In silico prediction of candidate gene targets for the management of African cassava whitefly (Bemisia tabaci, SSA1-SG1), a key vector of viruses causing cassava brown streak disease.

Whiteflies (Bemisia tabaci sensu lato) have a wide host range and are globally important agricultural pests. In Sub-Saharan Africa, they vector viruses that cause two ongoing disease epidemics: cassava brown streak disease and cassava mosaic virus disease. These two diseases threaten food security for more than 800 million people in Sub-Saharan Africa. Efforts are ongoing to identify target genes for the development of novel management options against the whitefly populations that vector these devastating viral diseases affecting cassava production in Sub-Saharan Africa. This study aimed to identify genes that mediate osmoregulation and symbiosis functions within cassava whitefly gut and bacteriocytes and evaluate their potential as key gene targets for novel whitefly control strategies. The gene expression profiles of dissected guts, bacteriocytes and whole bodies were compared by RNAseq analysis to identify genes with significantly enriched expression in the gut and bacteriocytes. Phylogenetic analyses identified three candidate osmoregulation gene targets: two α-glucosidases, SUC 1 and SUC 2 with predicted function in sugar transformations that reduce osmotic pressure in the gut; and a water-specific aquaporin (AQP1) mediating water cycling from the distal to the proximal end of the gut. Expression of the genes in the gut was enriched 23.67-, 26.54- and 22.30-fold, respectively. Genome-wide metabolic reconstruction coupled with constraint-based modeling revealed four genes (argH, lysA, BCAT & dapB) within the bacteriocytes as potential targets for the management of cassava whiteflies. These genes were selected based on their role and essentiality within the different essential amino acid biosynthesis pathways. A demonstration of candidate osmoregulation and symbiosis gene targets in other species of the Bemisia tabaci species complex that are orthologs of the empirically validated osmoregulation genes highlights the latter as promising gene targets for the control of cassava whitefly pests by in planta RNA interference.

What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species.

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.