Medical College of Wisconsin
CTSICores SearchResearch InformaticsREDCap

Transcriptional profiling at whole population and single cell levels reveals somatosensory neuron molecular diversity. Elife 2014 Dec 19;3

Date

12/20/2014

Pubmed ID

25525749

Pubmed Central ID

PMC4383053

DOI

10.7554/eLife.04660

Scopus ID

2-s2.0-84979258664 (requires institutional sign-in at Scopus site)   192 Citations

Abstract

The somatosensory nervous system is critical for the organism's ability to respond to mechanical, thermal, and nociceptive stimuli. Somatosensory neurons are functionally and anatomically diverse but their molecular profiles are not well-defined. Here, we used transcriptional profiling to analyze the detailed molecular signatures of dorsal root ganglion (DRG) sensory neurons. We used two mouse reporter lines and surface IB4 labeling to purify three major non-overlapping classes of neurons: 1) IB4(+)SNS-Cre/TdTomato(+), 2) IB4(-)SNS-Cre/TdTomato(+), and 3) Parv-Cre/TdTomato(+) cells, encompassing the majority of nociceptive, pruriceptive, and proprioceptive neurons. These neurons displayed distinct expression patterns of ion channels, transcription factors, and GPCRs. Highly parallel qRT-PCR analysis of 334 single neurons selected by membership of the three populations demonstrated further diversity, with unbiased clustering analysis identifying six distinct subgroups. These data significantly increase our knowledge of the molecular identities of known DRG populations and uncover potentially novel subsets, revealing the complexity and diversity of those neurons underlying somatosensation.

Author List

Chiu IM, Barrett LB, Williams EK, Strochlic DE, Lee S, Weyer AD, Lou S, Bryman GS, Roberson DP, Ghasemlou N, Piccoli C, Ahat E, Wang V, Cobos EJ, Stucky CL, Ma Q, Liberles SD, Woolf CJ

Author

Cheryl L. Stucky PhD Professor in the Cell Biology, Neurobiology and Anatomy department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Animals
Cell Separation
Cluster Analysis
Flow Cytometry
Ganglia, Spinal
Gene Expression Profiling
Mice
Patch-Clamp Techniques
Principal Component Analysis
Sensory Receptor Cells
Transcription, Genetic