musabase pag 2018
TRANSCRIPT
MUSABASE
Guillaume BauchetMueller lab
Plant and Animal Genome, San Diego, 2018
Musabase: A Phenotyping and Breeding
Database for Bananas
https://btiscience.org/lukas-mueller/#lab-members
Mueller lab
- Bioinformatics
- Genomics
- Databases
MUSABASE
+ 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
Project scope
Genomic Selection(Moses presentation)
But also:
-> Conventional breeding
-> Plant pathology
-> Parmer preferences
-> Germplasm Management
->Tissue culture
Project scope
Project scope
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!
=> Need for an “in situ” resource, a breeding information repository
The banana “digital ecosystem”
Ex situ conservation
Molecular data
Semantic data
Musabase
MUSABASE http://musabase.org/
MUSABASE
Field data collection: a demanding process…
MUSABASE
Field data collection: digitalize it!
Field data collection: digitalize it!
MUSABASE
Connecting dots between and within projects…
MUSABASE
Field
Lab
MGIS
Crop ontology
Field data collection: digitalize it!
MUSABASE
Barcoding
https://musabase.org/barcode
Field data collection: digitalize it!
MUSABASE
Ontologies: streamline management
http://submit.rtbbase.org/
Banana ontology Pipeline
Credits: EM-A Laporte, . Arnaud (Bioversity)
Field data collection: digitalize it!
MUSABASE
Ontologies: postcomposing
https://musabase.org/tools/composehttps://musabase.org/search/traits
Field data collection: digitalize it!
MUSABASE
Field geolocations
https://musabase.org/breeders/locations
Field data collection: digitalize it!
MUSABASE
Pedigree
David Lyon’s presentation
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)
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)
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/
-> 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
Connecting dots between and within projects…
MUSABASE
http://slideshare.net/solgenomicsField
Lab
MGIS
Crop ontology