Hidden Genetic Variations can be Detected Using New Nijmegen Method

Many hidden genetic variations can be detected with Chameleolyser, a new method developed in Nijmegen. The information is already yielding new patient diagnoses and may also lead to the discovery of as yet unknown disease genes, write Wouter Steyaert and Christian Gilissen of Radboudumc in Nature Communications.

Medical science has been using exome sequencing to map the genes of individual patients with rare diseases for about 15 years. With this technique, the DNA of a person's approximately 20,000 human genes are cut into small pieces so the DNA letters can be read off. This creates a huge amount of tiny DNA fragments, which are then reassembled into whole genes like a jigsaw puzzle. The result is an overview of that single person's 20,000 genes.

Evolutionary engine

'Unfortunately, such an overview is never quite complete,' says Christian Gilissen, professor of Genome Bioinformatics. 'That's because of the evolution of our genome, our hereditary material. When copying DNA, things sometimes go wrong. Small pieces of DNA disappear or are added. Some pieces are copied more than once. It also happens that a copied gene is placed somewhere else in the genome, giving you a pseudogene in addition to the original gene. These genetic "sloppinesses" are very important because they are the engine of evolution. This is how genetic changes arise. Changes that can be without effect or beneficial, but sometimes also cause new diseases.'

Confusing pseudogenes

Zooming in on the gene and pseudogenes for a moment. The gene has a function, the pseudogen usually does not. Over time, small changes, mutations, can occur in both the gene and pseudogen. But gene and pseudogen are so similar that when sequencing it is not clear which piece belongs to the gene and which to the pseudogen. Gilissen: 'For this reason, these DNA regions are not included in the analysis. A mutation found may originate from the pseudogen and have no meaning. If you add that mutation to the normal gene, you would make a wrong diagnosis. We don't want that.'

Making the invisible visible

With Wouter Steyaert, Gilissen developed a method - Chameleolyser - that detects gene and pseudogen combinations in existing exome sequencing data and can also visualize the genetic variations between them. Steyaert: 'We are now picking up a lot of genetic variation that was previously invisible. Per exome, we find about sixty additional genetic variants. For a number of people, this data allowed us to definitively determine the cause of their disease. With a new sequencing technique from PacBio, which analyzes longer stretches of DNA, we have established the reliability of our method.'

New disease genes, new diagnoses

The new method is interesting because it can be applied to already existing exome sequencing data. Thus, no new studies in patients are necessary. Any sequencing center in the world can apply the method.

Such a large-scale analysis can also provide new biological insights. In many disorders, the genetic cause can only be determined in half of the patients. We think we will also find new disease genes in those gene-pseudogen combinations. For some of those patients, that may be where the genetic cause for their condition lies."

Christian Gilissen, Professor of Genome Bioinformatics

Source:
Journal reference:

Steyaert, W., et al. (2023). Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation. Nature Communications. doi.org/10.1038/s41467-023-42531-9.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Meta-Analysis of ABA-Related Stress Responses Reveals Novel Gene Targets in Thale Cress