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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mary Ann Liebert, Inc., publishers
2021
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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. |
format | Online Article Text |
id | pubmed-7898406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Mary Ann Liebert, Inc., publishers |
record_format | MEDLINE/PubMed |
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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