Population Genetic Structure and Hybridization of Schistosoma haematobium in Nigeria

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Abstract

Background: Schistosomiasis is a major poverty-related disease caused by dioecious parasitic flatworms of the genus Schistosoma with a health impact on both humans and animals. Hybrids of human urogenital schistosome and bovine intestinal schistosome have been reported in humans in several of Nigeria’s neighboring West African countries. No empirical studies have been carried out on the genomic diversity of Schistosoma haematobium in Nigeria. Here, we present novel data on the presence and prevalence of hybrids and the population genetic structure of S. haematobium. Methods: 165 Schistosoma-positive urine samples were obtained from 12 sampling sites in Nigeria. Schistosoma haematobium eggs from each sample were hatched and each individual miracidium was picked and preserved in Whatman® FTA cards for genomic analysis. Approximately 1364 parasites were molecularly characterized by rapid diagnostic multiplex polymerase chain reaction (RD-PCR) for mitochondrial DNA gene (Cox1 mtDNA) and a subset of 1136 miracidia were genotyped using a panel of 18 microsatellite markers. Results: No significant difference was observed in the population genetic diversity (p > 0.05), though a significant difference was observed in the allelic richness of the sites except sites 7, 8, and 9 (p < 0.05). Moreover, we observed two clusters of populations: west (populations 1–4) and east (populations 7–12). Of the 1364 miracidia genotyped, 1212 (89%) showed an S. bovis Cox1 profile and 152 (11%) showed an S. haematobium cox1 profile. All parasites showed an S. bovis Cox1 profile except for some at sites 3 and 4. Schistosoma miracidia full genotyping showed 59.3% of the S. bovis ITS2 allele. Conclusions: This study provides novel insight into hybridization and population genetic structure of S. haematobium in Nigeria. Our findings suggest that S. haematobium x S. bovis hybrids are common in Nigeria. More genomic studies on both human- and animal-infecting parasites are needed to ascertain the role of animals in schistosome transmission.

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Detecting the number of clusters of individuals using the software structure: a simulation study

G Evanno, S. Regnaut, J Goudet (2005)

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

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Inference of Population Structure Using Multilocus Genotype Data

Jonathan Pritchard, Matthew Stephens, Peter Donnelly … (2001)

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.