A comparative genomics approach reveals a local genetic signature of Leishmania tropica in Morocco.

Abstract

In Morocco, cutaneous leishmaniasis (CL) caused by Leishmania (L.) tropica is an important health problem. Despite the high incidence of CL in the country, the genomic heterogeneity of these parasites is still incompletely understood. In this study, we sequenced the genomes of 14 Moroccan isolates of L. tropica collected from confirmed cases of CL to investigate their genomic heterogeneity. Comparative genomics analyses were conducted by applying the recently established Genome Instability Pipeline (GIP), which allowed us to conduct phylogenomic and principal components analyses (PCA), and to assess genomic variations at the levels of the karyotype, gene copy number, single nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs) variants. Read-depth analyses revealed a mostly disomic karyotype, with the exception of the stable tetrasomy of chromosome 31. In contrast, we identified important gene copy number variations across all isolates, which affect known virulence genes and thus were probably selected in the field. SNP-based cluster analysis of the 14 isolates revealed a core group of 12 strains that formed a tight cluster and shared 45.1 % (87 751) of SNPs, as well as two strains (M3015, Ltr_16) that clustered separately from each other and the core group, suggesting the circulation of genetically highly diverse strains in Morocco. Phylogenetic analysis, which compared our 14 L. tropica isolates against 40 published genomes of L. tropica from a diverse array of locations, confirmed the genetic difference of our Moroccan isolates from all other isolates examined. In conclusion, our results indicate potential regional variations in SNP profiles that may differentiate Moroccan L. tropica from other L. tropica strains circulating in endemic countries in the Middle East. Our report paves the way for future research with a larger number of strains that will allow correlation of diverse phenotypes (resistance to treatments, virulence) and origins (geography, host species, year of isolation) to defined genomic signals such as gene copy number variations or SNP profiles that may represent interesting biomarker candidates.