Plant-based microarray data at the European Bioinformatics Institute. Introducing AtMIAMExpress, a submission tool for Arabidopsis gene expression data to ArrayExpress

ArrayExpress is a public microarray repository founded on the Minimum Information About a Microarray Experiment (MIAME) principles that stores MIAME-compliant gene expression data. Plant-based data sets represent approximately one-quarter of the experiments in ArrayExpress. The majority are based on Arabidopsis (Arabidopsis thaliana); however, there are other data sets based on Triticum aestivum, Hordeum vulgare, and Populus subsp. AtMIAMExpress is an open-source Web-based software application for the submission of Arabidopsis-based microarray data to ArrayExpress. AtMIAMExpress exports data in MAGE-ML format for upload to any MAGE-ML-compliant application, such as J-Express and ArrayExpress. It was designed as a tool for users with minimal bioinformatics expertise, has comprehensive help and user support, and represents a simple solution to meeting the MIAME guidelines for the Arabidopsis community. Plant data are queryable both in ArrayExpress and in the Data Warehouse databases, which support queries based on gene-centric and sample-centric annotation. The AtMIAMExpress submission tool is available at http://www.ebi.ac.uk/at-miamexpress/. The software is open source and is available from http://sourceforge.net/projects/miamexpress/. For information, contact miamexpress@ebi.ac.uk.     

Human metabolic profiles are stably controlled by genetic and environmental variation

¹H Nuclear Magnetic Resonance spectroscopy (¹H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top‐down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource. In our unique design, identical and non‐identical twin pairs donated plasma and urine samples longitudinally. We acquired ¹H NMR spectra on the samples, and statistically decomposed variation in metabolite concentration into familial (genetic and common‐environmental), individual‐environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual‐environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in ¹H NMR‐detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker‐discovery studies. We provide a power‐calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect ¹H NMR‐based biomarkers quantifying predisposition to disease.     

Genetic differentiation and hybridization between greater and lesser spotted eagles (Accipitriformes:Aquila clanga, A. pomarina)

Greater and lesser spotted eagles (Aquila clanga, A. pomarina) are two closely related forest eagles overlapping in breeding range in east-central Europe. In recent years a number of mixed pairs have been observed, some of which fledged hybrid young. Here we use mitochondrial (control region) DNA sequences and AFLP markers to estimate genetic differentiation and possible gene flow between these species. In a sample of 83 individuals (61 pomarina, 20 clanga, 2 F1-hybrids) we found 30 mitochondrial haplotypes which, in a phylogenetic network, formed two distinct clusters differing on average by 3.0% sequence divergence. The two species were significantly differentiated both at the mitochondrial and nuclear (AFLP) genetic level. However, five individuals with pomarina phenotype possessed clanga-type mtDNA, suggesting occasional gene flow. Surprisingly, AFLP markers indicated that these mismatched birds (originating from Germany, E Poland and Latvia) were genetically intermediate between the samples of individuals in which mtDNA haplotype and phenotype agreed. This indicates that mismatched birds were either F1 or recent back-cross hybrids. Mitochondrial introgression was asymmetrical (no pomarina haplotype found in clanga so far), which may be due to assortative mating by size. Gene flow of nuclear markers was estimated to be about ten times stronger than for mtDNA, indicating a sex-bias in hybrid fertility in accordance with Haldanes rule. Hybridization between the two species may be more frequent and may occur much further west than hitherto assumed. This is supported by the recent discovery of a mixed pair producing at least one fledgling in NE Germany.     

ArrayExpress: a public database of gene expression data at EBI

ArrayExpress is a public repository for microarray-based gene expression data, resulting from the implementation of the MAGE object model to ensure accurate data structuring and the MIAME standard, which defines the annotation requirements. ArrayExpress accepts data as MAGE-ML files for direct submissions or data from MIAMExpress, the MIAME compliant web-based annotation and submission tool of EBI. A team of curators supports the submission process, providing assistance in data annotation. Data retrieval is performed through a dedicated web interface. Relevant results may be exported to ExpressionProfiler, the EBI based expression analysis tool available online (http://www.ebi.ac.uk/arrayexpress).     

Design and implementation of microarray gene expression markup language (MAGE-ML)

Background

Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies.

Results

To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems.

Conclusions

MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.     

A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection

We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10(-11)相似文献   

The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.