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Abstract
Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3–4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.
Genomic surveillance of Plasmodium falciparum could improve monitoring of drug resistance, but implementation has been hampered due to the large and complex genome. Here, de Cesare et al. develop a flexible and cost-effective nanopore sequencing approach to detect drug resistance and diagnostic escape for P. falciparum malaria.
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1 University of Oxford, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, Oxford, UK (GRID:grid.270683.8) (ISNI:0000 0004 0641 4511)
2 PATH, Lusaka, Zambia (GRID:grid.270683.8)
3 National Malaria Elimination Centre, Chainama, Lusaka, Zambia (GRID:grid.270683.8)
4 Max Planck Institute for Infection Biology, Berlin, Germany (GRID:grid.418159.0) (ISNI:0000 0004 0491 2699)
5 Imperial College London, London, UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111)
6 Brown University, Department of Pathology and Laboratory Medicine and Center for Computational Molecular Biology, Providence, USA (GRID:grid.40263.33) (ISNI:0000 0004 1936 9094)
7 University of Oxford, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, Oxford, UK (GRID:grid.270683.8) (ISNI:0000 0004 0641 4511); Max Planck Institute for Infection Biology, Berlin, Germany (GRID:grid.418159.0) (ISNI:0000 0004 0491 2699)