Computational approaches for effective CRISPR guide RNA design and evaluation

Computational approaches for effective CRISPR guide RNA design and evaluation

The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/ CRISPR-associated (Cas) system has emerged as the main technology for gene editing. Successful editing by CRISPR requires an appropriate Cas protein and guide RNA. However, low cleavage efficiency and off-target effects hamper th...

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Main Authors: Guanqing Liu, Yong Zhang, Tao Zhang
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
CRISPR
Guide RNA design
Efficiency
Specificity
Machine-learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037019303551
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spelling doaj-5b8038e55b374fa180f811af1c2200582021-01-02T05:08:17ZengElsevierComputational and Structural Biotechnology Journal2001-03702020-01-01183544Computational approaches for effective CRISPR guide RNA design and evaluationGuanqing Liu0Yong Zhang1Tao Zhang2Jiangsu Key Laboratory of Crop Genetics and Physiology/ Key Laboratory of Plant Functional Genomics of the Ministry of Education/ Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou 225009, China; Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, ChinaJiangsu Key Laboratory of Crop Genetics and Physiology/ Key Laboratory of Plant Functional Genomics of the Ministry of Education/ Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou 225009, China; Department of Biotechnology, School of Life Sciences and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China; Corresponding authors.Jiangsu Key Laboratory of Crop Genetics and Physiology/ Key Laboratory of Plant Functional Genomics of the Ministry of Education/ Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou 225009, China; Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; Corresponding authors.The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/ CRISPR-associated (Cas) system has emerged as the main technology for gene editing. Successful editing by CRISPR requires an appropriate Cas protein and guide RNA. However, low cleavage efficiency and off-target effects hamper the development and application of CRISPR/Cas systems. To predict cleavage efficiency and specificity, numerous computational approaches have been developed for scoring guide RNAs. Most scores are empirical or trained by experimental datasets, and scores are implemented using various computational methods. Herein, we discuss these approaches, focusing mainly on the features or computational methods they utilise. Furthermore, we summarise these tools and give some suggestions for their usage. We also recommend three versatile web-based tools with user-friendly interfaces and preferable functions. The review provides a comprehensive and up-to-date overview of computational approaches for guide RNA design that could help users to select the optimal tools for their research.http://www.sciencedirect.com/science/article/pii/S2001037019303551CRISPRGuide RNA designEfficiencySpecificityMachine-learning
collection DOAJ
language English
format Article
sources DOAJ
author Guanqing Liu
Yong Zhang
Tao Zhang
spellingShingle Guanqing Liu
Yong Zhang
Tao Zhang
Computational approaches for effective CRISPR guide RNA design and evaluation
Computational and Structural Biotechnology Journal
CRISPR
Guide RNA design
Efficiency
Specificity
Machine-learning
author_facet Guanqing Liu
Yong Zhang
Tao Zhang
author_sort Guanqing Liu
title Computational approaches for effective CRISPR guide RNA design and evaluation
title_short Computational approaches for effective CRISPR guide RNA design and evaluation
title_full Computational approaches for effective CRISPR guide RNA design and evaluation
title_fullStr Computational approaches for effective CRISPR guide RNA design and evaluation
title_full_unstemmed Computational approaches for effective CRISPR guide RNA design and evaluation
title_sort computational approaches for effective crispr guide rna design and evaluation
publisher Elsevier
series Computational and Structural Biotechnology Journal
issn 2001-0370
publishDate 2020-01-01
description The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/ CRISPR-associated (Cas) system has emerged as the main technology for gene editing. Successful editing by CRISPR requires an appropriate Cas protein and guide RNA. However, low cleavage efficiency and off-target effects hamper the development and application of CRISPR/Cas systems. To predict cleavage efficiency and specificity, numerous computational approaches have been developed for scoring guide RNAs. Most scores are empirical or trained by experimental datasets, and scores are implemented using various computational methods. Herein, we discuss these approaches, focusing mainly on the features or computational methods they utilise. Furthermore, we summarise these tools and give some suggestions for their usage. We also recommend three versatile web-based tools with user-friendly interfaces and preferable functions. The review provides a comprehensive and up-to-date overview of computational approaches for guide RNA design that could help users to select the optimal tools for their research.
topic CRISPR
Guide RNA design
Efficiency
Specificity
Machine-learning
url http://www.sciencedirect.com/science/article/pii/S2001037019303551
work_keys_str_mv AT guanqingliu computationalapproachesforeffectivecrisprguidernadesignandevaluation
AT yongzhang computationalapproachesforeffectivecrisprguidernadesignandevaluation
AT taozhang computationalapproachesforeffectivecrisprguidernadesignandevaluation
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