Reference gene validation for quantitative RT-PCR during biotic and abiotic stresses in Vitis vinifera.
Identifieur interne : 000486 ( Main/Exploration ); précédent : 000485; suivant : 000487Reference gene validation for quantitative RT-PCR during biotic and abiotic stresses in Vitis vinifera.
Auteurs : Alexandre Filipe Borges [Portugal] ; Catarina Fonseca [Portugal] ; Ricardo Boavida Ferreira [Portugal] ; Ana Maria Lourenço [Portugal] ; Sara Monteiro [Portugal]Source :
- PloS one [ 1932-6203 ] ; 2014.
Descripteurs français
- KwdFr :
- Analyse de profil d'expression de gènes (MeSH), Biologie informatique (MeSH), Feuilles de plante (effets des radiations), Feuilles de plante (génétique), Feuilles de plante (microbiologie), Gènes de plante (MeSH), Méthode de Monte Carlo (MeSH), Rayons ultraviolets (MeSH), Réaction de polymérisation en chaine en temps réel (MeSH), Régulation de l'expression des gènes végétaux (MeSH), Spectrophotométrie UV (MeSH), Stress physiologique (MeSH), Vitis (effets des radiations), Vitis (génétique), Vitis (microbiologie).
- MESH :
- effets des radiations : Feuilles de plante, Vitis.
- génétique : Feuilles de plante, Vitis.
- microbiologie : Feuilles de plante, Vitis.
- Analyse de profil d'expression de gènes, Biologie informatique, Gènes de plante, Méthode de Monte Carlo, Rayons ultraviolets, Réaction de polymérisation en chaine en temps réel, Régulation de l'expression des gènes végétaux, Spectrophotométrie UV, Stress physiologique.
English descriptors
- KwdEn :
- Computational Biology (MeSH), Gene Expression Profiling (MeSH), Gene Expression Regulation, Plant (MeSH), Genes, Plant (MeSH), Monte Carlo Method (MeSH), Plant Leaves (genetics), Plant Leaves (microbiology), Plant Leaves (radiation effects), Real-Time Polymerase Chain Reaction (MeSH), Spectrophotometry, Ultraviolet (MeSH), Stress, Physiological (MeSH), Ultraviolet Rays (MeSH), Vitis (genetics), Vitis (microbiology), Vitis (radiation effects).
- MESH :
- genetics : Plant Leaves, Vitis.
- microbiology : Plant Leaves, Vitis.
- radiation effects : Plant Leaves, Vitis.
- Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Plant, Genes, Plant, Monte Carlo Method, Real-Time Polymerase Chain Reaction, Spectrophotometry, Ultraviolet, Stress, Physiological, Ultraviolet Rays.
Abstract
Grapevine is one of the most cultivated fruit crop worldwide with Vitis vinifera being the species with the highest economical importance. Being highly susceptible to fungal pathogens and increasingly affected by environmental factors, it has become an important agricultural research area, where gene expression analysis plays a fundamental role. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is currently amongst the most powerful techniques to perform gene expression studies. Nevertheless, accurate gene expression quantification strongly relies on appropriate reference gene selection for sample normalization. Concerning V. vinifera, limited information still exists as for which genes are the most suitable to be used as reference under particular experimental conditions. In this work, seven candidate genes were investigated for their stability in grapevine samples referring to four distinct stresses (Erysiphe necator, wounding and UV-C irradiation in leaves and Phaeomoniella chlamydospora colonization in wood). The expression stability was evaluated using geNorm, NormFinder and BestKeeper. In all cases, full agreement was not observed for the three methods. To provide comprehensive rankings integrating the three different programs, for each treatment, a consensus ranking was created using a non-weighted unsupervised rank aggregation method. According to the last, the three most suitable reference genes to be used in grapevine leaves, regardless of the stress, are UBC, VAG and PEP. For the P. chlamydospora treatment, EF1, CYP and UBC were the best scoring genes. Acquaintance of the most suitable reference genes to be used in grapevine samples can contribute for accurate gene expression quantification in forthcoming studies.
DOI: 10.1371/journal.pone.0111399
PubMed: 25340748
PubMed Central: PMC4207820
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Being highly susceptible to fungal pathogens and increasingly affected by environmental factors, it has become an important agricultural research area, where gene expression analysis plays a fundamental role. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is currently amongst the most powerful techniques to perform gene expression studies. Nevertheless, accurate gene expression quantification strongly relies on appropriate reference gene selection for sample normalization. Concerning V. vinifera, limited information still exists as for which genes are the most suitable to be used as reference under particular experimental conditions. In this work, seven candidate genes were investigated for their stability in grapevine samples referring to four distinct stresses (Erysiphe necator, wounding and UV-C irradiation in leaves and Phaeomoniella chlamydospora colonization in wood). The expression stability was evaluated using geNorm, NormFinder and BestKeeper. In all cases, full agreement was not observed for the three methods. To provide comprehensive rankings integrating the three different programs, for each treatment, a consensus ranking was created using a non-weighted unsupervised rank aggregation method. According to the last, the three most suitable reference genes to be used in grapevine leaves, regardless of the stress, are UBC, VAG and PEP. For the P. chlamydospora treatment, EF1, CYP and UBC were the best scoring genes. Acquaintance of the most suitable reference genes to be used in grapevine samples can contribute for accurate gene expression quantification in forthcoming studies. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25340748</PMID><DateCompleted><Year>2016</Year><Month>01</Month><Day>13</Day></DateCompleted><DateRevised><Year>2020</Year><Month>03</Month><Day>06</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>9</Volume><Issue>10</Issue><PubDate><Year>2014</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS One</ISOAbbreviation></Journal><ArticleTitle>Reference gene validation for quantitative RT-PCR during biotic and abiotic stresses in Vitis vinifera.</ArticleTitle><Pagination><MedlinePgn>e111399</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0111399</ELocationID><Abstract><AbstractText>Grapevine is one of the most cultivated fruit crop worldwide with Vitis vinifera being the species with the highest economical importance. Being highly susceptible to fungal pathogens and increasingly affected by environmental factors, it has become an important agricultural research area, where gene expression analysis plays a fundamental role. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is currently amongst the most powerful techniques to perform gene expression studies. Nevertheless, accurate gene expression quantification strongly relies on appropriate reference gene selection for sample normalization. Concerning V. vinifera, limited information still exists as for which genes are the most suitable to be used as reference under particular experimental conditions. In this work, seven candidate genes were investigated for their stability in grapevine samples referring to four distinct stresses (Erysiphe necator, wounding and UV-C irradiation in leaves and Phaeomoniella chlamydospora colonization in wood). The expression stability was evaluated using geNorm, NormFinder and BestKeeper. In all cases, full agreement was not observed for the three methods. To provide comprehensive rankings integrating the three different programs, for each treatment, a consensus ranking was created using a non-weighted unsupervised rank aggregation method. According to the last, the three most suitable reference genes to be used in grapevine leaves, regardless of the stress, are UBC, VAG and PEP. For the P. chlamydospora treatment, EF1, CYP and UBC were the best scoring genes. Acquaintance of the most suitable reference genes to be used in grapevine samples can contribute for accurate gene expression quantification in forthcoming studies. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Borges</LastName><ForeName>Alexandre Filipe</ForeName><Initials>AF</Initials><AffiliationInfo><Affiliation>Disease & Stress Biology Laboratory, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal; Disease & Stress Biology Laboratory, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fonseca</LastName><ForeName>Catarina</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Disease & Stress Biology Laboratory, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ferreira</LastName><ForeName>Ricardo Boavida</ForeName><Initials>RB</Initials><AffiliationInfo><Affiliation>Disease & Stress Biology Laboratory, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal; Disease & Stress Biology Laboratory, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lourenço</LastName><ForeName>Ana Maria</ForeName><Initials>AM</Initials><AffiliationInfo><Affiliation>REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Monteiro</LastName><ForeName>Sara</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Disease & Stress Biology Laboratory, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.</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>2014</Year><Month>10</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D019295" MajorTopicYN="N">Computational Biology</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D020869" MajorTopicYN="N">Gene Expression Profiling</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018506" MajorTopicYN="N">Gene Expression Regulation, Plant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017343" MajorTopicYN="Y">Genes, Plant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009010" MajorTopicYN="N">Monte Carlo Method</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName><QualifierName UI="Q000528" MajorTopicYN="N">radiation effects</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D060888" MajorTopicYN="N">Real-Time Polymerase Chain Reaction</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013056" MajorTopicYN="N">Spectrophotometry, Ultraviolet</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013312" MajorTopicYN="N">Stress, Physiological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014466" MajorTopicYN="N">Ultraviolet Rays</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D027843" MajorTopicYN="N">Vitis</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName><QualifierName UI="Q000382" MajorTopicYN="Y">microbiology</QualifierName><QualifierName UI="Q000528" MajorTopicYN="N">radiation effects</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>04</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>09</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>10</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>10</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>1</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25340748</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0111399</ArticleId><ArticleId 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