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An efficient CRISPR vector toolbox for engineering large deletions in Arabidopsis thaliana

Overview of attention for article published in Plant Methods, August 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 1,267)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

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96 X users
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2 Facebook pages

Citations

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56 Dimensions

Readers on

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133 Mendeley
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Title
An efficient CRISPR vector toolbox for engineering large deletions in Arabidopsis thaliana
Published in
Plant Methods, August 2018
DOI 10.1186/s13007-018-0330-7
Pubmed ID
Authors

Rui Wu, Miriam Lucke, Yun-ting Jang, Wangsheng Zhu, Efthymia Symeonidi, Congmao Wang, Joffrey Fitz, Wanyan Xi, Rebecca Schwab, Detlef Weigel

Abstract

Our knowledge of natural genetic variation is increasing at an extremely rapid pace, affording an opportunity to come to a much richer understanding of how effects of specific genes are dependent on the genetic background. To achieve a systematic understanding of such GxG interactions, it is desirable to develop genome editing tools that can be rapidly deployed across many different genetic varieties. We present an efficient CRISPR/Cas9 toolbox of super module (SM) vectors. These vectors are based on a previously described fluorescence protein marker expressed in seeds allowing identification of transgene-free mutants. We have used this vector series to delete genomic regions ranging from 1.7 to 13 kb in different natural accessions of the wild plant Arabidopsis thaliana. Based on results from 53 pairs of sgRNAs targeting individual nucleotide binding site leucine-rich repeat (NLR) genes, we provide a comprehensive overview of obtaining heritable deletions. The SM series of CRISPR/Cas9 vectors enables the rapid generation of transgene-free, genome edited plants for a diversity of functional studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 96 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 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 133 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 20%
Student > Ph. D. Student 25 19%
Student > Master 19 14%
Student > Bachelor 15 11%
Student > Doctoral Student 5 4%
Other 16 12%
Unknown 27 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 60 45%
Biochemistry, Genetics and Molecular Biology 40 30%
Computer Science 3 2%
Engineering 2 2%
Social Sciences 1 <1%
Other 2 2%
Unknown 25 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 06 March 2019.
All research outputs
#785,200
of 25,399,318 outputs
Outputs from Plant Methods
#16
of 1,267 outputs
Outputs of similar age
#16,745
of 342,004 outputs
Outputs of similar age from Plant Methods
#1
of 32 outputs
Altmetric has tracked 25,399,318 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,267 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 98% 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 342,004 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 95% of its contemporaries.
We're also able to compare this research output to 32 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 99% of its contemporaries.