Unknown

Dataset Information

0

Predictable and precise template-free CRISPR editing of pathogenic variants.


ABSTRACT: Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a predicted genotype, enabling correction of disease-associated mutations in humans. We constructed a library of 2,000 Cas9 guide RNAs paired with DNA target sites and trained inDelphi, a machine learning model that predicts genotypes and frequencies of 1- to 60-base-pair deletions and 1-base-pair insertions with high accuracy (r?=?0.87) in five human and mouse cell lines. inDelphi predicts that 5-11% of Cas9 guide RNAs targeting the human genome are 'precise-50', yielding a single genotype comprising greater than or equal to 50% of all major editing products. We experimentally confirmed precise-50 insertions and deletions in 195 human disease-relevant alleles, including correction in primary patient-derived fibroblasts of pathogenic alleles to wild-type genotype for Hermansky-Pudlak syndrome and Menkes disease. This study establishes an approach for precise, template-free genome editing.

SUBMITTER: Shen MW 

PROVIDER: S-EPMC6517069 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications


Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a predicted genotype, enabling correction of disease-associated mutations in humans. We constructed a library of 2,000 Cas9 guide RNAs paired with DNA target sites and trained inDelphi, a machine learning model that predicts genotypes and frequencies of 1  ...[more]

Similar Datasets

| S-EPMC7481536 | biostudies-literature
| S-EPMC6813315 | biostudies-literature
2018-07-26 | GSE113698 | GEO
| S-EPMC6007333 | biostudies-other
| S-EPMC4299274 | biostudies-other
| S-EPMC7844696 | biostudies-literature
| S-EPMC3706373 | biostudies-literature
| S-EPMC7946428 | biostudies-literature
| S-EPMC6974980 | biostudies-literature
| S-EPMC5785341 | biostudies-literature