I'm investigating deletions in mtDNA by multiplex ddPCR and TaqMan probe of ND3 gene (target) and RNR2 as a reference copy. But, what I noticed. I found some mis… misestimating. The problem is that I got more copies of ND3 than reference. For example, 1600 copies of ND3 and 1500 of reference (RNR2). I know that is biologically impossible, but what happened? These samples don't have any mark of DNA degradation (checked by EF and Qubit).
First thing first, I thought it caused by degradation of mtDNA, which is difficult to assess it by standard methods like EF, Nanodrop or Qubit. So, in order to do this, I compared copies of RNR2 gene and reference autosomal genes - TERT and beta globin - using by multiplex ddPCR and TaqMans in these samples and other ones and I didn't find any differences.
Now, I have to exclude these samples from my analysis for a while, and I would appreciate hearing your thoughts on this. What do I need to do with it?
The number of mutant versus wildtype mitochondria varies between cells and tissues, and is continuously changing. Because cells have multiple mitochondria, different mitochondria in the same cell can have different variations of the mtDNA. This situation is known as heteroplasmy and is quite normal....many disorders only show when the level of heteroplasmy is high and the existance of a mutation in a few mitochondria is often not enough to generate a phenotype so in answer to your question yes some of your mitochondria could have a deletion or even just a polymorphism stopping one primer from annealing properly
Thank you for an answer, Paul Rutland!
We selected primers and probes in such a way that they do not include any polymorphic variants or known mutations.
Perhaps there's some truth in your thought. Maybe that people have a high risk of Alzheimer's disease with this heteroplasmy. But right now they're healthy in ~50-60 years old.
We investigate these people by NGS technology (MiSeq) and didn't find any deletions in this region. Maybe it was because heteroplasmy has that quantity of a low frequency to be able to identify it or an applied algorithm is not able to find it.
I want to understand whether a technical error has hidden in somewhere or is it has a biological justification.
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