Phenotypical and genetic differentiation of human populations for morphological and psychophysiological traits. Factor analysis

The multivariate genetic factor analysis is used, as first attempt, to study genetic bases of correlation variability of neurodynamic and psychodynamic levels of individual organization among isolates of Daghestan. Closer similarity between factors described in templates of phenotypic correlations is explained by lower heritability of the parameters under study. Interpopulation differences revealed by the multivariate genetic analysis are the result of differences in the genetic structure of the populations.     

Comparing G: multivariate analysis of genetic variation in multiple populations

The additive genetic variance–covariance matrix (G) summarizes the multivariate genetic relationships among a set of traits. The geometry of G describes the distribution of multivariate genetic variance, and generates genetic constraints that bias the direction of evolution. Determining if and how the multivariate genetic variance evolves has been limited by a number of analytical challenges in comparing G-matrices. Current methods for the comparison of G typically share several drawbacks: metrics that lack a direct relationship to evolutionary theory, the inability to be applied in conjunction with complex experimental designs, difficulties with determining statistical confidence in inferred differences and an inherently pair-wise focus. Here, we present a cohesive and general analytical framework for the comparative analysis of G that addresses these issues, and that incorporates and extends current methods with a strong geometrical basis. We describe the application of random skewers, common subspace analysis, the 4th-order genetic covariance tensor and the decomposition of the multivariate breeders equation, all within a Bayesian framework. We illustrate these methods using data from an artificial selection experiment on eight traits in Drosophila serrata, where a multi-generational pedigree was available to estimate G in each of six populations. One method, the tensor, elegantly captures all of the variation in genetic variance among populations, and allows the identification of the trait combinations that differ most in genetic variance. The tensor approach is likely to be the most generally applicable method to the comparison of G-matrices from any sampling or experimental design.     

Biometric analysis of Brachionus plicatilis ecotypes from Spanish lagoons

Univariate comparisons and several multivariate statistical analyses have been performed to study the morphometric variability of B. plicatilis. Both laboratory clones kept under constant conditions and natural populations from different Spanish lagoons and different times of the year have been compared. The results show that not only size, but also allometric coefficients are influenced by environmental factors. However, an important genetic component in the variation of shape and size has been visualized. A clear North-South ordination of the populations of the different lagoons and an important dispersion between their summer populations as well as great differences due to seasonal variation became apparent by the multivariate statistical analysis used.     

Genetic Clustering of Hepatitis C Virus Strains and Severity of Recurrent Hepatitis after Liver Transplantation

The influence of viral factors on the severity of hepatitis C virus (HCV)-related liver disease is controversial. We studied 68 liver transplant patients with recurrent hepatitis C, of whom 53 were infected by genotype 1 strains. Relationships between core sequences, serum HCV RNA levels, and fibrosis scores for each patient were analyzed in pairwise fashion 5 years after transplantation. We used Mantel's test, a matrix correlation method, to evaluate the correspondence between measured genetic distances and observed phenotypic differences. No clear relationship was found when all 68 patients were analyzed. In contrast, when the 53 patients infected by genotype 1 strains were analyzed, a strong positive relationship was found between genetic distance and differences in 5-year fibrosis scores (P = 0.001) and differences in virus load (P = 0.009). In other words, the smaller the genetic distance between two patients' viral core sequences, the smaller the difference between the two patients' fibrosis scores and viral replication levels. No relationship was found between genetic distance and differences in age, sex, or immunosuppression. In multivariate analysis, the degree of fibrosis was negatively related to the virus load (r = -0.68; P = 0.003). In the particular setting of liver transplantation, and among strains with closely related phylogenetic backgrounds (genotype 1), this study points to a correlation between the HCV genetic sequence and the variability of disease expression.     

Microsatellite and morphometric variation in Drosophila gouveai: the relative importance of historical and current factors in shaping the genetic population structure

Drosophila gouveai is a cactus-breeding species with a naturally fragmented distribution in central-western and southeastern Brazil. In this study, a neutral genetic marker (microsatellite DNA) and a quantitative trait (wing morphology) were used to investigate the population structure of eight populations of D. gouveai . Quantitative analysis was done using a morphometric approach and multivariate analysis of 17 wing parameters. Drosophila gouveai showed a large degree of genetic population differentiation ( F _ST = 0.245). A molecular analysis of variance showed that the population structure was attributable mainly to genetic differences among the population groups, which were correlated with regional groupings. A Bayesian cluster analysis also identified the same regional groupings as contributing to the population structure. Assignment tests revealed that the current gene flow was very restricted. The divergence in wing morphology among populations was also high, and revealed a geographical pattern that conformed to a latitudinal cline. In contrast to current factors such as migration-drift equilibrium, these results indicated that the genetic population structure of D. gouveai was shaped predominantly by historical factors.     

Variability of the essential oil of Viola etrusca

Essential oils obtained from different populations of Viola etrusca from Italy have been analysed to verify the phenotypic discontinuity observed in a previous study. All of the essential oils contained methyl salicylate as a main constituent. However, multivariate analysis showed differences among some populations, in particular between northern and southern ones. Results suggest that this species could be undergoing a slow schizogenetic differentiation process due to its genetic isolation.     

Dermatoglyphs and brachial plexus palsy

Perinatal brachial plexus palsy (PBPP) is a handicap quite commonly encountered in daily routine. Although birth trauma is considered to be the major cause of the defect, it has been observed that PBPP occurs only in some infants born under identical or nearly identical conditions. The aim of this study was to test the hypothesis of genetic predisposition for PBPP. It is well known that digito-palmar dermatoglyphs can be used to determine hereditary roots of some diseases. Thus, we found it meaningful to do a study analysis of digito-palmar dermatoglyphs in this disease as well, conducting it on 140 subjects (70 males and 70 females) diagnosed with PBPP. The control group was composed of fingerprints obtained from 400 adult and phenotypically healthy subjects (200 males and 200 females) from the Zagreb area. The results of multivariate and univariate analysis of variance have shown statistically significant differences between the groups observed. In spite of lower percentage of accurately classified female subjects by discriminant analysis, the results of quantitative analysis of digito-palmar dermatoglyphs appeared to suggest a genetic predisposition for the occurrence of PBPP.     

Morphological variability between wild populations and inbred stocks of a Chinese minnow, Gobiocypris rarus

Gobiocypris rarus, a small, native cyprinid fish, is currently widely used in research on fish pathology, genetics, toxicology, embryology, and physiology in China. To develop this species as a model laboratory animal, inbred strains have been successfully created. In this study, to explore a method to discriminate inbred strains and evaluate inbreeding effects, morphological variation among three wild populations and three inbred stocks of G. rarus was investigated by the multivariate analysis of eight meristic and 30 morphometric characters. Tiny intraspecific variations in meristic characters were found, but these were not effective for population distinction. Stepwise discriminant analysis and cluster analysis of conventional measures and truss network data showed considerable divergence among populations, especially between wild populations and inbred stocks. The average discriminant accuracy for all populations was 82.1% based on conventional measures and 86.4% based on truss data, whereas the discriminant accuracy for inbred strains was much higher. These results suggested that multivariate analyses of morphometric characters are an effective method for discriminating inbred strains of G. rarus. Morphological differences between wild populations and inbred strains appear to result from both genetic differences and environmental factors. Thirteen characters, extracted from stepwise discriminant analysis, played important roles in morphological differentiation. These characters were mainly measures related to body depth and head size.     

Genetic differentiation in a captive population of the endangered Siberian crane (Grus leucogeranus Pall.)

DNA fingerprinting, followed by multivariate analysis of data, was used to characterize genetic heterogeneity in captive populations of the endangered Siberian and sandhill cranes. The genetic structure revealed reflected the natural population and species distributions. The relevant groups differed not only from each other, but also from interspecies and inter-population hybrids bred in captivity. In this study we have tested an approach to the analysis of population structure based on individual genotypes. Interpretation of fingerprinting data by means of the analytical system applied here is a useful and reliable procedure for the estimation of genetic relationships between individuals.     

Divergence in mating signals correlates with ecological variation in the migratory songbird, Swainson's thrush (Catharus ustulatus)

Song divergence among populations of passerine birds is recognized as a potentially important premating isolation mechanism and may represent the first step in speciation. Because song divergence may be influenced by an array of acoustic, ecological, and genetic factors, the study of its origin requires a multifaceted approach. Here we describe the relationship between acoustic, neutral genetic and ecological variation in five populations of the Swainson's thrush: two from coastal temperate rainforest habitat representing the 'russet-backed' subspecies group, two from inland coniferous forest habitat representing the 'olive-backed' subspecies group, and one mixed locality that resides within a contact zone between the two groups. Song in the five populations is analysed using a multivariate analysis of spectral and temporal measurements, population genetic structure is assessed using an analysis of five microsatellite loci and ecological differences between populations are quantified using an analysis of climatic parameters. Matrix correspondence tests are used to distinguish between the potential for drift and selection in driving song divergence. No significant correlation was found between acoustic and genetic distance suggesting that song divergence cannot be explained by drift alone. A significant correlation between ecological and acoustic distance after accounting for genetic distance, suggests a potential role for ecological selection on divergence in spectral and temporal components of Swainson's thrush song.     

Use of the integral parameter of dermatoglyphic differences for determining the type of zygosity of twins]

A method is described increasing the reliability of twin zygosity diagnosis in cases when the possibility of using a large number of mendelian markers is restricted. The method is based on the determination of generalized index of dermatoglyphic differences between members of twin pair for 18 characteris of finger and palm dermatoglyphics and on principles of multivariate genetic analysis, which is worked out to determine the degree of heritability of multifactorial character and to study the structure of hereditary predisposition to multifactorial diseases. The efficiency of the method with respect to determinating the type of twin zygosity is approximately equivalent to the efficiency of using 5--6 mendelian marker systems.     

Inclusion of Dominance Effects in the Multivariate GBLUP Model

New proposals for models and applications of prediction processes with data on molecular markers may help reduce the financial costs of and identify superior genotypes in maize breeding programs. Studies evaluating Genomic Best Linear Unbiased Prediction (GBLUP) models including dominance effects have not been performed in the univariate and multivariate context in the data analysis of this crop. A single cross hybrid construction procedure was performed in this study using phenotypic data and actual molecular markers of 4,091 maize lines from the public database Panzea. A total of 400 simple hybrids resulting from this process were analyzed using the univariate and multivariate GBLUP model considering only additive effects additive plus dominance effects. Historic heritability scenarios of five traits and other genetic architecture settings were used to compare models, evaluating the predictive ability and estimation of variance components. Marginal differences were detected between the multivariate and univariate models. The main explanation for the small discrepancy between models is the low- to moderate-magnitude correlations between the traits studied and moderate heritabilities. These conditions do not favor the advantages of multivariate analysis. The inclusion of dominance effects in the models was an efficient strategy to improve the predictive ability and estimation quality of variance components.     

Genetic differentiation in a captive population of the endangered Siberian crane (Grus leucogeranus Pall.)

DNA fingerprinting, followed by multivariate analysis of data, was used to characterize genetic heterogeneity in captive populations of the endangered Siberian and sandhill cranes. The genetic structure revealed reflected the natural population and species distributions. The relevant groups differed not only from each other, but also from interspecies and inter-population hybrids bred in captivity. In this study we have tested an approach to the analysis of population structure based on individual genotypes. Interpretation of fingerprinting data by means of the analytical system applied here is a useful and reliable procedure for the estimation of genetic relationships between individuals.     

Environmental effects on the structure of the G‐matrix

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance–covariance ( G ) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between‐environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between‐population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G . Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.     

Multivariate heredity of melanin-based coloration,body mass and immunity

The genetic covariation among different traits may cause the appearance of correlated response to selection on multivariate phenotypes. Genes responsible for the expression of melanin-based color traits are also involved in other important physiological functions such as immunity and metabolism by pleiotropy, suggesting the possibility of multivariate evolution. However, little is known about the relationship between melanin coloration and these functions at the additive genetic level in wild vertebrates. From a multivariate perspective, we simultaneously explored inheritance and selection of melanin coloration, body mass and phytohemagglutinin (PHA)-mediated immune response by using long-term data over an 18-year period collected in a wild population of the common kestrel Falco tinnunculus. Pedigree-based quantitative genetic analyses showed negative genetic covariance between melanin-based coloration and body mass in male adults and positive genetic covariance between body mass and PHA-mediated immune response in fledglings as predicted by pleiotropic effects of melanocortin receptor activity. Multiple selection analyses showed an increased fitness in male adults with intermediate phenotypic values for melanin color and body mass. In male fledglings, there was evidence for a disruptive selection on rump gray color, but a stabilizing selection on PHA-mediated immune response. Our results provide an insight into the evolution of multivariate traits genetically related with melanin-based coloration. The differences in multivariate inheritance and selection between male and female kestrels might have resulted in sexual dimorphism in size and color. When pleiotropic effects are present, coloration can evolve through a complex pathway involving correlated response to selection on multivariate traits.     

Reaction norms of Arabidopsis. V. Flowering time controls phenotypic architecture in response to nutrient stress

The evolutionary and environmental stability of character correlations has increasingly been the focus of ecological and quantitative genetic studies. Although the genetic stability of character correlations is a central assumption of quantitative genetic models of phenotypic evolution, theoretical considerations suggest that both the genetic and the phenotypic architecture should change in response to selection and to environmental heterogeneity. We investigate genetic (population) differences and plasticity to nutrient availability of the phenotypic architecture describing the whole-plant phenotype of Arabidopsis thaliana (Brassicaceae). We found significant genetic differences among early and late flowering ecotypes in the relationships between several traits, when a path-analytical model was used to estimate character correlations. Furthermore, we found significant plasticity of several path coefficients when nutrient levels were altered. A whole-plant analysis considering all paths in the model simultaneously confirmed that populations of A. thaliana are characterized by distinct phenotypic architectures, and that these are altered in different ways by environmental changes. We discuss the implications of these findings for our understanding of selective pressure on and response by multivariate phenotypes.     

Genetic diversity measures of local European beef cattle breeds for conservation purposes

This study was undertaken to determine the genetic structure, evolutionary relationships, and the genetic diversity among 18 local cattle breeds from Spain, Portugal, and France using 16 microsatellites. Heterozygosities, estimates of Fst, genetic distances, multivariate and diversity analyses, and assignment tests were performed. Heterozygosities ranged from 0.54 in the Pirenaica breed to 0.72 in the Barrosã breed. Seven percent of the total genetic variability can be attributed to differences among breeds (mean F_st = 0.07; P < 0.01). Five different genetic distances were computed and compared with no correlation found to be significantly different from 0 between distances based on the effective size of the population and those which use the size of the alleles. The Weitzman recursive approach and a multivariate analysis were used to measure the contribution of the breeds diversity. The Weitzman approach suggests that the most important breeds to be preserved are those grouped into two clusters: the cluster formed by the Mirandesa and Alistana breeds and that of the Sayaguesa and Tudanca breeds. The hypothetical extinction of one of those clusters represents a 17% loss of diversity. A correspondence analysis not only distinguished four breed groups but also confirmed results of previous studies classifying the important breeds contributing to diversity. In addition, the variation between breeds was sufficiently high so as to allow individuals to be assigned to their breed of origin with a probability of 99% for simulated samples.     

POPULATION STRUCTURE OF MORPHOLOGICAL TRAITS IN CLARKIA DUDLEYANA. II. CONSTANCY OF WITHIN-POPULATION GENETIC VARIANCE

Recent quantitative genetic studies have attempted to infer long-term selection responsible for differences in observed phenotypes. These analyses are greatly simplified by the assumption that the within-population genetic variance remains constant through time and over space, or for the multivariate case, that the matrix of additive genetic variances and covariances (G matrix) is constant. We examined differences in G matrices and the association of these differences with differences in multivariate means (Mahalanobis D²) among 11 populations of the California endemic annual plant, Clarkia dudleyana. Based on nine continuous morphological traits, the relationship between Mahalanobis D² and a distance measure summarizing differences in G matrices reflected no concomitant change in (co)variances with changes in means. Based on both broad- and narrow-sense analyses, we found little evidence that G matrices differed between populations. These results suggest that both the additive and nonadditive (co)variances for traits have remained relatively constant despite changes in means.     

Meaning of biodistance statistics: a test case using adult monozygotic twins

Anthropometry, historically one of the primary research techniques in physical anthropology, has been widely utilized in biodistance studies. The complex genetic and environmental interaction that governs the expression of anthropometric dimensions, together with concerns over measurement error, have sometimes clouded the interpretation of biodistances based upon anthropometry. In this study, 51 pairs of adult monozygotic twins were analysed using discriminant analysis and Mahalanobis' generalized distance. Both male and female twins, grouped by first- versus second-born, displayed very small, statistically insignificant distances between groups. When literature estimates of intra-observer measurement errors were used as a frame of reference, the average absolute differences between the twin pairs were approximately twice the size of the measurement error estimates. The results of this study suggest that, first, the environmental effect upon the genetically influenced traits measured by anthropometry is not large enough to bring about significant multivariate differences between identical twin pairs; and, second, biodistance studies based upon anthropometry can be reliable so long as measurement error is minimized.