Publication Date:
2022-10-31
Description:
© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Northcutt, A. J., Kick, D. R., Otopalik, A. G., Goetz, B. M., Harris, R. M., Santin, J. M., Hofmann, H. A., Marder, E., & Schulz, D. J. Molecular profiling of single neurons of known identity in two ganglia from the crab Cancer borealis. Proceedings of the National Academy of Sciences of the United States of America, 116 (52) (2019): 26980-26990, doi: 10.1073/pnas.1911413116.
Description:
Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling—RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally defined neuron types can be classified by expression profile alone. The results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post hoc grouping, so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between 2 or more cell types. Therefore, this study supports the general utility of cell identification by transcriptional profiling, but adds a caution: It is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology, or innervation target can neuronal identity be unambiguously determined.
Description:
We thank members of the D.J.S., H.A.H., and E.M. laboratories for helpful discussions. We thank the Genomic Sequencing and Analysis Facility (The University of Texas [UT] at Austin) for library preparation and sequencing and the bioinformatics consulting team at the UT Austin Center for Computational Biology and Bioinformatics for helpful advice. This work was supported by National Institutes of Health grant R01MH046742-29 (to E.M. and D.J.S.) and the National Institute of General Medical Sciences T32GM008396 (support for A.J.N.) and National Institute of Mental Health grant 5R25MH059472-18 and the Grass Foundation (support for Neural Systems and Behavior Course at the Marine Biological Laboratory).
Keywords:
qPCR
;
RNA-seq
;
Stomatogastric
;
Expression profiling
Repository Name:
Woods Hole Open Access Server
Type:
Article
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