Abstract
Author(s): Lo, E; Bonizzoni, M; Hemming-Schroeder, E; Ford, A; Janies, DA; James, AA; Afrane, Y; Etemesi, H; Zhou, G; Githeko, A; Yan, G | Abstract: Single nucleotide polymorphisms (SNPs) have been shown to be useful in revealing population structure with continental-and regional-scale samples. In epidemiological study, a careful selection of SNPs to track disease spread in local communities would provide an important addition to traditional disease surveillance. This study used SNPs and microsatellites to examine population structure of Plasmodium falciparum at fine- scale in malaria-endemic areas of Western Kenya. A set of high performance (HP) SNPs were selected from a large SNP panel based on BELS ranking, FST values and minor allele frequency criteria. The discriminative power and assignment accuracy of different SNP panels including nonsynonymous SNPs, silent SNPs, previously published barcode SNPs, and the HP SNPs were evaluated together with microsatellites. Among all SNP panels, HP SNPs showed the highest level of differentiation and self-assignment accuracy on average among sites. Clear distinction was observed between the northern and southern P. falciparum samples, whereas samples from the south were least diverged from one another. These results were comparable to those by microsatellites. Nonsynonymous, silent, and barcode SNPs all showed similar levels of genetic variability to one another and weaker structure than the HP SNPs. We described here the procedure of selecting a set of HP SNPs from a large panel of SNPs that resolve population structure of P. falciparum between the northern and southern regions of Western Kenya. Future work is needed to determine if this procedure can result in SNPs panels capable of tracing Plasmodium spread at finer geographical scales.
Highlights
Single nucleotide polymorphisms (SNPs) are increasingly popular in population genetic studies due to their high number, low cost and ease of scoring, in addition to their rapid discovery rate by the advent of technology and analytical algorithm
Eighty-two of the 96 genotyped SNP loci produced a call rate of >95% and were highly concordant among duplicated samples in independent runs. Genotypes of these 82 SNPs were scored with confidence across samples, and they exhibited a wide distribution of minor allele frequencies (MAF) from rare (MAF < 10%) to common (MAF > 40%) with an average of 30.7% (Table 1, Supplementary File 2)
No significant linkage disequilibrium was detected among the nine tested microsatellite loci
Summary
Single nucleotide polymorphisms (SNPs) are increasingly popular in population genetic studies due to their high number, low cost and ease of scoring, in addition to their rapid discovery rate by the advent of technology and analytical algorithm. Knowledge of P. falciparum malaria dispersion patterns at both global and local scales is important to targeting control efforts at epidemic hotspots This in part relies on the application of powerful and effective molecular markers and analytical tools to track pathogen spread and origin. High throughput analytical platforms have been used successfully to assess and discover SNPs in P. falciparum (Mu et al, 2007; Volkman et al, 2007; Neafsey et al, 2008) These studies provided remarkable biological insights on the global genetic structure of the pathogen, the recombination rates and arrangements of the genome (Mu et al, 2005), as well as genome-wide search for association with antimalarial drug resistance (Anderson et al, 2005; Mu et al, 2007; AmambuaNgwa et al, 2012). The growing amount of SNP data deposited in databases such as PlasmoDB (Bahl et al, 2003) and dbSNP at the National Center for Biotechnology Information (NCBI) are powerful resources for selecting and applying SNPs in population studies
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