Generación de una base de datos de genes involucrados en la resistencia y tolerancia del banano ante la infección por la Sigatoka Negra como instrumento para el control de enfermedades

Abstract

The climate crisis makes the establishment of crop diseases more common, such as Black Leaf Streak caused by the fungus Pseudocercospora fijiensis, which causes around $500 million in losses worldwide annually in banana crops. The measures currently taken are not viable in the long term, so other alternatives with new technologies should be chosen. The project aims to develop a database with genes for resistance and/or tolerance of banana (M. acuminata) to Black Sigatoka disease (P. fijiensis) through a transcriptomic analysis between a tolerant cultivar (Tuu Gia) and another susceptible (Williams) to the pathogen for disease control. The approach is purely bioinformatic, so sequenced cDNA from a previous biological assay was used as raw material. They went through pre-eliminary analysis and then differential expression analysis to obtain a list of genes that went through comparative analysis with rice to identify homologues. Finally, genes responsible for resistance were chosen by enrichment analysis. About 25 tolerance and/or resistance genes were found. Genes with this feature are expressed even before infection. The MAPK metabolic pathway and the genetic families of WRKY, AP2/EREBP, GST, among others, predominate. There is a fluctuation of the overrepresentation of genetic families at each time post- infection sampled. It is concluded that the development of the resistance gene database could be accomplished using bioinformatics.