standard genetic distance (D) matrices obtained for these two sets of data were tested against design matrices specifying hypotheses concerning the affiliations of the tested populations. The tests against single designs were carried out by means of Mantel tests. Our results consistently show lower distances among J populations than with their NJ neighbors, most simply explained by the common origin of the former. Yet, there is evidence also of genetic similarity between J and corresponding NJ populations, suggesting reciprocal gene flow between these populations or convergent selection in a common environment. The results of our study also indicate that stochastic factors are likely to have played a role in masking the descent relationships of the J populations.     

RAPD variation and population genetic structure in Prunus mahaleb (Rosaceae), an animal-dispersed tree

We examined the patterns of random amplified polymorphic DNA (RAPD) variation among seven Prunus mahaleb (Rosaceae) populations extending over approximately 100 km2 to examine local differentiation in relation to spatial isolation due to both geographical distance and differences in elevation. No less than 51. 4% of the RAPD loci were polymorphic, but very few were fixed and among-population variation accounted for 16.46% of variation in RAPD patterns. Mean gene diversity was 0.1441, with mean Nei's genetic diversity for individual populations ranging between 0.089 and 0.149. Mean GST value across loci was 0.1935 (range, 0.0162-0.4685), giving an average estimate for Nm of 1.191. These results suggest extensive gene flow among populations, but higher GST and lower Nm values relative to other outcrossing, woody species with endozoochorous dispersal, also suggest a process of isolation by distance. The combined effect of both geographical and elevation distances and nonoverlapping flowering and fruiting phenophases on the GST matrix was partially significant, revealing only marginal isolation of the P. mahaleb populations. The matrix correlation between estimated Nm values among populations and the geographical + elevation distance matrices (r = -0.4623, P = 0.07), suggests a marginal trend for more isolated populations to exchange less immigrants. Long-distance seed dispersal by efficient medium-sized frugivorous birds and mammals is most likely associated to the high levels of within-population genetic diversity. However, vicariance factors and demographic bottlenecks (high postdispersal seed and seedling mortality) explain comparatively high levels of local differentiation.     

NONSTATIONARY PATTERNS OF ISOLATION‐BY‐DISTANCE: INFERRING MEASURES OF LOCAL GENETIC DIFFERENTIATION WITH BAYESIAN KRIGING

Patterns of isolation‐by‐distance (IBD) arise when population differentiation increases with increasing geographic distances. Patterns of IBD are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate nonstationary patterns of IBD where the rate at which genetic differentiation accumulates varies across space. To characterize nonstationary patterns of IBD, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with two datasets: single nucleotide polymorphisms from human Swedish populations and dominant markers for alpine plant species.