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Musabase PAG 2018

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Musabase breeding database overview at the Plant and Animal Genome (banana genomics session)

Publié dans : Données & analyses
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Musabase PAG 2018

  1. 1. MUSABASE Guillaume Bauchet Mueller lab gjb99@cornell.du Plant and Animal Genome, San Diego, 2018 Musabase: A Phenotyping and Breeding Database for Bananas
  2. 2. https://btiscience.org/lukas-mueller/#lab-members Mueller lab - Bioinformatics - Genomics - Databases MUSABASE
  3. 3. + University of Queensland, Australia + National Banana Breeding Program, India + University of Malaya, Malaysia Improvement of banana for smallholder farmers in the Great Lakes Region of Africa Projectscope
  4. 4. Genomic Selection (Moses presentation) But also: -> Conventional breeding -> Plant pathology -> Parmer preferences -> Germplasm Management ->Tissue culture Projectscope
  5. 5. Projectscope multiple data types… - Phenotyping experiments - Participatory trials - Farmer surveys - Tissue culture - Sequencing data …and a wealth of biological specificities! - Various ploidy levels - Germplasm groups - Complex pedigrees - Plant and field size - Life cycle length => different tools and approaches!
  6. 6. => Need for an “in situ” resource, a breeding information repository The banana “digital ecosystem” Ex situ conservation Molecular data Semantic data
  7. 7. Musabase MUSABASE http://musabase.org/
  8. 8. MUSABASE Field data collection: a demanding process…
  9. 9. MUSABASE Field data collection: digitalize it!
  10. 10. Field data collection: digitalize it! MUSABASE
  11. 11. Connecting dots between and within projects… MUSABASE Field Lab MGIS Crop ontology
  12. 12. Field data collection: digitalize it! MUSABASE Barcoding https://musabase.org/barcode
  13. 13. Field data collection: digitalize it! MUSABASE Ontologies: streamline management http://submit.rtbbase.org/ Banana ontology Pipeline Credits: EM-A Laporte, . Arnaud (Bioversity)
  14. 14. Field data collection: digitalize it! MUSABASE Ontologies: postcomposing https://musabase.org/tools/compose https://musabase.org/search/traits
  15. 15. Field data collection: digitalize it! MUSABASE Field geolocations https://musabase.org/breeders/locations
  16. 16. Field data collection: digitalize it! MUSABASE Pedigree David Lyon’s presentation
  17. 17. Field data collection: digitalize it! MUSABASE Surveys https://odk.ona.io/ -> Need for dynamic data collection processes -Farmer surveys -Field procedure (crosses) -Lab procedure (tissue culture)
  18. 18. Field data collection: digitalize it! MUSABASE Wish list + Crossing tool http://btract.sgn.cornell.edu/ https://musabase.org/breeders/crosses/ Credits: Margaret Karanja, Trushar Shah (IITA)
  19. 19. MUSABASE -> Link ex situ (MGIS) vs in situ (musabase) data -> Link additional molecular resources (genome hub, gobii) -> Additional tools for banana breeders Perspectives: reach the “digital ecosystem” https://brapi.org/
  20. 20. -> On site trainings -> Data managers MUSABASE Perspectives: keep building partnership Arusha Tanzania NARO Uganda IITA Uganda BTI Cornell -> Collaborations with Bioversity/Crop ontology colleagues + new partners
  21. 21. Connecting dots between and within projects… MUSABASE Questions? gjb99@cornell.edu http://slideshare.net/solgenomics Field Lab MGIS Crop ontology

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