Defining the role of common variation in the genomic and biological architecture of adult human height.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Le déterminisme linguistique en Russie actuelle

Résumé : Depuis la fin de la perestroïka s'est mis en place en Russie un discours identitaire qui, en linguistique, prend des formes extrêmes, reposant sur un strict déterminisme de la pensée par la langue. Les organismes de financement de la recherche scientifique soutiennent des projets qui étudient le rapport entre la grammaire russe et le « caractère national russe ». Des objets nouveaux apparaissent : « l'image linguistique russe du monde », « la personnalité linguistique », la « linguoculturologie ». Cet ensemble discursif construit dans l'imaginaire une identité collective rassurante, reposant sur l'idée que 1) tous les gens qui parlent la même langue pensent de la même façon; 2) les langues, donc les pensées collectives, sont imperméables entre elles, et donc intraduisibles. Cette tendance néo-humboldtienne dans la linguistique russe actuelle se déploie en toute méconnaissance de ses origines historiques : le Romantisme allemand dans son opposition à la philosophie des Lumières, le positivisme évolutionnisme d'Auguste Comte et la linguistique déterministe de l'Allemagne des années 1930.AbstractSince the end of perestroika, in linguistics in Russia, a new form of discourse has taken place, which stresses a very tight determinism of thought by language. The funding organizations of scientific research back up projects studying the relationship between Russiangrammar and the « Russian national character ». New objects of knowledge come to light : « the Russian linguistic image of the world », « linguistic personnality », « culturology ». This kind of discourse builds up an imaginary comforting collective identity, which relies on the principle that 1) all the people who speak the same language think the same way; 2) languages, hence collective kinds of thought, are hermetically closed to each other, and untranslatable. This neo-humboldtian trend in contemporary Russian linguistics has no knowledge of its historical origins : German Romanticism in its Anti-Enlightenment trend, evolutionnist positivism of Auguste Comte, and deterministic linguistics in Germany in the 1930s.

Modeling stochasticity and robustness in gene regulatory networks.

MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Prevalent role of TCR alpha-chain in the selection of the preimmune repertoire specific for a human tumor-associated self-antigen.

The specificity of recognition of pMHC complexes by T lymphocytes is determined by the V regions of the TCR alpha- and beta-chains. Recent experimental evidence has suggested that Ag-specific TCR repertoires may exhibit a more V alpha- than V beta-restricted usage. Whether V alpha usage is narrowed during immune responses to Ag or if, on the contrary, restricted V alpha usage is already defined at the early stages of TCR repertoire selection, however, has remained unexplored. Here, we analyzed V and CDR3 TCR regions of single circulating naive T cells specifically detected ex vivo and isolated with HLA-A2/melan-A peptide multimers. Similarly to what was previously observed for melan-A-specific Ag-experienced T cells, we found a relatively wide V beta usage, but a preferential V alpha 2.1 usage. Restricted V alpha 2.1 usage was also found among single CD8(+) A2/melan-A multimer(+) thymocytes, indicating that V alpha-restricted selection takes place in the thymus. V alpha 2.1 usage, however, was independent from functional avidity of Ag recognition. Thus, interaction of the pMHC complex with selected V alpha-chains contributes to set the broad Ag specificity, as underlined by preferential binding of A2/melan-A multimers to V alpha 2.1-bearing TCRs, whereas functional outcomes result from the sum of these with other interactions between pMHC complex and TCR.

Phylogenetic alpha and beta diversities of butterfly communities correlate with climate in the western Swiss Alps

The observation of non-random phylogenetic distribution of traits in communities provides evidence for niche-based community assembly. Environment may influence the phylogenetic structure of communities because traits determining how species respond to prevailing conditions can be phylogenetically conserved. In this study, we investigate the variation of butterfly species richness and of phylogenetic - and -diversities along temperature and plant species richness gradients. Our study indicates that butterfly richness is independently positively correlated to temperature and plant species richness in the study area. However, the variation of phylogenetic - and -diversities is only correlated to temperature. The significant phylogenetic clustering at high elevation suggests that cold temperature filters butterfly lineages, leading to communities mostly composed of closely related species adapted to those climatic conditions. These results suggest that in colder and more severe conditions at high elevations deterministic processes and not purely stochastic events drive the assemblage of butterfly communities.

Mapping the proteome of Leishmania Viannia parasites using two-dimensional polyacrylamide gel electrophoresis and associated technologies.

In this study we have demonstrated the potential of two-dimensional electrophoresis (2DE)-based technologies as tools for characterization of the Leishmania proteome (the expressed protein complement of the genome). Standardized neutral range (pH 5-7) proteome maps of Leishmania (Viannia) guyanensis and Leishmania (Viannia) panamensis promastigotes were reproducibly generated by 2DE of soluble parasite extracts, which were prepared using lysis buffer containing urea and nonidet P-40 detergent. The Coomassie blue and silver nitrate staining systems both yielded good resolution and representation of protein spots, enabling the detection of approximately 800 and 1,500 distinct proteins, respectively. Several reference protein spots common to the proteomes of all parasite species/strains studied were isolated and identified by peptide mass spectrometry (LC-ES-MS/MS), and bioinformatics approaches as members of the heat shock protein family, ribosomal protein S12, kinetoplast membrane protein 11 and a hypothetical Leishmania-specific 13 kDa protein of unknown function. Immunoblotting of Leishmania protein maps using a monoclonal antibody resulted in the specific detection of the 81.4 kDa and 77.5 kDa subunits of paraflagellar rod proteins 1 and 2, respectively. Moreover, differences in protein expression profiles between distinct parasite clones were reproducibly detected through comparative proteome analyses of paired maps using image analysis software. These data illustrate the resolving power of 2DE-based proteome analysis. The production and basic characterization of good quality Leishmania proteome maps provides an essential first step towards comparative protein expression studies aimed at identifying the molecular determinants of parasite drug resistance and virulence, as well as discovering new drug and vaccine targets.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

A genome-wide association search for type 2 diabetes genes in African Americans.

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

High level expression of human neuropeptide Y receptors in mammalian cells infected with a recombinant vaccinia virus.

Neuropeptide Y (NPY) is a 36 amino acid peptide present in the central and peripheral nervous system. Numerous studies point to a role of NPY in cardiovascular regulation. NPY effects are mediated through stimulation of specific cell surface G protein-coupled receptors. To allow biochemical studies of the receptor and of its interaction with the ligand, we have developed a potent expression system for NPY receptors using a recombinant vaccinia virus. A human NPY receptor cDNA was fused to a strong vaccinia virus promoter and inserted into the viral genome by homologous recombination. Recombinant viruses were isolated and tested for their ability to induce NPY binding site expression following infection of mammalian cell lines. Using saturation and competition binding experiments we measured a Bmax of 5-10 x 10(6) NPY binding sites per cell. The Kd for the binding of NPY is about 20 nM. Labelling of infected cells with a fluorochrome-labelled NPY indicated that the recombinant protein integrates into the cell membrane.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Genetic interplay between HLA-C and MIR148A in HIV control and Crohn disease.

Variation in the 3' untranslated region (3'UTR) of the HLA-C locus determines binding of the microRNA Hsa-miR-148a, resulting in lower cell surface expression of alleles that bind miR-148a relative to those alleles that escape its binding. The HLA-C 3'UTR variant was shown to associate with HIV control, but like the vast majority of disease associations in a region dense with causal candidates, a direct effect of HLA-C expression level on HIV control was not proven. We demonstrate that a MIR148A insertion/deletion polymorphism associates with its own expression levels, affecting the extent to which HLA-C is down-regulated, the level of HIV control, and the risk of Crohn disease only among those carrying an intact miR-148a binding site in the HLA-C 3'UTR. These data illustrate a direct effect of HLA-C expression level on HIV control that cannot be attributed to other HLA loci in linkage disequilibrium with HLA-C and highlight the rich complexity of genetic interactions in human disease.

Species distributions and interactions in a changing world : from understanding to forecasting

Les écosystèmes fournissent de nombreuses ressources et services écologiques qui sont utiles à la population humaine. La biodiversité est une composante essentielle des écosystèmes et maintient de nombreux services. Afin d'assurer la permanence des services écosystémiques, des mesures doivent être prises pour conserver la biodiversité. Dans ce but, l'acquisition d'informations détaillées sur la distribution de la biodiversité dans l'espace est essentielle. Les modèles de distribution d'espèces (SDMs) sont des modèles empiriques qui mettent en lien des observations de terrain (présences ou absences d'une espèce) avec des descripteurs de l'environnement, selon des courbes de réponses statistiques qui décrive la niche réalisée des espèces. Ces modèles fournissent des projections spatiales indiquant les lieux les plus favorables pour les espèces considérées. Le principal objectif de cette thèse est de fournir des projections plus réalistes de la distribution des espèces et des communautés en montagne pour le climat présent et futur en considérant non-seulement des variables abiotiques mais aussi biotiques. Les régions de montagne et l'écosystème alpin sont très sensibles aux changements globaux et en même temps assurent de nombreux services écosystémiques. Cette thèse est séparée en trois parties : (i) fournir une meilleure compréhension du rôle des interactions biotiques dans la distribution des espèces et l'assemblage des communautés en montagne (ouest des Alpes Suisses), (ii) permettre le développement d'une nouvelle approche pour modéliser la distribution spatiale de la biodiversité, (iii) fournir des projections plus réalistes de la distribution future des espèces ainsi que de la composition des communautés. En me focalisant sur les papillons, bourdons et plantes vasculaires, j'ai détecté des interactions biotiques importantes qui lient les espèces entre elles. J'ai également identifié la signature du filtre de l'environnement sur les communautés en haute altitude confirmant l'utilité des SDMs pour reproduire ce type de processus. A partir de ces études, j'ai contribué à l'amélioration méthodologique des SDMs dans le but de prédire les communautés en incluant les interactions biotiques et également les processus non-déterministes par une approche probabiliste. Cette approche permet de prédire non-seulement la distribution d'espèces individuelles, mais également celle de communautés dans leur entier en empilant les projections (S-SDMs). Finalement, j'ai utilisé cet outil pour prédire la distribution d'espèces et de communautés dans le passé et le futur. En particulier, j'ai modélisé la migration post-glaciaire de Trollius europaeus qui est à l'origine de la structure génétique intra-spécifique chez cette espèce et évalué les risques de perte face au changement climatique. Finalement, j'ai simulé la distribution des communautés de bourdons pour le 21e siècle afin d'évaluer les changements probables dans ce groupe important de pollinisateurs. La diversité fonctionnelle des bourdons va être altérée par la perte d'espèces spécialistes de haute altitude et ceci va influencer la pollinisation des plantes en haute altitude. - Ecosystems provide a multitude of resources and ecological services, which are useful to human. Biodiversity is an essential component of those ecosystems and guarantee many services. To assure the permanence of ecosystem services for future generation, measure should be applied to conserve biodiversity. For this purpose, the acquisition of detailed information on how biodiversity implicated in ecosystem function is distributed in space is essential. Species distribution models (SDMs) are empirical models relating field observations to environmental predictors based on statistically-derived response surfaces that fit the realized niche. These models result in spatial predictions indicating locations of the most suitable environment for the species and may potentially be applied to predict composition of communities and their functional properties. The main objective of this thesis was to provide more accurate projections of species and communities distribution under current and future climate in mountains by considering not solely abiotic but also biotic drivers of species distribution. Mountain areas and alpine ecosystems are considered as particularly sensitive to global changes and are also sources of essential ecosystem services. This thesis had three main goals: (i) a better ecological understanding of biotic interactions and how they shape the distribution of species and communities, (ii) the development of a novel approach to the spatial modeling of biodiversity, that can account for biotic interactions, and (iii) ecologically more realistic projections of future species distributions, of future composition and structure of communities. Focusing on butterfly and bumblebees in interaction with the vegetation, I detected important biotic interactions for species distribution and community composition of both plant and insects along environmental gradients. I identified the signature of environmental filtering processes at high elevation confirming the suitability of SDMs for reproducing patterns of filtering. Using those case-studies, I improved SDMs by incorporating biotic interaction and accounting for non-deterministic processes and uncertainty using a probabilistic based approach. I used improved modeling to forecast the distribution of species through the past and future climate changes. SDMs hindcasting allowed a better understanding of the spatial range dynamic of Trollius europaeus in Europe at the origin of the species intra-specific genetic diversity and identified the risk of loss of this genetic diversity caused by climate change. By simulating the future distribution of all bumblebee species in the western Swiss Alps under nine climate change scenarios for the 21st century, I found that the functional diversity of this pollinator guild will be largely affected by climate change through the loss of high elevation specialists. In turn, this will have important consequences on alpine plant pollination.

Identification concept and the use of probabilities in forensic odontology--an approach by philosophical discussion.

This paper questions the practitioners' deterministic approach(es) in forensic identification and notes the limits of their conclusions in order to encourage a discussion to question current practices. With this end in view, a hypothetical discussion between an expert in dentistry and an enthusiastic member of a jury, eager to understand the scientific principles of evidence interpretation, is presented. This discussion will lead us to regard any argument aiming at identification as probabilistic.