Abstract
The genus Ceratocystis includes many phytopathogenic fungi that affect different plant species. One of these is Ceratocystis cacaofunesta, which is pathogenic to the cocoa tree and causes Ceratocystis wilt, a lethal disease for the crop. However, little is known about how this pathogen interacts with its host. The knowledge and identification of possible genes encoding effector proteins are essential to understanding this pathosystem. The present work aimed to predict genes that code effector proteins of C. cacaofunesta from a comparative analysis of the genomes of five Ceratocystis species available in databases. We performed a new genome annotation through an in-silico analysis. We analyzed the secretome and effectorome of C. cacaofunesta using the characteristics of the peptides, such as the presence of signal peptide for secretion, absence of transmembrane domain, and richness of cysteine residues. We identified 160 candidate effector proteins in the C. cacaofunesta proteome that could be classified as cytoplasmic (102) or apoplastic (58). Of the total number of candidate effector proteins, 146 were expressed, presenting an average of 206.56 transcripts per million. Our database was created using a robust bioinformatics strategy, followed by manual curation, generating information on pathogenicity-related genes involved in plant interactions, including CAZymes, hydrolases, lyases, and oxidoreductases. Comparing proteins already characterized as effectors in Sordariomycetes species revealed five groups of protein sequences homologous to C. cacaofunesta. These data provide a valuable resource for studying the infection mechanisms of these pathogens in their hosts.