Genomic resources in plant breeding for sustainable agriculture

Authors

Mahendar Thudi, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) & University of Southern Queensland
Rajeev K. Varshney, Leibniz Institute of Plant Genetics and Crop Plant ResearchFollow
James C. Schnable, University of Nebraska - LincolnFollow

Document Type

Article

Date of this Version

2021

Citation

Journal of Plant Physiology 257 (2021)

https://doi.org/10.1016/j.jplph.2020.153351

Comments

2020 The Author(s).

Abstract

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, con- ventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965− 85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker- assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.