DiatOmicBase: a versatile gene‐centered platform for mining functional omics data in diatom research

• Published in: The Plant journal : for cell and molecular biology Vol. 121; no. 6; pp. e70061 - n/a
• Main Authors: Villar, Emilie, Zweig, Nathanaël, Vincens, Pierre, Cruz de Carvalho, Helena, Duchene, Carole, Liu, Shun, Monteil, Raphael, Dorrell, Richard G., Fabris, Michele, Vandepoele, Klaas, Bowler, Chris, Falciatore, Angela
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.03.2025; Wiley; John Wiley and Sons Inc
• Subjects: Annotations; Aquatic environment; Availability; Biochemistry, Molecular Biology; bioinformatics; Biotechnology; cell biology; Data analysis; data collection; Data Mining; Databases, Genetic; Datasets; diatoms; Diatoms - genetics; DNA methylation; ecotype variants; ecotypes; evolution; Experiments; gene expression regulation; gene models; Gene sequencing; genes; Genetic resources; Genome - genetics; genome browser; genome portal; Genomes; Genomics; histone marks; Histones; Life Sciences; Marine microorganisms; methylation; microalgae; Microbiology and Parasitology; Molecular Sequence Annotation; Network analysis; non‐coding RNAs; Phaeodactylum tricornutum; physiology; Plankton; protein domains; Proteomics; Quantitative Methods; Resource; Ribonucleic acid; RNA; RNA‐Seq datasets; sequence analysis; species; Thalassiosira pseudonana; Transcriptome - genetics; Transcriptomics; Thalassiosira pseudonana; ecotype variants; diatoms; RNA‐Seq datasets; Phaeodactylum tricornutum; genome portal; genome browser; gene models; histone marks; protein domains; non‐coding RNAs; RNA-Seq datasets; noncoding RNAs
• ISSN: 0960-7412; 1365-313X; 1365-313X
• DOI: 10.1111/tpj.70061

SUMMARY Diatoms are prominent microalgae found in all aquatic environments. Over the last 20 years, thanks to the availability of genomic and genetic resources, diatom species such as Phaeodactylum tricornutum and Thalassiosira pseudonana have emerged as valuable experimental model systems for exploring topics ranging from evolution to cell biology, (eco)physiology, and biotechnology. Since the first genome sequencing projects initiated more than 20 years ago, numerous genome‐enabled datasets have been generated, based on RNA‐Seq and proteomics experiments, epigenomes, and ecotype variant analysis. Unfortunately, these resources, generated by various laboratories, are often in disparate formats and challenging to access and analyze. Here we present DiatOmicBase, a genome portal gathering comprehensive omics resources from P. tricornutum and T. pseudonana to facilitate the exploration of dispersed public datasets and the design of new experiments based on the prior‐art. DiatOmicBase provides gene annotations, transcriptomic profiles and a genome browser with ecotype variants, histone and methylation marks, transposable elements, non‐coding RNAs, and read densities from RNA‐Seq experiments. We developed a semi‐automatically updated transcriptomic module to explore both publicly available RNA‐Seq experiments and users' private datasets. Using gene‐level expression data, users can perform exploratory data analysis, differential expression, pathway analysis, biclustering, and co‐expression network analysis. Users can create heatmaps to visualize pre‐computed comparisons for selected gene subsets. Automatic access to other bioinformatic resources and tools for diatom comparative and functional genomics is also provided. Focusing on the resources currently centralized for P. tricornutum, we showcase several examples of how DiatOmicBase strengthens molecular research on diatoms, making these organisms accessible to a broad research community. Significance Statement In recent years, diatoms have become the subject of increasing interest because of their ecological importance and their biotechnological potential for natural products such as pigments and polyunsaturated fatty acids. Here, we present an interactive web‐based server that integrates public diatom omics (genomics, transcriptomics, epigenomics, proteomics, sequence variants) data to connect individual diatom genes to broader‐scale functional processes.