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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Ghanasyam Rallapalli, Eric M Kemen, Alexandre Robert-Seilaniantz, Cécile Segonzac, Graham J Etherington, Kee Hoon Sohn, Daniel MacLean, Jonathan D G Jones

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. More... »

PAGES

341

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2164-15-341

DOI

http://dx.doi.org/10.1186/1471-2164-15-341

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038944519

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24884414


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