COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data

Abstract

BackgroundComplex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays.MethodsCOIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample.ResultsCOIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples.ConclusionsThe capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.Electronic supplementary materialThe online version of this article (doi:10.1186/1475-2875-14-4) contains supplementary material, which is available to authorized users.

Genetic relatedness analysis reveals the cotransmission of genetically related Plasmodium falciparum parasites in Thiès, Senegal

“…These pseudohaplotypes are actually conservative representations of genetic similarity because they underestimate the true similarity between genomes when the polygenomic infection is composed of more than two strains. During the sampling timeframe and setting in Thiès, Senegal, the average complexity of infection (COI) in polygenomic infections is two [22], and the pseudohaplotypes reflect the genetic similarity of the genomes.…”

“…A polygenomic infection was simulated by drawing two random sets of SNPs from the full set of 3132, where each set of SNPs represents one of a pair of genomes in a superinfection. We assumed pairs of genomes because the average number of unique strains in our sample of polygenomic infections is two [22]. …”

“…We previously published a method for estimating the COI of polygenomic infections based on a set of biallelic SNP markers [22]. Our method, known as COIL, assumes that polygenomic infections are composed of unrelated parasite strains, which we now know is not always the case in natural populations.…”

The utility of genomic data forPlasmodium vivaxpopulation surveillance

“…This approach relies on a termination threshold e; it does not report any strain that might be present in a ratio smaller than e. Finally, COI can be estimated from a set of SNP markers using COIL. 60 This approach uses a Bayesian approach to estimate the likelihood of distinct COI based on molecular barcode data. 60 Identification and application of markers of the status of these populations will enable a better understanding of the changing population genetics and ultimately lead to better strategies and more effective distribution of limited resources in the global effort to eradicate malaria.…”

Within-infection diversity ofPlasmodium falciparumantigens reflects host-mediated selection

“…Multi-lineage P. falciparum infections are commonly characterized using small panels of putatively neutral SNPs [29], microsatellite markers [30], or size-length polymorphisms [31,32]. These approaches can quantify the number of clonal lineages within an infection [33,34], but are of limited use for understanding the mechanics of within-host selection. Whole genome shotgun sequencing has begun to provide information at the nucleotide level [35][36][37], but the predominance of host DNA in clinical samples limits the depth of parasite genome sampling.…”