| Title |
Marker-free genetic manipulations in yeast using CRISPR/CAS9 system
|
|---|---|
| Published in |
Current Genetics, April 2018
|
| DOI | 10.1007/s00294-018-0831-y |
| Pubmed ID | |
| Authors |
Inga Soreanu, Adi Hendler, Danielle Dahan, Daniel Dovrat, Amir Aharoni |
| Abstract |
The budding yeast is currently one of the major model organisms for the study of a wide variety of biological processes. Genetic manipulation of yeast involves the extensive usage of selectable markers that can lead to undesired effects. Thus, marker-free genetic manipulation in yeast is highly desirable for gene/promoter replacement and various other applications. Here we combine the power of selectable markers followed by CRISPR/CAS9 genome editing for common genetic manipulations in yeast in a marker-free manner. We demonstrate our approach for whole gene and promoter replacements and for high-efficiency operator array integration. Our approach allows the utilization of many thousands of existing strains including library strains for the generation of significant genetic changes in yeast in a marker-free and cloning-free fashion. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 80 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 19% |
| Researcher | 13 | 16% |
| Student > Bachelor | 12 | 15% |
| Student > Master | 9 | 11% |
| Professor > Associate Professor | 4 | 5% |
| Other | 8 | 10% |
| Unknown | 19 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 35 | 44% |
| Agricultural and Biological Sciences | 16 | 20% |
| Engineering | 2 | 3% |
| Chemical Engineering | 1 | 1% |
| Veterinary Science and Veterinary Medicine | 1 | 1% |
| Other | 4 | 5% |
| Unknown | 21 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2023.
All research outputs
#4,151,326
of 23,862,416 outputs
Outputs from Current Genetics
#104
of 1,214 outputs
Outputs of similar age
#77,596
of 332,640 outputs
Outputs of similar age from Current Genetics
#2
of 24 outputs
Altmetric has tracked 23,862,416 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,214 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 91% of its peers.
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We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.