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Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - November 2015

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Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - November 2015

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Presenting the Integrated Breeding Platform (IBP) and the IBP Breeding Management System at the Symposium on Crop Breeding Databases, held by
the American Society of Agronomy (ASA), the Crop Science Society of America (CSSA) and the Soil Science Society of America (SSSA) for their Annual Meeting in Minneapolis.

Presenting the Integrated Breeding Platform (IBP) and the IBP Breeding Management System at the Symposium on Crop Breeding Databases, held by
the American Society of Agronomy (ASA), the Crop Science Society of America (CSSA) and the Soil Science Society of America (SSSA) for their Annual Meeting in Minneapolis.

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Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - November 2015

  1. 1. IBP Breeding Management System An Integrated Software Product to Manage a Modern Plant Breeding Program Mark Sawkins and IBP Team Symposium--Crop Breeding Databases 2015 Annual Meeting, 15-18 November 2015, Minneapolis
  2. 2. Outline  Introduction to the Integrated Breeding Platform (IBP)  The IB & Genotyping databases  IBP Breeding Management System (BMS)  Ontology Management System (OMS)  Linkage to other public crop breeding initiatives  BMS deployment strategy Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  3. 3. Integrated Breeding Platform (IBP)  Conceived during phase II of the Generation Challenge Programme (GCP)  Improve the efficiency of plant breeding programmes in developing countries  Enable plant breeders to access modern breeding technologies, breeding materials and related information in a centralised, integrated and practical manner  www.integratedbreeding.net Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  4. 4. Integrated Breeding Platform (IBP)  Software tools ◦ Breeding Management System (BMS)  Breeding services and products ◦ Genotyping Support Services (GSS) supporting first time users from developing country breeding programs; ◦ Trait and metabolite, drought phenotyping and other phenotyping services; ◦ Location analysis and climate resources online  Professional support ◦ Establishment of regional Hubs to support and promote use of IBP software and services. ◦ Breeding support; capacity building, social networks and Communities of Practice Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  5. 5. BMS Features Program & Information Management • WorkBench (dashboard view) • Study Browser • Breeder Queries • Ontology Manager (10 crops) • Germplasm Import Tool • Data Import Tool Breeding activities • Germplasm List Manager • Crossing Manager • Nursery Manager, with Seed Inventory • Trial Manager Statistical Analysis – Breeding View: • Single-Site Analysis • Multi-Site Analysis • Multi-Year Multi-Site Analysis; • Breeding View Standalone for QTL • Quality Assurance Marker-Assisted Breeding • Genotypic Data Management System (GDMS) • QTL Analysis Tools • Molecular Breeding Design Tool (MBDT) • OptiMAS
  6. 6. Integrated Breeding Database Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015  Genealogy Management System (GMS) ◦ Germplasm nomenclature, chronology, IP and passport data ◦ Pedigrees and breeding history  Phenotyping Data Management System (DMS) ◦ Germplasm characterization and evaluation data ◦ Annotated with Crop Research and Crop Trait Ontologies  Genotypic Data Management System (GDMS) ◦ Medium density fingerprinting data ◦ Genotyping data for MAS and MABC ◦ Genotyping data for Marker-trait association analysis
  7. 7. Integrated Breeding Database Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015  International Crop Information Database (ICIS) ◦ “open-source” “open-license” generic crop information system under development since the early 1990’s by researchers from CGIAR and non CGIAR partners  Review of ICIS in 2013 ◦ Current system suffers performance and complexity problems ◦ Current model is not intuitive ◦ Desire an optimum phenotyping database which meets user needs in the most efficient way  Initial mapping of sample problems to the Chado with ND extensions showed a good fit ◦ Natural Diversity Module is an extension to the Chado schema to better support natural diversity data (phenotypic)  Take an “additive approach” to table inclusion, no need to include all Chado tables
  8. 8. Integrated Breeding Database Details of the database at the foundation of the BMS: ICIS CHADO
  9. 9. Ontology Management System  Preloaded with crop, location and breeding ontologies  Elizabeth Arnaud and team at Bioversity  Customizable  Effort to streamline and reconcile the ontologies this year  Current crops ◦ Bean, Cassava, Chickpea, Cowpea, Groundnut, Maize, Rice, Sorghum, Soybean, and wheat.  Next Crops ◦ Yam, Pearl millet, Barley, Sunflower, Sweet potato, Oat  Future crops ◦ Cocoa, Coffee, forages, Musa, Potato, Tef... ...and “Your Crop” (Trait Dictionary template v5 (TDv5) Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  10. 10. IBP Breeding Management System (BMS)
  11. 11. BMS Workbench The Workbench offers access to multiple breeding programs and allows users to add and remove programs as required.
  12. 12. List Manager
  13. 13. Germplasm Search
  14. 14. Crossing Manager
  15. 15. Nursery Manager
  16. 16. Trial Manager
  17. 17. Technicians’ Training, Jan 2012, Bamako, Mali. Photo credit: A. Portugal (IBP). Support for electronic data capture  Field Book (Kansas State University)  KD Smart (Diversity Arrays)  FieldLab (IRRI)  .csv files
  18. 18. Breeding View – Statistical Analysis  Simple graphical Interface for phenotypic and genotypic analysis ◦ Single site ◦ G x E ◦ QTL detection  Choice of Genstat or R-scripts  Developed with partners at WUR and VSNi
  19. 19. Current Analysis Pipelines
  20. 20. Support for Marker Implementation  OptiMAS ◦ Developed at INRA, Le Moulon ◦ Implementation of markers in a MARS breeding scheme ◦ Identify and track favorable alleles through cycles of recombination and selection  Molecular Breeding Decision Tool (MBDT) ◦ Developed by team at ICRISAT ◦ Implementation of markers in a MAS and MABC context
  21. 21. Linking to other Plant Breeding Systems  Plant Breeding API (BRAPI) ◦ Definition of a standard API to be implemented by interested parties (http://docs.brapi.apiary.io/#) ◦ BMGF supported development of an open, shared Application Programming Interface (API) for crop breeding ◦ Facilitate data exchange among different initiatives ◦ Expand the range of tools available to IBP clients ◦ Reduce duplication of effort and support more efficient use of resources ◦ Contact Lukas Mueller lam87@cornell.edu Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  22. 22. Members of the collaboration BRAPI KDDart (Diversity Arrays Technology) BMS (IBP) Triticeae Toolbox (T-CAP) Cassavabase (Cornell/BTI) B4R (IRRI) Flapjack, Germinate (JHI) GOBI (Cornell) Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015 Other interested parties
  23. 23. BMS Deployment  In December 2014 an adoption strategy and roadmap was developed, including the establishment of regional hubs ◦ ESA (East and South Africa) ◦ WCA (West and Central Africa) ◦ SSA (South & South East Asia)  First BMS conversion started with the National Agricultural Research organization (NARO) Uganda in February 2015 Mark Sawkins’ presentation of the BMS ASA, CSSA, SSSA Annual Meetings – 15-18 November 2015
  24. 24. IBP Regional Hubs
  25. 25. For more information Licensing questions: Stewart Andrews (s.andrews@cgiar.org)
  26. 26. Credits
  27. 27. Thank you!

Editor's Notes

  •  - pink = ICIS
     - orange = CHADO
     - purple = new 2014/2015 (there’s a bit more purple there now since March)
     
    Large Data Volumes - Our database doesn’t scale well so we hold a deal of it in memory right now to achieve performance. The changes we need to make in this to improve this are in Ontology, Lists and Experiments (plots). This is the natural next step of the DB tuning. Small changes in the right places make a big difference.
    Reporting - In order for reporting to work - the Breeders Queries - at larger volumes we probably need to ‘publish’ studies and copy the data into differently shaped tables for quicker queries. This is fairly standard practice in most reporting DBs. This will, I hope, be OK to include for Version5, based on Jan Erik’s Road Map.
    Search - search is incredibly important for a system like ours and we are not sure the relational DB model is going to satisfy all the search capability we may need. We will be experimenting with other search engines as well to complement the basics in the current DB - again I hope this will fit into the V5 roadmap.

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