Transcriptome analysis of the honey bee fungal pathogen, Ascosphaera apis: implications for host pathogenesis

Abstract

Abstract Background We present a comprehensive transcriptome analysis of the fungus Ascosphaera apis, an economically important pathogen of the Western honey bee (Apis mellifera) that causes chalkbrood disease. Our goals were to further annotate the A. apis reference genome and to identify genes that are candidates for being differentially expressed during host infection versus axenic culture. Results We compared A. apis transcriptome sequence from mycelia grown on liquid or solid media with that dissected from host-infected tissue. 454 pyrosequencing provided 252 Mb of filtered sequence reads from both culture types that were assembled into 10,087 contigs. Transcript contigs, protein sequences from multiple fungal species, and ab initio gene predictions were included as evidence sources in the Maker gene prediction pipeline, resulting in 6,992 consensus gene models. A phylogeny based on 12 of these protein-coding loci further supported the taxonomic placement of Ascosphaera as sister to the core Onygenales. Several common protein domains were less abundant in A. apis compared with related ascomycete genomes, particularly cytochrome p450 and protein kinase domains. A novel gene family was identified that has expanded in some ascomycete lineages, but not others. We manually annotated genes with homologs in other fungal genomes that have known relevance to fungal virulence and life history. Functional categories of interest included genes involved in mating-type specification, intracellular signal transduction, and stress response. Computational and manual annotations have been made publicly available on the Bee Pests and Pathogens website. Conclusions This comprehensive transcriptome analysis substantially enhances our understanding of the A. apis genome and its expression during infection of honey bee larvae. It also provides resources for future molecular studies of chalkbrood disease and ultimately improved disease management.