title: QTL analysis for discovery of genes involved in drug responses.
abstract: The completed Plasmodium falciparum genome sequence poses a significant challenge: how do we bring this wealth of data to bear against the steady march of malaria parasites towards multiple-drug resistance? Studies of parasite drug resistance have until now focused on a qualitative, single-gene concept of resistance determination; however, the emergence of powerful genomics tools insists that these questions be rephrased. It is now possible to address the true genetic complexity underlying quantitative drug sensitivities. Quantitative trait loci (QTL) mapping is an effective tool for tracking multi-gene traits by partitioning genetic effects that influence these traits into specific genomic regions. A cross between two parasite clones captures allele combinations that have segregated into progeny clones that display varying sensitivity to drugs. The specific allele forms and their combinations contributed by each parent are, in effect, genetic signatures of their unique evolutionary histories. In addition to resistance genes, per se, a drug resistant parasite carries co-evolved gene combinations comprising a genetic background of drug resistance. Research into drug resistance necessarily has been directed at specific genes and mechanisms favored by a priori knowledge and assumptions about how resistance works. QTL mapping, by superimposing real biological phenotypes on genome sequence, structural polymorphisms, and gene expression data, can provide an alternative, unbiased view of the network of gene actions that build a complex phenotype. Through an integrated approach, studies can move beyond the search for markers of resistance to instead characterize the predisposition of parasites to develop new resistances and cross-resistances.
authors.affiliation: University of California San Francisco, Department of Epidemiology and Biostatistics, San Francisco, CA 94143-0560, USA.
authors.forename: Saunak
authors.initials: S
authors.lastname: Sen
authors.forename: Michael
authors.initials: M
authors.lastname: Ferdig
mesh_terms: D000483:Alleles; D000818:Animals; D005075:Biological Evolution; D002738:Chloroquine / Q000494:pharmacology; D002874:Chromosome Mapping; D015195:Drug Design; D004351:Drug Resistance / Q000235:genetics*; D018432:Drug Resistance, Multiple / Q000235:genetics; D015870:Gene Expression; D005796:Genes; D018503:Genome, Protozoan; D023281:Genomics; D006801:Humans; D016778:Malaria, Falciparum / Q000188:drug therapy / Q000235:genetics*; D011110:Polymorphism, Genetic; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D011803:Quinine / Q000494:pharmacology
chemical_list: D002738:Chloroquine; D011803:Quinine