Towards the understanding of the cocoa transcriptome: Production and analysis of an exhaustive dataset of ESTs of Theobroma cacao L. generated from various tissues and under various conditions

Theobroma cacao L., is a tree originated from the tropical rainforest of South America. It is one of the major cash crops for many tropical countries. T. cacao is mainly produced on smallholdings, providing resources for 14 million farmers. Disease resistance and T. cacao quality improvement are two important challenges for all actors of cocoa and chocolate production. T. cacao is seriously affected by pests and fungal diseases, responsible for more than 40% yield losses and quality improvement, nutritional and organoleptic, is also important for consumers. An international collaboration was formed to develop an EST genomic resource database for cacao. Fifty-six cDNA libraries were constructed from different organs, different genotypes and different environmental conditions. A total of 149,650 valid EST sequences were generated corresponding to 48,594 unigenes, 12,692 contigs and 35,902 singletons. A total of 29,849 unigenes shared significant homology with public sequences from other species. Gene Ontology (GO) annotation was applied to distribute the ESTs among the main GO categories. A specific information system (ESTtik) was constructed to process, store and manage this EST collection allowing the user to query a database. To check the representativeness of our EST collection, we looked for the genes known to be involved in two different metabolic pathways extensively studied in other plant species and important for T. cacao qualities: the flavonoid and the terpene pathways. Most of the enzymes described in other crops for these two metabolic pathways were found in our EST collection. A large collection of new genetic markers was provided by this ESTs collection. This EST collection displays a good representation of the T. cacao transcriptome, suitable for analysis of biochemical pathways based on oligonucleotide microarrays derived from these ESTs. It will provide numerous genetic markers that will allow the construction of a high density gene map of T. cacao. This EST collection represents a unique and important molecular resource for T. cacao study and improvement, facilitating the discovery of candidate genes for important T. cacao trait variation. (Résumé d'auteur

On-line high-precision carbon position-specific stable isotope analysis: a review

Since the first commercial availability of gas chromatographs coupled with a combustion furnace and an isotope ratio mass spectrometry in 1990, compound-specific stable isotope analysis of organic molecules has been at the origin of scientific breakthroughs in a wide range of research fields. The presence of non-reacting atoms, however, can mask changes in molecular stable isotopic signatures; position-specific isotope analysis (PSIA) is the study of intramolecular isotopic variations. After a brief consideration of the potential and prospect of this new level in isotopic studies, in this study, we review few existing custom-built systems for on-line PSIA using continuous flow isotope ratio mass spectrometry instrumentation and how researchers have addressed issues related to this technique. Molecular fragmentation processes observed and optimised for various molecules are also discussed for on-line PSIA, as it would provide information on their application to new compounds

Generating constrained random graphs using multiple edge switches

The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distributions. However, in general, it is not necessarily possible to access all graphs obeying some given con- straints through a classical switching procedure calling on pairs of edges. We therefore propose to get round this issue by generalizing this classical approach through the use of higher-order edge switches. This method, which we denote by "k-edge switching", makes it possible to progres- sively improve the covered portion of a set of constrained graphs, thereby providing an increasing, asymptotically certain confidence on the statistical representativeness of the obtained sample.Comment: 15 page

Expression cartography of human tissues using self organizing maps

Background: The availability of parallel, high-throughput microarray and sequencing experiments poses a challenge how to best arrange and to analyze the obtained heap of multidimensional data in a concerted way. Self organizing maps (SOM), a machine learning method, enables the parallel sample- and gene-centered view on the data combined with strong visualization and second-level analysis capabilities. The paper addresses aspects of the method with practical impact in the context of expression analysis of complex data sets.
Results: The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten thousands of genes to a few thousands of metagenes where each metagene acts as representative of a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of gene sets well corresponding to molecular processes in the respective tissues. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering provide a better signal-to-noise ratio and a better representativeness of the method if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues into essentially three clusters containing nervous, immune system and the remaining tissues. 
Conclusions: The global view on the behavior of a few well-defined modules of correlated and differentially expressed genes is more intuitive and more informative than the separate discovery of the expression levels of hundreds or thousands of individual genes. The metagene approach is less sensitive to a priori selection of genes. It can detect a coordinated expression pattern whose components would not pass single-gene significance thresholds and it is able to extract context-dependent patterns of gene expression in complex data sets.
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Expression cartography of human tissues using self organizing maps

Background: The availability of parallel, high-throughput microarray and sequencing experiments poses a challenge how to best arrange and to analyze the obtained heap of multidimensional data in a concerted way. Self organizing maps (SOM), a machine learning method, enables the parallel sample- and gene-centered view on the data combined with strong visualization and second-level analysis capabilities. The paper addresses aspects of the method with practical impact in the context of expression analysis of complex data sets.
Results: The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten thousands of genes to a few thousands of metagenes where each metagene acts as representative of a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of gene sets well corresponding to molecular processes in the respective tissues. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering provide a better signal-to-noise ratio and a better representativeness of the method if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues into essentially three clusters containing nervous, immune system and the remaining tissues. 
Conclusions: The global view on the behavior of a few well-defined modules of correlated and differentially expressed genes is more intuitive and more informative than the separate discovery of the expression levels of hundreds or thousands of individual genes. The metagene approach is less sensitive to a priori selection of genes. It can detect a coordinated expression pattern whose components would not pass single-gene significance thresholds and it is able to extract context-dependent patterns of gene expression in complex data sets.
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Inverse association of circulating SIRT1 and adiposity. A study on underweight, normal weight, and obese patients

Context: Sirtuins (SIRTs) are NAD+-dependent deacetylases, cellular sensors to detect energy availability, and modulate metabolic processes. SIRT1, the most studied family member, influences a number of tissues including adipose tissue. Expression and activity of SIRT1 reduce with weight gain and increase in conditions of starvation. Objective: To focus on SIRT1 plasma concentrations in different conditions of adiposity and to correlate SIRT1 with fat content and distribution, energy homeostasis and inflammation in under-weight, normal-weight, and obese individuals. Materials and Methods: 21 patients with anorexia nervosa, 26 normal-weight and 75 patients with obesity were evaluated. Body fat composition by dual-energy X-ray absorptiometry, ultrasound liver adiposity, echocardiographic epicardial fat thickness (EFT), inflammatory (ESR, CRP, and fibrinogen), and metabolic (FPG, insulin, LDL- and HDL-cholesterol, triglycerides) parameters, calculated basal metabolic rate (BMR) and plasma SIRT1 (ELISA) were measured. Results: SIRT1 was significantly higher in anorexic patients compared to normal-weight and obese patients (3.27 ± 2.98, 2.27 ± 1.13, and 1.36 ± 1.31 ng/ml, respectively). Linear regression models for each predictor variable adjusted for age and sex showed that SIRT1 concentration was inversely and significantly correlated with EFT, fat mass %, liver fat content, BMR, weight, BMI, WC, LDL-cholesterol, insulin, ESR. Stepwise multiple regression analysis revealed that age and EFT were the best independent correlates of SIRT1 (β = -0.026 ± 0.011, p = 0.025, and β = -0.516 ± 0.083, p < 0.001, respectively). Conclusions: Plasma SIRT1 shows a continuous pattern that inversely follows the whole spectrum of adiposity. SIRT1 significantly associates with EFT, a strong index of visceral fat phenotype, better than other indexes of adiposity studied here

Association between C-reactive protein with all-cause mortality in ELSA-Brasil cohort

Background: High-sensitive C-reactive protein (hsCRP) has been proposed as a marker of incident cardiovascular disease and vascular mortality, and it may also be a marker of non-vascular mortality. However, most evidence comes from either North American or European cohorts. The present proposal aims to investigate the association of high-sensitive C-reactive protein with the risk of all-cause mortality in a multi-ethnic Brazilian population Methods: Cohort data from baseline (2008–2010) of 14 792 subjects participating in the Brazilian Longitudinal Study of Adult Health were used. HsCRP was assayed with Immunochemistry. The association of baseline covariates with all-cause mortality was calculated by Cox regression for univariate model and adjusted for different confounders after mean follow-up of 8.0 ± 1.1 years. The final model was adjusted for age, sex, self-rated race/ethnicity, schooling, health behaviours and prevalent chronic disease. Results: The risk of death increased steadily by quartiles of hsCRP from 1.45 (95% Confidence Interval: 1.05, 2.01) in Quartile 2 to 1.95 (1.42, 2.69) in Quartile 4 compared to Quartile 1. Furthermore, the persistence of a significant graded association after the exclusion of deaths in the first year of follow-up suggests that these results are unlikely to be due to reverse causality. Finally, the hazard ratios were unaffected by the exclusion of participants that had self-reported past medical history for diabetes, cancer and chronic obstructive pulmonary disease. Conclusions: Our study shows that hsCRP levels is associated with mortality in a highly admixed population, independently of a large set of lifestyle and clinical variables

Children’s body composition and stress, the ChiBS study : aims, design, methods, population and participation characteristics

BACKGROUND: The last decades, the prevalence of childhood obesity has increased. Apart from other lifestyle factors, the effect of chronic psychosocial stress on the development of obesity has been recognized. However, more research is needed into the influence of chronic stress on appetite regulation, energy balance and body composition, as well as on the interaction with physical activity/sedentary behavior, diet and sleep in children. In this regard, the ChiBS study (Children’s Body composition and Stress) was designed at the Ghent University. Within this paper, we describe the aims, design, methods, participation and population characteristics of the ChiBS study. METHODS: The influence of chronic stress on changes in body composition is investigated over a two-year follow-up period (February-June 2010, 2011 and 2012) in primary-school children between 6 and 12 years old in the city Aalter (Flanders, Belgium). Stress is measured by child- and parent-reported stress-questionnaires, as well as by objective stress biomarkers (serum, salivary and hair cortisol) and heart rate variability. Body composition is evaluated using basic anthropometric measurements and air displacement plethysmography. Additional information on socio-economic status, medical history, physical activity, dietary intake and sleep are obtained by questionnaires, and physical activity by accelerometers. RESULTS: The participation percentage was 68.7% (N = 523/761), with 71.3% of the children willing to participate in the first follow-up survey. Drop-out proportions were highest for serum sampling (12.1%), salivary sampling (8.3%) and heart rate variability measurements (7.4%). DISCUSSION: The ChiBS project is unique in its setting: its standardized and longitudinal approach provides valuable data and new insights into the relationship between stress and changes in body composition in a large cohort of young children. In addition, this study allows an in-depth investigation of the validity of the different methods that were used to assess stress levels in children

Relating the metatranscriptome and metagenome of the human gut

Although the composition of the human microbiome is now wellstudied, the microbiota’s \u3e8 million genes and their regulation remain largely uncharacterized. This knowledge gap is in part because of the difficulty of acquiring large numbers of samples amenable to functional studies of the microbiota. We conducted what is, to our knowledge, one of the first human microbiome studies in a well-phenotyped prospective cohort incorporating taxonomic, metagenomic, and metatranscriptomic profiling at multiple body sites using self-collected samples. Stool and saliva were provided by eight healthy subjects, with the former preserved by three different methods (freezing, ethanol, and RNAlater) to validate self-collection. Within-subject microbial species, gene, and transcript abundances were highly concordant across sampling methods, with only a small fraction of transcripts (\u3c5%) displaying between-method variation. Next, we investigated relationships between the oral and gut microbial communities, identifying a subset of abundant oral microbes that routinely survive transit to the gut, but with minimal transcriptional activity there. Finally, systematic comparison of the gut metagenome and metatranscriptome revealed that a substantial fraction (41%) of microbial transcripts were not differentially regulated relative to their genomic abundances. Of the remainder, consistently underexpressed pathways included sporulation and amino acid biosynthesis, whereas up-regulated pathways included ribosome biogenesis and methanogenesis. Across subjects, metatranscriptional profiles were significantly more individualized than DNA-level functional profiles, but less variable than microbial composition, indicative of subject-specific whole-community regulation. The results thus detail relationships between community genomic potential and gene expression in the gut, and establish the feasibility of metatranscriptomic investigations in subject-collected and shipped samples