↓ Skip to main content

Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9

Overview of attention for article published in Nature Biotechnology, January 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Citations

dimensions_citation
3199 Dimensions

Readers on

mendeley
4306 Mendeley
citeulike
5 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
Published in
Nature Biotechnology, January 2016
DOI 10.1038/nbt.3437
Pubmed ID
Authors

John G Doench, Nicolo Fusi, Meagan Sullender, Mudra Hegde, Emma W Vaimberg, Katherine F Donovan, Ian Smith, Zuzana Tothova, Craig Wilen, Robert Orchard, Herbert W Virgin, Jennifer Listgarten, David E Root

Abstract

CRISPR-Cas9-based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.

X Demographics

X Demographics

The data shown below were collected from the profiles of 76 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4,306 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 15 <1%
United Kingdom 8 <1%
Germany 6 <1%
Canada 6 <1%
Finland 4 <1%
Austria 3 <1%
Denmark 3 <1%
Belgium 2 <1%
China 2 <1%
Other 9 <1%
Unknown 4248 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 985 23%
Researcher 736 17%
Student > Bachelor 496 12%
Student > Master 490 11%
Student > Doctoral Student 186 4%
Other 507 12%
Unknown 906 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1515 35%
Agricultural and Biological Sciences 960 22%
Medicine and Dentistry 175 4%
Immunology and Microbiology 168 4%
Neuroscience 109 3%
Other 378 9%
Unknown 1001 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 132. 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 25 April 2024.
All research outputs
#322,992
of 25,784,004 outputs
Outputs from Nature Biotechnology
#744
of 8,625 outputs
Outputs of similar age
#5,640
of 404,127 outputs
Outputs of similar age from Nature Biotechnology
#16
of 103 outputs
Altmetric has tracked 25,784,004 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,625 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.5. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 404,127 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.