Adoption of modern breeding tools in developing countries: challenges and opportunities – J-M Ribaut

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Presentation by the GCP Director at an international workshop on genomics and integrated breeding, February 2014. More on the workshop: http://bit.ly/MwpliD You can also view the presentation on video here: http://bit.ly/1mVmVdS

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Adoption of modern breeding tools in developing countries: challenges and opportunities – J-M Ribaut

  1. 1. Jean-Marcel Ribaut 4th International Workshop on Next Generation Genomics and Integrated Breeding for Crop Improvement February 21, 2014 ICRISAT, Patancheru, India Adoption of modern breeding tools in developing countries: Challenges and Opportunities
  2. 2. Our Discussion Today: ♦ The human expertise ♦ Infrastructure ♦ Access to information and technology ♦ Data Management ♦ Labs and genomic resources ♦ Analytical tools and pipeline ♦ Support tools ♦ Social network ♦ Mindset and change in behavior ♦ Importance of support services ♦ Effective partnership ♦ Conclusion and perspectives
  3. 3. The Human Expertise
  4. 4. ♦ Integrated in research projects ♦ Formal training postgraduate programmes ♦ CB à la carte ♦ Training on technologies and related tools ♦ Academic/theory (curriculum, e-learning) ♦ Applications: How to use the tools ♦ Whom to train? ♦ Scientists (balance in expertise and experience) ♦ Training of technicians (translation of the tools) ♦ Training of the station managers (essential!) ♦ Awareness creation programme ♦ Focused workshop for a small group of breeders, plus international conferences and regional meetings  Training of future trainers in the regions How to organise CB activities
  5. 5. YEAR 1 MB project Initiation Intro to some MB approaches Field data analysis Mgnt of breeding data Field trial Mgnt system Trainees community YEAR 2 Updates on tools of year1 Adv molecular analysis Genotypic data Mgnt system Marker–trait associations Tools for MTA Trainees community YEAR 3 Updates on tools of year1&2 Configurable workflow Genetic diversity analysis Association mapping Partner specific projects Trainees community Eastern & Southern Africa – West and Central Africa – South & Southeast Asia WUR team, DM CoP & other technical trainers Specific training: Local level Specific Language Different level: Technicians Integrated Breeding Multiyear Course (IB–MYC) ESA WCA SSEA
  6. 6. It is required that trainees successfully complete the following assignments: ♦ Data management: The trainees must be able to properly identify and curate their own germplasm in the database, generate a fieldbook, save the phenotyping data to the database and use the tablet for data collection (field or lab) ♦ Statistics: The trainees choose a completed experiment for which they have data, and write a report including details such as the design used, physical layout, type of analysis applied and the conclusions ♦ Molecular breeding: The trainees write a brief plan of their project. If the work is in progress, they must include what steps have been completed and the planned next steps. Use the IBP tools to carry out their MB projects Trainee assignment to stay on board
  7. 7. IB–MYC trainees by region & gender Region Country Female Male Total WCA 9 8 46 54 WCA % 14.8 85.2 ESA 10 11 51 62 ESA % 17.7 82.3 NA 3 4 1 5 NA % 80 20 SSEA 9 14 35 49 SSEA % 28.6 71.4 Total 31 37 133 170 Total % 21.8 78.2 Region Country Female Male Total WCA 8 8 41 49 WCA % 16.3 83.7 ESA 8 9 38 47 ESA % 19.1 80.9 NA 3 4 1 5 NA % 80 20 SSEA 7 13 32 45 NA % 28.9 71.1 Total 26 34 112 146 Total % 23.3 76.7 Year 1 Year 2 ESA = Eastern and Southern Africa; NA = Northern Africa SSEA = South and Southeast Asia; WCA = West and Central Africa
  8. 8. Dissemination of CB knowledge ♦ Decentralized effort, the only affordable and sustainable approach ♦ Develop a self-contained manual and tutorials for the tools ♦ Should the tutorial be embedded in the tools? Each step linked to video, related e-learning material, quiz, study cases ♦ Provide adequate learning material that will serve several purposes: ♦ Working with e-learning specialists to format the workshop support material in a learning format (PBTN – UNL http://passel.unl.edu/communities/ibp) ♦ Create ready-for-use modules with related training material and quiz, customisable depending on the audience ♦ Identify partner(s) for dissemination in the target regions (Universities) ♦ Train future trainers ♦ Centralised support service (troubleshooting) ♦ Social network (question–answer, advise forum)
  9. 9. Infrastructure
  10. 10. ♦ Field infrastructure ♦ A must-have ♦ No fancy equipment needed, but very good baseline ♦ Providing the money is not sufficient (critical needs assessment and follow-up) ♦ Access to phenomics facilities? ♦ IT support Critical but less of an issue nowadays ♦ Increasing performance of personal computers ♦ Cheap and transportable UPS ♦ Move to cloud computing ♦ Cell phone technology ♦ Access to good internet connection (at least every few days) ♦ Laboratories: not a limitation anymore Critical for implementation
  11. 11. Field support issues Goal: Ensure proper and reliable phenotypic data ♦ Several NARS sites did/do not have optimal field station management practices and support personnel to ensure proper use and maintenance of their equipment and field plots ♦ Field areas invaded by weeds and shrubs (even small trees!) ♦ No field rotation schedule ♦ Poor drainage of access roads, or lack of water channel maintenance, leads to field erosion and lack of plot uniformity ♦ Field equipment (tractors, ploughs, etc.) stored in open-area ‘junk yards’ with little care, maintenance, calibration, etc. ♦ Encroachment by neighbouring farmers on station grounds ♦ For the most deficient cases, we made our infrastructure investments contingent on assurance from the station manager that proper field support systems would be established
  12. 12. Field Infrastructure Improvements in Africa (Support from 2010–2011) Burkina Faso INERA Farako-ba Rice Weather station $5,000 Banfora Rice Weather station, irrigation, fencing, plot rehab $91,000 Ghana SARI Tamale Cassava Weather station, irrigation, fencing, plot rehab $104,000 CSIR-CRI Kumasi Cassava Weather station $5,000 Pokuase Cassava Weather station $5,000 Kenya Egerton University Main campus Chickpea Rain-out shelter $8,000 Koibatek (FTC) Chickpea Weather station, irrigation, fencing, plot rehab $47,000 Kerio Valley Chickpea Weather station $5,000 Moi University Chepkoilel Maize, sorghum Weather station, irrigation, fencing, greenhouse $48,000 Sega Maize, sorghum Weather station, irrigation, fencing $25,000 Mali IER Sotuba Sorghum Weather station, irrigation, fencing, plot rehab $84,000 Cinzana Sorghum Weather station, irrigation, plot rehab $25,000 Farako Sorghum Weather station $5,000 Longorola Rice Weather station, irrigation, fencing, plot rehab $106,000 Nigeria IAR Kano Cassava Weather station, irrigation, fencing, plot rehab $70,000 NRCRI Umudike Cassava Weather station $5,000 NCRI Badeggi Rice Weather station, irrigation, fencing, plot rehab $129,000 Tanzania ARI-Naliendele Naliendele Groundnut, cassava Weather station, irrigation, fencing, plot rehab $124,000 Other espenses Engineering support $220,000 Shipment, admin fees $63,000 Training courses $160,000 TOTAL $1,334,000
  13. 13. Access to information and technology
  14. 14. Challenges: ♦ Most of the breeders in the developing world capture their data by hand and store them in hard copy (book) ♦ In general, protective and proprietary attitude prevents data sharing ♦ Not a top priority, no clear resources allocation, data still in the hands of the individual scientists DM: One of the major challenges in collaborative effort Implementation: ♦ Clear DM policy in place at the Institution level ♦ Quality and documentation improved thanks to : ♦ Adoption of new tools with predefined data-capture templates (eg, electronic FB) ♦ Suitable API to ensure systems and DB interoperability ♦ Proper budget allocation including support staff ♦ Part of the staff evaluation process ♦ Donor requirement beforehand Quality control must start at the scientist level Data management
  15. 15. Crop ontology: key to DM Courtesy Elizabeth Arnaud
  16. 16. Access to service laboratories ♦ Not really an issue anymore ♦ Large number of genotyping service providers ♦ Not only to generate genotypic data but also to help analyse it ♦ Accessible through the IBP at: https://www.integratedbreeding.net/genotyping-services ♦ Strongly discourage partners to invest in routine and/or largescale genotyping technologies ♦ Technologies are evolving too fast ♦ Burden on the staff ♦ More focus on data analysis ♦ Reduce local task as much as possible (send leaf/seed samples) But: ♦ Requires more planning ♦ Analysis turn-over might still be an issue
  17. 17. Availability of SNP markers at GCP for genotyping Crops SNP source No. of SNPs Status Maize Cornell University 1,250 Available for genotyping Cowpeas University of California, Riverside 1,122 Available for genotyping Chickpeas ICRISAT 2,068 Available for genotyping Pigeonpeas ICRISAT 1,616 Available for genotyping Rice Cornell University 2,015 Available for genotyping Cassava IITA, University of Maryland 1,740 Available for genotyping Sorghum Cornell University 1,503 Available for genotyping Common beans USDA–ARS (USA) 1,497 Available for genotyping Wheat Kansas State University 1,864 Available for genotyping Soya beans USDA–ARS (USA) 1,082 Available for genotyping Groundnut ICRISAT 91 Available for genotyping Genotyping at: LGC Genomics  Maize: 278 projects, about 25m data-points  Other crops: 241 projects, about 3m data-points  Primer mix distribution
  18. 18. Analytical tools and pipeline ♦ Difference between research and applied tools ♦ Difference between stand-alone and integrated tools ♦ A lot of very good tools are available ♦ Analytical Pipeline in the private sector: ♦ AGROBASE http://www.agronomix.com/GenII/PDM ♦ Doriane http://www.doriane.com ♦ KDDart http://www.diversityarrays.com ♦ Prism http://www.graphpad.com/scientific-software/prism/ ♦ Virtual lab for plant breeding http://www.vlpb.nl ♦ Analytical pipeline initiatives in the public sector ♦ Integrated Breeding Platform https://www.integratedbreeding.net ♦ IRRI’s trait pipeline http://irri.org/rice-today/the-pipeline-grows-stronger ♦ Seeds of Discovery http://seedsofdiscovery.org/seed/about/ ♦ Tassel http://www.maizegenetics.net ♦ Pipeline for high-throughput sequence analysis is in progress ♦ Allelic mining pipeline, still some way to go
  19. 19. Support or ‘peripheral’ tools ♦ What are we talking about? ♦ Handheld computers or tablets  Harness, anti-reflectance filters for field data capture ♦ Printers with special format ♦ Barcode readers, etc ♦ Most often forgotten…… ♦ Must be included in the planning and deployment ♦ Can have significant impact on the pipeline efficiency ♦ Might represent additional cost ♦ Specificities clearly define: ♦ Challenge, as it can be quite country-specific ♦ Language issue ♦ Availability ♦ Maintenance
  20. 20. Training at NRCRI (Yemi)
  21. 21. None of this is new, but it often happens informally and/or inefficiently They seek help from each other when stuck They draw lessons together from their experiences They tip and alert each other They explore topics together They share approaches that have worked for them They record what they learn together How do communities share & create knowledge? Social network: the concept of CoPs Potentially strong opportunity through social media!!
  22. 22. Mindset and change in behavior
  23. 23. ♦ Most people are reluctant or resistant to change ♦ Even clear benefits for change are not sufficient incentive ♦ Most changes can be implemented only by: ♦ Strong bottom-up demand ♦ Mandatory top-down decision ♦ Need to be ready to: ♦ Change the way you do business ♦ Dedicate time to learn new things ♦ Dedicate time to things that might not benefit your work directly ♦ Share results/methods in an open manner ♦ Adopt a corporative spirit ♦ Enforcement and implementation ♦ Big difference between the private and public sector To change people’s behavior: A real challenge!
  24. 24. The importance of support services
  25. 25. To be successful in enhancing plant-breeding efficiency in developing countries, much more than the simple release of an analytical pipeline is required! ♦ The technology development part is the easiest part ♦ Need for: ♦ Good support strategy that combines a centralised team for overall coordination, and a network of local hubs for daily operations ♦ Clear procedure: whom do I call or contact for what? ♦ Reliable, quick, local and adapted service to the user profile ♦ Different users different services:  CB needs  Breeding support  Customisation of the tools and pipeline ♦ Support service quality a presentation card of the entire Platform ♦ Poor support is a sure killer The needs and the context
  26. 26. The IBP support services Considering the nature of IBP, and the great diversity of potential users of the BMS, it is critical to provide a top-quality support services to ensure sustainable adoption ♦ Professional Support to be provided in three ways: ♦ Client-oriented breeding support primarily targeting developing- country breeders ♦ Capacity building support to provide professional and comprehensive training in orientation to, and using, the tools ♦ Interaction with peers through social networks and CoPs ♦ Technical Support to be provided at two levels to all users: ♦ Level 1: installation technical support  To overcome any difficulties in downloading, installing and getting started with the BMS and related tools ♦ Level 2: operational technical support  for users that might encounter problems in day-to-day use of the BMS and related tools
  27. 27. Central Support Team: Managers plus ad hoc specialists Promotion and commercialisation Team Users from Tier 2 Latin America Africa Asia (Europe, USA, Canada) DB/DM BMS CB Breeding Coordinate and facilitate access to IBP tools and services User feedback to impact on BMS development and implementation Organisation of IBP support services
  28. 28. Effective Partnerships
  29. 29. Indicators ♦ Money allocation to partners ♦ Significant in-kind contribution from partners ♦ Project teams find money outside GCP ♦ Partners continue to work together after GCP project ends ♦ Free exchange of information ♦ Partners not necessarily attracted (purely) by money, but to be part of a network ♦ Critical but indispensable intangibles – trust and goodwill Evolution of roles and responsibilities ♦ A switch: Leaders become mentors ♦ Knowledge applied & transferred: Trainees become doers & leaders ♦ Today, more than half of our PIs are from developing countries and more than half the grants go directly to National Programmes It takes time and resources to nurture and implement true partnership! True partnership
  30. 30. From the GCP External Review (2008) The panel noted that GCP community is one of the Programme’s crucial assets: “Perhaps the most important value of GCP thus far, is the opportunities it has provided for people of diverse backgrounds to think collectively about solutions to complex problems, and, in the process, to learn from one another.” The power of grouping forces
  31. 31. Linking upstream with applied science The sorghum case: From Cornell to African farmers’ fields with a stopover in Brazil: a ten-year effort ♦ Step 1: Competitive Project (initiated 2004) ♦ Led by Cornell Univ, in collaboration with EMBRAPA ♦ Plantlets screened under hydroponics – Alt1 Gene cloned Magalhaes et al. 2007, Nature Genetics, 39: 1156–1151 ♦ Step 2: Competitive Project (initiated 2007) ♦ Led by EMBRAPA in collaboration with Cornell ♦ Favourable alleles identified – Improved germplasm for Brazil Caniato et al. 2011, PLoS One 6, e20830 ♦ Step 3: Commissioned work (initiated 2009) ♦ Led by Moi University in collaboration with EMBRAPA ♦ Introgression of favourable alleles – Improved germplasm for Kenya and Niger The power of pooling expertise
  32. 32. The Power of working across Countries The Cassava CoP An active community to empower National Programmes to access and use new germplasm and technologies ♦ Component 1: Access to new alleles ♦ Germplasm exchange across South America and East Africa (IITA, a key partner here) ♦ Component 2: Strengthening the research community in Africa ♦ Countries involved: Nigeria (leader), Ghana, Tanzania, Uganda ♦ Another 9 countries added in 2012 ♦ Component 3: Visibility at international scene ♦ Eg, Nigeria’s National Root Crops Research Institute (NRCRI) now a key partner in the Bill & Melinda Gates Foundation breeding projects, resulting from GCP project ♦ Participate in marker development and sequencing effort ♦ Component 4: Government support ♦ Attracting federal funds to enhance infrastructure at NRCRI
  33. 33. ♦ Be strategic in partnership development ♦ Much more than simply numbers, no universal ‘template’:  Different kinds of partnerships for different needs  Different kinds of partnership for the same need ♦ Be selective, and cautious ♦ Can easily get out of hand, can be a distraction ♦ Plan for it, and do not underestimate effort needed: ♦ managing true partnerships takes time and resources!!! ♦ But, if managed well: ♦ One of the most efficient way to do business ♦ One of the most rewarding components of the work ♦ Creates a special group dynamic ♦ Critical to bring new ideas ♦ The best way to promote your work  others speak well of you  cultivates public trust, resultant positive public image without any PR effort Important to keep in mind
  34. 34. Conclusions and Perspectives
  35. 35. ♦ Access to suitable tools and analytical pipeline is not a key limitation anymore ♦ Capacity on most target countries is increasing significantly ♦ Human capacity: fast progresses ♦ Infrastructure: still slow ♦ Major challenge remains in the area of adoption and support ♦ We must have the buy-in of upper management of user institutions ♦ Must apply a proactive promotion with kick-off meeting at user institutions ♦ Stepwise approach starting populating the DB ♦ Support must be: reliable, quick, local and adapted to the user profile ♦ One size doesn’t fit all! ♦ Time is right (and ripe!) to make a change: ♦ Major public investments ♦ The technology is ready ♦ Solid international networking (e.g. CRPs, Gates’ Initiatives, GCP) ♦ Open access policy adopted and implemented Conclusions and Perspectives
  36. 36. The genomics impact on breeding Crop diversity Improved crops Genomics

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