Asadbeigi Adnan, Norouzi Milad, Vafaei Sadi Mohammad Sadegh, Saffari Mojtaba, Bakhtiarizadeh Mohammad Reza
Department of Medical Genetics, Cancer Institute, Faculty of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Front Bioeng Biotechnol. 2022 Aug 9;10:957131. doi: 10.3389/fbioe.2022.957131. eCollection 2022.
The efficiency of the CRISPR-Cas system is highly dependent on well-designed CRISPR RNA (crRNA). To facilitate the use of various types of CRISPR-Cas systems, there is a need for the development of computational tools to design crRNAs which cover different CRISPR-Cas systems with off-target analysis capability. Numerous crRNA design tools have been developed, but nearly all of them are dedicated to design crRNA for genome editing. Hence, we developed a tool matching the needs of both beginners and experts, named CaSilico, which was inspired by the limitations of the current crRNA design tools for designing crRNAs for Cas12, Cas13, and Cas14 CRISPR-Cas systems. This tool considers a comprehensive list of the principal rules that are not yet well described to design crRNA for these types. Using a list of important features such as mismatch tolerance rules, self-complementarity, GC content, frequency of cleaving base around the target site, target accessibility, and PFS (protospacer flanking site) or PAM (protospacer adjacent motif) requirement, CaSilico searches all potential crRNAs in a user-input sequence. Considering these features help users to rank all crRNAs for a sequence and make an informed decision about whether a crRNA is suited for an experiment or not. Our tool is sufficiently flexible to tune some key parameters governing the design of crRNA and identification of off-targets, which can lead to an increase in the chances of successful CRISPR-Cas experiments. CaSilico outperforms previous crRNA design tools in the following aspects: 1) supporting any reference genome/gene/transcriptome for which an FASTA file is available; 2) designing crRNAs that simultaneously target multiple sequences through conserved region detection among a set of sequences; 3) considering new CRISPR-Cas subtypes; and 4) reporting a list of different features for each candidate crRNA, which can help the user to select the best one. Given these capabilities, CaSilico addresses end-user concerns arising from the use of sophisticated bioinformatics algorithms and has a wide range of potential research applications in different areas, especially in the design of crRNA for pathogen diagnosis. CaSilico was successfully applied to design crRNAs for different genes in the SARS-CoV-2 genome, as some of the crRNAs have been experimentally tested in the previous studies.
CRISPR-Cas系统的效率高度依赖于精心设计的CRISPR RNA(crRNA)。为了便于使用各种类型的CRISPR-Cas系统,需要开发计算工具来设计crRNA,这些工具要涵盖不同的CRISPR-Cas系统并具备脱靶分析能力。已经开发了许多crRNA设计工具,但几乎所有工具都专门用于设计用于基因组编辑的crRNA。因此,我们开发了一种满足初学者和专家需求的工具,名为CaSilico,它的灵感来源于当前用于为Cas12、Cas13和Cas14 CRISPR-Cas系统设计crRNA的crRNA设计工具的局限性。该工具考虑了一系列尚未得到充分描述的主要规则,用于为这些类型设计crRNA。利用错配容忍规则、自我互补性、GC含量、靶位点周围切割碱基的频率、靶标可及性以及原间隔侧翼位点(PFS)或原间隔相邻基序(PAM)要求等重要特征列表,CaSilico在用户输入序列中搜索所有潜在的crRNA。考虑这些特征有助于用户对序列的所有crRNA进行排序,并就是否适合进行实验做出明智的决定。我们的工具具有足够的灵活性来调整一些控制crRNA设计和脱靶识别的关键参数,这可以增加CRISPR-Cas实验成功的机会。CaSilico在以下方面优于以前的crRNA设计工具:1)支持任何有FASTA文件可用的参考基因组/基因/转录组;2)通过一组序列中的保守区域检测设计同时靶向多个序列的crRNA;3)考虑新的CRISPR-Cas亚型;4)报告每个候选crRNA的不同特征列表,这可以帮助用户选择最佳的crRNA。鉴于这些功能,CaSilico解决了终端用户因使用复杂的生物信息学算法而产生的担忧,并在不同领域具有广泛的潜在研究应用,特别是在用于病原体诊断的crRNA设计方面。CaSilico已成功应用于为严重急性呼吸综合征冠状病毒2(SARS-CoV-2)基因组中的不同基因设计crRNA,因为其中一些crRNA在先前的研究中已经过实验测试。