Selection and Association of Drug Resistance in Plasmodium falciparum Rachel A. Myers1, Kate M. McGee1, Jon Keebler1, Gilean A. T. McVean2, Xin‑zhuan Su3, Jianbing Mu3 and Philip Awadalla1 1Department of Genetics, North Carolina State University, Raleigh, NC 27695‑7614, USA. of Statistics, University of Oxford, Oxford OX1 3TG, UK. 3Department of Biology, Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, 12735 Twinbrook Parkway, Rockville, MD 20850, USA 2Deparment Results Introduction P. falciparum is the most lethal causative agent of malaria and, due to wide spread use of anti-malarials such as chloroquine, quinine, and Fansidar®, has developed drug resistance. Therefore it is of interest to identify currently selected loci and genes that may become targets due to roles in drug metabolism. Population Structure Figure 1: Inferred Population Structure using SNP data Selection and Association Figure 3: Summary of Selection and Association Results Objective Identify genes associated with resistance to 8 drugs: artemisinin (ART), atovaquonepruguanil (ATO), chloroquine (CQ), cycloguanil (CYCLO), halofantrine (HAL), sulfadoxine-pyrimethamine (FANS), mefloquine (MEF), and quinine (QN), and loci potentially subject to natural and artificial selection. Figure 1 Plots of the top 5 eigenvectors or axes of variation from the data. The top 2 axes separate the 3 continents with evidence of migration and gene flow between African and American populations. Due to strong geographical effects, the populations were analyzed individually for drug resistance associations. Figure 2: Inferred Population Structure using SSR data Methods Data K=3 • SNP data: Chromosome 3 and random gene polymorphisms in 99 isolates from 4 geographical locations • SSR data: genome wide microsatellites • Phenotype data: IC50 of 8 drugs, where IC50 is the concentration required for 50% inhibition LN [P(data)] = -59383.7 K=4 LN [P(data)] = -59243.5 K=5 Analysis LN [P(data)] = -59722.5 SNP + Phenotype data Inferred Population Structure (Figure 1) EIGENSOFT1,2 SNP Association Results (Figure 3) 10 neutral genes MLHKA 4 test of neutrality MLHKA results (Table 1, Figure 3) Phenotype SSR data χ2 test of Association Structure 23 SSR Association Results (Figure 3) Inferred Population Structure (Figure 2) Figure 2 At K = 3 the log likelihood plateaued and populations clustered roughly to geographic region with the exception of known migrates. Like the SNP data, the SSR’s were analyzed by population for associations. Discussion We detected 16 SNP associations in 6 different genes and 7 SSR associations. The multiple drug resistance gene (mdr1) and the putative chloroquine resistance transporter (pfcrt) have well documented roles in drug resistance were associated. Additionally several hypothetical genes were associated, suggesting putative roles in drug metabolism. mdr1 and pfcrt have been reported as the target of selective sweeps and evidence of decreased diversity from the MLHKA test at mdr1 agree with those reports. Conversely, the results of the MLHKA test indicate increased diversity at pfcrt, suggesting balancing selection. This suggests the locus was a target of historical balancing selection until the use of anti-malaria drugs. The associated hypothetical proteins also show evidence of balancing selection. Acknowledgements This work was funded in part by a NIEHS training grant in Bioinformatics Figure 3 SNPs and SSRs with permutation based Bonferroni corrected p values ≤ 0.05 were considered associated. McDonald Kreitman (MK) test of neutrality compares ratio of synonymous to non-synonymous polymorphisms within and between species. The MK results are from Jeffares et al, 2007. Table 1 Table 1 displays the results of the MLHKA test. MLHKA tests ratio of polymorphism to substitutions of neutral and selected genes.The p values were obtain using maximum likelihood ratio test comparing the null model of 0 selected genes to the alternative of 6 selected genes. K > 1 indicates diversity is maintained while K < 1 indicates diversity is lost. References 1.Patterson, N., Price, A.L., and Reich, D. (2006) Population Structure and Eigenanalysis. PLOS Genetics 2 (12): e190. 2.Price A.L. et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38 (8): 904-909. 3. Falush,D., Stephens, M., and Pritchard, J.K. (2003) Inference of population structure using multilocus genotype data. Genetics 155: 945-959. 4. Wright, S.I. and Charlesworth, B. (2004) MLHKA- A maximum likelihood ratio test of natural selection, using polymorphism and divergence data. Genetics 168: 10711076.
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