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Screening and Validation

35 min Read
Video Summary

Although the CRISPR system for genome editing is efficient, not every cell in a population will be edited. Therefore, it is important to understand how to screen and validate edited cells efficiently.

On-Target Mutations

Before starting your experiment, it’s important to understand the possible outcomes of a CRISPR edit. Once sgRNA(s) and Cas9 have been introduced to a cell line, the generated edits will not be identical, nor will they necessarily occur in all alleles of a gene or all cells in a population. For example, when targeting a single gene of a diploid cell there are four possible outcomes:

  • No edit occurs,
  • One allele is edited (heterozygous mutation),
  • Both alleles are edited, but they carry a different sequence (biallelic mutation),
  • Both alleles are edited, and they carry the same sequence (homozygous mutation).

In most cases, a biallelic or homozygous mutation would be desired in order to be sure the gene of interest is completely edited and none of the wild type phenotype remains.

Screening Basics

The basic workflow of screening for edited cells is:

  • Perform your first screening assay on a mixed population to determine whether a significant number of cells developed the desired genome edit.
  • If some of the population was successfully edited, isolate single cells. This is commonly done using serial dilution. However, if any of the components include a fluorescent reporter, FACS (Fluorescence-Activated Cell Sorting) can be used to sort for cells which contain that component, thus enriching for edited cells.
  • Expand isolated cells to create clonal cell lines.
  • Perform screening on each clonal cell line, until finding one with the desired edit.

Edited cells may be screened differently depending on whether the edit was repaired using Homology Directed Repair (HDR), or Non-Homologous End Joining (NHEJ). The HDR pathway is used for specific edits by including a HDR template along with sgRNA(s) and Cas9. The sequence of the HDR template is used to repair the cut site, integrating the desired sequence at the cut region. In comparison, NHEJ is error-prone and causes indel mutations (short insertions or deletions) at the cut site.

Screening for Cells Edited with a HDR template

Here are some possible ways to screen for cells edited with an HDR template:

  • Include restriction sites in the HDR template that will generate a unique band pattern by restriction digest if positive.
  • Include a reporter element such as GFP in your template. Enrich with FACS and/or screen by fluorescent microscopy.
  • Include an antibiotic resistance gene in the template and screen by growing with that antibiotic.
  • A single nucleotide mutation can be detected if it disrupts a restriction site, altering the digestion pattern.
  • Sequencing. Sanger sequencing or Next Generation Sequencing (NGS) may be used, especially in the case of single nucleotide changes.

HDR events tend to be less common than indels created by NHEJ, so plan to screen a large number of colonies unless an enrichment method like FACS or antibiotic resistance is used.

We offer Custom CRISPR HDR Templates for all your gene knock-in needs.
Screening for Indels

Indels generated by NHEJ can be identified using a mismatch cleavage assay (commonly known as Surveyor), sequencing, or High Resolution Melting Analysis (HRMA) methods.

Table 1 — Comparison of Indel Screening Methods.

Mismatch Cleavage Detection Assay Sanger Sequencing Next Generation Sequencing High Resolution Melting
Sensitivity (detection limit of mutant DNA) 0.5-3% 1-2% 0.01% 2%
Mutation Sequence? No Yes Yes No
Cost per Assaya $ $$$$$ $$$$ $
Mixed population screening? Yes No Yes No
Clonal cell line screening? Yes, spiked with WT DNA Yes Yes Yes
Distinguishes heterozygosity from homozygosity? No Yes Yes Yes
High throughput? Yes No Yes Yes
Advantages Simple, fast. Simple, gives sequence information. Very sensitive, gives sequence information. Fast, non-destructive, distinguishes heterozygosity/ homozygosity.
Disadvantages Polymorphic locus will lead to false positives. May not distinguish heterozygous editing events if there is a high copy number. Expensive, cannot detect large indels. Set up cost for machinery can be high, cannot detect large indels.

a. Estimated cost per assay. $: < 1 USD; $$: < 5 USD, $$$: > 100 USD; $$$$: > 500 USD.

Source: “Detection of on-target and off-target mutations generated by CRISPR/Cas9 and other sequence-specific nucleases” Zischewski et al. Biotechnology Advances, Feb 2017, Vol. 35, pp. 95-104.

The Mismatch Cleavage Detection Assay

The most widely used method to detect indels caused by CRISPR gene editing is the mismatch cleavage assay (a.k.a. the Surveyor assay). This assay relies on the Surveyor nuclease, which causes a double stranded break at the 3’ end of any mismatches between two strands of annealed DNA.

General protocol for the mismatch cleavage assay:

  • PCR amplify the edited region from a cell population.
  • Denature the strands, then re-anneal. This allows the strands of DNA to separate then randomly re-hybridize, creating heteroduplexes.
  • Treat the DNA with the Surveyor nuclease. Surveyor nuclease will cut only if the strands have formed a heteroduplex.
  • Run digested DNA fragments on an agarose gel. Cleaved product shows the presence of heteroduplexes, indicating indel formation. Band brightness can be used to estimate efficiency: the brighter the cleaved product, the more efficient the editing was.
CRISPR Cas9 - Mismatch Cleavage Detection Assay (Surveyor Assay) Results

Figure 1 – Unedited cell lines show no cleavage products (Wild-type). In this comparison, sgRNA 2 is more effective than sgRNA 1.

Our Genomic Cleavage Detection Kit uses this method!

Sanger Sequencing

Sanger sequencing is mainly used to investigate individual clonal cell lines. The typical method is to amplify the targeted region by PCR then clone the amplicons into a vector. This way, each vector will carry only one gene copy, which generates a clean trace when sequenced. In order to determine the sequence of all gene copies, many colonies need to be screened. Although this method is considered the gold standard for indel detection, it can be expensive and time-consuming.

An alternate method can be used. By sequencing PCR amplicons directly, one can save on time and labour. However, potential problems arise when dealing with non-homozygous editing events. Alleles with a different sequence will generate a chromatogram with multiple traces and superimposed peaks. This may be simple enough when dealing with only two sequences, but in the case of polyploid organisms or copy number variations, it can result in many overlapping traces which are difficult to distinguish. Decoding these overlapping traces can be aided by using a program like DSDecode (5), TIDE (2), or CRISP-ID (6).

Did you know that abm offers Sanger Sequencing? Our Amplicon DNA Sequencing Service is a great choice for CRISPR screening.

Next Generation Sequencing

Another popular method for detecting indels is Next Generation Sequencing. This can be done either on a mixed population, or on clonal cell lines which are pooled for a high-throughput approach to screening.

For performing high throughput NGS screening:

  • Culture clonal cell lines in a 96 well plate. Establish a duplicate plate.
  • PCR amplify the edited region. Use barcoded primers to ensure that sequencing reads can later be matched with their original clone.
  • Pool the PCR amplified DNA.
  • Prepare and sequence the library.
  • Analyse sequencing data. This may be done using tools such as CRISPResso (7) or CRISPR Genome Analyzer (4).
  • Identify clones with the desired mutation. Expand these clones from the duplicate plate as desired.

NGS methods have several advantages over other screening methods. They are able to detect whether all alleles of a gene were correctly edited, exactly what indels were generated, and whether a cell population is truly monoclonal. However, these methods are more costly and are more complicated to analyse.

NGS sequencing is also an excellent method for investigating off-target effects of CRISPR editing (see our upcoming article: CRISPR Cas9 – Evaluating Off-Target Effects).

abm offers NGS services for CRISPR screening and validation, including Amplicon Sequencing for CRISPR validation.

Next Generation Sequencing

This method involves the analysis of the melt curve generated when performing real-time PCR in the presence of an intercalating fluorescent dye (similarly to qPCR). When the DNA is annealed in a double stranded form, the dye fluoresces. As the DNA is exposed to progressively higher temperatures, the dye is released and loses its fluorescent properties. By gathering this information, a melt curve is generated showing the temperature-dependent denaturation profile of the amplicons.

Each type of genome edit (wild-type, heterozygous mutation, biallelic mutation, or homozygous mutation) will generate a different melt curve. Therefore, HRMA makes it possible to distinguish between different mutant alleles. As well, the process leaves the amplicons intact, so they can be easily sequenced to determine the exact sequence of the edited region. Set up costs can be high, as HRMA machines cost from $10-25k. However, this is potentially mitigated by combining an existing qPCR machine with free HRMA software such as uAnalyze (8).

Other Indel Screening Methods

While we’ve covered some of the most popular screening methods above, there are many more that have been developed. Here is a brief summary of some other methods for CRISPR indel screening.

  • Cleaved Amplified Polymorphic Sequences (CAPS): Design sgRNAs so that if an indel is formed it will disrupt an enzyme restriction site, then use restriction enzyme digest for screening.
  • Loss of primer binding site: Design primers to amplify the edited region, with one primer that overlaps at the putative indel site.
  • Droplet Digital PCR (ddPCR): ddPCR is a type of quantitative PCR where the sample is fractionated into thousands of droplets, with amplification occurring in each droplet. For screening, design probes to amplify the edited region, with one probe that overlaps at the putative indel site. Droplets containing a mutant amplicon will only produce one signal, while WT will produce two.
  • Heteroduplex mobility assay: A heteroduplex formed by one strand of WT DNA + one strand of DNA with an indel will migrate slower than homoduplex DNA using polyacrylamide gel electrophoresis (PAGE).
  • IAmplified fragment length polymorphisms: If a large deletion is expected, it can be visualized by running the amplicon on an agarose gel.
  • Fluorescent PCR capillary gel electrophoresis: Use fluorophore primers to generate an amplicon then resolve by capillary gel electrophoresis. Amplicons with an indel mutation shows a difference in mobility to wild type.

For more information about our experiences with CRISPR screening, see our CRISPR Cas9 Case Studies.

CRISPR webinar

CRISPR Experimental Design Tool
  • Mutation detection using Surveyor nuclease. Qiu, P, et al. Biotechniques, Apr 2004, Vol. 36, pp. 702-707.
  • Easy quantitative assessment of genome editing by sequence trace decomposition. Brinkman, E, et al. Nucleic Acids Research, Dec 2014, Vol. 42, e168.
  • Genome editing assessment using CRISPR Genome Analyzer (CRISPR-GA). Güell M, et al. Bioinformatics, Oct 2014, Vol. 30, pp2968-2970.
  • Simple Methods for Generating and Detecting Locus-Specific Mutations Induced with TALENs in the Zebrafish Genome. Dahlem, T, et al. PLOS Genetics, Aug 2012, Vol. 8, e1002861.
  • DSDecode: A Web-Based Tool for Decoding of Sequencing Chromatograms for Genotyping of Targeted Mutations. Liu, W, et al. Molecular Plant, May 2015, Vol. 8, pp. 1431–1433.
  • CRISP-ID: decoding CRISPR mediated indels by Sanger sequencing. Dehairs, J, et al. Scientific Reports, Jun 2016, Vol. 6, e28973.
  • Analyzing CRISPR genome-editing experiments with CRISPResso. Pinello, L, et al. Nature Biotechnology, Jul 2016, Vol. 34, pp. 695-697.
  • uAnalyze: Web-Based High-Resolution DNA Melting Analysis with Comparison to Thermodynamic Predictions. Dwight, Z, et al. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Dec 2012, Vol. 9, pp. 1805-1811.