The CRISPR system has revolutionized the field of genetic engineering. It allows scientist to alter genes in a simple way. The basic principle of CRISPR is based on cutting at a specific point the target DNA, using a nicase enzyme (Cas) which is guided by a fragment of RNA called guide (gRNA). This guide is responsible for directing the enzyme to the point where it should cut. However, choosing the appropriate CRISPR components could be challenging. In this post, concepts that should be taken into account when designing and selecting the most appropriate RNA guides are discussed.

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RNA guides are 20 nucleotides sequences, complementary to the target DNA sequence. The function of these oligonucleotides is to detect and bind their complementary sequence in the target DNA. The purpose of this action is to direct Cas to the desired cleavage site. In order to cut the DNA, Cas has to recognize a sequence called PAM (protospacer adjacent motifs), which is adjacent to the gRNA target sequence. This sequence consists of 3 nucleotides (5′-NGG-3′ in the case of Cas9). When the Recognition is completed, Cas9 cuts the target DNA between gRNA positions 17 and 18.

One of the biggest challenges for the CRISPR system is to be able to identify efficiently the desired cutting sites, avoiding cuts in locations different than the target, commonly called off-targets. Therefore, cut efficiency depends not only on the activity of the Cas enzyme, but also on the efficiency and specificity of the guides for the recognition of the target DNA.

The perfect RNA guide should bind highly efficiently and specifically to the target sequence, minimizing possible off-target effects. At first glance, it may seem easy, but to ensure the balance between efficiency and specificity, certain parameters must be considered when designing the guides.

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RNA Guide Design

gRNA sequence

gRNA Sequence

The technique commonly chosen for guide production is expression and cloning. Thus, the efficiency in the synthesis and subsequent transcription will affect the CRISPR activity. Furthermore, certain motifs within this sequence can cause interference.

  • Sequences beginning with 5′ AG might generate errors, due to heterogeneity in transcription using T7 polymerase.
  • Base repetition may also be a problem in the synthesis. AAAAA, CCCCC, GGGG and UUUU decrease the cutting efficiency.
    • The GGGG sequence, specifically, may entail lower CRISPR activity, due to the tendency to form secondary structures. These structures make binding difficult.
    • UUUU sequences might also interfere with transcription by terminating the RNA polymerase III activity as it finds this sequence.
  • The repetition of thymines (TT+Y, TT+YY) in 3′ is also a problem, and could generate a considerable decrease in cutting efficiency.
  • In the same 3′ position, the GCC motif likely affects the cleavage efficiency of Cas.

Sequence lenght

The recommended lenght is 20 nucleotides:

  • Shorter sequences, 17-18 nucleotides, are more specific, but less efficient.
  • Larger sequences, more than 20 nucleotides, are less effective.

Nucleotide composition

Nucleotide composition may generate gRNA functional differences:

  • A high number of Adenines at positions 9-16, may increase the affinity of Cas. However, if this part of the sequence is enriched in Uracil or Guanine, it likely generates a less functional gRNA.
  • 40-80% of GC is considered optimal. In general, increased activity is favored if there are:
    • GSs in positions 4-5
    • GCs in the 6 nucleotides next to the PAM sequence

Nucleotide specific position

There are critical specific positions to guarantee a high CRISPR system efficiency.

The end of the gRNA sequence (nucleotides 16-20), close to PAM sequence, is key for the proper functioning of Cas. This region is known as “seed sequence”.

  • At positions 19 and 20 (Last nucleotides), purine bases, G or A, are preferred. Whereas, a Cytosine is completely not recommended in the last position.
  • In positions 16 and 18 Cytosine is preferable, especially in position 18, which corresponds to the Cas cutting site. In this case, Guanine is not recommended for these positions.

Sctructural characteristics

It is relevant to consider the secondary structure of the gRNA, self-folding, and the nucleotide access, when guides are being design.

The most important structural nucleotide positions are 18-20 and 51-53. They are the end and the scaffold part of the guide. They are essential because of the secondary structure of the sgRNA. It consists of a loop, in which positions 18-20 line up to match positions 51-53. Therefore, the sequences must be complementary for pairing. If there is an incorrect pairing, the efficiency will decrease.

Target sequence considerations

Where the target sequence is located in the DNA should also be considered. It is known that the gRNA activity decreases when the target sequence position is close to the C-terminal end. The probability of protein expression modification diminishes if the mutation is positioned nearby to the protein end.


In an attempt to overcome everything mentioned above, different online tools are available. These tools allow guide design by integrating algorithms created from the analysis of a large volume of data from CRISPR experiments. Some of these online tools are CHOPCHOP, CRISPOR, CRISPR-GE, CRISPR-P, asCRISPR or SnapGene.


Both are online, easy and free softwares, allowing guide desing for different types of experiments, such as gene KO, KI or activation/repression.

They take into account different predictive models to predict rigurously the specificity and efficiency of the cut. They consider the cell type and different PAM sequences depending on the Cas. Being compatible with more than 200 genomes, they allow to design guides in a specific region of the gene and provide primer sequences if desired.


Both are softwares for designing CRISPR experiments in plant.


It is designed for experiments that need to distinguish between genome elements of specific alleles. It is specifically created to determine single nucleotide variants (SNV).

Online softwares presented here are just some of the options available. New algorithms and systems are being developed every day in order to improve and refine the tools available to date.

At Abyntek, we provide an extensive catalogue and custom products validated by The Broad Institute of MIT and Harvard ensuring the best quality service. Our experienced scientific team will guide you, boosting your research to another level.

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