Significance Understanding how mammalian organisms achieve the full diversity of cell types in the adult organism is a central goal of developmental cell biology. Recent work has shown that some… Click to show full abstract
Significance Understanding how mammalian organisms achieve the full diversity of cell types in the adult organism is a central goal of developmental cell biology. Recent work has shown that some embryonic precursor cells can self-organize into developmental structures but the mechanisms of gene regulation that contribute to this process remain unknown. Here we show embryonic stem cells self-organize into distinct gene expression states that resemble developmental gene programs. We find that microRNAs, small noncoding regulators of gene expression, play a critical role in organizing fluctuations across gene networks to help achieve this organization into distinct expression states. Pluripotent embryonic stem cells (ESCs) contain the potential to form a diverse array of cells with distinct gene expression states, namely the cells of the adult vertebrate. Classically, diversity has been attributed to cells sensing their position with respect to external morphogen gradients. However, an alternative is that diversity arises in part from cooption of fluctuations in the gene regulatory network. Here we find ESCs exhibit intrinsic heterogeneity in the absence of external gradients by forming interconverting cell states. States vary in developmental gene expression programs and display distinct activity of microRNAs (miRNAs). Notably, miRNAs act on neighborhoods of pluripotency genes to increase variation of target genes and cell states. Loss of miRNAs that vary across states reduces target variation and delays state transitions, suggesting variable miRNAs organize and propagate variation to promote state transitions. Together these findings provide insight into how a gene regulatory network can coopt variation intrinsic to cell systems to form robust gene expression states. Interactions between intrinsic heterogeneity and environmental signals may help achieve developmental outcomes.
               
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