The clustered regularly interspaced short palindromic repeats (CRISPR) system is one of the benchmarks for gene editing. Its successful execution depends on its components. While the CRISPR-associated proteins, such as Cas9, are tasked with cutting a desired sequence, the single guide RNA (sgRNA) directs Cas9 to that sequence. This article explores the structure and importance of sgRNA and discusses the best design practices that maximize CRISPR-Cas9 efficiency.
What is sgRNA and its role in CRISPR-Cas9?
Understanding the structure of sgRNA
A sgRNA is a single-stranded guided RNA containing a 20 nucleotides-long CRISPR RNA (crRNA) that is complementary to the target region and a trans-activating crRNA (tracrRNA) sequence, which facilitates the binding between the Cas9 and crRNA. While crRNA and tracRNA are found separately in nature, the two sequences are fused by a linker loop during sgRNA design.¹
How does sgRNA guide Cas9 to the target sequence?
The tracRNA portion of sgRNA interacts with Cas9, inducing a conformational change that enhances DNA binding capability. As the complex moves along the DNA, it searches for a protospacer adjacent motif (PAM) downstream of the target region. Following this, the crRNA initiates base pairing with the complementary DNA strand. The Cas9 stabilizes the interaction and cleaves the complementary and non-complementary strands of approximately three nucleotides upstream of PAM, generating a double-stranded break (DSB).
The importance of sgRNA in genome editing
sgRNA is integral to the chain of events leading to the DSB and the subsequent gene repair that either introduces indel mutations for gene knockout or homology-directed repair for knock-in. Thus, sgRNA ensures the CRISPR-Cas system mediates the intended genomic and functional changes.
How to design effective sgRNA CRISPR sequences?
Key considerations in designing CRISPR sgRNA sequences
Besides the complementarity of the sgRNA sequence, several factors must be considered when designing sgRNA.
Firstly, the target sequence length must be optimal. 17-23 is the ideal range for the number of crRNA nucleotides, as longer sequences may lead to off-target editing, and shorter sequences compromise on specificity.
The location of the target sequence is another concern. A prerequisite for successful cleavage is the presence of a 2-6 bp long PAM on the non-complementary DNA strand downstream of the target site. For CRISPR systems using Cas9, the PAM sequence is 5′-NGG-3′, where N can be any nucleotide, although different Cas enzymes require different PAM sequences. It is also important to note that this sequence is not part of the target and must not be included in the sgRNA design.
One must also consider the percentage of guanine (G) and cytosine (C) in the crRNA, also known as the GC content. These bases are significant because they make more stable bonds with their complementary bases than adenine-thymine pairs (AT). The GC content should be high enough, although excessive GC content can cause sgRNA rigidity, Cas9 misfolding, and off-target effects. The optimum range is between 40% and 60%.²
Common pitfalls in CRISPR sgRNA design
- Limitation of the design to available PAM sequences
- Suboptimal GC content, which disrupts Cas9 activation and binding
- sgRNA homology with multiple genomic sites, which increases the likelihood of unintended edits
- Designing a sgRNA that will result in complete functional loss of the encoded protein
- Insufficient sgRNA expression levels
What are the factors affecting sgRNA efficiency?
Influence of sgRNA sequence on editing efficiency
The sgRNA sequence content is particularly relevant because it affects the potency of the CRISPR-Cas binding. While the GC content needs to be high enough to facilitate stable target binding, consecutive nucleotides such as poly-sequences (e.g., GGGGG…) can cause sgRNA misfolding and reduce efficiency.³
In addition, sgRNA sequence mismatches can diminish efficiency. Specifically, mismatches in the PAM-proximal region ~10-12 nucleotides upstream of PAM can severely impact binding. Furthermore, mismatches in the PAM-distal region near the sgRNA 5’ could interfere with the cleavage activity of Cas9.⁴
Off-target effects and their impact on CRISPR experiments
Faulty sgRNA design leads to off-target interactions with severe implications on CRISPR experiments.
- In disease research, off-target editing causes false and unexpected phenotypes, which may lead to the misinterpretation of the gene function in knockout experiments.
- In gene therapies, unintended edits can alter the genome and give rise to adverse effects.
- In genomic engineering, off-target mutations may lead to heterogeneity in clonal cell lines and obstruct reproducibility in protein production.
How can we optimize sgRNA design to maximize activity?
Strategies for improving sgRNA expression levels
One commonly used method in sgRNA design is through plasmid-expressed sgRNA, where the sgRNA sequence is transduced into cells as a part of a plasmid vector and is transcribed by the host cell into the sgRNA. Strategies for increasing sgRNA expression levels are as follows:
- Endogenous U6 promoters generate high transcription levels with correct sgRNA length.⁵
- Optimizing the sgRNA scaffold sequences, e.g., by shortening sequences that inhibit sgRNA transcription, such as TTTT in the PAM-proximal region.⁶
Rational design approaches for high editing efficiency
Modifications to the sgRNA structure can enhance editing efficiency. Some examples include:
- Addition of a hairpin structure to the sgRNA to prevent misfolding at difficult-to-edit DNA sites.⁷
- Chemically modifying the sgRNA to bind small molecules that can recognize mismatch pairs and modulate Cas9 activity to prevent off-target editing.⁸
Using synthetic sgRNA for enhanced performance
sgRNA can be synthesized in the laboratory by covalently linking ribonucleotides stepwise. The advantage of this method is the ability to modify the final sequence chemically. These modifications can significantly improve CRISPR-Cas performance by protecting the sgRNA from innate immune responses and exonucleases, mitigating the risk of degradation.⁹
How to evaluate the performance of sgRNA in editing systems?
CRISPR-Cas experiments should not proceed without a comprehensive sgRNA assessment.
Metrics for assessing sgRNA efficiency
Key metrics include:
- Indel Frequency: The rate of insertions or deletions at the target site.
- On-target cleavage efficiency: The amount of cleaved DNA at the target site
- Overall editing efficiency: The fraction of cells harboring the targeted mutation
Experiments or assays that test sgRNA performance
These metrics can be quantified using Sanger sequencing, next-generation sequencing or quantitative PCR. Furthermore, fluorescent reporter assays can be used to monitor and confirm editing efficiency.
Data analysis methods for CRISPR-Cas9 experiments
Advancements in machine learning and bioinformatics can streamline sgRNA design and assessment. Many computational tools have emerged, analyzing sequence data and employing deep learning algorithms to predict on-target and off-target scores and the resulting changes in gene expression.¹⁰'¹¹
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FAQs
How does sgRNA guide the CRISPR-Cas9 system to the target DNA?
The crRNA portion of sgRNA is complementary to the target DNA. It forms a complex with Cas9 and recognizes its target sequence via base pairing. Once bound, Cas9 introduces a double-strand break (DSB) at the target site, initiating genome editing.
How do different types of Cas proteins affect sgRNA design and its application?
Different Cas proteins recognize different PAM sequences and vary in size, specificity and function. For example, Cas9 requires an NGG PAM, while Cas12a recognizes a TTTV PAM (where V can be either A, G, or C) to navigate its sgRNA.12 Additionally, Cas9 variants like Cas9-HF1 enhance specificity, reducing off-target effects.13 Overall, using different Cas proteins broadens the scope of targetable genes.
How can sgRNA be delivered into cells for CRISPR applications?
sgRNA can be delivered via plasmids, ribonucleoproteins (RNPs) or viral vectors (AAV, lentivirus). RNP delivery ensures rapid editing with minimal off-target effects, while viral methods provide stable expression for long-term studies.
How is sgRNA used in therapeutic applications, such as in vivo gene editing?
In therapeutic settings, sgRNA is used for targeted gene correction or disruption. Delivery methods like lipid nanoparticles (LNPs) or AAV vectors enable precise in vivo editing for treating genetic diseases.
References
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- Liu X, Homma A, Sayadi J, Yang S, Ohashi J, Takumi T. Sequence features associated with the cleavage efficiency of CRISPR/Cas9 system. Sci Rep 2016;6(1):19675.
- Jung WJ, Park S-J, Cha S, Kim K. Factors affecting the cleavage efficiency of the CRISPR-Cas9 system. Anim Cells Sys 2024;28(1):75-83.
- Manghwar H, Li B, Ding X, Hussain A, Lindsey K, Zhang X, et al. CRISPR/Cas systems in genome editing: methodologies and tools for sgRNA design, off‐target evaluation, and strategies to mitigate off‐target effects. Adv Sci 2020;7(6):1902312.
- Wang C, Rollins JA. Efficient genome editing using endogenous U6 snRNA promoter-driven CRISPR/Cas9 sgRNA in Sclerotinia sclerotiorum. Fungal Genet Biol 2021;154:103598.
- Chey YC, Gierus L, Lushington C, Arudkumar JC, Geiger AB, Staker LG, et al. Optimal SpCas9-and SaCas9-mediated gene editing by enhancing gRNA transcript levels through scaffold poly-T tract reduction. BMC Genomics 2025;26:138.
- Riesenberg S, Helmbrecht N, Kanis P, Maricic T, Pääbo S. Improved gRNA secondary structures allow editing of target sites resistant to CRISPR-Cas9 cleavage. Nat Comm 2022;13(1):489.
- Liu X, Xiong W, Qi Q, Zhang Y, Ji H, Cui S, et al. Rational guide RNA engineering for small-molecule control of CRISPR/Cas9 and gene editing. Nucleic Acids Res 2022;50(8):4769-4783.
- Wang L, Han H. Strategies for improving the genome-editing efficiency of class 2 CRISPR/Cas system. Heliyon 2024;10(19).
- Cohen S, Bergman S, Lynn N, Tuller T. A tool for CRISPR-Cas9 sgRNA evaluation based on computational models of gene expression. Genome Med 2024;16(1):152.
- Ding S, Zheng J, Jia C. DeepMEns: an ensemble model for predicting sgRNA on-target activity based on multiple features. Brief Funct Genomics 2025;24:elae043.
- Zhang L, Zuris JA, Viswanathan R, Edelstein JN, Turk R, Thommandru B, et al. AsCas12a ultra nuclease facilitates the rapid generation of therapeutic cell medicines. Nat Commun 2021;12(1):3908.
- Bak SY, Jung Y, Park J, Sung K, Jang H-K, Bae S, et al. Quantitative assessment of engineered Cas9 variants for target specificity enhancement by single-molecule reaction pathway analysis. Nucleic Acids Res 2021;49(19):11312-11322.
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