Evidence-Based Annotation of the Malaria Parasite's Genome Using Comparative Expression Profiling

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Evidence-Based Annotation of the Malaria Parasite's Genome Using Comparative Expression Profiling

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Title: Evidence-Based Annotation of the Malaria Parasite's Genome Using Comparative Expression Profiling
Author: Zhou, Yingyao; Ramachandran, Vandana; Kumar, Kota Arun; Westenberger, Scott; Refour, Phillippe; Zhou, Bin; Li, Fengwu; Young, Jason A.; Chen, Kaisheng; Plouffe, David; Henson, Kerstin; Nussenzweig, Victor; Carlton, Jane; Vinetz, Joseph M.; Winzeler, Elizabeth A.; Duraisingh, Manoj T.; Hofmann, Oliver Marc

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Citation: Zhou, Yingyao, Vandana Ramachandran, Kota Arun Kumar, Scott Westenberger, Phillippe Refour, Bin Zhou, Fengwu Li, et al. 2008. Evidence-based annotation of the Malaria parasite's genome using comparative expression profiling. PLoS ONE 3(2): e1570.
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Abstract: A fundamental problem in systems biology and whole genome sequence analysis is how to infer functions for the many uncharacterized proteins that are identified, whether they are conserved across organisms of different phyla or are phylum-specific. This problem is especially acute in pathogens, such as malaria parasites, where genetic and biochemical investigations are likely to be more difficult. Here we perform comparative expression analysis on Plasmodium parasite life cycle data derived from P. falciparum blood, sporozoite, zygote and ookinete stages, and P. yoelii mosquito oocyst and salivary gland sporozoites, blood and liver stages and show that type II fatty acid biosynthesis genes are upregulated in liver and insect stages relative to asexual blood stages. We also show that some universally uncharacterized genes with orthologs in Plasmodium species, Saccharomyces cerevisiae and humans show coordinated transcription patterns in large collections of human and yeast expression data and that the function of the uncharacterized genes can sometimes be predicted based on the expression patterns across these diverse organisms. We also use a comprehensive and unbiased literature mining method to predict which uncharacterized parasite-specific genes are likely to have roles in processes such as gliding motility, host-cell interactions, sporozoite stage, or rhoptry function. These analyses, together with protein-protein interaction data, provide probabilistic models that predict the function of 926 uncharacterized malaria genes and also suggest that malaria parasites may provide a simple model system for the study of some human processes. These data also provide a foundation for further studies of transcriptional regulation in malaria parasites.
Published Version: doi:10.1371/journal.pone.0001570
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2215772/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4554117
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