ArrayExpress update--from an archive of functional genomics experiments to the atlas of gene expression.

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository--a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse--a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas--a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200,000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently-ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.

GOAL: a software tool for assessing biological significance of genes groups.

BACKGROUND: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then used to group together genes based on their similarity in expression profiles. Genes in each group are probably functionally related. The functional relevance among the genes in each group is usually characterized by utilizing available biological knowledge in public databases such as Gene Ontology (GO), KEGG pathways, association between a transcription factor (TF) and its target genes, and/or gene networks. RESULTS: We developed GOAL: Gene Ontology AnaLyzer, a software tool specifically designed for the functional evaluation of gene groups. GOAL implements and supports efficient and statistically rigorous functional interpretations of gene groups through its integration with available GO, TF-gene association data, and association with KEGG pathways. In order to facilitate more specific functional characterization of a gene group, we implement three GO-tree search strategies rather than one as in most existing GO analysis tools. Furthermore, GOAL offers flexibility in deployment. It can be used as a standalone tool, a plug-in to other computational biology tools, or a web server application. CONCLUSION: We developed a functional evaluation software tool, GOAL, to perform functional characterization of a gene group. GOAL offers three GO-tree search strategies and combines its strength in function integration, portability and visualization, and its flexibility in deployment. Furthermore, GOAL can be used to evaluate and compare gene groups as the output from computational biology tools such as clustering algorithms.

4DXpress: a database for cross-species expression pattern comparisons.

In the major animal model species like mouse, fish or fly, detailed spatial information on gene expression over time can be acquired through whole mount in situ hybridization experiments. In these species, expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for Drosophila or GXD for mouse. However, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. Therefore, we have integrated expression patterns for zebrafish, Drosophila, medaka and mouse into a central public repository called 4DXpress (expression database in four dimensions). Users can query anatomy ontology-based expression annotations across species and quickly jump from one gene to the orthologues in other species. Genes are linked to public microarray data in ArrayExpress. We have mapped developmental stages between the species to be able to compare developmental time phases. We store the largest collection of gene expression patterns available to date in an individual resource, reflecting 16 505 annotated genes. 4DXpress will be an invaluable tool for developmental as well as for computational biologists interested in gene regulation and evolution. 4DXpress is available at http://ani.embl.de/4DXpress.

Identification of conserved core xylem gene sets: conifer cDNA microarray development, transcript profiling and computational analyses.

One approach for investigating the molecular basis of wood formation is to integrate microarray profiling data sets and sequence analyses, comparing tree species with model plants such as Arabidopsis. Conifers may be included in comparative studies thanks to large-scale expressed sequence tag (EST) analyses, which enable the development of cDNA microarrays with very significant genome coverage. A microarray of 10,400 low-redundancy sequences was designed starting from white spruce (Picea glauca (Moench.) Voss) cDNAs. Computational procedures that were developed to ensure broad transcriptome coverage and efficient PCR amplification were used to select cDNA clones, which were re-sequenced in the microarray manufacture process. White spruce transcript profiling experiments that compared secondary xylem to phloem and needles identified 360 xylem-preferential gene sequences. The functional annotations of all differentially expressed sequences were highly consistent with the results of similar analyses carried out in angiosperm trees and herbaceous plants. Computational analyses comparing the spruce microarray sequences and core xylem gene sets from Arabidopsis identified 31 transcripts that were highly conserved in angiosperms and gymnosperms, in terms of both sequence and xylem expression. Several other spruce sequences have not previously been linked to xylem differentiation (including genes encoding TUBBY-like domain proteins (TLPs) and a gibberellin insensitive (gai) gene sequence) or were shown to encode proteins of unknown function encompassing diverse conserved domains of unknown function.