The recently identified kelch13 gene is an important marker of artemisinin resistance (ART-R) in malaria and has been linked to the slow-clearance rate (CR) clinical phenotype as well as treatment failures. In spite of this exciting discovery of a major gene affecting the trait, there are several indications that additional (or alternative) genes and gene interactions contribute to both the level of resistance, as measured by slow clearance times in the clinic and ring stage survival in the laboratory. Understanding the detailed functional role of various kelch13 mutants, their broader biological roles and functional partners, and their impact on fitness presents strategic hurdles to understanding and slowing the evolution and spread of ART-R. Recognizing that the phenotypic effect of a major resistance gene resides in a co-evolved whole-genome context, we will use quantitative trait locus (QTL) mapping combined with intensive and precise phenotyping across a set of eight inter-related experimental crosses constructed using our novel FRG huHep/huRBC mice We will use this that determine resistance and/or susceptibility to artemisinin and to partner drugs such as piperaquine and lumefantrine and to identify drug targets and susceptibility determinants for a wide range of compounds. In addition, we will examine the relationship between levels of ART-R and competitive growth in RBCs as a surrogate measure of fitness to identify the factors that will influence the spread of malarial resistance in African populations. to dissect this biological complexity. approach to find genes and pathways To identify the genes and pathways that influence the origins and spread of resistance we will (i) map the genetic determinants of ART-R to test our hypothesis that a complex genetic architecture and multiple genes are involved in ART-R, (ii) map genetic determinants of susceptibility to 24 antimalarial drugs, including the partner drugs of ART, piperiquine, along with antimalarial drugs targeting a wide range of biological processes and a set of candidate drugs for which the drug target is not known and, (iii) map the impact of ART-R on competitive growth using small volume head-to-head competitive-growth outcomes to compute a `relative fitness index' quantitative score for QTL mapping.
