The effect of sample size on estimates of genetic differentiation and effective population size for Schistosoma mansoni populations

Abstract Eradication or local extinction of the human parasite Schistosoma mansoni is a goal for many control programs. Population genetic analyses are helping to evaluate and guide these efforts, yet what to sample, how to sample and how densely to sample is not well established. We determined the S. mansoni allele frequency profile of nearly all infected inhabitants in two small Brazilian communities and created sub-samples representing 5–50% of all detected human infections (infrapopulations). Samples were selected at random with replacement, and each size class was replicated 100 times. Mean pairwise differentiation for all infrapopulations (Di) and the variance effective population size (Ne) were calculated for each sample. Prior to community-wide treatment, the true mean Di was moderate (0.095–0.123) and Ne large (>30,000). Most samples of 15% of all infrapopulations were required. At the 3 year follow-up after treatment, the Di increased and Ne was reduced by >15 fold. At this time sampling of >30–45% was needed to achieve the same accuracy. Following a second treatment and 4 years from baseline, the Di further increased and Ne decreased with little change in the sampling effort required. Extensive sampling is required for accurate estimates of these important population parameters. Characteristics such as population census size, infection prevalence, the community’s treatment history and the degree of infrapopulation differentiation should be taken into account. The intensity of infection was weakly correlated with the ability of a single infrapopulation to represent the component population (Dic), indicating a tendency toward random acquisition of parasite genotypes. This also suggests that targeted sampling from those most heavily infected will better represent the genetic diversity of the whole community than a random sample of infrapopulations.