RESUMO
The first draft of the human malaria parasite's genome was released in 2002. Since then, the malaria scientific community has witnessed a steady embrace of new and powerful functional genomic studies. Over the years, these approaches have slowly revolutionized malaria research and enabled the comprehensive, unbiased investigation of various aspects of the parasite's biology. These genome-wide analyses delivered a refined annotation of the parasite's genome, delivered a better knowledge of its RNA, proteins and metabolite derivatives, and fostered the discovery of new vaccine and drug targets. Despite the positive impacts of these genomic studies, most research and investment still focus on protein targets, drugs and vaccine candidates that were known before the publication of the parasite genome sequence. However, recent access to next-generation sequencing technologies, along with an increased number of genome-wide applications, is expanding the impact of the parasite genome on biomedical research, contributing to a paradigm shift in research activities that may possibly lead to new optimized diagnosis and treatments. This review provides an update of Plasmodium falciparum genome sequences and an overview of the rapid development of genomics and system biology applications that have an immense potential of creating powerful tools for a successful malaria eradication campaign.
Assuntos
Antimaláricos/uso terapêutico , Genômica , Malária Falciparum , Plasmodium falciparum/genética , Biologia de Sistemas/métodos , Animais , Genoma de Protozoário/genética , Humanos , Malária Falciparum/tratamento farmacológico , Malária Falciparum/genética , Malária Falciparum/prevenção & controle , Plasmodium falciparum/efeitos dos fármacos , Proteômica , TranscriptomaRESUMO
Recent genome-wide studies on nucleosome positioning in model organisms have shown strong evidence that nucleosome landscapes in the proximity of protein-coding genes exhibit regular characteristic patterns. Here, we propose a computational framework to discover novel genes in the human malaria parasite genome P. falciparum using nucleosome positioning inferred from MAINE-seq data. We rely on a classifier trained on the nucleosome landscape profiles of experimentally verified genes, and then used to discover new genes (without considering the primary DNA sequence). Cross-validation experiments show that our classifier is very accurate. About two thirds of the locations reported by the classifier match experimentally determined expressed sequence tags in GenBank, for which no gene has been annotated in the human malaria parasite.
