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Genome-wide SNP Analysis of Shows Differentiation at Drug-resistance-associated Loci Among Malaria Transmission Settings in Southern Mali

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Journal Front Genet
Date 2022 Oct 21
PMID 36267403
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Abstract

malaria cases in Africa represent over 90% of the global burden with Mali being amongst the 11 highest burden countries that account for 70% of this annual incidence. The persistence of despite massive global interventions is because of its genetic diversity that drives its ability to adapt to environmental changes, develop resistance to drugs, and evade the host immune system. Knowledge on genetic diversity across populations and intervention landscape is thus critical for the implementation of new strategies to eliminate malaria. This study assessed genetic variation with 12,177 high-quality SNPs from 830 Malian isolates collected between 2007 and 2017 from seven locations. The complexity of infections remained high, varied between sites, and showed a trend toward overall decreasing complexity over the decade. Though there was no significant substructure, allele frequencies varied geographically, partly driven by temporal variance in sampling, particularly for drug resistance and antigen loci. Thirty-two mutations in known drug resistance markers (, , , , and ) attained a frequency of at least 2% in the populations. SNPs within and around the major markers of resistance to quinolines ( and ) and antifolates ( and ) varied temporally and geographically, with strong linkage disequilibrium and signatures of directional selection in the genome. These geo-temporal populations also differentiated at alleles in immune-related loci, including, , , , and , as well as , which showed signatures of haplotype differentiation between populations Several regions across the genomes, including five known drug resistance loci, showed signatures of differential positive selection. These results suggest that drugs and immune pressure are dominant selective forces against in Mali, but their effect on the parasite genome varies temporally and spatially. Interventions interacting with these genomic variants need to be routinely evaluated as malaria elimination strategies are implemented.

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