euHCVdb: the European hepatitis C virus database

The hepatitis C virus (HCV) genome shows remarkable sequence variability, leading to the classification of at least six major genotypes, numerous subtypes and a myriad of quasispecies within a given host. A database allowing researchers to investigate the genetic and structural variability of all available HCV sequences is an essential tool for studies on the molecular virology and pathogenesis of hepatitis C as well as drug design and vaccine development. We describe here the European Hepatitis C Virus Database (euHCVdb, ), a collection of computer-annotated sequences based on reference genomes. The annotations include genome mapping of sequences, use of recommended nomenclature, subtyping as well as three-dimensional (3D) molecular models of proteins. A WWW interface has been developed to facilitate database searches and the export of data for sequence and structure analyses. As part of an international collaborative effort with the US and Japanese databases, the European HCV Database (euHCVdb) is mainly dedicated to HCV protein sequences, 3D structures and functional analyses

Testing the 'zero-sum game' hypothesis: An examination of school health policy and practice and inequalities in educational outcomes

Background: There is recognition that health and education are intrinsically linked, through for example the World Health Organizations' Health Promoting Schools' (HPS) framework. Nevertheless, promoting health via schools is seen by some as a 'zero-sum game'; that is, schools have nothing to gain, and in fact may experience detriments to the core business of academic attainment as a result of focussing resources on health. Crucially, there is a paucity of evidence around the impacts of health and well-being policy and practice on attainment, with recent Cochrane reviews highlighting this gap. This study explored the 'zero-sum game' hypothesis among schools with varying levels of deprivation; that is, the role of health and wellbeing interventions in schools in reducing, or widening, socioeconomic inequality in educational attainment. Methods: Wales-wide, school-level survey data on health policies and practices, reflective of the HPS framework, were captured in 2016 using the School Environment Questionnaire (SEQ). SEQ data were linked with routinely collected data on academic attainment. Primary outcomes included attendance and attainment at Key Stages 3 and 4. Interaction terms were fitted to test whether there was an interaction between FSM,overall HPS activity, and outcomes. Linear regression models were constructed separately for high (>15% of pupils) and low (<15%) Free School Meal (FSM) schools, adjusting for confounders. Findings: The final analyses included 48 low and 49 high FSM secondary schools. Significant interactions were observed between FSM and overall HPS for KS3 attainment (b=0.28; 95% CI: 0.09, 0.47) and attendance(b=0.05; 95% CI: 0.02, 0.09), reflecting an association between health improvement activities and education outcomes among high, but not low FSM schools. There was no significant interaction for KS4 attainment (b=0.18; 95% CI: -0.22, 0.57).Interpretation: Our findings did not support the 'zero-sum game' hypothesis; in fact, among more deprived schools, there was a tendency for better attendance and attainment at Key Stage 3. Schools must equip students with the skills required for good physical, mental health and well-being in addition to academic and cognitive skills. The study included a large, nationally representative sample of secondary schools;however, the cross-sectional nature has implications for causality

Développement et optimisation d’un outil de simulation en C++ de données génomiques en populations spatialisées

National audienceLe développement rapide des techniques de séquençage, ainsi que des moyens de calculs informatiques a révolutionné la génétique/génomique des populations ces 20 dernières années. Cependant, du fait de la difficulté à obtenir des données génomiques individuelles et géo-référencées pour de gros échantillons et de la lourdeur des modèles spatialement explicites, l’aspect spatial a souvent été délaissé. On assiste aujourd’hui à deux changements majeurs : les génomes individuels atteignent un prix raisonnable, les méthodes d’estimations basées sur la simulation de type ABC (Approximate Bayesian Computations) ont gagné un facteur 10 à 100 en terme d’efficacité grâce à l’utilisation des algorithmes de forêts aléatoires (Pudlo et al. 2015). De ce fait, il est maintenant envisageable de faire de l’estimation de paramètres démographiques (dispersion, densité et tailles de populations) et historiques (dater des changements démographiques) à partir de données génomiques sous des modèles démo-génétiques spatialisés de plus en plus réalistes. Améliorer ces techniques d’inférences et les modèles sous-jacents permettra de répondre à des questions essentielles pour mieux comprendre la répartition et l’évolution de la diversité génétique des populations dans le temps et l’espace. Notre but est d’implémenter un nouveau simulateur de données génomiques basé sur des algorithmes de coalescences pouvant considérer des modèles spatialisés, afin de l’utiliser pour faire de l’inférence démo-génétique. Les techniques modernes d’inférence, par ABC entre autres, nécessitant des algorithmes efficaces, autant en terme de vitesse d’exécution des calculs que de l’espace mémoire nécessaire, le choix des méthodes de stockage et d’indexation des arbres de coalescence et des génomes simulés est donc crucial pour permettre de simuler de gros jeux de données très rapidement (Kelleher et al. 2016). Ce projet vise le développement d’un logiciel autonome, open source, collaboratif (Git) et si possible en intégration continue. Il est organisé de façon à s’orienter vers une programmation dite ” moderne ” en C++, utilisant de manière extensive les nouveautés du standard (C++11/14/17), de manière à produire un code lisible, concis, optimisé et immédiatement réutilisabl

Application of ABC to infer the genetic history of Pygmy hunter-gatherer populations from Western Central Africa

International audienc

Application of Approximate Bayesian Computation to infer the genetic history of Pygmy hunter-gatherers populations from Western Central Africa

International audienc

DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data.

International audienceDIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows (i) the analysis of single nucleotide polymorphism data at large number of loci, apart from microsatellite and DNA sequence data, (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X. Freely available with a detailed notice document and example projects to academic users at http://www1.montpellier.inra.fr/CBGP/diyabc CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Integrative systematic revision reveals cryptic species in the Calliptamus genus

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16S rRNA amplicon sequencing for epidemiological surveys of bacteria in wildlife

The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculusdomesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs

Table of presence and absence for the twelve pathogenic OTUs in the 704 analysed rodents

This XLSX file shows the presence (1) or absence (0) for the twelve pathogenic OTUs in the spleen of the 704 analysed rodents after the data filtering

Gérez vos données de la recherche - Formation

Formation "En route vers la Science Ouverte" - Collège Doctoral - U