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February 15, 2011 (Vol. 31, No. 4)

Reshaping Whole Transcriptome Profiling

RNA-Seq Sample-Prep Reagents Aim to Help Analyze Previously Inaccessible Samples

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    Figure 1. For the sequencing data, the expression of each gene was quantified in reads/million (RPM) based on the alignment of both ends of the paired-end sequencing experiment. For the microarray data, probes were summarized into gene-expression values using RMA and the Ensembl Gene CDF file. The Y-axis is log2 fold change by microarray and X-axis log2 RPM fold change by sequencing. Differential gene expression is defined as greater than a twofold difference between samples. The results indicate that 857 genes were differentially expressed in smokers versus never smokers (S/N) as detected by RNA-Seq, with 289 genes detected by microarray analysis.

    The arrival of next-generation sequencing (NGS) technology has revolutionized the field of genomics and expanded the scope of scientific inquiry to sequence datasets from multiple genomes and transcriptomes. RNA-Seq is a specific technique enabled by next-generation sequencing and refers to direct sequencing of cDNAs to permit quantification of transcript levels from particular tissue or cell types.

    Unlike hybridization-based methods such as microarrays, RNA-Seq also provides direct sequence information that can be used to compare single nucleotide variants, map transcription start sites, and detect novel transcript splicing. The digital precision and sensitivity of RNA-Seq is well suited to the analysis of low input samples, such as small populations of circulating tumor cells, cancer cells, and stem cells where a more detailed transcriptome map may reveal the true biology of such systems.

    However, current technology for transcriptome sequencing requires a few hundred nanograms of total RNA (tens of thousands of cell equivalents). Moreover, many RNA-Seq protocols require additional enrichment steps to select for poly(A)+ RNA and/or to reduce the content of ribosomal RNA (rRNA) prior to NGS library construction. Procedures of this type require a higher amount of starting total RNA and also limit biological information derived from sequence analysis since often the whole tissue with a mixture of various cell types is used instead of pure cell populations.

    The Ovation® RNA-Seq System from NuGEN provides a complete solution for the preparation of double-stranded cDNA for NGS library construction from inputs as low as 500 picograms of total RNA (~50−100 cell equivalents) allowing analysis of isolated cells of a particular cell type. The protocol does not require rRNA reduction or poly(A)+ selection, which may bias or provide an incomplete representation of the transcriptome.

    The Ovation RNA-Seq FFPE System offers these same benefits and enables RNA-Seq analysis from formalin-fixed paraffin-embedded (FFPE) tissue, the most common source of archived clinical samples, especially in cancer studies. These RNA-Seq solutions have facilitated scientific discovery in diverse areas of research including gene-expression differences in bronchial airway epithelium associated with smoking and lung cancer, the characterization of the HIV genomes from clinical samples, and transcript profiling with RNA derived from FFPE samples.

    Researchers at the Boston University School of Medicine lead by Avrum Spira are working toward the discovery and development of biomarkers for lung cancer and COPD that are detectable before the onset of clinical symptoms. These researchers are specifically interested in gene-expression changes that occur in the airway epithelial cells of tobacco smokers that may ultimately serve as biomarkers for disease risk in smokers.

    The collection of sufficient total RNA for transcriptome analysis in such studies is limiting, as only a small number of the cells can be collected from the airway epithelium by bronchoscopy or using airway swabs. The differential gene-expression results shown in Figure 1 were generated using total RNA obtained from individuals who had never smoked and have no clinical indications of lung disease versus current smokers.

    Total RNA was processed using the Ovation RNA-Seq System for analysis by NGS, or amplified and labeled for analysis on Affymetrix® Exon 1.0 ST microarrays. The results indicate that a greater number of differentially expressed genes are detected by NGS (region shown in green) owing to the greater sensitivity and dynamic range of this technique in comparison to microarray-based methods.

    The RNA-Seq results provide a comprehensive and high-resolution view of the airway epithelial cell transcriptome and will provide insights into the molecular field of damage induced by smoking and the progression of tobacco-related lung disease. Moreover, each of the differentially expressed genes detected in the tobacco smokers are candidates for further development as lung cancer biomarkers.

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