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!!!UPDATE!!!

Objective: Generate a prioritized list of candidate genes from a QTL region based on phenotype information.

Output: Semantic integration of plant genomic and phenotypic data to enable ranking of candidate genes associated with fruit ripening in tomatoes (Solanum lycopersicum).

Fig 1. Biological entities and data flow. TODO: Add potato graphs.

Platform: Virtuoso Universal Server (OSE). The installation and deployment instructions can be found here.

Data sources:

• Non-RDF sources

  • SGN: (wild) tomato genome annotations and genetic markers (detailed description here)

    • Solanum lycopersicum
    • Solanum pennellii

  • QTLs extracted from Europe PMC articles/tables.

• RDF sources

  • Ensembl Plants: tomato genome annotations (release 33)
  • UniProt: (reference) tomato proteome (release 2016_11)

• Database cross-references

  • Gramene
  • NCBI's Gene, UniGene, RefSeq and Taxonomy
  • ENA
  • STRING
  • Plant Reactome
  • InterPro database members
  • OMA, OrthoDB, eggNOG, InParanoid and KEGG (KO) orthology databases
  • PaxDb

Features:

• web-based Faceted Browser on Linked Data sets
  • (Google-like)Text Search (e.g. fruit quality, Myb 12, SGN-M6466)
  • Entity Label Lookup including genome, chromosome/location (chromosome 11), QTL (QTL:PMC4321030_4_1_54), trait (fruit ripening), genetic marker (variation gene231_0-i11), gene symbol/ID (gene Solyc11g008770.1), protein accession/ID (K4D5D7), GO term/ID (GO:0009835), pathway (carotenoid biosynthesis)
  • Entity URI Lookup (e.g. http://purl.obolibrary.org/obo/TO_0002728)
• programmatic data access via SPARQL endpoint including some example queries & output
• Docker-ized Virtuoso server to easy on premise deployment
• automated data ingest & reconciliation procedures, which can aid in future updates of the platform when new releases of data sources become available

Current issues & limitations

• see this list of open (or closed) issues
• making tomato SGN data (in GFF) and QTLs from literature (in CSV) available in RDF requires manual effort aided by OpenRefine and a custom script in Python
• (non-)RDF data quality & curation (e.g. some Ensembl links to other resources)
• data licensing & re-use by private partners

Possible extensions:

• couple the Linked Data platform with an algorithm(s) to score/rank (candidate) genes associated with the trait of interest
• web interface including data visualization tailored to domain scientists