A novel method of differential gene expression analysis using multiple cDNA libraries applied to the identification of tumour endothelial genes

John Mj Herbert,Roy Bicknell,Sharon Sanderson,Dov Stekel,Victoria L Heath

doi:10.1186/1471-2164-9-153

John Mj Herbert, Roy Bicknell + Show 3 more

Open Access

https://doi.org/10.1186/1471-2164-9-153

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Abstract

BackgroundIn this study, differential gene expression analysis using complementary DNA (cDNA) libraries has been improved. Firstly by the introduction of an accurate method of assigning Expressed Sequence Tags (ESTs) to genes and secondly, by using a novel likelihood ratio statistical scoring of differential gene expression between two pools of cDNA libraries. These methods were applied to the latest available cell line and bulk tissue cDNA libraries in a two-step screen to predict novel tumour endothelial markers. Initially, endothelial cell lines were in silico subtracted from non-endothelial cell lines to identify endothelial genes. Subsequently, a second bulk tumour versus normal tissue subtraction was employed to predict tumour endothelial markers.ResultsFrom an endothelial cDNA library analysis, 431 genes were significantly up regulated in endothelial cells with a False Discovery Rate adjusted q-value of 0.01 or less and 104 of these were expressed only in endothelial cells. Combining the cDNA library data with the latest Serial Analysis of Gene Expression (SAGE) library data derived a complete list of 459 genes preferentially expressed in endothelium. 27 genes were predicted tumour endothelial markers in multiple tissues based on the second bulk tissue screen.ConclusionThis approach represents a significant advance on earlier work in its ability to accurately assign an EST to a gene, statistically measure differential expression between two pools of cDNA libraries and predict putative tumour endothelial markers before entering the laboratory. These methods are of value and available to researchers that are interested in the analysis of transcriptomic data.

Highlights

In this study, differential gene expression analysis using complementary DNA libraries has been improved
Two Expressed Sequence Tag (EST) pools and all Reference sequence project (Refseq) [21] mRNA sequences were aligned to the human genome using the Basic Local Alignment Search Tool (BLAST) like alignment tool (BLAT) [22]
The aligned sequences were collected into Perl data structures and a simple custom-clustering algorithm (Jake cluster) assigned each EST to a gene or gene prediction based on their overlapping genome position

Summary

Introduction

Differential gene expression analysis using complementary DNA (cDNA) libraries has been improved. By the introduction of an accurate method of assigning Expressed Sequence Tags (ESTs) to genes and secondly, by using a novel likelihood ratio statistical scoring of differential gene expression between two pools of cDNA libraries These methods were applied to the latest available cell line and bulk tissue cDNA libraries in a two-step screen to predict novel tumour endothelial markers. Our analysis [8] employed a cDNA subtractive Basic Local Alignment Search Tool (BLAST) [16], algorithm to predict endothelial specific genes This approach required cross referencing of the results to SAGE libraries to confidently predict endothelial expression due to a large number of false positives associated with the BLAST method of EST to gene assignment used. This 1000 sequence limit of DDD can remove small, but often potentially relevant, cDNA libraries from an analysis

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