RGeasy: a reference gene analysis tool for gene expression studies via RT-qPCR
Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are perfor...
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Published in: | BMC genomics Vol. 25; no. 1; pp. 907 - 12 |
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Main Authors: | , , , , , , |
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Language: | English |
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30-09-2024
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Abstract | Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. |
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AbstractList | Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes.Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. Keywords: Endogenous genes, Relative expression, Normalization Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora , and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. Abstract Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes. Therefore, it is essential to validate, experimentally, the candidate reference genes. Thus, although there are several studies that are performed to identify the most stable reference genes, most them validate genes for very specific conditions, not exploring the whole potential of the research since not all possible combinations of treatments and/or conditions of the study are explored. For this reason, new experiments must be conducted by researchers that have interest in analyzing gene expression of treatments and/or conditions present, but not explored, in these studies. Here, we present the RGeasy tool, which aims to facilitate the selection of reference genes, allowing the user to choose genes for a greater number of combinations of treatments/conditions, compared to the ones present in the original articles, through just a few clicks. RGeasy was validated with RT-qPCR data from gene expression studies performed in two coffee species, Coffea arabica and Coffea canephora, and it can be used for any animal, plant or microorganism species. In addition to displaying a rank of the most stable reference genes for each condition or treatment, the user also has access to the primer pairs for the selected reference genes. |
ArticleNumber | 907 |
Audience | Academic |
Author | de Souza, Micaele Rodrigues Ságio, Solange Aparecida Chalfun-Junior, Antonio Lima, André Almeida Barreto, Horllys Gomes Araújo, Ivo Pontes da Costa Arruda, Wosley |
Author_xml | – sequence: 1 givenname: Micaele Rodrigues surname: de Souza fullname: de Souza, Micaele Rodrigues organization: Laboratory of Molecular Analysis (LAM), Department of Life Sciences, Federal University of Tocantins, UFT, University Campus of Palmas, Palmas, TO, 402-970, Brazil – sequence: 2 givenname: Ivo Pontes surname: Araújo fullname: Araújo, Ivo Pontes organization: Computer Science Course, Federal University of Tocantins, University Campus of Palmas, Palmas, TO, Brazil – sequence: 3 givenname: Wosley surname: da Costa Arruda fullname: da Costa Arruda, Wosley organization: Computer Science Course, Federal University of Tocantins, University Campus of Palmas, Palmas, TO, Brazil – sequence: 4 givenname: André Almeida surname: Lima fullname: Lima, André Almeida organization: Laboratory of Plant Molecular Physiology, Department of Biology, Federal University of Lavras, Lavras, MG, Brazil – sequence: 5 givenname: Solange Aparecida surname: Ságio fullname: Ságio, Solange Aparecida organization: Laboratory of Molecular Analysis (LAM), Department of Life Sciences, Federal University of Tocantins, UFT, University Campus of Palmas, Palmas, TO, 402-970, Brazil – sequence: 6 givenname: Antonio surname: Chalfun-Junior fullname: Chalfun-Junior, Antonio organization: Laboratory of Plant Molecular Physiology, Department of Biology, Federal University of Lavras, Lavras, MG, Brazil – sequence: 7 givenname: Horllys Gomes surname: Barreto fullname: Barreto, Horllys Gomes email: horllys@uft.edu.br organization: Laboratory of Molecular Analysis (LAM), Department of Life Sciences, Federal University of Tocantins, UFT, University Campus of Palmas, Palmas, TO, 402-970, Brazil. horllys@uft.edu.br |
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References | MK Udvardi (10808_CR1) 2008; 20 10808_CR27 CL Andersen (10808_CR10) 2004; 64 10808_CR28 10808_CR25 CP Dos Santos (10808_CR7) 2020; 47 10808_CR26 J Vandesompele (10808_CR9) 2002; 3 A Figueiredo (10808_CR20) 2013; 6 V Arabkari (10808_CR3) 2020; 26 NC Freitas (10808_CR23) 2017; 128 LF Goulao (10808_CR19) 2012; 30 10808_CR24 MW Pfaffl (10808_CR11) 2004; 26 A Vieira (10808_CR18) 2011; 115 F Cruz (10808_CR17) 2009; 23 S Derveaux (10808_CR2) 2010; 50 10808_CR14 CF Barsalobres-Cavallari (10808_CR16) 2009; 10 F Xie (10808_CR13) 2012; 80 K de Carvalho (10808_CR21) 2013; 53 10808_CR5 N Silver (10808_CR12) 2006; 7 10808_CR6 MQ Martins (10808_CR22) 2017; 8 B Foquet (10808_CR8) 2020; 8 CN Fernandes-Brum (10808_CR15) 2017; 13 10808_CR4 |
References_xml | – volume: 20 start-page: 1736 year: 2008 ident: 10808_CR1 publication-title: Plant Cell doi: 10.1105/tpc.108.061143 contributor: fullname: MK Udvardi – ident: 10808_CR4 – volume: 23 start-page: 607 year: 2009 ident: 10808_CR17 publication-title: Mol Breeding doi: 10.1007/s11032-009-9259-x contributor: fullname: F Cruz – ident: 10808_CR26 – ident: 10808_CR6 – ident: 10808_CR28 – ident: 10808_CR24 doi: 10.1373/clinchem.2008.112797 – volume: 26 start-page: 833 year: 2020 ident: 10808_CR3 publication-title: Pathol Oncol Res doi: 10.1007/s12253-019-00627-y contributor: fullname: V Arabkari – volume: 8 start-page: e9618 year: 2020 ident: 10808_CR8 publication-title: PeerJ doi: 10.7717/peerj.9618 contributor: fullname: B Foquet – volume: 115 start-page: 891 year: 2011 ident: 10808_CR18 publication-title: Fungal Biol doi: 10.1016/j.funbio.2011.07.002 contributor: fullname: A Vieira – volume: 53 start-page: 315 year: 2013 ident: 10808_CR21 publication-title: Mol Biotechnol doi: 10.1007/s12033-012-9529-4 contributor: fullname: K de Carvalho – volume: 30 start-page: 741 year: 2012 ident: 10808_CR19 publication-title: Plant Mol Biol Rep doi: 10.1007/s11105-011-0382-6 contributor: fullname: LF Goulao – ident: 10808_CR14 doi: 10.1007/s10142-023-01055-7 – volume: 13 start-page: 1 year: 2017 ident: 10808_CR15 publication-title: Tree Genet Genomes doi: 10.1007/s11295-017-1213-1 contributor: fullname: CN Fernandes-Brum – volume: 6 start-page: 1 year: 2013 ident: 10808_CR20 publication-title: BMC Res Notes doi: 10.1186/1756-0500-6-388 contributor: fullname: A Figueiredo – volume: 3 start-page: research00341 year: 2002 ident: 10808_CR9 publication-title: Genome Biol doi: 10.1186/gb-2002-3-7-research0034 contributor: fullname: J Vandesompele – volume: 26 start-page: 509 year: 2004 ident: 10808_CR11 publication-title: Biotechnol Lett doi: 10.1023/B:BILE.0000019559.84305.47 contributor: fullname: MW Pfaffl – volume: 128 start-page: 663 year: 2017 ident: 10808_CR23 publication-title: Plant Cell Tissue Organ Cult (PCTOC) doi: 10.1007/s11240-016-1147-6 contributor: fullname: NC Freitas – volume: 64 start-page: 5245 year: 2004 ident: 10808_CR10 publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-04-0496 contributor: fullname: CL Andersen – ident: 10808_CR25 – ident: 10808_CR5 – ident: 10808_CR27 – volume: 10 start-page: 1 year: 2009 ident: 10808_CR16 publication-title: BMC Mol Biol doi: 10.1186/1471-2199-10-1 contributor: fullname: CF Barsalobres-Cavallari – volume: 7 start-page: 33 year: 2006 ident: 10808_CR12 publication-title: BMC Mol Biol doi: 10.1186/1471-2199-7-33 contributor: fullname: N Silver – volume: 80 start-page: 75 year: 2012 ident: 10808_CR13 publication-title: Plant Mol Biol doi: 10.1007/s11103-012-9885-2 contributor: fullname: F Xie – volume: 8 start-page: 307 year: 2017 ident: 10808_CR22 publication-title: Front Plant Sci doi: 10.3389/fpls.2017.00307 contributor: fullname: MQ Martins – volume: 50 start-page: 227 year: 2010 ident: 10808_CR2 publication-title: Methods doi: 10.1016/j.ymeth.2009.11.001 contributor: fullname: S Derveaux – volume: 47 start-page: 953 year: 2020 ident: 10808_CR7 publication-title: Mol Biol Rep doi: 10.1007/s11033-019-05187-7 contributor: fullname: CP Dos Santos |
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Snippet | Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference genes.... Abstract Gene expression through RT-qPCR can be performed by the relative quantification method, which requires the expression normalization through reference... |
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SubjectTerms | Algorithms Analysis Anopheles Coffea - genetics Coffea arabica Coffea canephora Coffee Control Efficiency Endogenous genes Examinations Gene expression Gene Expression Profiling - methods Gene Expression Profiling - standards Gene Expression Regulation, Plant Genes Genes, Plant Identification and classification Microorganisms Normalization Polymerase chain reaction Real-Time Polymerase Chain Reaction - methods Real-Time Polymerase Chain Reaction - standards Reference Standards Relative expression Software Testing Validation studies Validity |
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Title | RGeasy: a reference gene analysis tool for gene expression studies via RT-qPCR |
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