Metabolomics: A Way Forward for Crop Improvement

Abstract

Metabolomics is an emerging branch of "omics" and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment-gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.

Keywords: abiotic stress; biotic stress; crop improvement; mass spectrometry; metabolic profiling; metabolomics; metabolomics-assisted breeding.

Figure 1

System biology for understanding the plant stress mechanism. The central dogma of plant biology showed integrated applications of genomics, transcriptomics, proteomics, metabolomics, and phenomics under biotic/abiotic stresses. Different bioinformatics tools are applied for integrated analysis to study plant stress responses from the genome to phenome levels. The data generated from these analyses are exploited for metabolic engineering and can also be executed in modern breeding platforms to generate gene edited mutants via clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins (CRISPR/Cas9)/recombinant DNA technology to develop resistant crops.

Figure 2

Flowchart outlining the board mechanisms in plant metabolomics for crop improvement.

Figure 3

Quantitative trait loci (QTL) mapping for gene expression or a molecular phenotype. The flow of molecular information is represented from the DNA to the phenotype in response to biotic/abiotic stress signals. Black arrows indicate that each molecular phenotype can be mapped by using QTL mapping and genome-wide association studies (GWAS) techniques. Whereas, metabolic genome-wide association studies (mGWAS) does not require genetic information to investigate the effects of genetic deviations on metabolites. Red arrows show the corresponding levels of a specific gene, protein and metabolite. (eQTL: epigenomic QTL; pQTL: proteomic QTL; mQTL: metabolomic quantity trait loci; mGWAS: metabolomic genome-wide association studies).