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Conserved cell types with divergent features in human versus mouse cortex
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Abstract
Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.
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“As a third example of the great elaboration and specialization associated with consciousness, the more-advanced animal brains have the largest numbers of neuron types, with highly complex interactions (Strausfeld, 2012; Feinberg and Mallatt, 2016a; Hodge et al., 2019).”
From Phenomenal Consciousness and Emergence: Eliminating the Explanatory Gap (2020) · cites this paper as Hodge et al., 2019
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“nuclei were sorted using a standard gating strategy to exclude multiplets24”
From Integrated multimodal cell atlas of Alzheimer’s disease (2024) · cites this paper as [24]
In the citing paper
“8 out of 14 modules showed greater intra-module correlation than a comparable random gene set in the adult human brain dataset from Hodge et al (30) (Fig. 4B).”
From In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes (2020) · cites this paper as [30]
In the citing paper
“In addition, multiplex FISH is already being used to measure the proportions of transcriptomic types within a given brain tissue (Hodge et al., 2019; Moffitt et al., 2018; Zhang et al., 2020).”
From Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells (2020) · cites this paper as Hodge et al., 2019
In the citing paper
“Single-cell RNA-sequencing (scRNA-seq) studies have systematically characterized and classified cell types in individual regions of isocortex and hippocampus”
From A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“The application of single-cell RNA sequencing (scRNA-seq) to the neocortex and other brain regions has revealed a complex but tractable hierarchical organization of transcriptomic cell types that are consistent overall with knowledge from decades of anatomical, physiological and developmental studies but with an unmatched level of granularity7–11.”
From A multimodal cell census and atlas of the mammalian primary motor cortex (2021) · cites this paper as [10]
In the citing paper
“Substantiating previous studies9,10, our multimodal cross-species study of the primary motor cortex suggests that a general principle of cortical cell-type organization is its hierarchical relationship, whereby high-level classes linked by major branches comprise progressively finer subpopulations connected by minor branches.”
From A multimodal cell census and atlas of the mammalian primary motor cortex (2021) · cites this paper as [10]
In the citing paper
“Comparing human with mouse and non-human primates reveals both conserved and distinct cell type signatures, including species-specific differences in the proportions of cell populations and in gene expression within homologous cell classes and types (Bakken et al., 2020; Hodge et al., 2019; Krienen et al., 2020).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“Evolutionary conservation and divergence provide insight into the gene regulatory programs that were selected for their impact on cognitive function (Bakken et al., 2020; Hodge et al., 2019; Krienen et al., 2020).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“We observed numerous genes with categorical changes in cell-type-specific expression patterns (including NTNG1, IQGAP2 and TRPC3) and, in rare cases, genes that were a specific marker in one cell class in some species but not detected at all in the interneurons of the other species11”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“which suggests that the genes that encode these markers stably delineate a core repertoire of neocortical interneuron types in these species11,15,18”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“The expansion of this LAMP5+ LHX6+ cell type throughout the neocortex in diverse primates probably explains a recent observation11 that this cell type is much more abundant in the human temporal lobe than in the mouse V1.”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“they obtained 45 human interneuron clusters, whereas our marmoset data resolved to 22 clusters”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“However, in agreement with other reports11, these types were inconsistently observed across individual animals and regions, likely due to laminar location and low abundance, and were not analysed further.”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“Notably, this approach provides the means to evaluate and compare the circuit contributions and function of PV cINs across species, regardless of their genetic accessibility44,45.”
From Viral manipulation of functionally distinct interneurons in mice, non-human primates and humans (2020) · cites this paper as [44]
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Defining the Homo- and Heterodimerization Propensities of Metabotropic Glutamate Receptors
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“A recent scRNA-seq study comparing human and mouse cortical expression patterns (Hodge et al., 2019) found high conservation of cell types but divergence in expression patterns for many signaling proteins, motivating future analysis of human mGluR expression patterns.”
Kim, M., Haney, J. R., Zhang, P., Hernandez, L. M., Wang, L.-K., Pérez‐Cano, L., Loohuis, L. M. O., de la Torre-Ubieta, L., & Gandal, M. J. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00847-z · Cited by 76
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A Connectomic Hypothesis for the Hominization of the Brain
Changeux, J., Goulas, A., & Hilgetag, C. C. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa365 · Cited by 80
“looks remarkably similar from mice to humans (Hodge et al. 2019).”
BackgroundEpigenomic diversity of cortical projection neurons in the mouse brain
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Bombesin-Like Peptide Recruits Disinhibitory Cortical Circuits and Enhances Fear Memories
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Dentate gyrus astrocytes exhibit layer-specific molecular, morphological and physiological features
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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
“However, the recent application of high-throughput, quantitative methods such as single-cell or -nucleus transcriptomics (scRNAseq) (Hodge et al., 2019; Macosko et al., 2015; Saunders et al., 2018; Tasic et al., 2018; Tasic et al., 2016; Zeisel et al., 2018, Zeisel et al., 2015), electron microscopy (Zheng et al.”
BackgroundMethodInfluentialSelf-citationThe regulation of cortical neurogenesis
Villalba, A., Götz, M., & Borrell, V. (2020) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2020.10.003 · Cited by 80
Modelling epilepsy in the mouse: challenges and solutions
Marshall, G. F., Gonzalez‐Sulser, A., & Abbott, C. M. (2021) · Disease Models & Mechanisms · doi:10.1242/dmm.047449 · Cited by 80
Molecular features driving cellular complexity of human brain evolution
Caglayan, E., Ayhan, F., Liu, Y., Vollmer, R. M., Oh, E., Sherwood, C. C., Preuss, T. M., Yi, S. V., & Konopka, G. (2023) · Nature · doi:10.1038/s41586-023-06338-4 · Cited by 68
Human microglia maturation is underpinned by specific gene regulatory networks
Han, C. Z., Li, R. Z., Hansen, E., Trescott, S., Fixsen, B. R., Nguyen, C. T., Mora, C. M., Spann, N. J., Bennett, H. R., Poirion, O., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.07.016 · Cited by 84
Interindividual variation in human cortical cell type abundance and expression
Johansen, N., Somasundaram, S., Travaglini, K. J., Yanny, A. M., Shumyatcher, M., Casper, T., Cobbs, C., Dee, N., Ellenbogen, R. G., Ferreira, M. L., et al. (2023) · Science · doi:10.1126/science.adf2359 · Cited by 74
“Studies involving relatively few ( n = 3 to 8) healthy adult humans have shown strong interindividual concordance in the cortex because all cell types include representation from multiple donors without the need to explicitly account for donor of origin in the analysis ( 14 , 15 ).”
BackgroundInfluentialSelf-citationWang, M., Zhang, L., Novak, S. W., Yu, J., Gallina, I. S., Xu, L. L., Lim, C. K., Fernandes, S., Shokhirev, M. N., Williams, A. E., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02157-8 · Cited by 78
“…expressed many astrocyte markers, including GFAP, S100B, CD44 and AQP4, and showed increased expression of GFAP, AQP4, ID1 and ID3 compared to cortical astrocytes, resembling the expression profiles of subpial astrocytes observed in mice 46,47 and interlaminar astrocytes reported in humans 48,49 .”
Contrasting somatic mutation patterns in aging human neurons and oligodendrocytes
Ganz, J., Luquette, L. J., Bizzotto, S., Miller, M. B., Zhou, Z., Bohrson, C. L., Jin, H., Tran, A. V., Viswanadham, V., McDonough, G. A., et al. (2024) · Cell · doi:10.1016/j.cell.2024.02.025 · Cited by 77
Amyloid Cascade Hypothesis for the Treatment of Alzheimer’s Disease: Progress and Challenges
Wu, T., Ding, L., Cheng, Y., Jiang, S., Riaz, M. W., Fu, N., Mou, C., Ye, M., & Zheng, Y. (2022) · Aging and Disease · doi:10.14336/ad.2022.0412 · Cited by 81
“The human cerebral cortex, compared with mice, possesses conservative basic structure and cortical development while the area and number of neurons increased 1,000fold [95-97].”
BackgroundYu, 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
Perspectives on defining cell types in the brain
Mukamel, E. A., & Ngai, J. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.11.007 · Cited by 56
X-chromosome regulation and sex differences in brain anatomy
Raznahan, A., & Distèche, C. M. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.10.024 · Cited by 69
Single cell atlas for 11 non-model mammals, reptiles and birds
Chen, D., Sun, J. G., Zhu, J., Ding, X., Lan, T., Wang, X., Wu, W., Ou, Z., Zhu, L., Ding, P., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27162-2 · Cited by 68
Gomez, S. T., Blonde, J. D., Mendoza-Halliday, D., Kuebler, E. S., Everest, M., Wang, X., Inoue, W., Poulter, M. O., & Martínez-Trujillo, J. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa056 · Cited by 68
“the features of the action potential across similar cell types have been preserved through evolution (Hodge et al. 2019).”
BackgroundGenome-wide association studies of antidepressant class response and treatment-resistant depression
Li, Q. S., Tian, C., Hinds, D. A., Agee, M., Alipanahi, B., Auton, A., Bell, R. K., Bryc, K., Elson, S. L., Fontanillas, P., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01035-6 · Cited by 73
A marmoset brain cell census reveals regional specialization of cellular identities
Krienen, F. M., Levandowski, K. M., Zaniewski, H., del Rosario, R. C. H., Schroeder, M. E., Goldman, M., Wienisch, M., Lutservitz, A., Beja-Glasser, V. F., Chen, C., et al. (2023) · Science Advances · doi:10.1126/sciadv.adk3986 · Cited by 67
Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortexPreprint
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Single-cell analysis reveals dynamic changes of neural cells in developing human spinal cord
Zhang, Q., Wu, X., Fan, Y., Jiang, P., Zhao, Y., Yang, Y., Han, S., Bai, X., Chen, B., Han, J., et al. (2021) · EMBO Reports · doi:10.15252/embr.202152728 · Cited by 70
“Cross-species analysis can reveal the homology and heterogeneity of neural cells between species (Yu et al , 2014; Hodge et al , 2019).”
Guet-McCreight, A., Skinner, F. K., & Topolnik, L. (2020) · Frontiers in Neural Circuits · doi:10.3389/fncir.2020.00032 · Cited by 66
“Notably, homologies in expression patterns were found in mouse visual cortex and lateral motor cortex, suggesting similar richness in VIP+ cell diversity across species and brain areas (Hodge et al., 2019).”
BackgroundSTAB: a spatio-temporal cell atlas of the human brain
Song, L., Pan, S., Zhang, Z.-C., Jia, L., Chen, W.-H., & Zhao, X. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa762 · Cited by 65
A molecular and cellular perspective on human brain evolution and tempo
Lindhout, F. W., Krienen, F. M., Pollard, K. S., & Lancaster, M. A. (2024) · Nature · doi:10.1038/s41586-024-07521-x · Cited by 80
The cell-type underpinnings of the human functional cortical connectome
Zhang, X.-H., Anderson, K. M., Dong, H.-M., Chopra, S., Dhamala, E., Emani, P. S., Gerstein, M., Margulies, D. S., & Holmes, A. J. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01812-2 · Cited by 67
Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns
Cui, Q., Pamukcu, A., Cherian, S., Chang, I. Y. M., Berceau, B. L., Xenias, H. S., Higgs, M. H., Rajamanickam, S., Chen, Y., Du, X., et al. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2210-20.2021 · Cited by 62
An update on human astrocytes and their role in development and disease
de Majo, M., Koontz, M., Rowitch, D. H., & Ullian, E. M. (2020) · Glia · doi:10.1002/glia.23771 · Cited by 69
“Human astrocytes further display a unique set of genes that, importantly, are enriched for disease associated pathways (Hawrylycz et al., 2015; Hodge et al., 2019; Zhang et al., 2016) these include: metabolism (e.g., BBOX1), Wnt signaling (e.g., Wif1), and Ca2+ signaling (e.g., RyR3).”
BackgroundGluN3A excitatory glycine receptors control adult cortical and amygdalar circuits
Bossi, S., Dhanasobhon, D., Ellis‐Davies, G. C. R., Frontera, J. L., van Velze, M. D. B., Lourenço, J., Murillo, A., Luján, R., Casado, M., Pérez‐Otaño, I., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.05.016 · Cited by 66
“GluN3A subunits are expressed in the human brain (Hodge et al., 2019), and alterations in the Grin3a gene have been associated with several neurological and psychiatric disorders, including schizophrenia, bipolar disorder, and epilepsy (Crawley et al., 2022; Mueller and Meador-Woodruff, 2004;…”
Temporally distinct 3D multi-omic dynamics in the developing human brain
Heffel, M. G., Zhou, J., Zhang, Y., Lee, D.-S., Hou, K., Pastor-Alonso, O., Abuhanna, K. D., Galasso, J., Kern, C., Tai, C., et al. (2024) · Nature · doi:10.1038/s41586-024-08030-7 · Cited by 75
“…single-cell 3C profiles by the distribution of the distance between interacting loci using k -means clustering and found that single brain cells range from mainly containing short-range interactions (clusters 1–5) to containing a substantial amount of long-range interactions (clusters 6–10; Fig.”
Leveraging the Cell Ontology to classify unseen cell types
Wang, S., Pisco, A. O., McGeever, A., Brbić, M., Žitnik, M., Darmanis, S., Leskovec, J., Karkanias, J., & Altman, R. B. (2021) · Nature Communications · doi:10.1038/s41467-021-25725-x · Cited by 87
“Since the Allen Ontology does not contain cell type text de fi nition, we still kept weights of all edges in the Allen Ontology as 1.”
BackgroundMethodInfluentialRich, S., Chameh, H. M., Lefebvre, J., & Valiante, T. A. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110863 · Cited by 70
Cell-type-specific effects of age and sex on human cortical neurons
Chien, J.-F., Liu, H., Wang, B.-A., Luo, C., Bartlett, A., Castanon, R., Johnson, N. D., Nery, J. R., Osteen, J. K., Li, J., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.05.013 · Cited by 72
Evolution of neuronal identity in the cerebral cortex
Tosches, M. A., & Laurent, G. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.04.009 · Cited by 57
Sleep down state-active ID2/Nkx2.1 interneurons in the neocortex
Valero, M., Viney, T. J., Machold, R. P., Mederos, S., Zutshi, I., Schuman, B., Senzai, Y., Rudy, B., & Buzsáki, G. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00797-6 · Cited by 64
The evolution of the human brain and disease susceptibility
Pattabiraman, K., Muchnik, S. K., & Šestan, N. (2020) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2020.05.004 · Cited by 61
Roberts, C., Sahakian, B. J., & Robbins, T. W. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.001 · Cited by 63
Neuro-consequences of the spaceflight environment
Mhatre, S. D., Iyer, J. S., Puukila, S., Paul, A. M., Tahimic, C. G. T., Rubinstein, L., Lowe, M. G., Alwood, J. S., Sowa, M. B., Bhattacharya, S., et al. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.09.055 · Cited by 63
de Almeida, G. M., Souza, J. D. P., Mendes, N. D., Pontelli, M. C., Pinheiro, N. R., Nogueira, G. O., Cardoso, R. D. S., Paiva, I. M., Ferrari, G. D., Veras, F. P., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.674576 · Cited by 65
“Despite the importance of rodent-based models in neurosciences, rodent and human brains have major biochemical and functional differences that limit the use of mouse or rat brain models in translational neuroscience (Miller et al., 2010; Hodge et al., 2019).”
BackgroundSpatial transcriptomics in neuroscience
Jung, N., & Kim, T.-K. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-01093-y · Cited by 65
“In the past decade, a plethora of literature has reported diversely classi fi ed cell types in mouse and human brain tissues using single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) 3 – 7 .”
BackgroundLiu, Z., Zhang, S., James, B. T., Galani, K., Mangan, R. J., Fass, S. B., Liang, C., Wagle, M. M., Boix, C. A., Tanigawa, Y., et al. (2025) · Cell · doi:10.1016/j.cell.2025.06.031 · Cited by 75
An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types
Yao, Z., Liu, H., Xie, F., Fischer, S., Booeshaghi, A. S., Adkins, R. S., Aldridge, A. I., Ament, S. A., Pinto-Duarte, A., Bartlett, A., et al. (2020) · doi:10.1101/2020.02.29.970558 · Cited by 397
Self-citationLochocki, B., Boon, B. D. C., Verheul, S. R., Zada, L., Hoozemans, J. J. M., Ariese, F., & de Boer, J. F. (2021) · Communications Biology · doi:10.1038/s42003-021-01981-x · Cited by 61
A reference single-cell regulomic and transcriptomic map of cynomolgus monkeys
Qu, J., Yang, F., Zhu, T., Wang, Y., Fang, W., Ding, Y., Zhao, X. F., Qi, X., Xie, Q.-M., Chen, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31770-x · Cited by 62
Pushing the boundaries of brain organoids to study Alzheimer’s disease
Cerneckis, J., Bu, G., & Shi, Y. (2023) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2023.05.007 · Cited by 63
Expression and Function of GABA Receptors in Myelinating Cells
Serrano‐Regal, M. P., Bayón‐Cordero, L., Ordaz, R. P., Garay, E., Limón, A., Arellano, R. O., Matute, C., & Sánchez‐Gómez, M. V. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.00256 · Cited by 60
Bustos, F., Segarra-Fas, A., Nardocci, G., Cassidy, A., Antico, O., Davidson, L., Brandenburg, L., Macartney, T., Toth, R. L., Hastie, C. J., et al. (2020) · Developmental Cell · doi:10.1016/j.devcel.2020.09.025 · Cited by 58
“SMART-seq v4 RNA-Sequencing data from single nuclei within the human cortex was previously described (Hodge et al., 2019).”
MethodDefining the Teratoma as a Model for Multi-lineage Human Development
McDonald, D., Wu, Y., Dailamy, A., Tat, J., Parekh, U., Zhao, D., Hu, M. Y., Tipps, A. M. P., Zhang, K., & Mali, P. (2020) · Cell · doi:10.1016/j.cell.2020.10.018 · Cited by 60
“…aspects of development are highly species-specific, especially in neural development (Raff, 1996; Richardson et al., 1997; Fougerousse et al., 2000; Hodge et al., 2019) Although there have been studies of human embryonic development (Miller et al., 2014; Zhu et al., 2018), such studies are limited…”
Background
Metadata
- Authors
- Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., Yao, Z., Eggermont, J., Höllt, T., Levi, B. P., Shehata, S. I., Aevermann, B., Beller, A., Bertagnolli, D., Brouner, K., Casper, T., Cobbs, C., Dalley, R., Dee, N., Ding, S.-L., Ellenbogen, R. G., Fong, O., Garren, E., Goldy, J., Gwinn, R. P., Hirschstein, D., Keene, C. D., Keshk, M., Ko, A. L., Lathia, K., Mahfouz, A., Maltzer, Z., McGraw, M., Nguyen, T. N., Nyhus, J., Ojemann, J. G., Oldre, A., Parry, S., Reynolds, S., Rimorin, C., Shapovalova, N. V., Somasundaram, S., Szafer, A., Thomsen, E. R., Tieu, M., Quon, G., Scheuermann, R. H., Yuste, R., Sunkin, S. M., Lelieveldt, B., Feng, D., Ng, L., Bernard, A., Hawrylycz, M., Phillips, J. W., Tasic, B., Zeng, H., Jones, A. R., Koch, C., & Lein, E. S.
- Affiliations
- Allen Institute for Brain Science (US)
- University of California, Davis (US)
- Leiden University Medical Center (NL)
- J. Craig Venter Institute (US)
- University of Washington (US)
- Swedish Medical Center (US)
- Columbia University (US)
- Corresponding author
- Lein, Ed S.
- ORCID
- Hodge, Rebecca D.
- Bakken, Trygve E.
- Miller, Jeremy A.
- Smith, Kimberly A.
- Barkan, Eliza R.
- Graybuck, Lucas T.
- Close, Jennie L.
- Long, Brian
- Johansen, Nelson
- Yao, Zizhen
- Eggermont, Jeroen
- Höllt, Thomas
- Levi, Boaz P.
- Shehata, Soraya I.
- Aevermann, Brian
- Beller, Allison
- Bertagnolli, Darren
- Brouner, Krissy
- Casper, Tamara
- Cobbs, Charles
- Dalley, Rachel
- Dee, Nick
- Ding, Song-Lin
- Ellenbogen, Richard G.
- Fong, Olivia
- Goldy, Jeff
- Gwinn, Ryder P.
- Hirschstein, Daniel
- Keene, C. Dirk
- Ko, Andrew L.
- Lathia, Kanan
- Mahfouz, Ahmed
- Maltzer, Zoe
- Nguyen, Thuc Nghi
- Nyhus, Julie
- Ojemann, Jeffrey G.
- Oldre, Aaron
- Rimorin, Christine
- Shapovalova, Nadiya V.
- Somasundaram, Saroja
- Szafer, Aaron
- Thomsen, Elliot R.
- Tieu, Michael
- Quon, Gerald
- Scheuermann, Richard H.
- Yuste, Rafael
- Sunkin, Susan M.
- Lelieveldt, Boudewijn
- Feng, David
- Ng, Lydia
- Bernard, Amy
- Hawrylycz, Michael
- Phillips, John W.
- Tasic, Bosiljka
- Zeng, Hongkui
- Lein, Ed S.
- Venue
- Nature
- Published
- 2019-08-21
- Volume
- 573
- Issue
- 7772
- Pages
- 61-68
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6919571
- OpenAlex
- W2969948459
- Cited by
- 1,775
- References
- 89
- Citations by year
- 2026: 199 · 2025: 242 · 2024: 275 · 2023: 269 · 2022: 235 · 2021: 289 · 2020: 212 · 2019: 43
- FWCI
- 64.09
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- University of Washington
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (12720, 12721)
- National Institutes of Health (5u01mh114812-03, MH114812-02)
- National Institute of Mental Health (U01MH105982, U01MH114812, U19MH114830)
- National Institute of General Medical Sciences (T32GM008497)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- human cerebral cortex, middle temporal gyrus, cortical cell types, excitatory neurons, inhibitory neurons, single-nucleus RNA sequencing, human-mouse comparison, cortical laminar organization, species differences, neuronal morphology, gene expression
- MeSH terms
- RNA-Seq, Adolescent, Adult, Aged, Animals, Astrocytes, Cerebral Cortex, Biological Evolution, Female, Humans, Male, Middle Aged, Neural Inhibition, Neurons, Species Specificity, Principal Component Analysis, Mice, Young Adult, Single-Cell Analysis, Transcriptome
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