The DOI matches its Crossref record; 75 of the 78 references it cites were found in a registry or an index.
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.
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In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
Citations
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- Avsec, 2020, Deep learning at base-resolution reveals cis-regulatory motif syntax, bioRxiv
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
Maturation and circuit integration of transplanted human cortical organoids
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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
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
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
Metadata
- 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
- 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
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