Annual Report 2017 Tools and services that create synergies and accelerate genetic gains of breeding programs targeting the developing world Logo Social Profile Photo Primary Color Process (CMYK) C: 85 M: 0 Y: 55 K: 50 RGB R: 0 G: 107 B: 90 HEX #006b59 Branding Assets CGIAR Excellence in Breeding Platform CGIAR Excellence in Breeding Platform Annual Report 2017 Table of Contents 1. Key Results ............................................................................................................................................ 1 1.1 Highlight Platform Outputs ............................................................................................................. 1 1.2 Platform-specific quality control activities ...................................................................................... 1 1.3 Progress by Platform Modules ........................................................................................................ 2 1.4 Cross-Cutting Dimensions (at Platform Level) ................................................................................ 9 1.4.1 Gender, Youth and Capacity Development .................................................................................. 9 1.4.2 Open Data ..................................................................................................................................10 1.4.3 Intellectual Assets ......................................................................................................................10 2. Platform Effectiveness and Efficiency .................................................................................................11 2.1 Variance from Planned Platform Activities ...................................................................................11 2.2 Use of W1-2 Funding ....................................................................................................................12 2.3 Key External Partnerships .............................................................................................................12 2.4 Cross-CGIAR Partnerships (CRPs and other Platforms) .................................................................13 2.5 Monitoring, Evaluation, Impact Assessment and Learning (MELIA) .............................................13 2.6 Improving Efficiency ......................................................................................................................14 3. Platform Management ........................................................................................................................14 3.1 Platform Management and Governance ......................................................................................14 3.2 Management of Risks to Your Platform ........................................................................................14 3.3 Financial Summary ........................................................................................................................14 TABLES Table A: Reporting against Platform Specific Indicator .......................................................................15 Table B: Status of Planned Milestones ................................................................................................17 Table C: Cross-cutting Aspect of Outputs ...........................................................................................26 Table D: Common Results Reporting Indicators .................................................................................26 Table E: Intellectual Assets .................................................................................................................28 Table F: Main Areas of W1/2 Expenditure in 2017 .............................................................................28 Table G: List of Key External Partnerships...........................................................................................30 Table H: Status of Internal Collaborations between the Platform and Programs and among Platforms .............................................................................................................................................31 Table I: Monitoring, Evaluation, Impact Assessment and Learning ....................................................32 Table J: Platform Financial Report ......................................................................................................34 CGIAR Excellence in Breeding Platform Annual Report 2017 CGIAR Excellence in Breeding The International Maize and Wheat Platform (EiB) Improvement Center (CIMMYT) List of participating Centers and other key partners Biosciences eastern and central Africa - AfricaRice International Livestock Research Institute Hub International Center for Bioversity International Tropical Agriculture (CIAT) International Potato CIMMYT Center (CIP) Cornell University Corteva Agriscience Commonwealth Scientific and Industrial Diversity Arrays Research Organisation Technology (DArT) (CSIRO) Food and Agriculture The Crop Trust Organization of the United Nations (FAO) International Center Institut National de la for Agricultural Recherche Research in the Dry Agronomique (INRA) Areas (ICARDA) - CGIAR Excellence in Breeding Platform Annual Report 2017 International Crops International Institute Research Institute for of Tropical Agriculture the Semi-Arid Tropics (IITA) (ICRISAT) International Livestock Integrated Breeding Research Institute Platform (IBP) (ILRI) International Rice Research Institute James Hutton Institute (IRRI) John Innes Centre Kansas State University Nottingham University Monsanto Oregon State Queensland University University United States Syngenta Department of Agriculture (USDA) Wageningen World Agroforestry University Centre (ICRAF) WorldFish - CGIAR Excellence in Breeding Platform Annual Report 2017 1. Key Results 1.1 Highlight Platform Outputs: The platform leader was hired in August of 2017. The platform leader, Michael Quinn, and CIMMYT DDG, Marianne Bänziger, visited a large number of CGIAR-supported breeding programs – Africa Rice (Nigeria), CIAT (Colombia), CIMMYT (Kenya, India, Mexico), CIP (Kenya, Peru), ICRAF (Kenya), ICRISAT (Kenya, India), IITA (Nigeria), ILRI (Kenya), BeCA (Kenya), IRRI (Philippines, India), WorldFish (Malaysia) – to better understand challenges, needs and opportunities, and to explain how EiB can provide value to CGIAR breeding institutions and how best to work with EiB. A membership agreement that describes the commitments expected of breeding programs participating in EiB and the benefits they can expect to receive in turn was developed and distributed to CGIAR institutions. Signed membership agreements were returned from most CGIAR breeding programs. A meeting of EiB contributors and expert advisory group (EAG) members from CGIAR was held in Amsterdam. The outcomes of the meeting shaped the objectives and work plans of EiB for 2017 and will continue to do so for the next five years. It was also the first time that CGIAR breeders jointly discussed product development concepts and how to improve breeding program management. Another successful workshop was held at the National Crops Resources Research Institute in Uganda and supported by EiB, the High Throughput Genotyping Project (HTPG), the Genomics Open Source Breeding Informatics Initiative (GOBii) and the Integrated Genotyping Support and Services Project (IGSS). The objective of the workshop was to enable CGIAR and NARS programs to implement marker- assisted selection and integrate forward marker breeding strategies into the actual breeding process. In contrast to previous training approaches, the focus was on overcoming practical constraints and approaches for integrating markers into the breeding pipeline to accelerate genetic gains. The team worked on developing decision guides for breeding programs, and practical tools for DNA sampling in challenging environments. Another workshop assessed bottlenecks in high-throughput phenotyping among centers implementing such approaches, in order to identify how to implement lower cost phenotyping approaches. EiB supported the implementation of the Breeding Application Programming Interface (BrAPI), advancing towards the goal of interoperability of breeding and germplasm information systems, both existing and in development. In collaboration with the BigData Platform it emphasized the need for uniform data standards driving data integration. EiB further developed the first version of a Drupal- based Toolbox as a repository and gateway for tools, use cases, best practices and training materials, while serving as a discussion platform for the EiB community. EiB expanded its annual funding from US$ 2 million to US $6 million through bilateral funding from the Bill & Melinda Gates Foundation (BMGF), thus reaching 60% of its base budget. 1.2 Platform-specific quality control activities EiB enables breeding programs to make improvements through the implementation of best practices. Quality control within the Platform relies on ensuring that the skills, knowledge, know-how, tools and services being promoted and made available through EiB are aligned with best practice. For this it is important for EiB to understand exactly what best practice is. This is achieved in a number of ways, including an annual contributors’ meeting where experts from all over the world and from each discipline of breeding are brought together to discuss and decide on the practices, tools and services that EiB will promote and make available to breeding programs. -1- CGIAR Excellence in Breeding Platform Annual Report 2017 Another quality control measure used by EiB is the Breeding Program Assessment Tool (BPAT), implemented in collaboration with Queensland University and BMGF. The BPAT is a standard review approach for identifying what improvements can and should be considered by breeding programs. By using recommendations derived from the BPAT as guide to the specific improvements that should be prioritized for participating breeding programs, EiB is responding to the goals outlined by an external and highly qualified review process. In time, the BPAT will also serve as a means to measure the success of EiB in enabling breeding programs to adopt these recommendations. 1.3 Progress by Platform Modules: Module 1: Breeding program excellence The focus of Module 1 was to introduce key concepts and better understand the needs of the CGIAR and national agricultural research and extension system (NARES) breeding community. The concept of a product advancement process (stage gate management) was introduced through a series of workshops. The position of Product Manager/Market Analysis was opened to support the adoption of variety replacement strategies, in which breeding teams adopt market-oriented product profiles to increase variety turnover or initiate a market shift. Through a series of CGIAR/NARES breeding community network meetings, the breeding community has been made aware of how Module 1 can better help the programs achieve impact. In general, there is a reluctance to implement a structured approach due to the risks introduced with greater measurability. Based upon open discussions with meeting participants, it was determined that Module 1 objectives can be achieved by designing simple means of implementing best practices and with the constant involvement and support of Center/CRP leadership. The need for an emphasis on measuring breeding program success through the assessment of genetic gains was also introduced in the partner breeding community. The value of assessing genetic gains was recognized, but the preference among breeders was for more immediate feedback on the value of breeding program changes. Based on these conversations, we will continue to develop best practices for genetic gain improvements, but also develop a more practical assessment that would provide a less comprehensive but more frequent assessment of breeding program improvements. The annual assessment of program improvement would be a vehicle for ushering in Module 2 breeding program assessments. Progress over the reporting period was impeded by the lack of dedicated Module 1 leadership, with the early leader of Module 1 holding a separate role as the IRRI Breeding Lead during a time when IRRI was focused on restructuring for impact. As of 7 May 2018, Module 1 leadership has been engaged on a full-time basis. A greater impediment may exist if the Center DG/DDGRs do not actively oversee the implementation of Module 1 principles. Without the direct involvement of the DG/DDGR, breeders will continue to develop tool- or trait-driven products, rather than products designed for combined market and development impact. Module 2: Optimizing breeding schemes The focus of Module 2 was changed during 2017 from “Trait discovery and the toolbox” to “Optimizing breeding schemes”. This is in acknowledgement that the tools and services provided through modules 3, 4 and 5 will only have impact if applied as part of a strategic plan to increase rates of genetic gain, according to the targets set by Module 1. As a result, Module 2 will enable breeders to optimize their breeding strategy and improve new tools strategically, focusing on cost-benefit analyses of genomics and phenotyping tools and secondary traits, improved integration of trait breeding into mainstream breeding, and tools for optimizing breeding schemes. The Toolbox is now situated outside the modules, housing inputs from all five modules. -2- CGIAR Excellence in Breeding Platform Annual Report 2017 A headhunter has been recruited to find a leader for Module 2. After the first round of searching none of the candidates were found suitable. The second round of searching is coming to a close and it is expected that an offer will be made for the Module 2 leadership early in Q3 2018. Without a Module leader (and without an EiB Director for most of the year) very little Module 2 activity was conducted in 2017. A draft template to capture breeding programs’ current breeding schemes has been developed. Toward the objective of developing a simulation tool to provide decision support to breeders, discussions have been held with a private company that has developed such tools for Syngenta. Module 3: Genotyping / sequencing tools and services The focus of Module 3 is to promote and provide support for shared genotyping services to all EiB member programs, whether in the CGIAR or in NARES. A survey was sent out to all member programs to assess the needs, challenges and expectations for Module 3 covering three main areas of genotyping application: (i) A low density marker platform for forward breeding, (ii) a mid to high density sequencing platform for genomic selection and germplasm fingerprinting, and (iii) Quality Assessment/Quality Control (QA/QC) for breeding pipelines. The outcome of the survey supports genotyping sample forecasting, which is critical to service contract negotiation with various genotyping service providers, thereby supporting a key Module 3 objective. In 2017, most of the module outputs were delivered through two BMGF-funded sister projects, HTPG and IGSS. The HTPG project is geared towards low-density genotyping platforms (KASP markers technology) and a service contract led by ICRISAT was signed with Intertek to provide services to all EiB members as well as private partners. The project offers significant cost reduction in low-density genotyping (25% to 50% savings vs. in-house facilities) to all users and most of the CGIAR and NARS users also received genotyping subsidies from BMGF. The HTPG mode of operation relies on collective bargaining and sharing of marker information among all users in order to maintain low pricing; the minimum business volume to maintain the pricing agreement with Intertek was US $200,000 per annum. In 2017, the annual business volume was reported at over US $500,000, more than twice the annual minimum volume. The success of the project was mainly due to the expansion of the user base, with the inclusion of multiple private sector partners as well as growing number of crop programs switching over to outsourced genotyping providers such as HTPG. By the end of 2017, users representing a total of 13 crops had enrolled in the HTPG service, spanning seven CGIAR centers and over 30 NARS and private partners. -3- CGIAR Excellence in Breeding Platform Annual Report 2017 Total Business Volume (Aug 2016 - Nov 2017) $108,910 Total: $523,345 $76,251 $66,288 $52,224 $35,728 $11,136 $21,600 $7,008 $1,080 Verification Genotyping Acknowledging the need for cross-EiB module integration to provide better support for member programs, HTPG had multiple activity planning meetings with the Genomic Open-sourced Breeding Informatics Initiative (GOBii) in 2017. One key activity was the joint workshop in East Africa hosted by the National Crops Resources Research Institute (NACRRI), Uganda and sponsored by EiB, GOBii, IGSS and HTPG. The joint workshop covered three high-level components: (i) Initial engagement on the work of EiB in East Africa, (ii) decision support tools and services provided by GOBii, and (iii) HTPG and IGSS project discussions. Following that, on 4-6 December 2017, the HTPG annual meeting was held at ICRISAT, Hyderabad with participants from 30 public and private institutions from 19 countries. The annual meeting provided a good avenue for all HTPG users to interact and provide feedback. Overall, sampling logistics and decision support tools were identified as major constraints for many users to scale-up adoption of genotyping tools. The feedback provided in these meetings has helped set the direction for Module 3 to work even more closely with Module 4 and Module 5 in 2018. Furthermore, 2017 was the first year that the IGSS genotyping service was offered; previous years were dedicated to setting up the lab and providing training. IGSS initiated approximately 47 projects in which genotyping was offered at a subsidized price to initiate long-term molecular breeding within these programs. These projects are forecast to produce around 70,000 samples for genotyping between 2017 and 2019. In addition, two communities of practice (CoP) for maize and beans were set up with the participation of breeders from Ethiopia, Kenya, Uganda, Rwanda and Tanzania. These projects were initiated by forming a diversity panel composed of lines from all members. The IGSS hosted a workshop to organize the CoP and discuss genomic selection. The IGSS also participated in workshops/meetings for EiB, MERCI and MARI in Ethiopia, Rwanda, Tanzania and Uganda. Module 4 Survey to assess current status in phenotyping and TPE analysis An in-depth survey was executed following the EAG meeting in March 2017. The main objective of the survey was to assess the status of phenotyping in support of breeding in the different agri-food system -4- CGIAR Excellence in Breeding Platform Annual Report 2017 CGIAR research programs (AFS CRPs), and then define a benchmark to guide the choice of EiB interventions and further monitoring of progress. The survey was applied in five domains: (i) Informant information and perceptions. This included the CoP participant ID and initial perceptions; (ii) Targeting and screening. This domain refers to the environmental characterization of the target population of environments (TPE), to capture how well the conditions in which phenotyping is carried out are documented and reported, and whether traits are measured with specific facilities or high throughput phenotyping methods; (iii) Phenotyping/mechanization. This domain serves to identify the most frequent phenotypes being measured/recorded, and in what conditions, methods and stage in the breeding program. It also attempts to establish a baseline/benchmark/need diagnosis in the different AFS CRPs in terms of throughput/mechanization and automation, or infrastructure and management of research stations; (iv) Data storage, analysis and ranking. This domain refers to the use of statistical tools and methods to correct phenotypic data and increase their quality and the information for breeding selection; (v) Specialized phenotyping. This provides an inventory of needs for routine analysis of physicochemical composition and functional properties in plant and animal materials in support of breeding (e.g. near-infrared reflectance spectroscopy analysis for grain quality); (vi) Tools, training and support. This identifies possible tools that could be shared across the different AFS CRPs and training needs. A detailed analysis report was generated from the answers to the survey. The survey report is a rich diagnosis of the status of the AFS CRP breeding programs in terms of phenotyping. The survey report gives information on “low hanging fruit” (for instance, only about 60% of AFS CRP breeding programs use barcoding routinely and achieving a 100% mark seems to be a logical short-term target), areas where investment is needed (for instance mechanizing operations such as planting, weeding and harvesting), etc. From this survey, which gathered about 80 responses, the community of practice was created. An analysis of the survey was shared within the CoP along with other Module 4 updates. Tools and best practices: The documentation of best phenotyping practices and their conversion into adaptable/deployable solutions across AFS CRP breeding programs lies at the core of EiB Module 4. A first stage is to develop content by tapping into on-going experiences in the CoP and upload such content onto the ToolBox. The idea is to develop technical manuals and videos to show tools in action for easier replication/implementation, provide troubleshooting sections and links to potential equipment providers, providing a holistic information source for potential implementers. The concept was discussed with potential contributors and topics of common interest identified for elaboration in 2018. High throughput phenotyping A meeting was held on 6-7 November to discuss the use of drone-based imaging to generate phenotyping data in support of breeding programs. The rationale for the meeting was to gather together experts in the field to evaluate what is possible and identify remaining bottlenecks. Discussions focused on how to make these tools accessible to non-practitioners, and to breeders in particular. A solution was discussed that would allow new potential users to incorporate drone-based imaging in the scope of their breeding program while avoiding the obstacle of high initial time and material resource investment in technology adoption. Currently, some CGIAR centers have started to generate drone imagery, but the initial time and resource investment required to create a working solution in context has prevented the creation of solutions that can be easily replicated elsewhere. The solution developed in this meeting consists of a two-part service model: 1. Image generation (either in the scope of a regional hub or through a local service provider) with a standard operating procedure (SOP) manual to generate these images and a local app to ensure quality. -5- CGIAR Excellence in Breeding Platform Annual Report 2017 2. A cloud-based platform for data processing (with the possibility for a local version in cases of poor internet connection), inputting image data and outputting spectral indices. In implementing this solution, Module 4 would tap into the experiences of world experts in this domain (such as the University of Queensland, the Kansas State University (KSU)-French National Institute for Agricultural Research (INRA) group and a commercial startup) to set a gold standard of drone-based imaging operation in the CGIAR and NARES breeding programs. This solution would require expert support in IT-image analysis to facilitate both steps. A start-up associated with INRA-Avignon is currently developing a similar platform for INRA and would be keen to explore the expansion of this activity node in the CGIAR. Such node(s) could also be based in any of the regional phenotyping hubs being considered by the CGIAR. Module 5: Bioinformatics, biometrics and data management Module 5 survey results As an initial activity of EiB Module 5, a survey was conducted to assess the breeding informatics (IT, bioinformatics, and biometrics) support for CGIAR breeding programs. There were around 80 respondents from multiple CGIAR centers and geographies, as detailed in Table 1. To gauge awareness and interest in EiB and Module 5, participants were asked if they had heard of EiB and were interested in participating in Module 5. Of the 80 participants, 70% indicated they had heard of EiB and 91% responded that they were interested in participating in Module 5 activities. This clearly indicates that there is significant interest in EiB and the goals of Module 5. Table 1 Centers Responding to the Survey Bioversity, CIAT, CIMMYT, CIP, ICARDA, ICRISAT, IITA, ILRI, IRRI. Countries Represented Belgium, Colombia, Ethiopia, France, Ghana, India, Kenya, Mali, Mexico, Morocco, Niger, Nigeria, Peru, Pakistan, Philippines, Tanzania, Turkey, Zimbabwe. The survey focused on several key areas: IT infrastructure, data management, breeding process support and breeding decisions support. From the outset, it was believed that internet connection reliability was viewed as a major issue in many geographies; however, responses to the survey indicate only a small percentage of participants consider internet connections to be unreliable. Responses indicate that data accessibility and access to adequate computational resources are issues that need to be addressed, with 26% of participants indicating that it is difficult to access the data required to do their jobs. Survey results relating to IT infrastructure are presented in Annex 1. In terms of data accessibility and analysis related to decision support, the survey results indicate that only 41% of survey participants agree that they have easy access to data needed to make advancement decisions. Even more troubling is that only 30% of respondents agreed that they had easy access to information needed to make parental selections. This low number is likely related to poor access to historical data (only 20% agreed there was easy access) and the ability to trace advancement decisions (only 25% agreed there was easy access). Not only does this affect the ability to make well-informed decisions for parental selection, it also makes it very challenging to track genetic gain and evaluate the efficiency of breeding programs. These represent critical and fundamental issues that must be addressed if EiB is to be successful. The first key step in accomplishing this will be the full adoption of -6- CGIAR Excellence in Breeding Platform Annual Report 2017 breeding management software. Survey results relating to data accessibility and decision support are presented in Annex 2. Results related to data analysis and statistical consulting fared better in the survey, with 60% of respondents indicating that they had the biometrics consulting capacity and software needed to design and analyze field trials; however, only 20% of respondents agreed that it was straightforward to program analysis pipelines against databases. This may explain why only 47% of respondents agreed that all trials are analyzed in time to make advancement decisions, despite indications that software and consulting are available to breeders. Given the resource investment in planting, growing, and harvesting field trials, the inability to analyze the data on time is costly. It is clear decision support tools will benefit breeding programs, but bottlenecks in data access and data cleaning need to be addressed as a first step. Efficient breeding workflows and processes are another key driver in breeding program efficiency. Minimizing errors and reducing both time and cost for breeding processes can have a huge impact on the performance of breeding programs. The fact that industry breeding programs commonly use lean and Six Sigma principles to improve breeding processes is testament to the importance of optimizing SOPs. While the development of SOPs falls outside the scope of Module 5, building the IT support for efficient implementation of the SOPs should be a focus. While the survey only covered a subset of breeding processes that will require IT support, there clearly needs to be improvement in this area, with only 33% of respondents agreeing that they have adequate IT support for breeding workflows and processes. However, significant standardization of breeding process and workflows will be required to effectively build IT support. In the absence of standardization, developing tools will be costly and challenging, if not impossible. This is an area where Module 5 will need to collaborate closely with the other modules in EiB. Survey results relating to breeding process support are presented in Annex 3. Current landscape for breeding data management There are multiple systems in various stages of development for breeding management but, as indicated in the survey, these systems have yet to be adopted for routine use. One major focus of Module 5 needs to be facilitating the routine adoption of available systems, as this will address many of the needs identified in the survey. There can be several reasons for lack of adoption, including system performance, inadequate user training, lack of proper incentives or the cost of deploying and maintaining the systems. For all EiB member programs, clear metrics on the adoption of breeding systems should be required, and in cases where adoption rates are low, programs should provide clear feedback as to the root causes. Modern and efficient breeding programs are built on a foundation of fully adopted breeding management systems. These systems are the basis of accurate decision support and efficient breeding process. Figure 1 details major breeding management systems available to EiB breeding programs. While adoption is the most critical and urgent deliverable of Module 5, the interoperability of these systems is necessary to deliver downstream benefits of breeding process and decision support. To achieve interoperability, Module 5 must achieve 3 key deliverables: 1) Compatible implementations of Universally Unique Identifiers (UUIDs) for germplasm and other relevant entities. 2) Definition and full adoption of minimally acceptable metadata standards for all breeding data collected by member breeding programs. 3) A common BrAPI must be developed and implemented in all critical database systems adopted by member programs. -7- CGIAR Excellence in Breeding Platform Annual Report 2017 B4 BMS R GO BII Cassavabase Sample Global Trial Data Tracker/LIM Management S System Flat Files Figure 1. Current methods for managing data in CGIAR breeding programs. Dashed lines indicate that systems need to exchange information but are not interoperable. To support these efforts, M5 initiated two CoPs. Following the initial survey, a second survey was sent to solicit participation from people focused on M5-related activities. Eighty individuals from the AFS CRP system and from key Module 5 projects and partners, such as GOBii and the James Hutton Institute, indicated an interest in contributing to these CoPs on (1) Bioinformatics and Biometrics and (2) Breeding Data Management. These groups will hold online meetings and will also form working groups to address specific topics requested by the Module 5 EAG. The first meetings of these CoPs and working groups commenced in Q4 of 2017. Module 5 results framework and progress on year 1 deliverables The initial focus of Module 5 will be the routine adoption of breeding management systems and interoperability of key databases. A further major deliverable, a sustainable architecture for breeding management, process and decision support, will then follow. While it is key to implement a sustainable IT architecture, it is unlikely that this will be achievable in the first five years of the project. With that said, Module 5 will need to deliver a model for IT architecture and make significant progress in building towards this architecture in Phase I of EiB. Table B contains the key Module 5 deliverables for Year 1 of the project. The deliverables are combination of Year 1 deliverables established in the March 2017 EiB meeting (due at the end of 2017) and the deliverables from the BMGF results framework (due at the end of October 2018). The deliverable “Establish overall strategy and prioritize pipeline/breeding use case studies and related tools” will be a critical driver of subsequent Module 5 efforts. While data generation, acquisition, and quality control are obvious first steps, a clear path forward for development strategy and priorities needs to be established and approved by the EiB steering committee. It is also recommended that initial software and database development work be focused on more advanced breeding programs in terms of adoption of data management systems and best practices in data collection. Systems developed for advanced breeding programs could then be modified for adoption as additional programs are ready for implementation. -8- CGIAR Excellence in Breeding Platform Annual Report 2017 While great progress has been made on deliverables due by the end of 2017, there is significant work left on deliverables due in October 2018. For the deliverable “Establish overall strategy and prioritize pipeline/breeding use case studies and related tools”, it is proposed that a working session be held at the 2018 EiB EAG meeting, with the goal of identifying and prioritizing key use cases for the development of breeding IT support. For the deliverables “Report on the current landscape of databases, bioinformatics capabilities/software, and biometric capabilities/software”, “Documented gap analysis for the Year 1-2 case studies” and “Existing databases and tools assessed and updated”, it is recommended that a consultant be contracted to work with the newly formed Breeding Data Management CoP to identify and evaluate key database systems. For bioinformatics/biometrics software and capabilities, a working group has been formed as part of the Biometrics and Bioinformatics CoP to compile a list of available software and recommendations for improving accessibility and adoptions rates. A training and workshop plan is being formed in collaboration with partnering projects to address the deliverable “Exposure to and adoption of appropriate databases in member breeding programs” with the goal of having a finalized training schedule in place for 2018/2019 following the March 2018 EiB EAG meeting. In conclusion, the initial EiB Module 5 survey indicates there is significant interest in the Platform and critical gaps that must be addressed to improve the efficiency of member breeding programs. The highest priority will be addressing fundamental issues with data management, with a focus on increasing the adoption of breeding management systems and improving the interoperability of critical systems. Improvement of interoperability will focus on data QC and metadata standards, BrAPI and UUIDs with a focus on supporting the highest priority breeding use cases. 1.4 Cross-Cutting Dimensions (at Platform Level): 1.4.1 Gender, Youth and Capacity Development: Gender The CGIAR EiB Platform actively ensures that gender is a major component of its strategy by including women in its communities of practice, expert advisory groups, and training events. Through the documentation of personnel in membership agreements, we are able to emphasize the importance of gender balance in our membership. Furthermore, a Product Manager/Market Researcher for Breeding Product Development and Uptake has been hired to ensure socially inclusive needs and circumstances, particularly of women and youth in rural households in target geographies, are considered in product design and scaling strategies. Youth The CGIAR EiB Platform has addressed youth by hiring a Product Manager/Market Researcher for Breeding Product Development and Uptake to ensure that socially inclusive needs and circumstances, of youth in rural households in target geographies are considered in product design and scaling strategies. It is anticipated that new technologies will stimulate youth interest in the field, and that young scientists will make full use of resources available on the Platform web portal and Toolbox. Capacity Development The three primary areas of capacity development in EiB are: 1) Workshops/trainings, 2) Toolbox, and 3) Learning Management System (LMS). In 2017, the Platform held workshops/training events, including in East Africa, targeting improved use of genomics tools, and another which was focused on developing a centralized service for processing drone-based images. The Platform has invested in the documentation of tools by members, and in Platform personnel and consultants adapting those tools for a wider range of users, as part of a web-based Toolbox. Although the LMS is currently in its initial stages, it will be significant in ensuring that EiB is accessible to a greater number of people. -9- CGIAR Excellence in Breeding Platform Annual Report 2017 1.4.2 Open Data: While EiB may provide access to tools, services and knowledge from different sources, with varying usage policies, open access will always be prioritized and the outputs of EiB and its members through the Platform will be openly and freely available. The Platform will serve as a broker of genotyping services. Products submitted to the Toolbox and data generated by genotyping service providers will remain the intellectual property of the users with neither the Platform nor the service provider gaining any rights to the germplasm or data. Members of this Module will need to sign an agreement that contains the requirements for Platform service use and supply provisions. Platform staff will negotiate services with input from finance and legal experts. Pricing agreements reached with service providers will, if required by service providers, remain confidential. Members contributing to this Module shall ensure proper stewardship of their intellectual property as well as intellectual property belonging to other parties who have granted and confirmed permission to use. All parties using third party intellectual property must do so as part of any agreement they sign for this Module. Intellectual assets developed with Platform funding (including tools, germplasm, inventions, improvements, data, processes, technologies, software, trademarks, publications and other information products) will be made available to the public under appropriate licensing conditions. In circumstances where third-party intellectual property is utilized, conditions may be added as permitted under Section 6 of the CGIAR Principles on the Management of Intellectual Assets, which establishes the conditions for ‘limited exclusivity’ or ‘restrictive use’ agreements. Open-source solutions are preferred to facilitate inter-connectivity of tools and wide adoption. Management of pay-to-access third-party commercial software, computational infrastructure or expert advice may require cross-member licensing agreements that could be beneficial to providers while allowing for a larger user base and greater adoption. User feedback on the web platform will demonstrate if tools or services are performing poorly. The web administrator will need to ensure that user feedback is based on fact. 1.4.3 Intellectual Assets: A. CIMMYT, participating CGIAR Centers and partners manage the CGIAR EiB Platform Intellectual Assets (IA) in accordance with the CGIAR Principles for the Management of Intellectual Assets and the CGIAR Open Access and Data Management Policy. The CGIAR EiB Platform is not a legal entity distinct from the Centers that implement CRPs, and therefore IAs are managed across the research portfolio of each entity, without specific regard to MAIZE CRP projects or to outputs produced with CRP funding. Early each year, CGIAR Centers submit an Intellectual Asset report to the CGIAR System Management Board. In each report, the Center describes the most relevant IA management strategies and practices implemented during the previous calendar year; the Center also includes a separate detailed summary of intellectual property arrangements for Limited Exclusivity Agreements and Restricted Use Agreements (normally labeled as confidential, as a prerogative for the Center and due to obligations acquired with partners). As this information already has been provided through this avenue and under the same confidentiality restrictions it will not be duplicated here. All Centers are subject to obligations under (i) the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), (ii) the privacy of individuals; (iii) confidential obligations acquired; and/or (iv) intellectual property rights of third parties. -10- CGIAR Excellence in Breeding Platform Annual Report 2017 B. CIMMYT has not filed, nor has any CIMMYT partner informed CIMMYT, of any application for patent or plant variety protection associated with intellectual assets developed by the CGIAR EiB Platform. C. The most critical challenges for IA management in the context of the CGIAR EiB Platform are as follows: 1. Ensuring sufficient funding (including sufficient human resources), to implement all actions needed for a proper IA management on a timely basis. 2. Harmonization of licensing practices to disseminate digital sequence data with the Open Access obligation, in light of concerns raised among some ITPGRFA stakeholders in relation to the use of such datasets; 3. The rising bar for Centers’ privacy protection and accountability in the context of dealing with datasets, wherein such data include personal information that carry with them accompanying dissemination obligations under Open Access. Finally, it is unclear what the expected difference could be between IA management practices under the CGIAR EiB Platform versus those reflected in the IA reports to the CGIAR System Organization. 2. Platform Effectiveness and Efficiency 2.1 Variance from Planned Platform Activities: (a) Have any promising research areas or services been significantly expanded? Please give specific examples. Where has the money for expansion come from? No, there was no significant expansion of research areas or services. (b) Have any research lines, activities or services been dropped or significantly cut? Please give specific examples and brief reasons. If funding was reallocated to other work, where did the money go? Nothing has been dropped or significantly cut, but there was significantly less activity than planned within the first year of the Platform. This was due to a number of reasons, including that the Platform director did not begin until August, memberships still needed to be established, member breeding team action plans are yet to be defined, material for delivering to member breeding teams still needed to be developed, and, part-time module leadership has proven to be extremely challenging. To address this last point full-time staff will be appointed within each of the modules in 2018. (c) Have any research areas taken new directions due to unexpected research results (positive or negative)? Please give specific examples. Put “N/A” if not applicable.] Module 2, which was “Trait discovery and the Toolbox” been altered to focus on “Optimization of breeding schemes”. This is in acknowledgement that access to tools and services will have highest impact when applied strategically in a way that is aligned with the fundamental principles of plant breeding, quantitative genetics and biometrics. Trait discovery remains an important part of EiB and within the Platform the Toolbox now sits apart from the modules, providing services to all five. Module 4 has developed a greater focus on improving the quality, throughput and cost of phenotypic data for key traits on the product profile. This will primarily occur through improved mechanization and automation. This focus will come at the expense of more general phenotyping activities (including for example for research purposes), physiology approaches and proof of concept work. As an example, high throughput phenotyping will not have such a strong focus going forward except for in cases where -11- CGIAR Excellence in Breeding Platform Annual Report 2017 it has been shown to result in increased rates of genetic gain for key traits described in the product profile. 2.2 Use of W1-2 Funding: The main areas of expenditure of W1/2 funding for 2017 were Personnel Costs and Collaboration Costs. W1/2 funding made it possible to collaborate with the following key partners: Cornell University, IRRI, ICRISAT, and IRD. This collaboration was important while the Platform was understaffed, and many of its objectives could not have been accomplished without the involvement of partners. The Platform had a significant carryover in 2017 because many of its key positions were not in place; in 2018 it is expected that all key positions are hired and that pending milestones are accomplished. Type Restricted C onsider > 2017 Row Labels Carryover Total Budget Total 2017 Balance from 2016 2017 01 W1 & W2 Funding - Phase II - 2,000,000 1,181,564 818,436 01 g. EiB - 2,000,000 1,181,564 818,436 01 - Personnel Costs - 719,299 424,021 295,278 02 - Other Collaboration Costs - 589,716 301,472 288,244 03 -Supplies and Services - 401,723 184,284 217,439 04 - Operational Travel - 58,477 83,497 (25,020) 05 - Depreciation / Amortization - 24,163 60,388 (36,225) 07 - Indirect Costs - 206,622 127,902 78,720 Grand Total - 2,000,000 1,181,564 818,436 2.3 Key External Partnerships: Key external partnerships have been developed with Monsanto, DArT, Cornell University, Corteva The University of Queensland, HIPHEN, INRA-Avignon, CSIRO and Kansas State University. Monsanto have been driving many of the same objectives EiB is also targeting through a targeted project with IITA. Monsanto and EiB will work together to drive these objectives for IITA at an institutional level in addition to Monsanto committing to become an EiB Contributor, reflecting broader contributions to the Platform. This is proving to be an extremely valuable collaboration for many reasons. Monsanto have invested heavily in identifying and developing best practices which will be invaluable when shared with CGIAR breeding programs. Moreover, Monsanto have a very good reputation for executing breeding best practices, and their support for recommendations made to CGIAR breeding programs will contribute significantly toward their uptake in the CGIAR. Monsanto also have valuable -12- CGIAR Excellence in Breeding Platform Annual Report 2017 experience in the modernization CGIAR breeding programs through their work with the IITA Cowpea program. Across all modules, a meeting took place with representatives from Corteva. Outcomes of the meeting included Corteva committing as a contributor EiB, and the benefits of public-private collaboration through EiB were discussed, including the advantage of interacting with CGIAR breeding programs through a single entity, mutual interests in the area of pre-competitive breeding and development of future markets, and the creation of non-confidential knowledge. Potential areas for collaboration discussed included the sharing of Corteva knowledge and participation in communities of practice, co- investment in partner capabilities and use of DuPont Pioneer services, technical exchange programs, process documentation support, access to prior generation equipment and direct financial support. Further details to better define this partnership with Corteva will be finalized in 2018. The BPAT is managed by the University of Queensland. BPAT output is essential to the delivery of EiB objectives, being that BPAT recommendations form the foundation of action plans for each CGIAR Center to increase rates of genetic gains which EiB is tasked with enabling. As such, collaboration with the University of Queensland has been and continues to be extremely important. Cornell University is developing computation tools for genomic selection. Once developed, these tools will enable many of EiB’s objectives to be realized, particularly in modules 2, 3 and 5. Partnerships with HIPHEN and with INRA-Avignon, CSIRO and Kansas State University have been used to make progress on Module 4 objectives relating to remote-sensing imaging. 2.4 Cross-CGIAR Partnerships (CRPs and other Platforms): Excellence in Breeding works extremely closely with all CGIAR breeding centers, including AfricaRice, Bioversity, CIP, CIAT, CIMMYT, ICARDA, ICRAF, ICRISAT, IITA, ILRI, IRRI and WorldFish. In August CIMMYT DDGR Marianne Bänziger and incoming EiB Director Michael Quinn visited the headquarters of each Center, in addition to many regional offices, in order to establish better relationships. The visits were invaluable to create awareness and understanding of EiB, and to understand the individual and collective challenges and opportunities of the respective institutions. In 2017 the Expert Advisory Group met and set the following priorities for the CGIAR EiB Platform: • Cross-commodity learning – what works? • Access to expertise • Reducing redundancy • Reinvesting savings from previously redundant efforts or more effective approaches in better focused larger scale programs • Joint bargaining / better deals = pricing • Joint standards • Joint communication / stronger voice • Aligned proposals / attract the attention of donors 2.5 Monitoring, Evaluation, Impact Assessment and Learning (MELIA): • In 2017, Excellence in Breeding developed a results-based management framework to support strategic planning, monitoring, reporting, evaluation and learning. This framework builds on the EiB theory of change and includes a monitoring, evaluation, and learning plan, and indicators to monitor outputs and outcomes. • EiB was represented within the CGIAR Monitoring, Evaluation and Learning Community of Practice for the first time this year and began to work on issues related to measuring -13- CGIAR Excellence in Breeding Platform Annual Report 2017 development impact of the platforms, as well as consistent templates and tools for Phase II. The Community of Practice also provided excellent opportunities to share best practices and learning amongst monitoring, evaluation and learning specialists. • In 2017, EiB began to explore the use of a new management information system (MARLO- Managing Agricultural Research for Learning and Outcomes) in order to more easily plan and budget its work, monitor research progress, and report on Platform results in coming years. 2.6 Improving Efficiency: The adoption of high throughput genotyping services, as opposed to carrying out genotyping in-house, has improved efficiency in various CGIAR Centers. The cost savings of switching to HTPG is specific to each Center and crop, but user feedback indicates overall cost reductions of between 25 and 50%, due to reduced-cost outsourcing, better data quality and faster turnaround time. 3. Platform Management 3.1 Platform Management and Governance: No major changes to management and governance occurred in 2017. 3.2 Management of Risks to Your Platform: Programmatic Risks: Attracting the required staff to run the CGIAR EiB Platform took longer than expected, and many key positions remained open throughout 2017. An external headhunter was hired to assist in the recruitment of key Platform positions. Contextual Risks: In 2017 the CGIAR EiB Platform experienced no contextual risks. Institutional Risks: For the EiB CGIAR Platform, it is an institutional risk that Breeders are adequately funded and are willing to learn, adopt and adapt documented tools. Although the Platform is not a funder, through center visits it has identified bottlenecks affecting breeding programs. 3.3 Financial Summary: The financial status of the CGIAR EiB Platform is strong, in 2017 the Platform received US $2,000,000 from W1/W2 and closed with a carryover of $820,000 from W1/W2 funds. W3 funding for the period October 2017-September 2018 totals $1,866,811.90. Assuming the Platform receives $2,000,000 annually from W1/W2, EiB will reach a budget of $6M by 2020, as there is $4.8M budgeted from W3 (BMGF) for the period Oct 2019 – Sept 2020 and $5.2M for Oct 2020 – Sept 2021. Furthermore, the EiB will continue to look at other sources for additional funding. -14- CGIAR Excellence in Breeding Platform Annual Report 2017 TABLES Table A: Reporting against Platform Specific Indicators Comments (in relation Module Indicator Description to target, if one available) An online resource of validated tools and best practices, Infrastructure and functionality developed and implemented in knowledge and product resources documented following a "use the beta version of the portal. Implementation of the live version case" approach. Resources developed periodically of the portal will take place in 2018 as more content becomes reviewed/revised using a common framework. Public available. 2 communities implementing best tools and practices self-identify; All partners engaged in targeted implementation of high return to investment tools and practices across CG and NARS discovery and breeding programs. Clear knowledge of the range of best tools and practices available. Number of training resources developed and disseminated and EiB has adopted and will implement guidelines generated by the the number of courses/workshops conducted. CIMMYT Learning Management System (LMS). External material has been identified for the toolbox but needs to be reviewed, vetted and possibly modified before making available through the 2 toolbox. An EiB workshop was held in Africa in November addressing forward marker breeding applications, including DNA sampling, sample tracking and laboratory information management systems. -15- CGIAR Excellence in Breeding Platform Annual Report 2017 Development of data management systems is focused on A strategy for developing priority use cases has been developed 5 priority breeding use cases and coordinated across development and use cases prioritized. teams. Use of BrAPI-enabled high priority use cases. Peter Selby (BrAPI coordinator) was hired in the Fall of 2017. BrAPI 5 and local APIs developed and development remains ongoing. The strategy to implement year 1-2 case studies was developed. Breeding programs that routinely load phenotype and genotype Critical existing databases are BMS , B4R and the RTB databases (ie data into data management systems as part of routine breeding Cassavabase, Yambase, etc.). All member programs are aware of 5 practices. the existence of these databases. Further development of B4R is required to achieve adoption. Further work will be in 2018 and 2019 to ensure adoption. Development of tools are aligned with high priority use cases and To better understand what tools are required, what is currently coordinated across programs. Tools and databases are being used and the use cases that future tools need to support, a 5 accessible to all CGIAR breeding programs. Support the survey was conducted and summarized in 2017 (included in this development of databases and tools to complement and expand report). In addition, follow up surveys are underway for 2018 to the usefulness of existing bioinformatics initiatives. provide more detailed landscape analyses. Use of breeding views that provide breeders easy access to data Key analysis software has been identified and work is underway to needed for variety advancement and parental selection. develop open-source pipelines for trial analysis and candidate 5 selection. An EiB alpha release of a galaxy analysis pipeline has been achieved: http://galaxy-demo.excellenceinbreeding.org -16- CGIAR Excellence in Breeding Platform Annual Report 2017 Implementation of common ontologies and PUIDs for The AFS CRPs will be represented in the Big Data Platform Ontology germplasm, as indicated by BrAPI use. CoP through the M5 Breeding Data Management CoP being led by Kate Dreher. The Data Management CoP identified several 5 versions of UUID generators as the recommended system. More specific instructions on best practices are in preparation by the CoP. Use of protocols, manuals, and best practices for data Kate Dreher (CIMMYT) and Abhishek Rathore (ICRISAT) were 5 management and biometrics in Toolbox. Access to prioritized elected as the first CoP leaders. Best practices to first be defined by biometrics and bioinformatics advice, services and resources. a community of practice (CoP). Table B: Status of Planned Milestones [Please include the status update on the planned milestones (i.e., complete, extended or cancelled). If completed, please include evidence; if extended or cancelled, please provide a rationale.] 2017 milestones 2022 Platform outcomes (from status Provide evidence for completed milestones** or Module Milestone* proposal) (Complete, explanation for extended or cancelled Extended or Cancelled) Creation of clear product profiles, a (i) Members document current product Extended Part-time Leader was not able to accomplish in stage gate process “from breeding profiles and existing GxE information in 2017. Issue has been addressed by securing a full- cross-to-farm”, and appropriate Toolbox time leader for module 1 on May 7, 2018. breeding schemes commensurate (i) Members agree on standardized templates 1 with level of investment, best and approaches for defining and further practices and tools available results improving product profiles, considering in accelerated breeding cycles and gender and market informed seed-to-fork rates of genetic gain per unit time value chains, information about the target -17- CGIAR Excellence in Breeding Platform Annual Report 2017 that are 25% greater than current population of environments (TPE), and clear approaches. variety replacement strategies. (i) Member breeding programs establish a Extended Part-time Leader was not able to accomplish in format and process for implementing a stage 2017. Issue has been addressed by securing a full- gate system in their breeding program time leader for Module 1 on May 7, 2018. (ii) Best practices discussed and developed 1 for appropriate incentivization of breeding team members based on individual and breeding team performance relative to overall genetic gain and varietal replacement indicators and metrics. (i) Members upload methods and results for Extended Part-time Leader was not able to accomplish in current genetic gains assessments in Toolbox. 2017. Issue has been addressed by securing a full- (ii) Review current approaches to assessing time leader for Module 1 on May 7, 2018. rate of genetic gains (ROGG) within member 1 programs, private companies and published 2017 activities included working with CGIAR and literature. (iv) Face-to-face workshop among Private Sector Quantitative geneticists on breeders, socio-economists and seed developing standard operating procedures to specialists about purpose and approaches for assess breeding program success and genetic gain germplasm-related impact assessment assessments. Breeding programs access advice or visit to Extended Module 1 concepts have been introduced to best-practices sites on a self-funded basis various CGIAR and NARS breeding teams. 1 (i) Benchmark which CGIAR breeding Extended EiB is in close contact with BPAT. programs have BPAT assessments completed; 1 (ii) together with BMGF develop plan for prioritization and implementation of BPAT assessments with CGIAR breeding programs (i) Center leadership and participating Extended In 2017, we created two forums representing a 1 breeding programs sign membership combination of private and public breeders. The -18- CGIAR Excellence in Breeding Platform Annual Report 2017 agreement documenting commitment to the interaction was not good because the private EiB modernization process. EiB resources sector participants did not share while the (time, financial resources) will be directed at competition was present. We will be developing a members only. different format in the future for greater success. (ii) CGIAR research leaders participate in workshops with private sector breeding managers to gain an understanding of modern breeding program management. (i) Together with BMGF develop a plan for the Cancelled BMGF would prefer to prioritize the BPAT reviews prioritization and implementation of BPAT according to their own internal interests. assessments with up to 4 pilot NARS breeding programs. The other sub-milestones are covered elsewhere in (ii) Membership agreements are signed with the work plan. NARS research managers and breeding programs documenting commitment to the 1 EiB modernization process. EiB resources (time, financial resources) will be directed at members only. (iii) NARS research leaders participate in workshops with private sector breeding managers to gain an understanding of modern breeding program management. Increased rates of genetic gain (i) Common infrastructure and frameworks Complete Infrastructure and functionality developed and through use of best practices, for documentation of best practices, tools, implemented in the beta version of the portal. optimization of breeding strategy workflows and resources developed. Link to Implementation in the live version of the portal will 2 and more effective use of resources user review system. be conducted in 2018 as more content becomes (time, finances). (ii) Restricted domain developed for available. members documenting their breeding programs and progress. -19- CGIAR Excellence in Breeding Platform Annual Report 2017 Formation of / communication with CoPs Extended Development of CoP prior to placement of module 2 from relevant members of each module. 2 lead would be premature as the CoP would lose interest due to lack of engagement. Draft review guidelines and infrastructure Extended Limited need for this at end of 2017 due to limited developed. material on the toolbox at that time. Discussions 2 for guidelines have occurred and are largely finalized and are being documented Infrastructure still needs to be developed. (i) Development of best practice (i) Complete (i) EiB has adopted and will implement guidelines documentation for e-learning based on (ii) Extended. generated by the CIMMYT LMS 2 materials used at regional workshops (ii) External material identified but needs to be (ii) Identification of, and links to relevant reviewed, vetted and possibly modified to make external e-modules and courses appropriate for the toolbox. (i) Use cases of successful implementation of Extended Lack of capacity to achieve these milestones due to predictive tools providing value towards lack of headcount generally and lack of Module 2 breeding for product profiles documented. lead specifically. 2 (ii) Use cases of failed attempts of development of predictive tools documented. Members document trait and core breeding Extended Draft template for members to document pipelines pipelines in Toolbox developed. 2 Lack of capacity to achieve this milestone due to lack of headcount generally and Module 2 lead specifically. Members document breeding strategy in Extended Draft template for members to document pipelines Toolbox. developed. 2 Lack of capacity to achieve this milestone due to lack of headcount generally and module 2 lead specifically. Physical and virtual blue-sky discussions Cancelled. Low priority given to this at this time considering 2 associated with scientific meetings, to raise the size of opportunities to improve breeding with -20- CGIAR Excellence in Breeding Platform Annual Report 2017 and discuss ideas for high-payoff approaches currently available methods and technologies and discuss and design the incubation of before considering "game changers". project ideas. Allocation of modest resources to validate technologies in the incubator while jointly seeking additional funding to test more substantive “game changers”. At least 5 best practices/use cases and tools Extended Could not be achieved with part-time module lead. developed and documented. Going forward this is being addressed by applying 3 a full-time staff in Module 3 from the last half of 2018. Cost-benefit analysis approaches developed Extended Could not be achieved with part-time module lead. and tested with 2 breeding programs. Going forward this is being addressed by applying (iii) Members develop genomics data a full-time staff in Module 3 from the last half of 3 inventory for their breeding program, 2018. including marker type, trait value, trait genetic variance, range of genetic variance accounted for, costs etc. (i) Best practices and tools developed and Extended Could not be achieved with part-time module lead. documented. (ii) Key program parents Going forward this is being addressed by applying profiled at high density and characterized for a full-time staff in Module 3 from the last half of diagnostic SNPs. (i) Develop use cases and 2018. develop/contribute to implementation 3 guidelines for genotyping application in discovery and breeding. (ii) Update and refine existing documents, remove those no longer appropriate/applicable or when reviews are negative. (iii) Contribute to courses and workshops. $2.00 SNP genotyped sample; $15 genome Extended $2.50 per SNP genotype samples available through 3 profile. HTPG. Low cost genome profile available through IGSS. -21- CGIAR Excellence in Breeding Platform Annual Report 2017 400K SNP genotyped samples; 50K genome Partially profiles. (i) Obtain and aggregate AFS demand completed for supplies and services. Determine cross- through HTPG. AFS; Genotyping platform preferences, Minimum genotyping quality criteria, Maximum permissible turnaround time for genotyping applications, Minimum number of samples required (at defined unit costs), Minimum number/volume of supplies required, Minimum marker conversion rate, 3 Number of markers for marker conversion, etc. (ii) Use collated demand information to broker potential arrangements with service providers and solicit pricing feedback from AFS. (iii) Finalize brokering of supplies and services and obtain minimum order commitments from AFS. (iv) Obtain feedback from service providers and AFS clients and document issues, concerns and positive feedback collating to form a review for the Trait Discovery and Breeding Toolbox. (iv) Enlist expertise in marker conversion Cancelled. This is generally offered as part of the service by 3 from SSRs/INDELS to SNP-based platforms service providers. Prospect newer methods/approaches for Extended. Could not be achieved with part-time module lead. sampling/genotyping; use inputs from Going forward this is being addressed by putting on participating AFS, ARIs, private sector a full-time person in Module 3 from the last half of 3 partners and technology 2018. developers/providers; evaluate costs and constraints for application in discovery and breeding. Prepare annual review paper for -22- CGIAR Excellence in Breeding Platform Annual Report 2017 posting in the Trait Discovery and Breeding Toolbox. Lower-cost, better targeted (i) Process engineering specialist hired. Extended. Could not be achieved with part-time module lead. phenotypic data supports larger, (ii) A completed diagnosis of the gaps, needs Going forward this is being addressed by applying more cost-effective programs. and best approaches to increase plot two full-time staff in Module 4 from the last half of throughput/reduce costs through high- 2018. throughput phenotyping, mechanization, 4 automation. (iii) Identification of existing best practices and equipment in use by various programs. (iv) Community of practice for high through- put phenotyping established (i) Take stock of current use of laboratories, Extended Could not be achieved with part-time module lead. their capabilities and costs; prioritize needs Going forward this is being addressed by applying 4 based on member survey and feedback; (ii) two full-time staff in Module 4 from the last half of establish community of practice among NIRS 2018. users/internal service providers (i) Survey to assess phenotype and (i) Complete; (i) Survey document, results, report provided; (ii) environmental data collected, adoption of (ii) Complete; Meeting purpose and notes, high-through-put tools, GxExM and gene-to- (iii) Complete Meeting presentations on the EiB portal, and phenotype methods, and barriers to adoption Action plan report; (iii) Subscription to IPPN 4 in coordination with BPAT. (ii) Workshop on network. existing practices, with ARI and private sector participation; identification of quick wins. (iii) Join and participate in existing plant phenotyping networks. Consult with breeders and ARIs to identify Complete and Proposal draft developed. 4 tools for capture and analysis of high- interrupted throughput data – Priority setting Consult with breeders and ARIs to identify Extended. Could not be achieved with part-time module lead. 4 approaches for GxE analysis – Priority setting. Going forward this is being addressed by putting on -23- CGIAR Excellence in Breeding Platform Annual Report 2017 2 full-time staff in Module 4 from the last half of 2018. Bioinformatics tools that support Establish overall strategy and prioritize Completed. It should be noted that development of strategy is automation, data integration and pipeline/breeding use case studies and a work in progress all throughout development of 5 decision making are fully integrated related tools. data management systems as new use cases are for use in AFS breeding networks. identified. Having made that point, a strategy has been developed and use cases prioritized. (i) BrAPI coordinator hired. ii) Reference Completed (i) Peter Selby was hired in the Fall of 2017. client/server developed to test compliance. (ii) Strategy to implement year 1-2 case studies 5 (ii) Strategy to implement the Year 1-2 case developed. studies developed. (iii) Implementation of (iii) BrAPI and local APIs developed, with further BrAPI and local APIs for different systems. development ongoing. (i) Exposure to and adoption of appropriate Completed. Critical existing databases are BMS, B4R and the databases in member breeding programs. RTB-bases (i.e. Cassavabase, Yambase, etc.). ii) Identify existing systems that are critical to All member programs are aware of the existence of 5 achieving the EiB's objectives across breeding these databases. Further development of B4R is management systems. required to achieve adoption. Further work will be in 2018 and 2019 to ensure adoption. (i) Report on the current landscape of (i) Completed (i) The initial survey and report is included in the databases, bioinformatics annual report. Follow up surveys are underway to capabilities/software, and biometric provide more detailed landscape analyses capabilities/software; (ii) Documented gap 5 analysis for the Year 1-2 case studies; (iii) Existing databases and tools assessed and updated. (iii) Development or acquisition of new database and tools. (i) Identify key analyses and data required for Extended. Development efforts for analysis tools for selection candidate advancement and candidate selection are less centralized than for 5 parental selection (ii) Catalogue existing database development. Thorough cataloguing of analysis tools and pipelines. (iii) Initiate open- all analysis software may not be an effective approach. Key analysis software has been -24- CGIAR Excellence in Breeding Platform Annual Report 2017 source collaboration on breeding identified and work is underway to develop open- optimization suite. source pipelines for trial analysis and candidate selection. An EiB alpha release of a galaxy analysis pipeline has been achieved: http://galaxy- demo.excellenceinbreeding.org (i) Crop and Agronomy Ontology CoP (i) Completed; (i) The AFS CRPs will be represented in the Big Data incorporates reps from AFS CRPs; (ii) identify (ii) Completed Platform Ontology CoP through the M5 Breeding system for generating PUIds for breeding Data Management CoP being led by Kate Dreher. 5 germplasm. (iii) Crop ontology documented (ii) The Data Management CoP identified several for Tier 1 crops. (v) Strategy for GUIDs versions of UUID generators as the recommended defined. system. More specific instructions on best practices are in preparation by the CoP. (i) CoP for statisticians and bioinformatics (i) Completed; (i) Kate Dreher and Abhishek Rathore were elected leaders identified, participant list compiled, (ii) Extended as the first CoP leaders. Initial meetings were held and meetings initiated. (ii) First Annual in November and December of 2017. (ii) Due to Bioinformatics and Biometrics "Hackathon". travel schedules and availability of key participants (iii) Core operational guidelines for the hackathon was moved to February 2018. bioinformatics and biometrics defined. (iv) Common BrAPI defined. (v) Capacity development strategy for bioinformatics and software adoption developed. (v) Support 5 capacity building and the evaluation of new bioinformatics and biometrics tools and approaches in collaboration with distinct user groups and use cases prioritized in Modules 2-4. (vi) Training workshops for biometricians in CGIAR target countries to expand the number of resource persons. (vii) Broker access to proprietary software and computational capacity on a pay-per-use basis. -25- CGIAR Excellence in Breeding Platform Annual Report 2017 * Milestones include both outputs, output use and outcomes along the impact pathways. ** Provide link to any relevant open accessible document. Table C: Cross-cutting Aspect of Outputs [Please present % of outputs with principal (scored 2), significant (scored 1), and not targeted (scored 0), for gender, youth and capacity development and total overall number of outputs] Number (%) scored Number (%) Number (%) Total overall number Cross-cutting 2 (Principal) scored 1 scored 0 of outputs (significant) Gender 5% 0% 95% 34 Youth 0% 80% 20% CapDev 0% 100% 0% Table D: Common Results Reporting Indicators Table D-1: Key Platform Results from 2017, in Numbers Sphere Indicators Data Comments I1/I2*. Projected uptake (women and men) N/A Some CRPs may have some /hectares from current CRP investments (for data here for 2017, which innovations at user-ready or scaling stage only – would be welcome, but not see indicator C1) required I3. Number of policies/ investments (etc) modified N/A (e.g. Example of major in 2017, informed by CGIAR research achievements) -26- Influence CGIAR Excellence in Breeding Platform Annual Report 2017 C1. Number of innovations by phase - new in 2017 N/A C2. Number of formal partnerships in 2017, by Monsanto, University of Queensland, DArT, CIP, CIAT, CIMMYT, purpose (ongoing + new) AfricaRice C3. Participants in CGIAR activities 2017 In 2017, 81 people were trained, 22% of the people trained were (new +ongoing) women. C4. People trained in 2017 In 2017, 81 people were trained, 22% of the people trained were No Limited training women. The trainings took place in Kenya and Uganda. The conducted in 2017 due to lack organizations represented included: ICRISAT, IITA, IRRI, CIMMYT, of head count. Karlo, ARI, EIAR, NaCCRI, SARI, NaSSRRI-Uganda, DarT, Cassava- Tanzania, and the Ghana National Program. C5. Number of peer-reviewed publications None. Publ Publications are not a core objective of the Platform. C6. Altmetrics New indicator being introduced in 2018 – details tbc *Please note: I = Sphere of Influence and C = Sphere of Control Table D-2: List of Platform Innovations in 2017 (From indicator #C1 in Table C-1) Title of Phase of Novel or Contribution Geographic scope: for innovations in innovation research adaptive of Platform phases AV* or USE* only (minimum * research (sole, lead, (one country, region, multi-country, required for contributor) global) clarity) None. * Phases: PC - proof of concept, PIL - successful pilot, AV - available/ready for uptake, USE - uptake by next users. -27- Control CGIAR Excellence in Breeding Platform Annual Report 2017 Table E: Intellectual Assets Year Applicant(s) / Patent or Additional Link or PDF of Public communication * For patents, please indicate: (a) type of filling: reported owner(s) PVP Title information published relevant to the provisional / non-provisional; national direct, national (Center or partner) * application/ application/registration designated; multi-territory; (b) patent status: filled, registration pending, matured to non-provisional, discontinued, 2017 None None N/A N/A N/A registered or lapsed; (c) application / registration; (d) date of filling; (e) Date of Registration; (f) Date of Expiry / renewal * For PVP, please indicate: (i) variety name, (ii) status, (iii) country; (iv) application/registration number, (v) date of filling, (vi) date of registration/grant; (vii) date of expiry/renewal, (viii) breeder and crop Table F: Main Areas of W1/2 Expenditure in 2017 Optional Expenditure area * Estimated percentage of Space for your comments total W1/2 funding in 2017** [please remove notes below] Planned research: principal or sole funding source Planned research: Leveraging e.g. to strengthen the synthesis and international public goods nature of outputs by Platforms; or to W3/bilateral funding respond to changes in research conditions including fluctuations in funding. Catalyzing new research areas e.g. foresight, proof of concept studies for novel areas of work e.g. stand-alone programs, work by PMU, funding gender ‘add ons’ to other projects, and Gender research projects tagged as ‘principal’ for gender. Research projects tagged with a ‘significant’ gender tag should be included under one of the first three rows above (research) -28- CGIAR Excellence in Breeding Platform Annual Report 2017 Youth As for gender Capacity development As for gender Start-up or maintenance of partnerships (internal or external) Monitoring, learning and self- evaluation Evaluation studies and Impact Includes ex-ante assessments if these are specific studies, otherwise include under previous row Assessment studies e.g. immediate unplanned response to a new virulent disease, or moving germplasm collections Emergency/contingency as a result of conflict Other TOTAL FUNDING (AMOUNT) *use these categories wherever possible, delete unneeded rows and add rows if none of these are suitable. **we recognize that (i) some funding may fit more than one category but please try to apportion funding to its principal use and (ii) percentages may not add up to 100% -29- CGIAR Excellence in Breeding Platform Annual Report 2017 Table G: List of Key External Partnerships [Please list up to five important partnerships for 2017 for each Module, using the following table. An agreed list of partners’ types and areas of partnerships will be provided in the common results indicators manual (available early 2018).] Stage of Module Name of partner Partner type* Main area of partnership* research* 1 PC Abacusbio Ltd Economic Trait Involved in Early Discussion with developing an Economic Trait Assessment Study. (Peter Amir) Assessments Contingent on the hiring of the Product Manager in Kenya. 1 PC Syngenta Foundation & Client Based – Business Leveraging Syngenta sponsored projects about creating impact in the CGIAR breeding Market Edge Consulting of Plant Breeding programs. 1 PC Roy Cantrell Breeding Program Collaboration on process & potential teaching opportunities. Management From a Private Company Perspective 1, 2, 3, 4 Ongoing Corteva Private Corteva have made a commitment to be EiB contributors. Details that define this partnership & 5 are being finalized in 2018. 1, 2, 3, 4 Ongoing Monsanto Private Through a targeted project with IITA Monsanto have been driving many of the same & 5 objectives EiB is also targeting. Monsato and EiB will work together to drive these objectives for IITA at an institutional level in addition to Monsanto committing to be an EiB Contributor contributing to the platform more broadly. 5 DArT CIP, CIAT, CIMMYT, AfricaRice 5 Cornell University Collaborator Development of computations tools for implementation of genomic selection 4 Pilot HIPHEN Private Remote-sensing imaging 4 Pilot INRA-Avignon / CSIRO / Public Research Remote-sensing imaging KSU 1,2,3,4, University Queensland Public BPAT assessments conducted. EiB has a role to enable breeding teams to implement & 5 recommendations from BPAT assessments. * See instructions in the common results indicators manual (available early 2018). -30- CGIAR Excellence in Breeding Platform Annual Report 2017 Table H: Status of Internal (CGIAR) Collaborations between the Platform and Programs and among Platforms Brief description of collaboration (give and take between the Platforms and CRPs) and value added* Relevant Module Name of CRP or Platform CIP, CIAT, CIMMYT, AfricaRice These centers have signed EiB membership agreements which describes their commitment to work with EiB to 1, 2, 3, 4 & 5 and ICRISAT. implement their action plan leading to improvements in rates of genetic gain and/or greater scale of impact. Big Data Platform EiB was preparing for collaborations with the Big Data Platform in areas in which the platforms can work 1, 2, 3, 4 & 5 synergistically and/or that there are overlapping objectives. Examples include in the areas of environmental characterization (for genotype by environment modelling and for formation of product profiles); processing and interpreting high throughput phenotype data; handling, collating and interpreting data relating to what farmers are growing to inform product profiles and impact studies; and, to bring genomic, geographic, environmental and phenotypic data together for the purpose of better targeting of genebank accessions. Gender in Breeding platform EiB was preparing in 2017 to engage closely with the Gender in Breeding to ensure that EiB gives a primary Primarily 1 and consideration is given to gender and in particular that primary consideration is given to gender. indirectly 1, 2, 3, 4 & 5 Genebanks Platform EiB has been preparing to engage with the Genebanks platform to provide value to them in particular through the 3,4 & 5 tool and service-oriented modules to better enable their genotyping, phenotyping, data management and biometrics. *e.g. scientific or efficiency benefits -31- CGIAR Excellence in Breeding Platform Annual Report 2017 Table I: Monitoring, Evaluation, Impact Assessment and Learning Table I-1: Status of Evaluations, Impact Assessments and Other Learning Exercises Planned in the 2017 POWB Studies/learning exercises in 2017 (from POWB) Status Comments N/A N/A No evaluations, impact assessments or learning exercises were conducted, as EiB is still getting set up and has not yet begun to undertake many of its activities. Table I-2: Update on Actions Taken in Response to Relevant Evaluations (IEA, CCEEs and Others) Name of the Recommendation By By Management response – Action Plan Status evaluation whom when Evaluation of All CRPs should have a distinct partnership strategy N/A partnerships in and accompanying operational plan. CGIAR 2017 Evaluation of the Given that close linkages between the Genebank SMO Response: Even if protocols for data exchange and Genebanks CRP Platform and the Excellence in Breeding and Big use are primarily determined by Center implementation 2017 Data Platforms will be essential for strengthening of CGIAR Open Access policy, the Board emphasizes the genetic conservation and use, the Genebank expected key role to be played by the Genebank Platform Platform Management Team should agree with in connecting and articulating exchange of data and the managements of the other two Platforms information between the three Platforms. These efforts appropriate protocols for data exchange and use. will be reported in the respective Platform Annual This coordination will take advantage of CGIAR’s Reports. unique position of spanning the whole range of activities from conservation to use, and minimize -32- CGIAR Excellence in Breeding Platform Annual Report 2017 the Platforms developing as silos in isolation from Genebank CRP Response: The Crop Trust and MT agree one another. with this recommendation, although it should be noted that protocols for data exchange and use are primarily determined by Center implementation of CGIAR Open Access policy. Linkages are being carefully forged between the three Platforms. Genebank Platform representatives have been appointed to and are participating in the Expert Groups in the Excellence in Breeding Platform and joint activities are being planned with the Big Data Platform. 2014 IEA Review Publish on CRP websites the names of members Making minutes available on-line would require having MAIZE Ongoin Substantial on CRP and their qualifications, posting meeting agendas two versions of the minutes: an edited public version CRP g Implement Governance and and minutes, and otherwise sharing important (without confidential personal or business information) Team ation Management information. and an unedited version restricted to internal purposes and information to boards, Center senior management and main partners. -33- CGIAR Excellence in Breeding Platform Annual Report 2017 Table J: Platform Financial Report Amounts are in US$ Thousands Planned budget 2017 Actual expenditure 2017* Difference W1/2 W3/bilateral Total W1/2 W3/bilateral Total W1/2 W3/bilateral Total Module 1 1035 374 1409 199 100 300 836 274 1110 Module 2 249 69 318 213 3 217 36 65 101 Module 3 124 37 161 126 0 126 -2 37 35 Module 4 154 75 229 77 0 77 77 75 152 M5 240 65 305 238 0 238 2 65 67 Platform 197 79 277 336 0 336 -138 79 -59 Management & Support Cost Platform Total 2000 699 2699 1190 104 1293 810 596 1406 The source of the information is based on the L Series report submitted to the CGIAR. -34- CGIAR Excellence in Breeding Platform Annual Report 2017 Annexes Annex 1: Module 5 IT infrastructure survey results Yes No Don’t Know Does you center host a computational 55% 18% 28% cluster/Do you have access to cloud computing resources? Not Accessible Difficult to Access Accessible Easily Accessible How accessible is your organizational data 5% 21% 58% 16% which is required to do your job? Computational resources Computational resources are Computational resources exist but are not are excellent adequate adequate Do you have computational resources to 10% 45% 45% effectively do your job? Very Reliable Somewhat Reliable Unreliable Is your Internet connectivity reliable? 42% 55% 3% Challenging Somewhat Challenging Easy Data transfer between institutional systems is 32% 57% 11% (e.g. data on paper, slow file transfer, physical movement of hard drives) -i- CGIAR Excellence in Breeding Platform Annual Report 2017 Annex 2. Module 5 Data accessibility and decision support survey results Strongly Disagree Neither Agree Strongly Disagree Agree I have easy access to data needed to make advancement decisions. 7% 24% 27% 34% 7% It is easy to access historical performance on key varieties. 13% 37% 29% 17% 3% It is easy to trace advancement decisions on varieties. 7% 38% 29% 21% 4% It is easy to retrieve pedigree history on varieties/animals. 7% 24% 29% 34% 7% I have easy access to data on varieties developed in other breeding programs. 23% 40% 20% 16% 1% I have easy access to genotypic/genomic data generated in my institution on varieties. 14% 36% 20% 17% 13% I have access to relevant environmental information on experimental sites. 10% 14% 27% 37% 13% All of my experiments are analyzed in time to make advancement decisions. 3% 21% 29% 33% 14% I have access to biometrics consulting/software need to properly design and analyze 9% 14% 18% 47% 13% experiments. I have access to bioinformatics software/consulting to analyze genomic data. 11% 13% 28% 33% 16% I have access to software/consulting to perform QC on phenotypic and genomic data. 6% 17% 38% 29% 10% Unique ids and standard ontologies make it easy to merge data across programs and years. 8% 11% 22% 42% 18% All data is cleaned using appropriate QC methods. 8% 19% 42% 24% 8% Both cleaned and raw data are easily accessible. 9% 33% 32% 19% 8% It is straight forward to program analysis pipelines against databases. 6% 35% 38% 15% 5% I have easy access to information needed to make parental selections.* 5% 15% 50% 25% 5% *Indicates the question was added to an updated version of the survey (approximately 25% of the total respondents completed the updated version of the survey) -ii- CGIAR Excellence in Breeding Platform Annual Report 2017 Annex 3. Module 5 Breeding process support survey results Strongly Disagree Neither Agree Strongly Disagree Agree It is easy to access verified pure seed sources 9% 15% 23% 45% 8% for active varieties. I have adequate IT support for breeding 8% 30% 28% 25% 8% workflows and processes. I have access to GIS and software for site 16% 29% 25% 25% 6% selection and field mapping. I have access to effective field data collection 5% 35% 20% 35% 5% tools and software.* It is easy to track samples from the field to 12% 15% 29% 37% 7% the lab. Experiments rarely fail due to impure or 13% 17% 25% 38% 8% incorrect parents being used in crosses. I have access to software/consulting to 6% 17% 38% 29% 10% perform QC on phenotypic and genomic data. Inventory management tools and software 0% 30% 70% 0% 0% are routinely used.* Barcoding is routinely use for plots, seed 10% 10% 20% 55% 5% packets, tissue samples and DNA samples.* *Indicates the question was added to an updated version of the survey (approximately 25% of the total respondents completed the updated version of the survey) -iii- Breeding program excellence. A standard breeding program performance management system to monitor successes from the lab to the farmers’ fields, highlighting strategic areas for research and investment. Optimizing breeding schemes. Access to support and knowhow to optimize breeding schemes, respond appropriately to changes in resources and to extract maximum value from implementation of new technologies, tools or services to the breeding process to achieve the highest possible rate of genetic gain. Genotyping / sequencing tools and services. Access to genotyping services at reduced cost, and support for breeding programs to optimise the use of genomic data in their work. Phenotyping tools and services. Information about new tools and approaches to quantify plant and animal traits, access to services and shared infrastructure, and support the routine use of cutting-edge phenotyping in breeding programs. Bioinformatics, biometrics and data management tools and services. Access to integrated bioinformatics tools and biometrics support that allow breeding programs to harness the power of genotype, phenotype and other data. The Toolbox. An online portal for tools, services, advice and training enabling breeding teams to successfully identify and incorporate new approaches into the breeding process, from trait discovery to cultivar development. 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