AUTHOR=Gui Baoheng , Slone Jesse , Huang Taosheng TITLE=Perspective: Is Random Monoallelic Expression a Contributor to Phenotypic Variability of Autosomal Dominant Disorders? JOURNAL=Frontiers in Genetics VOLUME=Volume 8 - 2017 YEAR=2017 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2017.00191 DOI=10.3389/fgene.2017.00191 ISSN=1664-8021 ABSTRACT=

Several factors have been proposed as contributors to interfamilial and intrafamilial phenotypic variability in autosomal dominant disorders, including allelic variation, modifier genes, environmental factors and complex genetic and environmental interactions. However, regardless of the similarity of genetic background and environmental factors, asymmetric limb or trunk anomalies in a single individual and variable manifestation between monozygotic twins have been observed, indicating other mechanisms possibly involved in expressivity of autosomal dominant diseases. One such example is Holt-Oram syndrome (HOS), which is characterized by congenital cardiac defects and forelimb anomalies, mainly attributed to mutations in the TBX5 gene. We hypothesize that monoallelic expression of the TBX5 gene occurs during embryo development, and, in the context of a mutation, random monoallelic expression (RME) can create discrepant functions in a proportion of cells and thus contribute to variable phenotypes. A hybrid mouse model was used to investigate the occurrence of RME with the Tbx5 gene, and single-cell reverse transcription PCR and restriction digestion were performed for limb bud cells from developing embryos (E11.5) of the hybrid mice. RME of Tbx5 was observed in approximately two-thirds of limb bud cells. These results indicate that RME of the Tbx5 gene occurs frequently during embryo development, resulting in a mosaic expression signature (monoallelic, biallelic, or null) that may provide a potential explanation for the widespread phenotypic variability in HOS. This model will further provide novel insights into the variability of autosomal dominant traits and a better understanding of the complex expressivity of disease conditions.