Automation of bioinformatic tools to detect gene fusion events in the Leishmania braziliensis and Leishmania major genomes

This work tried to identify gene fusion events in the genome of Leishmania major and Leishmania braziliensis based on computational processes using bioinformatics tools, designing and implementing a protocol that allowed the automation in the identification process. The project was justified in the actual need to find therapeutic targets to generate new alternative treatment for leishmaniasis. Methodologically, the paper uses comparative genomics tools using two databases, FusionDB and Domain Fusion. The fused genes of these two databases were aligned against the complete genomes of both species of Leishmania implementing the Inparanoid algorithm with a 50% value of coverage. A total of 75 possible gene fusion events, 41 were duplication events after the speciation of organisms, 4 were bifunctional genes and the rest were false positives. These results served to check the validity of the method, giving clues about the nature of gene fusion events in Leishmania and serve the community to use the computer protocol as a tool that can be applied or extrapolated to other microorganisms.