An online bioinformatics tool predicts zinc finger and TALE nuclease off-target cleavage.
An online bioinformatics tool predicts zinc finger and TALE nuclease off-target cleavage.
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DOI：
10.1093/nar/gkt1326
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发表时间：
2014-04
影响因子：
14.9
通讯作者：
Bao G
中科院分区：
文献类型：
--
作者：
Fine EJ;Cradick TJ;Zhao CL;Lin Y;Bao G
尽管工程核酸酶可以有效地在期望的目标位点切割细胞内DNA，但主要的担忧仍然是可能在整个基因组中发生的潜在的“脱靶”切割。我们开发了一个在线工具：全基因组核酸酶脱靶位点预测报告（PROGNOS），有效地识别脱靶位点。预后的初始生物信息学算法通过预测先前确认的65个脱靶位点中的44个，并通过发现广泛研究的针对C-C趋化因子受体5型的锌指核酸酶（ZFNs）的新脱靶位点而得到验证。使用PROGNOS，我们快速地对新设计的转录激活子样效应核酸酶（含有Asn-Asn （NN）或Asn-Lys （NK）重复可变二残基（RVDs）和3指和4指ZFNs）的128个潜在脱靶位点进行了研究，并通过DNA测序验证了这些核酸酶的13个真正的脱靶位点。通过将核酸酶- dna相互作用的附加特征和新确认的脱靶位点纳入训练集，进一步改进了PROGNOS算法，这增加了在PROGNOS排名中发现的真正脱靶位点的百分比。通过在计算机上识别潜在的脱靶位点，PROGNOS允许选择更具体的靶位点，并帮助鉴定真正的脱靶位点，极大地促进了用于基因组编辑应用的工程核酸酶的设计。
Although engineered nucleases can efficiently cleave intracellular DNA at desired target sites, major concerns remain on potential ‘off-target’ cleavage that may occur throughout the genome. We developed an online tool: predicted report of genome-wide nuclease off-target sites (PROGNOS) that effectively identifies off-target sites. The initial bioinformatics algorithms in PROGNOS were validated by predicting 44 of 65 previously confirmed off-target sites, and by uncovering a new off-target site for the extensively studied zinc finger nucleases (ZFNs) targeting C-C chemokine receptor type 5. Using PROGNOS, we rapidly interrogated 128 potential off-target sites for newly designed transcription activator-like effector nucleases containing either Asn-Asn (NN) or Asn-Lys (NK) repeat variable di-residues (RVDs) and 3- and 4-finger ZFNs, and validated 13 bona fide off-target sites for these nucleases by DNA sequencing. The PROGNOS algorithms were further refined by incorporating additional features of nuclease–DNA interactions and the newly confirmed off-target sites into the training set, which increased the percentage of bona fide off-target sites found within the top PROGNOS rankings. By identifying potential off-target sites in silico, PROGNOS allows the selection of more specific target sites and aids the identification of bona fide off-target sites, significantly facilitating the design of engineered nucleases for genome editing applications.
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Tale-DNA相互作用的定量分析表明极性效应。
影响因子：
14.9
作者：
Meckler JF;Bhakta MS;Kim MS;Ovadia R;Habrian CH;Zykovich A;Yu A;Lockwood SH;Morbitzer R;Elsäesser J;Lahaye T;Segal DJ;Baldwin EP
通讯作者：
Baldwin EP
影响因子：
5.8
作者：
Grau, Jan;Boch, Jens;Posch, Stefan
通讯作者：
Posch, Stefan
影响因子：
14.9
作者：
Doyle EL;Booher NJ;Standage DS;Voytas DF;Brendel VP;Vandyk JK;Bogdanove AJ
通讯作者：
Bogdanove AJ
影响因子：
14.9
作者：
Cradick TJ;Fine EJ;Antico CJ;Bao G
通讯作者：
Bao G
用 TAL 效应器靶向 G：用 NN 和 NK 重复可变二残基构建的 TALEN 的活性比较
影响因子：
3.7
作者：
Christian ML;Demorest ZL;Starker CG;Osborn MJ;Nyquist MD;Zhang Y;Carlson DF;Bradley P;Bogdanove AJ;Voytas DF
通讯作者：
Voytas DF