Cited by 465Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesRNA Research and Splicing

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Detecting Activated Cell Populations Using Single-Cell RNA-Seq

Open access

Wu, Ye Emily, Pan, Lin, Zuo, Yanning, Li, Xinmin, Hong, Weizhe·2017·Neuron

DOI 10.1016/j.neuron.2017.09.026

Open this paper in CoChat — free account Open PDF

Abstract

Single-cell RNA sequencing offers a promising opportunity for probing cell types mediating specific behavioral functions and the underlying molecular programs. However, this has been hampered by a long-standing issue in transcriptional profiling of dissociated cells, specifically the transcriptional perturbations that are artificially induced during conventional whole-cell dissociation procedures. Here, we develop Act-seq, which minimizes artificially induced transcriptional perturbations and allows for faithful detection of both baseline transcriptional profiles and acute transcriptional changes elicited by behavior/experience-driven activity. Using Act-seq, we provide the first detailed molecular taxonomy of distinct cell types in the amygdala. We further show that Act-seq robustly detects seizure-induced acute gene expression changes in multiple cell types, revealing cell-type-specific activation profiles. Furthermore, we find that acute stress preferentially activates neuronal subpopulations that express the neuropeptide gene Cck. Act-seq opens the way for linking physiological stimuli with acute transcriptional dynamics in specific cell types in diverse complex tissues.

Integrity signals

Registry

Crossref · 10.1016/j.neuron.2017.09.026

Cites

63 of 63 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Untitled work
(2008) · Journal of Machine Learning Research · Cited by 33,051
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124
From circuits to behaviour in the amygdala
Janak, P. H., & Tye, K. M. (2015) · Nature · doi:10.1038/nature14188 · Cited by 2,011

Show all 62 references

Sorted by citations

Microglia states and nomenclature: A field at its crossroads
Paolicelli, R. C., Sierra, A., Stevens, B., Tremblay, M.-E., Aguzzi, A., Ajami, B., Amit, I., Audinat, E., Bechmann, I., Bennett, M., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.020 · Cited by 1,973
Molecular diversity and specializations among the cells of the adult mouse brain
Saunders, A., Macosko, E. Z., Wysoker, A., Goldman, M., Krienen, F. M., de Rivera, H., Bien, E., Baum, M., Bortolin, L., Wang, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.028 · Cited by 1,531
Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer
Zhang, L., Li, Z., Skrzypczynska, K. M., Fang, Q., Zhang, W., O’Brien, S. A., He, Y., Wang, L., Zhang, Q., Kim, A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.03.048 · Cited by 1,620
Challenges in unsupervised clustering of single-cell RNA-seq data
Kiselev, V. Y., Andrews, T. S., & Hemberg, M. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0088-9 · Cited by 1,205
A single-cell atlas of mouse brain macrophages reveals unique transcriptional identities shaped by ontogeny and tissue environment
Van Hove, H., Martens, L., Scheyltjens, I., De Vlaminck, K., Pombo Antunes, A. R., De Prijck, S., Vandamme, N., De Schepper, S., Van Isterdael, G., Scott, C. L., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0393-4 · Cited by 1,074
Confronting false discoveries in single-cell differential expression
Squair, J. W., Gautier, M., Kathe, C., Anderson, M. A., James, N. D., Hutson, T. H., Hudelle, R., Qaiser, T., Matson, K. J. E., Barraud, Q., et al. (2021) · doi:10.1101/2021.03.12.435024 · Cited by 1,086
Single-cell transcriptomic profiling of the aging mouse brain
Ximerakis, M., Lipnick, S. L., Innes, B. T., Simmons, S. K., Adiconis, X., Dionne, D., Mayweather, B. A., Nguyen, L., Niziolek, Z., Ozek, C., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0491-3 · Cited by 736
Single-nucleus chromatin accessibility and transcriptomic characterization of Alzheimer’s disease
Morabito, S., Miyoshi, E., Michael, N., Shahin, S., Martini, A. C., Head, E., Silva, J., Leavy, K., Perez-Rosendahl, M., & Swarup, V. (2021) · Nature Genetics · doi:10.1038/s41588-021-00894-z · Cited by 643
Astrocyte Reactivity: Subtypes, States, and Functions in CNS Innate Immunity
Sofroniew, M. V. (2020) · Trends in Immunology · doi:10.1016/j.it.2020.07.004 · Cited by 721
Single-Cell Profiles of Retinal Ganglion Cells Differing in Resilience to Injury Reveal Neuroprotective Genes
Tran, N. M., Shekhar, K., Whitney, I. E., Jacobi, A., Benhar, I., Hong, G., Yan, W., Adiconis, X., Arnold, M. E., Lee, J. M., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.11.006 · Cited by 627
Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior
Yap, E.-L., & Greenberg, M. E. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.013 · Cited by 706
Neural circuit mechanisms of social behavior
Chen, P., & Hong, W. (2018) · Neuron · doi:10.1016/j.neuron.2018.02.026 · Cited by 527
Self-citation
Molecular basis of astrocyte diversity and morphology across the CNS in health and disease
Endo, F., Kasai, A., Soto, J. S., Yu, X., Qu, Z., Hashimoto, H., Gradinaru, V., Kawaguchi, R., & Khakh, B. S. (2022) · Science · doi:10.1126/science.adc9020 · Cited by 560
Transcriptional Reprogramming of Distinct Peripheral Sensory Neuron Subtypes after Axonal Injury
Renthal, W. R., Tochitsky, I., Yang, L., Cheng, Y., Li, E., Kawaguchi, R., Geschwind, D. H., & Woolf, C. J. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.026 · Cited by 559
Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation
Miragaia, R. J., Gomes, T., Chomka, A., Jardine, L., Riedel, A., Hegazy, A. N., Whibley, N., Tucci, A., Chen, X., Lindeman, I., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.01.001 · Cited by 499
What is a cell type and how to define it?
Zeng, H. (2022) · Cell · doi:10.1016/j.cell.2022.06.031 · Cited by 439
Optogenetics for light control of biological systems
Emiliani, V., Entcheva, E. G., Hedrich, R., Hegemann, P., Konrad, K. R., Lüscher, C., Mahn, M., Pan, Z., Sims, R. R., Vierock, J., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00136-4 · Cited by 524
White matter aging drives microglial diversity
Safaiyan, S., Besson-Girard, S., Kaya, T., Cantuti-Castelvetri, L., Liu, L., Ji, H., Schifferer, M., Gouna, G., Usifo, F., Kannaiyan, N., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.01.027 · Cited by 477
Mapping microglia states in the human brain through the integration of high-dimensional techniques
Sankowski, R., Böttcher, C., Masuda, T., Geirsdottir, L., Sagar, Sindram, E., Seredenina, T., Muhs, A., Scheiwe, C., Shah, M. J., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0532-y · Cited by 449
Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain
Marsh, S. E., Walker, A. J., Kamath, T., Dissing-Olesen, L., Hammond, T. R., de Soysa, T. Y., Young, A. M. H., Murphy, S., Abdulraouf, A., Nadaf, N., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01022-8 · Cited by 431
Single Cell Sequencing Reveals Glial Specific Responses to Tissue Processing & Enzymatic Dissociation in Mice and Humans
Marsh, S. E., Kamath, T., Walker, A. J., Dissing-Olesen, L., Hammond, T. R., Young, A. M. H., Abdulraouf, A., Nadaf, N., Dufort, C., Murphy, S., et al. (2020) · doi:10.1101/2020.12.03.408542 · Cited by 430
Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior
Sathyamurthy, A., Johnson, K. R., Matson, K. J. E., Dobrott, C. I., Li, L., Ryba, A. R., Bergman, T. B., Kelly, M. C., Kelley, M. W., & Levine, A. J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.003 · Cited by 370
Different Neuronal Activity Patterns Induce Different Gene Expression Programs
Tyssowski, K. M., DeStefino, N. R., Cho, J.-H., Dunn, C. J., Poston, R. G., Carty, C. E., Jones, R. D., Chang, S. M., Romeo, P., Wurzelmann, M. K., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.04.001 · Cited by 390
Beyond bulk: a review of single cell transcriptomics methodologies and applications
Kulkarni, A., Anderson, A. G., Merullo, D. P., & Konopka, G. (2019) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.03.001 · Cited by 355
Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease
Piwecka, M., Rajewsky, N., & Rybak-Wolf, A. (2023) · Nature Reviews Neurology · doi:10.1038/s41582-023-00809-y · Cited by 320
MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing
Keren-Shaul, H., Kenigsberg, E., Jaitin, D. A., David, E., Paul, F., Tanay, A., & Amit, I. (2019) · Nature Protocols · doi:10.1038/s41596-019-0164-4 · Cited by 292
Improved tools to study astrocytes
Yu, X., Nagai, J., & Khakh, B. S. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0264-8 · Cited by 298
Trem2 restrains the enhancement of tau accumulation and neurodegeneration by β-amyloid pathology
Lee, S.-H., Meilandt, W. J., Xie, L., Gandham, V. D., Ngu, H., Barck, K. H., Rezzonico, M. G., Imperio, J., Lalehzadeh, G., Huntley, M. A., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.010 · Cited by 300
CellTalkDB: a manually curated database of ligand–receptor interactions in humans and mice
Shao, X., Liao, J., Li, C., Lu, X., Cheng, J., & Fan, X. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa269 · Cited by 296
Single-cell analysis of the cellular heterogeneity and interactions in the injured mouse spinal cord
Milich, L. M., Choi, J. S., Ryan, C. B., Cerqueira, S. R., Benavides, S., Yahn, S. L., Tsoulfas, P., & Lee, J. K. (2021) · The Journal of Experimental Medicine · doi:10.1084/jem.20210040 · Cited by 289
scCATCH: Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
Shao, X., Liao, J., Lu, X., Xue, R., Ai, N., & Fan, X. (2020) · iScience · doi:10.1016/j.isci.2020.100882 · Cited by 286
Cell type prioritization in single-cell data
Skinnider, M. A., Squair, J. W., Kathe, C., Anderson, M. A., Gautier, M., Matson, K. J. E., Milano, M., Hutson, T. H., Barraud, Q., Phillips, A. A., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0605-1 · Cited by 274
HypoMap—a unified single-cell gene expression atlas of the murine hypothalamus
Steuernagel, L., Lam, B. Y. H., Klemm, P., Dowsett, G. K. C., Bauder, C. A., Tadross, J. A., Hitschfeld, T. S., del Rio Martin, A., Chen, W., de Solis, A. J., et al. (2022) · Nature Metabolism · doi:10.1038/s42255-022-00657-y · Cited by 267
Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes
Armand, E. J., Li, J., Xie, F., Luo, C., & Mukamel, E. A. (2021) · Neuron · doi:10.1016/j.neuron.2020.12.010 · Cited by 241
Temporal and spatial cellular and molecular pathological alterations with single-cell resolution in the adult spinal cord after injury
Li, C., Wu, Z., Zhou, L., Shao, J., Hu, X., Xu, W., Ren, Y., Zhu, X., Ge, W., Zhang, K., et al. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00885-4 · Cited by 266
Questions and (some) answers on reactive astrocytes
Escartin, C., Guillemaud, O., & Carrillo‐de Sauvage, M. (2019) · Glia · doi:10.1002/glia.23687 · Cited by 275
Multimodal analysis of cell types in a hypothalamic node controlling social behavior
Kim, D.-W., Yao, Z., Graybuck, L. T., Kim, T. K., Nguyen, T. N., Smith, K. A., Fong, O., Yi, L., Koulena, N., Pierson, N., et al. (2019) · Cell · doi:10.1016/j.cell.2019.09.020 · Cited by 259
Disease-associated oligodendrocyte responses across neurodegenerative diseases
Pandey, S., Shen, K., Lee, S.-H., Shen, Y.-A. A., Wang, Y., Otero-García, M., Kotova, N., Vito, S. T., Laufer, B. I., Newton, D. F., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111189 · Cited by 227
Cannabinoid CB1 receptors in the amygdalar cholecystokinin glutamatergic afferents to nucleus accumbens modulate depressive-like behavior
Shen, C.-J., Zheng, D., Li, K., Yang, J., Pan, H., Yu, X.-D., Fu, J., Zhu, Y., Sun, Q.-X., Tang, M., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0299-9 · Cited by 231
Self-citation
Rare Pulmonary Neuroendocrine Cells Are Stem Cells Regulated by Rb, p53, and Notch
Ouadah, Y., Rojas, E., Riordan, D. P., Capostagno, S., Kuo, C. S., & Krasnow, M. A. (2019) · Cell · doi:10.1016/j.cell.2019.09.010 · Cited by 223
Astrocyte-immune cell interactions in physiology and pathology
Han, R. T., Kim, R. D., Molofsky, A. V., & Liddelow, S. A. (2021) · Immunity · doi:10.1016/j.immuni.2021.01.013 · Cited by 223
Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain
Tran, M. N., Maynard, K. R., Spangler, A., Huuki, L. A., Montgomery, K. D., Sadashivaiah, V., Tippani, M., Barry, B. K., Hancock, D. B., Hicks, S. C., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.09.001 · Cited by 219
Molecular Mechanisms of the Memory Trace
Asok, A., Leroy, F., Rayman, J. B., & Kandel, E. R. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.10.005 · Cited by 226
Early Alzheimer’s disease pathology in human cortex involves transient cell states
Gazestani, V., Kamath, T., Nadaf, N. M., Dougalis, A., Burris, S. J., Rooney, B., Junkkari, A., Vanderburg, C., Pelkonen, A., Gomez-Budia, M., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.005 · Cited by 209
Sexually Dimorphic Control of Parenting Behavior by the Medial Amygdala
Chen, P. B., Hu, R. K., Wu, Y. E., Pan, L., Huang, S., Micevych, P. E., & Hong, W. (2019) · Cell · doi:10.1016/j.cell.2019.01.024 · Cited by 209
Self-citation
Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies
Haimon, Z., Volaski, A., Orthgiess, J., Boura-Halfon, S., Varol, D., Shemer, A., Yona, S., Zuckerman, B., David, E., Chappell-Maor, L., et al. (2018) · Nature Immunology · doi:10.1038/s41590-018-0110-6 · Cited by 209
Human and mouse trigeminal ganglia cell atlas implicates multiple cell types in migraine
Yang, L., Xu, M., Bhuiyan, S. A., Li, J., Zhao, J., Cohrs, R. J., Susterich, J. T., Signorelli, S., Green, U., Stone, J. R., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.03.003 · Cited by 192
Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq
Hu, P., Fabyanic, E., Kwon, D. Y., Tang, S., Zhou, Z., & Wu, H. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.11.017 · Cited by 162
Single-cell transcriptomic analysis of somatosensory neurons uncovers temporal development of neuropathic pain
Wang, K., Wang, S., Chen, Y., Wu, D., Hu, X., Lu, Y., Wang, L., Bao, L., Li, C., & Zhang, X. (2021) · Cell Research · doi:10.1038/s41422-021-00479-9 · Cited by 196
Interleukin-10 Prevents Pathological Microglia Hyperactivation following Peripheral Endotoxin Challenge
Shemer, A., Scheyltjens, I., Frumer, G. R., Kim, J.-S., Grozovski, J., Ayanaw, S., Dassa, B., Van Hove, H., Chappell-Maor, L., Boura-Halfon, S., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.09.018 · Cited by 175
Microglia drive transient insult-induced brain injury by chemotactic recruitment of CD8+ T lymphocytes
Shi, Z., Yu, P., Lin, W., Chen, S., Hu, X., Chen, S., Cheng, J., Liu, Q., Yang, Y., Li, S., et al. (2023) · Neuron · doi:10.1016/j.neuron.2022.12.009 · Cited by 182
A Binary Cre Transgenic Approach Dissects Microglia and CNS Border-Associated Macrophages
Kim, J.-S., Kolesnikov, M., Peled-Hajaj, S., Scheyltjens, I., Xia, Y., Trzebanski, S., Haimon, Z., Shemer, A., Lubart, A., Van Hove, H., et al. (2021) · Immunity · doi:10.1016/j.immuni.2020.11.007 · Cited by 176
Transcriptional and spatial resolution of cell types in the mammalian habenula
Hashikawa, Y., Hashikawa, K., Rossi, M. A., Basiri, M. L., Liu, Y., Johnston, N. L., Ahmad, O. R., & Stuber, G. D. (2020) · Neuron · doi:10.1016/j.neuron.2020.03.011 · Cited by 167
An amygdala-to-hypothalamus circuit for social reward
Hu, R. K., Zuo, Y., Ly, T., Wang, J., Meera, P., Wu, Y. E., & Hong, W. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00828-2 · Cited by 174
Self-citation
Tissue damage induces a conserved stress response that initiates quiescent muscle stem cell activation
Machado, L., Geara, P., Camps, J., Dos Santos, M., Teixeira-Clerc, F., Van Herck, J., Varet, H., Legendre, R., Pawlotsky, J.-M., Sampaolesi, M., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.01.017 · Cited by 170
Functional hypoxia drives neuroplasticity and neurogenesis via brain erythropoietin
Wakhloo, D., Scharkowski, F., Curto, Y., Butt, U. J., Bansal, V., Steixner-Kumar, A. A., Wüstefeld, L., Rajput, A., Arinrad, S., Zillmann, M. R., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15041-1 · Cited by 162
Astrocytes and microglia: Models and tools
Guttenplan, K. A., & Liddelow, S. A. (2018) · The Journal of Experimental Medicine · doi:10.1084/jem.20180200 · Cited by 164
Neural control of affiliative touch in prosocial interaction
Wu, Y. E., Dang, J., Kingsbury, L., Zhang, M., Sun, F., Hu, R. K., & Hong, W. (2021) · Nature · doi:10.1038/s41586-021-03962-w · Cited by 156
Self-citation
Engram-specific transcriptome profiling of contextual memory consolidation
Rao‐Ruiz, P., Couey, J. J., Marcelo, I. M., Bouwkamp, C. G., Slump, D. E., Matos, M. R., van der Loo, R. J., Martins, G. J., van den Hout, M. C. G. N., van IJcken, W. F. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09960-x · Cited by 146
Enzymatic dissociation induces transcriptional and proteotype bias in brain cell populations
Mattei, D., Ivanov, A., van Oostrum, M., Pantelyushin, S., Richetto, J., Mueller, F., Beffinger, M. M., Schellhammer, L., vom Berg, J., Wollscheid, B., et al. (2020) · doi:10.1101/2020.05.14.095422 · Cited by 143
Enzymatic Dissociation Induces Transcriptional and Proteotype Bias in Brain Cell Populations
Mattei, D., Ivanov, A., van Oostrum, M., Pantelyushin, S., Richetto, J., Mueller, F., Beffinger, M., Schellhammer, L., vom Berg, J., Wollscheid, B., et al. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21217944 · Cited by 145
Organization of neural circuits underlying social behavior: A consideration of the medial amygdala
Raam, T., & Hong, W. (2021) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2021.02.008 · Cited by 134
Self-citation
Single Cell RNA Sequencing in Atherosclerosis Research
Williams, J. W., Winkels, H., Durant, C. P., Zaitsev, K., Ghosheh, Y., & Ley, K. F. (2020) · Circulation Research · doi:10.1161/circresaha.119.315940 · Cited by 142
Single‐Cell RNA Sequencing Reveals the Temporal Diversity and Dynamics of Cardiac Immunity after Myocardial Infarction
Jin, K., Gao, S., Yang, P., Guo, R., Li, D., Zhang, Y., Lu, X., Fan, G., & Fan, X. (2022) · Small Methods · doi:10.1002/smtd.202100752 · Cited by 135
A platform for efficient establishment and drug-response profiling of high-grade serous ovarian cancer organoids
Senkowski, W., Gall-Mas, L., Falco, M. M., Li, Y., Lavikka, K., Kriegbaum, M. C., Oikkonen, J., Bulanova, D. R., Pietras, E. J., Voßgröne, K., et al. (2023) · Developmental Cell · doi:10.1016/j.devcel.2023.04.012 · Cited by 128
Single cell atlas of spinal cord injury in mice reveals a pro-regenerative signature in spinocerebellar neurons
Matson, K. J. E., Russ, D. E., Kathe, C., Hua, I., Maric, D., Ding, Y., Krynitsky, J., Pursley, R. H., Sathyamurthy, A., Squair, J. W., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33184-1 · Cited by 142
Context-Specific Striatal Astrocyte Molecular Responses Are Phenotypically Exploitable
Yu, X., Nagai, J., Martí-Solano, M., Soto, J. S., Coppola, G., Babu, M. M., & Khakh, B. S. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.021 · Cited by 123
Astrocyte immunometabolic regulation of the tumour microenvironment drives glioblastoma pathogenicity
Perelroizen, R., Philosof, B., Budick-Harmelin, N., Chernobylsky, T., Ron, A., Katzir, R., Shimon, D., Tessler, A., Adir, O., Gaoni-Yogev, A., et al. (2022) · Brain · doi:10.1093/brain/awac222 · Cited by 131
Induction of a torpor-like hypothermic and hypometabolic state in rodents by ultrasound
Yang, Y., Yuan, J., Field, R. L., Ye, D., Hu, Z., Xu, K., Xu, L., Gong, Y., Yue, Y., Kravitz, A. V., et al. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00804-z · Cited by 125
Derivation and transcriptional reprogramming of border-forming wound repair astrocytes after spinal cord injury or stroke in mice
O’Shea, T. M., Ao, Y., Wang, S., Ren, Y., Cheng, A. L., Kawaguchi, R., Shi, Z., Swarup, V., & Sofroniew, M. V. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01684-6 · Cited by 129
Isolation and Culture of Microglia
Bohlen, C. J., Bennett, F. C., & Bennett, M. L. (2018) · Current Protocols in Immunology · doi:10.1002/cpim.70 · Cited by 118
GABAergic‐astrocyte signaling: A refinement of inhibitory brain networks
Mederos, S., & Perea, G. (2019) · Glia · doi:10.1002/glia.23644 · Cited by 117
FGF21 suppresses alcohol consumption through an amygdalo-striatal circuit
Flippo, K. H., Trammell, S. A. J., Gillum, M. P., Aklan, İ., Perez, M. B., Yavuz, Y., Smith, N. K., Jensen-Cody, S. O., Zhou, B., Claflin, K. E., et al. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2021.12.024 · Cited by 119
Make war not love: The neural substrate underlying a state-dependent switch in female social behavior
Liu, M., Kim, D.-W., Zeng, H., & Anderson, D. J. (2022) · Neuron · doi:10.1016/j.neuron.2021.12.002 · Cited by 118
Neuronal types in the mouse amygdala and their transcriptional response to fear conditioning
Hochgerner, H., Singh, S., Tibi, M., Lin, Z., Skarbianskis, N., Admati, I., Ophir, O., Reinhardt, N., Netser, S., Wagner, S., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01469-3 · Cited by 110
RDoC-based categorization of amygdala functions and its implications in autism
Hennessey, T., Andari, E., & Rainnie, D. G. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.04.007 · Cited by 107
Trans-Seq maps a selective mammalian retinotectal synapse instructed by Nephronectin
Tsai, N. Y., Wang, F., Toma, K., Chen, Y., Takatoh, J., Pai, E. L.-L., Wu, K., Matcham, A. C., Yin, L., Dang, E. J., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01068-8 · Cited by 97
Hypothalamic oestrogen receptor alpha establishes a sexually dimorphic regulatory node of energy expenditure
van Veen, J. E., Kammel, L. G., Bunda, P., Shum, M., Reid, M., Massa, M. G., Arneson, D. V., Park, J. W., Zhang, Z., Joseph, A., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-0189-6 · Cited by 93
Cortical Representations of Conspecific Sex Shape Social Behavior
Kingsbury, L., Huang, S., Raam, T., Ye, L. S., Don, W., Hu, R. K., Li, Y., & Hong, W. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.020 · Cited by 89
Self-citation
Differences in neurotropism and neurotoxicity among retrograde viral tracers
Sun, L., Tang, Y., Yan, K., Yu, J., Zou, Y., Xu, W., Xiao, K., Zhang, Z., Li, W., Wu, B., et al. (2019) · Molecular Neurodegeneration · doi:10.1186/s13024-019-0308-6 · Cited by 91
The cellular basis of distinct thirst modalities
Pool, A., Wang, T., Stafford, D. A., Chance, R. K., Lee, S., Ngai, J., & Oka, Y. (2020) · Nature · doi:10.1038/s41586-020-2821-8 · Cited by 92
Reciprocal activity of AgRP and POMC neurons governs coordinated control of feeding and metabolism
Solís, A. J. D., Río-Martín, A. D., Radermacher, J., Chen, W., Steuernagel, L., Bauder, C. A., Eggersmann, F. R., Morgan, D. A., Lena, C. A., Sue, M. W., et al. (2024) · Nature Metabolism · doi:10.1038/s42255-024-00987-z · Cited by 94
Social reprogramming in ants induces longevity-associated glia remodeling
Sheng, L., Shields, E. J., Gospočić, J., Glastad, K. M., Ratchasanmuang, P., Berger, S. L., Raj, A., Little, S. C., & Bonasio, R. (2020) · Science Advances · doi:10.1126/sciadv.aba9869 · Cited by 81
Transcriptomic atlas and interaction networks of brain cells in mouse CNS demyelination and remyelination
Hou, J., Zhou, Y., Cai, Z., Terekhova, M., Swain, A., Andhey, P. S., Guimaraes, R. M., Ulezko Antonova, A., Qiu, T., Sviben, S., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112293 · Cited by 85
Tanycyte-Independent Control of Hypothalamic Leptin Signaling
Yoo, S., Cha, D., Kim, D. W., Hoang, T. V., & Blackshaw, S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00240 · Cited by 82
Extensive and spatially variable within-cell-type heterogeneity across the basolateral amygdala
O’Leary, T. P., Sullivan, K. E., Wang, L., Clements, J., Lemire, A. L., & Cembrowski, M. S. (2020) · eLife · doi:10.7554/elife.59003 · Cited by 81
A transcriptional rheostat couples past activity to future sensory responses
Tsukahara, T., Brann, D. H., Pashkovski, S. L., Guitchounts, G., Bozza, T. C., & Datta, S. R. (2021) · Cell · doi:10.1016/j.cell.2021.11.022 · Cited by 77
Single cell transcriptomics in neuroscience: cell classification and beyond
Tasic, B. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.04.021 · Cited by 83
A novel environment-evoked transcriptional signature predicts reactivity in single dentate granule neurons
Jaeger, B. N., Linker, S. B., Parylak, S., Barron, J. J., Gallina, I. S., Saavedra, C. D., Fitzpatrick, C., Lim, C. K., Schafer, S. T., Lacar, B., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05418-8 · Cited by 83
Glial fibrillary acidic protein in Alzheimer’s disease: a narrative review
Leipp, F., Vialaret, J., Mohaupt, P., Coppens, S., Jaffuel, A., Niehoff, A., Lehmann, S., & Hirtz, C. (2024) · Brain Communications · doi:10.1093/braincomms/fcae396 · Cited by 88
Exercise-induced angiogenesis is dependent on metabolically primed ATF3/4+ endothelial cells
Fan, Z., Turiel, G., Ardicoglu, R., Ghobrial, M., Masschelein, E., Kocijan, T., Zhang, J., Tan, G., Fitzgerald, G., Gorski, T., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.07.015 · Cited by 82
Large-Scale Integration of Single-Cell RNA-Seq Data Reveals Astrocyte Diversity and Transcriptomic Modules across Six Central Nervous System Disorders
Qian, Z., Qin, J., Lai, Y., Zhang, C., & Zhang, X. (2023) · Biomolecules · doi:10.3390/biom13040692 · Cited by 81
An Activity-Mediated Transition in Transcription in Early Postnatal Neurons
Stroud, H., Yang, M. G., Tsitohay, Y. N., Davis, C. P., Sherman, M. A., Hrvatin, S., Ling, E., & Greenberg, M. E. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.008 · Cited by 78
Macrophage heterogeneity in the single-cell era: facts and artifacts
Hume, D. A., Millard, S. M., & Pettit, A. R. (2023) · Blood · doi:10.1182/blood.2023020597 · Cited by 83
Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses
O'Toole, S. M., Oyibo, H. K., & Keller, G. B. (2023) · Neuron · doi:10.1016/j.neuron.2023.08.015 · Cited by 103
Common cell type nomenclature for the mammalian brain
Miller, J. A., Gouwens, N. W., Tasic, B., Collman, F., van Velthoven, C. T. J., Bakken, T. E., Hawrylycz, M., Zeng, H., Lein, E. S., & Bernard, A. (2020) · eLife · doi:10.7554/elife.59928 · Cited by 75
Genome-Wide Analysis of Differential Gene Expression and Splicing in Excitatory Neurons and Interneuron Subtypes
Huntley, M. A., Srinivasan, K., Friedman, B. A., Wang, T.-M., Yee, A. X., Wang, Y., Kaminker, J. S., Sheng, M., Hansen, D. V., & Hanson, J. E. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.1615-19.2019 · Cited by 69
CSF1R inhibition rescues tau pathology and neurodegeneration in an A/T/N model with combined AD pathologies, while preserving plaque associated microglia
Lodder, C., Scheyltjens, I., Stancu, I., Lucena, P. B., de Ravé, M. G., Vanherle, S., Vanmierlo, T., Cremers, N., Vanrusselt, H., Brône, B., et al. (2021) · Acta Neuropathologica Communications · doi:10.1186/s40478-021-01204-8 · Cited by 71
Molecular and cellular evolution of the amygdala across species analyzed by single-nucleus transcriptome profiling
Yu, B., Zhang, Q., Lin, L., Zhou, X., Ma, W., Wen, S., Li, C., Wang, W., Wu, Q., Wang, X., et al. (2023) · Cell Discovery · doi:10.1038/s41421-022-00506-y · Cited by 80
Self-citation
Heterogeneity of Satellite Cells Implicates DELTA1/NOTCH2 Signaling in Self-Renewal
Yartseva, V., Goldstein, L. D., Rodman, J., Kates, L., Chen, M. Z., Chen, Y.-J. J., Foreman, O., Siebel, C. W., Modrusan, Z. D., Peterson, A. S., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2019.12.100 · Cited by 75

Authors: Wu, Y. E., Pan, L., Zuo, Y., Li, X., & Hong, W.
Affiliations: University of California, Los Angeles (US)
Corresponding author: Hong, Weizhe
ORCID: Wu, Ye Emily
Pan, Lin
Zuo, Yanning
Li, Xinmin
Hong, Weizhe
Venue: Neuron
Publisher: Elsevier BV
Published: 2017-10
Volume: 96
Issue: 2
Pages: 313-329.e6
ISSN: 0896-6273 (ISSN-L)
DOI: 10.1016/j.neuron.2017.09.026
OpenAlex: W2762506555
Cited by: 438
References: 62
Citations by year: 2026: 33 · 2025: 43 · 2024: 37 · 2023: 65 · 2022: 83 · 2021: 64 · 2020: 50 · 2019: 39 · 2018: 22 · 2017: 2
FWCI: 12.63
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 375 d)
Locations: Neuron (publishedVersion)
PubMed (publishedVersion)
Funders: Whitehall Foundation
NARSAD Young Investigator
Searle Scholars Award
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords: single-cell RNA sequencing, seizure-induced gene expression, acute stress response, cholecystokinin, neuronal subpopulations
MeSH terms: Amygdala, Animals, Male, Mice, Inbred C57BL, Organ Culture Techniques, Sequence Analysis, RNA, Mice, Single-Cell Analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Detecting Activated Cell Populations Using Single-Cell RNA-Seq

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks