A comparison of RNA-seq and exon arrays for whole genome transcription profiling of the L5 spinal nerve transection model of neuropathic pain in the rat
- Equal contributors
1 Department of Structural and Molecular Biology, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK
2 Laboratorio de Investigacion, Fundacion IMABIS, Avda. Jorge Luis Borges nº15 Bl.3 Pl.3, 29010, Malaga, Spain
3 The Wolfson Centre for Age-Related Diseases, Wolfson Wing, Hodgkin Building, King’s College London, Guy's Campus, London Bridge, London SE1 1UL, UK
4 Boehringer Ingelheim Pharma GmbH & Co. KG, Target Discovery Research Germany, Birkendorferstraße 67, 88397, Biberach an der Riß, Germany
5 Department of Medical and Life Sciences, Furtwangen University, Jakob-Kienzle-Str. 17, D-78054 VS-Schwenningen, Germany
6 Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, England
Molecular Pain 2014, 10:7 doi:10.1186/1744-8069-10-7Published: 28 January 2014
The past decade has seen an abundance of transcriptional profiling studies of preclinical models of persistent pain, predominantly employing microarray technology. In this study we directly compare exon microarrays to RNA-seq and investigate the ability of both platforms to detect differentially expressed genes following nerve injury using the L5 spinal nerve transection model of neuropathic pain. We also investigate the effects of increasing RNA-seq sequencing depth. Finally we take advantage of the “agnostic” approach of RNA-seq to discover areas of expression outside of annotated exons that show marked changes in expression following nerve injury.
RNA-seq and microarrays largely agree in terms of the genes called as differentially expressed. However, RNA-seq is able to interrogate a much larger proportion of the genome. It can also detect a greater number of differentially expressed genes than microarrays, across a wider range of fold changes and is able to assign a larger range of expression values to the genes it measures. The number of differentially expressed genes detected increases with sequencing depth. RNA-seq also allows the discovery of a number of genes displaying unusual and interesting patterns of non-exonic expression following nerve injury, an effect that cannot be detected using microarrays.
We recommend the use of RNA-seq for future high-throughput transcriptomic experiments in pain studies. RNA-seq allowed the identification of a larger number of putative candidate pain genes than microarrays and can also detect a wider range of expression values in a neuropathic pain model. In addition, RNA-seq can interrogate the whole genome regardless of prior annotations, being able to detect transcription from areas of the genome not currently annotated as exons. Some of these areas are differentially expressed following nerve injury, and may represent novel genes or isoforms. We also recommend the use of a high sequencing depth in order to detect differential expression for genes with low levels of expression.