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Validation of oligoarrays for quantitative exploration of the transcriptome

BACKGROUND: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and se...

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Autores principales: Nygaard, Vigdis, Liu, Fang, Holden, Marit, Kuo, Winston P, Trimarchi, Jeff, Ohno-Machado, Lucila, Cepko, Connie L, Frigessi, Arnoldo, Glad, Ingrid K, Wiel, Mark A van de, Hovig, Eivind, Lyng, Heidi
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2430212/
https://www.ncbi.nlm.nih.gov/pubmed/18513391
http://dx.doi.org/10.1186/1471-2164-9-258
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author Nygaard, Vigdis
Liu, Fang
Holden, Marit
Kuo, Winston P
Trimarchi, Jeff
Ohno-Machado, Lucila
Cepko, Connie L
Frigessi, Arnoldo
Glad, Ingrid K
Wiel, Mark A van de
Hovig, Eivind
Lyng, Heidi
author_facet Nygaard, Vigdis
Liu, Fang
Holden, Marit
Kuo, Winston P
Trimarchi, Jeff
Ohno-Machado, Lucila
Cepko, Connie L
Frigessi, Arnoldo
Glad, Ingrid K
Wiel, Mark A van de
Hovig, Eivind
Lyng, Heidi
author_sort Nygaard, Vigdis
collection PubMed
description BACKGROUND: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5·10(5). Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE. RESULTS: A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8·10(5 )(oligoarrays), 1.1·10(5 )(MPSS) and 7.6·10(4 )(SAGE), whereas the corresponding sum for all detected transcripts was 1.1·10(6 )(oligoarrays), 2.8·10(5 )(MPSS) and 3.8·10(5 )(SAGE). CONCLUSION: The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5·10(5 )suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands.
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spelling pubmed-24302122008-06-17 Validation of oligoarrays for quantitative exploration of the transcriptome Nygaard, Vigdis Liu, Fang Holden, Marit Kuo, Winston P Trimarchi, Jeff Ohno-Machado, Lucila Cepko, Connie L Frigessi, Arnoldo Glad, Ingrid K Wiel, Mark A van de Hovig, Eivind Lyng, Heidi BMC Genomics Research Article BACKGROUND: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5·10(5). Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE. RESULTS: A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8·10(5 )(oligoarrays), 1.1·10(5 )(MPSS) and 7.6·10(4 )(SAGE), whereas the corresponding sum for all detected transcripts was 1.1·10(6 )(oligoarrays), 2.8·10(5 )(MPSS) and 3.8·10(5 )(SAGE). CONCLUSION: The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5·10(5 )suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands. BioMed Central 2008-05-30 /pmc/articles/PMC2430212/ /pubmed/18513391 http://dx.doi.org/10.1186/1471-2164-9-258 Text en Copyright © 2008 Nygaard 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
Nygaard, Vigdis
Liu, Fang
Holden, Marit
Kuo, Winston P
Trimarchi, Jeff
Ohno-Machado, Lucila
Cepko, Connie L
Frigessi, Arnoldo
Glad, Ingrid K
Wiel, Mark A van de
Hovig, Eivind
Lyng, Heidi
Validation of oligoarrays for quantitative exploration of the transcriptome
title Validation of oligoarrays for quantitative exploration of the transcriptome
title_full Validation of oligoarrays for quantitative exploration of the transcriptome
title_fullStr Validation of oligoarrays for quantitative exploration of the transcriptome
title_full_unstemmed Validation of oligoarrays for quantitative exploration of the transcriptome
title_short Validation of oligoarrays for quantitative exploration of the transcriptome
title_sort validation of oligoarrays for quantitative exploration of the transcriptome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2430212/
https://www.ncbi.nlm.nih.gov/pubmed/18513391
http://dx.doi.org/10.1186/1471-2164-9-258
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