Genomic epidemiology of Plasmodium knowlesi reveals putative genetic drivers of adaptation in Malaysia

Sabah, Malaysia, has amongst the highest burden of human Plasmodium knowlesi infection in the country, associated with increasing encroachment on the parasite’s macaque host habitat. However, the genomic make-up of P. knowlesi in Sabah was previously poorly understood. To inform on local patterns of transmission and putative adaptive drivers, we conduct population-level genetic analyses of P. knowlesi human infections using 52 new whole genomes from Sabah, Malaysia, in combination with publicly available data. We identify the emergence of distinct geographical subpopulations within the macaque-associated clusters using IBD-based connectivity analysis. Secondly, we report on introgression events between the clusters, which may be linked to differentiation of the subpopulations, and that overlap genes critical for survival in human and mosquito hosts. Using village-level locations from P. knowlesi infections, we also identify associations between several introgressed regions and both intact forest perimeter-area ratio and mosquito vector habitat suitability. Our findings provide further evidence of the complex role of changing ecosystems and sympatric macaque hosts in Malaysia driving distinct genetic changes seen in P. knowlesi populations. Future expanded analyses of evolving P. knowlesi genetics and environmental drivers of transmission will be important to guide public health surveillance and control strategies. Author Summary The zoonotic P. knowlesi parasite is an emerging, yet understudied, cause of malaria in Southeast Asia. Sabah, Malaysia, has amongst the highest burden of human P. knowlesi infection in the country, however, the region is currently understudied. Thus, we produced a collection of high-quality P. knowlesi genomes from Sabah, and in combination with publicly available data, performed an extensive population genetics analysis. Our work contributes novel insights for Plasmodium knowlesi population genetics and genetic epidemiology. ### Competing Interest Statement The authors have declared no competing interest.