Product Line 2.1. Breeding informatics, high-throughput marker applications, and multi-environment testing
The success of modern rice breeding depends on the use of accurate selection criteria derived from multiple sources of information. To implement marker-assisted breeding effectively, an integrated breeding platform is required that has an efficient information system for managing breeding logistics and information from different sources (phenotypic, genetic, genomic, etc.) and provides efficient analytical pipelines and decision support tools. This can lead to a shortening of the breeding cycle while minimizing resource requirements. An efficient system for genotyping markers tightly linked or diagnostic of trait-controlling genes is also needed. Phenotypic information needs to be collected from environments that are representative of the target population of environments (TPE) to reveal and explore genotype-by-environment interactions (GEI). Efficient multi-environment testing (MET) networks are needed for determining the stability and adaptability of genotypes and the discrimination power of specific environments. MET networks can also facilitate the exchange of germplasm among breeding programs, which can potentially speed up the development of new varieties while increasing genetic diversity.
Breeding efficiency can be increased by using more accurate selection criteria, shortening breeding duration, and minimizing resource requirements. Approaches for improving the quality of phenotyping and genotyping information are efficient management of breeding logistics, well-designed and well-managed MET networks, and an efficient genotyping system for tightly linked or functional markers of trait-controlling genes. An optimal breeding strategy in terms of duration and resource requirements can be designed using appropriate decision support tools. A suite of decision-making tools will be developed for all major breeding methods applicable to rice such as cross selection, backcrossing, gene pyramiding, and recurrent selection, including genomic selection.
2.1.1. Integrated breeding platform with rice-specific marker applications and decision tools.
IRIS content will be greatly improved through quality checks, reorganization of existing data sets, and uploading of well-curated historical data sets. Efficient analytical pipelines will be developed for predicting breeding value (genetic merit) using pedigree, marker, and phenotypic data. A suite of decision support tools will be developed to assist in the design of efficient marker-/genomics-assisted breeding strategies. Decision support tools will be developed through collaboration with the Integrated Plant Breeding Platform (IBP) project of the Generation Challenge Program.
2.1.2. Global rice germplasm information system to support rice breeding
A global rice information system will be developed that integrates phenotypic data with genetic, genomic, and genotypic data with breeding decision support tools to support the implementation of modern rice breeding strategies. Data integration is one of the key components in developing breeding informatics. The system includes data curation tools, a data-processing pipeline, Web visualization, and simple data-mining tools. The breeding decision support tools (2.1.1) will also be migrated into the integrated data environment. This will add critical value through Web-based data access and use to the key products of the IBP project.
2.1.3. High-throughput SNP genotyping platform for breeding applications
We will establish high-throughput SNP marker platforms at IRRI (or an associated lab in Asia) and CIAT to provide SNP marker development and genotyping services to GRiSP researchers and public- and private-sector partners. These facilities will greatly accelerate the application of SNPs to genetic research and breeding, including DNA fingerprinting, mapping, and marker-assisted selection. Low-cost SNP fingerprints for INGER nominations, breeding lines, and released varieties will enable quality control, seed purity testing, and tracking adoption rates. An efficient genotyping platform for SNPs that are diagnostic for important traits will also be developed and diagnostic SNP markers for key traits will be validated, optimized, and made available for deployment in breeding programs.
2.1.4. Multi-environment testing (MET) and international germplasm evaluation (INGER)
The new MET system will be a systematic and multistage testing scheme for promising breeding lines developed by GRiSP breeding programs. To be managed by GRiSP, MET will involve public- and private-sector partners at the key locations. This will allow for products to be channeled quickly into the right target environments and markets, while generating valuable feedback from farmers, millers, consumers, and other stakeholders in the public, private, and NGO sector. Through INGER, NARES can exchange superior materials among themselves for release directly to farmers or use in hybridization. Aside from seeds, INGER will facilitate the worldwide exchange of nonseed biological materials and breeding-related information. In Africa, INGER will be embedded in the Africa Rice Breeding Task Force. This task force will be established to regroup scarce human resources devoted to rice breeding in Africa and it will aim to achieve higher rice productivity through (1) the identification of required plant types responding to farmers’ needs and consumers’ preferences in well-characterized target populations of environments; (2) establishment of a regional rice variety testing network using extensive METs and centralized G × E analyses; (3) development of accelerated and regionally accepted varietal release procedures; and (4) development of alternative and effective models for seed production systems.
The next users of breeding informatics and germplasm are rice breeders in GRiSP, the private sector, and NARES. The final users are farmers for varieties released through the MET/INGER system and the Africa Rice Breeding Task Force. The availability of high-quality phenotypic data on key agronomic traits and access to an efficient genotyping system and computing facilities will increase breeding efficiency. The product line will have a close linkage with theme 1 activities related to databases and seed distribution. Established consortia such as CURE for the unfavorable rice environments of Asia and IRRC for the favorable environments will link improved germplasm with appropriate management practices and cropping systems. The Africa Rice Breeding Task Force will greatly stimulate the uptake of new varieties in and beyond AfricaRice’s 24 member states. Germplasm from theme 1, management practices from theme 3, and seed production and dissemination strategies from theme 6 will be linked with theme 2. Linkage with nationally and internationally funded development projects will facilitate delivery of improved varieties to farmers (theme 6).
The breeding informatics activities (2.1.1 and 2.1.2) are currently partially funded by the GCP/BMGF IBP project (about $700,000 for the next 2 years). A one-time investment is required to develop the facilities for high-throughput SNP genotyping. Some work on trait-specific SNP marker development is funded by the Syngenta-IRRI SKEP project ($300,000 for 2010-12). The work on product 2.1.3 will be partially supported by the Japan Rice Breeding project and BMGF-STRASA, BMGF-GSR, and BMGF/USAID-CSISA projects. This activity will require infusion of funds to NARES partners to support the key testing sites and generate high-quality data at about $5,000 per site per season. The INGER component (nurseries and seed exchange) will be partially funded by STRASA and GSR projects. Additional funding will be required to support all three products under this product line.