Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts. Currently, CRISPR/Cas9 is a promising RNA-guided genome editing technology, which consists of a Cas9 nuclease and a single-guide RNA (sgRNA). Considering the significant differences between lncRNAs and protein-coding genes, it is necessary to investigate sgRNA-designing method optimized for lncRNAs.
Researchers from Xishuangbanna Tropical Botanical Garden (XTBG) studied the application of CRISPR/Cas9 technology in gene editing, especially for sgRNA design against long noncoding RNA (lncRNA). They first evaluated the performance of a series of known sgRNA design tools on coding and noncoding datasets and analyzed the different performances in terms of sgRNA specificity to lncRNA, including nucleic acid sequence, genomic location, and editing mechanism preference.
The researchers also introduced a machine learning algorithm CRISPRlnc based on support vector machines that aims to simulate the CRISPR knockout (CRISPRko) and CRISPR inhibition (CRISPRi) mechanisms to predict the target’s targeting activity. CRISPRlnc combines paired-sgRNA design and off-target analysis to achieve one-stop design of CRISPR/Cas9 sgRNA for noncoding genes.
By comparing the performance of CRISPRlnc with several existing methods on multiple datasets, the researchers conclude that CRISPRlnc performs much better than existing methods for lncRNA-specific sgRNA design, both for CRISPRko and CRISPRi mechanisms.
"We proposed a new machine learning method, CRISPRlnc, for designing lncRNA-specific sgRNA in CRISPR/Cas9 system. Performance comparison shows that CRISPRlnc is far superior to existing methods for lncRNA-specific sgRNA design in both CRISPRko and CRISPRi mechanisms,” said LIU Changning of XTBG.
To facilitate the use of CRISPRlnc, the researchers developed a web server (http://predict.crisprlnc.cc) and made it available for download on GitHub. For the convenience of users, they integrate services such as paired sgRNA design and off-target risk analysis into the implementation of the CRISPRlnc tool, and provide a variety of information such as on-target validity, off-target risk and genomic location to help further select sgRNAs.
The study was partly supported by the Strategic Priority Research Program of the Chinese Academy of Sciences and the National Natural Science Foundation of China. Results were published in Briefings in Bioinformatcis.
Contact
LIU Changning Ph.D Principal Investigator
Key Laboratory of Tropical Plant Resources and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun 666303, Yunnan, China
E-mail: liuchangning@xtbg.ac.cn
First published: 29 February 2024
