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High night temperature strongly impacts TCA cycle, amino acid and polyamine biosynthetic pathways in rice in a sensitivity-dependent manner.

Glaubitz U, Erban A, Kopka J, Hincha DK, Zuther E - J. Exp. Bot. (2015)

Bottom Line: Increased expression levels of ADC2 and ODC1, genes encoding enzymes catalysing the first committed steps of putrescine biosynthesis, were restricted to sensitive cultivars under HNT.Additionally, transcript levels of eight polyamine biosynthesis genes were correlated with HNT sensitivity.Responses to HNT in the vegetative stage result in distinct differences between differently responding cultivars with a dysregulation of central metabolism and an increase of polyamine biosynthesis restricted to sensitive cultivars under HNT conditions and a pre-adaptation of tolerant cultivars already under control conditions with higher levels of potentially protective compatible solutes.

View Article: PubMed Central - PubMed

Affiliation: Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, D-14476 Potsdam, Germany.

No MeSH data available.


(A) Principal component analysis (PCA) of GC-MS metabolite profiles of leaves from 12 rice cultivars 48 DAS under control conditions (blue, ◊) or after 23 d (48 DAS) of HNT treatment (red, □). Tolerance groups are colour-coded (dark to light) as indicated in the figure. Scores of principal components PC1 and PC2 are shown together with the percentage of the total variance explained. (B) Metabolites with the top ten most positive and negative loadings from PC1 and PC2 are shown in panel. Metabolites with high intensities compared to the median are coloured in red, metabolites with low intensities in blue. Gray indicates a missing value.
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Figure 1: (A) Principal component analysis (PCA) of GC-MS metabolite profiles of leaves from 12 rice cultivars 48 DAS under control conditions (blue, ◊) or after 23 d (48 DAS) of HNT treatment (red, □). Tolerance groups are colour-coded (dark to light) as indicated in the figure. Scores of principal components PC1 and PC2 are shown together with the percentage of the total variance explained. (B) Metabolites with the top ten most positive and negative loadings from PC1 and PC2 are shown in panel. Metabolites with high intensities compared to the median are coloured in red, metabolites with low intensities in blue. Gray indicates a missing value.

Mentions: In total, 156 metabolites were identified in two control and two HNT experiments and annotated according to the MPIMP-Golm inventory list (Kopka et al., 2005) (Supplementary Table S2). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed on a reduced dataset of 75 metabolites common to all four experiments. Principal components (PC) 1 and 2, which together explained 51.7% of the total variance, clearly separated the metabolite profiles of the three most sensitive cultivars (M202, DR2, IR62266-42-6-2) under HNT conditions from all others (Fig. 1A). Loadings of PC1 with the highest values were adipo-2,6-lactam, dehydroascorbic acid dimer and quinic acid, while proline, galactaric acid and asparagine showed the lowest values (Fig. 1B). For PC2 proline, lysine and asparagine were the loadings with highest value and galactaric acid, 4-hydroxy-trans cinnamic acid and raffinose with the lowest (Fig. 1B). These metabolites had the highest impact on the separation of sensitive from intermediate and tolerant cultivars under HNT conditions. No distinct separation of the two subspecies could be found when both conditions were analysed together, whereas a separation of indica and japonica cultivars was apparent in a PCA using only data from control experiments (Supplementary Fig. S1). Selected representative metabolites of PC1 and PC3 with the 20 highest PC loading values responsible for this separation are shown in Supplementary Table S3.


High night temperature strongly impacts TCA cycle, amino acid and polyamine biosynthetic pathways in rice in a sensitivity-dependent manner.

Glaubitz U, Erban A, Kopka J, Hincha DK, Zuther E - J. Exp. Bot. (2015)

(A) Principal component analysis (PCA) of GC-MS metabolite profiles of leaves from 12 rice cultivars 48 DAS under control conditions (blue, ◊) or after 23 d (48 DAS) of HNT treatment (red, □). Tolerance groups are colour-coded (dark to light) as indicated in the figure. Scores of principal components PC1 and PC2 are shown together with the percentage of the total variance explained. (B) Metabolites with the top ten most positive and negative loadings from PC1 and PC2 are shown in panel. Metabolites with high intensities compared to the median are coloured in red, metabolites with low intensities in blue. Gray indicates a missing value.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4588888&req=5

Figure 1: (A) Principal component analysis (PCA) of GC-MS metabolite profiles of leaves from 12 rice cultivars 48 DAS under control conditions (blue, ◊) or after 23 d (48 DAS) of HNT treatment (red, □). Tolerance groups are colour-coded (dark to light) as indicated in the figure. Scores of principal components PC1 and PC2 are shown together with the percentage of the total variance explained. (B) Metabolites with the top ten most positive and negative loadings from PC1 and PC2 are shown in panel. Metabolites with high intensities compared to the median are coloured in red, metabolites with low intensities in blue. Gray indicates a missing value.
Mentions: In total, 156 metabolites were identified in two control and two HNT experiments and annotated according to the MPIMP-Golm inventory list (Kopka et al., 2005) (Supplementary Table S2). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed on a reduced dataset of 75 metabolites common to all four experiments. Principal components (PC) 1 and 2, which together explained 51.7% of the total variance, clearly separated the metabolite profiles of the three most sensitive cultivars (M202, DR2, IR62266-42-6-2) under HNT conditions from all others (Fig. 1A). Loadings of PC1 with the highest values were adipo-2,6-lactam, dehydroascorbic acid dimer and quinic acid, while proline, galactaric acid and asparagine showed the lowest values (Fig. 1B). For PC2 proline, lysine and asparagine were the loadings with highest value and galactaric acid, 4-hydroxy-trans cinnamic acid and raffinose with the lowest (Fig. 1B). These metabolites had the highest impact on the separation of sensitive from intermediate and tolerant cultivars under HNT conditions. No distinct separation of the two subspecies could be found when both conditions were analysed together, whereas a separation of indica and japonica cultivars was apparent in a PCA using only data from control experiments (Supplementary Fig. S1). Selected representative metabolites of PC1 and PC3 with the 20 highest PC loading values responsible for this separation are shown in Supplementary Table S3.

Bottom Line: Increased expression levels of ADC2 and ODC1, genes encoding enzymes catalysing the first committed steps of putrescine biosynthesis, were restricted to sensitive cultivars under HNT.Additionally, transcript levels of eight polyamine biosynthesis genes were correlated with HNT sensitivity.Responses to HNT in the vegetative stage result in distinct differences between differently responding cultivars with a dysregulation of central metabolism and an increase of polyamine biosynthesis restricted to sensitive cultivars under HNT conditions and a pre-adaptation of tolerant cultivars already under control conditions with higher levels of potentially protective compatible solutes.

View Article: PubMed Central - PubMed

Affiliation: Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, D-14476 Potsdam, Germany.

No MeSH data available.