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Current Drug Targets - Infectious Disorders

Editor-in-Chief

ISSN (Print): 1568-0053
ISSN (Online): 1875-5852

QTL Analysis for Discovery of Genes Involved in Drug Responses

Author(s): Saunak Sen and Michael Ferdig

Volume 4, Issue 1, 2004

Page: [53 - 63] Pages: 11

DOI: 10.2174/1568005043480916

Price: $65

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 coevolved 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.

Keywords: malaria genetics, chloroquine, quinine, genomics


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