Dissecting malaria biology and epidemiology using population genetics and genomics
- Journal Title
- Int J Parasitol
- Publication Type
- Journal Article in press
- Abstract
- Molecular approaches have an increasingly recognized utility in surveillance of malaria parasite populations, not only in defining prevalence and incidence with higher sensitivity than traditional methods, but also in monitoring local and regional parasite transmission patterns. In this review, we provide an overview of population genetic and genomic studies of human-infecting Plasmodium species, highlighting recent advances in the field. In accordance with the renewed impetus for malaria eradication, many studies are now using genetic and genomic epidemiology to support local evidence-based intervention strategies. Microsatellite genotyping remains a popular approach for both Plasmodium falciparum and Plasmodium vivax. However, with the increasing availability of whole genome sequencing data enabling effective single nucleotide polymorphism-based panels tailored to a given study question and setting, this approach is gaining popularity. The availability of new reference genomes for Plasmodium malariae and Plasmodium ovale should see a surge in similar molecular studies on these currently neglected species. Genomic studies are revealing new insights into important adaptive mechanisms of the parasite including antimalarial drug resistance. The advent of new methodologies such as selective whole genome amplification for dealing with extensive human DNA in low density field isolates should see genome-wide approaches becoming routine for parasite surveillance once the economic costs outweigh the current cost benefits of targeted approaches.
- Publisher
- Elsevier
- Research Division(s)
- Population Health And Immunity
- PubMed ID
- 27825828
- Publisher's Version
- https://doi.org/10.1016/j.ijpara.2016.08.006
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2016-11-14 11:36:17
Last Modified: 2016-11-17 11:26:01