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. 2022 Jul 11;22(1):333.
doi: 10.1186/s12870-022-03718-2.

Transcription-associated metabolomic profiling reveals the critical role of frost tolerance in wheat

Affiliations

Transcription-associated metabolomic profiling reveals the critical role of frost tolerance in wheat

Liangjie Lv et al. BMC Plant Biol. .

Abstract

Background: Low temperature is a crucial stress factor of wheat (Triticum aestivum L.) and adversely impacts on plant growth and grain yield. Multi-million tons of grain production are lost annually because crops lack the resistance to survive in winter. Particularlly, winter wheat yields was severely damaged under extreme cold conditions. However, studies about the transcriptional and metabolic mechanisms underlying cold stresses in wheat are limited so far.

Results: In this study, 14,466 differentially expressed genes (DEGs) were obtained between wild-type and cold-sensitive mutants, of which 5278 DEGs were acquired after cold treatment. 88 differential accumulated metabolites (DAMs) were detected, including P-coumaroyl putrescine of alkaloids, D-proline betaine of mino acids and derivativ, Chlorogenic acid of the Phenolic acids. The comprehensive analysis of metabolomics and transcriptome showed that the cold resistance of wheat was closely related to 13 metabolites and 14 key enzymes in the flavonol biosynthesis pathway. The 7 enhanced energy metabolites and 8 up-regulation key enzymes were also compactly involved in the sucrose and amino acid biosynthesis pathway. Moreover, quantitative real-time PCR (qRT-PCR) revealed that twelve key genes were differentially expressed under cold, indicating that candidate genes POD, Tacr7, UGTs, and GSTU6 which were related to cold resistance of wheat.

Conclusions: In this study, we obtained the differentially expressed genes and differential accumulated metabolites in wheat under cold stress. Using the DEGs and DAMs, we plotted regulatory pathway maps of the flavonol biosynthesis pathway, sucrose and amino acid biosynthesis pathway related to cold resistance of wheat. It was found that candidate genes POD, Tacr7, UGTs and GSTU6 are related to cold resistance of wheat. This study provided valuable molecular information and new genetic engineering clues for the further study on plant resistance to cold stress.

Keywords: Flavonoid biosynthesis; Frost-resistant; Metabolome; Sucrose and amino acid biosynthesis; Transcriptome; Wheat (Triticum aestivum).

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Cold Stress effects on plant development. A Shoot morphology. B Survival rate (%). C Proline content (ug/g). D, Catalase activity (μmoL*min*g)−1 FW. E, Soluble sugar contents (mg/g FW). F Malondialdehyde content (nmol/g FW). G Peroxidase activity (μmoL/(min*g) FW). H Superoxidase activity (U/(min*g) FW). The data are means ± SD(n ≥ 10). Different letters indicate significant differences between treatments and control plants from Student’s unpaired two-tailed t-test (P < 0.05). CK, Jimai 325; MU, MU-134
Fig. 2
Fig. 2
Correlation and PCA analysis of all transcripts and identification of DEGs. A Correlation analysis of all samples. B PCA plot of transcriptome results. C Venn diagram of DEGs before and after cold stress in the same varieties; D, Venn diagram of DEGs between varieties before and after cold stress. Above and below the horizontal line are up-regulated and down-regulated genes, respectively; E Numbers of DEGs between different comparisons. F Venn diagram of DEGs among 4 comparison groups (FDR < 0.05 and FC ≥ 2). The numbers in parentheses showed percentages concerning the total genes. CK1, before treatment Jimai 325; CK2, cold treatment Jimai 325; MU1, before treatment MU-134; MU2, cold treatment MU-134
Fig. 3
Fig. 3
GO (A) and KEGG (B) functional classifications of the annotated unigenes in wheat. The unigenes were distributed into three GO categories: biological process (a), cellular component (b), and molecular function (c). The unigenes were divided into five KEGG groups: cellular processes (a), environmental information processing (b), genetic information processing (c), metabolism (d) and organismal systems (e)
Fig. 4
Fig. 4
Transcription factor classification and expression profile. A Classification of transcription factors. B The expression profile of frost-resistance-related transcription factors. The numbers in the pie represent quantities. Expression was normalized; green represents low expression; red represents high expression
Fig. 5
Fig. 5
Differentially accumulated metabolites of wheat in response to cold stress. A PCA plot of metabolomic results. B Numbers of differentially accumulated metabolites under different treatments. C Venn diagram of differentially accumulated metabolites (FDR < 0.05 and FC ≥ 2). D, K-means clustering analysis of the differentially accumulated metabolites into nine clusters according to their expression profile. The cluster names and the number of metabolites for each cluster are indicated. CK1, before treatment Jimai 325; CK2, cold treatment Jimai 325; MU1, before treatment MU-134; MU2, cold treatment MU-134
Fig. 6
Fig. 6
Hierarchical cluster and KEGG enrichment analysis for all metabolome samples of frost resistance traits in wheat. A Hierarchical cluster analysis of all samples metabolite content. Blue represents low expression and red represents high expression. B KEGG pathway enrichment analysis based on the differentially accumulated metabolites in MU1_vs_CK1(B) and CK2_vs_MU2 (C). The top 20 statistics of KEGG pathway enrichment were shown. The dot color represents the size of the P-value. The smaller the q value, the closer the color is to red. The dot size represents the number of different genes contained in each pathway
Fig. 7
Fig. 7
The Heatmap of key metabolites in response to the cold treatment in MU and CK. Gray represents low fold change and red represents high fold change
Fig. 8
Fig. 8
Kegg functional classifications (A) and Kmeans (B) of the differentially expressed related genes and metabolites in response to the cold treatment in MU2 and CK2
Fig. 9
Fig. 9
Correlation network analysis of differential metabolites and differential expression genes related to frost tolerance in wheat. The red lines indicate positive correlation; the green line indicates negative correlation, the blue line indicates the correlation is not significant. Metabolites were marked red, structural genes were green. The size of the red circle represents the number of genes associated with the metabolite. The thickness of the ring frame of metabolite group was adjusted to indicate the differential multiple of metabolites. The line thickness between nodes represents the degree of correlation between two nodes
Fig. 10
Fig. 10
Transcript and metabolic profiling of significantly differential metabolites and DEGs in flavonol biosynthesis pathway in wheat under cold treatment. A The map of integrative analysis in flavonol biosynthesis metabolites and their biosynthesis-related key enzymes. Red font: significantly up-regulated differential metabolites or DEGs encoding the corresponding enzyme; green font: significantly down-regulated differential metabolites or DEGs encoding the corresponding enzyme; Blue font: significantly up/down-regulated DEGs encoding the corresponding enzyme; Black font: the enzyme encoding genes and differential metabolites detected but with no significant difference. Black arrow lines: ko00940; Blue arrow lines: ko00941; Red arrow lines: ko00944. DEGs and DAMs were investigated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) to map to the possible KEGG pathway maps for the biological interpretation of systemic functions (www.kegg.jp/kegg/kegg1.html). B Heatmap of differential metabolites accumulation flavonol biosynthesis pathway. The color bar presented at the top right represents the level of metabolites, where red indicates the metabolites with a higher level, and blue indicates metabolites with a lower level. C Heatmap of DEGs enriched flavonol biosynthesis pathway. Gene expression was scaled using normalized FPKM for the mean value of three biological replicates. A color bar was presented at the top right, and the colors from blue to red indicate low to high expression. 4CL, 4-coumarate--CoA ligase; ANS, anthocyanidin synthase; CHI, chalcone isomerase; CHS, chalcone synthase; CYP73, trans-cinnamate 4-monooxygenase; CYP75B1, flavonoid 3′-monooxygenase; CYP93B2_16, flavone synthase II; CYP98, 5-O-(4-coumaroyl)-D-quinate 3′-monooxygenase; FG2, Kaempferol-3-O-rutinoside; FLS, flavonol synthase; HCT, shikimate O-hydroxycinnamoyltransferase; PAL, phenylalanine ammonia-lyase; UGT73C6, flavonol-3-O-L-rhamnoside-7-O-glucosyltransferase; CSE, caffeoyl shikimate esterase
Fig. 11
Fig. 11
Transcript and metabolic profiling of significantly differential metabolites and DEGs through sugar and amino acids metabolic pathways in wheat under cold treatment. A The map of integrative analysis in sugar and amino acids metabolites and their biosynthesis-related key enzymes. Red font: significantly up-regulated differential metabolites or DEGs encoding the corresponding enzyme; green font: significantly down-regulated differential metabolites or DEGs encoding the corresponding enzyme; Blue font: significantly up/down-regulated DEGs encoding the corresponding enzyme; Black font: the enzyme encoding genes and differential metabolites detected but with no significant difference. DEGs and DAMs were investigated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) to map to the possible KEGG pathway maps for the biological interpretation of systemic functions (www.kegg.jp/kegg/kegg1.html). B Heatmap of differential metabolites accumulation in sugar and amino acids biosynthesis pathways. The color bar presented at the top right represents the level of metabolites, where red indicates the metabolites with a higher level, and blue indicates metabolites with a lower level. C Heatmap of DEGs enriched in sugar and amino acids biosynthesis pathways. Gene expression was scaled using normalized FPKM for the mean value of three biological replicates. A color bar was presented at the top right, and the colors from blue to red indicate low to high expression. SPP, sucrose-6-phosphatase; ADC, arginine decarboxylase; rbtK, D-ribulokinase; ansA, L-asparaginase; GOLS, inositol 3-alpha-galactosyltransferase; ahcY, adenosylhomocysteinase; xylB, xylulokinase; HK, hexokinase; pyk, pyruvate kinase; proA, glutamate 5-kinase; SPS, sucrose-phosphate synthase; cysE, serine O-acetyltransferase; GLUL, glutamine synthetase; GLA, alpha-galactosidase; GPI, glucose-6-phosphate isomerase; aroK, shikimate kinase; cel, endoglucanase; RFS, raffinose synthase; POP2, 4-aminobutyrate---pyruvate transaminase; cysK, cysteine synthase
Fig. 12
Fig. 12
The relative expression levels of twelve selected DEGs were compared by RNA-seq and qRT-PCR. A Expression patterns of the 12 genes involved in the Cold stress of wheat. B correlation analysis based on RNA-Seq and qRT-PCR data. The line chart shows the gene expression level from the transcriptome (FPKM); The qRT-PCR expression levels were calculated as a ratio relative to the level of expression of CK1, which was set as 1. Bars indicate means ± standard deviations (SDs) of at least three independent biological replicates

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