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Crossing enhanced and high fidelity SpCas9 nucleases to optimize specificity and cleavage

Overview of attention for article published in Genome Biology (Online Edition), October 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

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6 tweeters

Citations

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71 Dimensions

Readers on

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109 Mendeley
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Title
Crossing enhanced and high fidelity SpCas9 nucleases to optimize specificity and cleavage
Published in
Genome Biology (Online Edition), October 2017
DOI 10.1186/s13059-017-1318-8
Pubmed ID
Authors

Péter István Kulcsár, András Tálas, Krisztina Huszár, Zoltán Ligeti, Eszter Tóth, Nóra Weinhardt, Elfrieda Fodor, Ervin Welker

Abstract

The propensity for off-target activity of Streptococcus pyogenes Cas9 (SpCas9) has been considerably decreased by rationally engineered variants with increased fidelity (eSpCas9; SpCas9-HF1). However, a subset of targets still generate considerable off-target effects. To deal specifically with these targets, we generated new "Highly enhanced Fidelity" nuclease variants (HeFSpCas9s) containing mutations from both eSpCas9 and SpCas9-HF1 and examined these improved nuclease variants side by side to decipher the factors that affect their specificities and to determine the optimal nuclease for applications sensitive to off-target effects. These three increased-fidelity nucleases can routinely be used only with perfectly matching 20-nucleotide-long spacers, a matching 5' G extension being more detrimental to their activities than a mismatching one. HeFSpCas9 exhibit substantially improved specificity for those targets for which eSpCas9 and SpCas9-HF1 have higher off-target propensity. The targets can also be ranked by their cleavability and off-target effects manifested by the increased fidelity nucleases. Furthermore, we show that the mutations in these variants may diminish the cleavage, but not the DNA-binding, of SpCas9s. No single nuclease variant shows generally superior fidelity; instead, for highest specificity cleavage, each target needs to be matched with an appropriate high-fidelity nuclease. We provide here a framework for generating new nuclease variants for targets that currently have no matching optimal nuclease, and offer a simple means for identifying the optimal nuclease for targets in the absence of accurate target-ranking prediction tools.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 109 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 25%
Researcher 21 19%
Student > Bachelor 16 15%
Student > Master 11 10%
Student > Doctoral Student 7 6%
Other 12 11%
Unknown 15 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 46%
Agricultural and Biological Sciences 24 22%
Medicine and Dentistry 4 4%
Engineering 3 3%
Computer Science 2 2%
Other 6 6%
Unknown 20 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 10 January 2018.
All research outputs
#3,514,076
of 12,347,188 outputs
Outputs from Genome Biology (Online Edition)
#2,023
of 2,812 outputs
Outputs of similar age
#94,179
of 276,137 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 12,347,188 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,812 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 276,137 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them