An expression map for Anopheles gambiae

Journal article

Abstract

Background

Quantitative transcriptome data for the malaria-transmitting mosquito Anopheles gambiae covers a broad range of biological and experimental conditions, including development, blood feeding and infection. Web-based summaries of differential expression for individual genes with respect to these conditions are a useful tool for the biologist, but they lack the context that a visualisation of all genes with respect to all conditions would give. For most organisms, including A. gambiae, such a systems-level view of gene expression is not yet available.

Results

We have clustered microarray-based gene-averaged expression values, available from VectorBase, for 10194 genes over 93 experimental conditions using a self-organizing map. Map regions corresponding to known biological events, such as egg production, are revealed. Many individual gene clusters (nodes) on the map are highly enriched in biological and molecular functions, such as protein synthesis, protein degradation and DNA replication. Gene families, such as odorant binding proteins, can be classified into distinct functional groups based on their expression and evolutionary history. Immunity-related genes are non-randomly distributed in several distinct regions on the map, and are generally distant from genes with house-keeping roles. Each immunity-rich region appears to represent a distinct biological context for pathogen recognition and clearance (e.g. the humoral and gut epithelial responses). Several immunity gene families, such as peptidoglycan recognition proteins (PGRPs) and defensins, appear to be specialised for these distinct roles, while three genes with physically interacting protein products (LRIM1/APL1C/TEP1) are found in close proximity.

Conclusions

The map provides the first genome-scale, multi-experiment overview of gene expression in A. gambiae and should also be useful at the gene-level for investigating potential interactions. A web interface is available through the VectorBase website http://www.vectorbase.org/. It is regularly updated as new experimental data becomes available.

Authors: Maccallum, RM; Redmond, SN; Christophides, GK

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: BioMed Central
• Journal: BMC Genomics
• Volume: 12
• Issue: 1
• Pages: 620-620
• Publication date: 2011-12-20
• DOI: 10.1186/1471-2164-12-620
• EISSN: 1471-2164
• ISSN: 1471-2164
• Language: English
• Keywords: Gene expression profiling; Gene expression; Computational biology; Evolutionary biology; Malaria; Biology; Transcriptome; Gene; DNA microarray; Genetics; Anopheles gambiae; Context (archaeology)