25 research outputs found

    Writing, Reading, and Translating the Clustered Protocadherin Cell Surface Recognition Code for Neural Circuit Assembly

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    The ability of neurites of individual neurons to distinguish between themselves and neurites from other neurons and to avoid self (self-avoidance) plays a key role in neural circuit assembly in both invertebrates and vertebrates. Similarly, when individual neurons of the same type project into receptive fields of the brain, they must avoid each other to maximize target coverage (tiling). Counterintuitively, these processes are driven by highly specific homophilic interactions between cell surface proteins that lead to neurite repulsion rather than adhesion. Among these proteins in vertebrates are the clustered protocadherins (Pcdhs), and key to their function is the generation of enormous cell surface structural diversity. Here we review recent advances in understanding how a Pcdh cell surface code is generated by stochastic promoter choice; how this code is amplified and read by homophilic interactions between Pcdh complexes at the surface of neurons; and, finally, how the Pcdh code is translated to cellular function, which mediates self-avoidance and tiling and thus plays a central role in the development of complex neural circuits. Not surprisingly, Pcdh mutations that diminish homophilic interactions lead to wiring defects and abnormal behavior in mice, and sequence variants in the Pcdh gene cluster are associated with autism spectrum disorders in family-based genetic studies in humans

    Writing, Reading, and Translating the Clustered Protocadherin Cell Surface Recognition Code for Neural Circuit Assembly

    Get PDF
    The ability of neurites of individual neurons to distinguish between themselves and neurites from other neurons and to avoid self (self-avoidance) plays a key role in neural circuit assembly in both invertebrates and vertebrates. Similarly, when individual neurons of the same type project into receptive fields of the brain, they must avoid each other to maximize target coverage (tiling). Counterintuitively, these processes are driven by highly specific homophilic interactions between cell surface proteins that lead to neurite repulsion rather than adhesion. Among these proteins in vertebrates are the clustered protocadherins (Pcdhs), and key to their function is the generation of enormous cell surface structural diversity. Here we review recent advances in understanding how a Pcdh cell surface code is generated by stochastic promoter choice; how this code is amplified and read by homophilic interactions between Pcdh complexes at the surface of neurons; and, finally, how the Pcdh code is translated to cellular function, which mediates self-avoidance and tiling and thus plays a central role in the development of complex neural circuits. Not surprisingly, Pcdh mutations that diminish homophilic interactions lead to wiring defects and abnormal behavior in mice, and sequence variants in the Pcdh gene cluster are associated with autism spectrum disorders in family-based genetic studies in humans

    An Epigenetic Signature for Monoallelic Olfactory Receptor Expression

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    Constitutive heterochromatin is traditionally viewed as the static form of heterochromatin that silences pericentromeric and telomeric repeats in a cell cycleand differentiation-independent manner. Here, we show that, in the mouse olfactory epithelium, olfactory receptor (OR) genes are marked in a highly dynamic fashion with the molecular hallmarks of constitutive heterochromatin, H3K9me3 and H4K20me3. The cell type and developmentally dependent deposition of these marks along the OR clusters are, most likely, reversed during the process of OR choice to allow for monogenic and monoallelic OR expression. In contrast to the current view of OR choice, our data suggest that OR silencing takes place before OR expression, indicating that it is not the product of an OR-elicited feedback signal. Our findings suggest that chromatin-mediated silencing lays a molecular foundation upon which singular and stochastic selection for gene expression can be applied
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