Department of Neurobiology; Weaver Lab
Computational Neuroscience | Molecular and Cellular Neuroscience | Systems Biology
Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.
single-cells, cell-network, transcriptional heterogeneity, transcriptional phenotypes, network topology
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Copyright © 2016 Park, Zhu, O'Sullivan, Ogunnaike, Weaver, Schwaber and Vadigepalli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
DOI of Published Version
Park J, Zhu H, O'Sullivan S, Ogunnaike BA, Weaver DR, Schwaber JS and Vadigepalli R (2016) Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock. Front. Neurosci. 10:481. doi: 10.3389/fnins.2016.00481. Link to article on publisher's website
Frontiers in Neuroscience
Park, James; Zhu, Haisun; O'Sullivan, Sean; Ogunnaike, Babatunde A.; Weaver, David R.; Schwaber, James S.; and Vadigepalli, Rajanikanth, "Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock" (2016). Neurobiology Publications and Presentations. 153.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.