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Open Access Highly Accessed Research article

Digital gene expression analysis of two life cycle stages of the human-infective parasite, Trypanosoma brucei gambiense reveals differentially expressed clusters of co-regulated genes

Nicola J Veitch1, Paul CD Johnson2, Urmi Trivedi3, Sandra Terry1, David Wildridge1 and Annette MacLeod1*

Author Affiliations

1 Wellcome Centre for Molecular Parasitology, Glasgow Biomedical Research Centre, University of Glasgow, Glasgow, G12 8TA, UK

2 Robertson Centre for Biostatistics, Boyd Orr Building, University of Glasgow, Glasgow, G12 8QQ, UK

3 The Gene Pool, Ashworth Laboratories, The King's Buildings, The University of Edinburgh, Edinburgh, EH9 3JT, UK

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BMC Genomics 2010, 11:124  doi:10.1186/1471-2164-11-124

Published: 22 February 2010

Abstract

Background

The evolutionarily ancient parasite, Trypanosoma brucei, is unusual in that the majority of its genes are regulated post-transcriptionally, leading to the suggestion that transcript abundance of most genes does not vary significantly between different life cycle stages despite the fact that the parasite undergoes substantial cellular remodelling and metabolic changes throughout its complex life cycle. To investigate this in the clinically relevant sub-species, Trypanosoma brucei gambiense, which is the causative agent of the fatal human disease African sleeping sickness, we have compared the transcriptome of two different life cycle stages, the potentially human-infective bloodstream forms with the non-human-infective procyclic stage using digital gene expression (DGE) analysis.

Results

Over eleven million unique tags were generated, producing expression data for 7360 genes, covering 81% of the genes in the genome. Compared to microarray analysis of the related T. b. brucei parasite, approximately 10 times more genes with a 2.5-fold change in expression levels were detected. The transcriptome analysis revealed the existence of several differentially expressed gene clusters within the genome, indicating that contiguous genes, presumably from the same polycistronic unit, are co-regulated either at the level of transcription or transcript stability.

Conclusions

DGE analysis is extremely sensitive for detecting gene expression differences, revealing firstly that a far greater number of genes are stage-regulated than had previously been identified and secondly and more importantly, this analysis has revealed the existence of several differentially expressed clusters of genes present on what appears to be the same polycistronic units, a phenomenon which had not previously been observed in microarray studies. These differentially regulated clusters of genes are in addition to the previously identified RNA polymerase I polycistronic units of variant surface glycoproteins and procyclin expression sites, which encode the major surface proteins of the parasite. This raises a number of questions regarding the function and regulation of the gene clusters that clearly warrant further study.