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HoloFood Data Portal: holo-omic datasets for analysing host-microbiota interactions in animal production
Alexander B Rogers1, Varsha Kale1, Germana Baldi1
1European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK.
Database : the Journal of Biological Databases and Curation
|January 11, 2025
Summary
The HoloFood project studied host-microbiota interactions in salmon and chicken using multiomic data. A new data portal simplifies access to these complex datasets for improved research.
Area of Science:
- Animal Production
- Microbiome Research
- Bioinformatics
Background:
- Host-microbiota interactions significantly impact animal production efficiency.
- Analyzing multiomic data and metadata presents challenges due to data diversity and complexity.
- Previous data accessibility was fragmented across multiple public repositories.
Purpose of the Study:
- To investigate the impact of host-microbiota interactions on salmon and chicken production using a hologenomic approach.
- To develop a centralized data resource simplifying access to complex, multi-repository datasets.
- To provide a model for future multiomics data accessibility.
Main Methods:
- Analysis of multiomic data, phenotypic characteristics, and metadata from salmon and chicken.
- Integration of data from public archives (BioSamples, ENA, MetaboLights, MGnify).
- Development of the HoloFood Data Portal for streamlined data retrieval.
Main Results:
- The HoloFood Data Portal provides unified access to multiomic and phenotypic data linked to host-microbiota samples.
- Project-specific metagenome-assembled genomes and viral catalogues are available.
- The portal facilitates easier access to derived analyses and associated metadata.
Conclusions:
- The HoloFood Data Portal effectively simplifies access to complex, multi-repository datasets.
- This approach enhances the usability of multiomic data for studying host-microbiota interactions in animal production.
- The portal serves as a valuable model for future data integration and accessibility in biological research.
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