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使用 MENdel 在基因治疗和功能基因组学的精确基因编辑应用中部署 MMEJ。

Deploying MMEJ using MENdel in precision gene editing applications for gene therapy and functional genomics.

机构信息

Dept. of Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, USA.

Program in Bioinformatics and Computational Biology, Iowa State University, Ames, IA, USA.

出版信息

Nucleic Acids Res. 2021 Jan 11;49(1):67-78. doi: 10.1093/nar/gkaa1156.

Abstract

Gene-editing experiments commonly elicit the error-prone non-homologous end joining for DNA double-strand break (DSB) repair. Microhomology-mediated end joining (MMEJ) can generate more predictable outcomes for functional genomic and somatic therapeutic applications. We compared three DSB repair prediction algorithms - MENTHU, inDelphi, and Lindel - in identifying MMEJ-repaired, homogeneous genotypes (PreMAs) in an independent dataset of 5,885 distinct Cas9-mediated mouse embryonic stem cell DSB repair events. MENTHU correctly identified 46% of all PreMAs available, a ∼2- and ∼60-fold sensitivity increase compared to inDelphi and Lindel, respectively. In contrast, only Lindel correctly predicted predominant single-base insertions. We report the new algorithm MENdel, a combination of MENTHU and Lindel, that achieves the most predictive coverage of homogeneous out-of-frame mutations in this large dataset. We then estimated the frequency of Cas9-targetable homogeneous frameshift-inducing DSBs in vertebrate coding regions for gene discovery using MENdel. 47 out of 54 genes (87%) contained at least one early frameshift-inducing DSB and 49 out of 54 (91%) did so when also considering Cas12a-mediated deletions. We suggest that the use of MENdel helps researchers use MMEJ at scale for reverse genetics screenings and with sufficient intra-gene density rates to be viable for nearly all loss-of-function based gene editing therapeutic applications.

摘要

基因编辑实验通常会引起易错的非同源末端连接,用于修复 DNA 双链断裂 (DSB)。微同源介导的末端连接 (MMEJ) 可以为功能基因组和体细胞治疗应用产生更可预测的结果。我们比较了三种 DSB 修复预测算法——MENTHU、inDelphi 和 Lindel——在独立的 5885 个不同 Cas9 介导的小鼠胚胎干细胞 DSB 修复事件数据集,识别 MMEJ 修复的同源基因型 (PreMAs)。MENTHU 正确识别了所有可用 PreMAs 的 46%,与 inDelphi 和 Lindel 相比,敏感性分别提高了约 2 倍和 60 倍。相比之下,只有 Lindel 正确预测了主要的单碱基插入。我们报告了新算法 MENdel,它是 MENTHU 和 Lindel 的组合,在这个大数据集中实现了同源移码突变的最具预测性的覆盖。然后,我们使用 MENdel 估计了脊椎动物编码区中 Cas9 靶向同源移码诱导 DSB 的频率,用于基因发现。54 个基因中的 47 个 (87%)至少含有一个早期移码诱导 DSB,而考虑到 Cas12a 介导的缺失,则有 49 个 (91%)。我们建议使用 MENdel 有助于研究人员在大规模反向遗传学筛选中使用 MMEJ,并具有足够的基因内密度率,几乎所有基于失活的基因编辑治疗应用都具有可行性。

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