Single-cell transcriptomic analysis of mouse neocortical development
Open accessPublished version of a preprint
Abstract
The development of the mammalian cerebral cortex depends on careful orchestration of proliferation, maturation, and migration events, ultimately giving rise to a wide variety of neuronal and non-neuronal cell types. To better understand cellular and molecular processes that unfold during late corticogenesis, we perform single-cell RNA-seq on the mouse cerebral cortex at a progenitor driven phase (embryonic day 14.5) and at birth—after neurons from all six cortical layers are born. We identify numerous classes of neurons, progenitors, and glia, their proliferative, migratory, and activation states, and their relatedness within and across age. Using the cell-type-specific expression patterns of genes mutated in neurological and psychiatric diseases, we identify putative disease subtypes that associate with clinical phenotypes. Our study reveals the cellular template of a complex neurodevelopmental process, and provides a window into the cellular origins of brain diseases.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Previous studies mostly perform scRNA seq in younger mice, while single nucleus RNA sequencing is more common in adult mice.
“Previous studies mostly perform scRNA seq in younger mice, while single nucleus RNA sequencing is more common in adult mice (Hook et al., 2018;Loo et al., 2019;Zeisel et al., 2015;Zhou et al., 2020).”
From Single-cell resolution analysis of the crosstalk between chemogenically activated astrocytes and microglia (2020) · cites this paper as Loo et al., 2019
The Results section, “Single-cell transcriptomics of the E14.5 and P0 cortex” (page unavailable), confirms that this study used single-cell RNA sequencing in embryonic and newborn mice. The paper does not establish that previous studies mostly used younger mice or that single-nucleus sequencing was more common in adults; its Introduction also describes single-cell RNA-seq being used to catalog adult nervous-system cells. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease
Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.018 · Cited by 5,493 · see citing works
Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4178-07.2008 · Cited by 3,129 · 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
Genes and molecular pathways underpinning ciliopathies
Reiter, J. F., & Leroux, M. R. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.60 · Cited by 1,588 · see citing works
Transcriptional landscape of the prenatal human brain
Miller, J. A., Ding, S.-L., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Ebbert, A., Riley, Z. L., Royall, J. J., Aiona, K., et al. (2014) · Nature · doi:10.1038/nature13185 · Cited by 1,325 · 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
Pollen, A. A., Nowakowski, T. J., Shuga, J., Wang, X., Leyrat, A. A., Lui, J. H., Li, N., Szpankowski, L., Fowler, B., Chen, P., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2967 · Cited by 920 · see citing works
SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs)
Abrahams, B. S., Arking, D. E., Campbell, D. B., Mefford, H. C., Morrow, E. M., Weiss, L. A., Menashe, I., Wadkins, T., Banerjee-Basu, S., & Packer, A. (2013) · Molecular Autism · doi:10.1186/2040-2392-4-36 · Cited by 873 · see citing works
Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system
Sunkin, S. M., Ng, L., Lau, C., Dolbeare, T., Gilbert, T. L., Thompson, C. L., Hawrylycz, M., & Dang, C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1042 · Cited by 796 · see citing works
Developmental diversification of cortical inhibitory interneurons
Mayer, C., Hafemeister, C., Bandler, R. C., Machold, R., Batista Brito, R., Jaglin, X., Allaway, K., Butler, A., Fishell, G., & Satija, R. (2018) · Nature · doi:10.1038/nature25999 · Cited by 492 · see citing works
Nuclear RNA-seq of single neurons reveals molecular signatures of activation
Lacar, B., Linker, S. B., Jaeger, B. N., Krishnaswami, S. R., Barron, J. J., Kelder, M. J. E., Parylak, S. L., Paquola, A. C. M., Venepally, P., Novotny, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11022 · Cited by 405 · see citing works
Gonchar, Y. (2008) · Frontiers in Neuroanatomy · doi:10.3389/neuro.05.003.2007 · Cited by 369 · see citing works
Disentangling neural cell diversity using single-cell transcriptomics
Poulin, J.-F., Tasic, B., Hjerling-Leffler, J., Trimarchi, J. M., & Awatramani, R. (2016) · Nature Neuroscience · doi:10.1038/nn.4366 · Cited by 293 · see citing works
Pearson, B. L., Simon, J. M., McCoy, E. S., Salazar, G., Fragola, G., & Zylka, M. J. (2016) · Nature Communications · doi:10.1038/ncomms11173 · Cited by 127 · see citing works
Self-citationDecision making during interneuron migration in the developing cerebral cortex
Guo, J., & Anton, E. S. (2014) · Trends in Cell Biology · doi:10.1016/j.tcb.2013.12.001 · Cited by 104 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 51
- [1]Custo Greig LF Woodworth MB Galazo MJ Padmanabhan H Macklis JD Molecular logic of neocortical projection neuron specification, development and diversity Nat. Rev. Neurosci. 2013 14 755 769 10.1038/nrn3586 24105342 PMC3876965 · DOI · Paper page
- [2]Noctor SC Martinez-Cerdeno V Ivic L Kriegstein AR Cortical neurons arise in symmetric and asymmetric division zones and migrate through specific phases Nat. Neurosci. 2004 7 136 144 10.1038/nn1172 14703572 · DOI · Paper page
- [4]Polleux F Whitford KL Dijkhuizen PA Vitalis T Ghosh A Control of cortical interneuron migration by neurotrophins and PI3-kinase signaling Development 2002 129 3147 3160 12070090
- [6]de la Torre-Ubieta L Won H Stein JL Geschwind DH Advancing the understanding of autism disease mechanisms through genetics Nat. Med. 2016 22 345 361 10.1038/nm.4071 27050589 PMC5072455 · DOI · Paper page
- [7]Molyneaux BJ DeCoN: genome-wide analysis of in vivo transcriptional dynamics during pyramidal neuron fate selection in neocortex Neuron 2015 85 275 288 10.1016/j.neuron.2014.12.024 25556833 PMC4430475 · DOI
- [8]Bakken TE A comprehensive transcriptional map of primate brain development Nature 2016 535 367 375 10.1038/nature18637 27409810 PMC5325728 · DOI
- [11]Macosko EZ Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets Cell 2015 161 1202 1214 10.1016/j.cell.2015.05.002 26000488 PMC4481139 · DOI · Paper page
- [13]Chen R Wu X Jiang L Zhang Y Single-cell RNA-seq reveals hypothalamic cell diversity Cell Rep. 2017 18 3227 3241 10.1016/j.celrep.2017.03.004 28355573 PMC5782816 · DOI · Paper page
- [14]Lake BB Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain Nat. Biotechnol. 2018 36 70 80 10.1038/nbt.4038 29227469 PMC5951394 · DOI · Paper page
- [15]Sathyamurthy A Massively parallel single nucleus transcriptional profiling defines spinal cord neurons and their activity during behavior Cell Rep. 2018 22 2216 2225 10.1016/j.celrep.2018.02.003 29466745 PMC5849084 · DOI · Paper page
- [16]Zylka MJ Simon JM Philpot BD Gene length matters in neurons Neuron 2015 86 353 355 10.1016/j.neuron.2015.03.059 25905808 PMC4584405 · DOI
- [17]Molyneaux BJ Arlotta P Menezes JR Macklis JD Neuronal subtype specification in the cerebral cortex Nat. Rev. Neurosci. 2007 8 427 437 10.1038/nrn2151 17514196 · DOI
- [19]Molyneaux BJ Arlotta P Hirata T Hibi M Macklis JD Fezl is required for the birth and specification of corticospinal motor neurons Neuron 2005 47 817 831 10.1016/j.neuron.2005.08.030 16157277 · DOI
- [20]Elsen GE The protomap is propagated to cortical plate neurons through an Eomes-dependent intermediate map Proc. Natl Acad. Sci. USA 2013 110 4081 4086 10.1073/pnas.1209076110 23431145 PMC3593833 · DOI · Paper page
- [21]Zhao F Lufkin T Gelb BD Expression of Tfap2d, the gene encoding the transcription factor Ap-2 delta, during mouse embryogenesis Gene. Expr. Patterns 2003 3 213 217 10.1016/S1567-133X(02)00067-4 12711551 · DOI
- [24]Gao Z Neurod1 is essential for the survival and maturation of adult-born neurons Nat. Neurosci. 2009 12 1090 1092 10.1038/nn.2385 19701197 PMC3365543 · DOI · Paper page
- [25]Chen YJ Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types Sci. Rep. 2017 7 45656 10.1038/srep45656 28361918 PMC5374502 · DOI
- [26]Englund C Pax6, Tbr2, and Tbr1 are expressed sequentially by radial glia, intermediate progenitor cells, and postmitotic neurons in developing neocortex J. Neurosci. 2005 25 247 251 10.1523/JNEUROSCI.2899-04.2005 15634788 PMC6725189 · DOI · Paper page
- [27]Wiegreffe C Bcl11a (Ctip1) Controls Migration of Cortical Projection Neurons through Regulation of Sema3c Neuron 2015 87 311 325 10.1016/j.neuron.2015.06.023 26182416 · DOI
- [28]Goebbels S Genetic targeting of principal neurons in neocortex and hippocampus of NEX-Cre mice Genesis 2006 44 611 621 10.1002/dvg.20256 17146780 · DOI
- [29]Inta D Neurogenesis and widespread forebrain migration of distinct GABAergic neurons from the postnatal subventricular zone Proc. Natl Acad. Sci. USA 2008 105 20994 20999 10.1073/pnas.0807059105 19095802 PMC2605417 · DOI
- [30]Khodosevich K Seeburg PH Monyer H Major signaling pathways in migrating neuroblasts Front. Mol. Neurosci. 2009 2 7 10.3389/neuro.02.007.2009 19668709 PMC2724029 · DOI
- [32]Tamura K Insulin-like growth factor binding protein-7 (IGFBP7) blocks vascular endothelial cell growth factor (VEGF)-induced angiogenesis in human vascular endothelial cells Eur. J. Pharmacol. 2009 610 61 67 10.1016/j.ejphar.2009.01.045 19374835 · DOI
- [33]Kriegstein A Alvarez-Buylla A The glial nature of embryonic and adult neural stem cells Annu. Rev. Neurosci. 2009 32 149 184 10.1146/annurev.neuro.051508.135600 19555289 PMC3086722 · DOI · Paper page
- [34]Sahara S Yanagawa Y O’Leary DD Stevens CF The fraction of cortical GABAergic neurons is constant from near the start of cortical neurogenesis to adulthood J. Neurosci. 2012 32 4755 4761 10.1523/JNEUROSCI.6412-11.2012 22492031 PMC3325497 · DOI · Paper page
- [35]Zeisel A Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq Science 2015 347 1138 1142 10.1126/science.aaa1934 25700174 · DOI · Paper page
- [36]Frantz GD Bohner AP Akers RM McConnell SK Regulation of the POU domain gene SCIP during cerebral cortical development J. Neurosci. 1994 14 472 485 10.1523/JNEUROSCI.14-02-00472.1994 7905511 PMC6576830 · DOI
- [37]Telley L Sequential transcriptional waves direct the differentiation of newborn neurons in the mouse neocortex Science 2016 351 1443 1446 10.1126/science.aad8361 26940868 · DOI
- [38]Pollen AA Molecular identity of human outer radial glia during cortical development Cell 2015 163 55 67 10.1016/j.cell.2015.09.004 26406371 PMC4583716 · DOI · Paper page
- [39]Nowakowski TJ Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex Science 2017 358 1318 1323 10.1126/science.aap8809 29217575 PMC5991609 · DOI · Paper page
- [40]Workman AD Charvet CJ Clancy B Darlington RB Finlay BL Modeling transformations of neurodevelopmental sequences across mammalian species J. Neurosci. 2013 33 7368 7383 10.1523/JNEUROSCI.5746-12.2013 23616543 PMC3928428 · DOI · Paper page
- [41]Otis EM Brent R Equivalent ages in mouse and human embryos Anat. Rec. 1954 120 33 63 10.1002/ar.1091200104 13207763 · DOI
- [44]Hodge RD Tbr2 expression in Cajal-Retzius cells and intermediate neuronal progenitors is required for morphogenesis of the dentate gyrus J. Neurosci. 2013 33 4165 4180 10.1523/JNEUROSCI.4185-12.2013 23447624 PMC3623668 · DOI
- [45]Gu X Inducible genetic lineage tracing of cortical hem derived Cajal-Retzius cells reveals novel properties PLoS. ONE. 2011 6 e28653 10.1371/journal.pone.0028653 22174859 PMC3236758 · DOI
- [47]Renton AE Chio A Traynor BJ State of play in amyotrophic lateral sclerosis genetics Nat. Neurosci. 2014 17 17 23 10.1038/nn.3584 24369373 PMC4544832 · DOI
- [48]Cuyvers E Sleegers K Genetic variations underlying Alzheimer’s disease: evidence from genome-wide association studies and beyond Lancet Neurol. 2016 15 857 868 10.1016/S1474-4422(16)00127-7 27302364 · DOI
- [51]Guo J Developmental disruptions underlying brain abnormalities in ciliopathies Nat. Commun. 2015 6 7857 10.1038/ncomms8857 26206566 PMC4515781 · DOI
- [53]Jay TR Disease Progression-Dependent Effects of TREM2 Deficiency in a Mouse Model of Alzheimer’s Disease J. Neurosci. 2017 37 637 647 10.1523/JNEUROSCI.2110-16.2016 28100745 PMC5242410 · DOI · Paper page
- [55]Krishnan A Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder Nat. Neurosci. 2016 19 1454 1462 10.1038/nn.4353 27479844 PMC5803797 · DOI
- [56]Raj, B. et al. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat Biotechnol, 10.1038/nbt.4103 (2018). PMC5938111 29608178 · DOI
- [57]Biase FH Rainbow-Seq: Combining Cell Lineage Tracing with Single-Cell RNA Sequencing in Preimplantation Embryos iScience 2018 7 16 29 10.1016/j.isci.2018.08.009 30267678 PMC6135740 · DOI
- [58]Campbell JN A molecular census of arcuate hypothalamus and median eminence cell types Nat. Neurosci. 2017 20 484 496 10.1038/nn.4495 28166221 PMC5323293 · DOI · Paper page
- [59]Parikshak NN Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism Cell 2013 155 1008 1021 10.1016/j.cell.2013.10.031 24267887 PMC3934107 · DOI · Paper page
- [60]Willsey AJ Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism Cell 2013 155 997 1007 10.1016/j.cell.2013.10.020 24267886 PMC3995413 · DOI · Paper page
- [61]King IF Topoisomerases facilitate transcription of long genes linked to autism Nature 2013 501 58 62 10.1038/nature12504 23995680 PMC3767287 · DOI
- [63]Johnson WE Li C Rabinovic A Adjusting batch effects in microarray expression data using empirical Bayes methods Biostatistics 2007 8 118 127 10.1093/biostatistics/kxj037 16632515 · DOI · Paper page
- [64]Rousseeuw J Silhouettes P A graphical aid to the interpretation and validation of cluster analysis J. Comput. Appl. Math. 1987 20 53 65 10.1016/0377-0427(87)90125-7 · DOI · Paper page
- [65]Varemo L Nielsen J Nookaew I Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods Nucleic Acids Res. 2013 41 4378 4391 10.1093/nar/gkt111 23444143 PMC3632109 · DOI
- [67]Welch JD Hartemink AJ Prins JF SLICER: inferring branched, nonlinear cellular trajectories from single cell RNA-seq data Genome Biol. 2016 17 106 10.1186/s13059-016-0975-3 27215581 PMC4877799 · DOI
- [68]Chen J Xu H Aronow BJ Jegga AG Improved human disease candidate gene prioritization using mouse phenotype BMC Bioinforma. 2007 8 392 10.1186/1471-2105-8-392 PMC2194797 17939863 · DOI · Paper page
- [69]Street K Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics BMC Genom. 2018 19 477 10.1186/s12864-018-4772-0 PMC6007078 29914354 · DOI · Paper page
Cited by
Sorted by citations
A Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation
Polioudakis, D., de la Torre-Ubieta, L., Langerman, J., Elkins, A. G., Shi, X., Stein, J. L., Vuong, C. K., Nichterwitz, S., Gevorgian, M., Opland, C. K., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.06.011 · Cited by 513 · see citing works
Molecular logic of cellular diversification in the mouse cerebral cortex
Di Bella, D. J., Habibi, E., Stickels, R. R., Scalia, G., Brown, J., Yadollahpour, P., Yang, S. M., Abbate, C., Biancalani, T., Macosko, E. Z., et al. (2021) · Nature · doi:10.1038/s41586-021-03670-5 · Cited by 464 · see citing works
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 · see citing works
DeSisto, J., O’Rourke, R., Jones, H. E., Pawlikowski, B., Malek, A. D., Bonney, S., Guimiot, F., Jones, K. L., & Siegenthaler, J. A. (2020) · Developmental Cell · doi:10.1016/j.devcel.2020.06.009 · Cited by 241 · see citing works
Spatially resolved epigenomic profiling of single cells in complex tissues
Lu, T., Ang, C. E., & Zhuang, X. (2022) · Cell · doi:10.1016/j.cell.2022.09.035 · Cited by 197 · see citing works
Bhattacherjee, A., Djekidel, M. N., Chen, R., Chen, W., Tuesta, L. M., & Zhang, Y. (2019) · Nature Communications · doi:10.1038/s41467-019-12054-3 · Cited by 174 · see citing works
Resolving organoid brain region identities by mapping single-cell genomic data to reference atlases
Fleck, J. S., Sanchís-Calleja, F., He, Z., Santel, M., Boyle, M. J., Camp, J. G., & Treutlein, B. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.02.015 · Cited by 118 · see citing works
β2-microglobulin functions as an endogenous NMDAR antagonist to impair synaptic function
Gao, Y., Hong, Y., Huang, L., Zheng, S., Zhang, H., Wang, S., Yao, Y., Zhao, Y., Zhu, L., Xu, Q., et al. (2023) · Cell · doi:10.1016/j.cell.2023.01.021 · Cited by 75 · see citing works
Network modeling of single-cell omics data: challenges, opportunities, and progresses
Blencowe, M., Arneson, D., Ding, J., Chen, Y.-W., Saleem, Z., & Yang, X. (2019) · Emerging Topics in Life Sciences · doi:10.1042/etls20180176 · Cited by 73 · see citing works
Bhattacherjee, A., Zhang, C., Watson, B. R., Djekidel, M. N., Moffitt, J. R., & Zhang, Y. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01455-9 · Cited by 71 · see citing works
Weigel, B., Tegethoff, J. F., Grieder, S. D., Lim, B., Nagarajan, B., Liu, Y.-C., Truberg, J., Papageorgiou, D., Adrian-Segarra, J. M., Schmidt, L. K., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01959-7 · Cited by 31 · see citing works
Philtjens, S., Turnbull, M. T., Thedy, B. P., Moon, Y., & Kim, J. (2020) · doi:10.1101/2020.04.27.064881 · Cited by 7 · see citing works
“Previous studies mostly perform scRNA seq in younger mice, while single nucleus RNA sequencing is more common in adult mice (Hook et al., 2018; Loo et al., 2019; Zeisel et al., 2015; Zhou et al., 2020).”
- Authors
- Loo, L., Simon, J. M., Xing, L., McCoy, E. S., Niehaus, J. K., Guo, J., Anton, E. S., & Zylka, M. J.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Zylka, Mark J.
- ORCID
- Venue
- Nature Communications
- Published
- 2019-01-11
- Volume
- 10
- Issue
- 1
- Pages
- 134-134
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC6329831
- OpenAlex
- W2908670724
- Cited by
- 289
- References
- 17
- Citations by year
- 2026: 27 · 2025: 42 · 2024: 28 · 2023: 38 · 2022: 46 · 2021: 56 · 2020: 35 · 2019: 16 · 2018: 1
- FWCI
- 12.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UNC Libraries
- Funders
- Simons Foundation (393316)
- National Institutes of Health (NS 090029)
- National Institute of Mental Health (R01MH060929)
- National Institute of Neurological Disorders and Stroke (P30NS045892, F31NS105397, R01NS090029, R56NS090029, T32NS007431)
- National Institute of Environmental Health Sciences (R56ES028236, DP1ES024088, P30ES010126)
- National Institute of Child Health and Human Development
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD079124)
- 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
- neocortex development, cortical development, cerebral cortex, neuronal cell types, glial cell types, neural progenitor cells, neuronal migration, cortical layers, single-cell transcriptomics, disease-associated genes, mouse embryo
- MeSH terms
- Ciliopathies, Animals, Base Sequence, Mental Disorders, Cell Line, Female, Humans, Male, Mice, Inbred C57BL, Neurons, Stem Cells, Transcription, Genetic, Sequence Analysis, RNA, Cell Lineage, Neocortex, Gene Expression Profiling, Embryonic Development, Mice, HEK293 Cells, Single-Cell Analysis, Neurodevelopmental Disorders
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