Plant Metabolomics: An Emerging Technology for Crop Improvement

Abstract

The astounding ability of plants to make smart decisions in response to environment is evident. As they have evolved a long list of complex and unique processes that involve photosynthesis, totipotency, long-distance signaling, and ability to restore structural and metabolic memory, recognition, and communication via emission of the selected class of volatiles. In recent years, use of metabolite profiling techniques in detection, unam - biguous identification, quantification, and rapid analysis of the minute quantity of cel lular micromolecules has increased considerably. Metabolomics is key to understand the chemical footprints during different phases of growth and development of plants. To feed the ever-increasing population with limited inputs and in a rapidly changing environment is the biggest challenges that the world agriculture faces today. To achieve the project genetic gains, the breeding strategies employing marker-assisted selection for high-yielding varieties and identifying germplasm resistant to abiotic and biotic stresses are already in vogue. Henceforth, new approaches are needed to discover and deploy agronomically important gene/s that can help crops better withstand weather extremes and growing pest prevalence worldwide. In this context, metabolic engineering technol - ogy looks viable option, with immense potential to deliver the future crops. leaves and early flowering. The Arabidopsis At-LBD37/ASL39-overexpressor plants showed similar morphological leaf changes (i.e., hyponastic leaves), and had increased levels of amino acids and metabolites related to nitrogen metabolism. Subsequent profiling of metabolites and transcriptomes of the rice Os- LBD37/ASL39 -overexpressing lines ascertained the same function of Os- LBD37/ASL39 in rice and Arabidopsis . The analysis revealed notable features in rice overexpressor plants including early heading, metabolite alterations (related to nitrogen metabolism), and advanced leaf senescence. These findings established a close association between Os- LBD37/ ASL39 and nitrogen metabolism in rice. for small compounds, including primary metabolites; ultra-pressure liquid chromatography-quadruple-TOF-MS (UPLC-Q-TOF-MS) for hydrophilic compounds; capillary electrophoresis-TOF-MS (CE-TOF-MS) for ionic compounds; and liquid chromatography-ion trap-TOF-MS (LC-IT-TOF-MS) for polar lipids. The study defined a correlation between genetic diversity metabolite trait a amylose/total samples, rice varieties, and the two mutants, high-, middle-, low-amylose/ total starch ratios, respectively. The amylose/total starch ratio was found to be associated with metabolites in rice kernels of the cultivars. this association was not observed in the mutants. The two loss-of-function mutants- e1 , a starch synthase IIIa ( SSIIIa )-deficient mutant and