3' tag digital gene expression profiling of human brain and universal reference RNA using Illumina Genome Analyzer

Yan W Asmann,Gregory A Poland,Edith A Perez,Terry M Therneau,Sumit Middha,David I Smith,Eric D Wieben,Jean-Pierre A Kocher,Eric W Klee,Ann L Oberg,E Aubrey Thompson

doi:10.1186/1471-2164-10-531

Abstract

BackgroundMassive parallel sequencing has the potential to replace microarrays as the method for transcriptome profiling. Currently there are two protocols: full-length RNA sequencing (RNA-SEQ) and 3'-tag digital gene expression (DGE). In this preliminary effort, we evaluated the 3' DGE approach using two reference RNA samples from the MicroArray Quality Control Consortium (MAQC).ResultsUsing Brain RNA sample from multiple runs, we demonstrated that the transcript profiles from 3' DGE were highly reproducible between technical and biological replicates from libraries constructed by the same lab and even by different labs, and between two generations of Illumina's Genome Analyzers. Approximately 65% of all sequence reads mapped to mitochondrial genes, ribosomal RNAs, and canonical transcripts. The expression profiles of brain RNA and universal human reference RNA were compared which demonstrated that DGE was also highly quantitative with excellent correlation of differential expression with quantitative real-time PCR. Furthermore, one lane of 3' DGE sequencing, using the current sequencing chemistry and image processing software, had wider dynamic range for transcriptome profiling and was able to detect lower expressed genes which are normally below the detection threshold of microarrays.Conclusion3' tag DGE profiling with massive parallel sequencing achieved high sensitivity and reproducibility for transcriptome profiling. Although it lacks the ability of detecting alternative splicing events compared to RNA-SEQ, it is much more affordable and clearly out-performed microarrays (Affymetrix) in detecting lower abundant transcripts.

Highlights

Massive parallel sequencing has the potential to replace microarrays as the method for transcriptome profiling
Our initial analyses focused on defining the reproducibility of 3' tag digital gene expression (DGE) and determining the depth of sequencing required to achieve a reasonable coverage of the transcriptome
Our analysis highlights the precise nature of DGE profiling, as demonstrated by the high reproducibility between technical replicates of the same library run in different lanes, and between biological replicates of different libraries on the same or different flow cells runs

Summary

Introduction

Massive parallel sequencing has the potential to replace microarrays as the method for transcriptome profiling. There are two protocols: full-length RNA sequencing (RNASEQ) and 3'-tag digital gene expression (DGE) In this preliminary effort, we evaluated the 3' DGE approach using two reference RNA samples from the MicroArray Quality Control Consortium (MAQC). The transcriptome can be profiled by high throughput techniques including SAGE [1], microarray [2,3], and sequencing of clones from cDNA libraries [4,5]. Until recently the application of sequencing technology in transcriptome profiling has been limited by high cost, by the need to amplify DNA through bacterial cloning, and by the traditional Sanger approach of sequencing by chain termination [7]

Methods

Results

Conclusion