EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics

Rallapalli, Ghanasyam, Kemen, Eric M, Robert-Seilaniantz, Alexandre, Segonzac, Cécile, Etherington, Graham J, Sohn, Kee Hoon, MacLean, Daniel and Jones, Jonathan D G (2014) EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics. BMC Genomics, 15. ISSN 1471-2164

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Abstract

Background: Next Generation Sequencing technologies have facilitated differential gene expression analysis through RNA-seq and Tag-seq methods. RNA-seq has biases associated with transcript lengths, lacks uniform coverage of regions in mRNA and requires 10–20 times more reads than a typical Tag-seq. Most existing Tag-seq methods either have biases or not high throughput due to use of restriction enzymes or enzymatic manipulation of 5’ ends of mRNA or use of RNA ligations.  Results: We have developed EXpression Profiling through Randomly Sheared cDNA tag Sequencing (EXPRSS) that employs acoustic waves to randomly shear cDNA and generate sequence tags at a relatively defined position (~150-200 bp) from the 3′ end of each mRNA. Implementation of the method was verified through comparative analysis of expression data generated from EXPRSS, NlaIII-DGE and Affymetrix microarray and through qPCR quantification of selected genes. EXPRSS is a strand specific and restriction enzyme independent tag sequencing method that does not require cDNA length-based data transformations. EXPRSS is highly reproducible, is high-throughput and it also reveals alternative polyadenylation and polyadenylated antisense transcripts. It is cost-effective using barcoded multiplexing, avoids the biases of existing SAGE and derivative methods and can reveal polyadenylation position from paired-end sequencing.  Conclusions: EXPRSS Tag-seq provides sensitive and reliable gene expression data and enables high-throughput expression profiling with relatively simple downstream analysis.

Item Type: Article
Additional Information: © Rallapalli et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Uncontrolled Keywords: next generation sequencing,tag-seq,high throughput expression profiling,rna-seq,exprss
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School

Faculty of Science > School of Computing Sciences
Faculty of Science > School of Biological Sciences
Depositing User: Pure Connector
Date Deposited: 09 Nov 2016 14:00
Last Modified: 22 Apr 2020 01:55
URI: https://ueaeprints.uea.ac.uk/id/eprint/61290
DOI: 10.1186/1471-2164-15-341

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