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Mol Biotechnol. 2010 Jun;45(2):101-10. doi: 10.1007/s12033-010-9249-6.

Power of deep sequencing and agilent microarray for gene expression profiling study.

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  • 1State Key Laboratory of Molecular Oncology, Cancer Institute Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100021, People's Republic of China. fenglin@cicams.ac.cn

Abstract

Next-generation sequencing-based Digital Gene Expression tag profiling (DGE) has been used to study the changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with these platforms. In this study, 17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were >0.99 and the detection variance was <9% for both platforms. The dynamic range of microarray was fixed with four orders of magnitude, whereas that of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical, and feasible, which may be useful for most biological researchers.

PMID:
20432071
[PubMed - indexed for MEDLINE]
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