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. 2023 Feb 3:13:1110910.
doi: 10.3389/fpls.2022.1110910. eCollection 2022.

Transcriptome-based analysis of key pathways relating to yield formation stage of foxtail millet under different drought stress conditions

Jing Wang  1 , Zexin Sun  1 , Xinning Wang  1 , Ying Tang  1 , Xinyi Li  1 , Chuanyou Ren  1 , Jingyao Ren  1 , Xiaoguang Wang  1 , Chunji Jiang  1 , Chao Zhong  1 , Shuli Zhao  1 , He Zhang  1 , Xibo Liu  1 , Shuli Kang  1 , Xinhua Zhao  1 , Haiqiu Yu  1
Affiliations

Transcriptome-based analysis of key pathways relating to yield formation stage of foxtail millet under different drought stress conditions

Jing Wang et al. Front Plant Sci. .

Abstract

Although foxtail millet, as small Panicoid crop, is of drought resilient, drought stress has a significant effect on panicle of foxtail millet at the yield formation stage. In this study, the changes of panicle morphology, photosynthesis, antioxidant protective enzyme system, reactive oxygen species (ROS) system, and osmotic regulatory substance and RNA-seq of functional leaves under light drought stress (LD), heavy drought stress (HD), light drought control (LDCK) and heavy drought control (HDCK) were studied to get a snap-shot of specific panicle morphological changes, physiological responses and related molecular mechanisms. The results showed that the length and weight of panicle had decreased, but with increased empty abortive rate, and then yield dropped off 14.9% and 36.9%, respectively. The photosynthesis of millet was significantly decreased, like net photosynthesis rate, stomatal conductance and transpiration rate, especially under HD treatment with reluctant recovery from rehydration. Under LD and HD treatment, the peroxidase (POD) was increased by 34% and 14% and the same as H2O2 by 34.7% and 17.2% compared with LDCK and HDCK. The ability to produce and inhibit O2- free radicals under LD treatment was higher than HD. The content of soluble sugar was higher under LD treatment but the proline was higher under HD treatment. Through RNA-seq analysis, there were 2,393 and 3,078 different genes expressed under LD and HD treatment. According to the correlation analysis between weighted gene coexpression network analysis (WGCNA) and physiological traits, the co-expression network of several modules with high correlation was constructed, and some hub genes of millet in response to drought stress were found. The expression changes relating to carbon fixation, sucrose and starch synthesis, lignin synthesis, gibberellin synthesis, and proline synthesis of millet were specifically analyzed. These findings provide a full perspective on how drought affects the yield formation of foxtail millet by constructing one work model thereby providing theoretical foundation for hub genes exploration and drought resistance breeding of foxtail millet.

Keywords: DEGs; RNA-seq; drought stress; foxtail millet; physiological index; yield formation.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The morphology changes of panicle under different drought treatment and control.
Figure 2
Figure 2
Antioxidant enzyme activities, ROS content, osmotic regulatory substance and photosynthetic characteristics under different drought treatment; (A) peroxidase activity (POD); (B) superoxide dismutase activity (SOD); (C) Anti-superoxide anion viability unit (ASAFR); (D) soluble sugars content (SS); (E) H2O2 content; (F) proline content (Pro); (G) Net photosynthetic rate (Pn); (H) Stomatal conductivity (Gs); (I) Transpiration rate (Tr). *P<0.05, **P<0.01.
Figure 3
Figure 3
Number of expressed genes with and without simulated drought. The number of genes was selected based on the cut-off values of FDR ≤0.05 and |log2 FC|≥ 1. (A) Number of genes expressed in each treatment under drought stress. (B) Summary of the number of DEGs under drought stress; (C) Venn diagrams, representing DEGs including upregulated genes in LDCK and LD and HDCK and HD; (D) Venn diagrams, representing DEGs including downregulated genes in LDCK and LD and HDCK and HD; (E) Comparison of photosynthesis under drought stress; (F) Synthesis of sucrose and starch under genetic drought stress.
Figure 4
Figure 4
KEGG enrichment analysis of foxtail millet leaves under LD and HD treatment. (A) KEGG analysis of differentially expressed genes under LD; (B) KEGG analysis of differentially expressed genes under HD.
Figure 5
Figure 5
Weighted gene co-expression network analysis (WGCNA) of effectively expressed genes under LD and HD treatment. (A) Hierarchical cluster tree showing co-expression modules identified by WGCNA. Each leaf in the tree represents one gene. The major tree branches constitute 19 modules labeled with different colors; (B) Correlation analysis between gene co-expression network modules and physiological indices. The horizontal axis represents different physiological traits, and the vertical axis represents the module eigengenes in each module. Each frame contains the corresponding correlations and P values. *P<0.05, **P<0.01, ***P<0.001.
Figure 6
Figure 6
Co-expression regulatory network analysis of five key co-expression modules. (A) Co-expression regulatory network analysis of the MM06 module; (B) Co-expression regulatory network analysis of the MM13 module; (C) Co-expression regulatory network analysis of the MM14 module; (D) Co-expression regulatory network analysis of the MM04 module; (E) Co-expression regulatory network analysis of the MM06 module.
Figure 7
Figure 7
Photosynthetic carbon sequestration with sucrose and starch and synthesis, gibberellin synthesis under drought stress gene changes. The color patch represents the FPKM value. Red and blue indicate significant upward and downward revisions Gene (log2 |fold-change| ≥ 1). (A) Heat map of drought response DEGs involved in photosynthetic carbon fixation, sucrose and starch synthesis pathways under drought stress. (B) Heat map of drought-responsive DEGs involved in gibberellin synthetic pathways under drought stress.
Figure 8
Figure 8
Lignin synthesis, changes in proline synthesis genes under drought stress. The color patch represents the FPKM value. Red and blue indicate Significant upward and downward revisions Gene (log2 |fold-change| ≥ 1). (A) Heat map of drought response DEGs involved in lignin synthesis pathways under drought stress. (B) Heat map of drought response DEGs involved in proline synthesis pathways under drought stress.
Figure 9
Figure 9
Correlation between qRT-PCR and RNA-seq based on their respective data from twelve candidate transcripts. Each point represents a fold change value of expression at LD or HD compared with that of CK (A) AGPL3; (B) P5CS2; (C) GLU3; (D) PSB28; (E) ADC2; (F) ACS1; (G) BGLU7; (H) CPA; (I) TPP9; (J) CIN1.
Figure 10
Figure 10
Regulation model of foxtail millet under drought stress at yield formation stage and the key pathway including phytohormones, antioxidants, phenylpropanoid synthesis pathways, osmotic regulatory pathways, and photosynthetic carbon fixation pathways. Red font indicates increased and up-regulated change. Green font indicates decreased and down-regulated change.
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References

    1. Abdel-Ghany S. E., Ullah F., Ben-Hur A., Reddy A. S. N. (2020). Transcriptome analysis of drought-resistant and drought-sensitive sorghum (Sorghum bicolor) genotypes in response to PEG-induced drought stress. Int. J. Mol. Sci. 21, 772. doi: 10.3390/ijms21030772 - DOI - PMC - PubMed
    1. Alscher R. G., Erturk N., Heath L. S. (2002). Role of superoxide dismutases (SODs) in controlling oxidative stress in plants. J. Exp. Bot. 53 (372), 1331–1341. doi: 10.1093/jexbot/53.372.1331 - DOI - PubMed
    1. Austin D. F. (2006). Fox-tail millets (Setaria: Poaceae) abandoned food in two hemispheres. Econ Bot. 60, 143–158. doi: 10.1663/0013-0001(2006)60[143:FMSPFI]2.0.CO;2 - DOI
    1. Bai Y., Feng Z., Paerhati M., Wang J. (2021). Phenylpropanoid metabolism enzyme activities and gene expression in postharvest melons inoculated with Alternaria alternate . Appl. Biol. Chem. 64, 83. doi: 10.1186/s13765-021-00654-x - DOI
    1. Bennetzen J. L., Schmutz J., Wang H., Percifield R., Hawkins J., Pontaroli A. C., et al. . (2012). Reference genome sequence of the model plant setaria. Nat. Biotechnol. 30, 555–561. doi: 10.1038/nbt.2196 - DOI - PubMed

Grants and funding

This work was supported by the National Key Research and Development Program of China (2019YFD1002204); Shenyang Agricultural University introduced talent research project (20153042).