Taxonomic congruence in Eskimoid populations.

The study compares distance relationships in Eskimoid populations based on metric and attribute data with linguistic relationships based on structural and lexicostatistical data. Taxonomic congruence and the non-specificity hypothesis are investigated by matrix correlations and by a clustering procedure. The matrix correlation approaches employed are the Pearson product-moment correlation coefficient and the Spearman rank-order correlation coefficient. An unweighted pair-group clustering procedure provides a visual comparison of biological and linguistic relationships. Data consist of 74 craniometric measurements and 28 cranial observations taken on 12 Eskimoid populations. Mahalanobis' D2 and Balakrishnan and Sanghvi's B2 were used to compute the metric and attribute distances, respectively. The results indicate that a strict adherence to the non-specificity hypothesis is untenable. Also, there is better concordance between the sexes for metric distances than for attribute distances, and the metric data are more concordant with linguistic relationships than are the attribute data.     

Incomplete distance matrices,supertrees and bat phylogeny

In this paper, we evaluate the relative performance of competing approaches for estimating phylogenies from incomplete distance matrices. The direct approach proceeds with phylogenetic reconstruction while ignoring missing cells, whereas the indirect approach proceeds by estimating the missing distances prior to phylogenetic analysis. Two distinct indirect procedures based on the ultrametric inequality and the four-point condition are further compared. Using simulations, we show that more reliable results are obtained when such indirect methods are used. Expectedly, the phylogenies become less accurate as the percentage of missing cells increases, but combining different estimation methods greatly improves the accuracy. An application to bat phylogeny confirms the results obtained in the simulation study and illustrates the effect of missing distances in the construction of supertrees.     

Population‐specific deviations of global human craniometric variation from a neutral model

Past studies have revealed that much of human craniometric variation follows a neutral model of population relationships. At the same time, there is evidence for the influence of natural selection in having shaped some global diversity in craniometrics. In order to partition these effects, and to explore other potential population‐specific influences, this article analyzes residuals of craniometric distances from a geographically based neutral model of population structure. W.W. Howells' global craniometric data set was used for these analyses, consisting of 57 measurements for 22 populations around the world, excluding Polynesia and Micronesia because of the relatively recent settlement of these regions. Phenotypic and geographic distances were derived between all pairs of populations. Three‐dimensional multidimensional scaling configurations were obtained for both distance matrices, and compared using a Procrustes rotation method to show which populations do not fit the geographic model. This analysis revealed three major deviations: the Buriat, Greenland Inuit, and Peru. The deviations of the Buriat and Greenland Inuit appear to be related to long‐term adaptation to cold environments. The Peruvian sample is more similar to other New World populations than expected based on geographic distance alone. This deviation likely reflects the evolutionarily recent movement of human populations into South America, such that these populations are further from genetic equilibrium. This same pattern is seen in South American populations in a comparative analysis of classical genetic markers, but not in a comparative analysis of STR loci, perhaps reflecting the higher mutation rate for the latter. Am J Phys Anthropol, 2010. © 2009 Wiley‐Liss, Inc.     

Microevolutionary relationships between phylogeographical history,climate change and morphological variability in the common vole (Microtus arvalis) across France

Aim In this study, we analyse microevolutionary processes in common voles (Microtus arvalis) through the investigation of tooth morphological structure, in order to assess the relative impact of climate and phylogeographical history. Microevolutionary studies have shown that climate change may play a role in both population phylogeography and phenotypic differentiation. However, relatively little is known about the precise relationship between phylogeography and phenotypic variability and about how organisms respond to climate change. Location France, from sea level to the Alps (5 to > 2300 m a.s.l.). Methods This morphological analysis is based on first lower molar measurements from 16 geographically distinct common vole populations. Size and shape components are assessed separately. Population structure patterns are characterized using canonical variate analysis. We use phylogenetic analyses of two regions of mitochondrial DNA (the control region and the cytochrome b gene) to infer genetic structure. We calculate climate parameters from temperature and precipitation data. We investigate the influence of climate, geography and phylogeographical history on the phenotype using (1) multiple regression tests, (2) pairwise comparison of observation‐by‐variable matrices, and (3) a correlation method designed to compare three matrices. Results All populations were clearly structured, whatever the dataset. Neither size nor shape variation was correlated with climate parameters, but tooth shape was strongly correlated with both genetic structure and geographical distance. Main conclusions In French Microtus arvalis populations, molar shape differentiation is clearly associated with both phylogeographical history and geographical distance. Population phylogeographical history has a greater relevance than climate in accounting for variation in tooth morphology.     

StAMPP: an R package for calculation of genetic differentiation and structure of mixed‐ploidy level populations

Statistical Analysis of Mixed‐Ploidy Populations (StAMPP) is a freely available R package for calculation of population structure and differentiation based on single nucleotide polymorphism (SNP) genotype data from populations of any ploidy level, and/or mixed‐ploidy levels. StAMPP provides an advance on previous similar software packages, due to an ability to calculate pairwise F_ST values along with confidence intervals, Nei's genetic distance and genomic relationship matrixes from data sets of mixed‐ploidy level. The software code is designed to efficiently handle analysis of large genotypic data sets that are typically generated by high‐throughput genotyping platforms. Population differentiation studies using StAMPP are broadly applicable to studies of molecular ecology and conservation genetics, as well as animal and plant breeding.     

Effects of landscape and history on diversification of a montane, stream-breeding amphibian

Aim The aim of this study was to understand the roles of landscape features in shaping patterns of contemporary and historical genetic diversification among populations of the Andean tree frog (Hypsiboas andinus) across spatial scales. Location Andes mountains, north‐western Argentina, South America. Methods Mitochondrial DNA control region sequences were utilized to assess genetic differentiation among populations and calculate population pair‐wise genetic distances. Three models of movement, namely traditional straight‐line distance and two effective distances based on habitat classification, were examined to determine which of these explained the most variation in pair‐wise population genetic differentiation. The two habitat classifications were based on digital vegetation and hydrology layers that were generated from a 90‐m resolution digital elevation model (DEM) and known relationships between elevation and habitat. Mantel tests were conducted to test for correlations between geographic and genetic distance matrices and to estimate the percentage variation explained by each type of geographic distance. To investigate the location of possible barriers to gene flow, we used Monmonier’s maximum difference algorithm as implemented in barrier 2.2. Results At both geographic scales, effective distances explained more variation in genetic differentiation than did straight‐line distance. The least‐cost distances based on the simple classification performed better than the more detailed habitat classification. We controlled for the effects of historical range fragmentation determined from previous nested clade analyses, and therefore evaluated the effect of different distances on the genetic variation attributable to more recent factors. Effective distances identified populations that were highly divergent as a result of isolation in unsuitable habitats. The proposed locations of barriers to gene flow identified using Monmonier’s maximum difference algorithm corresponded well with earlier analyses and supported findings from our partial Mantel tests. Main conclusions Our results indicate that landscape features have been important in both historical and contemporary genetic structuring of populations of H. andinus at both large and small spatial scales. A landscape genetic perspective offers novel insights not provided by traditional phylogeographic studies: (1) effective distances can better explain patterns of differentiation in populations, especially in heterogeneous landscapes where barriers to dispersal may be common; and (2) least‐cost path analysis can help to identify corridors of movement between populations that are biologically more realistic.     

Demerelate: calculating interindividual relatedness for kinship analysis based on codominant diploid genetic markers using R

The Demerelate package offers algorithms to calculate different interindividual relatedness measurements. Three different allele sharing indices, five pairwise weighted estimates of relatedness and four pairwise weighted estimates with sample size correction are implemented to analyse kinship structures within populations. Statistics are based on randomization tests; modelling relatedness coefficients by logistic regression, modelling relatedness with geographic distance by mantel correlation and comparing mean relatedness between populations using pairwise t‐tests. Demerelate provides an advance on previous software packages by including some estimators not available in R to date, along with F_IS, as well as combining analysis of relatedness and spatial structuring. An UPGMA tree visualizes genetic relatedness among individuals. Additionally, Demerelate summarizes information on data sets (allele vs. genotype frequencies; heterozygosity; F_IS values). Demerelate is – to our knowledge – the first R package implementing basic allele sharing indices such as Blouin's M_xy relatedness, the estimator of Wang corrected for sample size (wang_xy), estimators based on Morans I adapted to genetic relatedness as well as combining all estimators with geographic information. The R environment enables users to better understand relatedness within populations due to the flexibility of Demerelate of accepting different data sets as empirical data, reference data, geographical data and by providing intermediate results. Each statistic and tool can be used separately, which helps to understand the suitability of the data for relatedness analysis, and can be easily implemented in custom pipelines.     

Positive correlation between vegetation dissimilarity and genetic differentiation of Carex sempervirens

Synthesizing genetic data at population level and vegetation data at community level may give insight into how ecological and evolutionary processes associated with different vegetation influence genetic diversity and differentiation of plant populations. We correlated population genetic patterns of Carex sempervirens with community vegetation patterns in abandoned subalpine grassland in the Swiss Alps. Within-population genetic diversity (percentage of polymorphic bands and Nei's gene diversity) of C. sempervirens was not significantly correlated with plant richness, evenness or Shannon's diversity index (Pearson correlation coefficient |r|<0.32, P>0.10). However, the genetic distance (F_ST) between C. sempervirens populations was significantly positively correlated with the vegetation dissimilarity between communities (Mantel's r=0.23, P<0.01). The correlation between the population genetic differentiation and the vegetation dissimilarity was not due to the parallel effects of geographic isolation or site conditions, because F_ST was not correlated with the geographic distance or the pairwise differences in any of the measured site condition parameters. One likely mechanism is that different plant communities were associated with different selective forces, which, in turn, influenced the genetic differentiation between C. sempervirens populations. Another possibility is that the vegetation heterogeneity (dissimilarity) generated ecological barriers against gene flow and thus enhanced the genetic differentiation between C. sempervirens populations.     

Craniometric Data Supports Demic Diffusion Model for the Spread of Agriculture into Europe

Background

The spread of agriculture into Europe and the ancestry of the first European farmers have been subjects of debate and controversy among geneticists, archaeologists, linguists and anthropologists. Debates have centred on the extent to which the transition was associated with the active migration of people as opposed to the diffusion of cultural practices. Recent studies have shown that patterns of human cranial shape variation can be employed as a reliable proxy for the neutral genetic relationships of human populations.

Methodology/Principal Findings

Here, we employ measurements of Mesolithic (hunter-gatherers) and Neolithic (farmers) crania from Southwest Asia and Europe to test several alternative population dispersal and hunter-farmer gene-flow models. We base our alternative hypothetical models on a null evolutionary model of isolation-by-geographic and temporal distance. Partial Mantel tests were used to assess the congruence between craniometric distance and each of the geographic model matrices, while controlling for temporal distance. Our results demonstrate that the craniometric data fit a model of continuous dispersal of people (and their genes) from Southwest Asia to Europe significantly better than a null model of cultural diffusion.

Conclusions/Significance

Therefore, this study does not support the assertion that farming in Europe solely involved the adoption of technologies and ideas from Southwest Asia by indigenous Mesolithic hunter-gatherers. Moreover, the results highlight the utility of craniometric data for assessing patterns of past population dispersal and gene flow.     

Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices

Background  

Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes.     

Patterns of sexual dimorphism in the Persian Leopard (Panthera pardus saxicolor) and implications for sex differentiation

Extant felids show a high degree of inter-sexual dimorphism, meaning significant size differences between males and females. Such a differentiation may have various ecological, behavioural and evolutionary implications, at both species and subspecies levels. We have investigated the sexual size differences in one of the most dimorphic felids, i.e. the Leopard (Panthera pardus), based on 63 craniometric and 55 morphometric samples from Iran which belong to the subspecies Persian Leopard (P. p. saxicolor). In order to explore patterns of sexual dimorphism, multivariate statistical analysis on 24 skull variables as well as univariate approaches for two body measurements were applied. We found significant inter-sexual differences in skull size whereas it was not meaningful after removing the effect of size to address skull shape. Moreover, inter-sexual differentiation was also remarkable when comparing morphometric body measurements in adults, showing that the males possess a larger head mass and longer body, but sub-adults did not show any remarkable differentiation between sexes. A combination of craniometric and morphological features is proposed for sex differentiation in Leopards.     

High gene flow between populations of Macrotermes michaelseni (Isoptera, Termitidae)

Termite alates are thought to be poor active flyers, and this should lead to considerable genetic differentiation on small spatial scales. However, using four microsatellite loci for the termite Macrotermes michaelseni we found low values of genetic differentiation (F_ST) across a spatial scale of even more than 50 km. Genetic differentiation between populations increased with spatial distance up to 50 km. Furthermore, up to this distance, the scatter around the linear regression of genetic differentiation versus spatial distance increased with spatial distance. This suggests that across such spatial distances gene flow and genetic drift are of about equal importance, and near equilibrium. Using a regional F_ST as well as the distance between populations with non-significant F_ST-values (up to 25 km), gene flow is sufficiently high so that populations may be regarded as panmictic on spatial scales of 25 to 50 km. The apparent contradiction between dispersal distances observed in the field and estimates of gene flow from genetic markers may be due to the masses of swarming alates. Assuming a leptokurtic distribution of dispersal distances, atleast some alates are expected to travel considerable distances, most likely by passive drift. Received 25 January 2005; revised 11 April 2005; accepted 26 April 2005.     

Contrasting patterns of spatial genetic structure of diploid and triploid populations of the clonal aquatic species,<Emphasis Type="Italic">Butomus umbellatus (Butomaceae)</Emphasis>, in Central Europe

Genetic diversity in a sample of an aquatic plantButomus umbellatus from 37 localities in Czechia and Slovakia was studied by analyzing six polymorphic loci in three enzymatic systems (SKDH, PGD and AAT). Diversity among ramets was low in eight populations with relatively extensive sampling (only one population possessed more than one multilocus genotype), suggesting high clonality of reproduction in these populations. However, among-population diversity was high: G = 0.782 and 0.881 for the samples of diploid and triploid populations, respectively. Heterozygosity of individual plants averaged over variable loci was also high: H = 0.554 for diploids and 0.453 for triploids. Genetic differentiation among populations was additionally studied using cluster analysis. Several populations of diploids clustered separately from all other populations, whereas another group of diploid populations clustered with some triploid populations, indicating the possibility of relatively recent, probably multiple origin of these triploid populations from their diploid progenitors. Association between matrices of Nei’s genetic distances among populations from different localities and matrices of geographic distances among these localities revealed highly significant correlation for the sample of diploid populations (r = 0.60,P < 0.001) but no significant correlation for the sample of triploid populations (r = 0.02,P = 0.593). These results indicate a spatial structure of diploid populations in accordance with the isolation by distance model, and a random distribution of genotypes among triploid populations ofB. umbellatus.     

Effect of mating structure on variation in inbreeding

An analysis is made of the variation among individuals in finite populations of the proportion of their genes which are identical by descent. There are two causes of this variability: variation in pedigree among individuals, and linkage which causes whole blocks of genes to be identical or nonidentical by descent. The variation between and within populations is analyzed in detail for several mating systems: monoecious populations with and without random selfing, and dioecious populations with and without a hierarchical mating structure. Transition matrices for two-locus descent measures are given for each system. Total variability is obtained by integrating these measures over the distribution of map distances over whole chromosomes. Approximate methods are also developed for unlinked loci. Unless populations have a very small effective size (N_e) there is little variation in inbreeding between populations. For unlinked loci, the coefficient of variation in nonidentity within populations approaches about 1/√3N_e for random selfing, 1/√6N_e for monogamous matings and 1/√12N_e for monoecy with selfing excluded or dioecy with random pairing. If there is no association between map distance and initial heterozygosity or effect on quantitative traits, the coefficient of variation in mean heterozygosity over the genome is related to that in nonidentity, and the additional variation in a quantitative trait due to dominant genes equals the product of the square of the initial inbreeding depression and the squared coefficient of variation of nonidentity.     

Geographical patterns of turnover and nestedness-resultant components of allelic diversity among populations

The analysis of geographical patterns in population divergence has always been a powerful way to infer microevolutionary processes involved in population differentiation, and several approaches have been used to investigate such patterns. Most frequently, multivariate spatial patterns of population differentiation are analyzed by computing pairwise genetic distances or F_ST (or related statistics, such as ?_ST from AMOVA), which are then correlated with geographical distances or landscape features. However, when calculating distances, especially based on presence-absence of alleles in local populations, there would be a confounding effect of allelic richness differences in the population differentiation. Moreover, the relative magnitude of these components and their spatial patterns can help identifying microevolutionary processes driving population differentiation. Here we show how recent methodological advances in ecological community analyses that allows partitioning dissimilarity into turnover (turnover) and richness differences, or nestedness-resultant dissimilarity, can be applied to allelic variation data, using an endemic Cerrado tree (Dipteryx alata) as a case study. Individuals from 15 local populations were genotyped for eight microsatellite loci, and pairwise dissimilarities were computed based on presence-absence of alleles. The turnover of alleles among populations represented 69?% of variation in dissimilarity, but only the richness difference component shows a clear spatial structure, appearing as a westward decrease of allelic richness. We show that decoupling richness difference and turnover components of allelic variation reveals more clearly how similarity among populations reflects geographical patterns in allelic diversity that can be interpreted in respect to historical range expansion in the species.     

Consistency of population genetics parameters estimated from isozyme and RAPDs dataset in species of genus <Emphasis Type="Italic">Prosopis</Emphasis> (Leguminosae,Mimosoideae)

Genetic variability, population structure and differentiation among 17 populations of 5 species and 2 natural interspecific hybrids of section Algarobia of genus Prosopis were analyzed from data of 23 isozyme and 28 RAPD loci. Both markers indicated that the studied populations are highly variable. P. alba populations in average showed lower values of genetic variability estimates from isozyme data, but this trend was not observed for RAPD markers. The hierarchical analyses of the distribution of genetic variability showed that the highest proportion of variation occurred within populations, the differentiation among species was intermediate and the lowest component was observed among populations within species. The consistency between results from both dataset implies that they are not biased and reflect the actual genetic structure of the populations analyzed. The matrices of Euclidean distances obtained from the two sets of markers were highly correlated according to Mantel test. In both cases the corresponding phenogram and MDS plot tended to cluster conspecific populations while hybrid populations were not intermediate between putative parents. Some disagreements between isozyme and RAPD phenograms were observed mainly in the affinities of hybrid populations. Such inconsistencies might result from reticular rather than dichotomic evolutionary relationships. The phenetic associations retrieved gave no support to the division of the section Algarobia into series.     

Genome‐wide differentiation in closely related populations: the roles of selection and geographic isolation

Population divergence in geographic isolation is due to a combination of factors. Natural and sexual selection may be important in shaping patterns of population differentiation, a pattern referred to as ‘isolation by adaptation’ (IBA). IBA can be complementary to the well‐known pattern of ‘isolation by distance’ (IBD), in which the divergence of closely related populations (via any evolutionary process) is associated with geographic isolation. The barn swallow Hirundo rustica complex comprises six closely related subspecies, where divergent sexual selection is associated with phenotypic differentiation among allopatric populations. To investigate the relative contributions of selection and geographic distance to genome‐wide differentiation, we compared genotypic and phenotypic variation from 350 barn swallows sampled across eight populations (28 pairwise comparisons) from four different subspecies. We report a draft whole‐genome sequence for H. rustica, to which we aligned a set of 9493 single nucleotide polymorphisms (SNPs). Using statistical approaches to control for spatial autocorrelation of phenotypic variables and geographic distance, we find that divergence in traits related to migratory behaviour and sexual signalling, as well as geographic distance, together explain over 70% of genome‐wide divergence among populations. Controlling for IBD, we find 42% of genomewide divergence is attributable to IBA through pairwise differences in traits related to migratory behaviour and sexual signalling alone. By (i) combining these results with prior studies of how selection shapes morphological differentiation and (ii) accounting for spatial autocorrelation, we infer that morphological adaptation plays a large role in shaping population‐level differentiation in this group of closely related populations.     

A generalized multivariate approach to pattern discovery from replicated and incomplete genome-wide measurements

Estimation of pairwise correlation from incomplete and replicated molecular profiling data is an ubiquitous problem in pattern discovery analysis, such as clustering and networking. However, existing methods solve this problem by ad hoc data imputation, followed by aveGation coefficient type approaches, which might annihilate important patterns present in the molecular profiling data. Moreover, these approaches do not consider and exploit the underlying experimental design information that specifies the replication mechanisms. We develop an Expectation-Maximization (EM) type algorithm to estimate the correlation structure using incomplete and replicated molecular profiling data with a priori known replication mechanism. The approach is sufficiently generalized to be applicable to any known replication mechanism. In case of unknown replication mechanism, it is reduced to the parsimonious model introduced previously. The efficacy of our approach was first evaluated by comprehensively comparing various bivariate and multivariate imputation approaches using simulation studies. Results from real-world data analysis further confirmed the superior performance of the proposed approach to the commonly used approaches, where we assessed the robustness of the method using data sets with up to 30 percent missing values.     

Distances as Degrees of Freedom

Abstract

Tertiary contact distance information of varying resolution for large biological molecules abounds in the literature. The results provided herein develop a framework by which information of this type can be used to reduce the allowable configuration space of a macromolecule. The approach combines graph theory and distance geometry. Large molecules are represented as simple, undirected graphs, with atoms, or groups, as vertices, and distances between them as edges. It is shown that determination of the exact structure of a molecule in three dimensions only requires the specification of all the distances in a single tetrahedron, and four distances to every other atom. This is 4N-10 distances which is a subset of the total N(N-l)/2 unique distances in a molecule consisting of N atoms. This requirement for only 4N-10 distances has serious implications for distance geometry implementations in which all N(N-l)/2 distances are specified by bounded random numbers. Such distance matrices represent overspecified systems which when solved lead to non-obvious distribution of any error caused by inherent contradictions in the input data. It is also shown that numerous valid subsets of 4N-10 distances can be constructed. It is thus possible to tailor a subset of distances using all known distances as degrees of freedom, and thereby reduce the configuration space of the molecule. Simple algebraic relationships are derived that relate sets of distances, and complicated rotations are avoided. These relationships are used to construct minimum, complete sets of distances necessary to specify the exact structure of the entire molecule in three dimensions from incomplete distance information, and to identify sets of inconsistent distances. The method is illustrated for the flexible structural types present in large ribosomal RNAs: 1.) A five-membered ring; 2.) a chemically bonded chain with its ends in contact (i.e., a hairpin loop); 3.) the spatial orientation of two separate molecules, and; 4.) an RNA helix that can have variation in individual base pairs, giving rise to global deviation from standardized helical forms.     

Quantitative trait, genetic, environmental, and geographical distances among populations of the C4 grass Trachypogon plumosus in Neotropical savannas

Venezuelan savannas are exposed to land‐use changes and biological invasions which compromise their persistence and function. The native C₄ grass Trachypogon plumosus is the most important component of the savannas under diverse combinations of climate and soils, suggesting substantial interpopulation variation. We examined quantitative traits and isozyme variation of nine populations of this grass and related these estimates to geographical and environmental features of sampled locations. Isozyme diversity estimates were based on 10 polymorphic enzyme systems whereas 21 quantitative traits, from field and controlled growth conditions, were evaluated. Distance matrices for quantitative traits, isozyme, geographical and environmental data were subjected to clustering analysis. Correspondence between quantitative trait distance and genetic distance, and their association to geographical and environmental distances were analysed with Mantel tests. All quantitative traits differed significantly among populations. The average Q_ST calculated for eight quantitative traits measured in the greenhouse was 0.157. Isozyme diversity differed significantly among populations. About 28% of total isozyme variation occurred among populations. Significant positive associations were detected between environmental, quantitative field traits, and geographical distance as well as between the later and genetic distances. Genetic distances did not correspond significantly with quantitative traits nor did environmental distances. Ecologically meaningful associations were detected between field quantitative traits, environmental, and geographical data using cluster analysis. Our results support the hypothesis that processes of the neutral type are mainly responsible for the variation patterns observed in T. plumosus populations in Venezuelan savannas. Variation observed for quantitative traits among populations seems to be due to the effect of environmental conditions on phenotypically plastic traits, and not the result of directional selection favouring different phenotypes in different populations.