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Abstract The past decade has witnessed a rapid evolution in identifying more versatile clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) nucleases and their functional variants, as well as in developing precise CRISPR/Cas-derived genome editors. The programmable and robust features of the genome editors provide an effective RNA-guided platform for fundamental life science research and subsequent applications in diverse scenarios, including biomedical innovation and targeted crop improvement. One of the most essential principles is to guide alterations in genomic sequences or genes in the intended manner without undesired off-target impacts, which strongly depends on the efficiency and specificity of single guide RNA (sgRNA)-directed recognition of targeted DNA sequences. Recent advances in empirical scoring algorithms and machine learning models have facilitated sgRNA design and off-target prediction. In this review, we first briefly introduce the different features of CRISPR/Cas tools that should be taken into consideration to achieve specific purposes. Secondly, we focus on the computer-assisted tools and resources that are widely used in designing sgRNAs and analyzing CRISPR/Cas-induced on- and off-target mutations. Thirdly, we provide insights into the limitations of available computational tools that would help researchers of this field for further optimization. Lastly, we suggest a simple but effective workflow for choosing and applying web-based resources and tools for CRISPR/Cas genome editing.
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This content will become publicly available on January 1, 2026
Navigating Computational Resources for the CRISPR Classroom
What You Will Learn in This Chapter In this chapter, instructors will develop foundational knowledge about how to select and use computational tools to teach CRISPR-Cas technologies. Broadly speaking, CRISPR-Cas is a sequence-based technology. Computational resources provide a platform for managing and interacting with these sequences. With appropriate instructional design, computational tools are a valuable complement to lessons about CRISPR-Cas technologies and are essential support tools for CRISPR-Cas experiments. With an ever-growing suite of computational tools available, in this chapter, instructors will learn to navigate the landscape of these tools to select the most appropriate tools for their classroom or laboratory needs. Instructors will learn to identify when computational resources are appropriate for use in their classroom (and when they are not appropriate), then how to select the most appropriate tools for their unique needs. Additionally, we introduce instructors to best practices in instructional design for using CRISPR-Cas computational tools in the classroom. Throughout, instructors will learn both the rationale and principle behind selection so they can evaluate tools discussed in this chapter and new ones as they become available.
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- Award ID(s):
- 2310684
- PAR ID:
- 10586842
- Publisher / Repository:
- Springer Nature Switzerland
- Date Published:
- Page Range / eLocation ID:
- 163 to 189
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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