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Journal of Genetic Engineering and Biotechnology Research(JGEBR)

ISSN: 2690-912X | DOI: 10.33140/JGEBR

Impact Factor: 1.2

Analysis of Antimalarial Drug Resistance Genes of Plasmodium Falciparum 3d7 to Understand Its Expression: A Bioinformatics Approach

Abstract

Gemechis Waktole, Donghee Cho

Background Malaria, which poses a threat to half of the world’s population, is one of the most serious infectious diseases. Ethiopia is a nation with a significant malaria burden. In Ethiopia, Plasmodium falciparum accounts for 64% of cases of malaria, with P. vivax causing the remaining instances (34 percent). The disease still claims the lives of countless children globally, mostly in sub-Saharan African nations, and malaria continues to be a significant public health issue in Ethiopia despite various advancements in malaria control measures. The potential for analyzing parasite genetics to support both national and international efforts to eradicate parasites is immense. To analyze regulatory components such as CpG islands, transcription factors (TFs), and their corresponding binding sites (TFBSs) involved in the control of gene expression of Plasmodium falciparum 3D7 isolate drug resistance genes.

Results Nine drug resistance-related gene-coding sequences from the NCBI database were examined for this analysis. Only functional genes (protein-coding genes) were taken into consideration. Accordingly, genes affected by Plasmodium falciparum 3D7 drug resistance had 1-6 TSS, and five common candidate motifs (MPfI, MPfII, MPfIII, MPfIV, and MPfV) were found in the promoter prediction by neural network promoter prediction results. According to the study, CpG islands are poorly distributed in both the promoter and gene body regions, which may interfere with the accessibility of the promoter to transcription factors and, ultimately, the production of the genes.

Conclusion This in silico analysis of genes encoding Plasmodium falciparum drug resistance-related genes may be useful for enhancing knowledge of the molecular data and supporting the identification of gene regulatory elements in the promoter regions.

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