Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Abstract

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum.

Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, inter-population differentiation, and the degree to which allele frequencies are correlated between populations.

Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Figure 1

Diversity at assayed SNPs (SNP π). (a) Nonsynonymous and silent SNP diversity by population. Significantly lower nonsynonymous SNP diversity (determined by bootstrapping) is indicated by asterisks: *P < 0.05; **P < 0.001; ***P < 0.0001. Error bars indicate 95% confidence intervals derived from bootstrapping. (b) SNP π on chromosome 7 for chloroquine resistant (red) and chloroquine sensitive (blue) samples. The disparity in diversity near 460 kb indicated with gray shading likely corresponds to a selective sweep associated with the pfcrt locus.

Figure 2

Maximum likelihood phylogeny of global samples. Blue, red, and green branches represent parasites from Asia, Africa, and the Americas, respectively. Parasites that were sequenced and thus were used for the discovery of SNPs are indicated by yellow diamonds. Nodes exhibiting bootstrap support levels of at least 50% or 90% are indicated by gray dots and black dots, respectively.

Figure 3

Nonsynonymous and silent divergence (F_ST). (a) Significantly greater nonsynonymous divergence (determined by bootstrapping) is indicated by asterisks: *P < 0.05; **P < 0.001; ***P < 0.0001. Error bars indicate 95% confidence intervals determined from bootstrapping. (b) Proportion of SNPs with significant Senegal versus Thailand F_ST (P < 0.05) controlling for average derived allele frequency in Senegal and Thailand.

Figure 4

Distribution of Thailand-Senegal divergence (F_ST), plotted separately for markers in low diversity (SNP π < 0.005) and high diversity (SNP π > 0.005) windows. Window size is 20 kb.

Figure 5

Derived allele frequency spectra in (a) Senegal and (b) Thailand. Bins exhibiting significant differences in frequency by Fisher's exact test between nonsynonymous and silent SNPs are indicated by asterisks: *P < 0.05).

Figure 6

Significance and count of excess nonsynonymous SNPs segregating at various disparities in frequency between Senegal and Thailand. Statistical significance was evaluated in relation to synonymous SNP counts using Fisher's exact test. Horizontal dotted line indicates a P-value threshold of 0.05.

Figure 7

Linkage disequilibrium, measured by r², for each of the four population samples: (a) Senegal; (b) Malawi; (c) Brazil; (d) Thailand. Plotted are the measured r² for linked markers (blue lines) and for unlinked markers (red lines), as well as the level of background LD expected because of small sample size (green lines).