rsos.royalsocietypublishing.org Research Cite this article: Trost B, Moir CA, Gillespie ZE, Kusalik A, Mitchell JA, Eskiw CH. 2015 Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fbroblasts. R. Soc. open sci. 2: 150402. http://dx.doi.org/10.1098/rsos.150402 Received: 12 August 2015 Accepted: 2 September 2015 Subject Category: Cellular and molecular biology Subject Areas: molecular biology Keywords: RNA-seq, microarrays, transcriptome analysis, fbroblasts, gene expression Author for correspondence: Christopher H. Eskiw e-mail: c.eskiw@usask.ca Electronic supplementary material is available at http://dx.doi.org/10.1098/rsos.150402 or via http://rsos.royalsocietypublishing.org. Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fbroblasts Brett Trost 1 , Catherine A. Moir 2,3 , Zoe E. Gillespie 4 , Anthony Kusalik 1 , Jennifer A. Mitchell 5,6 and Christopher H. Eskiw 2,4 1 Department of Computer Science, University of Saskatchewan, Saskatoon Canada S7N 5C9 2 Department of Life Sciences, Brunel University, Uxbridge UB8 3PH, UK 3 Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK 4 Department of Food and Bioproduct Sciences, University of Saskatchewan, Saskatoon Canada S7N 5A8 5 Department of Cell and Systems Biology, and 6 Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto Canada M5S 3G5 BT, 0000-0003-4863-7273 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, 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.