| Title |
A Mammalian enhancer trap resource for discovering and manipulating neuronal cell types
|
|---|---|
| Published in |
eLife, March 2016
|
| DOI | 10.7554/elife.13503 |
| Pubmed ID | |
| Authors |
Yasuyuki Shima, Ken Sugino, Chris Martin Hempel, Masami Shima, Praveen Taneja, James B Bullis, Sonam Mehta, Carlos Lois, Sacha B Nelson |
| Abstract |
There is a continuing need for driver strains to enable cell type-specific manipulation in the nervous system. Each cell type expresses a unique set of genes, and recapitulating expression of marker genes by BAC transgenesis or knock-in has generated useful transgenic mouse lines. However since genes are often expressed in many cell types, many of these lines have relatively broad expression patterns. We report an alternative transgenic approach capturing distal enhancers for more focused expression. We identified an enhancer trap probe often producing restricted reporter expression and developed efficient enhancer trap screening with the PiggyBac transposon. We established more than 200 lines and found many lines that label small subsets of neurons in brain substructures, including known and novel cell types. Images and other information about each line are available online (enhancertrap.bio.brandeis.edu). |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 55% |
| Japan | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 3 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 73% |
| Scientists | 3 | 27% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 4% |
| United Kingdom | 2 | 1% |
| Japan | 1 | <1% |
| France | 1 | <1% |
| Unknown | 129 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 26% |
| Researcher | 34 | 24% |
| Student > Postgraduate | 13 | 9% |
| Student > Master | 10 | 7% |
| Student > Doctoral Student | 7 | 5% |
| Other | 17 | 12% |
| Unknown | 22 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 51 | 37% |
| Agricultural and Biological Sciences | 39 | 28% |
| Biochemistry, Genetics and Molecular Biology | 16 | 12% |
| Medicine and Dentistry | 3 | 2% |
| Engineering | 2 | 1% |
| Other | 4 | 3% |
| Unknown | 24 | 17% |