- Autores: Beraldi D, Blaxter M, Borges S, Cravo P, Creasey A, Fawcett R, Hunt P, Kumar S, Loewe L, Martinelli A, Modrzynska K, Otto TD, Pain A, Rodrigues L, Thomson M, Trivedi U
- Journal: BMC Genomics
- Link: http://www.ncbi.nlm.nih.gov/pubmed/?term=Experimental+evolution%2C+genetic+analysis+and+genome+re-sequencing+reveal+the+mutation+conferring+artemisinin+resistance+in+an+isogenic+lineage+of+malaria+parasites
Classical and quantitative linkage analyses of genetic crosses have traditionally been used to map genes of interest, such as those conferring chloroquine or quinine resistance in malaria parasites. Next-generation sequencing technologies now present the possibility of determining genome-wide genetic variation at single base-pair resolution. Here, we combine in vivo experimental evolution, a rapid genetic strategy and whole genome re-sequencing to identify the precise genetic basis of artemisinin resistance in a lineage of the rodent malaria parasite, Plasmodium chabaudi. Such genetic markers will further the investigation of resistance and its control in natural infections of the human malaria, P. falciparum.
A lineage of isogenic in vivo drug-selected mutant P. chabaudi parasites was investigated. By measuring the artemisinin responses of these clones, the appearance of an in vivo artemisinin resistance phenotype within the lineage was defined. The underlying genetic locus was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (Illumina Solexa) defined the point mutations, insertions, deletions and copy-number variations arising in the lineage. Eight point mutations arise within the mutant lineage, only one of which appears on chromosome 2. This missense mutation arises contemporaneously with artemisinin resistance and maps to a gene encoding a de-ubiquitinating enzyme.
This integrated approach facilitates the rapid identification of mutations conferring selectable phenotypes, without prior knowledge of biological and molecular mechanisms. For malaria, this model can identify candidate genes before resistant parasites are commonly observed in natural human malaria populations.