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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2015
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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. |
format | Online Article Text |
id | pubmed-4593695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
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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