SAPTA: a new design tool for improving TALE nuclease activity.

SAPTA: a new design tool for improving TALE nuclease activity.
复制标题

DOI:
10.1093/nar/gkt1363
复制
发表时间:
2014-04
影响因子:
14.9
通讯作者:
Bao G
Bao G
中科院分区:
生物学2区
文献类型:
--
作者:
Lin Y;Fine EJ;Zheng Z;Antico CJ;Voit RA;Porteus MH;Cradick TJ;Bao G

文献摘要

参考文献

被引文献

相似文献

类转录激活因子效应核酸酶 (TALEN) 已成为基因组编辑的强大工具,因为其 DNA 结合域的氨基酸序列与 TALEN 核苷酸靶标之间的连接代码非常简单。虽然最初的 TALEN 设计指南非常有用,但需要开发用户友好的工具来定义最佳的 TALEN 设计以实现稳健的基因组编辑。在这里,我们评估了现有指南,并根据测试的 205 个 TALEN 制定了新的 TALEN 设计指南,并建立了预测 TALEN 活性的评分算法(SAPTA)作为新的在线设计工具。对于任何感兴趣的输入基因,SAPTA 都会给出潜在 TALEN 靶位点的排名列表,有助于根据预测的活性选择最佳 TALEN 对。基于 SAPTA 的 TALEN 设计将平均细胞内 TALEN 单体活性提高了 3 倍以上,并且含有重复变量二残基 NK 的 TALEN 的平均内源基因修饰频率为 39%,该重复变量二残基 NK 有利于特异性而不是活性。预计 SAPTA 将成为一种有用且灵活的工具,用于为基因组编辑应用设计高活性 TALEN。 SAPTA 可以通过网站 http://baolab.bme.gatech.edu/Research/BioinformaticTools/TAL_targeter.html 访问。
Transcription activator-like effector nucleases (TALENs) have become a powerful tool for genome editing due to the simple code linking the amino acid sequences of their DNA-binding domains to TALEN nucleotide targets. While the initial TALEN-design guidelines are very useful, user-friendly tools defining optimal TALEN designs for robust genome editing need to be developed. Here we evaluated existing guidelines and developed new design guidelines for TALENs based on 205 TALENs tested, and established the scoring algorithm for predicting TALEN activity (SAPTA) as a new online design tool. For any input gene of interest, SAPTA gives a ranked list of potential TALEN target sites, facilitating the selection of optimal TALEN pairs based on predicted activity. SAPTA-based TALEN designs increased the average intracellular TALEN monomer activity by >3-fold, and resulted in an average endogenous gene-modification frequency of 39% for TALENs containing the repeat variable di-residue NK that favors specificity rather than activity. It is expected that SAPTA will become a useful and flexible tool for designing highly active TALENs for genome-editing applications. SAPTA can be accessed via the website at http://baolab.bme.gatech.edu/Research/BioinformaticTools/TAL_targeter.html.
DOI: 10.1093/nar/gkq704
发表时间: 2011-01
影响因子: 14.9
作者:
Li T;Huang S;Jiang WZ;Wright D;Spalding MH;Weeks DP;Yang B
通讯作者: Yang B
DOI: 10.1038/nbt.2170
发表时间: 2012-05
影响因子: 46.9
作者:
通讯作者: --
DOI: 10.1073/pnas.1019533108
发表时间: 2011-02-08
影响因子: 11.1
作者:
Mahfouz, Magdy M.;Li, Lixin;Zhu, Jian-Kang
通讯作者: Zhu, Jian-Kang
DOI: 10.1126/science.1178811
发表时间: 2009-12-11
期刊: SCIENCE
影响因子: 56.9
作者:
Boch, Jens;Scholze, Heidi;Bonas, Ulla
通讯作者: Bonas, Ulla
DOI: 10.1038/nbt.2517
发表时间: 2013-03-01
影响因子: 46.9
作者:
Kim, Yongsub;Kweon, Jiyeon;Kim, Jin-Soo
通讯作者: Kim, Jin-Soo