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Key Maize Drought-Responsive Genes and Pathways Revealed by Comparative Transcriptome and Physiological Analyses of Contrasting Inbred Lines

Overview
Journal Int J Mol Sci
Publisher MDPI
Date 2019 Mar 16
PMID 30871211
Citations 49
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Abstract

To unravel the molecular mechanisms underpinning maize ( L.) drought stress tolerance, we conducted comprehensive comparative transcriptome and physiological analyses of drought-tolerant YE8112 and drought-sensitive MO17 inbred line seedlings that had been exposed to drought treatment for seven days. Resultantly, YE8112 seedlings maintained comparatively higher leaf relative water and proline contents, greatly increased peroxidase activity, but decreased malondialdehyde content, than MO17 seedlings. Using an RNA sequencing (RNA-seq)-based approach, we identified a total of 10,612 differentially expressed genes (DEGs). From these, we mined out four critical sets of drought responsive DEGs, including 80 specific to YE8112, 5140 shared between the two lines after drought treatment (SD_TD), five DEGs of YE8112 also regulated in SD_TD, and four overlapping DEGs between the two lines. Drought-stressed YE8112 DEGs were primarily associated with nitrogen metabolism and amino-acid biosynthesis pathways, whereas MO17 DEGs were enriched in the ribosome pathway. Additionally, our physiological analyses results were consistent with the predicted RNA-seq-based findings. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) analysis and the RNA-seq results of twenty representative DEGs were highly correlated (² = 98.86%). Crucially, tolerant line YE8112 drought-responsive genes were predominantly implicated in stress signal transduction; cellular redox homeostasis maintenance; , , , and transcriptional factor modulated; carbohydrate synthesis and cell-wall remodeling; amino acid biosynthesis; and protein ubiquitination processes. Our findings offer insights into the molecular networks mediating maize drought stress tolerance.

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References
1.
Reidy B, Nosberger J, Fleming A . Differential expression of alpha- and beta-expansin genes in the elongating leaf of Festuca pratensis. Plant Mol Biol. 2001; 46(4):491-504. DOI: 10.1023/a:1010621417854. View

2.
Livak K, Schmittgen T . Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2002; 25(4):402-8. DOI: 10.1006/meth.2001.1262. View

3.
Wang W, Vinocur B, Shoseyov O, Altman A . Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci. 2004; 9(5):244-52. DOI: 10.1016/j.tplants.2004.03.006. View

4.
Nielsen T, Rung J, Villadsen D . Fructose-2,6-bisphosphate: a traffic signal in plant metabolism. Trends Plant Sci. 2004; 9(11):556-63. DOI: 10.1016/j.tplants.2004.09.004. View

5.
Mao X, Cai T, Olyarchuk J, Wei L . Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005; 21(19):3787-93. DOI: 10.1093/bioinformatics/bti430. View