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

Abstract

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...

Integrated 16S and metabolomics revealed the mechanism of drought resistance and nitrogen uptake in rice at the heading stage under different nitrogen levels

“…Differentially expressed genes involved in phenylalanine, tyrosine and tryptophan biosynthesis were all upregulated specifically in a drought-tolerant Eruca line under drought stress (Huang et al, 2019). Energy metabolism pathways change strongly under abrupt drought-flood alteration stress (Xiong et al, 2019b). This study also showed that under drought stress and N application, the rhizosphere soil was mainly enriched in the energy metabolism pathway.…”

Exogenous GbHMGS1 Overexpression Improves the Contents of Three Terpenoids in Transgenic Populus

“…The data were log2-transformed in Excel 2007 (Microsoft, USA), and the resulting data matrix was then imported into the SIMCA software package (version 14.0, Umetrics, Umeå, Sweden). In addition, partial least squares discriminant analysis (PLS-DA), orthogonal projections to latent structures (OPLS-DA), and other metabolome analysis methods were performed according to the methods described by Xiong et al [34].…”