大规模数据集可预测原发性 T 细胞经 CRISPR-Cas9 编辑后的修复情况。
Large dataset enables prediction of repair after CRISPR-Cas9 editing in primary T cells.
机构信息
Chan-Zuckerberg Biohub, San Francisco, CA, USA.
Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
出版信息
Nat Biotechnol. 2019 Sep;37(9):1034-1037. doi: 10.1038/s41587-019-0203-2. Epub 2019 Jul 29.
Abstract
Understanding of repair outcomes after Cas9-induced DNA cleavage is still limited, especially in primary human cells. We sequence repair outcomes at 1,656 on-target genomic sites in primary human T cells and use these data to train a machine learning model, which we have called CRISPR Repair Outcome (SPROUT). SPROUT accurately predicts the length, probability and sequence of nucleotide insertions and deletions, and will facilitate design of SpCas9 guide RNAs in therapeutically important primary human cells.
摘要
对 Cas9 诱导的 DNA 切割后的修复结果的理解仍然有限，特别是在原代人细胞中。我们在原代人 T 细胞中的 1656 个靶标基因组位点上对修复结果进行测序，并使用这些数据来训练机器学习模型，我们称之为 CRISPR 修复结果（SPROUT）。SPROUT 可准确预测核苷酸插入和缺失的长度、概率和序列，并将有助于设计在治疗上重要的原代人细胞中的 SpCas9 向导 RNA。
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