Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions

Wu, Si; Tohge, Takayuki; Cuadros-Inostroza, Álvaro; Tong, Hao; Tenenboim, Hezi; Kooke, Rik; Méret, Michaël; Keurentjes, Joost J. B.; Nikoloski, Zoran; Fernie, Alisdair R.; Willmitzer, Lothar; Brotman, Yariv

doi:10.1016/j.molp.2017.08.012

Cited by 106 publications

(102 citation statements)

References 64 publications

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“…Thus, environmental variation is a key variable that must be considered in order to fully understand the plasticity of the map between host plant genotype and leaf microbiome phenotype. Environmental variables have been manipulated in GWAS of other environmentally sensitive plant traits (Li et al ., ; Wu et al ., ). For example, one GWAS of flowering time in A. thaliana was replicated in growth chambers simulating four distinct natural climates.…”

Section: Workflowmentioning

confidence: 97%

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

et al. 2019

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Summary Environmental sequencing shows that plants harbor complex communities of microbes that vary across environments. However, many approaches for mapping plant genetic variation to microbe‐related traits were developed in the relatively simple context of binary host–microbe interactions under controlled conditions. Recent advances in sequencing and statistics make genome‐wide association studies (GWAS) an increasingly promising approach for identifying the plant genetic variation associated with microbes in a community context. This review discusses early efforts on GWAS of the plant phyllosphere microbiome and the outlook for future studies based on human microbiome GWAS. A workflow for GWAS of the phyllosphere microbiome is then presented, with particular attention to how perspectives on the mechanisms, evolution and environmental dependence of plant–microbe interactions will influence the choice of traits to be mapped.

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Section: Workflowmentioning

confidence: 97%

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

et al. 2019

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“…As we have discussed above, the spatial−temporal and environment‐dependent expression of key regulators of metabolic pathways lead to the metabolic diversity at the individual level. Some studies based on metabolome data from different tissues (Chen et al ., ; Matsuda et al ., ; Chen et al ., ) or under different conditions (Wu et al ., ) have also identified diverse genetic determinants for the same or structurally similar compounds. Although combined mGWAS under different conditions enhanced the power to identify causative genes (Wu et al ., ), knowledge about the variation in the content ratio of each individual metabolite is still lacking, as well as knowledge about deciphering its genetic basis with mGWAS.…”

Section: Mgwas‐based Multi‐dimensional Analysismentioning

confidence: 99%

“…Some studies based on metabolome data from different tissues (Chen et al ., ; Matsuda et al ., ; Chen et al ., ) or under different conditions (Wu et al ., ) have also identified diverse genetic determinants for the same or structurally similar compounds. Although combined mGWAS under different conditions enhanced the power to identify causative genes (Wu et al ., ), knowledge about the variation in the content ratio of each individual metabolite is still lacking, as well as knowledge about deciphering its genetic basis with mGWAS. However, rigorously designed mGWAS based on metabolite content ratios under different conditions will contribute not only to the understanding of metabolic diversity under constantly changing environments, but also lead to the identification of key regulators for stress responses from the lens of the metabolome.…”

Section: Mgwas‐based Multi‐dimensional Analysismentioning

confidence: 99%

Metabolic GWAS‐based dissection of genetic bases underlying the diversity of plant metabolism

2018

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Plants have served as sources providing humans with metabolites for food and nutrition, biomaterials for living, and treatment for pain and disease. Plants produce a huge array of metabolites, with an immense diversity at both the population and individual levels. Dissection of the genetic bases for metabolic diversity has attracted increasing research attention. The concept of genome-wide association study (GWAS) was extended to studies on the diversity of plant metabolome that benefitted from the development of mass-spectrometry-based analytical systems and genome sequencing technologies. Metabolic genome-wide association study (mGWAS) is one of the most powerful tools for global identification of genetic determinants for diversity of plant metabolism. Recently, mGWAS has been performed for various species with continuous improvements, providing deeper insights into the genetic bases of metabolic diversity. In this review, we discuss fully the achievements to date and remaining challenges that are associated with both mGWAS and mGWAS-based multi-dimensional analysis. We begin with a summary of GWAS and its development based on statistical methods and populations. As variation in targeted traits is essential for GWAS, we review metabolic diversity and its rise at both the population and individual levels. Subsequently, the application of mGWAS for plants and its corresponding achievements are fully discussed. We address the current knowledge on mGWAS-based multi-dimensional analysis and emerging insights into the diversity of metabolism.

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“…The iTRAQ-labeled quantitative LC-MS/MS proteomics and LC-MS/MS metabolomics technology provides an effective method for the investigation of altered proteins and metabolites in plant cells during environmental stress (Frost et al , 2015; Wu et al , 2017). This study characterized the changes of the metabolome and the proteome of spike during the panicle differentiation stage in response to abrupt drought-flood alternation stress.…”

Section: Discussionmentioning

confidence: 99%

Metabolomics and proteomics analyses of grain yield reduction in rice under abrupt drought-flood alternation

Xiong

Shen

et al. 2018

Preprint

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9 10 analysis of spike metabolites was proceeded by LC-MS (liquid chromatograph-mass 32 spectrometry) firstly. Then the Heat-map, PCA, PLS-DA, OPLS-DA and response ranking 33 test of OPLS-DA model methods were used to analysis the function of differential metabolites 34 (DMs) during the rice panicle differentiation stage under abrupt drought-flood alteration. In 35 addition, relative quantitative analysis of spike total proteins under the treatment was 36 conducted iTRAQ (isobaric tags for relative and absolute quantification) and LC-MS. In this 37 study, 5708 proteins were identified and 4803 proteins were quantified. The identification and 38 analysis of DEPs function suggested that abrupt drought-flood alteration treatment can 39 promote carbohydrate metabolic, stress response, oxidation-reduction, defense response, and 40 energy reserve metabolic process, etc, during panicle differentiation stage. In this study 41 relative quantitative proteomics, metabolomics and physiology data (soluble protein content, 42 superoxide dismutase activity, hydrogen peroxidase activity, peroxidase activity, 43 malondialdehyde content, free proline content, soluble sugar content and net photosynthetic 44 rate) analysis were applied to explicit the response mechanism of rice panicle differentiation 45 stage under abrupt drought-flood alteration and provides a theoretical basis for the disaster 46 prevention and mitigation. 47 48 Abstract 49 Abrupt drought-flood alternation is a meteorological disaster that frequently occurs during 50 summer in southern China and the Yangtze river basin, often causing a significant loss of rice 51 production. In this study, a quantitative analysis of spike metabolites was conducted via liquid 52 chromatograph-mass spectrometry (LC-MS), and Heat-map, PCA, PLS-DA, OPLS-DA, and a 53 response ranking test of OPLS-DA model methods were used to analyze functions of 54 differential metabolites (DMs) during the rice panicle differentiation stage under abrupt 55 drought-flood alternation. The results showed that 102 DMs were identified from the rice 56 spike between T1 (abrupt drought-flood alternation) and CK0 (control) treatment, 104 DMs 57 were identified between T1 and CK1 (drought) treatment and 116 DMs were identified 58 between T1 and CK2 (flood) treatment. In addition, a relative quantitative analysis of spike 59 total proteins was conducted using isobaric tags for relative and absolute quantification 60 (iTRAQ) and LC-MS. The identification and analysis of DEPs functions indicates that abrupt 61 3drought-flood alternation treatment can promote carbohydrate metabolic, stress response, 62 oxidation-reduction, defense response, and energy reserve metabolic process during the 63 panicle differentiation stage. In this study, relative quantitative metabolomics and proteomics 64 analyses were applied to explore the response mechanism of rice panicle differentiation in 65 response to abrupt drought-flood alternation. 66 Keywords: Rice (Oryza sativa L.), abrupt drought-flood alternation, metabolomics, 67 p...

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Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions

Cited by 106 publications

References 64 publications

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

Metabolic GWAS‐based dissection of genetic bases underlying the diversity of plant metabolism

Metabolomics and proteomics analyses of grain yield reduction in rice under abrupt drought-flood alternation

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