Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing

By D. Usoskin, Alessandro Furlan, S. Islam, Hind Abdo, P. Lönnerberg, Daohua Lou, Jens Hjerling-Leffler, J. Haeggström, O. Kharchenko, Peter V. Kharchenko and 2 more. Nature Neuroscience, 2014

1,916 citations recorded by the source corpus.

Subfields: Dermatology, Physiology, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/b91f7fe7a54159663946e5a88937af4e268edbb4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Physiology

1. G. Zamponi
2. Daniel J. Garry
3. Aviv Regev
4. Ernest Arenas
5. R. Gereau

In Sensory Systems

1. Kenneth D. Harris
2. Mala Murthy

Citations in the corpus

• Molecular Architecture of the Mouse Nervous System (2018, methodology): “Within the peripheral sensory neurons (of the dorsal root ganglia), cell-types were divided into three main branches: peptidergic (8 types), non-peptidergic (6 types) and neurofilament (3 types), which suggests refinements to previous classifications (Li et al., 2016; Usoskin et al., 2014) (Table S2”
• Adult Mouse Cortical Cell Taxonomy by Single Cell Transcriptomics (2016, neutral): “15).”
• Using neural networks for reducing the dimensions of single-cell RNA-Seq data (2017, methodology): “PCA has been used extensively for clustering single cells (1,10,11).”
• Cell Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression (2016, positive): “…category are highly informative for separating cell types within the MB. Previous studies demonstrated that cells can be identified based on subsets of genes, but these genes were not typically linked in terms of cellular function (Tasic et al., 2016; Usoskin et al., 2015; Zeisel et al., 2015).”
• Sensory Neurons Co-opt Classical Immune Signaling Pathways to Mediate Chronic Itch (2017, positive): “Again using a previously published single-cell RNA-seq dataset (Usoskin et al., 2015), we identified that JAK1 is enriched in pruriceptive neurons (Figure S6A).”
• Could a Neuroscientist Understand a Microprocessor? (2016, background): “algorithms that go from anatomy to function at the moment that go considerably 191 beyond cell-type clustering [29,34,35] it is far from obvious how a connectome would 192 allow an understanding of the brain.”
• TFOS DEWS II pain and sensation report (2017, positive): “This allows sensory neuron types to be classified into a larger number of subtypes with distinct transcriptional profiles, molecular markers and functional properties, some of which are associated with pathological signs [34].”
• Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning (2016, background): “Recent studies have demonstrated that de novo cell type discovery and identification of functionally distinct cell subpopulations are possible via unbiased analysis of all transcriptomic information provided by scRNA-seq data [8].”
• ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis (2015, methodology): “These plots show cell type misclassification rates (using QDA) as a function of dropout rate for the preprocessing using PCA and ZIFA on simulated data sets based on the ( a ) Pollen [15] and ( b ) Usoskin [16] data sets.”
• Classes and continua of hippocampal CA 1 inhibitory neurons revealed by single ‐ cell transcriptomics (2017, methodology): “This method has successfully identified the major cell classes in several neuronal circuits (Habib et al., 2016, 2017; Macosko et al., 2015; Tasic et al., 2016; Usoskin et al., 2015; Zeisel et al., 2015).”
• Revealing the vectors of cellular identity with single-cell genomics (2016, methodology): “It has been used repeatedly in single-cell analysis, including iteratively 107 , having its axes inferred from bulk data and then applied to single-cells 108 , and combined with an expectation-maximization (EM) algorithm to fit a finite mixture of Gaussians to PCA-reduced expression profiles 101 .”
• The Physiology, Pathology, and Pharmacology of Voltage-Gated Calcium Channels and Their Future Therapeutic Potential (2015, background): “2 have recently been characterized in molecular detail (Reynders et al., 2015; Usoskin et al., 2015).”
• Single-cell transcriptome sequencing: recent advances and remaining challenges (2016, methodology): “…to detect such cell-to-cell heterogeneity and capitalize upon it to uncover population structure and cell dynamics hidden at the group level. scRNA-seq has been used to dissect heterogeneous cell populations and complex tissues, such as intestine 77 , spleen 16 , lung 78 , or brain 42,79–83 .”