Title |
Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity
|
---|---|
Published in |
Genome Biology, April 2013
|
DOI | 10.1186/gb-2013-14-4-r31 |
Pubmed ID | |
Authors |
Yohei Sasagawa, Itoshi Nikaido, Tetsutaro Hayashi, Hiroki Danno, Kenichiro D Uno, Takeshi Imai, Hiroki R Ueda |
Abstract |
Development of a highly reproducible and sensitive single-cell RNA sequencing (RNA-seq) method would facilitate the understanding of the biological roles and underlying mechanisms of non-genetic cellular heterogeneity. In this study, we report a novel single-cell RNA-seq method called Quartz-Seq that has a simpler protocol and higher reproducibility and sensitivity than existing methods. We show that single-cell Quartz-Seq can quantitatively detect various kinds of non-genetic cellular heterogeneity, and can detect different cell types and different cell-cycle phases of a single cell type. Moreover, this method can comprehensively reveal gene-expression heterogeneity between single cells of the same cell type in the same cell-cycle phase. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 14 | 24% |
United States | 8 | 14% |
United Kingdom | 2 | 3% |
Austria | 2 | 3% |
China | 2 | 3% |
Canada | 2 | 3% |
Germany | 1 | 2% |
France | 1 | 2% |
Unknown | 26 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 41 | 71% |
Scientists | 16 | 28% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 3% |
Japan | 7 | 1% |
United Kingdom | 3 | <1% |
France | 2 | <1% |
Sweden | 2 | <1% |
South Africa | 2 | <1% |
Austria | 1 | <1% |
Australia | 1 | <1% |
Netherlands | 1 | <1% |
Other | 7 | 1% |
Unknown | 637 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 183 | 27% |
Student > Ph. D. Student | 143 | 21% |
Student > Master | 75 | 11% |
Student > Bachelor | 50 | 7% |
Student > Doctoral Student | 32 | 5% |
Other | 112 | 16% |
Unknown | 85 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 289 | 43% |
Biochemistry, Genetics and Molecular Biology | 166 | 24% |
Medicine and Dentistry | 39 | 6% |
Neuroscience | 25 | 4% |
Computer Science | 19 | 3% |
Other | 50 | 7% |
Unknown | 92 | 14% |