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Trypanosomatidae are a dangerous family of Euglenobionta parasites that threaten the health and economy of millions of people around the world. More precisely describing the population biology and reproductive mode of such pests is not only a matter of pure science, but can also be useful for understanding parasite adaptation, as well as how parasitism, specialization (parasite specificity), and complex life cycles evolve over time. Studying this parasite's reproductive strategies and population structure can also contribute key information to the understanding of the epidemiology of associated diseases; it can also provide clues for elaborating control programs and predicting the probability of success for control campaigns (such as vaccines and drug therapies), along with emergence or re-emergence risks. Population genetics tools, if appropriately used, can provide precise and useful information in these investigations. In this paper, we revisit recent data collected during population genetics surveys of different Trypanosoma species in sub-Saharan Africa. Reproductive modes and population structure depend not only on the taxon but also on the geographical location and data quality (absence or presence of DNA amplification failures). We conclude on issues regarding future directions of research, in particular vis-à-vis genotyping and sampling strategies, which are still relevant yet, too often, neglected issues.

Background: Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (allelic dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright's FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and allelic dropouts are locus specific and likely produce high variance of Wright's FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex., Methods: We have performed various simulations of clonal and partially clonal populations. We introduce allelic dropouts and null alleles in clonal data sets and compare the results with those that exhibit increasing rates of sexual recombination. We use the narrow relationship that links Wright's FIS to genetic diversity in purely clonal populations as assessment criterion, since this relationship disappears faster with sexual recombination than with amplification problems of certain alleles., Results: We show that the relevance of our criterion for detecting poorly amplified alleles depends partly on the population structure, the level of homoplasy and/or mutation rate. However, the interpretation of data becomes difficult when the number of poorly amplified alleles is above 50%. The application of this method to reinterpret published data sets of pathogenic clonal microbes (yeast and trypanosomes) confirms its usefulness and allows refining previous estimates concerning important pathogenic agents., Conclusion: Our criterion of superimposing between the FIS expected under clonality and the observed FIS, is effective when amplification difficulties occur in low to moderate frequencies (20-30%).