Genetic surveillance in the Greater Mekong Subregion and South Asia to support malaria control and elimination

Abstract

The use of parasite genetic data by National Malaria Control Programmes (NMCPs) is currently limited, and typically focused on specific genetic features or a small number of study sites. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS). By integrating simple sample collection procedures in the routine operations of public health facilities, GenRe-Mekong enables NMCPs to conduct large-scale surveillance project in endemic regions. Samples are processed by the SpotMalaria platform, which uses high-throughput technologies to produce a broad set of genotypes, including most known drug resistance markers, species markers and a genomic barcode. Through the application of heuristics based on published evidence, GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions that are used to map prevalence of resistance to multiple drugs. To date, GenRe-Mekong has worked with NMCPs in five countries, and with several large-scale research projects, processing 9,645 samples from clinical cases. The monitoring of resistance markers has been especially valuable for NMCPs tracking the recent rapid spread of DHA-piperaquine resistant parasites across the region. In Vietnam and Laos, data from GenRe-Mekong have provided novel knowledge about the spread of these resistant strains in provinces previously thought to be unaffected. GenRe-Mekong facilitates data sharing by aggregating at regional level results from different countries, providing cross-border views of the spread of resistant strains.

Mapping genetic markers of artemisinin resistance in Plasmodium falciparum malaria in Asia: a systematic review and spatiotemporal analysis

“…Large scale sample collections have been ongoing in the GMS during these years, which will contribute more K13 distribution data in the near future. 33 …”

“…We have included the list of articles used in this study in the appendix (pp 16–38 ). This publication uses data from the GenRe-Mekong Project, 33 which is funded by the Bill & Melinda Gates Foundation (OPP11188166, OPP1204268) and the SpotMalaria Project coordinated by the MalariaGEN Resource Centre with funding from Wellcome (206194, 090770). The authors would like to thank the staff of Wellcome Sanger Institute sample management, genotyping, sequencing, and informatics teams for their contribution.…”

Within-household clustering of genetically related Plasmodium falciparum infections in a moderate transmission area of Uganda

“…However, while the multiallelic, high-diversity nature of microsatellite loci has some advantages, this type of marker can be cumbersome to evaluate, particularly when considering larger numbers of loci to more accurately de ne relatedness between infections. Other genotyping techniques that are able to resolve multiallelic loci, such as multiplex amplicon or "microhaplotype" sequencing, can provide rich data from polyclonal infections and leverage current sequencing technologies to more easily allow evaluation of larger numbers of loci, providing higher resolution to evaluate transmission particularly in moderate-high transmission settings [25,[31][32][33][34]. While these methods are more expensive and require more extensive laboratory and bioinformatics structure than the methods used in this study, they may be preferred techniques in the future as sequencing costs continue to decline.…”

Within-Household Clustering of Genetically Related Plasmodium Falciparum Infections In A Moderate Transmission Area of Uganda

“…Other genotyping techniques that are able to resolve multiallelic loci, such as multiplex amplicon or "microhaplotype" sequencing, can provide rich data from polyclonal infections and leverage current sequencing technologies to more easily allow evaluation of larger numbers of loci, providing higher resolution to evaluate transmission particularly in moderate-high transmission settings. (25,(31)(32)(33)(34) While these methods are more expensive and require more extensive laboratory and bioinformatics structure than the methods used in this study, they may be preferred techniques in the future as sequencing costs continue to decline.…”