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Kuenne, C.

Publications and source records attributed to Kuenne, C..

3 recordsLinked to original sources

Genetic compensation is triggered by mutant mRNA degradation

Genetic compensation by transcriptional modulation of related gene(s) (also known as transcriptional adaptation) has been reported in numerous systems 1-3; 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 genes 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.

genetics

UROPA GUI: A web platform for genomic region annotation

The annotation of genomic ranges such as peaks resulting from ChIP-seq/ATAC-seq or other techniques represents a fundamental task of bioinformatics analysis with considerable impact on many downstream analyses. In our previous work, we introduced the Universal Robust Peak Annotator (UROPA), a flexible command line based tool which improves upon the functionality of existing annotation software. In order to reduce the complexity for biologists and clinicians, we have implemented an intuitive web-based graphical user interface (GUI) and fully functional service platform for UROPA. This extension will empower all users to generate annotations for regions of interest interactively.\n\nAvailability and ImplementationThe open source UROPA GUI server was implemented in R Shiny and Python and is available from http://loosolab.mpi-bn.mpg.de. The source code of our App can be downloaded at https://github.molgen.mpg.de/loosolab/UROPA_GUI under the MIT license.

bioinformatics

Single-cell transcriptional regulations and accessible chromatin landscape of cell fate decisions in early heart development

Formation and segregation of the cell lineages forming the vertebrate heart have been studied extensively by genetic cell tracing techniques and by analysis of single marker gene expression both in embryos and differentiating ES cells. However, the underlying gene regulatory networks driving cell fate transitions during early cardiogenesis is only partially understood, in part due to limited cell numbers and substantial cellular heterogeneity within the early embryo. Here, we comprehensively characterized cardiac progenitor cells (CPC) marked by Nkx2-5 and Isl1 expression from embryonic days E7.5 to E9.5 using single-cell RNA sequencing. By leveraging on cell-to-cell heterogeneity, we identified different previously unknown cardiac sub-populations. Reconstruction of the developmental trajectory revealed that Isl1+ CPC represent a transitional cell population maintaining a prolonged multipotent state, whereas extended expression of Nkx-2.5 commits CPC to a unidirectional cardiomyocyte fate. Correlation-based analysis of cells in the unstable multipotent state uncovered underlying gene regulatory networks associated with differentiation. Furthermore, we show that CPC fate transitions are associated with distinct open chromatin states, which critically depend on Isl1 for accessibility of enhancers. In contrast, forced expression of Nkx2-5 eliminated multipotency of Isl1+ cells and established a unidirectional cardiomyocyte fate. Our data provides a transcriptional map for early cardiogenic events at single-cell resolution and establishes a general model of transcriptional and epigenetic regulations during cardiac progenitor cell fate decisions.

developmental biology