Transcriptome and Proteome-Based Network Analysis Reveals a Model of Gene Activation in Wheat Resistance to Stripe Rust
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 quantif...
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Published in | International journal of molecular sciences Vol. 20; no. 5; p. 1106 |
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Main Authors | , , , , , , , , |
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ISSN | 1422-0067 1661-6596 1422-0067 |
DOI | 10.3390/ijms20051106 |
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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. |
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AbstractList | 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.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. 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. 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. Stripe rust, caused by the pathogen f. sp. ( ), is an important fungal foliar disease of wheat ( ). To study the mechanism underlying the defense of wheat to , 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 -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 resistance. This study indicated that the transcriptional regulation model plays an important role in activating resistance-related genes in wheat responding to stress. [...]the mechanism underlying wheat resistance activation in response to Pst remains to be fully elucidated. Taking the classical genetics resistance gene locus into consideration, we used gene expression patterns and the co-expression relationships to construct the regulative module network of wheat responding to stripe rust infection with an edge weight higher than 0.1. [...]we delineated a module associated with core transcription processes, including spliceosome and transcript regulator function, in the early stages of the response of the N9134 wheat resistant line to Pst-inoculation. 2. [...]significant differential enrichment was found for phagosome, circadian rhythm-plant, and flavonoid biosynthesis at 24 and 48 hpi only; for glutathione metabolism, carbon metabolism, basal transcription factors, citrate cycle, glyoxylate and dicarboxylate metabolism, and riboflavin metabolism at 48 and 72 hpi only; and for arginine and proline metabolism, one carbon pool by folate, biosynthesis of amino acids, sulfur metabolism, alanine, aspartate and glutamate metabolism, monobactam biosynthesis, and selenocompound metabolism at 48 hpi only. |
Author | Yan, Zhaogui Fu, Ying Zhang, Lu Wang, Yajuan Wang, Changyou Zhang, Hong Song, Weining Ji, Wanquan Guo, Huan |
AuthorAffiliation | 3 Shaanxi Research Station of Crop Gene Resource & Germplasm Enhancement, Ministry of Agriculture, Shaanxi 712100, China 2 College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China; gyan@mail.hzau.edu.cn 1 State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China; zhangh1129@nwafu.edu.cn (H.Z.); fuying2008@126.com (Y.F.); guohuan2018@163.com (H.G.); zhanglu162049@163.com (L.Z.); chywang2004@126.com (C.W.); sweining2002@yahoo.com (W.S.); wangyj7604@163.com (Y.W.) |
AuthorAffiliation_xml | – name: 3 Shaanxi Research Station of Crop Gene Resource & Germplasm Enhancement, Ministry of Agriculture, Shaanxi 712100, China – name: 2 College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China; gyan@mail.hzau.edu.cn – name: 1 State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China; zhangh1129@nwafu.edu.cn (H.Z.); fuying2008@126.com (Y.F.); guohuan2018@163.com (H.G.); zhanglu162049@163.com (L.Z.); chywang2004@126.com (C.W.); sweining2002@yahoo.com (W.S.); wangyj7604@163.com (Y.W.) |
Author_xml | – sequence: 1 givenname: Hong surname: Zhang fullname: Zhang, Hong – sequence: 2 givenname: Ying surname: Fu fullname: Fu, Ying – sequence: 3 givenname: Huan surname: Guo fullname: Guo, Huan – sequence: 4 givenname: Lu surname: Zhang fullname: Zhang, Lu – sequence: 5 givenname: Changyou surname: Wang fullname: Wang, Changyou – sequence: 6 givenname: Weining surname: Song fullname: Song, Weining – sequence: 7 givenname: Zhaogui orcidid: 0000-0002-2246-9251 surname: Yan fullname: Yan, Zhaogui – sequence: 8 givenname: Yajuan surname: Wang fullname: Wang, Yajuan – sequence: 9 givenname: Wanquan surname: Ji fullname: Ji, Wanquan |
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Keywords | iTRAQ wheat stripe rust transcriptome-proteome associated analysis WGCNA splicing regulator |
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Snippet | 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... Stripe rust, caused by the pathogen f. sp. ( ), is an important fungal foliar disease of wheat ( ). To study the mechanism underlying the defense of wheat to ,... [...]the mechanism underlying wheat resistance activation in response to Pst remains to be fully elucidated. Taking the classical genetics resistance gene... Stripe rust, caused by the pathogen Puccinia striiformis f. sp. tritici ( Pst ), is an important fungal foliar disease of wheat ( Triticum aestivum ). To study... |
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SubjectTerms | Basidiomycota - pathogenicity Biosynthesis Disease Resistance - genetics Enzymes Flavonoids Gene expression Gene Expression Regulation, Plant Gene Regulatory Networks - genetics Genomes High-Throughput Nucleotide Sequencing Host-Pathogen Interactions - genetics Infections Metabolism Pathogens Peptides Plant Diseases - genetics Plant Diseases - microbiology Protein expression Proteins Proteome - genetics Proteomics Proteomics - methods Seedlings - genetics Studies Transcriptional Activation - genetics Transcriptome - genetics Triticum - genetics Triticum - growth & development Triticum - microbiology Wheat |
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Title | Transcriptome and Proteome-Based Network Analysis Reveals a Model of Gene Activation in Wheat Resistance to Stripe Rust |
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