AbstractPlasmodium knowlesi, a malaria parasite of old-world macaque monkeys, is used extensively to model Plasmodium biology. Recently P. knowlesi was found in the human population of Southeast Asia, particularly Malaysia. P. knowlesi causes un-complicated to severe and fatal malaria in the human host with features in common with the more prevalent and virulent malaria caused by Plasmodium falciparum.As such P. knowlesi presents a unique opportunity to inform an experimental model for malaria with clinical data from same-species human infections.Experimental lines of P. knowlesi represent well characterised genetically static parasites and to maximise their utility as a backdrop for understanding malaria pathophysiology, genetically diverse contemporary clinical isolates, essentially wild-type, require comparable characterization.The Oxford Nanopore PCR-free long-read sequencing platform was used to sequence P. knowlesi parasites from archived clinical samples. The sequencing platform and assembly pipeline was designed to facilitate capturing data on important multiple gene families, including the P. knowlesi schizont-infected cell agglutination (SICA) var genes and the Knowlesi-Interspersed Repeats (KIR) genes.The SICAvar and KIR gene families code for antigenically variant proteins that have been difficult to resolve and characterise. Analyses presented here suggest that the family members have arisen through a process of gene duplication, selection pressure and variation. Highly evolving genes tend to be located proximal to genetic elements that drive change rather than regions that support core gene conservation. For example, the virulence-associated P. falciparum erythrocyte membrane protein (PfEMP1) gene family members are restricted to relatively unstable sub-telomeric regions. In contrast the SICAvar and KIR genes are located throughout the genome but as the study presented here shows, they occupy otherwise gene-sparse chromosomal locations.The novel methods presented here offer the malaria research community new tools to generate comprehensive genome sequence data from small clinical samples and renewed insight into these complex real-world parasites.Author summaryMalaria is a potentially severe disease caused by parasite species within genus Plasmodium. Even though the number of cases is in decline there were over 200 million reported cases of malaria in 2019 that resulted in >400,000 deaths. Despite huge research efforts we still do not understand precisely how malaria makes some individuals very ill and by extension how to successfully augment and manage severe disease.Here we developed a novel method to generate comprehensive robust genome sequences from the malaria parasite Plasmodium knowlesi collected from clinical samples.We propose to use the method and initial data generated here to begin to build a resource to identify disease associated genetic traits of P. knowlesi taken from patient’s samples. In addition to the methodology, what further sets this work apart is the unique opportunity to utilize same-species experimental P. knowlesi parasites to discover a potential role for particular parasite traits in the differential disease progression we observe in patients with P. knowlesi malaria.While we developed the methods to study severe malaria, they are affordable and accessible, and offer the wider malaria research community the means to add context and insight into real-world malaria parasites.