Genomic imprinting is an epigenetic process that leads to parent of origin-specific gene expression in a subset of genes. Imprinted genes are essential for brain development, and deregulation of imprinting is associated with neurodevelopmental diseases and the pathogenesis of psychiatric disorders. However, the cell-type specificity of imprinting at single cell resolution, and how imprinting and thus gene dosage regulates neuronal circuit assembly is still largely unknown. Here, MADM (Mosaic Analysis with Double Markers) technology was employed to assess genomic imprinting at single cell level. By visualizing MADM-induced uniparental disomies (UPDs) in distinct colors at single cell level in genetic mosaic animals, this experimental paradigm provides a unique quantitative platform to systematically assay the UPD-mediated imbalances in imprinted gene expression at unprecedented resolution. An experimental pipeline based on FACS, RNA-seq and bioinformatics analysis was established and applied to systematically map cell-type-specific ‘imprintomes’ in the mouse brain. The results revealed that parental-specific expression of imprinted genes per se is rarely cell-type-specific even at the individual cell level. Conversely, when we extended the comparison to downstream responses resulting from imbalanced imprinted gene expression, we discovered an unexpectedly high degree of cell-type specificity. Furthermore, we determined a novel function of genomic imprinting in cortical astrocyte production and in olfactory bulb (OB) granule cell generation. These results suggest important functional implication of genomic imprinting for generating cell-type diversity in the brain. In addition, MADM provides a powerful tool to study candidate genes by concomitant genetic manipulation and fluorescent labelling of single cells. MADM-based candidate gene approach was utilized to identify potential imprinted genes involved in the generation of cortical astrocytes and OB granule cells. We investigated p57Kip2, a maternally expressed gene and known cell cycle regulator. Although we found that p57Kip2 does not play a role in these processes, we detected an unexpected function of the paternal allele previously thought to be silent. Finally, we took advantage of a key property of MADM which is to allow unambiguous investigation of environmental impact on single cells. The experimental pipeline based on FACS and RNA-seq analysis of MADM-labeled cells was established to probe the functional differences of single cell loss of gene function compared to global loss of function on a transcriptional level. With this method, both common and distinct responses were isolated due to cell-autonomous and non-autonomous effects acting on genotypically identical cells. As a result, transcriptional changes were identified which result solely from the surrounding environment. Using the MADM technology to study genomic imprinting at single cell resolution, we have identified cell-type-specific gene expression, novel gene function and the impact of environment on single cell transcriptomes. Together, these provide important insights to the understanding of mechanisms regulating cell-type specificity and thus diversity in the brain.
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Laukoter S. Role of genomic imprinting in cerebral cortex development. 2018:1-139. doi:10.15479/AT:ISTA:th1057
Laukoter, S. (2018). Role of genomic imprinting in cerebral cortex development. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th1057
Laukoter, Susanne. “Role of Genomic Imprinting in Cerebral Cortex Development.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th1057.
S. Laukoter, “Role of genomic imprinting in cerebral cortex development,” Institute of Science and Technology Austria, 2018.
Laukoter S. 2018. Role of genomic imprinting in cerebral cortex development. Institute of Science and Technology Austria.
Laukoter, Susanne. Role of Genomic Imprinting in Cerebral Cortex Development. Institute of Science and Technology Austria, 2018, pp. 1–139, doi:10.15479/AT:ISTA:th1057.
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