Research

Background and Mission

Modern Genome Engineering Tools give us access to a wide range of genome modifications. We can now knock out, knock down or activate virtually any gene to study its role during physiology and disease.

Phenomenally similar perturbations in a gene can produce a wide range of phenotypes in animal models and same mutations can lead to variable expression of human disease. The Genome Engineering and Measurement Lab investigates the technical and biological parameters that are responsible for this variability.

Technical Parameters

Off-target effects constitute an inherent characteristic of all types of manipulations we do to biological systems; small molecules can bind and modulate the activity of secondary enzymes, siRNAs can target other mRNAs and RNA guided nucleases like Cas9 can induce double stranded breaks in unwanted sites in the genome. Identification of the off target profile of Cas nucleases is thus important to understand its source and rationally design better and safer genome engineering tools.

Biological Parameters

Penetrance and expressivity are two terms used by geneticists to describe the black box that lies between genotype and phenotype. It is widely accepted that environmental factors and genetic background are the primary causes for incomplete penetrance and variable expressivity. In GEML, we analyse what causes different alleles to behave differently and how some cells can compensate genetic mutations. Our ultimate goal is to identify pathways important for modulating the genetic compensation response in human cells and devise ways to use this knowledge for ameliorating disease symptoms.

Selected Publications

Genetics in Light of Transcriptional Adaptation.

Kontarakis Z and Stainier DYR
Trends in Genetics. 2020 Sep 11 
external page doi:10.1016/j.tig.2020.08.008 (free access external page here)

Transcriptional adaptation in Caenorhabditis elegans.

Serobyan V, Kontarakis Z, El-Brolosy MA, Welker JM, Tolstenkov O, Saadeldein AM, Retzer N, Gottschalk A, Wehman AM, Stainier DY.
Elife. 2020 Jan 17;9. pii: e50014.
external page doi:10.7554/eLife.50014 external page PubMed PMID: 31951195

Genetic compensation triggered by mutant mRNA degradation.

El-Brolosy MA, Kontarakis Z, Rossi A, Kuenne C, Günther S, Fukuda N, Kikhi K,
Boezio GLM, Takacs CM, Lai SL, Fukuda R, Gerri C, Giraldez AJ, Stainier DYR. 
Nature. 2019 Apr;568(7751):193-197.
external page doi: 10.1038/s41586-019-1064-z external page PubMed PMID: 30944477

Genetic compensation induced by deleterious mutations but not gene knockdowns.

Rossi A*, Kontarakis Z*, Gerri C, Nolte H, Hölper S, Krüger M, Stainier DY.
Nature. 2015 Aug 13;524(7564):230-3.
external page doi: 10.1038/nature14580 external page PubMed PMID: 26168398

Making sense of anti-sense data.

Stainier DY, Kontarakis Z, Rossi A.
Dev Cell. 2015 Jan 12;32(1):7-8.
external page doi: 10.1016/j.devcel.2014.12.012 external page PubMed PMID: 25584794

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