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使用定量实时PCR进行单细胞表达谱分析的工作流程。

The workflow of single-cell expression profiling using quantitative real-time PCR.

作者信息

Ståhlberg Anders, Kubista Mikael

机构信息

1Department of Pathology, Sahlgrenska Cancer Center, University of Gothenburg, Box 425, 40530 Gothenburg, Sweden.

出版信息

Expert Rev Mol Diagn. 2014 Apr;14(3):323-31. doi: 10.1586/14737159.2014.901154.

Abstract

Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are studied. New cell types and cell subtypes may be found and relevant pathways and expression networks can be identified. The most powerful technique for single-cell expression profiling is currently quantitative reverse transcription real-time PCR (RT-qPCR). A robust RT-qPCR workflow for highly sensitive and specific measurements in high-throughput and a reasonable degree of multiplexing has been developed for targeting mRNAs, but also microRNAs, non-coding RNAs and most recently also proteins. We review the current state of the art of single-cell expression profiling and present also the improvements and developments expected in the next 5 years.

摘要

生物材料是异质的,当暴露于刺激时,其中存在的各种细胞会有不同反应。通过分解样本并逐个研究细胞,可以消除许多复杂性。单细胞分析揭示了在研究经典样本时未被注意到的反应。可能会发现新的细胞类型和细胞亚型,并能识别相关途径和表达网络。目前,单细胞表达分析最强大的技术是定量逆转录实时PCR(RT-qPCR)。已经开发出一种强大的RT-qPCR工作流程,用于在高通量下进行高灵敏度和特异性测量,并实现合理程度的多重检测,该流程不仅可用于靶向mRNA,还可用于靶向微小RNA、非编码RNA,最近还可用于蛋白质。我们综述了单细胞表达分析的当前技术水平,并介绍了未来5年有望实现的改进和发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c342/4819576/6569129597d9/iero_a_901154_f0001_b.jpg

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