Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution
Open accessPublished version of a preprint
Abstract
Genetic perturbations of cortical development can lead to neurodevelopmental disease, including autism spectrum disorder (ASD). To identify genomic regions crucial to corticogenesis, we mapped the activity of gene-regulatory elements generating a single-cell atlas of gene expression and chromatin accessibility both independently and jointly. This revealed waves of gene regulation by key transcription factors (TFs) across a nearly continuous differentiation trajectory, distinguished the expression programs of glial lineages, and identified lineage-determining TFs that exhibited strong correlation between linked gene-regulatory elements and expression levels. These highly connected genes adopted an active chromatin state in early differentiating cells, consistent with lineage commitment. Base-pair-resolution neural network models identified strong cell-type-specific enrichment of noncoding mutations predicted to be disruptive in a cohort of ASD individuals and identified frequently disrupted TF binding sites. This approach illustrates how cell-type-specific mapping can provide insights into the programs governing human development and disease.
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?
Many autism spectrum disorder risk genes associated with transcriptional regulation and chromatin remodelling are crucial for cortical development.
“Many ASD risk genes associated with transcriptional regulation and chromatin remodelling are crucial for cortical development21,22.”
From Single-cell brain organoid screening identifies developmental defects in autism (2023) · cites this paper as [22]
The OLIG1 module was previously identified as crucial for oligodendrocyte differentiation in the developing human cortex.
“This module was previously identified as crucial for oligodendrocyte differentiation in the developing human cortex22, highlighting the involvement of the oligodendrocytes in ASD pathophysiology.”
From Single-cell brain organoid screening identifies developmental defects in autism (2023) · cites this paper as [22]
Single-cell multiomics allows uncovering mechanisms of gene regulation across different omics layers but lacks spatial information, which is crucial to understanding cellular function in tissue.
“Single-cell multiomics allows uncovering of the mechanisms of gene regulation across different omics layers6–9 but lacks spatial information, which is crucial to understanding cellular function in tissue.”
From Spatial epigenome–transcriptome co-profiling of mammalian tissues (2023) · cites this paper as [9]
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259 · see citing works
A Unified Approach to Interpreting Model Predictions
Lundberg, S., & Lee, S.-I. (2017) · arXiv · doi:10.48550/arxiv.1705.07874 · Cited by 23,707 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453 · see citing works
The mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434 · see citing works
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101 · see citing works
McGinnis, C. S., Murrow, L. M., & Gartner, Z. J. (2019) · Cell Systems · doi:10.1016/j.cels.2019.03.003 · Cited by 4,521 · see citing works
Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes
Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., Rahl, P. B., Lee, T. I., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.03.035 · Cited by 4,143 · see citing works
La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118 · see citing works
Generalizing RNA velocity to transient cell states through dynamical modeling
Bergen, V., Lange, M., Peidli, S., Wolf, F. A., & Theis, F. J. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0591-3 · Cited by 2,951 · see citing works
Learning Important Features Through Propagating Activation Differences
Shrikumar, A., Greenside, P., & Kundaje, A. (2017) · arXiv · doi:10.48550/arxiv.1704.02685 · Cited by 2,761 · see citing works
Self-citationThe contribution of de novo coding mutations to autism spectrum disorder
Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., et al. (2014) · Nature · doi:10.1038/nature13908 · Cited by 2,585 · see citing works
Predicting effects of noncoding variants with deep learning–based sequence model
Zhou, J., & Troyanskaya, O. G. (2015) · Nature Methods · doi:10.1038/nmeth.3547 · Cited by 2,338 · see citing works
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295 · see citing works
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure
Alexa, A., Rahnenführer, J., & Lengauer, T. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl140 · Cited by 2,194 · see citing works
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084 · see citing works
Recovering Gene Interactions from Single-Cell Data Using Data Diffusion
van Dijk, D., Sharma, R., Nainys, J., Yim, K., Kathail, P., Carr, A. J., Burdziak, C., Moon, K. R., Chaffer, C. L., Pattabiraman, D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.061 · Cited by 1,829 · see citing works
Chromatin accessibility and the regulatory epigenome
Klemm, S. L., Shipony, Z., & Greenleaf, W. J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0089-8 · Cited by 1,793 · see citing works
Self-citationConserved cell types with divergent features in human versus mouse cortex
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., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775 · see citing works
chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data
Schep, A. N., Wu, B., Buenrostro, J. D., & Greenleaf, W. J. (2017) · Nature Methods · doi:10.1038/nmeth.4401 · Cited by 1,680 · see citing works
Self-citationUniquely Hominid Features of Adult Human Astrocytes
Oberheim, N. A., Takano, T., Han, X., He, W., Lin, J. H. C., Wang, F., Xu, Q., Wyatt, J. D., Pilcher, W., Ojemann, J. G., et al. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.4707-08.2009 · Cited by 1,488 · see citing works
Khan, A., Fornés, O., Stigliani, A., Gheorghe, M., Castro-Mondragon, J. A., van der Lee, R., Bessy, A., Chèneby, J., Kulkarni, S. R., Tan, G., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1126 · Cited by 1,436 · see citing works
Neurogenic radial glia in the outer subventricular zone of human neocortex
Hansen, D. V., Lui, J. H., Parker, P. R. L., & Kriegstein, A. R. (2010) · Nature · doi:10.1038/nature08845 · Cited by 1,388 · see citing works
Development and Evolution of the Human Neocortex
Lui, J. H., Hansen, D. V., & Kriegstein, A. R. (2011) · Cell · doi:10.1016/j.cell.2011.06.030 · Cited by 1,342 · 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
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247 · see citing works
The chromatin accessibility landscape of primary human cancers
Corces, M. R., Granja, J. M., Shams, S., Louie, B. H., Seoane, J. A., Zhou, W., Silva, T. C., Groeneveld, C., Wong, C. K., Cho, S. W., et al. (2018) · Science · doi:10.1126/science.aav1898 · Cited by 1,230 · see citing works
Self-citationChromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin
Ma, S., Zhang, B., LaFave, L. M., Earl, A. S., Chiang, Z., Hu, Y., Ding, J., Brack, A., Kartha, V. K., Tay, T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.056 · Cited by 1,146 · see citing works
The bHLH Transcription Factors OLIG2 and OLIG1 Couple Neuronal and Glial Subtype Specification
Zhou, Q., & Anderson, D. J. (2002) · Cell · doi:10.1016/s0092-8674(02)00677-3 · Cited by 1,059 · see citing works
Kelley, D. R., Snoek, J., & Rinn, J. L. (2016) · Genome Research · doi:10.1101/gr.200535.115 · Cited by 1,048 · see citing works
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039 · see citing works
The origin and specification of cortical interneurons
Wonders, C. P., & Anderson, S. A. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn1954 · Cited by 980 · see citing works
Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex
Nowakowski, T. J., Bhaduri, A., Pollen, A. A., Alvarado, B., Mostajo-Radji, M. A., Di Lullo, E., Haeussler, M., Sandoval-Espinosa, C., Liu, S. J., Velmeshev, D., et al. (2017) · Science · doi:10.1126/science.aap8809 · Cited by 964 · see citing works
Willsey, A. J., Sanders, S. J., Li, M., Dong, S., Tebbenkamp, A. T., Muhle, R. A., Reilly, S. K., Lin, L., Fertuzinhos, S., Miller, J. A., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.020 · Cited by 934 · see citing works
Molecular Identity of Human Outer Radial Glia during Cortical Development
Pollen, A. A., Nowakowski, T. J., Chen, J., Retallack, H., Sandoval-Espinosa, C., Nicholas, C. R., Shuga, J., Liu, S. J., Oldham, M. C., Diaz, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.09.004 · Cited by 908 · see citing works
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis
Farrell, J. A., Wang, Y., Riesenfeld, S. J., Shekhar, K., Regev, A., & Schier, A. F. (2018) · Science · doi:10.1126/science.aar3131 · Cited by 876 · 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
Molecular logic of neocortical projection neuron specification, development and diversity
Greig, L. C., Woodworth, M. B., Galazo, M. J., Padmanabhan, H., & Macklis, J. D. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3586 · Cited by 863 · see citing works
OSVZ progenitors of human and ferret neocortex are epithelial-like and expand by integrin signaling
Fietz, S. A., Kelava, I., Vogt, J., Wilsch-Bräuninger, M., Stenzel, D., Fish, J. L., Corbeil, D., Riehn, A., Distler, W., Nitsch, R., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2553 · Cited by 830 · see citing works
The Cellular and Molecular Landscapes of the Developing Human Central Nervous System
Silbereis, J. C., Pochareddy, S., Zhu, Y., Li, M., & Sestan, N. (2016) · Neuron · doi:10.1016/j.neuron.2015.12.008 · Cited by 818 · see citing works
Integrative functional genomic analysis of human brain development and neuropsychiatric risks
Li, M., Santpere, G., Imamura Kawasawa, Y., Evgrafov, O. V., Gulden, F. O., Pochareddy, S., Sunkin, S. M., Li, Z., Shin, Y., Zhu, Y., et al. (2018) · Science · doi:10.1126/science.aat7615 · Cited by 810 · see citing works
Cicero predicts cis-regulatory DNA interactions from single-cell chromatin accessibility data
Pliner, H. A., Packer, J. S., McFaline-Figueroa, J. L., Cusanovich, D. A., Daza, R. M., Aghamirzaie, D., Srivatsan, S., Qiu, X., Jackson, D., Minkina, A., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.06.044 · Cited by 789 · see citing works
A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility
Cusanovich, D. A., Hill, A. J., Aghamirzaie, D., Daza, R. M., Pliner, H. A., Berletch, J. B., Filippova, G. N., Huang, X., Christiansen, L., DeWitt, W. S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.052 · Cited by 759 · see citing works
Buenrostro, J. D., Corces, M. R., Lareau, C. A., Wu, B., Schep, A. N., Aryee, M. J., Majeti, R., Chang, H. Y., & Greenleaf, W. J. (2018) · Cell · doi:10.1016/j.cell.2018.03.074 · Cited by 670 · see citing works
Self-citationParker, S. C. J., Stitzel, M. L., Taylor, D. L., Orozco, J. M., Erdos, M. R., Akiyama, J. A., van Bueren, K. L., Chines, P. S., Narisu, N., Program, N. C. S., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317023110 · Cited by 665 · see citing works
Bentsen, M. S., Goymann, P., Schultheis, H., Klee, K., Petrova, A., Wiegandt, R., Fust, A., Preussner, J., Kuenne, C. T., Braun, T. W., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18035-1 · Cited by 649 · see citing works
Cell stress in cortical organoids impairs molecular subtype specification
Bhaduri, A., Andrews, M. G., Mancia Leon, W., Jung, D., Shin, D., Allen, D., Jung, D., Schmunk, G., Haeussler, M., Salma, J., et al. (2020) · Nature · doi:10.1038/s41586-020-1962-0 · Cited by 624 · see citing works
Sloan, S. A., Darmanis, S., Huber, N., Khan, T. A., Birey, F., Caneda, C., Reimer, R., Quake, S. R., Barres, B. A., & Paşca, S. P. (2017) · Neuron · doi:10.1016/j.neuron.2017.07.035 · Cited by 593 · see citing works
Self-citationSequential regulatory activity prediction across chromosomes with convolutional neural networks
Kelley, D. R., Reshef, Y. A., Bileschi, M., Belanger, D., McLean, C. Y., & Snoek, J. (2018) · Genome Research · doi:10.1101/gr.227819.117 · Cited by 537 · see citing works
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
Oscillatory Control of Factors Determining Multipotency and Fate in Mouse Neural Progenitors
Imayoshi, I., Isomura, A., Harima, Y., Kawaguchi, K., Kori, H., Miyachi, H., Fujiwara, T., Ishidate, F., & Kageyama, R. (2013) · Science · doi:10.1126/science.1242366 · Cited by 509 · see citing works
Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
Granja, J. M., Klemm, S., McGinnis, L. M., Kathiria, A. S., Mezger, A., Corces, M. R., Parks, B., Gars, E., Liedtke, M., Zheng, G. X. Y., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0332-7 · Cited by 498 · see citing works
Self-citationLOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor
Sheffield, N. C., & Bock, C. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv612 · Cited by 456 · see citing works
Human astrocytes: structure and functions in the healthy brain
Vasile, F., Dossi, E., & Rouach, N. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1383-5 · Cited by 428 · see citing works
Constructing the cerebral cortex: Neurogenesis and fate determination
McConnell, S. K. (1995) · Neuron · doi:10.1016/0896-6273(95)90168-x · Cited by 416 · see citing works
Single-cell epigenomics: Recording the past and predicting the future
Kelsey, G., Stegle, O., & Reik, W. (2017) · Science · doi:10.1126/science.aan6826 · Cited by 415 · see citing works
New insights into the development of the human cerebral cortex
Molnár, Z., Clowry, G. J., Šestan, N., Alzu’bi, A., Bakken, T. E., Hevner, R. F., Hüppi, P. S., Kostović, I., RAKIC, P. T., Anton, E. S., et al. (2019) · Journal of Anatomy · doi:10.1111/joa.13055 · Cited by 401 · see citing works
Global reference mapping of human transcription factor footprints
Vierstra, J., Lazar, J., Sandstrom, R., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Haugen, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2528-x · Cited by 386 · see citing works
Nowakowski, T. J., Pollen, A. A., Sandoval-Espinosa, C., & Kriegstein, A. R. (2016) · Neuron · doi:10.1016/j.neuron.2016.09.005 · Cited by 347 · see citing works
Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes
Stergachis, A. B., Neph, S. J., Reynolds, A. P., Humbert, R., Miller, B. G., Paige, S. L., Vernot, B., Cheng, J. B., Thurman, R. E., Sandstrom, R. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.07.020 · Cited by 331 · see citing works
Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder
An, J.-Y., Lin, K., Zhu, L., Werling, D. M., Dong, S., Brand, H., Wang, H. Z., Zhao, X., Schwartz, G. B., Collins, R. L., et al. (2018) · Science · doi:10.1126/science.aat6576 · Cited by 316 · see citing works
Transcriptome and epigenome landscape of human cortical development modeled in organoids
Amiri, A., Coppola, G., Scuderi, S., Wu, F., Roychowdhury, T., Liu, F., Pochareddy, S., Shin, Y., Safi, A., Song, L., et al. (2018) · Science · doi:10.1126/science.aat6720 · Cited by 302 · see citing works
Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk
Zhou, J., Park, C. Y., Theesfeld, C. L., Wong, A. K., Yuan, Y., Scheckel, C., Fak, J. J., Funk, J., Yao, K., Tajima, Y., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0420-0 · Cited by 287 · see citing works
Jacquet, B. V., Salinas-Mondragon, R., Liang, H.-X., Therit, B., Buie, J. D., Dykstra, M., Campbell, K., Ostrowski, L., Brody, S., & Ghashghaei, H. T. (2009) · Development · doi:10.1242/dev.041129 · Cited by 277 · see citing works
Astrocytes as a Source for Extracellular Matrix Molecules and Cytokines
Wiese, S., Karus, M., & Faissner, A. (2012) · Frontiers in Pharmacology · doi:10.3389/fphar.2012.00120 · Cited by 262 · see citing works
Chromatin accessibility dynamics in a model of human forebrain development
Trevino, A. E., Sinnott-Armstrong, N., Andersen, J., Yoon, S.-J., Huber, N., Pritchard, J. K., Chang, H. Y., Greenleaf, W. J., & Pașca, S. P. (2020) · Science · doi:10.1126/science.aay1645 · Cited by 251 · see citing works
Self-citationFixed single-cell transcriptomic characterization of human radial glial diversity
Thomsen, E. R., Mich, J. K., Yao, Z., Hodge, R. D., Doyle, A. M., Jang, S., Shehata, S. I., Nelson, A. M., Shapovalova, N. V., Levi, B. P., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3629 · Cited by 227 · see citing works
Rubenstein, J. L. R. (2010) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2010.02307.x · Cited by 170 · see citing works
Cell-type-specific 3D epigenomes in the developing human cortex
Song, M., Pebworth, M.-P., Yang, X., Abnousi, A., Fan, C., Wen, J., Rosen, J. D., Choudhary, M. N. K., Cui, X., Jones, I. R., et al. (2020) · Nature · doi:10.1038/s41586-020-2825-4 · Cited by 143 · see citing works
Ramanathan, S., Woodroffe, A., Flodman, P. L., Mays, L. Z., Hanouni, M., Modahl, C., Steinberg-Epstein, R., Bocian, M. E., Spence, M. A., & Smith, M. (2004) · BMC Medical Genetics · doi:10.1186/1471-2350-5-10 · Cited by 87 · see citing works
Expression and Localization of Myelin Basic Protein in Oligodendrocytes and Transfected Fibroblasts
Barbarese, E., Barry, C. T., Chou, C. J., Goldstein, D. J., Nakos, G. A., Hyde‐DeRuyscher, R., Scheld, K., & Carson, J. H. (1988) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1988.tb01153.x · Cited by 70 · see citing works
Li, Z., Cogswell, M., Hixson, K. M., Brooks‐Kayal, A. R., & Russek, S. J. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00285 · Cited by 37 · see citing works
SA75LARGE-SCALE TRANSCRIPTOME-WIDE CHARACTERIZATION OF ASD, SCHIZOPHRENIA, AND BIPOLAR DISORDER
Gandal, M. J., Zhang, P., Walker, R. L., Won, H., Hadjimichael, E., van Bakel, H., Haney, J. R., Jaffe, A. E., White, K. P., Peters, M. A., et al. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.08.297 · Cited by 33 · see citing works
Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data
Tjärnberg, A., Mahmood, O., Jackson, C. A., Saldi, G.-A., Cho, K., Christiaen, L., & Bonneau, R. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008569 · Cited by 32 · see citing works
Flagged first, then by citations
3 of the 78 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
A single-cell atlas of chromatin accessibility in the human genome
Zhang, K., Hocker, J. D., Miller, M., Hou, X., Chiou, J., Poirion, O. B., Qiu, Y., Li, Y. E., Gaulton, K. J., Wang, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.10.024 · Cited by 502 · see citing works
Maturation and circuit integration of transplanted human cortical organoids
Revah, O., Gore, F., Kelley, K. W., Andersen, J., Sakai, N., Chen, X., Li, M.-Y., Birey, F., Yang, X., Saw, N. L., et al. (2022) · Nature · doi:10.1038/s41586-022-05277-w · Cited by 504 · see citing works
Self-citationSpatial epigenome–transcriptome co-profiling of mammalian tissues
Zhang, D., Deng, Y., Kukanja, P., Agirre, E., Bartosovic, M., Dong, M., Ma, C., Ma, S., Su, G., Bao, S., et al. (2023) · Nature · doi:10.1038/s41586-023-05795-1 · Cited by 483 · see citing works
AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model
Avsec, Ž., Latysheva, N., Cheng, J., Novati, G., Taylor, K. R., Ward, T., Bycroft, C., Nicolaisen, L., Arvaniti, E., Pan, J., et al. (2025) · doi:10.1101/2025.06.25.661532 · Cited by 395 · see citing works
Advancing regulatory variant effect prediction with AlphaGenome
Avsec, Ž., Latysheva, N., Cheng, J., Novati, G., Taylor, K. R., Ward, T., Bycroft, C., Nicolaisen, L., Arvaniti, E., Pan, J., et al. (2026) · Nature · doi:10.1038/s41586-025-10014-0 · Cited by 373 · see citing works
Bryois, J., Calini, D., Macnair, W., Foo, L., Urich, E., Ortmann, W., Iglesias, V. A., Selvaraj, S., Nutma, E., Marzin, M., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01128-z · Cited by 311 · see citing works
Targeting immune–fibroblast cell communication in heart failure
Amrute, J. M., Luo, X., Penna, V., Yang, S., Yamawaki, T., Hayat, S., Bredemeyer, A., Jung, I.-H., Kadyrov, F. F., Heo, G. S., et al. (2024) · Nature · doi:10.1038/s41586-024-08008-5 · Cited by 298 · see citing works
Single-cell brain organoid screening identifies developmental defects in autism
Li, C., Fleck, J. S., Martins-Costa, C., Burkard, T. R., Themann, J., Stuempflen, M., Peer, A. M., Vertesy, Á., Littleboy, J. B., Esk, C., et al. (2023) · Nature · doi:10.1038/s41586-023-06473-y · Cited by 283 · see citing works
Molecular and cellular evolution of the primate dorsolateral prefrontal cortex
Ma, S., Škarica, M., Li, Q., Xu, C., Risgaard, R. D., Tebbenkamp, A. T. N., Mato-Blanco, X., Kovner, R., Krsnik, Ž., de Martin, X., et al. (2022) · Science · doi:10.1126/science.abo7257 · Cited by 256 · see citing works
Characterizing cis-regulatory elements using single-cell epigenomics
Preissl, S., Gaulton, K. J., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-022-00509-1 · Cited by 251 · see citing works
Functional inference of gene regulation using single-cell multi-omics
Kartha, V. K., Duarte, F. M., Hu, Y., Ma, S., Chew, J. G., Lareau, C. A., Earl, A., Burkett, Z. D., Kohlway, A. S., Lebofsky, R., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100166 · Cited by 224 · see citing works
Uzquiano, A., Kedaigle, A. J., Pigoni, M., Paulsen, B. D. S., Adiconis, X., Kim, K., Faits, T., Nagaraja, S., Antón-Bolaños, N., Gerhardinger, C., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.010 · Cited by 250 · see citing works
Herring, C. A., Simmons, R. K., Freytag, S., Poppe, D., Moffet, J. J. D., Pflueger, J., Buckberry, S., Vargas-Landín, D. B., Clément, O., Goñi, E., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.039 · Cited by 226 · see citing works
Human brain organogenesis: Toward a cellular understanding of development and disease
Kelley, K. W., & Pașca, S. P. (2021) · Cell · doi:10.1016/j.cell.2021.10.003 · Cited by 233 · see citing works
Self-citationGenomics, convergent neuroscience and progress in understanding autism spectrum disorder
Willsey, H. R., Willsey, A. J., Wang, B., & State, M. W. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00576-7 · Cited by 229 · see citing works
SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data
Persad, S., Choo, Z.-N., Dien, C., Sohail, N., Masilionis, I., Chaligné, R., Nawy, T., Brown, C. C., Sharma, R., Pe’er, I., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01716-9 · Cited by 222 · see citing works
Liu, I., Jiang, L., Samuelsson, E. R., Salas, S. M., Beck, A., Hack, O. A., Jeong, D., Shaw, M. L., Englinger, B., LaBelle, J. J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01236-3 · Cited by 213 · see citing works
Single-cell analysis of prenatal and postnatal human cortical development
Velmeshev, D., Perez, Y., Yan, Z., Valencia, J. E., Castaneda-Castellanos, D. R., Wang, L., Schirmer, L., Mayer, S., Wick, B., Wang, S., et al. (2023) · Science · doi:10.1126/science.adf0834 · Cited by 204 · see citing works
A fast, scalable and versatile tool for analysis of single-cell omics data
Zhang, K., Zemke, N. R., Armand, E. J., & Ren, B. (2024) · Nature Methods · doi:10.1038/s41592-023-02139-9 · Cited by 185 · see citing works
Single-cell atlases: shared and tissue-specific cell types across human organs
Elmentaite, R., Conde, C. D., Yang, L., & Teichmann, S. A. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00449-w · Cited by 171 · see citing works
Molecular and cellular dynamics of the developing human neocortex
Wang, L., Wang, C., Moriano, J., Chen, S., Zuo, G., Cebrián‐Silla, A., Zhang, S., Mukhtar, T., Wang, S., Song, M., et al. (2025) · Nature · doi:10.1038/s41586-024-08351-7 · Cited by 173 · see citing works
Assembloid CRISPR screens reveal impact of disease genes in human neurodevelopment
Meng, X., Yao, D., Imaizumi, K., Chen, X., Kelley, K. W., Reis, N., Thete, M. V., McKinney, A. A., Kulkarni, S., Panagiotakos, G., et al. (2023) · Nature · doi:10.1038/s41586-023-06564-w · Cited by 145 · see citing works
Self-citationPampari, A., Shcherbina, A., Kvon, E. Z., Kosicki, M., Nair, S., Kundu, S., Kathiria, A. S., Risca, V. I., Kuningas, K., Alasoo, K., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.25.630221 · Cited by 161 · see citing works
Self-citationProtein translation: biological processes and therapeutic strategies for human diseases
Jia, X., He, X., Huang, C., Li, J., Dong, Z., & Liu, K. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01749-9 · Cited by 143 · see citing works
Purification and characterization of human neural stem and progenitor cells
Liu, D. D., He, J. Q., Sinha, R., Eastman, A. E., Toland, A. M. S., Morri, M., Neff, N. F., Vogel, H. S., Uchida, N., & Weissman, I. L. (2023) · Cell · doi:10.1016/j.cell.2023.02.017 · Cited by 124 · see citing works
Li, C., Virgilio, M. C., Collins, K. L., & Welch, J. D. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01476-y · Cited by 130 · see citing works
Multi-omic profiling of the developing human cerebral cortex at the single-cell level
Zhu, K., Bendl, J. M., Rahman, S., Vicari, J. M., Coleman, C., Clarence, T., Latouche, O., Tsankova, N. M., Li, A., Brennand, K., et al. (2023) · Science Advances · doi:10.1126/sciadv.adg3754 · Cited by 116 · see citing works
Integration of spatial and single-cell data across modalities with weakly linked features
Chen, S., Zhu, B., Huang, S., Hickey, J. W., Lin, K. Z., Snyder, M., Greenleaf, W. J., Nolan, G. P., Zhang, N. R., & Ma, Z. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01943-0 · Cited by 119 · see citing works
Self-citationAmeen, M., Sundaram, L., Shen, M., Banerjee, A., Kundu, S., Nair, S., Shcherbina, A., Gu, M., Wilson, K. D., Varadarajan, A., et al. (2022) · Cell · doi:10.1016/j.cell.2022.11.028 · Cited by 109 · see citing works
Self-citationHuman fetal brain self-organizes into long-term expanding organoids
Hendriks, D. F. G., Pagliaro, A., Andreatta, F., Ma, Z., van Giessen, J., Massalini, S., López‐Iglesias, C., van Son, G. J. F., DeMartino, J., Damen, M. J. A., et al. (2024) · Cell · doi:10.1016/j.cell.2023.12.012 · Cited by 106 · see citing works
Brain Chimeroids reveal individual susceptibility to neurotoxic triggers
Antón-Bolaños, N., Faravelli, I., Faits, T., Andreadis, S., Kästli, R., Trattaro, S., Adiconis, X., Wei, A., Kumar, A. S., Bella, D. J. D., et al. (2024) · Nature · doi:10.1038/s41586-024-07578-8 · Cited by 107 · see citing works
Immunological Markers for Central Nervous System Glia
Huang, H., He, W., Tang, T., & Qiu, M.-S. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00938-2 · Cited by 86 · see citing works
Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines
Zhu, Q., Zhao, X., Zhang, Y., Li, Y., Liu, S., Han, J., Sun, Z., Wang, C., Deng, D., Tang, Y., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43991-9 · Cited by 92 · see citing works
Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms
Patowary, A., Zhang, P., Jops, C. T., Vuong, C. K., Ge, X., Hou, K., Kim, M., Gong, N. N., Margolis, M. P., Vo, D., et al. (2024) · Science · doi:10.1126/science.adh7688 · Cited by 87 · see citing works
Wang, S. K., Nair, S., Li, R., Kraft, K., Pampari, A., Patel, A., Kang, J. B., Luong, C., Kundaje, A. B., & Chang, H. Y. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100164 · Cited by 88 · see citing works
Self-citationOber-Reynolds, B., Wang, C., Ko, J. M., Rios, E. J., Aasi, S. Z., Davis, M. M., Oro, A. E., & Greenleaf, W. J. (2023) · Nature Genetics · doi:10.1038/s41588-023-01445-4 · Cited by 83 · see citing works
Self-citationLi, Q. (2023) · Genome biology · doi:10.1186/s13059-023-02988-9 · Cited by 94 · see citing works
Microfluidics for Neuronal Cell and Circuit Engineering
Habibey, R., Arias, J. E. R., Striebel, J., & Busskamp, V. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00212 · Cited by 86 · see citing works
Spatial transcriptomics reveals human cortical layer and area specification
Qian, X., Coleman, K., Jiang, S., Kriz, A. J., Marciano, J. H., Luo, C., Cai, C., Manam, M. D., Caglayan, E., Lai, A., et al. (2025) · Nature · doi:10.1038/s41586-025-09010-1 · Cited by 84 · see citing works
Micali, N., Ma, S., Li, M., Kim, S., Mato-Blanco, X., Sindhu, S. K., Arellano, J. I., Gao, T., Shibata, M., Gobeske, K. T., et al. (2023) · Science · doi:10.1126/science.adf3786 · Cited by 82 · see citing works
Noack, F., Vangelisti, S., Raffl, G., Carido, M., Diwakar, J., Chong, F., & Bonev, B. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-01002-4 · Cited by 74 · see citing works
Interpreting non-coding disease-associated human variants using single-cell epigenomics
Gaulton, K. J., Preißl, S., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00598-6 · Cited by 79 · see citing works
Joint variational autoencoders for multimodal imputation and embedding
Kalafut, N. C., Huang, X. L., & Wang, D. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00663-z · Cited by 77 · see citing works
Brennan, K., Weilert, M., Krueger, S., Pampari, A., Liu, H., Yang, A. W. H., Morrison, J. A., Hughes, T. R., Rushlow, C. A., Kundaje, A. B., et al. (2023) · Developmental Cell · doi:10.1016/j.devcel.2023.07.007 · Cited by 76 · see citing works
Self-citationPredicting gene expression from DNA sequence using deep learning models
Barbadilla-Martínez, L., Klaassen, N. H. M., van Steensel, B., & de Ridder, J. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00841-2 · Cited by 83 · see citing works
Massively parallel characterization of regulatory elements in the developing human cortex
Deng, C., Whalen, S., Steyert, M., Ziffra, R., Przytycki, P. F., Inoue, F., Pereira, D. A., Capauto, D., Norton, S., Vaccarino, F. M., et al. (2024) · Science · doi:10.1126/science.adh0559 · Cited by 72 · see citing works
Self-citationMitra, S., Malik, R., Wong, W., Rahman, A., Hartemink, A. J., Pritykin, Y., Dey, K. K., & Leslie, C. S. (2024) · Nature Genetics · doi:10.1038/s41588-024-01689-8 · Cited by 67 · see citing works
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 71 · see citing works
Chromatin accessibility during human first-trimester neurodevelopment
Mannens, C. C. A., Hu, L., Lönnerberg, P., Schipper, M., Reagor, C. C., Li, X., He, X., Barker, R. A., Sundström, E., Posthuma, D., et al. (2024) · Nature · doi:10.1038/s41586-024-07234-1 · Cited by 67 · see citing works
Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers
Sundaram, L., Kumar, A., Zatzman, M., Salcedo, A., Ravindra, N. G., Shams, S., Louie, B. H., Bagdatli, S. T., Myers, M. A., Sarmashghi, S., et al. (2024) · Science · doi:10.1126/science.adk9217 · Cited by 66 · see citing works
Self-citationTissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles
Sakaue, S., Weinand, K., Isaac, S., Dey, K. K., Jagadeesh, K. A., Kanai, M., Watts, G. F. M., Zhu, Z., Accelerating Medicines Partnership® RA/SLE Program and Network, Albrecht, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01682-1 · Cited by 60 · see citing works
Single-cell transcriptomic landscape of the developing human spinal cord
Andersen, J., Thom, N., Shadrach, J. L., Chen, X., Onesto, M. M., Amin, N. D., Yoon, S.-J., Li, L., Greenleaf, W. J., Müller, F., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01311-w · Cited by 61 · see citing works
Self-citationHuman assembloids reveal the consequences of CACNA1G gene variants in the thalamocortical pathway
Kim, J.-I., Miura, Y., Li, M.-Y., Revah, O., Selvaraj, S., Birey, F., Meng, X., Thete, M. V., Pavlov, S. D., Andersen, J., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.09.020 · Cited by 59 · see citing works
Self-citationKing, H. W., Wells, K. L., Shipony, Z., Kathiria, A. S., Wagar, L. E., Lareau, C. A., Orban, N. T., Capasso, R., Davis, M. M., Steinmetz, L. M., et al. (2021) · Science Immunology · doi:10.1126/sciimmunol.abh3768 · Cited by 53 · see citing works
Self-citationSingle-cell joint profiling of multiple epigenetic proteins and gene transcription
Xiong, H., Wang, Q., Li, C. C., & He, A. (2024) · Science Advances · doi:10.1126/sciadv.adi3664 · Cited by 56 · see citing works
A single-cell multiomic analysis of kidney organoid differentiation
Yoshimura, Y., Muto, Y., Ledru, N., Wu, H., Omachi, K., Miner, J. H., & Humphreys, B. D. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2219699120 · Cited by 52 · see citing works
A community effort to optimize sequence-based deep learning models of gene regulation
Rafi, A. M., Nogina, D., Penzar, D., Lee, D., Lee, D., KIM, N. S., Kim, S., Kim, D., Shin, Y., Kwak, I., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02414-w · Cited by 51 · see citing works
Zhao, L., Chen, J., Zhang, Z., Wu, W., Lin, X., Gao, M., Yang, Y., Zhao, P., Xu, S., Yang, C., et al. (2024) · Advanced Science · doi:10.1002/advs.202401383 · Cited by 49 · see citing works
The molecular genetics of nELAVL in brain development and disease
Mulligan, M. R., & Bicknell, L. S. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-023-01456-z · Cited by 47 · see citing works
epiAneufinder identifies copy number alterations from single-cell ATAC-seq data
Ramakrishnan, A., Symeonidi, A., Hanel, P., Schmid, K., Richter, M. L., Schubert, M., & Colomé‐Tatché, M. (2023) · Nature Communications · doi:10.1038/s41467-023-41076-1 · Cited by 47 · see citing works
Decoding enhancer complexity with machine learning and high-throughput discovery
Smith, G. D., Ching, W. H., Cornejo‐Páramo, P., & Wong, E. S. W. (2023) · Genome biology · doi:10.1186/s13059-023-02955-4 · Cited by 43 · see citing works
Spatially resolved gene regulatory and disease-related vulnerability map of the adult Macaque cortex
Lei, Y., Cheng, M., Li, Z., Zhuang, Z., Wu, L. L., Sun, Y., Han, L., Huang, Z., Wang, Y., Wang, Z., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34413-3 · Cited by 47 · see citing works
Cazares, T. A., Rizvi, F. W., Iyer, B., Chen, X., Kotliar, M., Bejjani, A. T., Wayman, J. A., Donmez, O. A., Wronowski, B., Parameswaran, S., et al. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010863 · Cited by 42 · see citing works
Casingal, C. R., Descant, K. D., & Anton, E. S. (2022) · Neuron · doi:10.1016/j.neuron.2022.01.034 · Cited by 42 · see citing works
Tracking single-cell evolution using clock-like chromatin accessibility loci
Xiao, Y., Jin, W., Ju, L., Fu, J., Wang, G., Yu, M., Chen, F., Qian, K., Wang, X., & Zhang, Y. (2024) · Nature Biotechnology · doi:10.1038/s41587-024-02241-z · Cited by 43 · see citing works
Evolving cell states and oncogenic drivers during the progression of IDH-mutant gliomas
Wu, J., Castro, L. N. G., Battaglia, S., Farran, C. A. E., D’Antonio, J. P., Miller, T. E., Suvà, M. L., & Bernstein, B. (2024) · Nature Cancer · doi:10.1038/s43018-024-00865-3 · Cited by 41 · see citing works
Zug, R. (2022) · Biology Open · doi:10.1242/bio.058896 · Cited by 42 · see citing works
A single-cell multi-omic atlas spanning the adult rhesus macaque brain
Chiou, K. L., Huang, X., Bohlen, M. O., Tremblay, S., DeCasien, A. R., O’Day, D. R., Spurrell, C. H., Gogate, A. A., Zintel, T. M., Andrews, M. G., et al. (2023) · Science Advances · doi:10.1126/sciadv.adh1914 · Cited by 40 · see citing works
Benchmarking brain organoid recapitulation of fetal corticogenesis
Cheroni, C., Trattaro, S., Caporale, N., Tobon, A., Tenderini, E., Sebastiani, S., Troglio, F., Gabriele, M., Bressan, R. B., Pollard, S. M., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02279-0 · Cited by 37 · see citing works
multiDGD: A versatile deep generative model for multi-omics data
Schuster, V., Dann, E., Krogh, A., & Teichmann, S. A. (2024) · Nature Communications · doi:10.1038/s41467-024-53340-z · Cited by 37 · see citing works
Toward transcriptomics as a primary tool for rare disease investigationPreprint
Montgomery, S., Bernstein, J. A., & Wheeler, M. (2022) · Cold Spring Harbor molecular case studies · doi:10.1101/mcs.a006198 · Cited by 46 · see citing works
Setting the clock of neural progenitor cells during mammalian corticogenesis
Koo, B., Lee, K., Ming, G., Yoon, K., & Song, H. (2022) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2022.05.013 · Cited by 37 · see citing works
Mechanisms underlying the effect of voluntary running on adult hippocampal neurogenesis
Gao, Y., Syed, M., & Zhao, X. (2023) · Hippocampus · doi:10.1002/hipo.23520 · Cited by 34 · see citing works
Liu, Q., Ma, W., Chen, R., Li, S., Wang, Q., Wei, C., Hong, Y., Sun, H., Cheng, Q., Zhao, J., et al. (2024) · Advanced Science · doi:10.1002/advs.202308384 · Cited by 34 · see citing works
The use of single-cell multi-omics in immuno-oncology
Ma, A., Xin, G., & Ma, Q. (2022) · Nature Communications · doi:10.1038/s41467-022-30549-4 · Cited by 34 · see citing works
Yeo, R. W., Zhou, O. Y., Zhong, B. L., Sun, E., Negredo, P. N., Nair, S., Sharmin, M., Ruetz, T. J., Wilson, M., Kundaje, A. B., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00449-3 · Cited by 37 · see citing works
Self-citationSingh, R., Wu, A. P., Mudide, A., & Berger, B. (2024) · Cell Systems · doi:10.1016/j.cels.2024.04.005 · Cited by 34 · see citing works
Valproic acid exposure decreases neurogenic potential of outer radial glia in human brain organoids
Zang, Z., Yin, H., Du, Z., Xie, R., Yang, L., Cai, Y., Wang, L., Zhang, D., Li, X., Liu, T., et al. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.1023765 · Cited by 35 · see citing works
Shu, M., Hong, D., Lin, H., Zhang, J., Luo, Z., Du, Y., Sun, Z., Yin, M., Yin, Y., Liu, L., et al. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.11.011 · Cited by 28 · see citing works
Li, Z., Liu, G., Yang, L., Sun, M., Zhang, Z., Xu, Z., Gao, Y., Jiang, X., Su, Z., Li, X., et al. (2023) · Protein & Cell · doi:10.1093/procel/pwad036 · Cited by 31 · see citing works
Annotating the genome at single-nucleotide resolution with DNA foundation models
de Almeida, B. P., Dalla-Torre, H., Richard, G., Blum, C. F., Hexemer, L., Gélard, M., Mendoza‐Revilla, J., Tang, Z., Marin, F. I., Emms, D., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02881-2 · Cited by 35 · see citing works
Darbandi, S. F., An, J., Lim, K. J., Page, N. F., Liang, L., Young, D. M., Ypsilanti, A. R., State, M. W., Nord, A. S., Sanders, S., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114329 · Cited by 32 · see citing works
Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses
Wu, Y., Zhang, C., Wang, L., Li, Y., & Xiao, X. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbad002 · Cited by 28 · see citing works
Cerebral Organoids as an Experimental Platform for Human Neurogenomics
Nowakowski, T. J., & Salama, S. R. (2022) · Cells · doi:10.3390/cells11182803 · Cited by 26 · see citing works
CMOT: cross-modality optimal transport for multimodal inference
Alatkar, S. A., & Wang, D. (2023) · Genome biology · doi:10.1186/s13059-023-02989-8 · Cited by 24 · see citing works
Three‐dimensional chromatin re‐organization during muscle stem cell aging
Yang, B. A., Larouche, J. A., Sabin, K., Fraczek, P. M., Parker, S. C. J., & Aguilar, C. A. (2023) · Aging Cell · doi:10.1111/acel.13789 · Cited by 26 · see citing works
Single-cell multiomics decodes regulatory programs for mouse secondary palate development
Yan, F., Suzuki, A., Iwaya, C., Pei, G., Chen, X., Yoshioka, H., Yu, M., Simon, L. M., Iwata, J., & Zhao, Z. (2024) · Nature Communications · doi:10.1038/s41467-024-45199-x · Cited by 26 · see citing works
EpiAgent: foundation model for single-cell epigenomics
Chen, X., Li, K., Cui, X., Wang, Z., Jiang, Q., Lin, J., Li, Z., Gao, Z., Lv, H., & Jiang, R. (2025) · Nature Methods · doi:10.1038/s41592-025-02822-z · Cited by 31 · see citing works
Development, Diversity, and Death of MGE-Derived Cortical Interneurons
Williams, R. H., & Riedemann, T. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179297 · Cited by 24 · see citing works
Phospho-seq: integrated, multi-modal profiling of intracellular protein dynamics in single cells
Blair, J. D., Hartman, A., Zenk, F. L., Wahle, P., Brancati, G., Dalgarno, C., Treutlein, B., & Satija, R. (2025) · Nature Communications · doi:10.1038/s41467-025-56590-7 · Cited by 25 · see citing works
Mapping the developmental trajectory of human astrocytes reveals divergence in glioblastoma
Sojka, C., Wang, H. V., Bhatia, T. N., Li, Y., Chopra, P., Sing, A., Voss, A. J., King, A. T., Wang, F., Joseph, K., et al. (2025) · Nature Cell Biology · doi:10.1038/s41556-024-01583-9 · Cited by 24 · see citing works
He, C., Kalafut, N. C., Sandoval, S. O., Risgaard, R. D., Sirois, C. L., Yang, C., Khullar, S., Suzuki, M., Huang, X., Chang, Q., et al. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100409 · Cited by 25 · see citing works
Noack, F., Vangelisti, S., Ditzer, N., Chong, F., Albert, M., & Bonev, B. (2023) · Nature Cell Biology · doi:10.1038/s41556-023-01296-5 · Cited by 26 · see citing works
Hua, H., Wang, Y., Wang, X., Wang, S., Zhou, Y., Liu, Y., Liang, Z., Ren, H., Lu, S., Wu, S., et al. (2024) · Cell stem cell · doi:10.1016/j.stem.2024.04.010 · Cited by 25 · see citing works
Decoding sequence determinants of gene expression in diverse cellular and disease states
Lal, A., Karollus, A., Gunsalus, L. M., Garfield, D., Nair, S., Tseng, A. M., Gordon, M. G., Blischak, J., Geijn, B. V. D., Bhangale, T., et al. (2026) · Nature Methods · doi:10.1038/s41592-026-03102-0 · Cited by 24 · see citing works
Practical Considerations for Single‐Cell Genomics
Regan, C., & Preall, J. B. (2022) · Current Protocols · doi:10.1002/cpz1.498 · Cited by 25 · see citing works
Autism spectrum disorder research: knowledge mapping of progress and focus between 2011 and 2022
Jiang, M., Lu, T., Yang, K., Li, X., Zhao, L., Zhang, D., Li, J., & Wang, L. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1096769 · Cited by 25 · see citing works
Adameyko, I. I., Bakken, T. E., Bhaduri, A., Chhatbar, C., Filbin, M. G., Gate, D., Hochgerner, H., Kim, C. N., Krull, J. E., Manno, G. L., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01827-9 · Cited by 25 · see citing works
A matter of space and time: Emerging roles of disease-associated proteins in neural development
Panagiotakos, G., & Pașca, S. P. (2021) · Neuron · doi:10.1016/j.neuron.2021.10.035 · Cited by 24 · see citing works
Self-citationMicrofluidic single‐cell multiomics analysis
Xu, X., Zhang, Q., Li, M., Lin, S., Liang, S., Cai, L., Zhu, H., Su, R. J., & Yang, C. J. (2022) · Open Research (University of Surrey) · doi:10.1002/viw.20220034 · Cited by 23 · see citing works
- Authors
- Trevino, A. E., Müller, F., Andersen, J., Sundaram, L., Kathiria, A., Shcherbina, A., Farh, K., Chang, H. Y., Pașca, A. M., Kundaje, A., Pașca, S. P., & Greenleaf, W. J.
- Affiliations
- Stanford University (US)
- Saarland University (DE)
- Stanford Medicine (US)
- Illumina (United States) (US)
- Howard Hughes Medical Institute (US)
- Chan Zuckerberg Biohub San Francisco (US)
- Corresponding author
- Pașca, Sergiu P.
- Greenleaf, William J.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 184
- Issue
- 19
- Pages
- 5053-5069.e23
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W3194509722
- Cited by
- 478
- References
- 78
- Citations by year
- 2026: 76 · 2025: 99 · 2024: 110 · 2023: 99 · 2022: 75 · 2021: 17 · 2020: 1
- FWCI
- 24.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 380 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, other-oa)
- PubMed (publishedVersion)
- Funders
- Leland Stanford Junior University
- 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 Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- cortical development, chromatin accessibility, gene regulatory elements, single-cell atlas, transcription factors, lineage commitment, autism spectrum disorder, non-coding mutations, transcription factor binding sites, neural network model, neurodevelopmental disorders
- MeSH terms
- Deep Learning, Astrocytes, Cell Differentiation, Cerebral Cortex, Chromatin, Glutamates, Humans, Mutation, Neurons, Regulatory Sequences, Nucleic Acid, Cluster Analysis, Fuzzy Logic, Gene Expression Regulation, Developmental, Cell Lineage, Epigenesis, Genetic, 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