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

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, interpopulation 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.

We wish to thank all members of the sample collection team in Senegal (Ambroise Ahouidi, Lamine Ndiaye, Oumar Ly, Younouss Diedhiou, Theophile Sene, Amadou Mbaye and Dior Diop), and in Malawi (Terrie Taylor, Karl Seydel, Jacqui Montgomery, Edson Dembo, Malcolm Molyneux, and Stephen Rogerson), as well as all the patients and their families for allowing us to collect blood for the isolation of the parasite. We thank all the members of the Broad Sequencing Platform and the Affymetrix genotyping platform at the Broad. Thanks to Nira Mahesh and Gilberto Ramirez for help with sample preparation, and to Alejandro Miguel Katzin, Valnice de Jesus Peres, and Emilia AS Kimura for collection and culture-adaptation of parasites from Brazil. We thank MR4 for providing us with malaria parasites contributed by the following depositors: WE Collins (MRA-362); DE Kyle (MRA-159, MRA-176, MRA-202, MRA-204, MRA-205, MRA-206, MRA- 207, MRA-285); LH Miller and D Baruch (MRA-330); X Su (MRA-818, MRA-821, MRA-822); W Trager (MRA-733); D Walliker (MRA-151, MRA- 152, MRA-153, MRA-200); TE Wellems (MRA-155, MRA-156); and Y Wu (MRA-201). Special thanks to John Barnwell for providing P. reichenowi DNA. Our thanks to David Roos and the team at PlasmoDB [15] for access to the 3D7 genome sequence, and for help making the data available to the malaria community through the PlasmoDB resource. The authors are supported by a grant from the National Institutes of Health, SPARC funding of The Broad Institute of MIT and Harvard, the Burroughs-Wellcome Fund, The Bill and Melinda Gates Foundation, the NIAID Microbial Sequencing Center, the Ellison Medical Foundation, Fogarty International and the Exxon Mobil Foundation. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research Resources.