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. 2023 Feb 14;24(4):3856.
doi: 10.3390/ijms24043856.

Global Responses of Autopolyploid Sugarcane Badila (Saccharum officinarum L.) to Drought Stress Based on Comparative Transcriptome and Metabolome Profiling

Shan Yang  1 , Na Chu  2 , Naijie Feng  1 , Bolin Zhou  1 , Hongkai Zhou  1 , Zuhu Deng  2 , Xuefeng Shen  1 , Dianfeng Zheng  1
Affiliations

Global Responses of Autopolyploid Sugarcane Badila (Saccharum officinarum L.) to Drought Stress Based on Comparative Transcriptome and Metabolome Profiling

Shan Yang et al. Int J Mol Sci. .

Abstract

Sugarcane (Saccharum spp. hybrid) is frequently affected by seasonal drought, which causes substantial declines in quality and yield. To understand the drought resistance mechanisms of S. officinarum, the main species of modern sugarcane, at a molecular level, we carried out a comparative analysis of transcriptome and metabolome profiling of the sugarcane variety Badila under drought stress (DS). Compared with control group (CG) plants, plants exposed to DS had 13,744 (6663 up-regulated and 7081 down-regulated) differentially expressed genes (DEGs). GO and KEGG analysis showed that the DEGs were enriched in photosynthesis-related pathways and most DEGs had down-regulated expression. Moreover, the chlorophyll content, photosynthesis (Photo), stomatal conductance (Cond), intercellular carbon dioxide concentration (Ci) and transpiration rate (Trmmol) were sharply decreased under DS. These results indicate that DS has a significant negative influence on photosynthesis in sugarcane. Metabolome analysis identified 166 (37 down-regulated and 129 up-regulated) significantly regulated metabolites (SRMs). Over 50% of SRMs were alkaloids, amino acids and their derivatives, and lipids. The five most significantly enriched KEGG pathways among SRMs were Aminoacyl-tRNA biosynthesis, 2-Oxocarboxylic acid metabolism, Biosynthesis of amino acids, Phenylalanine metabolism, and Arginine and proline metabolism (p < 0.05). Comparing CG with DS for transcriptome and metabolome profiling (T_CG/DS and M_CG/DS, respectively), we found three of the same KEGG-enriched pathways, namely Biosynthesis of amino acids, Phenylalanine metabolism and Arginine and proline metabolism. The potential importance of Phenylalanine metabolism and Arginine and proline metabolism was further analyzed for response to DS in sugarcane. Seven SRMs (five up-regulated and two down-regulated) and 60 DEGs (17 up-regulated and 43 down-regulated) were enriched in Phenylalanine metabolism under DS, of which novel.31261, Sspon.04G0008060-1A, Sspon.04G0008060-2B and Sspon.04G0008060-3C were significantly correlated with 7 SRMs. In Arginine and proline metabolism, eight SRMs (seven up-regulated and one down-regulated) and 63 DEGs (32 up-regulated and 31 down-regulated) were enriched, of which Sspon.01G0026110-1A (OAT) and Sspon.03G0002750-3D (P5CS) were strongly associated with proline (r > 0.99). These findings present the dynamic changes and possible molecular mechanisms of Phenylalanine metabolism as well as Arginine and proline metabolism under DS and provide a foundation for future research and sugarcane improvement.

Keywords: arginine and proline; drought; metabolome; phenylalanine; sugarcane; transcriptome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Phenotype of Badila with drought stress (DS; left) or normal watering (control group, CG; right).
Figure 2
Figure 2
Physiological and biochemical indexes. Photo, Cond, Ci and Trmmol indicate net photosynthesis, stomatal conductance, intercellular carbon dioxide concentration and transpiration rate, respectively. Error bars represent standard deviation among means for three different samples. Different letters on bars indicate statistically significant differences between treatments (p < 0.05).
Figure 3
Figure 3
Results of RNA-seq and RT-qPCR for 12 genes. The gene expression level of RNA-seq shows as Log2(fold change) and the fold-change is based on the FPKM values of drought stress group relative to control group. The gene expression level of RT-qPCR shows as Log2(fold change = 2−ΔΔCt).
Figure 4
Figure 4
Top 50 enriched GO pathways in a comparison of CG and DS transcriptomes.
Figure 5
Figure 5
Top 20 enriched KEGG pathways in a comparison of CG and DS transcriptomes.
Figure 6
Figure 6
Classification of significantly regulated metabolites (SRMs).
Figure 7
Figure 7
Top 20 enriched KEGG pathways in a comparison of CG and DS metabolomes.
Figure 8
Figure 8
Analysis of DEGs and SRMs in the phenylalanine metabolism pathway. Enriched (A) SRMs and (B) DEGs color-coded according to fold-change between CG and DS groups. |log2FC| denotes |log2Fold Change|. Solid line stands for direct reaction. Dashed line stands for indirect reaction, which means it have to go through multiple reactions.
Figure 9
Figure 9
Correlation network of DEGs and SRMs in the phenylalanine metabolism pathway. The genes and metabolites color-coded according to fold-change between the CG and DS groups. |log2FC| denotes |log2Fold Change|.
Figure 10
Figure 10
Analysis of DEGs and SRMs in the arginine and proline metabolism pathway. (A) Enriched SRMs for the CG/DS groups. (B) Enriched DEGs for the CG/DS groups. |log2FC| denotes |log2Fold Change|. Solid line stands for direct reaction. Dashed line stands for indirect reaction, which means it have to go through multiple reactions.
Figure 11
Figure 11
Correlation network graph of DEGs and SRMs in the arginine and proline metabolism pathway for comparison of the CG and DS groups. The genes and metabolites color-coded according to fold-change between the CG and DS groups. |log2FC| denotes |log2Fold Change|.
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