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Background Human cutaneous leishmaniasis caused by Leishmania (Viannia) braziliensis is highly prevalent in the Peruvian jungle, where it affects military forces deployed to fight against drug trafficking and civilian people that migrate from the highland to the lowland jungle for economic activities such as mining, agriculture, construction, and chestnut harvest. We explored the genetic diversity and population structure of 124 L . (V . ) braziliensis isolates collected from the highland (Junín, Cusco, and Ayacucho) and lowland Peruvian jungle (Loreto, Ucayali, and Madre de Dios). All samples were genotyped using Multilocus Microsatellite Typing (MLMT) of ten highly polymorphic markers. Principal findings High polymorphism and genetic diversity were found in Peruvian isolates of L . (V . ) braziliensis . Most markers are not in Hardy-Weinberg equilibrium; this deviation is most likely caused by local inbreeding, as shown by the positive F IS values. Linkage Disequilibrium in subpopulations was not strong, suggesting the reproduction was not strictly clonal. Likewise, for the first time, two genetic clusters of this parasite were determined, distributed in both areas of the Peruvian jungle, which suggested a possible recent colonization event of the highland jungle from the lowland jungle. Conclusions L . (V . ) braziliensis exhibits considerable genetic diversity with two different clusters in the Peruvian jungle. Migration analysis suggested a colonization event between geographical areas of distribution. Although no human migration was observed at the time of sampling, earlier displacement of humans, reservoirs, or vectors could have been responsible for the parasite spread in both regions. 

An approach to the coalescent, the fractional coalescent (f-coalescent), is introduced. The derivation is based on the discrete-time Cannings population model in which the variance of the number of offspring depends on the parameter α. This additional parameter α affects the variability of the patterns of the waiting times; values of $\alpha <1$lead to an increase of short time intervals, but occasionally allow for very long time intervals. When $\alpha =1$, the f-coalescent and the Kingman’s n-coalescent are equivalent. The distribution of the time to the most recent common ancestor and the probability that n genes descend from m ancestral genes in a time interval of length T for the f-coalescent are derived. The f-coalescent has been implemented in the population genetic model inference software Migrate. Simulation studies suggest that it is possible to accurately estimate α values from data that were generated with known α values and that the f-coalescent can detect potential environmental heterogeneity within a population. Bayes factor comparisons of simulated data with $\alpha <1$and real data (H1N1 influenza and malaria parasites) showed an improved model fit of the f-coalescent over the n-coalescent. The development of the f-coalescent and its inclusion into the inference program Migratefacilitates testing for deviations from the n-coalescent.