Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved..
The increasing emergence of Cas9 variants has attracted broad interest, as these variants were designed to expand CRISPR applications. New Cas9 variants typically feature higher editing efficiency, improved editing specificity, or alternative PAM sequences. To select Cas9 variants and gRNAs for high-fidelity and efficient genome editing, it is crucial to systematically quantify the editing performances of gRNAs and develop prediction models based on high-quality datasets. Using synthetic gRNA-target paired libraries and next-generation sequencing, we compared the activity and specificity of gRNAs of four SpCas9 variants. The nucleotide composition in the PAM-distal region had more influence on the editing efficiency of HiFi Cas9 and LZ3 Cas9. We further developed machine learning models to predict the gRNA efficiency and specificity for the four Cas9 variants. To aid users from broad research areas, the machine learning models for the predictions of gRNA editing efficiency within human genome sites are available on our website.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:43 |
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| Enthalten in: |
Cell reports - 43(2024), 2 vom: 27. Feb., Seite 113765 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Jianbo [VerfasserIn] |
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| Links: |
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| Themen: |
CP: Molecular biology |
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| Anmerkungen: |
Date Completed 04.03.2024 Date Revised 04.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.celrep.2024.113765 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
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| 520 | |a Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a The increasing emergence of Cas9 variants has attracted broad interest, as these variants were designed to expand CRISPR applications. New Cas9 variants typically feature higher editing efficiency, improved editing specificity, or alternative PAM sequences. To select Cas9 variants and gRNAs for high-fidelity and efficient genome editing, it is crucial to systematically quantify the editing performances of gRNAs and develop prediction models based on high-quality datasets. Using synthetic gRNA-target paired libraries and next-generation sequencing, we compared the activity and specificity of gRNAs of four SpCas9 variants. The nucleotide composition in the PAM-distal region had more influence on the editing efficiency of HiFi Cas9 and LZ3 Cas9. We further developed machine learning models to predict the gRNA efficiency and specificity for the four Cas9 variants. To aid users from broad research areas, the machine learning models for the predictions of gRNA editing efficiency within human genome sites are available on our website | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a CP: Molecular biology | |
| 650 | 4 | |a Cas9 variants | |
| 650 | 4 | |a gene editing | |
| 650 | 4 | |a machine learning | |
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| 700 | 1 | |a Wu, Panfeng |e verfasserin |4 aut | |
| 700 | 1 | |a Cao, Zhoutao |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Guanlan |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Zhike |e verfasserin |4 aut | |
| 700 | 1 | |a Yan, Jianfeng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Heng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Yangfan |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Rong |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Lijia |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Mengcheng |e verfasserin |4 aut | |
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