Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock

Author(s)Park,James
Author(s)Zhu,Haisun
Author(s)O'Sullivan,Sean
Author(s)Ogunnaike,Babatunde A.
Author(s)Weaver,David P.
Author(s)Schwaber,James S.
Author(s)Vadigepalli,Rajanikanth
Ordered AuthorJames Park, Haisun Zhu, Sean O'Sullivan, Babatunde A. Ogunnaike, David R.Weaver , James S. Schwaber and RajanikanthVadigepalli
UD AuthorOgunnaike, Babatunde A; Schwaber, James S; Vadigepalli, Rajanikanth
Date Accessioned2017-07-25T19:33:18Z
Date Available2017-07-25T19:33:18Z
Copyright Date2016 Park, Zhu, O'Sullivan, Ogunnaike, Weaver, Schwaber and Vadigepalli.
Publication Date10/25/16
DescriptionPublisher's PDF
AbstractSingle-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 Developmenteloped 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.
DepartmentUniversity of Delaware, Department of Chemical and Biomolecular Engineering
CitationPark, J., Zhu, H., O'Sullivan, S., Ogunnaike, B. A., Weaver, D. P., Schwaber, J. S., & Vadigepalli, R. (2016). Single-cell transcriptional analysis reveals novel neuronal phenotypes and interaction networks involved in the central circadian clock. Frontiers in Neuroscience, 10, 481. doi:10.3389/fnins.2016.00481
DOI10.3389/fnins.2016.00481
ISSN1662-453X
URLhttp://udspace.udel.edu/handle/19716/21603
LanguageEnglish
PublisherFrontiers Media Sa
dc.rightsCC BY 4.0
dc.sourceFrontiers in Neuroscience
dc.source.urihttp://journal.frontiersin.org/journal/neuroscience#
TitleSingle-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock
TypeArticle
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