Retinal Müller glial cells, in addition to providing homeostatic support to retinal neurons, have been shown to engage in modulation of neuronal activity and regulate vasomotor responses in the retina, among other functions. Calcium-mediated signaling in Müller cells has been implicated to play a significant role in the intracellular and intercellular interactions necessary to carry out these functions. Although the basic molecular mechanisms of calcium signaling in Müller cells have been described, the dynamics of calcium responses in Müller cells have not been fully explored. Here, we provide a quantitative characterization of calcium signaling in an in vitro model of Müller cell signaling using the rMC-1 cell line, a well-established line developed from rat Müller cells. rMC-1 cells displayed robust intracellular calcium transients and the capacity to support calcium transient-mediated intercellular calcium waves with signaling dynamics similar to that reported for Müller cells in in situ retinal preparations. Furthermore, pharmacological perturbations of intracellular calcium transients with thapsigargin and intercellular calcium waves with purinergic receptor antagonists and gap junction blockers (PPADS and FFA, respectively) suggest that the molecular mechanisms that underlie calcium signaling in rMC-1 cells has been conserved with those of Müller cells. This model provides a robust in vitro system for investigating specific mechanistic hypotheses of intra- and intercellular calcium signaling in Müller cells.

As they proliferate, living cells undergo transitions between specific molecularly and developmentally distinct states. Despite the functional centrality of these transitions in multicellular organisms, it has remained challenging to determine which transitions occur and at what rates without perturbations and cell engineering. Here, we introduce kin correlation analysis (KCA) and show that quantitative cell-state transition dynamics can be inferred, without direct observation, from the clustering of cell states on pedigrees (lineage trees). Combining KCA with pedigrees obtained from time-lapse imaging and endpoint single-molecule RNA-fluorescence in situ hybridization (RNA-FISH) measurements of gene expression, we determined the cell-state transition network of mouse embryonic stem (ES) cells. This analysis revealed that mouse ES cells exhibit stochastic and reversible transitions along a linear chain of states ranging from 2C-like to epiblast-like. Our approach is broadly applicable and may be applied to systems with irreversible transitions and non-stationary dynamics, such as in cancer and development.

Cellular reprogramming highlights the epigenetic plasticity of the somatic cell state. Long noncoding RNAs (lncRNAs) have emerging roles in epigenetic regulation, but their potential functions in reprogramming cell fate have been largely unexplored. We used single-cell RNA sequencing to characterize the expression patterns of over 16,000 genes, including 437 lncRNAs, during defined stages of reprogramming to pluripotency. Self-organizing maps (SOMs) were used as an intuitive way to structure and interrogate transcriptome data at the single-cell level. Early molecular events during reprogramming involved the activation of Ras signaling pathways, along with hundreds of lncRNAs. Loss-of-function studies showed that activated lncRNAs can repress lineage-specific genes, while lncRNAs activated in multiple reprogramming cell types can regulate metabolic gene expression. Our findings demonstrate that reprogramming cells activate defined sets of functionally relevant lncRNAs and provide a resource to further investigate how dynamic changes in the transcriptome reprogram cell state.