Autosomal monoallelic expression (MAE) is a recently discovered epigenetic phenomenon that controls the relative expression of maternal and paternal alleles in more than 10% of mammalian genes. The way the active allele is randomly chosen and then stably maintained due to MAE closely resembles X chromosome inactivation, though MAE affects genes in both male and female cells. When the two alleles are functionally distinct, MAE can profoundly affect cell fate, causing two sister cells within the sam individual to perform in diametrically opposite ways, depending on whether the normal or mutant allele of the gene is active. Understanding the function and mechanism of MAE should significantly contribute to revealing the precise link between specific gene variants and susceptibility to a variety of disorders. Genes subject to MAE are implicated in major diseases including cancer, autism, and Alzheimer's disease, promising that MAE research will have a significant impact on multiple fields of biomedicine. However, progress in understanding mechanistic and functional aspects of MAE has been hindered by the inadequacy of traditional technological approaches, which don't allow for systematic analysis of a mechanism that inherently generates enormous cell-to-cell variation. This epigenetic heterogeneity masks variation in allelic expression in contexts where cells are analyzed in bulk, such as most genome-wide and high-throughput research strategies. As a result, researchers have lacked basic knowledge or even the tools for efficiently generating this knowledge. In response, we have developed and validated several pioneering methods that circumvent this barrier, and enable accurate and precise assessment of MAE in human cells and tissues. Thus, for the first time, we can conduct systematic functional, mechanistic, and genetic studies of MAE. We propose to use and extend several novel technologies to directly address critical questions about MAE biology. We will dissect the molecular mechanisms involved in MAE initiation, development, and stable maintenance over multiple cell divisions in human cells, opening the door to targeted manipulation of allelic activity. We also propose to answer the following fundamental functional questions about effects of MAE: How prevalent is MAE in an organism in vivo? How does it vary between individuals? What are the functional consequences of widespread MAE? Successful completion of this project will provide crucial knowledge for precise interpretation of genotype- phenotype relationship in the context of human normal development and disease. It will also provide new understanding of cell-to-cell and between-individual variability. These insights, as well as knowledge of the mechanisms that control the activity of specific alleles of multiple human genes, may be translated into diagnostic, preventative, and therapeutic treatments in the context of personalized medicine.
Recently, a novel mechanism of gene regulation was found to affect many human genes involved in cancer, Alzheimer's, and other major diseases, opening the possibility of fundamentally new approaches to diagnosis, prevention, and patient treatment. However, it has been exceptionally difficult to perform systematic research on this epigenetic mechanism due to the absence of appropriate tools. We have recently developed several new technologies, which we propose to use in an aggressive research program to close this major research gap and open up a new area of translational research.
|Ma, Haiting; Wert, Katherine J; Shvartsman, Dmitry et al. (2018) Establishment of human pluripotent stem cell-derived pancreatic ?-like cells in the mouse pancreas. Proc Natl Acad Sci U S A 115:3924-3929|
|Savova, V; Vinogradova, S; Pruss, D et al. (2017) Risk alleles of genes with monoallelic expression are enriched in gain-of-function variants and depleted in loss-of-function variants for neurodevelopmental disorders. Mol Psychiatry 22:1785-1794|
|Dunford, Andrew; Weinstock, David M; Savova, Virginia et al. (2017) Tumor-suppressor genes that escape from X-inactivation contribute to cancer sex bias. Nat Genet 49:10-16|
|Savova, Virginia; Chun, Sung; Sohail, Mashaal et al. (2016) Genes with monoallelic expression contribute disproportionately to genetic diversity in humans. Nat Genet 48:231-237|
|Savova, Virginia; Patsenker, Jon; Vigneau, Sébastien et al. (2016) dbMAE: the database of autosomal monoallelic expression. Nucleic Acids Res 44:D753-6|
|Liu, X Shawn; Wu, Hao; Ji, Xiong et al. (2016) Editing DNA Methylation in the Mammalian Genome. Cell 167:233-247.e17|