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从飞摩尔级 RNA 样本进行数字转录组谱分析。

Digital transcriptome profiling from attomole-level RNA samples.

机构信息

Helicos BioSciences Corporation, Cambridge, MA 02139, USA.

出版信息

Genome Res. 2010 Apr;20(4):519-25. doi: 10.1101/gr.102129.109. Epub 2010 Feb 4.

Abstract

Accurate profiling of minute quantities of RNA in a global manner can enable key advances in many scientific and clinical disciplines. Here, we present low-quantity RNA sequencing (LQ-RNAseq), a high-throughput sequencing-based technique allowing whole transcriptome surveys from subnanogram RNA quantities in an amplification/ligation-free manner. LQ-RNAseq involves first-strand cDNA synthesis from RNA templates, followed by 3' polyA tailing of the single-stranded cDNA products and direct single molecule sequencing. We applied LQ-RNAseq to profile S. cerevisiae polyA+ transcripts, demonstrate the reproducibility of the approach across different sample preparations and independent instrument runs, and establish the absolute quantitative power of this method through comparisons with other reported transcript profiling techniques and through utilization of RNA spike-in experiments. We demonstrate the practical application of this approach to define the transcriptional landscape of mouse embryonic and induced pluripotent stem cells, observing transcriptional differences, including over 100 genes exhibiting differential expression between these otherwise very similar stem cell populations. This amplification-independent technology, which utilizes small quantities of nucleic acid and provides quantitative measurements of cellular transcripts, enables global gene expression measurements from minute amounts of materials and offers broad utility in both basic research and translational biology for characterization of rare cells.

摘要

以全局方式准确分析微量 RNA 可以推动许多科学和临床学科的关键进展。在这里,我们介绍了低量 RNA 测序 (LQ-RNAseq),这是一种基于高通量测序的技术,可在无需扩增/连接的情况下,从亚纳克 RNA 量中进行全转录组调查。LQ-RNAseq 首先从 RNA 模板合成第一链 cDNA,然后对单链 cDNA 产物进行 3' polyA 加尾,然后直接进行单分子测序。我们将 LQ-RNAseq 应用于 S. cerevisiae polyA+转录本的分析,证明了该方法在不同样本制备和独立仪器运行之间的可重复性,并通过与其他报道的转录谱分析技术的比较以及通过 RNA 掺入实验的利用,证明了该方法的绝对定量能力。我们证明了这种方法在定义小鼠胚胎和诱导多能干细胞转录图谱中的实际应用,观察到转录差异,包括这两个非常相似的干细胞群体之间差异表达的 100 多个基因。这种不依赖扩增的技术,利用少量核酸并提供细胞转录物的定量测量,能够从小量材料中进行全基因表达测量,并在基础研究和转化生物学中广泛用于稀有细胞的表征。

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