Malaria is the cause of significant global morbidity and mortality. The completion of its genome sequence promises to accelerate the process of developing new treatments for this debilitating disease by yielding a wealth of new targets. However, only 35% of the proteins identified in the genome sequencing project have a presumed function and an even smaller percentage (<13%) have direct experimental evidence supporting their functional assignment. Given that malaria is an intracellular parasite with difficult genetics, these numbers are unlikely to change significantly in the future if conventional methods are used for determining function. However, functional information could cost-effectively be added to the P. falciparum genome using new high-throughput technologies, such as global gene expression-monitoring. However, before such a goal can be realized it will be important to determine whether or not genes whose products interact with one another and have similar functional roles have common gene expression profiles in P. falciparum. To test this we will examine gene expression profiles from a large number of P. falciparum stages and ask whether or not genes expressed at the same time and at the same place have similar functions. For experimental validation we will concentrate on a group of genes whose expression pattern suggests they may be involved in the reorganization of the erythrocyte cytoskeleton in ring-stage parasites. As a by product of this investigation, new genes involved in host parasite interactions will be confirmed and a transcriptional map will be created showing when and to what level each gene is expressed for all accessible stages of the lifecycle. The data should also aid in the experimental annotation of the genome, allow gene models to be re-evaluated and serve as a rich source of material for others interested in data-mining the parasite genome. The basic genomic methods described here should serve as models for determining gene function in other parasites with difficult genetics.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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Genomics, Computational Biology and Technology Study Section (GCAT)
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Joy, Deirdre A
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Scripps Research Institute
La Jolla
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