SRA

Worldwide, 20-25% of all harvested fruit and vegetables are lost annually in the field and throughout the postharvest supply handling chain due to spoilage by fungal pathogens. Most impactful postharvest pathogens exhibit necrotrophic lifestyles, resulting in rotting of the host tissues and complete loss of marketable commodities. Necrotrophic fungi can readily infect ripe fruit leading to the rapid establishment of disease symptoms. However, these pathogens generally fail to infect unripe fruit, or remain quiescent until host and environmental conditions stimulate a successful infection. Current research on necrotrophic infections of fruit was mainly focused on the host by characterizing genetic and physicochemical factors that inhibit or promote the disease. However, the pathogenicity and virulence strategies employed by necrotrophic pathogens in ripe and unripe fruit are mostly understudied. Here, we provide a first comparative transcriptomics study of fungal postharvest pathogens: Botrytis cinerea, Rhizopus stolonifer and Fusarium acuminatum, all of which display necrotrophic behavior when infecting fruit. We de novo assembled and annotated the transcriptomes of R. stolonifer, and F. acuminatum and performed a differential gene expression analysis comparing the three fungal transcriptomes during fruit infection with that of fungal in-vitro growth. Analysis of the differentially expressed genes for enrichment of functional annotations revealed shared strategies of the three fungi during infection of compatible (ripe fruit) and incompatible (unripe fruit) hosts. We furthermore selected candidate genes that are involved in these strategies to characterize their expression during infection of unripe and ripe-like fruit of the non-ripening (nor) tomato mutant, both of which are physiologically and biochemically similar to unripe wildtype fruit. By enabling a better understanding of fungal necrotrophic infection  strategies, we move closer to generating accurate models of fruit diseases and development of early detection tools and effective management strategies. Overall design: Differential expression analysis of pathogen genes in green or red fruit compared to in vitro. Classification of differentially expressed genes by gene ontology, Pfam domains, and other functional categories.