Effective identification of CRISPR/Cas9-induced and naturally occurred mutations in rice using a multiplex ligation-dependent probe amplification-based method.

So far it has not yet been possible to clearly demonstrate whether a new change in the genome of plants has arisen through an application of genome editing or whether a naturally occurring mutation is present. This study by Biswas et al. 2020 describes a method to detect both CRISPR/Cas-induced and naturally occurring mutations. Changes at the target sequence as well as unwanted off-target effects in the genome can be recorded. At first glance, the publication gives the impression that the method presented makes it possible to distinguish changes that have arisen by the genetic scissors from naturally occurring mutations. But that’s not the case.
A detection method is described which is based on a previously used method called multiplex ligation-dependent probe amplification (MLPA). This method is used in the study on various rice plants that have different genetic backgrounds or have been modified with genome editing. A prerequisite for the implementation of this method is that the target sequence that is to be changed by CRISPR/Cas9 is known to the scientists. On this basis, specific DNA probes are then developed which, can only fully bind to the target sequence if the original DNA sequence is still present. Should a new change occur in the target sequence, the probes cannot bind to the DNA. The bound DNA probes are replicated and evaluated in a classic PCR process.

There are three possible outcomes:

1. The probes were able to bind within the target region and a peak is visible during the evaluation on the computer. The original DNA sequence is still there.

2. The probes cannot bind and there is no peak in the evaluation, so there is a change in the target sequence

3. A smaller peak is produced, which is an indication of the presence of a mixture of the first two results. This is the case when the original sequence is present on one chromosome and a newly created mutation is present on the other chromosome. This change is then heterozygous.

For the detection of off-target effects, the scientists design the probes on the basis of predictions from computer programs that determine the five areas of the genetic material that are most similar to the target sequence. The MLPA method works as described for the changes to the target sequence: If a new mutation is present in an off-target area, the probes cannot bind and there is no peak in the evaluation.
For the detection of naturally occurring variants, different rice varieties are examined, which are known to have mutations at certain locations in the genetic make-up. The probes are then specifically designed for areas of the genome in which natural variants are known. This means that the naturally occurring mutations in the genome are also known. The probes can then be used to detect such genetic variants.

Several DNA samples from different rice plants can be mixed and examined at the same time, which is a great advantage of this method. However, the exact sequence of the DNA sequence cannot be defined; the individual samples must be sequenced for this.

A quote from the discussion of the study makes it clear that whole genome sequencing methods still have to be used in order to identify unknown off-target effects in the entire genome:

However, for off-target detection, MLPA-based method can only be used for simultaneously detection of previously identified off-target, but not unknown off-targets. In this case, NGS is super advantageous over MLPA.

It is still not possible to provide definitive evidence as to whether new, unwanted changes in the genetic material are due to errors of the genetic scissors or to spontaneously occurring mutations.

Biswas S, Li R, Hong J, Zhao X, Yuan Z, Zhang D, Shi J (2020) Effective identification of CRISPR/Cas9-induced and naturally occurred mutations in rice using a multiplex ligation-dependent probe amplification-based method. Theor Appl Genet. doi:10.1007/s00122-020-03600-5