Pathogen recognition in compatible plant-microbe interactions.
Identifieur interne : 000950 ( Main/Exploration ); précédent : 000949; suivant : 000951Pathogen recognition in compatible plant-microbe interactions.
Auteurs : Fabio Rezzonico [Suisse] ; Oliver Rupp [Allemagne] ; Johannes Fahrentrapp [Suisse]Source :
- Scientific reports [ 2045-2322 ] ; 2017.
Descripteurs français
- KwdFr :
- Analyse de profil d'expression de gènes (méthodes), Botrytis (pathogénicité), Feuilles de plante (génétique), Feuilles de plante (microbiologie), Interactions hôte-pathogène (MeSH), Lycopersicon esculentum (génétique), Lycopersicon esculentum (microbiologie), Maladies des plantes (génétique), Maladies des plantes (microbiologie), Phytophthora infestans (pathogénicité), Protéines végétales (génétique), Régulation de l'expression des gènes végétaux (MeSH), Saccharomycetales (pathogénicité), Simulation numérique (MeSH), Spécificité d'espèce (MeSH), Séquençage de l'exome entier (méthodes), Séquençage nucléotidique à haut débit (MeSH), Théorème de Bayes (MeSH).
- MESH :
- génétique : Feuilles de plante, Lycopersicon esculentum, Maladies des plantes, Protéines végétales.
- microbiologie : Feuilles de plante, Lycopersicon esculentum, Maladies des plantes.
- méthodes : Analyse de profil d'expression de gènes, Séquençage de l'exome entier.
- pathogénicité : Botrytis, Phytophthora infestans, Saccharomycetales.
- Interactions hôte-pathogène, Régulation de l'expression des gènes végétaux, Simulation numérique, Spécificité d'espèce, Séquençage nucléotidique à haut débit, Théorème de Bayes.
English descriptors
- KwdEn :
- Bayes Theorem (MeSH), Botrytis (pathogenicity), Computer Simulation (MeSH), Gene Expression Profiling (methods), Gene Expression Regulation, Plant (MeSH), High-Throughput Nucleotide Sequencing (MeSH), Host-Pathogen Interactions (MeSH), Lycopersicon esculentum (genetics), Lycopersicon esculentum (microbiology), Phytophthora infestans (pathogenicity), Plant Diseases (genetics), Plant Diseases (microbiology), Plant Leaves (genetics), Plant Leaves (microbiology), Plant Proteins (genetics), Saccharomycetales (pathogenicity), Species Specificity (MeSH), Whole Exome Sequencing (methods).
- MESH :
- chemical , genetics : Plant Proteins.
- genetics : Lycopersicon esculentum, Plant Diseases, Plant Leaves.
- methods : Gene Expression Profiling, Whole Exome Sequencing.
- microbiology : Lycopersicon esculentum, Plant Diseases, Plant Leaves.
- pathogenicity : Botrytis, Phytophthora infestans, Saccharomycetales.
- Bayes Theorem, Computer Simulation, Gene Expression Regulation, Plant, High-Throughput Nucleotide Sequencing, Host-Pathogen Interactions, Species Specificity.
Abstract
Microbial infections in plant leaves remain a major challenge in agriculture. Hence an understanding of disease mechanisms at the molecular level is of paramount importance for identifying possible intervention points for their control. Whole-transcriptome changes during early disease stages in susceptible plant species are less well-documented than those of resistant ones. This study focuses on the differential transcriptional changes at 24 hours post inoculation (hpi) in tomato leaflets affected by three pathogens: (1) Phytophthora infestans, (2) Botrytis cinerea, and (3) Oidium neolycopersici. Grey mould (B. cinerea) was the disease that had progressed the most by 24 hpi, both in terms of visible symptoms as well as differential gene expression. By means of RNA-seq, we identified 50 differentially expressed tomato genes specifically induced by B. cinerea infection and 18 specifically induced by P. infestans infection at 24 hpi. Additionally, a set of 63 genes were differentially expressed during all three diseases when compared by a Bayesian approach to their respective mock infections. And Gene expression patterns were found to also depend on the inoculation technique. These findings suggest a specific and distinct transcriptional response in plant leaf tissue in reaction to B. cinerea and P. infestans invasion at 24 hpi, indicating that plants may recognize the attacking pathogen.
DOI: 10.1038/s41598-017-04792-5
PubMed: 28743967
PubMed Central: PMC5526865
Affiliations:
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(pathogénicité)</term><term>Protéines végétales (génétique)</term><term>Régulation de l'expression des gènes végétaux (MeSH)</term><term>Saccharomycetales (pathogénicité)</term><term>Simulation numérique (MeSH)</term><term>Spécificité d'espèce (MeSH)</term><term>Séquençage de l'exome entier (méthodes)</term><term>Séquençage nucléotidique à haut débit (MeSH)</term><term>Théorème de Bayes (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Plant Proteins</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Lycopersicon esculentum</term><term>Plant Diseases</term><term>Plant Leaves</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Feuilles de plante</term><term>Lycopersicon esculentum</term><term>Maladies des plantes</term><term>Protéines végétales</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Gene Expression Profiling</term><term>Whole 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Hence an understanding of disease mechanisms at the molecular level is of paramount importance for identifying possible intervention points for their control. Whole-transcriptome changes during early disease stages in susceptible plant species are less well-documented than those of resistant ones. This study focuses on the differential transcriptional changes at 24 hours post inoculation (hpi) in tomato leaflets affected by three pathogens: (1) Phytophthora infestans, (2) Botrytis cinerea, and (3) Oidium neolycopersici. Grey mould (B. cinerea) was the disease that had progressed the most by 24 hpi, both in terms of visible symptoms as well as differential gene expression. By means of RNA-seq, we identified 50 differentially expressed tomato genes specifically induced by B. cinerea infection and 18 specifically induced by P. infestans infection at 24 hpi. Additionally, a set of 63 genes were differentially expressed during all three diseases when compared by a Bayesian approach to their respective mock infections. And Gene expression patterns were found to also depend on the inoculation technique. These findings suggest a specific and distinct transcriptional response in plant leaf tissue in reaction to B. cinerea and P. infestans invasion at 24 hpi, indicating that plants may recognize the attacking pathogen.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28743967</PMID><DateCompleted><Year>2019</Year><Month>02</Month><Day>27</Day></DateCompleted><DateRevised><Year>2019</Year><Month>02</Month><Day>27</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2045-2322</ISSN><JournalIssue CitedMedium="Internet"><Volume>7</Volume><Issue>1</Issue><PubDate><Year>2017</Year><Month>07</Month><Day>25</Day></PubDate></JournalIssue><Title>Scientific reports</Title><ISOAbbreviation>Sci Rep</ISOAbbreviation></Journal><ArticleTitle>Pathogen recognition in compatible plant-microbe interactions.</ArticleTitle><Pagination><MedlinePgn>6383</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/s41598-017-04792-5</ELocationID><Abstract><AbstractText>Microbial infections in plant leaves remain a major challenge in agriculture. Hence an understanding of disease mechanisms at the molecular level is of paramount importance for identifying possible intervention points for their control. Whole-transcriptome changes during early disease stages in susceptible plant species are less well-documented than those of resistant ones. This study focuses on the differential transcriptional changes at 24 hours post inoculation (hpi) in tomato leaflets affected by three pathogens: (1) Phytophthora infestans, (2) Botrytis cinerea, and (3) Oidium neolycopersici. Grey mould (B. cinerea) was the disease that had progressed the most by 24 hpi, both in terms of visible symptoms as well as differential gene expression. By means of RNA-seq, we identified 50 differentially expressed tomato genes specifically induced by B. cinerea infection and 18 specifically induced by P. infestans infection at 24 hpi. Additionally, a set of 63 genes were differentially expressed during all three diseases when compared by a Bayesian approach to their respective mock infections. And Gene expression patterns were found to also depend on the inoculation technique. These findings suggest a specific and distinct transcriptional response in plant leaf tissue in reaction to B. cinerea and P. infestans invasion at 24 hpi, indicating that plants may recognize the attacking pathogen.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Rezzonico</LastName><ForeName>Fabio</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Research Group Environmental Genomics and Systems Biology, Zurich University of Applied Sciences, Wädenswil, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rupp</LastName><ForeName>Oliver</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Giessen, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fahrentrapp</LastName><ForeName>Johannes</ForeName><Initials>J</Initials><Identifier Source="ORCID">0000-0003-4259-6634</Identifier><AffiliationInfo><Affiliation>Research Group for Viticulture, Zurich University of Applied Sciences, Wädenswil, Switzerland. johannes.fahrentrapp@zhaw.ch.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>07</Month><Day>25</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Sci Rep</MedlineTA><NlmUniqueID>101563288</NlmUniqueID><ISSNLinking>2045-2322</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D010940">Plant Proteins</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001499" MajorTopicYN="N">Bayes Theorem</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D020171" MajorTopicYN="N">Botrytis</DescriptorName><QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003198" MajorTopicYN="N">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D020869" MajorTopicYN="N">Gene Expression Profiling</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018506" MajorTopicYN="N">Gene Expression Regulation, Plant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D059014" MajorTopicYN="N">High-Throughput Nucleotide Sequencing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D054884" MajorTopicYN="N">Host-Pathogen Interactions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018551" MajorTopicYN="N">Lycopersicon esculentum</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000382" MajorTopicYN="Y">microbiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055750" MajorTopicYN="N">Phytophthora infestans</DescriptorName><QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010935" MajorTopicYN="N">Plant Diseases</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010940" MajorTopicYN="N">Plant Proteins</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004718" MajorTopicYN="N">Saccharomycetales</DescriptorName><QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013045" MajorTopicYN="N">Species Specificity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073359" MajorTopicYN="N">Whole Exome Sequencing</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>02</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>05</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>7</Month><Day>27</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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IdType="pubmed">26456092</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Allemagne</li><li>Suisse</li></country></list><tree><country name="Suisse"><noRegion><name sortKey="Rezzonico, Fabio" sort="Rezzonico, Fabio" uniqKey="Rezzonico F" first="Fabio" last="Rezzonico">Fabio Rezzonico</name></noRegion><name sortKey="Fahrentrapp, Johannes" sort="Fahrentrapp, Johannes" uniqKey="Fahrentrapp J" first="Johannes" last="Fahrentrapp">Johannes Fahrentrapp</name></country><country name="Allemagne"><noRegion><name sortKey="Rupp, Oliver" sort="Rupp, Oliver" uniqKey="Rupp O" first="Oliver" last="Rupp">Oliver Rupp</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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