Functional Genomics of Plasmodium falciparum: a new approach for identifying therapeutic targets against malaria
Karine G. Le Roch, Y. Zhou, Jeffrey R. Johnson, Jason Young, Claire Kidgell, Elizabeth A. Winzeler
Abstract
Karine G. Le Roch, Y. Zhou, Jeffrey R. Johnson, Jason Young, Claire Kidgell, Elizabeth A. Winzeler
Abstract
In 1996, an international consortium was established to determine the sequence of the 26 Mb Plasmodium falciparum genome. Six years later, the genome sequence was published with an estimation of 5,268 genes. However, 60% of these predicted genes encode hypothetical proteins that share little or no sequence similarity with proteins from other organisms. Elucidation of function using traditional forward and reverse genetic techniques with these hypothetical P. falciparum genes is proving challenging and time consuming. As a result, high‐throughput genomic and proteomic techniques have emerged as important tools to elucidate gene function more rapidly and cost‐effectively. Despite the major challenges posed by the wealth of data generated by high‐throughput genomics and proteomics, we have developed methods to optimize the analysis of these large data sets. Here, we describe how we interpret the data to generate biologically relevant conclusions, which will improve the general understanding of the biology of the malaria parasite as well as lead to the identification of new promising targets for drug and vaccine developments.
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In 1996, an international consortium was established to determine the sequence of the 26 Mb Plasmodium falciparum genome. Six years later, the genome sequence was published with an estimation of 5,268 genes. However, 60% of these predicted genes encode hypothetical proteins that share little or no sequence similarity with proteins from other organisms. Elucidation of function using traditional forward and reverse genetic techniques with these hypothetical P. falciparum genes is proving challenging and time consuming. As a result, high‐throughput genomic and proteomic techniques have emerged as important tools to elucidate gene function more rapidly and cost‐effectively. Despite the major challenges posed by the wealth of data generated by high‐throughput genomics and proteomics, we have developed methods to optimize the analysis of these large data sets. Here, we describe how we interpret the data to generate biologically relevant conclusions, which will improve the general understanding of the biology of the malaria parasite as well as lead to the identification of new promising targets for drug and vaccine developments.
Key concepts: Biology, Computational biology, Genome, Plasmodium falciparum, Genomics, Functional genomics, Proteomics, Identification (biology)