Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.

Nicholas Santantonio,Claudio Ayala-Hernández,Star Yanxin Gao,Abhishek Rathore,Manish Roorkiwal,Susan Mccouch,Kelly R Robbins,Pooran M Gaur,Yoseph Beyene,Chellapilla Bharadwaj,Xuecai Zhang,Elizabeth Jones,Jose Crossa,Manje Gowda,Kate Dreher,Paulino Pérez-Rodríguez,Michael Olsen,Sikiru Adeniyi Atanda,Rajeev K Varshney

doi:10.3389/fpls.2020.00353

Abstract

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.

Highlights

Crop improvement through plant breeding is a process of continuous genetic improvement through selection and recombination of superior lines
The principal component plot for the maize dataset shows clustering by population but there is a significant overlap between populations
Prediction across seedtypes was accomplished to determine if the allele frequency and linkage disequilibrium (LD) pattern is sufficiently shared between seed-types

Summary

Introduction

Crop improvement through plant breeding is a process of continuous genetic improvement through selection and recombination of superior lines. While all the aforementioned factors are critical, the ability to identify and effectively implement new technologies can be challenging. This is especially true for publicly funded breeding programs in Africa and South Asia, where resource and infrastructure limitations make the adoption of new technologies challenging. The need to overcome these limitations and improve the effectiveness of breeding programs is urgent, given the historically low rates of genetic gains in many programs serving Africa and South Asia (Godfray et al, 2010; Cobb et al, 2019), expected population growth (Alexandratos and Bruinsma, 2012), and the potential impacts of climate change on crop production (Ritchie et al, 2018)

Methods

Results

Discussion

Conclusion