RustFungiGenomicsV1, Main, Exploration, bibRecord, 000066

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

Identifieur interne : 000066 ( Main/Exploration ); précédent : 000065; suivant : 000067

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

Auteurs : Hong Zhang [République populaire de Chine] ; Ying Fu [République populaire de Chine] ; Huan Guo [République populaire de Chine] ; Lu Zhang [République populaire de Chine] ; Changyou Wang [République populaire de Chine] ; Weining Song [République populaire de Chine] ; Zhaogui Yan [République populaire de Chine] ; Yajuan Wang [République populaire de Chine] ; Wanquan Ji [République populaire de Chine]

Source :

International journal of molecular sciences [ 1422-0067 ] ; 2019.

RBID : pubmed:30836695

Descripteurs français

KwdFr :
- Activation de la transcription (génétique), Basidiomycota (pathogénicité), Interactions hôte-pathogène (génétique), Maladies des plantes (génétique), Maladies des plantes (microbiologie), Plant (génétique), Protéome (génétique), Protéomique (méthodes), Régulation de l'expression des gènes végétaux (MeSH), Réseaux de régulation génique (génétique), Résistance à la maladie (génétique), Séquençage nucléotidique à haut débit (MeSH), Transcriptome (génétique), Triticum (croissance et développement), Triticum (génétique), Triticum (microbiologie).
MESH :
- croissance et développement : Triticum.
- génétique : Activation de la transcription, Interactions hôte-pathogène, Maladies des plantes, Plant, Protéome, Réseaux de régulation génique, Résistance à la maladie, Transcriptome, Triticum.
- microbiologie : Maladies des plantes, Triticum.
- méthodes : Protéomique.
- pathogénicité : Basidiomycota.
- Régulation de l'expression des gènes végétaux, Séquençage nucléotidique à haut débit.

English descriptors

KwdEn :
- Basidiomycota (pathogenicity), Disease Resistance (genetics), Gene Expression Regulation, Plant (MeSH), Gene Regulatory Networks (genetics), High-Throughput Nucleotide Sequencing (MeSH), Host-Pathogen Interactions (genetics), Plant Diseases (genetics), Plant Diseases (microbiology), Proteome (genetics), Proteomics (methods), Seedlings (genetics), Transcriptional Activation (genetics), Transcriptome (genetics), Triticum (genetics), Triticum (growth & development), Triticum (microbiology).
MESH :
- chemical , genetics : Proteome.
- genetics : Disease Resistance, Gene Regulatory Networks, Host-Pathogen Interactions, Plant Diseases, Seedlings, Transcriptional Activation, Transcriptome, Triticum.
- growth & development : Triticum.
- methods : Proteomics.
- microbiology : Plant Diseases, Triticum.
- pathogenicity : Basidiomycota.
- Gene Expression Regulation, Plant, High-Throughput Nucleotide Sequencing.

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.

DOI: 10.3390/ijms20051106
PubMed: 30836695
PubMed Central: PMC6429138

Affiliations:

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<term>Gene Regulatory Networks (genetics)</term>
<term>High-Throughput Nucleotide Sequencing (MeSH)</term>
<term>Host-Pathogen Interactions (genetics)</term>
<term>Plant Diseases (genetics)</term>
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<term>Proteome (genetics)</term>
<term>Proteomics (methods)</term>
<term>Seedlings (genetics)</term>
<term>Transcriptional Activation (genetics)</term>
<term>Transcriptome (genetics)</term>
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<term>Basidiomycota (pathogénicité)</term>
<term>Interactions hôte-pathogène (génétique)</term>
<term>Maladies des plantes (génétique)</term>
<term>Maladies des plantes (microbiologie)</term>
<term>Plant (génétique)</term>
<term>Protéome (génétique)</term>
<term>Protéomique (méthodes)</term>
<term>Régulation de l'expression des gènes végétaux (MeSH)</term>
<term>Réseaux de régulation génique (génétique)</term>
<term>Résistance à la maladie (génétique)</term>
<term>Séquençage nucléotidique à haut débit (MeSH)</term>
<term>Transcriptome (génétique)</term>
<term>Triticum (croissance et développement)</term>
<term>Triticum (génétique)</term>
<term>Triticum (microbiologie)</term>
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<keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Proteome</term>
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</keywords>
<keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Disease Resistance</term>
<term>Gene Regulatory Networks</term>
<term>Host-Pathogen Interactions</term>
<term>Plant Diseases</term>
<term>Seedlings</term>
<term>Transcriptional Activation</term>
<term>Transcriptome</term>
<term>Triticum</term>
</keywords>
<keywords scheme="MESH" qualifier="growth & development" xml:lang="en"><term>Triticum</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Activation de la transcription</term>
<term>Interactions hôte-pathogène</term>
<term>Maladies des plantes</term>
<term>Plant</term>
<term>Protéome</term>
<term>Réseaux de régulation génique</term>
<term>Résistance à la maladie</term>
<term>Transcriptome</term>
<term>Triticum</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Proteomics</term>
</keywords>
<keywords scheme="MESH" qualifier="microbiologie" xml:lang="fr"><term>Maladies des plantes</term>
<term>Triticum</term>
</keywords>
<keywords scheme="MESH" qualifier="microbiology" xml:lang="en"><term>Plant Diseases</term>
<term>Triticum</term>
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<keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Protéomique</term>
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<term>High-Throughput Nucleotide Sequencing</term>
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<keywords scheme="MESH" xml:lang="fr"><term>Régulation de l'expression des gènes végétaux</term>
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<front><div type="abstract" xml:lang="en">Stripe rust, caused by the pathogen <i>Puccinia striiformis</i>
 f. sp. <i>tritici</i>
 (<i>Pst</i>
), is an important fungal foliar disease of wheat (<i>Triticum aestivum</i>
). To study the mechanism underlying the defense of wheat to <i>Pst</i>
, 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 <i>Pst</i>
-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 <i>Pst</i>
 resistance. This study indicated that the transcriptional regulation model plays an important role in activating resistance-related genes in wheat responding to <i>Pst</i>
 stress.</div>
</front>
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</JournalIssue>
<Title>International journal of molecular sciences</Title>
<ISOAbbreviation>Int J Mol Sci</ISOAbbreviation>
</Journal>
<ArticleTitle>Transcriptome and Proteome-Based Network Analysis Reveals a Model of Gene Activation in Wheat Resistance to Stripe Rust.</ArticleTitle>
<ELocationID EIdType="pii" ValidYN="Y">E1106</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.3390/ijms20051106</ELocationID>
<Abstract><AbstractText>Stripe rust, caused by the pathogen <i>Puccinia striiformis</i>
 f. sp. <i>tritici</i>
 (<i>Pst</i>
), is an important fungal foliar disease of wheat (<i>Triticum aestivum</i>
). To study the mechanism underlying the defense of wheat to <i>Pst</i>
, 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 <i>Pst</i>
-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 <i>Pst</i>
 resistance. This study indicated that the transcriptional regulation model plays an important role in activating resistance-related genes in wheat responding to <i>Pst</i>
 stress.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Hong</ForeName>
<Initials>H</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. zhangh1129@nwafu.edu.cn.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Fu</LastName>
<ForeName>Ying</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. fuying2008@126.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Guo</LastName>
<ForeName>Huan</ForeName>
<Initials>H</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. guohuan2018@163.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Lu</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. zhanglu162049@163.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Changyou</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. chywang2004@126.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Song</LastName>
<ForeName>Weining</ForeName>
<Initials>W</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. sweining2002@yahoo.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Yan</LastName>
<ForeName>Zhaogui</ForeName>
<Initials>Z</Initials>
<Identifier Source="ORCID">0000-0002-2246-9251</Identifier>
<AffiliationInfo><Affiliation>College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China. gyan@mail.hzau.edu.cn.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Yajuan</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. wangyj7604@163.com.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Shaanxi Research Station of Crop Gene Resource & Germplasm Enhancement, Ministry of Agriculture, Shaanxi 712100, China. wangyj7604@163.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ji</LastName>
<ForeName>Wanquan</ForeName>
<Initials>W</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Shaanxi 712100, China. jiwanquan2008@126.com.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Shaanxi Research Station of Crop Gene Resource & Germplasm Enhancement, Ministry of Agriculture, Shaanxi 712100, China. jiwanquan2008@126.com.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>2016YFD0100302</GrantID>
<Agency>The National Key Research and Development Program of China</Agency>
<Country></Country>
</Grant>
<Grant><GrantID>2017YFD0100701</GrantID>
<Agency>The National Key Research and Development Program of China</Agency>
<Country></Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2019</Year>
<Month>03</Month>
<Day>04</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>Switzerland</Country>
<MedlineTA>Int J Mol Sci</MedlineTA>
<NlmUniqueID>101092791</NlmUniqueID>
<ISSNLinking>1422-0067</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D020543">Proteome</NameOfSubstance>
</Chemical>
</ChemicalList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D001487" MajorTopicYN="N">Basidiomycota</DescriptorName>
<QualifierName UI="Q000472" MajorTopicYN="N">pathogenicity</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D060467" MajorTopicYN="N">Disease Resistance</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018506" MajorTopicYN="N">Gene Expression Regulation, Plant</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D053263" MajorTopicYN="N">Gene Regulatory Networks</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D059014" MajorTopicYN="N">High-Throughput Nucleotide Sequencing</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D054884" MajorTopicYN="N">Host-Pathogen Interactions</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D010935" MajorTopicYN="N">Plant Diseases</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
<QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D020543" MajorTopicYN="N">Proteome</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D040901" MajorTopicYN="N">Proteomics</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D036226" MajorTopicYN="N">Seedlings</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015533" MajorTopicYN="N">Transcriptional Activation</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D059467" MajorTopicYN="N">Transcriptome</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D014908" MajorTopicYN="N">Triticum</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
<QualifierName UI="Q000254" MajorTopicYN="N">growth & development</QualifierName>
<QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">WGCNA</Keyword>
<Keyword MajorTopicYN="N">iTRAQ</Keyword>
<Keyword MajorTopicYN="N">splicing regulator</Keyword>
<Keyword MajorTopicYN="N">stripe rust</Keyword>
<Keyword MajorTopicYN="N">transcriptome-proteome associated analysis</Keyword>
<Keyword MajorTopicYN="N">wheat</Keyword>
</KeywordList>
</MedlineCitation>
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<Month>01</Month>
<Day>14</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2019</Year>
<Month>02</Month>
<Day>24</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2019</Year>
<Month>02</Month>
<Day>27</Day>
</PubMedPubDate>
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<Month>3</Month>
<Day>7</Day>
<Hour>6</Hour>
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Transcriptome and Proteome-Based Network Analysis Reveals a Model of Gene Activation in Wheat Resistance to Stripe Rust.

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

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