Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
Summary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting...
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doaj-8930b2f12fd84f7187b4303a1fcd68612020-11-25T03:12:41ZengElsevierCell Reports2211-12472018-02-012261413142310.1016/j.celrep.2018.01.045Hybridization Kinetics Explains CRISPR-Cas Off-Targeting RulesMisha Klein0Behrouz Eslami-Mossallam1Dylan Gonzalez Arroyo2Martin Depken3Kavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the Netherlands; Corresponding authorSummary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting is often minimized by choosing especially high-specificity guide sequences, based on algorithms that codify empirically determined off-targeting rules. A lack of mechanistic understanding of these rules has so far necessitated their ad hoc implementation, likely contributing to the limited precision of present algorithms. To understand the targeting rules, we kinetically model the physics of guide-target hybrid formation. Using only four parameters, our model elucidates the kinetic origin of the experimentally observed off-targeting rules, thereby rationalizing the results from both binding and cleavage assays. We favorably compare our model to published data from CRISPR-Cas9, CRISPR-Cpf1, CRISPR-Cascade, as well as the human Argonaute 2 system.http://www.sciencedirect.com/science/article/pii/S2211124718300779CRISPRCas9Cpf1RNA guided nucleasekinetic modelingoff-target prediction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Misha Klein Behrouz Eslami-Mossallam Dylan Gonzalez Arroyo Martin Depken |
spellingShingle |
Misha Klein Behrouz Eslami-Mossallam Dylan Gonzalez Arroyo Martin Depken Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules Cell Reports CRISPR Cas9 Cpf1 RNA guided nuclease kinetic modeling off-target prediction |
author_facet |
Misha Klein Behrouz Eslami-Mossallam Dylan Gonzalez Arroyo Martin Depken |
author_sort |
Misha Klein |
title |
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules |
title_short |
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules |
title_full |
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules |
title_fullStr |
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules |
title_full_unstemmed |
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules |
title_sort |
hybridization kinetics explains crispr-cas off-targeting rules |
publisher |
Elsevier |
series |
Cell Reports |
issn |
2211-1247 |
publishDate |
2018-02-01 |
description |
Summary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting is often minimized by choosing especially high-specificity guide sequences, based on algorithms that codify empirically determined off-targeting rules. A lack of mechanistic understanding of these rules has so far necessitated their ad hoc implementation, likely contributing to the limited precision of present algorithms. To understand the targeting rules, we kinetically model the physics of guide-target hybrid formation. Using only four parameters, our model elucidates the kinetic origin of the experimentally observed off-targeting rules, thereby rationalizing the results from both binding and cleavage assays. We favorably compare our model to published data from CRISPR-Cas9, CRISPR-Cpf1, CRISPR-Cascade, as well as the human Argonaute 2 system. |
topic |
CRISPR Cas9 Cpf1 RNA guided nuclease kinetic modeling off-target prediction |
url |
http://www.sciencedirect.com/science/article/pii/S2211124718300779 |
work_keys_str_mv |
AT mishaklein hybridizationkineticsexplainscrisprcasofftargetingrules AT behrouzeslamimossallam hybridizationkineticsexplainscrisprcasofftargetingrules AT dylangonzalezarroyo hybridizationkineticsexplainscrisprcasofftargetingrules AT martindepken hybridizationkineticsexplainscrisprcasofftargetingrules |
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1724649094897467392 |