Ocean Gene Atlas

Ocean Gene Atlas provides searchable mapping and visualization of gene biogeography in marine plankton by querying protein sequences, nucleotide sequences, or hidden Markov models against global ocean reference gene catalogs and linking hits to environmental metadata.

Key Features:

• Data integration: Integrates gene sequence catalogs from the European Nucleotide Archive (ENA), environmental context from PANGAEA, and gene abundance estimates derived by mapping sequence reads onto gene catalogs.
• Sequence similarity search: Uses BLAST and HMMER to identify homologs from user queries composed of nucleotide sequences, protein sequences, or hidden Markov models.
• Gene abundance estimation: Estimates gene abundances by mapping sequence reads onto reference gene catalogs.
• Visualization: Displays abundance and location of target sequences on world maps, shows taxonomic distribution, and overlays environmental features such as temperature and nutrient levels.
• Alignment filtering: Provides adjustable alignment quality cutoffs for filtering search results.
• Phylogenetic contextualization: Infers phylogenetic trees to situate user queries among environmental homologs and reference sequences.
• Reference datasets: Includes the Ocean Microbial Reference Gene Catalog (OM-RGC) comprising ~40 million non-redundant prokaryotic gene sequences associated with Tara Oceans and Global Ocean Sampling (GOS), and MATOU comprising over 116 million eukaryote unigenes.

Scientific Applications:

• Biogeography studies: Investigates spatial distribution patterns of genes across different oceanic regions.
• Environmental genomics: Correlates gene abundances with environmental parameters to study organismal and community responses to environmental variation.
• Microbial ecology: Explores microbial diversity and function using large marine gene catalogs such as OM-RGC and MATOU.

Methodology:

Performs sequence similarity searches with BLAST or HMMER using nucleotide sequences, protein sequences, or hidden Markov models; maps sequence reads onto gene catalogs to estimate gene abundances; applies alignment quality cutoffs for result filtering; and infers phylogenetic trees to contextualize homologs.