Strategies for effective use of genomic information in crop breeding programs serving Africa and South Asia

Much of the world’s population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.

Bibliographic Details

Main Authors:	Santantonio, N., Atanda, A.S., Beyene, Y., Varshney, R.K., Olsen, M., Jones, E., Roorkiwal, M., Gowda, M., Chellapilla Bharadwaj, Pooran M. Gaur, Xuecai Zhang, Dreher, K.A., Ayala Hernández, C., Crossa, J., Perez-Rodriguez, P., Rathore, A., Yanxin Gao, McCouch, S., Robbins, K.
Format:	Article biblioteca
Language:	English
Published:	Frontiers 2020
Subjects:	MARKER-ASSISTED SELECTION, PLANT BREEDING, EXPERIMENTAL DESIGN,
Online Access:	https://hdl.handle.net/10883/20819
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