Reduced genetic diversity, increased isolation and multiple introductions of invasive giant hogweed in the western Swiss Alps.

Abstract The giant hogweed (Heracleum mantegazzianum) has successfully invaded 19 European countries as well as parts of North America. It has become a problematic species due to its ability to displace native flora and to cause public health hazards. Applying population genetics to species invasion can help reconstruct invasion history and may promote more efficient management practice. We thus analysed levels of genetic variation and population genetic structure of H. mantegazzianum in an invaded area of the western Swiss Alps as well as in its native range (the Caucasus), using eight nuclear microsatellite loci together with plastid DNA markers and sequences. On both nuclear and plastid genomes, native populations exhibited significantly higher levels of genetic diversity compared to invasive populations, confirming an important founder event during the invasion process. Invasive populations were also significantly more differentiated than native populations. Bayesian clustering analysis identified five clusters in the native range that corresponded to geographically and ecologically separated groups. In the invaded range, 10 clusters occurred. Unlike native populations, invasive clusters were characterized by a mosaic pattern in the landscape, possibly caused by anthropogenic dispersal of the species via roads and direct collection for ornamental purposes. Lastly, our analyses revealed four main divergent groups in the western Swiss Alps, likely as a consequence of multiple independent establishments of H. mantegazzianum.

Phytogeographical origin of Madeiran common beans based on phaseolin patterns

The objective of this work was to determine the geographic origin of the Madeiran common bean (Phaseolus vulgaris) gene pool. Phaseolin patterns of 50 accessions representing the diversity of common bean collected in Madeira, Portugal, and conserved in the ISOPlexis Germplasm Bank, were analysed using the Experion automated electrophoresis system, based on lab-on-a-chip technology. Five common bean standard varieties with typical phaseolin patterns were used to determine the phytogeographical origin of the Madeiran common bean accessions. Ninety two percent of the accessions exhibited a phaseolin pattern consistent with the one of common bean types belonging to the Andean gene pool, while the origin of the remaining 8% of the accessions was indistinguishable. The application of a similarity coefficient of 85%, based on Pearson correlations, increases the number of accessions with uncertain pattern. The analytical approach used permitted the determination of the origin of the common bean gene pool, which is Andean in 98% of the cases, and clustering of the observed variability among the Madeiran common beans.

Efficiency of informational transfer in regular and complex networks

We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.

Models of social networks based on social distance attachment

We propose a class of models of social network formation based on a mathematical abstraction of the concept of social distance. Social distance attachment is represented by the tendency of peers to establish acquaintances via a decreasing function of the relative distance in a representative social space. We derive analytical results (corroborated by extensive numerical simulations), showing that the model reproduces the main statistical characteristics of real social networks: large clustering coefficient, positive degree correlations, and the emergence of a hierarchy of communities. The model is confronted with the social network formed by people that shares confidential information using the Pretty Good Privacy (PGP) encryption algorithm, the so-called web of trust of PGP.

Gene expression profiling reveals consistent differences between clinical samples of human leukaemias and their model cell lines.

Microarray gene expression profiles of fresh clinical samples of chronic myeloid leukaemia in chronic phase, acute promyelocytic leukaemia and acute monocytic leukaemia were compared with profiles from cell lines representing the corresponding types of leukaemia (K562, NB4, HL60). In a hierarchical clustering analysis, all clinical samples clustered separately from the cell lines, regardless of leukaemic subtype. Gene ontology analysis showed that cell lines chiefly overexpressed genes related to macromolecular metabolism, whereas in clinical samples genes related to the immune response were abundantly expressed. These findings must be taken into consideration when conclusions from cell line-based studies are extrapolated to patients.

Genetic diversity of cultivated accessions and wild species of rubber tree using EST‑SSR markers

The objective of this work was to evaluate the efficiency of EST‑SSR markers in the assessment of the genetic diversity of rubber tree genotypes (Hevea brasiliensis) and to verify the transferability of these markers for wild species of Hevea. Forty‑five rubber tree accessions from the Instituto Agronômico (Campinas, SP, Brazil) and six wild species were used. Information provided by modified Roger's genetic distance were used to analyze EST‑SSR data. UPGMA clustering divided the samples into two major groups with high genetic differentiation, while the software Structure distributed the 51 clones into eight groups. A parallel could be established between both clustering analyses. The 30 polymorphic EST‑SSRs showed from two to ten alleles and were efficient in amplifying the six wild species. Functional EST‑SSR microsatellites are efficient in evaluating the genetic diversity among rubber tree clones and can be used to translate the genetic differences among cultivars and to fingerprint closely related materials. The accessions from the Instituto Agronômico show high genetic diversity. The EST‑SSR markers, developed from Hevea brasiliensis, show transferability and are able to amplify other species of Hevea.

Genetic diversity between improved banana diploids using canonical variables and the Ward-MLM method

The objective of this work was to estimate the genetic diversity of improved banana diploids using data from quantitative analysis and from simple sequence repeats (SSR) marker, simultaneously. The experiment was carried out with 33 diploids, in an augmented block design with 30 regular treatments and three common ones. Eighteen agronomic characteristics and 20 SSR primers were used. The agronomic characteristics and the SSR were analyzed simultaneously by the Ward-MLM, cluster, and IML procedures. The Ward clustering method considered the combined matrix obtained by the Gower algorithm. The Ward-MLM procedure identified three ideal groups (G1, G2, and G3) based on pseudo-F and pseudo-t² statistics. The dendrogram showed relative similarity between the G1 genotypes, justified by genealogy. In G2, 'Calcutta 4' appears in 62% of the genealogies. Similar behavior was observed in G3, in which the 028003-01 diploid is the male parent of the 086079-10 and 042079-06 genotypes. The method with canonical variables had greater discriminatory power than Ward-MLM. Although reduced, the genetic variability available is sufficient to be used in the development of new hybrids.

Open Educational Resources: an opportunity for virtual learning institutions

The Universitat Oberta de Catalunya (UOC, Open University of Catalonia) is involved inseveral research projects and educational activities related to the use of Open Educational Resources (OER). Some of the discussed issues in the concept of OER are research issues which are being tackled in two EC projects (OLCOS and SELF). Besides the research part, the UOC aims at developing a virtual centre for analysing and promoting the concept of OERin Europe in the sector of Higher and Further Education. The objectives are to makeinformation and learning services available to provide university management staff,eLearning support centres, faculty and learners with practical information required to create, share and re-use such interoperable digital content, tools and licensing schemes. In the realisation of these objectives, the main activities are the following: to provide organisationaland individual e-learning end-users with orientation; to develop perspectives and useful recommendations in the form of a medium-term Roadmap 2010 for OER in Higher and Further Education in Europe; to offer practical information and support services about how to create, share and re-use open educational content by means of tutorials, guidelines, best practices, and specimen of exemplary open e-learning content; to establish a larger group ofcommitted experts throughout Europe and other continents who not only share theirexpertise but also steer networking, workshops, and clustering efforts; and to foster and support a community of practice in open e-learning content know-how and experiences.

A cophenetic correlation coefficient for Tocher's method

The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

In conspectu prope totius urbis: an application of different visual methods at the ager Tarraconensis landscape

We present in this paper the results of the application of several visual methods on a group of locations, dated between VI and I centuries BC, of the ager Tarraconensis (Tarragona, Spain) a Hinterland of the roman colony of Tarraco. The difficulty in interpreting the diverse results in a combined way has been resolved by means of the use of statistical methods, such as Principal Components Analysis (PCA) and K-means clustering analysis. These methods have allowed us to carry out site classifications in function of the landscape's visual structure that contains them and of the visual relationships that could be given among them.

Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis.

The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease as well as common cellular and molecular pathways. Disease-specific signatures were leveraged to build a multi-disease classifier, which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of IFN-regulated gene programs with the skin database revealed a significant inverse correlation between IFN-β and IFN-γ programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. In addition, these studies provide a framework for developing tools for personalized medicine toward the precise prediction, prevention, and treatment of disease on an individual level.

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The quality of environmental data analysis and propagation of errors are heavily affected by the representativity of the initial sampling design [CRE 93, DEU 97, KAN 04a, LEN 06, MUL07]. Geostatistical methods such as kriging are related to field samples, whose spatial distribution is crucial for the correct detection of the phenomena. Literature about the design of environmental monitoring networks (MN) is widespread and several interesting books have recently been published [GRU 06, LEN 06, MUL 07] in order to clarify the basic principles of spatial sampling design (monitoring networks optimization) based on Support Vector Machines was proposed. Nonetheless, modelers often receive real data coming from environmental monitoring networks that suffer from problems of non-homogenity (clustering). Clustering can be related to the preferential sampling or to the impossibility of reaching certain regions.

eggNOG v4.0: nested orthology inference across 3686 organisms

With the increasing availability of various 'omics data, high-quality orthology assignment is crucial for evolutionary and functional genomics studies. We here present the fourth version of the eggNOG database (available at http://eggnog.embl.de) that derives nonsupervised orthologous groups (NOGs) from complete genomes, and then applies a comprehensive characterization and analysis pipeline to the resulting gene families. Compared with the previous version, we have more than tripled the underlying species set to cover 3686 organisms, keeping track with genome project completions while prioritizing the inclusion of high-quality genomes to minimize error propagation from incomplete proteome sets. Major technological advances include (i) a robust and scalable procedure for the identification and inclusion of high-quality genomes, (ii) provision of orthologous groups for 107 different taxonomic levels compared with 41 in eggNOGv3, (iii) identification and annotation of particularly closely related orthologous groups, facilitating analysis of related gene families, (iv) improvements of the clustering and functional annotation approach, (v) adoption of a revised tree building procedure based on the multiple alignments generated during the process and (vi) implementation of quality control procedures throughout the entire pipeline. As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood trees, as well as broad functional annotation. Users can access the complete database of orthologous groups via a web interface, as well as through bulk download.

Genetic associations in the detection of QTLs for wheat spike-related traits

The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.

Insights into the biogeographical history of the Lower Guinea Forest Domain: evidence for the role of refugia in the intraspecific differentiation of Aucoumea klaineana.

Determining the biogeographical histories of rainforests is central to our understanding of the present distribution of tropical biodiversity. Ice age fragmentation of central African rainforests strongly influenced species distributions. Elevated areas characterized by higher species richness and endemism have been postulated to be Pleistocene forest refugia. However, it is often difficult to separate the effects of history and of present-day ecological conditions on diversity patterns at the interspecific level. Intraspecific genetic variation could yield new insights into history, because refugia hypotheses predict patterns not expected on the basis of contemporary environmental dynamics. Here, we test geographically explicit hypotheses of vicariance associated with the presence of putative refugia and provide clues about their location. We intensively sampled populations of Aucoumea klaineana, a forest tree sensitive to forest fragmentation, throughout its geographical range. Characterizing variation at 10 nuclear microsatellite loci, we were able to obtain phylogeographic data of unprecedented detail for this region. Using Bayesian clustering approaches, we demonstrated the presence of four differentiated genetic units. Their distribution matched that of forest refugia postulated from patterns of species richness and endemism. Our data also show differences in diversity dynamics at leading and trailing edges of the species' shifting distribution. Our results confirm predictions based on refugia hypotheses and cannot be explained on the basis of present-day ecological conditions.