27-1 Progress and Challenges in the Use of High-Density Genetic Markers by CGIAR Breeding Programs to Increase Genetic Gains for Major Food Crops in the Developing World.

See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Symposium--Meeting the Challenge: Genotyping Diverse Germplasm and Providing Tools for Crop Improvement
Sunday, October 21, 2012: 2:30 PM
Duke Energy Convention Center, Room 264, Level 2
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Gary Atlin1, Edward S. Buckler2, Jean-Luc Jannink3, Susan R. McCouch4, Vanessa S. Windhausen5, Raman Babu6, Jose Crossa7, Marco Lopez7, Jeffrey Endelman3, Rajeev Varshney8, Hei Leung9, Charles Hash10, Yoseph Beyene11 and Kassa Semagn11, (1)Bill & Melinda Gates Foundation, Seattle, WA
(2)Institute for Genomic Diversity, USDA-ARS/Cornell University, Ithaca, NY
(3)USDA-ARS, Robert W. Holley Center for Agriculture and Health, Ithaca, NY
(4)Plant Breeding and Genetics, Cornell University, Ithaca, NY
(5)Universitat Hohenheim, Stuttgart, Germany
(6)CIMMYT, Hyderabad, India
(7)CIMMYT, Texcoco, Mexico
(8)ICRISAT, Hyderabad, India
(9)IRRI, Manila, Philippines
(10)GT-Biotechnology, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
(11)CIMMYT, Nairobi, Kenya
The breeding programs of Consultative Group on International Agricultural Research (CGIAR) centers are beginning to use high-density genotyping (HDG) technology, ranging from relatively small SNP arrays to very large chips and genotyping-by-sequencing (GBS) technologies that detect hundreds of thousands of polymorphisms.  Low cost HDG will permit the integration of genotypic information across multiple populations, allowing faster localization of useful QTL alleles and generating very large datasets for training of genomic selection (GS) models. Most use to date has been for association mapping and diversity studies, but HDG is not yet used routinely for genomic selection in CGIAR centers.  The CIMMYT Global Maize Program is piloting the implementation of HDG in its breeding to support GS, which has the potential to reduce breeding cycle time and increase rates of gain.  Initial results in maize indicate that GS accuracy will be sufficient for identifying parents with high breeding value for rapid-cycle marker-based recurrent selection, but may not be  for predicting phenotypic value. The situation may be different in other crops.  Delivering useful genomic predictions to breeders to support selection decisions will require substantial improvements in the integration of genotypic, phenotypic, and pedigree data in all the major CGIAR breeding programs, and the costs of DNA extraction and genotyping will need to be reduced. Large investments in breeding informatics capacity and DNA extraction systems will be required that may be beyond the capacity of most public and private sector breeding programs in the developing world.  Centralized genotyping and breeding informatics services may be the most effective approach for delivering the benefits of HDG technology to CGIAR breeding programs and partners.  Networked, “open-source” genomic selection programs integrating CGIAR breeding programs with those of national programs and small regional breeding programs are likely to be needed to deliver the promise of the technology to smallholder farmers.
See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Symposium--Meeting the Challenge: Genotyping Diverse Germplasm and Providing Tools for Crop Improvement