Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA.
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nature. 2018 Nov;563(7733):646-651. doi: 10.1038/s41586-018-0686-x. Epub 2018 Nov 7.
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.
在 Cas9 切割之后,没有供体模板的 DNA 修复通常被认为是随机的、异质的,并且在基因破坏之外不切实际。在这里,我们表明无模板 Cas9 编辑是可预测的,并且能够精确地修复到预测的基因型,从而能够纠正人类相关疾病突变。我们构建了一个由 2000 个 Cas9 向导 RNA 与 DNA 靶标配对组成的文库,并在 InDelphi 中进行了训练,InDelphi 是一种机器学习模型,可高精度(r=0.87)预测五个人类和小鼠细胞系中 1 到 60 个碱基对缺失和 1 个碱基对插入的基因型和频率。InDelphi 预测,靶向人类基因组的 5-11%的 Cas9 向导 RNA 是“精确-50”,产生一个由大于或等于所有主要编辑产物的 50%组成的单一基因型。我们通过实验证实了 195 个人类疾病相关等位基因中的精确-50 插入和缺失,包括对 Hermansky-Pudlak 综合征和 Menkes 病患者来源原代成纤维细胞中致病性等位基因的校正,使其成为野生型基因型。这项研究建立了一种精确的、无模板基因组编辑方法。