Applications of Multi-Omics Technologies for Crop Improvement

Abstract

Multiple “omics” approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the “phenotype to genotype” and “genotype to phenotype” concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Physiological and Multi-Omics Approaches for Explaining Drought Stress Tolerance and Supporting Sustainable Production of Rice

“…The emergence of innovation in omics technologies has led to the deciphering of a large amount of molecular machinery to adapt to a large number of environmental factors. Besides, multiomics data integration and molecular modeling protocols can be employed to understand the complex traits to unearth the tolerance mechanism and yield of major legumes and cereal crops (Pazhamala et al, 2021;Yang et al, 2021). It is pertinent that enhancing tolerance to drought in rice requires the establishment of research programs to investigate complex networks of molecular interactions.…”

Molecular Insights into Freezing Stress in Peach Based on Multi-Omics and Biotechnology: An Overview

“…Developing tolerance to external elements is necessary for the plant to maintain homeostasis, which is crucial for proper growth and yield [ 38 ]. To acquire a deeper understanding of the tolerance mechanisms, omics approaches have emerged as significant ultra-modern techniques [ 39 ]. Genomics, transcriptomics, proteomics, and metabolomics have been widely utilized for dissecting the role of freezing tolerance genes in the survival of peaches during extremely cold conditions ( Figure 1 ).…”

Applications of cell- and tissue-specific ‘omics to improve plant productivity

“…However, it was only after the nineteenth century that major scientific breakthroughs were made in plant breeding, driving significant advances in productivity. The development and application of ‘omics technologies in recent years, such as high-throughput sequencing, proteomics and metabolomics, have enhanced research into plant biology tremendously [ 3–7 ]. As a result, we have gained a better understanding of the genetics and complex biological processes that underpin plant productivity.…”