Literature DB >> 28146356

sgRNA Scorer 2.0: A Species-Independent Model To Predict CRISPR/Cas9 Activity.

Raj Chari1, Nan Cher Yeo1,2, Alejandro Chavez1,2, George M Church1,2.   

Abstract

It has been possible to create tools to predict single guide RNA (sgRNA) activity in the CRISPR/Cas9 system derived from Streptococcus pyogenes due to the large amount of data that has been generated in sgRNA library screens. However, with the discovery of additional CRISPR systems from different bacteria, which show potent activity in eukaryotic cells, the approach of generating large data sets for each of these systems to predict their activity is not tractable. Here, we present a new guide RNA tool that can predict sgRNA activity across multiple CRISPR systems. In addition to predicting activity for Cas9 from S. pyogenes and Streptococcus thermophilus CRISPR1, we experimentally demonstrate that our algorithm can predict activity for Cas9 from Staphylococcus aureus and S. thermophilus CRISPR3. We also have made available a new version of our software, sgRNA Scorer 2.0, which will allow users to identify sgRNA sites for any PAM sequence of interest.

Entities:  

Keywords:  CRISPR; Cas9; genome engineering; sgRNA activity prediction; sgRNA scorer

Mesh:

Substances:

Year:  2017        PMID: 28146356      PMCID: PMC5793212          DOI: 10.1021/acssynbio.6b00343

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  18 in total

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Journal:  Nat Methods       Date:  2016-12-19       Impact factor: 28.547

4.  Improved vectors and genome-wide libraries for CRISPR screening.

Authors:  Neville E Sanjana; Ophir Shalem; Feng Zhang
Journal:  Nat Methods       Date:  2014-08       Impact factor: 28.547

5.  Sequence determinants of improved CRISPR sgRNA design.

Authors:  Han Xu; Tengfei Xiao; Chen-Hao Chen; Wei Li; Clifford A Meyer; Qiu Wu; Di Wu; Le Cong; Feng Zhang; Jun S Liu; Myles Brown; X Shirley Liu
Journal:  Genome Res       Date:  2015-06-10       Impact factor: 9.043

6.  In vivo genome editing using Staphylococcus aureus Cas9.

Authors:  F Ann Ran; Le Cong; Winston X Yan; David A Scott; Jonathan S Gootenberg; Andrea J Kriz; Bernd Zetsche; Ophir Shalem; Xuebing Wu; Kira S Makarova; Eugene V Koonin; Phillip A Sharp; Feng Zhang
Journal:  Nature       Date:  2015-04-01       Impact factor: 49.962

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

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Journal:  Nat Biotechnol       Date:  2016-01-18       Impact factor: 54.908

8.  Unraveling CRISPR-Cas9 genome engineering parameters via a library-on-library approach.

Authors:  Raj Chari; Prashant Mali; Mark Moosburner; George M Church
Journal:  Nat Methods       Date:  2015-07-13       Impact factor: 28.547

9.  CHOPCHOP v2: a web tool for the next generation of CRISPR genome engineering.

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Journal:  Genome Biol       Date:  2015-11-24       Impact factor: 13.583

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  74 in total

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Authors:  Amy R Poe; Bei Wang; Maria L Sapar; Hui Ji; Kailyn Li; Tireniolu Onabajo; Rushaniya Fazliyeva; Mary Gibbs; Yue Qiu; Yuzhao Hu; Chun Han
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Journal:  Nat Biotechnol       Date:  2020-07-06       Impact factor: 54.908

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Journal:  Mol Cell Biol       Date:  2018-09-14       Impact factor: 4.272

4.  Impact of Losing hRpn13 Pru or UCHL5 on Proteasome Clearance of Ubiquitinated Proteins and RA190 Cytotoxicity.

Authors:  Vasty Osei-Amponsa; Vinidhra Sridharan; Mayank Tandon; Christine N Evans; Kimberly Klarmann; Kwong Tai Cheng; Justin Lack; Raj Chari; Kylie J Walters
Journal:  Mol Cell Biol       Date:  2020-08-28       Impact factor: 4.272

5.  Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

Authors:  Hui Kwon Kim; Seonwoo Min; Myungjae Song; Soobin Jung; Jae Woo Choi; Younggwang Kim; Sangeun Lee; Sungroh Yoon; Hyongbum Henry Kim
Journal:  Nat Biotechnol       Date:  2018-01-29       Impact factor: 54.908

6.  An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

Authors:  Jun Wang; Xiuqing Zhang; Lixin Cheng; Yonglun Luo
Journal:  RNA Biol       Date:  2019-09-27       Impact factor: 4.652

7.  Multilayered VBC score predicts sgRNAs that efficiently generate loss-of-function alleles.

Authors:  Georg Michlits; Julian Jude; Matthias Hinterndorfer; Melanie de Almeida; Gintautas Vainorius; Maria Hubmann; Tobias Neumann; Alexander Schleiffer; Thomas Rainer Burkard; Michaela Fellner; Max Gijsbertsen; Anna Traunbauer; Johannes Zuber; Ulrich Elling
Journal:  Nat Methods       Date:  2020-06-08       Impact factor: 28.547

8.  Atheroprotective Flow Upregulates ITPR3 (Inositol 1,4,5-Trisphosphate Receptor 3) in Vascular Endothelium via KLF4 (Krüppel-Like Factor 4)-Mediated Histone Modifications.

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Journal:  Arterioscler Thromb Vasc Biol       Date:  2019-05       Impact factor: 8.311

9.  CRISPR Guide RNA Cloning for Mammalian Systems.

Authors:  Sathiji Nageshwaran; Alejandro Chavez; Nan Cher Yeo; Xiaoge Guo; Alissa Lance-Byrne; Angela Tung; James J Collins; George M Church
Journal:  J Vis Exp       Date:  2018-10-02       Impact factor: 1.355

10.  Efficient Genome Engineering of a Virulent Klebsiella Bacteriophage Using CRISPR-Cas9.

Authors:  Juntao Shen; Jinjie Zhou; Guo-Qiang Chen; Zhi-Long Xiu
Journal:  J Virol       Date:  2018-08-16       Impact factor: 5.103

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