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Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts

DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibrobla...

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Autores principales: Trost, Brett, Moir, Catherine A., Gillespie, Zoe E., Kusalik, Anthony, Mitchell, Jennifer A., Eskiw, Christopher H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4593695/
https://www.ncbi.nlm.nih.gov/pubmed/26473061
http://dx.doi.org/10.1098/rsos.150402
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author Trost, Brett
Moir, Catherine A.
Gillespie, Zoe E.
Kusalik, Anthony
Mitchell, Jennifer A.
Eskiw, Christopher H.
author_facet Trost, Brett
Moir, Catherine A.
Gillespie, Zoe E.
Kusalik, Anthony
Mitchell, Jennifer A.
Eskiw, Christopher H.
author_sort Trost, Brett
collection PubMed
description DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data.
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spelling pubmed-45936952015-10-15 Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts Trost, Brett Moir, Catherine A. Gillespie, Zoe E. Kusalik, Anthony Mitchell, Jennifer A. Eskiw, Christopher H. R Soc Open Sci Cellular and Molecular Biology DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data. The Royal Society Publishing 2015-09-30 /pmc/articles/PMC4593695/ /pubmed/26473061 http://dx.doi.org/10.1098/rsos.150402 Text en http://creativecommons.org/licenses/by/4.0/ © 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Cellular and Molecular Biology
Trost, Brett
Moir, Catherine A.
Gillespie, Zoe E.
Kusalik, Anthony
Mitchell, Jennifer A.
Eskiw, Christopher H.
Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title_full Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title_fullStr Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title_full_unstemmed Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title_short Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
title_sort concordance between rna-sequencing data and dna microarray data in transcriptome analysis of proliferative and quiescent fibroblasts
topic Cellular and Molecular Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4593695/
https://www.ncbi.nlm.nih.gov/pubmed/26473061
http://dx.doi.org/10.1098/rsos.150402
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