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Transcriptome and Proteome-Based Network Analysis Reveals a Model of Gene Activation in Wheat Resistance to Stripe Rust

Hong Zhang, Ying Fu, Huan Guo, Lu Zhang, Changyou Wang, Weining Song, Zhaogui Yan, Yajuan Wang, Wanquan Ji.

Int. J. Mol. Sci.

DOI:10.3390/ijms20051106

 

 

Abstract: Stripe rust, caused by the pathogen Puccinia striiformis f. sp. tritici (Pst), is an important fungal foliar disease of wheat (Triticum aestivum). To study the mechanism underlying the defense of wheat to Pst, we used the next-generation sequencing and isobaric tags for relative and absolute quantification (iTRAQ) technologies to generate transcriptomic and proteomic profiles of seedling leaves at different stages under conditions of pathogen stress. By conducting comparative proteomic analysis using iTRAQ, we identified 2050, 2190, and 2258 differentially accumulated protein species at 24, 48, and 72 h post-inoculation (hpi). Using pairwise comparisons and weighted gene co-expression network analysis (WGCNA) of the transcriptome, we identified a stress stage-specific module enriching in transcription regulator genes. The homologs of several regulators, including splicing and transcription factors, were similarly identified as hub genes operating in the Pst-induced response network. Moreover, the Hsp70 protein were predicted as a key point in protein–protein interaction (PPI) networks from STRING database. Taking the genetics resistance gene locus into consideration, we identified 32 induced proteins in chromosome 1BS as potential candidates involved in Pst resistance. This study indicated that the transcriptional regulation model plays an important role in activating resistance-related genes in wheat responding to Pst stress.