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精确表达非常小的细胞群体。

Accurate expression profiling of very small cell populations.

机构信息

Institute for Research in Biomedicine, Barcelona, Spain.

出版信息

PLoS One. 2010 Dec 28;5(12):e14418. doi: 10.1371/journal.pone.0014418.

Abstract

BACKGROUND

Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because available cell numbers are limited. Currently available alternative methods for expression profiling from nanograms of RNA or from very small cell populations lack a broad validation of results to provide accurate information about the measured transcripts.

METHODS AND FINDINGS

We provide evidence that currently available methods for expression profiling of very small cell populations are prone to technical noise and therefore cannot be used efficiently as discovery tools. Furthermore, we present Pico Profiling, a new expression profiling method from as few as ten cells, and we show that this approach is as informative as standard techniques from thousands to millions of cells. The central component of Pico Profiling is Whole Transcriptome Amplification (WTA), which generates expression profiles that are highly comparable to those produced by others, at different times, by standard protocols or by Real-time PCR. We provide a complete workflow from RNA isolation to analysis of expression profiles.

CONCLUSIONS

Pico Profiling, as presented here, allows generating an accurate expression profile from cell populations as small as ten cells.

摘要

背景

表达谱分析,即测量细胞或组织类型的所有转录本,是目前描述其生理状态的最全面方法。鉴于目前可用的精确分析方法需要数千到数百万个细胞中发现的 RNA 量,许多从事专门细胞类型研究的生物学领域无法使用这些技术,因为可用的细胞数量有限。目前,从纳克 RNA 或非常小的细胞群体中进行表达谱分析的替代方法缺乏对结果的广泛验证,无法提供有关所测量转录本的准确信息。

方法和发现

我们提供的证据表明,目前用于非常小的细胞群体表达谱分析的方法容易受到技术噪声的影响,因此不能有效地用作发现工具。此外,我们提出了 Pico Profiling,这是一种从仅十个细胞中进行表达谱分析的新方法,我们表明这种方法与从数千到数百万个细胞中使用标准技术一样具有信息量。Pico Profiling 的核心组件是全转录本扩增(WTA),它生成的表达谱与其他人在不同时间使用标准方案或实时 PCR 生成的表达谱高度可比。我们提供了从 RNA 分离到表达谱分析的完整工作流程。

结论

如本文所述,Pico Profiling 允许从小至十个细胞的细胞群体中生成准确的表达谱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0141/3010985/d260814e0c23/pone.0014418.g001.jpg

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