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Effective screen of CRISPR/Cas9-induced mutants in rice by single-strand conformation polymorphism

Overview of attention for article published in Plant Cell Reports, March 2016
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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 (#12 of 2,188)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
5 blogs

Citations

dimensions_citation
74 Dimensions

Readers on

mendeley
113 Mendeley
Title
Effective screen of CRISPR/Cas9-induced mutants in rice by single-strand conformation polymorphism
Published in
Plant Cell Reports, March 2016
DOI 10.1007/s00299-016-1967-1
Pubmed ID
Authors

Xuelian Zheng, Shixin Yang, Dengwei Zhang, Zhaohui Zhong, Xu Tang, Kejun Deng, Jianping Zhou, Yiping Qi, Yong Zhang

Abstract

A method based on DNA single-strand conformation polymorphism is demonstrated for effective genotyping of CRISPR/Cas9-induced mutants in rice. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) has been widely adopted for genome editing in many organisms. A large proportion of mutations generated by CRISPR/Cas9 are very small insertions and deletions (indels), presumably because Cas9 generates blunt-ended double-strand breaks which are subsequently repaired without extensive end-processing. CRISPR/Cas9 is highly effective for targeted mutagenesis in the important crop, rice. For example, homozygous mutant seedlings are commonly recovered from CRISPR/Cas9-treated calli. However, many current mutation detection methods are not very suitable for screening homozygous mutants that typically carry small indels. In this study, we tested a mutation detection method based on single-strand conformational polymorphism (SSCP). We found it can effectively detect small indels in pilot experiments. By applying the SSCP method for CRISRP-Cas9-mediated targeted mutagenesis in rice, we successfully identified multiple mutants of OsROC5 and OsDEP1. In conclusion, the SSCP analysis will be a useful genotyping method for rapid identification of CRISPR/Cas9-induced mutants, including the most desirable homozygous mutants. The method also has high potential for similar applications in other plant species.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
Italy 1 <1%
Benin 1 <1%
Sri Lanka 1 <1%
Argentina 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 106 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 27%
Student > Ph. D. Student 22 19%
Student > Master 13 12%
Student > Bachelor 9 8%
Student > Doctoral Student 4 4%
Other 11 10%
Unknown 24 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 45%
Biochemistry, Genetics and Molecular Biology 32 28%
Computer Science 2 2%
Engineering 2 2%
Business, Management and Accounting 1 <1%
Other 5 4%
Unknown 20 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 33. 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 23 September 2019.
All research outputs
#1,038,616
of 22,858,915 outputs
Outputs from Plant Cell Reports
#12
of 2,188 outputs
Outputs of similar age
#19,722
of 300,567 outputs
Outputs of similar age from Plant Cell Reports
#2
of 41 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,188 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 99% 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 300,567 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 93% of its contemporaries.
We're also able to compare this research output to 41 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.