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Zusammenfassung:
The Phaeoexplorer project aims to generate annotated genome assemblies and transcriptome data for a broad range of brown algal species to address key questions about their biology and evolutionary history. More than 60 genomes of brown algae and closely-related sister species have been sequenced to date. To provide the community with a collaborative hub for accessing, visualizing and analyzing the brown algal genome and transcriptome resources, we have developed a web portal using the Django framework (https://phaeoexplorer.sb-roscoff.fr) to house the annotated genome sequences along with a broad range of associated resources. These resources include an integrated environment based on the Galaxy Genome Annotation project dedicated to the management and visualization of genomic data through user-friendly interfaces (including JBrowse genome browsers), deployed in an automated way with a set of custom Python tools [1] (https://gitlab.sb-roscoff.fr/abims/e-infra/gga_load_data). Other resources include information about the sequenced strains; assembly and annotation metrics; data download facilities; SequenceServer [2] BLAST facilities, deployed with an Ansible role (https://galaxy.ansible.com/abims_sbr/sequenceserver) and a R Shiny web application designed to explore RNAseq data of the model alga Ectocarpus (https://rnaseqaggregator.sb-roscoff.fr/ectocarpus). Over the next few months, we plan to extend the Phaeoexplorer database with additional resources (experimental protocols, genomes of associated bacterial symbionts and a Genomicus-based [3] comparative genomics resource). Still partially restricted, in the long term, the objective is for the Phaeoexplorer database to be a user-friendly public access point to brown algal genomes for the entire phycology community, with regular genome releases. In the future, similar databases will be implemented for red algae and fungi; and, within the context of the European Reference Genome Atlas project and other future large genome sequencing programs, in partnership with the BIPAA/Genouest and the SeBiMER/Ifremer bioinformatics platforms, we plan to further automate and scale up the omics data integration pipeline.
