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BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment

Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of s...

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Autores principales: Boel, Annekatrien, Steyaert, Woutert, De Rocker, Nina, Menten, Björn, Callewaert, Bert, De Paepe, Anne, Coucke, Paul, Willaert, Andy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962088/
https://www.ncbi.nlm.nih.gov/pubmed/27461955
http://dx.doi.org/10.1038/srep30330
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author Boel, Annekatrien
Steyaert, Woutert
De Rocker, Nina
Menten, Björn
Callewaert, Bert
De Paepe, Anne
Coucke, Paul
Willaert, Andy
author_facet Boel, Annekatrien
Steyaert, Woutert
De Rocker, Nina
Menten, Björn
Callewaert, Bert
De Paepe, Anne
Coucke, Paul
Willaert, Andy
author_sort Boel, Annekatrien
collection PubMed
description Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from https://github.com/WouterSteyaert/BATCH-GE.git. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome.
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spelling pubmed-49620882016-08-08 BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment Boel, Annekatrien Steyaert, Woutert De Rocker, Nina Menten, Björn Callewaert, Bert De Paepe, Anne Coucke, Paul Willaert, Andy Sci Rep Article Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from https://github.com/WouterSteyaert/BATCH-GE.git. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome. Nature Publishing Group 2016-07-27 /pmc/articles/PMC4962088/ /pubmed/27461955 http://dx.doi.org/10.1038/srep30330 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Boel, Annekatrien
Steyaert, Woutert
De Rocker, Nina
Menten, Björn
Callewaert, Bert
De Paepe, Anne
Coucke, Paul
Willaert, Andy
BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title_full BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title_fullStr BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title_full_unstemmed BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title_short BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
title_sort batch-ge: batch analysis of next-generation sequencing data for genome editing assessment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962088/
https://www.ncbi.nlm.nih.gov/pubmed/27461955
http://dx.doi.org/10.1038/srep30330
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