Gene expression atlas at the European bioinformatics institute

Abstract

The Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive of Functional Genomics Data. A simple interface allows the user to query for differential gene expression either (i) by gene names or attributes such as Gene Ontology terms, or (ii) by biological conditions, e.g. diseases, organism parts or cell types. The gene queries return the conditions where expression has been reported, while condition queries return which genes are reported to be expressed in these conditions. A combination of both query types is possible. The query results are ranked using various statistical measures and by how many independent studies in the database show the particular gene-condition association. Currently, the database contains information about more than 200,000 genes from nine species and almost 4500 biological conditions studied in over 30,000 assays from over 1000 independent studies.

Figure 1.

Gene Expression Atlas home page. Querying for gene(s) will identify all genes whose annotation matches your query. The ‘Conditions’ parameter will identify all experiments in which the conditions that match your query appear. Searches can be restricted only to genes belonging to a given organism and also by direction of differential expression.

Figure 2.

‘Gene page’ for Mus musculus Saa4. The following information is displayed: (A) summary of terms and external databases cross-references, as well as orthologue genes, which allows comparison of orthologues across the Atlas; (B) expression heat map listing all the conditions in which the gene was observed differentially expressed. The heatmap cell colour ranges from red, i.e. up-regulated, to blue, i.e. down-regulated. For each condition, the number of independent studies in which the gene was observed significantly up- or down-regulated is provided. Saa4 is over-expressed in ‘liver’, in 16 independent studies, which is consistent with the notion that liver is the primary site of Saa4 mRNA transcription (8) and (C) thumbnail plots of gene expression profiles for the studies in which the gene was found to be differentially expressed. Saa4 shows the highest significance of differential expression in the experiment E-MEXP-1190, comparing kidney, liver and spleen, each assayed in several replicates. A link to the experimental details in the ArrayExpress Archive of Functional Genomics Data is provided for each experiment.

Figure 3.

Gene expression profile page for experiment E-MEXP-1190 showing the table of genes with similar expression profile to Saa4, identified through similarity search. In the main graph, the horizontal axis shows all samples in this experiment, grouped by EF. The vertical axis shows the expression levels for Saa4 in each sample. The EF ‘organism part’ is selected and, under this condition, Saa4 has notably higher expression values in liver, as expected. Sample attributes can be selected from the ‘Sample attributes’ table and highlighted on the graph.

Figure 4.

Query results for human genes matching GO term ‘Wnt signaling pathway’ expressed in condition ‘carcinoma’. The ‘conditions’ auto complete function uses the EFO controlled vocabulary to expand queries, to query synonyms and to suggest query terms (top). In this example, SOX4 gene is over-expressed in adenocarcinoma in three different independent studies. Results are split over several pages and can be downloaded using the link provided (middle). Advanced query functionality is accessed using the ‘advanced search’ link below the ‘Search Atlas’ button.

Figure 5.

Distributions of differentially expressed genes over (A) experiments and (B) EFs. Error bars in (B) mark the 25% and 75% quantiles in the differentially expressed gene count for each EF.