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 pagedoi:10.1016/j.tig.2020.08.008call_made (free access external pageherecall_made)
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 pagedoi:10.7554/eLife.50014call_made external pagePubMed PMID: 31951195call_made
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 pagedoi: 10.1038/s41586-019-1064-zcall_made external pagePubMed PMID: 30944477call_made
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 pagedoi: 10.1038/nature14580call_made external pagePubMed PMID: 26168398call_made
Making sense of anti-sense data.
Stainier DY, Kontarakis Z, Rossi A.
Dev Cell. 2015 Jan 12;32(1):7-8.
external pagedoi: 10.1016/j.devcel.2014.12.012call_made external pagePubMed PMID: 25584794call_made