Genetic compensation is triggered by mutant mRNA degradation

June 13, 2018
HSW 1057


Genetic compensation by transcriptional modulation of related gene(s) (also known as transcriptional adaptation) has been reported in numerous systems; however, whether and how such a response can be activated in the absence of protein feedback loops is unknown. Here, we develop and analyze several models of transcriptional adaptation in zebrafish and mouse that we show are not caused by loss of protein function. We find that the increase in transcript levels is due to enhanced transcription, and observe a correlation between the levels of mutant mRNA decay and transcriptional upregulation of related genes. To assess the role of mutant mRNA degradation in triggering transcriptional adaptation, we use genetic and pharmacological approaches and find that mRNA degradation is indeed required for this process. Notably, uncapped RNAs, themselves subjected to rapid degradation, can also induce transcriptional adaptation. Next, we generate alleles that fail to transcribe the mutated gene and find that they do not show transcriptional adaptation, and exhibit more severe phenotypes than those observed in alleles displaying mutant mRNA decay. Transcriptome analysis of these different alleles reveals the upregulation of hundreds of genes with enrichment for those showing sequence similarity with the mutated gene's mRNA, suggesting a model whereby mRNA degradation products induce the response via sequence similarity. These results expand the role of the mRNA surveillance machinery in buffering against mutations by triggering the transcriptional upregulation of related genes. Besides implications for our understanding of disease-causing mutations, our findings will help design mutant alleles with minimal transcriptional adaptation-derived compensation.

Matthew Gruner
Publication Date: 
June 4, 2018
Presentation Paper: 
Paper Author: 
Mohamed El-Brolosy, Andrea Rossi, Zacharias Kontarakis, Carsten Kuenne, Stefan Guenther, Nana Fukuda, Carter Takacs, Shih-Lei Lai, Ryuichi Fukuda, Claudia Gerri, Khrievono Kikhi, Antonio Giraldez, Didier Y.R. Stainier
1 Department of Developmental Genetics, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
2 ECCPS Bioinformatics and Deep Sequencing Platform, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
3 Department of Genetics, Yale University School of Medicine, New Haven, USA.
bioRxiv preprint first posted online May. 22, 2018; doi: The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.