单细胞测序
单细胞测序(英语:Single cell sequencing)采取优化的下一代DNA测序技术(NGS)检测单细胞的序列,可以获得特定微环境下的细胞序列差异以方便研究其功能差异等[1]。对个体细胞的DNA测序可以帮助我们了解例如在癌症中的小范围细胞的变异;对其进行RNA测序可以帮助我们了解和鉴别不同的细胞类型与其表现的基因,对研究发育生物学等有较大裨益。[2]
![](http://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/%D0%9E%D1%81%D0%BD%D0%BE%D0%B2%D0%BD%D1%8B%D0%B5_%D1%88%D0%B0%D0%B3%D0%B8_%D0%BF%D1%80%D0%B8_%D1%81%D0%B5%D0%BA%D0%B2%D0%B5%D0%BD%D0%B8%D1%80%D0%BE%D0%B2%D0%B0%D0%BD%D0%B8%D0%B8_%D0%94%D0%9D%D0%9A_%D0%BE%D0%B4%D0%B8%D0%BD%D0%BE%D1%87%D0%BD%D1%8B%D1%85_%D0%BA%D0%BB%D0%B5%D1%82%D0%BE%D0%BA.png/220px-%D0%9E%D1%81%D0%BD%D0%BE%D0%B2%D0%BD%D1%8B%D0%B5_%D1%88%D0%B0%D0%B3%D0%B8_%D0%BF%D1%80%D0%B8_%D1%81%D0%B5%D0%BA%D0%B2%D0%B5%D0%BD%D0%B8%D1%80%D0%BE%D0%B2%D0%B0%D0%BD%D0%B8%D0%B8_%D0%94%D0%9D%D0%9A_%D0%BE%D0%B4%D0%B8%D0%BD%D0%BE%D1%87%D0%BD%D1%8B%D1%85_%D0%BA%D0%BB%D0%B5%D1%82%D0%BE%D0%BA.png)
需要考虑的问题
编辑分离单细胞
编辑在全基因组扩增和测序前,有很多方法可以分离细胞个体,其中流式细胞术(FACS)较为常用。个体细胞可以用显微操作来收集,[3][4]这样较为快捷而且成本较低,但是比较有技术难度,而且显微镜下对细胞的错误分类容易影响实验结果。激光捕获显微切割技术(LCM)亦可以用来收集单细胞。但是尽管激光捕获显微切割可以保留样本细胞在组织中的空间位置,但是捕获单细胞的时候容易连带周围细胞的物质。[5][6][7] 高通量的细胞个体分离还可以使用微流控技术。微流控技术和流式细胞技术都能准确而自动地分离无偏样本。但是,两种方法都要求首先将细胞从其为环境中脱离,因此可能在RNA表达分析中造成对转录数据的干扰。[8][9]
细胞分析数量
编辑单细胞RNA测序
编辑单细胞RNA测序也称scRNA-Seq。通常而言,一般的组织细胞RNA-seq实验会产生1000万个读数,如果一个基因的频率超过50RPKM,即每百万读数中每千个碱基中超过50个,这一基因即被认为有表达。泊松分布下,1kb长的基因有超过500个读数和4%的最小变异系数,即CV值;哺乳动物细胞通产含有200,000个mRNA,因此至少要用50个单细胞一起才能到达最小CV值;考虑到逆转录的效率和环境干扰等因素,为得到准确的表达和细胞种类的识别,需要使用的细胞数量实际要更多。[5]
参见
编辑参考资料
编辑- ^ Eberwine J, Sul JY, Bartfai T, Kim J. The promise of single-cell sequencing. Nature Methods. January 2014, 11 (1): 25–7. PMID 24524134. doi:10.1038/nmeth.2769.
- ^ Pennisi E. Chronicling embryos, cell by cell, gene by gene. Science. April 2018, 360 (6387): 367. PMID 29700246. doi:10.1126/science.360.6387.367.
- ^ Zong C, Lu S, Chapman AR, Xie XS. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science. December 2012, 338 (6114): 1622–6. Bibcode:2012Sci...338.1622Z. PMC 3600412 . PMID 23258894. doi:10.1126/science.1229164.
- ^ Kurimoto K, Yabuta Y, Ohinata Y, Saitou M. Global single-cell cDNA amplification to provide a template for representative high-density oligonucleotide microarray analysis. Nature Protocols. 2007, 2 (3): 739–52. PMID 17406636. doi:10.1038/nprot.2007.79.
- ^ 5.0 5.1 "Shapiro E, Biezuner T, Linnarsson S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nature Reviews. Genetics. September 2013, 14 (9): 618–30. PMID 23897237. doi:10.1038/nrg3542."
- ^ Yachida S, Jones S, Bozic I, Antal T, Leary R, Fu B, Kamiyama M, Hruban RH, Eshleman JR, Nowak MA, Velculescu VE, Kinzler KW, Vogelstein B, Iacobuzio-Donahue CA. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature. October 2010, 467 (7319): 1114–7. Bibcode:2010Natur.467.1114Y. PMC 3148940 . PMID 20981102. doi:10.1038/nature09515.
- ^ Frumkin D, Wasserstrom A, Itzkovitz S, Harmelin A, Rechavi G, Shapiro E. Amplification of multiple genomic loci from single cells isolated by laser micro-dissection of tissues. BMC Biotechnology. February 2008, 8 (17): 17. PMC 2266725 . PMID 18284708. doi:10.1186/1472-6750-8-17.
- ^ Dalerba P, Kalisky T, Sahoo D, Rajendran PS, Rothenberg ME, Leyrat AA, Sim S, Okamoto J, Johnston DM, Qian D, Zabala M, Bueno J, Neff NF, Wang J, Shelton AA, Visser B, Hisamori S, Shimono Y, van de Wetering M, Clevers H, Clarke MF, Quake SR. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nature Biotechnology. November 2011, 29 (12): 1120–7. PMC 3237928 . PMID 22081019. doi:10.1038/nbt.2038.
- ^ White AK, VanInsberghe M, Petriv OI, Hamidi M, Sikorski D, Marra MA, Piret J, Aparicio S, Hansen CL. High-throughput microfluidic single-cell RT-qPCR. Proceedings of the National Academy of Sciences of the United States of America. August 2011, 108 (34): 13999–4004. Bibcode:2011PNAS..10813999W. PMC 3161570 . PMID 21808033. doi:10.1073/pnas.1019446108.