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.
Original language | English |
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Article number | 341 |
Journal | BMC Genomics |
Volume | 15 |
DOIs | |
Publication status | Published - 6 May 2014 |
Keywords
- Next generation sequencing
- Tag-seq
- High throughput expression profiling
- RNA-seq
- EXPRSS
Profiles
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Jonathan Jones
- School of Biological Sciences - Professor of Biology
- Plant Sciences - Member
Person: Research Group Member, Academic, Teaching & Research
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Daniel Maclean
- School of Computing Sciences - Honorary Professor
- The Sainsbury Laboratory - Head of Bioinformatics (TSL)
Person: Honorary, Academic, Teaching & Research