We have demonstrated that essentially all monoallelic expression in cells (in vitro and in vivo) was due to a stochastic process (and therefore not regulated as is the case for X-chromosome inactivation or imprinting). We profiled primary fibroblasts that were clonally propagated, and compared those to fibroblasts that were not clonally related. This revealed only a few genes with consistent monoallelic expression within a clone. We expanded these analyses in vivo, by studying human T-cells for which we also obtained clonal information by inferring their T-cell receptor rearrangements. From this data, we could demonstrate that clonal random monoallelic expression for autosomal genes are scarce (in contrast to earlier papers) and that random monoallelic expression instead frequently arise as a consequence of stochastic gene expression. We went further to demonstrate that determinants for monoallelic expression resulting from stochastic gene expression is cell size, activation state and cell cycle state (This work was publised in Reinius, Mold et al. Nature Genetics 2016). To obtain deeper insights into stochastic transcription, we developed a statistical inference procedure to infer transcriptional bursting kinetics from single-cell RNA-seq data, which revealed that mammalian genes are all expressed in a bursty manner, and it identified distinct regulatory sequences that control bursting frequencies and sizes. This work was published (Larsson et al. Nature 2019). We next demonstrated that stochastic transcription, in the form of transcriptional bursting, could explain eseentially all the allelic patterns observed in single cells. Moreover, we demonstrated that the burst frequency is determining the frequency of monollelic observations at the single-cell level. This work was published (Larsson e al. PLoS Comp biol 2021). All this work together clearly demonstrated the nature of monoallelic expression in cells, the extent of transcriptional bursting, and how bursting kinetics affect allelic flucatuations. We have also investigated the clonality in gene expression, which looks drastically different than the allelic observations. Clonal structures underly heterogeneity observed at the RNA and protein levels. This work us curretly under peer-review.
