Analysis of Anti-malarial drug-resistant genes of Plasmodium falciparum 3D7 to understand its expression: the bioinformatics approach

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Abstract Malaria is one of the most important infectious diseases that threaten half of the world’s population. Ethiopia is among countries with a high malaria burden. Plasmodium falciparum is the most common (64%) cause of malaria in Ethiopia while P. vivax accounts for the remaining cases (34%). Despite numerous advances in malaria control strategies, the disease still kills countless children worldwide, mainly in sub-Saharan African countries and malaria still remains a major public health problem in Ethiopia. Analyzing parasite genetics has enormous potential to aid both efforts at elimination as well as international efforts toward eradication. Therefore, this study is aimed to insilico analysis of regulatory elements such as CpG islands, transcription factors (TFs) and their corresponding binding sites (TFBSs) involved in the regulation of gene expression of Plasmodium falciparum 3D7 isolates drug resistant genes. In this analysis nine drug resistance affecting gene coding sequences, available in NCBI database with the start codon at the beginning of the sequence and only functional genes (protein coding) were deliberated. Accordingly, the promoter prediction by neural network promoter prediction result showed Plasmodium falciparum 3D7 drug resistance affecting genes have 1–6 TSS and five common candidate motifs (MPfI, MPfII, MPfIII, MPfIV and MPfV) were identified. The study indicates the poor occurrence of CpG islands in both gene body and promoter regions which may affect the access of promoter region of genes to their transcription factors, hence affecting their expression. In general, this in silico analysis of genes encoding for Plasmodium falciparum drug resistance affecting genes could be helpful to add knowledge about the molecular data and supportive to identify gene regulatory elements in the promoter regions.

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