FungiDB (fungidb.org) is a free online resource for data mining and functional genomics analysis for fungal and oomycete species. FungiDB is part of the Eukaryotic Pathogen Genomics Database Resource (EuPathDB, eupathdb.org) platform that integrates genomic, transcriptomic, proteomic, and phenotypic datasets, and other types of data for pathogenic and nonpathogenic, free-living and parasitic organisms. FungiDB is one of the largest EuPathDB databases containing nearly 100 genomes obtained from GenBank, Aspergillus Genome Database (AspGD), The Broad Institute, Joint Genome Institute (JGI), Ensembl, and other sources. FungiDB offers a user-friendly web interface with embedded bioinformatics tools that support custom in silico experiments that leverage FungiDB-integrated data. In addition, a Galaxy-based workspace enables users to generate custom pipelines for large-scale data analysis (e.g., RNA-Seq, variant calling, etc.). This review provides an introduction to the FungiDB resources and focuses on available features, tools, and queries and how they can be used to mine data across a diverse range of integrated FungiDB datasets and records.

Environmental conditions profoundly affect plant disease development; however, the underlying molecular bases are not well understood. Here we show that elevated temperature significantly increases the susceptibility of Arabidopsis to Pseudomonas syringae pv. tomato (Pst) DC3000 independently of the phyB/PIF thermosensing pathway. Instead, elevated temperature promotes translocation of bacterial effector proteins into plant cells and causes a loss of ICS1-mediated salicylic acid (SA) biosynthesis. Global transcriptome analysis reveals a major temperature-sensitive node of SA signalling, impacting ~60% of benzothiadiazole (BTH)-regulated genes, including ICS1 and the canonical SA marker gene, PR1. Remarkably, BTH can effectively protect Arabidopsis against Pst DC3000 infection at elevated temperature despite the lack of ICS1 and PR1 expression. Our results highlight the broad impact of a major climate condition on the enigmatic molecular interplay between temperature, SA defence and function of a central bacterial virulence system in the context of a widely studied susceptible plant–pathogen interaction.

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions.

Summary Nannochloropsis oceanica is an oleaginous microalga rich in ω3 long‐chain polyunsaturated fatty acids (LC‐PUFAs) content, in the form of eicosapentaenoic acid (EPA). We identified the enzymes involved in LC‐PUFA biosynthesis in N. oceanica CCMP1779 and generated multigene expression vectors aiming at increasing LC‐PUFA content in vivo. We isolated the cDNAs encoding four fatty acid desaturases (FAD) and determined their function by heterologous expression in S. cerevisiae. To increase the expression of multiple fatty acid desaturases in N. oceanica CCMP1779, we developed a genetic engineering toolkit that includes an endogenous bidirectional promoter and optimized peptide bond skipping 2A peptides. The toolkit also includes multiple epitopes for tagged fusion protein production and two antibiotic resistance genes. We applied this toolkit, towards building a gene stacking system for N. oceanica that consists of two vector series, pNOC‐OX and pNOC‐stacked. These tools for genetic engineering were employed to test the effects of the overproduction of one, two or three desaturase‐encoding cDNAs in N. oceanica CCMP1779 and prove the feasibility of gene stacking in this genetically tractable oleaginous microalga. All FAD overexpressing lines had considerable increases in the proportion of LC‐PUFAs, with the overexpression of Δ12 and Δ5 FAD encoding sequences leading to an increase in the final ω3 product, EPA.

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