Literature DB >> 24652479

Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos.

Na Liu1, Lin Liu, Xinghua Pan.   

Abstract

Cellular heterogeneity within a cell population is a common phenomenon in multicellular organisms, tissues, cultured cells, and even FACS-sorted subpopulations. Important information may be masked if the cells are studied as a mass. Transcriptome profiling is a parameter that has been intensively studied, and relatively easier to address than protein composition. To understand the basis and importance of heterogeneity and stochastic aspects of the cell function and its mechanisms, it is essential to examine transcriptomes of a panel of single cells. High-throughput technologies, starting from microarrays and now RNA-seq, provide a full view of the expression of transcriptomes but are limited by the amount of RNA for analysis. Recently, several new approaches for amplification and sequencing the transcriptome of single cells or a limited low number of cells have been developed and applied. In this review, we summarize these major strategies, such as PCR-based methods, IVT-based methods, phi29-DNA polymerase-based methods, and several other methods, including their principles, characteristics, advantages, and limitations, with representative applications in cancer stem cells, early development, and embryonic stem cells. The prospects for development of future technology and application of transcriptome analysis in a single cell are also discussed.

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Year:  2014        PMID: 24652479     DOI: 10.1007/s00018-014-1601-8

Source DB:  PubMed          Journal:  Cell Mol Life Sci        ISSN: 1420-682X            Impact factor:   9.261


  67 in total

Review 1.  RNA sequencing: advances, challenges and opportunities.

Authors:  Fatih Ozsolak; Patrice M Milos
Journal:  Nat Rev Genet       Date:  2010-12-30       Impact factor: 53.242

2.  Systems biology and new technologies enable predictive and preventative medicine.

Authors:  Leroy Hood; James R Heath; Michael E Phelps; Biaoyang Lin
Journal:  Science       Date:  2004-10-22       Impact factor: 47.728

3.  A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome.

Authors:  Marc Sultan; Marcel H Schulz; Hugues Richard; Alon Magen; Andreas Klingenhoff; Matthias Scherf; Martin Seifert; Tatjana Borodina; Aleksey Soldatov; Dmitri Parkhomchuk; Dominic Schmidt; Sean O'Keeffe; Stefan Haas; Martin Vingron; Hans Lehrach; Marie-Laure Yaspo
Journal:  Science       Date:  2008-07-03       Impact factor: 47.728

4.  Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction.

Authors:  Y Y Zhu; E M Machleder; A Chenchik; R Li; P D Siebert
Journal:  Biotechniques       Date:  2001-04       Impact factor: 1.993

5.  Robust measurement of telomere length in single cells.

Authors:  Fang Wang; Xinghua Pan; Keri Kalmbach; Michelle L Seth-Smith; Xiaoying Ye; Danielle M F Antumes; Yu Yin; Lin Liu; David L Keefe; Sherman M Weissman
Journal:  Proc Natl Acad Sci U S A       Date:  2013-05-09       Impact factor: 11.205

6.  Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing.

Authors:  Zhigang Xue; Kevin Huang; Chaochao Cai; Lingbo Cai; Chun-yan Jiang; Yun Feng; Zhenshan Liu; Qiao Zeng; Liming Cheng; Yi E Sun; Jia-yin Liu; Steve Horvath; Guoping Fan
Journal:  Nature       Date:  2013-07-28       Impact factor: 49.962

Review 7.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

8.  mRNA-Seq of single prostate cancer circulating tumor cells reveals recapitulation of gene expression and pathways found in prostate cancer.

Authors:  Gordon M Cann; Zulfiqar G Gulzar; Samantha Cooper; Robin Li; Shujun Luo; Mai Tat; Sarah Stuart; Gary Schroth; Sandhya Srinivas; Mostafa Ronaghi; James D Brooks; Amirali H Talasaz
Journal:  PLoS One       Date:  2012-11-07       Impact factor: 3.240

9.  Alternative isoform regulation in human tissue transcriptomes.

Authors:  Eric T Wang; Rickard Sandberg; Shujun Luo; Irina Khrebtukova; Lu Zhang; Christine Mayr; Stephen F Kingsmore; Gary P Schroth; Christopher B Burge
Journal:  Nature       Date:  2008-11-27       Impact factor: 49.962

10.  Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity.

Authors:  Yohei Sasagawa; Itoshi Nikaido; Tetsutaro Hayashi; Hiroki Danno; Kenichiro D Uno; Takeshi Imai; Hiroki R Ueda
Journal:  Genome Biol       Date:  2013-04-17       Impact factor: 13.583

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  12 in total

1.  Single-Cell Sequencing and Organoids: A Powerful Combination for Modelling Organ Development and Diseases.

Authors:  Yuebang Yin; Peng-Yu Liu; Yinghua Shi; Ping Li
Journal:  Rev Physiol Biochem Pharmacol       Date:  2021       Impact factor: 5.545

Review 2.  Mass spectrometry-based characterization of endogenous peptides and metabolites in small volume samples.

Authors:  Ta-Hsuan Ong; Emily G Tillmaand; Monika Makurath; Stanislav S Rubakhin; Jonathan V Sweedler
Journal:  Biochim Biophys Acta       Date:  2015-01-21

3.  Aberrant expression of maternal Plk1 and Dctn3 results in the developmental failure of human in-vivo- and in-vitro-matured oocytes.

Authors:  Yong Fan; Hong-Cui Zhao; Jianqiao Liu; Tao Tan; Ting Ding; Rong Li; Yue Zhao; Jie Yan; Xiaofang Sun; Yang Yu; Jie Qiao
Journal:  Sci Rep       Date:  2015-02-03       Impact factor: 4.379

Review 4.  Single-cell Transcriptome Study as Big Data.

Authors:  Pingjian Yu; Wei Lin
Journal:  Genomics Proteomics Bioinformatics       Date:  2016-02-11       Impact factor: 7.691

5.  High resolution temporal transcriptomics of mouse embryoid body development reveals complex expression dynamics of coding and noncoding loci.

Authors:  Brian S Gloss; Bethany Signal; Seth W Cheetham; Franziska Gruhl; Dominik C Kaczorowski; Andrew C Perkins; Marcel E Dinger
Journal:  Sci Rep       Date:  2017-07-27       Impact factor: 4.379

Review 6.  Single-cell RNA-sequencing of the brain.

Authors:  Raquel Cuevas-Diaz Duran; Haichao Wei; Jia Qian Wu
Journal:  Clin Transl Med       Date:  2017-06-08

Review 7.  Single-cell sequencing and tumorigenesis: improved understanding of tumor evolution and metastasis.

Authors:  Darrell L Ellsworth; Heather L Blackburn; Craig D Shriver; Shahrooz Rabizadeh; Patrick Soon-Shiong; Rachel E Ellsworth
Journal:  Clin Transl Med       Date:  2017-04-12

8.  SCDevDB: A Database for Insights Into Single-Cell Gene Expression Profiles During Human Developmental Processes.

Authors:  Zishuai Wang; Xikang Feng; Shuai Cheng Li
Journal:  Front Genet       Date:  2019-09-26       Impact factor: 4.599

9.  Single Cell Analysis: From Technology to Biology and Medicine.

Authors:  Xinghua Pan
Journal:  Single Cell Biol       Date:  2014

Review 10.  Single Cell Isolation and Analysis.

Authors:  Ping Hu; Wenhua Zhang; Hongbo Xin; Glenn Deng
Journal:  Front Cell Dev Biol       Date:  2016-10-25
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