新基因组测序方法能够在单细胞水平上分析基因表达谱

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生物学家和遗传学家长期以来想要在单个细胞水平上分析基因表达谱,但是技术限制一直使得它不能成为现实。

根据2012年7月22日在线发表在Nature Biotechnology期刊上的一项研究,研究人员第一次证实一种新的被称作Smart-Seq的基因组测序方法能够帮助科学家们对临床上重要性的单个细胞进行深入分析。Smart-Seq可能有着很多方面的应用,包括帮助科学家们更好地理解肿瘤产生的复杂性。这是非常重要的,因为很多临床上重要性的细胞只以较小的数量存在而且需要进行单个细胞分析。

以前的研究表明对于单个基因而言,它经常通过不同的配置而产生同种蛋白的几种不同形式。这种被称为剪接的现象意味着来自同一种组织的细胞并不像人们之前所想象中那么同质化。

如今,在这项新研究中,研究人员开发出一种方法而能够完整地绘制出单个细胞的基因表达谱。通过显示哪些基因是有活性的,科学家们就可能准确地描述和研究来自同一种组织的单个细胞之间的基因表达差异。

在这项研究中,研究人员研究了一名患有复发性恶性黑色素瘤的病人血液系统中的肿瘤细胞。一旦研究人员在常规性的血液测试中鉴定出肿瘤细胞,他们就利用Smart-Seq来分析它们的基因表达谱。通过利用这种方法,研究人员能够证实肿瘤细胞激活很多重要的膜蛋白,这些膜蛋白被认为负责躲避体内监控系统,并在血液或淋巴中进行扩散。

Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells

Daniel Ramsköld, Shujun Luo, Yu-Chieh Wang, Robin Li, Qiaolin Deng, Omid R Faridani, Gregory A Daniels, Irina Khrebtukova, Jeanne F Loring, Louise C Laurent, Gary P Schroth & Rickard Sandberg

Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type–specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which enhances detailed analyses of alternative transcript isoforms and identification of single-nucleotide polymorphisms. We determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. We found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including candidate biomarkers for melanoma circulating tumor cells. Our protocol will be useful for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

全文链接:http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.2282.html

来源:生物谷

 

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