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Proneural genes are among the most early-acting genes in nervous system development, instructing blast cells to commit to a neuronal fate. Drosophila Atonal and Achaete-Scute complex (AS-C) genes, as well as their vertebrate orthologs, are basic helix-loop-helix (bHLH) transcription factors with such proneural activity. We show here that a C. elegans AS-C homolog, hlh-4, functions in a fundamentally different manner. In the embryonic, larval, and adult nervous systems, hlh-4 is expressed exclusively in a single nociceptive neuron class, ADL, and its expression in ADL is maintained via transcriptional autoregulation throughout the life of the animal. However, in hlh-4 null mutants, the ADL neuron is generated and still appears neuronal in overall morphology and expression of panneuronal and pansensory features. Rather than acting as a proneural gene, we find that hlh-4 is required for the ADL neuron to function properly, to adopt its correct morphology, to express its unusually large repertoire of olfactory receptor-encoding genes, and to express other known features of terminal ADL identity, including neurotransmitter phenotype, neuropeptides, ion channels, and electrical synapse proteins. hlh-4 is sufficient to induce ADL identity features upon ectopic expression in other neuron types. The expression of ADL terminal identity features is directly controlled by HLH-4 via a phylogenetically conserved E-box motif, which, through bioinformatic analysis, we find to constitute a predictive feature of ADL-expressed terminal identity markers. The lineage that produces the ADL neuron was previously shown to require the conventional, transient proneural activity of another AS-C homolog, hlh-14, demonstrating sequential activities of distinct AS-C-type bHLH genes in neuronal specification. Taken together, we have defined here an unconventional function of an AS-C-type bHLH gene as a terminal selector of neuronal identity and we speculate that such function could be reflective of an ancestral function of an "ur-" bHLH gene.
Pubmed ID: 29672507
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View all literature mentionsCentral data repository for nematode biology including complete genomic sequence, gene predictions and orthology assignments from range of related nematodes.Data concerning genetics, genomics and biology of C. elegans and related nematodes. Derived from initial ACeDB database of C. elegans genetic and sequence information, WormBase includes genomic, anatomical and functional information of C. elegans, other Caenorhabditis species and other nematodes. Maintains public FTP site where researchers can find many commonly requested files and datasets, WormBase software and prepackaged databases.
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View all literature mentionsNEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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