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Selection and validation of endogenous reference genes using a high throughput approach
BACKGROUND: Endogenous reference genes are commonly used to normalize expression levels of other genes with the assumption that the expression of the former is constant in different tissues and in different physiopathological conditions. Whether this assumption is correct it is, however, still matte...
Autores principales: | , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC516027/ https://www.ncbi.nlm.nih.gov/pubmed/15310404 http://dx.doi.org/10.1186/1471-2164-5-55 |
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author | Jin, Ping Zhao, Yingdong Ngalame, Yvonne Panelli, Monica C Nagorsen, Dirk Monsurró, Vladia Smith, Kina Hu, Nan Su, Hua Taylor, Phil R Marincola, Francesco M Wang, Ena |
author_facet | Jin, Ping Zhao, Yingdong Ngalame, Yvonne Panelli, Monica C Nagorsen, Dirk Monsurró, Vladia Smith, Kina Hu, Nan Su, Hua Taylor, Phil R Marincola, Francesco M Wang, Ena |
author_sort | Jin, Ping |
collection | PubMed |
description | BACKGROUND: Endogenous reference genes are commonly used to normalize expression levels of other genes with the assumption that the expression of the former is constant in different tissues and in different physiopathological conditions. Whether this assumption is correct it is, however, still matter of debate. In this study, we searched for stably expressed genes in 384 cDNA array hybridization experiments encompassing different tissues and cell lines. RESULTS: Several genes were identified whose expression was highly stable across all samples studied. The usefulness of 8 genes among them was tested by normalizing the relative gene expression against test genes whose expression pattern was known. The range of accuracy of individual endogenous reference genes was wide whereas consistent information could be obtained when information pooled from different endogenous reference genes was used. CONCLUSIONS: This study suggests that even when the most stably expressed genes in array experiments are used as endogenous reference, significant variation in test gene expression estimates may occur and the best normalization is achieved when data from several endogenous reference genes are pooled together to minimize minimal but significant variation among samples. We are presently optimizing strategies for the preparation of endogenous reference gene mixtures that could yield information comparable to that of data pooled from individual endogenous reference gene normalizations. |
format | Text |
id | pubmed-516027 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-5160272004-09-05 Selection and validation of endogenous reference genes using a high throughput approach Jin, Ping Zhao, Yingdong Ngalame, Yvonne Panelli, Monica C Nagorsen, Dirk Monsurró, Vladia Smith, Kina Hu, Nan Su, Hua Taylor, Phil R Marincola, Francesco M Wang, Ena BMC Genomics Research Article BACKGROUND: Endogenous reference genes are commonly used to normalize expression levels of other genes with the assumption that the expression of the former is constant in different tissues and in different physiopathological conditions. Whether this assumption is correct it is, however, still matter of debate. In this study, we searched for stably expressed genes in 384 cDNA array hybridization experiments encompassing different tissues and cell lines. RESULTS: Several genes were identified whose expression was highly stable across all samples studied. The usefulness of 8 genes among them was tested by normalizing the relative gene expression against test genes whose expression pattern was known. The range of accuracy of individual endogenous reference genes was wide whereas consistent information could be obtained when information pooled from different endogenous reference genes was used. CONCLUSIONS: This study suggests that even when the most stably expressed genes in array experiments are used as endogenous reference, significant variation in test gene expression estimates may occur and the best normalization is achieved when data from several endogenous reference genes are pooled together to minimize minimal but significant variation among samples. We are presently optimizing strategies for the preparation of endogenous reference gene mixtures that could yield information comparable to that of data pooled from individual endogenous reference gene normalizations. BioMed Central 2004-08-13 /pmc/articles/PMC516027/ /pubmed/15310404 http://dx.doi.org/10.1186/1471-2164-5-55 Text en Copyright © 2004 Jin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jin, Ping Zhao, Yingdong Ngalame, Yvonne Panelli, Monica C Nagorsen, Dirk Monsurró, Vladia Smith, Kina Hu, Nan Su, Hua Taylor, Phil R Marincola, Francesco M Wang, Ena Selection and validation of endogenous reference genes using a high throughput approach |
title | Selection and validation of endogenous reference genes using a high throughput approach |
title_full | Selection and validation of endogenous reference genes using a high throughput approach |
title_fullStr | Selection and validation of endogenous reference genes using a high throughput approach |
title_full_unstemmed | Selection and validation of endogenous reference genes using a high throughput approach |
title_short | Selection and validation of endogenous reference genes using a high throughput approach |
title_sort | selection and validation of endogenous reference genes using a high throughput approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC516027/ https://www.ncbi.nlm.nih.gov/pubmed/15310404 http://dx.doi.org/10.1186/1471-2164-5-55 |
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