Multi-omics revolution to promote plant breeding efficiency
| Autor: | Umer Mahmood, Xiaodong Li, Yonghai Fan, Wei Chang, Yue Niu, Jiana Li, Cunmin Qu, Kun Lu |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Frontiers in Plant Science, Vol 13 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1664-462X 09451374 |
| DOI: | 10.3389/fpls.2022.1062952 |
| Popis: | Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world’s food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits. |
| Databáze: | Directory of Open Access Journals |
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