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Get Free AccessGrain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based 'dietary protein' biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.
Uday Chand Jha, Harsh Nayyar, Swarup K. Parida, Rupesh Deshmukh, Eric von Wettberg, Kadambot Siddique (2022). Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools. , 23(14), DOI: https://doi.org/10.3390/ijms23147710.
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Type
Article
Year
2022
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.3390/ijms23147710
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