| 引用本文: | 孙瑜,蔡小宁,陈德富,高山.NgAgo-gDNA基因组编辑系统的成功及启示[J].生物信息学,2016,14(3):167-172. |
| SUN Yu,CAI Xiaoning,CHEN Defu,GAO Shan.NgAgo-gDNA will stimulate the development of genome editing systems[J].Chinese Journal of Bioinformatics,2016,14(3):167-172. |
|
| 摘要: |
| 韩春雨等发明的DNA指导的基因组编辑系统NgAgo-gDNA,比原有的RNA指导的基因组编辑系统CRISPR-Cas9在靶向特异性(防脱靶),反应可控性和基因组编辑范围等方面都有显著的改进。NgAgo-gDNA不是一项简单的改进,是一项具有开拓性的工作,沿着这条研究路线,可以继续开发出更先进的基因组编辑系统。该研究充分体现了生物信息学,特别是大数据挖掘在未来生命科学研究中的重要地位。本文仅从生物信息学角度,谈谈这项研究的价值、意义以及可能引发的相关研究方向。 |
| 关键词: 基因组编辑 NgAgo CRISPR Cas9 RNAi 全长转录组 PacBio |
| DOI：10.3969/j.issn.1672-5565.2016.03.07 |
| 分类号:Q786 |
| 文献标识码:A |
| 基金项目:中央高校基本科研业务费(南开大学) |
|
| NgAgo-gDNA will stimulate the development of genome editing systems |
|
SUN Yu1,CAI Xiaoning2,CHEN Defu1,GAO Shan1
|
|
(1.College of Life Sciences,Nankai University,Tianjin 300071,China;2.Nanjing Xiaozhuang University,Nanjing 211171,China)
|
| Abstract: |
| A new genome editing system named NgAgo-gDNA was invented using 5 phosphorylated single-stranded guide DNA (gDNA) of 24 nucleotides and Natronobacterium gregoryi Argonaute (NgAgo). This system outperformed the RNA-guided genome editing system CRISPR-Cas9 on several features. The success of the NgAgo-gDNA project demonstrated the importance of bioinformatics in biological research and will stimulate the development of genome editing systems. The NgAgo-gDNA project was initiated from searching homologs of TtAgo and PfAgo, two other enzymes from the AGO protein family. The authors used the software PSI-BLAST against the NCBI NR database to retrieve homologous protein sequences. After further analysis and filtering, they found the NgAgo protein (GenBank: AFZ73749.1), which works at the temperature of 37 ℃. The key step in the NgAgo-gDNA project is to narrow down a great number of AGO homologous protein sequences to several candidates using bioinformatics methods for experimental validation of their functions. These bioinformatics methods were not explained in the published paper but could belong to the empirical methodology. An alternative but advanced methodology is to use machine learning algorithms (e.g. support vector machine or random forest) to modify AGO proteins which work at a temperature close to 37 ℃. The future studies can be conducted in several fields using bioinformatics methods. First, the structural information of the NgAgo protein can be used to reveal the mechanism of the DNA and protein interaction. The sequence with structure comparison between NgAgo and TtAgo & PfAgo or other AGO proteins will help understand their molecular functions. Second, using the sequence or structure similarities, more RNA-or DNA-binding proteins can be retrieved from the public databases to help design new genome editing systems. Third, since RNAi (RNA interference) uses AGO to cleave double stranded RNAs, the guide-target complexes of AGO proteins need be studied to reveal the common mechanisms and differences between genome editing and RNAi. Fourth, a great number of AGO genes from lower to higher organisms can be used to study the evolution of AGO and the coevolution between the viruses and the hosts. |
| Key words: Genome editing NgAgo CRISPR Cas9 RNAi Full-length transcriptome PacBio |
