Literature DB >> 25449304

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

Hiroko Matsunaga1, Mari Goto1, Koji Arikawa1, Masataka Shirai1, Hiroyuki Tsunoda1, Huan Huang2, Hideki Kambara3.   

Abstract

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes.
Copyright © 2014 Elsevier Inc. All rights reserved.

Keywords:  Gene expression; Single cell; mRNA-seq

Mesh:

Substances:

Year:  2014        PMID: 25449304     DOI: 10.1016/j.ab.2014.10.011

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  7 in total

Review 1.  Wake-up alarm: virtual time-lapse gene expression landscape illuminates mechanisms underlying dormancy breaking of germinating spores.

Authors:  Hayato Tsuyuzaki; Ryosuke Ujiie; Masamitsu Sato
Journal:  Curr Genet       Date:  2021-03-29       Impact factor: 3.886

2.  TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq.

Authors:  Shigeyuki Shichino; Satoshi Ueha; Shinichi Hashimoto; Tatsuro Ogawa; Hiroyasu Aoki; Bin Wu; Chang-Yu Chen; Masahiro Kitabatake; Noriko Ouji-Sageshima; Noriyoshi Sawabata; Takeshi Kawaguchi; Toshitugu Okayama; Eiji Sugihara; Shigeto Hontsu; Toshihiro Ito; Yasunori Iwata; Takashi Wada; Kazuho Ikeo; Taka-Aki Sato; Kouji Matsushima
Journal:  Commun Biol       Date:  2022-06-27

3.  Vertical flow array chips reliably identify cell types from single-cell mRNA sequencing experiments.

Authors:  Masataka Shirai; Koji Arikawa; Kiyomi Taniguchi; Maiko Tanabe; Tomoyuki Sakai
Journal:  Sci Rep       Date:  2016-11-23       Impact factor: 4.379

4.  DBTSS/DBKERO for integrated analysis of transcriptional regulation.

Authors:  Ayako Suzuki; Shin Kawano; Toutai Mitsuyama; Mikita Suyama; Yae Kanai; Katsuhiko Shirahige; Hiroyuki Sasaki; Katsushi Tokunaga; Katsuya Tsuchihara; Sumio Sugano; Kenta Nakai; Yutaka Suzuki
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

5.  Site-specific gene expression analysis using an automated tissue micro-dissection punching system.

Authors:  Takuya Yoda; Masahito Hosokawa; Kiyofumi Takahashi; Chikako Sakanashi; Haruko Takeyama; Hideki Kambara
Journal:  Sci Rep       Date:  2017-06-28       Impact factor: 4.379

6.  Combinatory use of distinct single-cell RNA-seq analytical platforms reveals the heterogeneous transcriptome response.

Authors:  Yukie Kashima; Ayako Suzuki; Ying Liu; Masahito Hosokawa; Hiroko Matsunaga; Masataka Shirai; Kohji Arikawa; Sumio Sugano; Takashi Kohno; Haruko Takeyama; Katsuya Tsuchihara; Yutaka Suzuki
Journal:  Sci Rep       Date:  2018-02-22       Impact factor: 4.379

Review 7.  Single-cell sequencing techniques from individual to multiomics analyses.

Authors:  Yukie Kashima; Yoshitaka Sakamoto; Keiya Kaneko; Masahide Seki; Yutaka Suzuki; Ayako Suzuki
Journal:  Exp Mol Med       Date:  2020-09-15       Impact factor: 8.718

  7 in total

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