Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p

Lower risk of atopic dermatitis among infants born extremely preterm compared with higher gestational age

International audienceBackground It is not yet known whether the risk of developing atopic dermatitis (AD) is influenced by preterm birth. Moreover, AD risk has not been assessed in a large sample of extremely preterm infants (<29weeks' gestation). Objectives To determine whether the risk of AD is influenced by preterm birth. Methods We investigated the relationship between gestational age (GA) and AD using data from two independent population-based cohorts, including a total of 2329 preterm infants, of whom 479 were born extremely preterm. Results There was a lower percentage of children with AD in the extremely preterm group compared with those born at a greater GA (Epipage cohort, 2-year outcome: 133% for 24-28weeks, 176% for 29-32weeks, 218% for 33-34weeks, P=002; LIFT cohort, 5-year outcome: 11% for 24-28weeks, 215% for 29-32weeks, 196% for 33-34weeks, P=011). After adjusting for confounding variables, a lower GA (<29weeks) was significantly associated with decreased risk of AD in the Epipage cohort [adjusted odds ratio (aOR) 057, 95% confidence interval (CI) 037-087; P=0009] and the LIFT cohort (aOR 041, 95% CI 018-090; P=003). Conclusions Very low GA (<29weeks) was associated with a lower risk of AD compared with higher GA (29-34weeks) and full-term birth

Effect of early life hypoxia and diet composition on growth, feed intake and oxygen consumption of rainbow trout (Oncorhynchus mykiss) in later life

Session Nutrition: Physiology and RequirementsEffect of early life hypoxia and diet composition on growth, feed intake and oxygen consumption of rainbow trout (Oncorhynchus mykiss) in later life. Aquaculture Europe 201