Factor and principal component analyses as alternatives to index selection

Summary Selections from factor and principal component analyses were compared with those from the Smith-Hazel index when selecting for several switchgrass (Panicum virgatum L.) traits. The objective of this study was to examine several alternatives to index selection. Such procedures would potentially eliminate problems of selection associated with Smith-Hazel indices, including errors in genetic parameter estimates and difficulty in assigning relative economic weights to traits. Selection was performed on 1,280 plants that were evaluated over 2 years at 1 location, in a randomized complete block design with 4 replicates. The plants were evaluated for forage yield and several forage quality traits. The comparisons of index selection with principal factor analysis, maximum-likelihood factor analysis and principal component analysis were made for three sets of traits (five traits per set) to estimate repeatability for the comparisons. Multivariate analyses were performed on both simple and genotypic correlation matrices. Comparisons were made by computing Spearman's rank correlations between selection index plant scores and scores computed from multivariate analysis and by determining the number of plants selected in common for the selection methods. Among the three multivariate analysis methods evaluated in this study, principal component analysis had the highest correlation with index selection. The high correlation for principal component analysis of simple correlation matrices indicates the potential for using this statistical method for selection purposes. This would permit the breeder to reduce field costs (e.g., time, labor, equipment) required to obtain the genetic parameter estimates necessary to construct selection indices.     

Ornaments Reveal Resistance of North European Cultures to the Spread of Farming

The transition to farming is the process by which human groups switched from hunting and gathering wild resources to food production. Understanding how and to what extent the spreading of farming communities from the Near East had an impact on indigenous foraging populations in Europe has been the subject of lively debates for decades. Ethnographic and archaeological studies have shown that population replacement and admixture, trade, and long distance diffusion of cultural traits lead to detectable changes in symbolic codes expressed by associations of ornaments on the human body. Here we use personal ornaments to document changes in cultural geography during the Mesolithic-Neolithic transition. We submitted a binary matrix of 224 bead-types found at 212 European Mesolithic and 222 Early Neolithic stratigraphic units to a series of spatial and multivariate analyses. Our results reveal consistent diachronic and geographical trends in the use of personal ornaments during the Neolithisation. Adoption of novel bead-types combined with selective appropriation of old attires by incoming farmers is identified in Southern and Central Europe while cultural resistance leading to the nearly exclusive persistence of indigenous personal ornaments characterizes Northern Europe. We argue that this pattern reflects two distinct cultural trajectories with different potential for gene flow.     

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.     

Killing pigs and talking to nonna: “wog” versus “cosmopolitan” Italianitá among second-generation Italian-Australians and the role of family

This paper extends the literature on second-generation migrants by examining the construction of ethnicity (Italianitá) over time. We compare two cohorts of second-generation Italian-Australians: the post-World War II cohort and the post-1980s cohort. Ethnographic data for this research were collected with second-generation Italian-Australians in Perth over a thirty-year period. Our findings highlight important differences between these two groups based on socio-historical context and transnational experiences. Informants draw on these differences to distinguish between “wog” vs. “cosmopolitan” forms of Italianitá. While these contrasting identities highlight cultural discontinuities between cohorts, both groups construct their ethnicity through the trope of the Italian migrant family. Employing the theoretical notions of “intimate culture” and “familial habitus” we theorize family as integral to conceptualizations of ethnic field and show how it has been overlooked and devalued in analyses of diaspora politics and identity.     

A Comparison of Multivariate Genome-Wide Association Methods

Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three quantitative traits and one bi-allelic quantitative trait locus (QTL), and varied the number of traits associated with the QTL (explained variance 0.1%), minor allele frequency of the QTL, residual correlation between the traits, and the sign of the correlation induced by the QTL relative to the residual correlation. We compared the power of the methods using empirically fixed significance thresholds (α = 0.05). Our results showed that the multivariate methods implemented in PLINK, SNPTEST, MultiPhen and BIMBAM performed best for the majority of the tested scenarios, with a notable increase in power for scenarios with an opposite sign of genetic and residual correlation. All multivariate analyses resulted in a higher power than univariate analyses, even when only one of the traits was associated with the QTL. Hence, use of multivariate GWAS methods can be recommended, even when genetic correlations between traits are weak.     

Structure and stability of genetic variance–covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three‐spined stickleback

The genetic variance–covariance matrix ( G ) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G ‐matrices is limited for two reasons. First, phenotypes are high‐dimensional, whereas traditional statistical methods are tuned to estimate and analyse low‐dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high‐dimensional G ‐matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half‐sib breeding design of three‐spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low‐temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability—as well as the similarity among G ‐matrices—may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G ‐matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G , they also illustrate that by enabling the estimation of large G ‐matrices, the BSFG method can improve predicted evolutionary responses to selection.     

Phenotypic variation and covariation indicate high evolvability of acoustic communication in crickets

Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and Gryllus texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive‐dominance variation was estimated. Finally, phenotypic variance–covariance ( P ) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions, and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits, we found evidence for X‐linked inheritance. On the one hand, the observed genetic architecture does not suggest rapid divergence, although sex linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences.     

Leaf size, sapling allometry, and Corner's rules: phylogeny and correlated evolution in maples (Acer)

We studied the evolution of leaf size, sapling canopy allometry, and related traits in 17 Acer species growing in the understory of temperate deciduous forests, using parsimony methods, randomization tests, and independent contrasts calculated on idena phylogeny inferred from nuclear ribosomal internal transcribed spacer (ITS) sequences. Bivariate correlations and multivariate analyses indicated two independent suites of coevolving traits, and the results were robust over a range of alternative phylogenies. The first suite consisted of strong positive correlations among twig thickness, leaf size, inflorescence length, and branch spacing (Corner's rules). Seed size and mature height were also weakly corre- lated with these traits. The second suite reflected aspects of sapling crown allometry, including crown size, stem diameter, and total leaf area, which appear to be related to shade tolerance. There was a weak negative correlation between sapling crown size and mavegetative ture height, but no correlation with leaf or seed size. Most correlattion were similar in magnitude for ahistorical and independent contrasts analyses, and discrepancies between these two measures were greater in traits with lower levels of convergent evolution. The evolutionary correlations among twig, leaf, seed, inflorescence, and canopy dimensions emphasize the need for integrated theories of evolution and function of these disparate traits.     

Factor analysis of the heart rate spectrum

The methodical problems of factor analysis of the heart rate spectrum have been considered: the multivariate normal assumption, factorability of the intercorrelation matrix, criteria for determining the number of factors, and the validity of the factor analysis model. Unnormalized and normalized variables, the matrices of Pearson’s and Spearman’s correlation coefficients were used. In the process of factor analysis (principal components method, Varimax Rotation), the restrictions and the possibility of different statistical criteria and procedures were explored. The meaning of the selected factors and the possibility of using the intercorrelation matrix of Spearman coefficients for unnormalized variables were considered.     

Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests

BACKGROUND AND AIMS: When ecologically important plant traits are correlated they may be said to constitute an ecological 'strategy' dimension. Through identifying these dimensions and understanding their inter-relationships we gain insight into why particular trait combinations are favoured over others and into the implications of trait differences among species. Here we investigated relationships among several traits, and thus the strategy dimensions they represented, across 2134 woody species from seven Neotropical forests. METHODS: Six traits were studied: specific leaf area (SLA), the average size of leaves, seed and fruit, typical maximum plant height, and wood density (WD). Trait relationships were quantified across species at each individual forest as well as across the dataset as a whole. 'Phylogenetic' analyses were used to test for correlations among evolutionary trait-divergences and to ascertain whether interspecific relationships were biased by strong taxonomic patterning in the traits. KEY RESULTS: The interspecific and phylogenetic analyses yielded congruent results. Seed and fruit size were expected, and confirmed, to be tightly related. As expected, plant height was correlated with each of seed and fruit size, albeit weakly. Weak support was found for an expected positive relationship between leaf and fruit size. The prediction that SLA and WD would be negatively correlated was not supported. Otherwise the traits were predicted to be largely unrelated, being representatives of putatively independent strategy dimensions. This was indeed the case, although WD was consistently, negatively related to leaf size. CONCLUSIONS: The dimensions represented by SLA, seed/fruit size and leaf size were essentially independent and thus conveyed largely independent information about plant strategies. To a lesser extent the same was true for plant height and WD. Our tentative explanation for negative WD-leaf size relationships, now also known from other habitats, is that the traits are indirectly linked via plant hydraulics.     

Exploring pleiotropy using principal components

A standard multivariate principal components (PCs) method was utilized to identify clusters of variables that may be controlled by a common gene or genes (pleiotropy). Heritability estimates were obtained and linkage analyses performed on six individual traits (total cholesterol (Chol), high and low density lipoproteins, triglycerides (TG), body mass index (BMI), and systolic blood pressure (SBP)) and on each PC to compare our ability to identify major gene effects. Using the simulated data from Genetic Analysis Workshop 13 (Cohort 1 and 2 data for year 11), the quantitative traits were first adjusted for age, sex, and smoking (cigarettes per day). Adjusted variables were standardized and PCs calculated followed by orthogonal transformation (varimax rotation). Rotated PCs were then subjected to heritability and quantitative multipoint linkage analysis. The first three PCs explained 73% of the total phenotypic variance. Heritability estimates were above 0.60 for all three PCs. We performed linkage analyses on the PCs as well as the individual traits. The majority of pleiotropic and trait-specific genes were not identified. Standard PCs analysis methods did not facilitate the identification of pleiotropic genes affecting the six traits examined in the simulated data set. In addition, genes contributing 20% of the variance in traits with over 0.60 heritability estimates could not be identified in this simulated data set using traditional quantitative trait linkage analyses. Lack of identification of pleiotropic and trait-specific genes in some cases may reflect their low contribution to the traits/PCs examined or more importantly, characteristics of the sample group analyzed, and not simply a failure of the PC approach itself.     

Ethnographic Studies of Childhood: A Historical Overview

In this article, I briefly survey the ethnographic research literature on childhood in the 20th century, beginning with the social and intellectual contexts for discussions of childhood at the turn of the 20th century. The observations of Bronislaw Malinowski and Margaret Mead in the 1920s were followed by later ethnographers, also describing childhood, some of whom criticized developmental theories; still others were influenced initially by Freudian and other psychoanalytic theories and later by the suggestions of Edward Sapir for research on the child's acquisition of culture. The Six Cultures Study led by John Whiting at midcentury was followed by diverse trends of the period after 1960—including field studies of infancy, the social and cultural ecology of children's activities, and language socialization. Ethnographic evidence on hunting and gathering and agricultural peoples was interpreted in evolutionary as well as cultural and psychological terms. The relationship between ethnography and developmental psychology remained problematic.     

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.     

Holistic anthropological research of Hvar Islanders, Croatia--from parish registries to DNA studies in 33 years

The complexity of interactions between hereditary, environmental and cultural factors in determining human phenotypes is often underestimated in biomedical research. In this paper, we present 33 years of holistic anthropological research that was being conducted since 1971 in the island of Hvar, Croatia. During this period, detailed characterization of migrations, demography, isonymy, linguistic differences, anthropometric traits (head and body dimensions), physiological (cardio-respiratory) properties, quantitative and qualitative dermatoglyphic traits, radiogrammetric metacarpal bone dimensions and genetic traits (classical antigens, HLA diversity, DNA short tandem repeat -STR, mitochondrial DNA and Y-chromosome polymorphisms) was performed. The analysis of this large collection of data using both model-bound and model-free approaches showed that the complexity underlying human biological traits may be considerably greater than generally assumed, which has important implications for design of future studies into genetic determinants of complex traits.     

The effects of environmental heterogeneity on multivariate selection on reproductive traits in female great tits

Describing natural selection on phenotypic traits under varying environmental conditions is essential for a quantitative assessment of the scale at which adaptation might occur and of the impact of environmental variability on evolution. Here we analyzed patterns of multivariate selection via fecundity and viability on three reproductive traits (laying date, clutch size, and egg weight) in a population of great tits (Parus major). We quantified selection under different environmental conditions using (1) local variation in breeding density and (2) distinct areas of the population's habitat. We found that selection gradients were generally stronger for fecundity than for viability selection. We also found correlational selection acting on the combination of laying date and clutch size; this is the first documented evidence of such selection acting on these two traits in a passerine bird. Our analyses showed that both local breeding density and habitat significantly influenced selection patterns, hence favoring different patterns of reproductive investment at a small-scale relative to typical dispersal distances in this species. Canonical rotation of the nonlinear selection matrices yielded similar conclusions as traditional nonlinear selection analyses, and also showed that the main axes of selection and fitness surfaces varied over space within the population. Our results emphasize the importance of quantifying different forms of selection, and of including variation in environmental conditions at small scales to gain a better understanding of potential evolutionary dynamics in wild populations. This study suggests that the fitness landscape for this species is relatively rugged at scales relevant to the life histories of individual birds and their close relatives.     

Determining the effective dimensionality of the genetic variance-covariance matrix

Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by Amemiya (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery.     

Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.     

A twin study of dental dimension. II. Independent genetic determinants

To demonstrate the presence of independent genetic determinants of multiple correlated tooth dimensions from twin data, a multivariate analysis was performed on the covariance matrices of monozygotic and dizygotic within-pair differences for mesiodistal and buccolingual dimensions of 28 teeth of the secondary dentition. The results provided strong evidences that the correlation among tooth dimensions is primarily genetic in origin, probably attributable to the pleiotropic action of either independent genes or groups of genes. Among the genetic factors that were identified, one appeared to affect the maxillary teeth in general while a second influenced primarily the anterior mandibular teeth. There was a striking tendency for homologous measurements on the right and left sides to be associated with the same genetic factor. In contrast, genetic determination of the maxillary and mandibular dentition seemed to be independent of each other, and a wider range of genetic factors were found to influence the mandibular than the maxillary teeth, suggesting that a differential degree of evolutionary stability may have been achieved in the teeth of the two jaws.     

Genetic diversity of Capsicum chinensis (Solanaceae) accessions based on molecular markers and morphological and agronomic traits

We estimated the genetic diversity of 49 accessions of the hot pepper species Capsicum chinensis through analyses of 12 physicochemical traits of the fruit, eight multi-categorical variables, and with 32 RAPD primers. Data from the physicochemical traits were submitted to analysis of variance to estimate the genetic parameters, and their means were clustered by the Scott-Knott test. The matrices from the individual and combined distance were estimated by multivariate analyses before applying Tocher's optimization method. All physicochemical traits were examined for genetic variability by analysis of variance. The responses of these traits showed more contribution from genetic than from environmental factors, except the percentage of dry biomass, content of soluble solids and vitamin C level. Total capsaicin had the greatest genetic divergence. Nine clusters were formed from the quantitative data based on the generalized distance of Mahalanobis, using Tocher's method; four were formed from the multi-categorical data using the Cole-Rodgers coefficient, and eight were formed from the molecular data using the Nei and Li coefficient. The accessions were distributed into 14 groups using Tocher's method, and no significant correlation between pungency and origin was detected. Uni- and multivariate analyses permitted the identification of marked genetic diversity and fruit attributes capable of being improved through breeding programs.     

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.