Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower

Autores
Ochogavía, Ana Claudia; Novello, Maria Angelina; Picardi, Liliana Amelia; Nestares, Graciela María
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Quantitative real-time PCR (qPCR) is currently the most accurate method for detecting differential gene expression, but depends greatly on normalization to stably expressed housekeeping genes. Transcriptomics analyses and experimental validation in different plant species have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. Thus, reliable validation of reference genes is required to ensure proper normalization. This paper presents a systematic comparison of ten potential reference genes in sunflower: five commonly used genes (Actin, Elongation Factor1, Plastid-encode RNA polymerase, Tubulin, and Ubiquitin, as ACT, EF1, PEP, TUB, and UBQ respectively), as well as five new candidates (Translation initiation factor, MicroRNA precursors 171 and 156, Ask-interacting protein, and Protein of unknown function, as ETIF5, MIR171, MIR156, SKIP, and UNK2 respectively). Reference gene expression stability was examined by qPCR across 20 biological samples, representing different tissues at various developmental stages. Expression of all 10 genes was variable to some extent, but that of ACT, UNK2, and EF1 was overall the most stable. A combination of ETIF5/UNK2/EF1 would be appropriate to use as a reference panel for normalizing gene expression data among vegetative tissues, whereas the combination of ACT/MIR156/UNK2 is most suitable for reproductive tissues. Reference genes selected in this study were further validated by examining relative expression of ahas1, one of three acetohydroxyacid synthase genes of sunflower. Our identification and validation of suitable normalizer genes will be of use to ensure accurate results in future transcriptomics studies in this crop.
Fil: Ochogavía, Ana Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Novello, Maria Angelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Picardi, Liliana Amelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo de Investigaciones de la Universidad Nacional de Rosario; Argentina
Fil: Nestares, Graciela María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Materia
HELIANTHUS ANNUUS L.
QPCR
REFERENCE GENES PANEL
STABLY EXPRESSED GENES
UNK2
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/53300
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/53300
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflowerOchogavía, Ana ClaudiaNovello, Maria AngelinaPicardi, Liliana AmeliaNestares, Graciela MaríaHELIANTHUS ANNUUS L.QPCRREFERENCE GENES PANELSTABLY EXPRESSED GENESUNK2https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Quantitative real-time PCR (qPCR) is currently the most accurate method for detecting differential gene expression, but depends greatly on normalization to stably expressed housekeeping genes. Transcriptomics analyses and experimental validation in different plant species have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. Thus, reliable validation of reference genes is required to ensure proper normalization. This paper presents a systematic comparison of ten potential reference genes in sunflower: five commonly used genes (Actin, Elongation Factor1, Plastid-encode RNA polymerase, Tubulin, and Ubiquitin, as ACT, EF1, PEP, TUB, and UBQ respectively), as well as five new candidates (Translation initiation factor, MicroRNA precursors 171 and 156, Ask-interacting protein, and Protein of unknown function, as ETIF5, MIR171, MIR156, SKIP, and UNK2 respectively). Reference gene expression stability was examined by qPCR across 20 biological samples, representing different tissues at various developmental stages. Expression of all 10 genes was variable to some extent, but that of ACT, UNK2, and EF1 was overall the most stable. A combination of ETIF5/UNK2/EF1 would be appropriate to use as a reference panel for normalizing gene expression data among vegetative tissues, whereas the combination of ACT/MIR156/UNK2 is most suitable for reproductive tissues. Reference genes selected in this study were further validated by examining relative expression of ahas1, one of three acetohydroxyacid synthase genes of sunflower. Our identification and validation of suitable normalizer genes will be of use to ensure accurate results in future transcriptomics studies in this crop.Fil: Ochogavía, Ana Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaFil: Novello, Maria Angelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaFil: Picardi, Liliana Amelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo de Investigaciones de la Universidad Nacional de Rosario; ArgentinaFil: Nestares, Graciela María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaSouthern Cross Publishing2017-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/53300Ochogavía, Ana Claudia; Novello, Maria Angelina; Picardi, Liliana Amelia; Nestares, Graciela María; Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower; Southern Cross Publishing; Plant Omics; 10; 4; 7-2017; 210-2181836-3644CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.21475/poj.10.04.17.pne831info:eu-repo/semantics/altIdentifier/url/http://www.pomics.com/ochogavia_10_4_2017_210_218.pdfinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:41:27Zoai:ri.conicet.gov.ar:11336/53300instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:41:27.662CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
title Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
spellingShingle Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
Ochogavía, Ana Claudia
HELIANTHUS ANNUUS L.
QPCR
REFERENCE GENES PANEL
STABLY EXPRESSED GENES
UNK2
title_short Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
title_full Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
title_fullStr Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
title_full_unstemmed Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
title_sort Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower
dc.creator.none.fl_str_mv Ochogavía, Ana Claudia
Novello, Maria Angelina
Picardi, Liliana Amelia
Nestares, Graciela María
author Ochogavía, Ana Claudia
author_facet Ochogavía, Ana Claudia
Novello, Maria Angelina
Picardi, Liliana Amelia
Nestares, Graciela María
author_role author
author2 Novello, Maria Angelina
Picardi, Liliana Amelia
Nestares, Graciela María
author2_role author
author
author
dc.subject.none.fl_str_mv HELIANTHUS ANNUUS L.
QPCR
REFERENCE GENES PANEL
STABLY EXPRESSED GENES
UNK2
topic HELIANTHUS ANNUUS L.
QPCR
REFERENCE GENES PANEL
STABLY EXPRESSED GENES
UNK2
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Quantitative real-time PCR (qPCR) is currently the most accurate method for detecting differential gene expression, but depends greatly on normalization to stably expressed housekeeping genes. Transcriptomics analyses and experimental validation in different plant species have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. Thus, reliable validation of reference genes is required to ensure proper normalization. This paper presents a systematic comparison of ten potential reference genes in sunflower: five commonly used genes (Actin, Elongation Factor1, Plastid-encode RNA polymerase, Tubulin, and Ubiquitin, as ACT, EF1, PEP, TUB, and UBQ respectively), as well as five new candidates (Translation initiation factor, MicroRNA precursors 171 and 156, Ask-interacting protein, and Protein of unknown function, as ETIF5, MIR171, MIR156, SKIP, and UNK2 respectively). Reference gene expression stability was examined by qPCR across 20 biological samples, representing different tissues at various developmental stages. Expression of all 10 genes was variable to some extent, but that of ACT, UNK2, and EF1 was overall the most stable. A combination of ETIF5/UNK2/EF1 would be appropriate to use as a reference panel for normalizing gene expression data among vegetative tissues, whereas the combination of ACT/MIR156/UNK2 is most suitable for reproductive tissues. Reference genes selected in this study were further validated by examining relative expression of ahas1, one of three acetohydroxyacid synthase genes of sunflower. Our identification and validation of suitable normalizer genes will be of use to ensure accurate results in future transcriptomics studies in this crop.
Fil: Ochogavía, Ana Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Novello, Maria Angelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Picardi, Liliana Amelia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo de Investigaciones de la Universidad Nacional de Rosario; Argentina
Fil: Nestares, Graciela María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
description Quantitative real-time PCR (qPCR) is currently the most accurate method for detecting differential gene expression, but depends greatly on normalization to stably expressed housekeeping genes. Transcriptomics analyses and experimental validation in different plant species have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. Thus, reliable validation of reference genes is required to ensure proper normalization. This paper presents a systematic comparison of ten potential reference genes in sunflower: five commonly used genes (Actin, Elongation Factor1, Plastid-encode RNA polymerase, Tubulin, and Ubiquitin, as ACT, EF1, PEP, TUB, and UBQ respectively), as well as five new candidates (Translation initiation factor, MicroRNA precursors 171 and 156, Ask-interacting protein, and Protein of unknown function, as ETIF5, MIR171, MIR156, SKIP, and UNK2 respectively). Reference gene expression stability was examined by qPCR across 20 biological samples, representing different tissues at various developmental stages. Expression of all 10 genes was variable to some extent, but that of ACT, UNK2, and EF1 was overall the most stable. A combination of ETIF5/UNK2/EF1 would be appropriate to use as a reference panel for normalizing gene expression data among vegetative tissues, whereas the combination of ACT/MIR156/UNK2 is most suitable for reproductive tissues. Reference genes selected in this study were further validated by examining relative expression of ahas1, one of three acetohydroxyacid synthase genes of sunflower. Our identification and validation of suitable normalizer genes will be of use to ensure accurate results in future transcriptomics studies in this crop.
publishDate 2017
dc.date.none.fl_str_mv 2017-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/53300
Ochogavía, Ana Claudia; Novello, Maria Angelina; Picardi, Liliana Amelia; Nestares, Graciela María; Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower; Southern Cross Publishing; Plant Omics; 10; 4; 7-2017; 210-218
1836-3644
CONICET Digital
CONICET
url http://hdl.handle.net/11336/53300
identifier_str_mv Ochogavía, Ana Claudia; Novello, Maria Angelina; Picardi, Liliana Amelia; Nestares, Graciela María; Identification of suitable reference genes by quantitative real-time PCR for gene expression normalization in sunflower; Southern Cross Publishing; Plant Omics; 10; 4; 7-2017; 210-218
1836-3644
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.21475/poj.10.04.17.pne831
info:eu-repo/semantics/altIdentifier/url/http://www.pomics.com/ochogavia_10_4_2017_210_218.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Southern Cross Publishing
publisher.none.fl_str_mv Southern Cross Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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