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Computational Tools and Resources Supporting CRISPR-Cas Experiments
The CRISPR-Cas system has become a cutting-edge technology that revolutionized genome engineering. The use of Cas9 nuclease is currently the method of choice in most tasks requiring a specific DNA modification. The rapid development in the field of CRISPR-Cas is reflected by the constantly expanding...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290941/ https://www.ncbi.nlm.nih.gov/pubmed/32455882 http://dx.doi.org/10.3390/cells9051288 |
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author | Sledzinski, Pawel Nowaczyk, Mateusz Olejniczak, Marta |
author_facet | Sledzinski, Pawel Nowaczyk, Mateusz Olejniczak, Marta |
author_sort | Sledzinski, Pawel |
collection | PubMed |
description | The CRISPR-Cas system has become a cutting-edge technology that revolutionized genome engineering. The use of Cas9 nuclease is currently the method of choice in most tasks requiring a specific DNA modification. The rapid development in the field of CRISPR-Cas is reflected by the constantly expanding ecosystem of computational tools aimed at facilitating experimental design and result analysis. The first group of CRISPR-Cas-related tools that we review is dedicated to aid in guide RNA design by prediction of their efficiency and specificity. The second, relatively new group of tools exploits the observed biases in repair outcomes to predict the results of CRISPR-Cas edits. The third class of tools is developed to assist in the evaluation of the editing outcomes by analysis of the sequencing data. These utilities are accompanied by relevant repositories and databases. Here we present a comprehensive and updated overview of the currently available CRISPR-Cas-related tools, from the perspective of a user who needs a convenient and reliable means to facilitate genome editing experiments at every step, from the guide RNA design to analysis of editing outcomes. Moreover, we discuss the current limitations and challenges that the field must overcome for further improvement in the CRISPR-Cas endeavor. |
format | Online Article Text |
id | pubmed-7290941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72909412020-06-17 Computational Tools and Resources Supporting CRISPR-Cas Experiments Sledzinski, Pawel Nowaczyk, Mateusz Olejniczak, Marta Cells Review The CRISPR-Cas system has become a cutting-edge technology that revolutionized genome engineering. The use of Cas9 nuclease is currently the method of choice in most tasks requiring a specific DNA modification. The rapid development in the field of CRISPR-Cas is reflected by the constantly expanding ecosystem of computational tools aimed at facilitating experimental design and result analysis. The first group of CRISPR-Cas-related tools that we review is dedicated to aid in guide RNA design by prediction of their efficiency and specificity. The second, relatively new group of tools exploits the observed biases in repair outcomes to predict the results of CRISPR-Cas edits. The third class of tools is developed to assist in the evaluation of the editing outcomes by analysis of the sequencing data. These utilities are accompanied by relevant repositories and databases. Here we present a comprehensive and updated overview of the currently available CRISPR-Cas-related tools, from the perspective of a user who needs a convenient and reliable means to facilitate genome editing experiments at every step, from the guide RNA design to analysis of editing outcomes. Moreover, we discuss the current limitations and challenges that the field must overcome for further improvement in the CRISPR-Cas endeavor. MDPI 2020-05-22 /pmc/articles/PMC7290941/ /pubmed/32455882 http://dx.doi.org/10.3390/cells9051288 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Sledzinski, Pawel Nowaczyk, Mateusz Olejniczak, Marta Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title | Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title_full | Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title_fullStr | Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title_full_unstemmed | Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title_short | Computational Tools and Resources Supporting CRISPR-Cas Experiments |
title_sort | computational tools and resources supporting crispr-cas experiments |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290941/ https://www.ncbi.nlm.nih.gov/pubmed/32455882 http://dx.doi.org/10.3390/cells9051288 |
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