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Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data

During CRISPR-directed gene editing, multiple gene repair mechanisms interact to produce a wide and largely unpredictable variety of sequence changes across an edited population of cells. Shortcomings inherent to previously available proposal-based insertion and deletion (indel) analysis software ne...

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Autores principales: Bloh, Kevin, Kanchana, Rohan, Bialk, Pawel, Banas, Kelly, Zhang, Zugui, Yoo, Byung-Chun, Kmiec, Eric B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7898406/
https://www.ncbi.nlm.nih.gov/pubmed/33571043
http://dx.doi.org/10.1089/crispr.2020.0022
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author Bloh, Kevin
Kanchana, Rohan
Bialk, Pawel
Banas, Kelly
Zhang, Zugui
Yoo, Byung-Chun
Kmiec, Eric B.
author_facet Bloh, Kevin
Kanchana, Rohan
Bialk, Pawel
Banas, Kelly
Zhang, Zugui
Yoo, Byung-Chun
Kmiec, Eric B.
author_sort Bloh, Kevin
collection PubMed
description During CRISPR-directed gene editing, multiple gene repair mechanisms interact to produce a wide and largely unpredictable variety of sequence changes across an edited population of cells. Shortcomings inherent to previously available proposal-based insertion and deletion (indel) analysis software necessitated the development of a more comprehensive tool that could detect a larger range and variety of indels while maintaining the ease of use of tools currently available. To that end, we developed Deconvolution of Complex DNA Repair (DECODR). DECODR can detect indels formed from single or multi-guide CRISPR experiments without a limit on indel size. The software is accurate in determining the identities and positions of inserted and deleted bases in DNA extracts from both clonally expanded and bulk cell populations. The accurate identification and output of any potential indel allows for DECODR analysis to be executed in experiments utilizing potentially any configuration of donor DNA sequences, CRISPR-Cas, and endogenous DNA repair pathways.
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spelling pubmed-78984062021-02-22 Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data Bloh, Kevin Kanchana, Rohan Bialk, Pawel Banas, Kelly Zhang, Zugui Yoo, Byung-Chun Kmiec, Eric B. CRISPR J Research Articles During CRISPR-directed gene editing, multiple gene repair mechanisms interact to produce a wide and largely unpredictable variety of sequence changes across an edited population of cells. Shortcomings inherent to previously available proposal-based insertion and deletion (indel) analysis software necessitated the development of a more comprehensive tool that could detect a larger range and variety of indels while maintaining the ease of use of tools currently available. To that end, we developed Deconvolution of Complex DNA Repair (DECODR). DECODR can detect indels formed from single or multi-guide CRISPR experiments without a limit on indel size. The software is accurate in determining the identities and positions of inserted and deleted bases in DNA extracts from both clonally expanded and bulk cell populations. The accurate identification and output of any potential indel allows for DECODR analysis to be executed in experiments utilizing potentially any configuration of donor DNA sequences, CRISPR-Cas, and endogenous DNA repair pathways. Mary Ann Liebert, Inc., publishers 2021-02-01 2021-02-19 /pmc/articles/PMC7898406/ /pubmed/33571043 http://dx.doi.org/10.1089/crispr.2020.0022 Text en © Kevin Bloh, et al. 2021; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Bloh, Kevin
Kanchana, Rohan
Bialk, Pawel
Banas, Kelly
Zhang, Zugui
Yoo, Byung-Chun
Kmiec, Eric B.
Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title_full Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title_fullStr Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title_full_unstemmed Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title_short Deconvolution of Complex DNA Repair (DECODR): Establishing a Novel Deconvolution Algorithm for Comprehensive Analysis of CRISPR-Edited Sanger Sequencing Data
title_sort deconvolution of complex dna repair (decodr): establishing a novel deconvolution algorithm for comprehensive analysis of crispr-edited sanger sequencing data
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7898406/
https://www.ncbi.nlm.nih.gov/pubmed/33571043
http://dx.doi.org/10.1089/crispr.2020.0022
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