Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock.
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.
Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Sidney Kimmel Medical College, Thomas Jefferson UniversityPhiladelphia, PA, USA; Department of Chemical and Biomolecular Engineering, University of DelawareNewark, NJ, USA.
James
J
Park
Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Sidney Kimmel Medical College, Thomas Jefferson University Philadelphia, PA, USA.
Haisun
H
Zhu
Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Sidney Kimmel Medical College, Thomas Jefferson University Philadelphia, PA, USA.
Sean
S
O'Sullivan
Department of Chemical and Biomolecular Engineering, University of Delaware Newark, NJ, USA.
Babatunde A
BA
Ogunnaike
Department of Neurobiology, University of Massachusetts Medical School Worcester, MA, USA.
David R
DR
Weaver
Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Sidney Kimmel Medical College, Thomas Jefferson UniversityPhiladelphia, PA, USA; Department of Chemical and Biomolecular Engineering, University of DelawareNewark, NJ, USA.
James S
JS
Schwaber
Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Sidney Kimmel Medical College, Thomas Jefferson UniversityPhiladelphia, PA, USA; Department of Chemical and Biomolecular Engineering, University of DelawareNewark, NJ, USA.
Rajanikanth
R
Vadigepalli
cell-network; network topology; single-cells; transcriptional heterogeneity; transcriptional phenotypes