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Transcriptome and Metabolome Analysis of Upland Cotton (Gossypium hirsutum) Seed Pretreatment with MgSO4 in Response to Salinity Stress - PubMed

  • ️Sat Jan 01 2022

Transcriptome and Metabolome Analysis of Upland Cotton (Gossypium hirsutum) Seed Pretreatment with MgSO4 in Response to Salinity Stress

Wei Ren et al. Life (Basel). 2022.

Abstract

Upland cotton (Gossypium hirsutum) is a salt-tolerant crop that can withstand high salinity levels without showing signs of harm to the plant. However, the plant is more prone to salinity stress at the germination stage and a poor germination as well as poor crop stand lead to a weak productivity. It is possible to obtain a comprehensive picture of the cotton seedling germination and establishment against salt stress by examining dynamic changes in the transcriptomic and metabolomic profiles. The reported study employed a pretreatment of cotton seeds by soaking them in 0.2% Magnesium Sulphate (MgSO4) solution at room temperature for 4, 8, and 12 h. The analysis of variance based on the studied traits emergence rate, above and underground plant parts' fresh weight measured, displayed significant differences of the three treatments compared with the control. A total of 28,801 and 264 differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) were discovered to code for biological processes such as response to salt stress, cellular response to salt stress, abscisic acid receptor PYR/PYL, regulation of seed growth and germination, and auxin-activated signaling pathways. A large amount of ethylene-responsive transcription factors (ERF) was identified (1235) as differentially expressed, followed by bHLH (252), WRKY (96), MYB (202), GATA (81), RABA (64), DIVARICATA (28), and MADs-box (26) in treated seedling samples. Functional enrichment analysis revealed the significant roles in the hormones and signal transduction, carbohydrates metabolism, and biosynthesis of amino acids, promoting salt stress tolerance. Our results indicated positive effects of MgSO4 at 4 h treatment on seedling germination and growth, seemingly by activating certain growth-regulating enzymes (auxins, gibberellins, jasmonates, abscisic acid, and salicylic acid) and metabolites (phenolic acids, flavonoids, and akaloids). Such pretreatment of MgSO4 on seeds would be beneficial in future cotton management under saline conditions to enhance good crop stand and productivity.

Keywords: DAMs; DEGs; RNA-seq; cotton; salinity tolerance; seed treatment.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1

Mean comparisons of phenotypic traits at different MgSO4 treatments on cotton seed under study; (a) germination percentage at 10 days after planting, (b) germination percentage at 25 days after planting, (c) root fresh weight at 25 days after planting (d) shoot fresh weight at 25 days after planting. Plots showed statistical differences among treated samples. Bar plots with overlapping error bars are statistically insignificant, similarly, letters on bars show statistical significance if samples do not share these letters with each other and vice versa. CK: control (0 h), M4: 4 h treatment of seeds with MgSO4, M8: 8 h treatment of seeds with MgSO4, M12: 12 h treatment of seeds with MgSO4.

Figure 2
Figure 2

Correlation matrix of control and different MgSO4 treatments samples for 4, 8, and 12 h on cotton seedlings. CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; MgSO4 treatment at 12 h, −1,2,3 representing replication.

Figure 3
Figure 3

Summary of Differentially Expressed Genes (DEGs); X-axis displays all possible comparisons for MgSO4 treatments in differential expression patterns. Y-axis represented the number of DEGs as: blue colored bars showing total DEGs; Orange colored revealing up-regulated; and Gray colored depicting down-regulated DEGs. CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; MgSO4 treatment at 12 h.

Figure 4
Figure 4

Venn diagrams illustrating DEGs. The sum of the numbers in each circle represents the total number of expressed genes within a comparison. In contrast, the numbers in the overlapping areas represent the number of expressed genes shared (a) among CK and treatment comparison groups and (b) among different treatment comparison groups of cotton seedlings. CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; MgSO4 treatment at 12 h.

Figure 5
Figure 5

Heat map showing KEGG enrichment analysis of significant DEGs grouped into 15 classes involved in different functional pathways changed their expression significantly in the CK and 0.2% MgSO4-treated sample groups (a) CK_vs_M4, (b) CK_vs_M8, (c) CK_vs_M12, (d) M4_vs_M8, (e) M4_vs_M12, and (f) M8_vs_M12. The color gradient in this shape’s background reveals the corresponding p-value. Legends on the right are the description of the color gradient of p-value and classes of functional pathways.

Figure 6
Figure 6

Quality control of metabolites identified in the experimental seedling sample extracts. (a) Pearson’s correlation coefficients; (b) Principal component analysis (PCA) of metabolites extract of cotton seedlings from CK and treated groups after 4, 8, and 12 h treatment with MgSO4; each sample in triplicates and quality control mix for metabolomics; (c) K-means diagram of the differentially accumulated metabolites among treated seedling sample groups (CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; M8: MgSO4 treatment at 8 h; M12: MgSO4 treatment at 12 h; −1,2,3 representing replications). The x-axis represents the sample groups, and the Y-axis represents the relative content of standardized metabolites. Sub-class represents the number of the metabolite category with the same changing trend, and the metabolite represents the number of metabolites in the category (metabolites within each sub-class are given in Supplementary Table S13).

Figure 7
Figure 7

Venn diagrams for the representation of consensus results of DAMs classifying the samples by metabolites accumulated in treated samples (a) among CK and treatment comparison groups and (b) among different treatment comparison groups of cotton seedlings. CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; MgSO4 treatment at 12 h.

Figure 8
Figure 8

Heat map analysis of DAMs exhibiting fold change of top significant (p < 0.05) DAMs grouped into more 16 classes related to different treatment groups and CK. The four columns represent the treatment groups and CK samples (Green: Control (0 h), Brown: M4 (4 h), Purple: M8 (8 h), Magenta: M12 (12 h)) with further three sub-divisions, one for each biological replicate in every sample group. The correlation coefficients were utilized to classify different features determined by Pearson correlation based on average/means as a clustering algorithm. The color gradient from green (–2) to red (2) depicts the number of compounds, presented as relative fold change.

Figure 9
Figure 9

Comparison of principal component analysis of (a) DAMs and (b) DEGs associated with Ck and MgSO4 treatments in cotton seedlings. (CK: 0 h, M4: 4 h, M8: 8 h, M12: 12 h).

Figure 10
Figure 10

Correlation network diagram for expression of DEGs and DAMs abundance related to Glucose-1-phosphate, A-Ketoglutaric acid, and L-Glutamine under salt stress from treated seedling sample comparison groups: (a) CK-vs-M4, (b) CK-vs-M8, (c) CK-vs-M12, CK: MgSO4 treatment at 0 h; M4: MgSO4 treatment at 4 h; M8: MgSO4 treatment at 8 h; M12: MgSO4 treatment at 12 h. The green circles represent the regulatory pathways metabolites and red circles are for the representation of genes involved in the expression. The solid connecting line is positive and dotted for negative correlations.

Figure 11
Figure 11

Validation of expression results using qRT-PCR representing the correlation between qRT-PCR and RNA-seq expression results for 10 selected DEGs related to salt-stress tolerance.

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References

    1. Liu Y., Ye N., Liu R., Chen M., Zhang J. H2O2 mediates the regulation of ABA catabolism and GA biosynthesis in Arabidopsis seed dormancy and germination. J. Exp. Bot. 2010;61:2979–2990. doi: 10.1093/jxb/erq125. - DOI - PMC - PubMed
    1. Wahid A., Perveen M., Gelani S., Basra S.M.A. Pretreatment of seed with H2O2 improves salt tolerance of wheat seedlings by alleviation of oxidative damage and expression of stress proteins. J. Plant Physiol. 2007;164:283–294. doi: 10.1016/j.jplph.2006.01.005. - DOI - PubMed
    1. Iqbal M.M., Khan T.M., Iqbal M.S., Khan A.H. Estimation of genetic potential for salt tolerance in Gossypium hirsutum L. J. Agric. Res. 2013;51:03681157.
    1. Parihar P., Singh S., Singh R., Singh V.P., Prasad S.M. Effect of salinity stress on plants and its tolerance strategies: A review. Environ. Sci. Pollut. Res. 2015;22:4056–4075. doi: 10.1007/s11356-014-3739-1. - DOI - PubMed
    1. Sarfraz Z., Iqbal M.S., Pan Z., Jia Y., He S., Wang Q., Qin H., Liu J., Liu H., Yang J., et al. Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton. BMC Genom. 2018;19:776. doi: 10.1186/s12864-018-5129-4. - DOI - PMC - PubMed

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