in Plasmodium falciparum

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.