Genome Dynamics during Environmental Adaptation Reveal Strain-Specific Differences in Gene Copy Number Variation, Karyotype Instability, and Telomeric Amplification.

Protozoan parasites of the genus adapt to environmental change through chromosome and gene copy number variations. Only little is known about external or intrinsic factors that govern genomic adaptation. Here, by conducting longitudinal genome analyses of 10 new clinical isolates, we uncovered important differences in gene copy number among genetically highly related strains and revealed gain and loss of gene copies as potential drivers of long-term environmental adaptation in the field.

Genetic diversity and structure in Leishmania infantum populations from southeastern Europe revealed by microsatellite analysis.

Background: The dynamic re-emergence of visceral leishmaniasis (VL) in south Europe and the northward shift to Leishmania-free European countries are well-documented. However, the epidemiology of VL due to Leishmania infantum in southeastern (SE) Europe and the Balkans is inadequately examined. Herein, we aim to re-evaluate and compare the population structure of L.

Multilocus microsatellite typing (MLMT) of strains from Turkey and Cyprus reveals a novel monophyletic L. donovani sensu lato group.

Background: New foci of human CL caused by strains of the Leishmania donovani (L. donovani) complex have been recently described in Cyprus and the Çukurova region in Turkey (L. infantum) situated 150 km north of Cyprus.

The paraphyletic composition of Leishmania donovani zymodeme MON-37 revealed by multilocus microsatellite typing.

Multilocus microsatellite typing (MLMT) was employed to compare strains of Leishmania donovani belonging to the MON-37 zymodeme (MON-37 strains) from Cyprus and Israel to MON-37 strains from the Indian subcontinent, the Middle East, China and East Africa as well as strains of other zymodemes. The MLMT data were processed with a distance-based method for construction of phylogenetic trees, factorial correspondence analysis and a Bayesian model-based clustering algorithm. All three approaches assigned the MON-37 strains to different distantly related genetically defined subgroups, corresponding to their geographical origin.