Evolution of pallium, hippocampus, and cortical cell types revealed by single-cell transcriptomics in reptiles
Abstract
Evolution of the brain: Just how related are reptilian and mammalian brains? Tosches et al. used single-cell transcriptomics to study turtle, lizard, mouse, and human brain samples. They assessed how the mammalian six-layered cortex might be derived from the reptilian three-layered cortex. Despite a lack of correspondence between layers, mammalian astrocytes and adult neural stem cells shared evolutionary origins. General classes of interneuron types were represented across the evolutionary span, although subtypes were species-specific. Pieces of the much-folded mammalian hippocampus were represented as adjacent fields in the reptile brains. Science , this issue p. 881
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
The reptilian cortex contains interneurons that are transcriptionally similar to the major classes of mammalian cortical interneurons.
“the reptilian cortex contains interneurons that exhibit transcriptional similarities with the major classes of cortical interneurons described mammals”
From Development and Functional Diversification of Cortical Interneurons (2018) · cites this paper as Tosches et al., 2018
There is no evidence for further diversification among GABAergic interneurons in the reptilian cortex.
“there is no evidence for further diversification among GABAergic interneurons in the reptilian cortex”
From Development and Functional Diversification of Cortical Interneurons (2018) · cites this paper as Tosches et al., 2018
At least the major interneuron types existed in the common ancestor of reptiles and mammals.
“which suggest that at least these types of interneuron existed in the ancestor of reptiles and mammals”
From Development and Functional Diversification of Cortical Interneurons (2018) · cites this paper as Tosches et al., 2018
New interneuron types in mammals probably arose through diversification of ancestral gene regulatory programs.
“the generation of new types of interneuron in mammals probably arise through the diversification of the ancestral generegulatory programs”
From Development and Functional Diversification of Cortical Interneurons (2018) · cites this paper as Tosches et al., 2018
Cites
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 · see citing works
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · see citing works
GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits
Tremblay, R., Lee, S., & Rudy, B. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.033 · Cited by 2,033 · see citing works
Shared and distinct transcriptomic cell types across neocortical areas
Tasic, B., Yao, Z., Graybuck, L. T., Smith, K. A., Nguyen, T. N., Bertagnolli, D., Goldy, J., Garren, E., Economo, M. N., Viswanathan, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0654-5 · Cited by 1,746 · see citing works
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
Tasic, B., Menon, V., Nguyen, T. N., Kim, T. K., Jarsky, T., Yao, Z., Levi, B., Gray, L. T., Sorensen, S. A., Dolbeare, T., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4216 · Cited by 1,714 · see citing works
Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics
Shekhar, K., Lapan, S. W., Whitney, I. E., Tran, N. M., Macosko, E. Z., Kowalczyk, M., Adiconis, X., Levin, J. Z., Nemesh, J., Goldman, M., et al. (2016) · Cell · doi:10.1016/j.cell.2016.07.054 · Cited by 1,176 · see citing works
Molecular diversity of midbrain development in mouse, human, and stem cells
La Manno, G., Gyllborg, D., Codeluppi, S., Nishimura, K., Salto, C., Zeisel, A., Borm, L. E., Stott, S. R. W., Toledo, E. M., Villaescusa, J. C., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.027 · Cited by 835 · see citing works
Canonical genetic signatures of the adult human brain
Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., Jegga, A. G., Aronow, B. J., Lee, C.-K., Bernard, A., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4171 · Cited by 663 · see citing works
Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons
Habib, N., Li, Y., Heidenreich, M., Swiech, L., Avraham-Davidi, I., Trombetta, J. J., Hession, C., Zhang, F., & Regev, A. (2016) · Science · doi:10.1126/science.aad7038 · Cited by 601 · see citing works
Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation
Kolodziejczyk, A. A., Kim, J. K., Tsang, J. C. H., Ilicic, T., Henriksson, J., Natarajan, K. N., Tuck, A. C., Gao, X., Bühler, M., Liu, P., et al. (2015) · Cell Stem Cell · doi:10.1016/j.stem.2015.09.011 · Cited by 570 · see citing works
Neocortical Evolution: Neuronal Circuits Arise Independently of Lamination
Karten, H. J. (2013) · Current Biology · doi:10.1016/j.cub.2012.11.013 · Cited by 126 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Integrative single-cell analysis
Stuart, T., & Satija, R. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0093-7 · Cited by 1,460 · see citing works
Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity
Welch, J. D., Kozareva, V., Ferreira, A., Vanderburg, C., Martin, C., & Macosko, E. Z. (2019) · Cell · doi:10.1016/j.cell.2019.05.006 · Cited by 1,193 · see citing works
Construction of a human cell landscape at single-cell level
Han, X., Zhou, Z., Fei, L., Sun, H., Wang, R., Chen, Y., Chen, H., Wang, J., Tang, H., Ge, W., et al. (2020) · Nature · doi:10.1038/s41586-020-2157-4 · Cited by 1,087 · see citing works
Comparative cellular analysis of motor cortex in human, marmoset and mouse
Bakken, T. E., Jorstad, N. L., Hu, Q., Lake, B. B., Tian, W., Kalmbach, B. E., Crow, M., Hodge, R. D., Krienen, F. M., Sorensen, S. A., et al. (2021) · Nature · doi:10.1038/s41586-021-03465-8 · Cited by 812 · see citing works
Development and Functional Diversification of Cortical Interneurons
Lim, L., Mi, D., Llorca, A., & Marín, O. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.009 · Cited by 714 · see citing works
“Consistent with this idea, recent work has revealed that the reptilian cortex contains interneurons that exhibit transcriptional similarities with the major classes of cortical interneurons described mammals (Tosches et al., 2018), which suggest that at least these types of interneuron existed in the ancestor of repti…”
InfluentialWhat is a cell type and how to define it?
Zeng, H. (2022) · Cell · doi:10.1016/j.cell.2022.06.031 · Cited by 439 · see citing works
Architectures of neuronal circuits
Luo, L. (2021) · Science · doi:10.1126/science.abg7285 · Cited by 390 · see citing works
Innovations present in the primate interneuron repertoire
Krienen, F. M., Goldman, M., Zhang, Q., C. H. del Rosario, R., Florio, M., Machold, R., Saunders, A., Levandowski, K., Zaniewski, H., Schuman, B., et al. (2020) · Nature · doi:10.1038/s41586-020-2781-z · Cited by 381 · see citing works
Innovations in Primate Interneuron Repertoire
Krienen, F. M., Goldman, M., Zhang, Q., del Rosario, R., Florio, M., Machold, R., Saunders, A., Levandowski, K., Zaniewski, H., Schuman, B., et al. (2019) · doi:10.1101/709501 · Cited by 372 · see citing works
The diversity of GABAergic neurons and neural communication elements
Huang, Z. J., & Paul, A. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0195-4 · Cited by 201 · see citing works
Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains
Khrameeva, E., Kurochkin, I., Han, D., Guijarro, P., Kanton, S., Santel, M., Qian, Z., Rong, S., Mazin, P., Sabirov, M., et al. (2020) · Genome Research · doi:10.1101/gr.256958.119 · Cited by 162 · see citing works
Pessoa, L., Medina, L., Hof, P. R., & Desfilis, E. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.09.021 · Cited by 105 · see citing works
Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse
Bakken, T. E., Jorstad, N. L., Hu, Q., Lake, B. B., Tian, W., Kalmbach, B. E., Crow, M., Hodge, R. D., Krienen, F. M., Sorensen, S. A., et al. (2020) · doi:10.1101/2020.03.31.016972 · Cited by 809 · see citing works
In search of common developmental and evolutionary origin of the claustrum and subplate
Bruguier, H., Suarez, R., Manger, P., Hoerder‐Suabedissen, A., Shelton, A. M., Oliver, D. K., Packer, A. M., Ferran, J. L., García‐Moreno, F., Puelles, L., et al. (2020) · Journal of Comparative Neurology · doi:10.1002/cne.24922 · Cited by 84 · see citing works
Dual midbrain and forebrain origins of thalamic inhibitory interneurons
Jager, P., Moore, G., Calpin, P., Durmishi, X., Salgarella, I., Menage, L., Kita, Y., Wang, Y., Kim, D. W., Blackshaw, S., et al. (2021) · eLife · doi:10.7554/elife.59272 · Cited by 61 · see citing works
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 · see citing works
Self-citationStructure, biophysics, and circuit function of a “giant” cortical presynaptic terminal
Vandael, D., & Jonas, P. (2024) · Science · doi:10.1126/science.adg6757 · Cited by 45 · see citing works
A community-based transcriptomics classification and nomenclature of neocortical cell types
Yuste, R., Hawrylycz, M., Aalling, N., Aguilar-Valles, A., Arendt, D., Armañanzas, R., Ascoli, G. A., Bielza, C., Bokharaie, V., Bergmann, T. B., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0685-8 · Cited by 32 · see citing works
Self-citationRamirez, M. D., Bui, T. N., & Katz, P. S. (2024) · Journal of Comparative Neurology · doi:10.1002/cne.25628 · Cited by 10 · see citing works
Hierarchical sensory processing in zebrafish thalamocortical-like circuits
Trinh, A.-T., Ostenrath, A. M., del Castillo-Berges, I., Cachin, F., Koç, M., Kraus, S., Serneels, B., Kawakami, K., & Yaksi, E. (2026) · Science · doi:10.1126/science.aec2171 · Cited by 5 · see citing works
- Authors
- Tosches, M. A., Yamawaki, T. M., Naumann, R. K., Jacobi, A. A., Tushev, G., & Laurent, G.
- Affiliations
- Max Planck Institute for Brain Research (DE)
- Corresponding author
- Tosches, Maria Antonietta
- Yamawaki, Tracy M.
- Laurent, Gilles
- ORCID
- Venue
- Science
- Published
- 2018-05-25
- Volume
- 360
- Issue
- 6391
- Pages
- 881-888
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2801175520
- Semantic Scholar
- f1aa8ef0833383ff12bf092eb6fa0a45228c8050
- Cited by
- 506
- References
- 11
- Citations by year
- 2026: 45 · 2025: 62 · 2024: 69 · 2023: 55 · 2022: 77 · 2021: 80 · 2020: 62 · 2019: 44 · 2018: 12
- FWCI
- 18.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- European Research Council (322705)
- Max Plank Society
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- pallium, hippocampus, cortical cell types, glutamatergic neurons, GABAergic interneurons, reptile brain evolution, gene regulatory programs, gene expression atlas, single-cell transcriptomics
- MeSH terms
- Animals, Biological Evolution, Hippocampus, Neuroglia, Neurons, Reptiles, Neocortex, Gene Expression Profiling, Cell Tracking, Single-Cell Analysis, GABAergic Neurons
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