Machine learning based CRISPR gRNA design for therapeutic exon skipping.
Machine learning based CRISPR gRNA design for therapeutic exon skipping.
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DOI：
10.1371/journal.pcbi.1008605
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发表时间：
2021-01
影响因子：
4.3
通讯作者：
Gifford DK
中科院分区：
文献类型：
--
作者：
Louie W;Shen MW;Tahiry Z;Zhang S;Worstell D;Cassa CA;Sherwood RI;Gifford DK
通过诱导跳过有害外显子来恢复基因功能已被证明对治疗遗传疾病有效。然而，许多临床上成功的外显子跳读疗法是需要频繁给药的基于阿托伐他汀的短暂治疗。基于CRISPR-Cas9的基因组编辑导致外显子跳读是一种有前途的治疗方式，可以永久缓解遗传疾病。我们表明，机器学习可以选择Cas9指导RNA，这些RNA会破坏剪接受体并导致靶向外显子的跳跃。我们通过实验测量了小鼠胚胎干细胞中由1，063个指导RNA靶向的791个剪接序列的多样化基因组整合文库的外显子跳跃频率。我们发现我们的方法SkipGuide能够以0.68（50%阈值预测外显子跳跃频率）和0.93（70%阈值预测外显子跳跃频率）的精度识别有效的指导RNA。我们预期SkipGuide将可用于选择指导RNA候选物以评估CRISPR-Cas9介导的外显子跳跃疗法。基因治疗的一种形式是外显子跳跃，其中细胞被迫从突变转录物中排除有问题的外显子，使得所得蛋白质具有功能。最近的研究表明，CRISPR技术可以诱导治疗性外显子跳跃。通过使用特异性引导RNA，可以进行外显子的剪接受体序列的靶向破坏，这可以导致其跳跃。然而，外显子可以具有靶向其剪接受体的许多候选向导RNA，并且并非所有向导RNA都将导致足够水平的外显子跳跃。可以鉴定将导致外显子被跳过的指导RNA的预测方法将有助于指导治疗开发工作。我们提出了SkipGuide，这是一种机器学习方法，用于预测由靶向其剪接受体区域的指导RNA引起的外显子跳跃水平。为了开发和评估SkipGuide，我们实验性地测量了小鼠细胞系中由多个向导RNA靶向的一组不同外显子的跳跃水平。我们证明SkipGuide可以准确地识别导致高水平外显子跳跃的指导RNA。
Restoring gene function by the induced skipping of deleterious exons has been shown to be effective for treating genetic disorders. However, many of the clinically successful therapies for exon skipping are transient oligonucleotide-based treatments that require frequent dosing. CRISPR-Cas9 based genome editing that causes exon skipping is a promising therapeutic modality that may offer permanent alleviation of genetic disease. We show that machine learning can select Cas9 guide RNAs that disrupt splice acceptors and cause the skipping of targeted exons. We experimentally measured the exon skipping frequencies of a diverse genome-integrated library of 791 splice sequences targeted by 1,063 guide RNAs in mouse embryonic stem cells. We found that our method, SkipGuide, is able to identify effective guide RNAs with a precision of 0.68 (50% threshold predicted exon skipping frequency) and 0.93 (70% threshold predicted exon skipping frequency). We anticipate that SkipGuide will be useful for selecting guide RNA candidates for evaluation of CRISPR-Cas9-mediated exon skipping therapy. One form of genetic therapy is exon skipping, where a cell is forced to exclude problematic exons from a mutant transcript such that the resultant protein is functional. Recent studies show that CRISPR technology can induce therapeutic exon skipping. By using a specific guide RNA, targeted disruption of an exon’s splice acceptor sequence can be performed, which can result in its skipping. However, an exon may have many candidate guide RNAs that target its splice acceptor, and not all guide RNAs will lead to a sufficient level of exon skipping. A predictive method that can identify a guide RNA that will cause an exon to be skipped would be useful for guiding therapeutic development efforts. We present SkipGuide, a machine learning method for predicting the exon skipping level caused by a guide RNA that targets its splice acceptor region. To develop and evaluate SkipGuide, we experimentally measured the skipping levels of a diverse set of exons targeted by multiple guide RNAs in a mouse cell line. We demonstrate that SkipGuide can accurately identify the guide RNAs that lead to high levels of exon skipping.
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影响因子：
5.8
作者：
Bretschneider, Hannes;Gandhi, Shreshth;Frey, Brendan J.
通讯作者：
Frey, Brendan J.
影响因子：
48
作者：
Mali, Prashant;Esvelt, Kevin M.;Church, George M.
通讯作者：
Church, George M.
影响因子：
46.9
作者：
Doench JG;Fusi N;Sullender M;Hegde M;Vaimberg EW;Donovan KF;Smith I;Tothova Z;Wilen C;Orchard R;Virgin HW;Listgarten J;Root DE
通讯作者：
Root DE
影响因子：
48
作者：
Katz, Yarden;Wang, Eric T.;Airoldi, Edoardo M.;Burge, Christopher B.
通讯作者：
Burge, Christopher B.
Biopython：用于计算分子生物学和生物信息学的免费 Python 工具。
DOI：
10.1093/bioinformatics/btp163
发表时间：
2009-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者：
de Hoon MJ