NMR‐based Metabolomics to Study the Cold‐acclimation Strategy of Two <i>Miscanthus</i> Genotypes

Gall, Hyacinthe Le; Fontaine, Jean-Xavier; Molinié, Roland; Pelloux, Jérôme; Mesnard, François; Gillet, Françoise; Fliniaux, Ophélie

doi:10.1002/pca.2649

Cited by 23 publications

(10 citation statements)

References 21 publications

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“…In addition, a similar technique was used in rice, and the results identified salt tolerant cultivars (Liu et al, 2013;Gupta and De, 2017). Moreover, many metabolite analyses have been conducted in wheat, maize, tomato, and soybean crops in relation to drought, cold, and heat stress (Semel et al, 2007;Bowne et al, 2012;Silvente et al, 2012;Witt et al, 2012;Sun et al, 2016;Le et al, 2017;Paupiere et al, 2017). Several metabolomics techniques including LC/GC-MS, GC/EI-TOF-MS, HPLC, and NMR have been widely used in crop species such as, rice, tomato, maize and soybean in response to abiotic (drought, salt, oxidative, and temperature) and biotic stress conditions (Ghatak et al, 2018).…”

Section: Metabolomicsmentioning

confidence: 99%

Applications of Multi-Omics Technologies for Crop Improvement

et al. 2021

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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.

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Section: Metabolomicsmentioning

confidence: 99%

Applications of Multi-Omics Technologies for Crop Improvement

et al. 2021

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“…Various studies have been carried out recently on metabolomic responses to cold stress (tomato, wheat, maize, miscanthus) [29,[186][187][188][189], including several medicinal plants [190], but Arabidopsis thaliana is the species traditionally more studied on such respects. In this grass, cold stress generates increases in most of its metabolites, including proline, sugars and TCA-cycle intermediates [191].…”

Section: Temperature Stressmentioning

confidence: 99%

Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress

et al. 2021

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Metabolomics is a technology that generates large amounts of data and contributes to obtaining wide and integral explanations of the biochemical state of a living organism. Plants are continuously affected by abiotic stresses such as water scarcity, high temperatures and high salinity, and metabolomics has the potential for elucidating the response-to-stress mechanisms and develop resistance strategies in affected cultivars. This review describes the characteristics of each of the stages of metabolomic studies in plants and the role of metabolomics in the characterization of the response of various plant species to abiotic stresses.

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“…The field of plant metabolomic analysis was pioneered by Magnetic Resonance Nuclear (NMR). It has greatly contributed to investigating primary and secondary metabolites in the context of topics ranging from food traceability [ 138 ] to plant response to abiotic [ 139 ] and biotic stresses [ 140 ]. To date other technologies e.g., matrix-assisted laser desorption/ionization (MALDI)–MS for metabolite imaging [ 141 ], Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) [ 142 ] and MS coupled with different systems of separation (LC, gas-chromatography (GC) and capillary electrophoresis (CE )) [ 143 ], are available to perform plant metabolomic analysis at an advanced level.…”

Section: Omic Technologies In the Plant World: From Genomics To Mementioning

confidence: 99%

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

et al. 2018

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The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

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NMR‐based Metabolomics to Study the Cold‐acclimation Strategy of Two Miscanthus Genotypes

Abstract: These two genotypes seem to have a different adaptation strategy in cold conditions. The studied change in the metabolome concerns different types of molecules related to the cold-tolerant behaviour of Miscanthus. Copyright © 2016 John Wiley & Sons, Ltd.

Cited by 23 publications

References 21 publications

Applications of Multi-Omics Technologies for Crop Improvement

Applications of Multi-Omics Technologies for Crop Improvement

Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

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