Abstract
Brazil is a unique and understudied setting for malaria, with complex foci of transmission associated with human and environmental conditions. An understanding of the population genomic diversity of P.vivax parasites across Brazil can support malaria control strategies. Through whole genome sequencing of P.vivax isolates across 7 Brazilian states, we use population genomic approaches to compare genetic diversity within country (n=123), continent (6 countries, n=315) and globally (26countries, n=885). We confirm that South American isolates are distinct, have more ancestral populations than the other global regions, with differentiating mutations in genes under selective pressure linked to antimalarial drugs (pvmdr1, pvdhfr-ts) and mosquito vectors (pvcrmp3, pvP45/48, pvP47). We demonstrate Brazil as a distinct parasite population, with signals of selection including ABC transporter (PvABCI3) and PHIST exported proteins. Brazil has a complex population structure, with evidence of P.simium infections and Amazonian parasites separating into multiple clusters. Overall, our work provides the first Brazil-wide analysis of P.vivax population structure and identifies important mutations, which can inform future research and control measures. AI is funded by an MRC LiD PhD studentship. TGC is funded by the Medical Research Council (Grant no. MR/M01360X/1, MR/N010469/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1). SC is funded by Medical Research Council UK grants (MR/M01360X/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1) and Bloomsbury SET (ref. CCF17-7779). FN is funded by The Shloklo Malaria Research Unit - part of the Mahidol Oxford Research Unit, supported by the Wellcome Trust (Grant no. 220211). ARSB is funded by São Paulo Research Foundation - FAPESP (Grant no. 2002/09546-1). RLDM is funded by Brazilian National Council for Scientific and Technological Development - CNPq (Grant no. 302353/2003-8 and 471605/2011-5); CRFM is funded by FAPESP (Grant no. 2020/06747-4) and CNPq (Grant no. 302917/2019-5 and 408636/2018-1); JGD is funded by FAPESP fellowships (2016/13465-0 and 2019/12068-5) and CNPq (Grant no. 409216/2018-6).
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