A comparative atlas of single-cell chromatin accessibility in the human brain
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Abstract
Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer’s disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.
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Brains were collected using highly optimized brain preparation methods with a mean postmortem interval of 7.0 h that enable exceptionally high-quality snRNA-seq, snATAC-seq and MERFISH profiling.
“Brains were collected using highly optimized brain preparation methods (mean postmortem interval = 7.0 h; Extended Data Fig. 1b) that enable exceptionally high-quality snRNA-seq, snATAC–seq and MERFISH profiling17–19,23,36,37.”
From Integrated multimodal cell atlas of Alzheimer’s disease (2024) · cites this paper as [36]
The section “A single-cell chromatin accessibility atlas of human brains” (page unavailable) reports snATAC-seq profiling of dissected human brain regions and quality-control evidence for reliable data. Our copy does not give a mean postmortem interval of 7.0 hours or establish that the brain preparation methods enabled high-quality snRNA-seq and MERFISH profiling. (LLM, conf=0.84)
Experimental — accuracy not yet measuredDNase-seq and ChIP-seq from ENCODE and the Epigenomics Roadmap and pseudo-bulk single-cell ATAC-seq from CATlas focus the model towards distal regulatory elements.
“as well as DNase-seq and ChIP–seq from ENCODE and the Epigenomics Roadmap31,99 and pseudo-bulk single-cell ATAC–seq data from CATlas100,101, which focuses the model towards distal regulatory elements.”
From Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation (2025) · cites this paper as [101]
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404 · see citing works
Scikit-learn: Machine Learning in Python
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016 · see citing works
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437 · see citing works
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849 · 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
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Self-citationIntegrated analysis of multimodal single-cell data
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zagar, M., et al. (2020) · doi:10.1101/2020.10.12.335331 · Cited by 15,508 · see citing works
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488 · see citing works
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826 · cited 4× · see citing works
“Step 10: Visualization For visualization, we applied UMAP ( 71 ).”
InfluentialdeepTools2: a next generation web server for deep-sequencing data analysis
Ramírez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., Heyne, S., Dündar, F., & Manke, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw257 · Cited by 8,096 · see citing works
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814 · see citing works
Self-citationBiological 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
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · cited 3× · see citing works
“…catalogs of candidate regulatory sequences in the human genome, most notably those generated by the ENCODE and EpigenomeRoadmap consortia( 6 , 7 , 18 , 19 ), still lack theinformation about cell-type – specific activities of each element, especially those identified from brain tissues,…”
BackgroundSelf-citationFrom Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635 · see citing works
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
Hafemeister, C., & Satija, R. (2019) · Genome Biology · doi:10.1186/s13059-019-1874-1 · Cited by 4,479 · see citing works
Buniello, A., MacArthur, J. A. L., Cerezo, M., Harris, L. W., Hayhurst, J., Malangone, C., McMahon, A., Morales, J., Mountjoy, E., Sollis, E., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1120 · Cited by 4,000 · see citing works
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716 · see citing works
Non-negative Matrix Factorization with Sparseness Constraints
Hoyer, P. (2004) · Journal of machine learning research · doi:10.48550/arxiv.cs/0408058 · Cited by 3,085
eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0090-3 · Cited by 3,005 · see citing works
Self-citationMolecular Architecture of the Mouse Nervous System
Zeisel, A., Hochgerner, H., Lönnerberg, P., Johnsson, A., Memic, F., van der Zwan, J., Häring, M., Braun, E., Borm, L. E., La Manno, G., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.021 · Cited by 2,995 · see citing works
Self-citationScrublet: computational identification of cell doublets in single-cell transcriptomic data
Wolock, S. L., Lopez, R., & Klein, A. M. (2018) · doi:10.1101/357368 · Cited by 2,758 · cited 4× · see citing works
“Next, cell-by-genecountmatriceswereusedasinput, withdefaultparameters,thedoubletscoreswere calculatedforbothobservednucleix i f g and simulated doublets y i f g using Scrublet ( 65 ).”
MethodInfluentialScrublet: computational identification of cell doublets in single-cell transcriptomic data
Wolock, S. L., Lopez, R., & Klein, A. M. (2019) · Cell Systems · doi:10.1016/j.cels.2018.11.005 · Cited by 2,758 · see citing works
Non-negative Matrix Factorization with Sparseness ConstraintsPreprint
Hoyer, P. O. (2004) · doi:10.5555/1005332.1044709 · Cited by 2,625 · see citing works
(2012) · doi:10.1016/j.jmoldx.2011.08.002 · Cited by 2,567 · see citing works
Self-Attention with Relative Position Representations
Shaw, P., Uszkoreit, J., & Vaswani, A. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers) · doi:10.18653/v1/n18-2074 · Cited by 2,505 · see citing works
Pvclust: an R package for assessing the uncertainty in hierarchical clustering
Suzuki, R., & Shimodaira, H. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl117 · Cited by 2,456 · see citing works
The State of US Health, 1990-2010: Burden of Diseases, Injuries, and Risk Factors
Murray, C. J. L. (2013) · JAMA · doi:10.1001/jama.2013.13805 · Cited by 2,438 · cited 4× · see citing works
“Midbrain (1) Cerebellum (2) Hippocampus (3)”
BackgroundInfluentialIdentification of common genetic risk variants for autism spectrum disorder
Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium, Grove, J., BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0344-8 · Cited by 2,421 · see citing works
fitdistrplus : An R Package for Fitting Distributions
Delignette‐Muller, M. L., & Dutang, C. (2015) · Journal of Statistical Software · doi:10.18637/jss.v064.i04 · Cited by 2,391 · see citing works
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2493-4 · Cited by 2,378 · see citing works
Self-citationSingle-cell chromatin accessibility reveals principles of regulatory variation
Buenrostro, J. D., Wu, B., Litzenburger, U. M., Ruff, D., Gonzales, M. L., Snyder, M. P., Chang, H. Y., & Greenleaf, W. J. (2015) · Nature · doi:10.1038/nature14590 · Cited by 2,308 · see citing works
Jansen, I. E., Savage, J. E., Watanabe, K., Bryois, J., Williams, D. M., Steinberg, S., Sealock, J., Karlsson, I. K., Hägg, S., Athanasiu, L., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0311-9 · Cited by 2,277 · see citing works
ADHD Working Group of the Psychiatric Genomics Consortium (PGC), Demontis, D., Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, 23andMe Research Team, Walters, R. K., Martin, J., Mattheisen, M., Als, T. D., Agerbo, E., Baldursson, G., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0269-7 · Cited by 2,203 · see citing works
Molecular diversity and specializations among the cells of the adult mouse brain
Saunders, A., Macosko, E. Z., Wysoker, A., Goldman, M., Krienen, F. M., de Rivera, H., Bien, E., Baum, M., Bortolin, L., Wang, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.028 · Cited by 1,847 · see citing works
The UCSC Genome Browser database: update 2011
Fujita, P. A., Rhead, B. L., Zweig, A. S., Hinrichs, A. S., Karolchik, D., Cline, M., Goldman, M. J., Barber, G. P., Clawson, H., Coelho, A., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq963 · Cited by 1,836 · see citing works
The ENCODE Blacklist: Identification of Problematic Regions of the Genome
Amemiya, H. M., Kundaje, A., & Boyle, A. P. (2019) · Scientific Reports · doi:10.1038/s41598-019-45839-z · Cited by 1,831 · 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
A comparative encyclopedia of DNA elements in the mouse genome
Yue, F., Cheng, Y., Breschi, A., Vierstra, J., Wu, W., Ryba, T., Sandstrom, R., Ma, Z., Davis, C., Pope, B. D., et al. (2014) · Nature · doi:10.1038/nature13992 · Cited by 1,781 · see citing works
Conserved 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 · cited 4× · see citing works
“To quantify the similarity between cell clusters from two modalities, we calculated an overlapping score as the sum of the minimum proportion of cells/nuclei in each cluster that overlapped within each coembedding cluster ( 8 ).”
BackgroundMethodInfluentialSelf-citationTranscriptome-scale super-resolved imaging in tissues by RNA seqFISH
Eng, C.-H. L., Lawson, M., Zhu, Q., Dries, R., Koulena, N., Takei, Y., Yun, J., Cronin, C., Karp, C., Yuan, G.-C., et al. (2019) · Nature · doi:10.1038/s41586-019-1049-y · Cited by 1,754 · see citing works
Self-citationShared 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
Self-citationAdult 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
Self-citationchromVAR: 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
Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
International Multiple Sclerosis Genetics Consortium, Patsopoulos, N. A., Baranzini, S. E., Santaniello, A., Shoostari, P., Cotsapas, C., Wong, G., Beecham, A. H., James, T., Replogle, J., et al. (2019) · Science · doi:10.1126/science.aav7188 · Cited by 1,471 · see citing works
Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., de Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0152-6 · Cited by 1,443 · see citing works
Self-citationZhou, W., Nielsen, J. B., Fritsche, L. G., Dey, R., Gabrielsen, M. E., Wolford, B. N., LeFaive, J., VandeHaar, P., Taliun, S. A. G., Gifford, A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0184-y · Cited by 1,406 · see citing works
Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region
Moffitt, J. R., Bambah-Mukku, D., Eichhorn, S. W., Vaughn, E., Shekhar, K., Perez, J. D., Rubinstein, N. D., Hao, J., Regev, A., Dulac, C., et al. (2018) · Science · doi:10.1126/science.aau5324 · Cited by 1,365 · see citing works
A map of the cis-regulatory sequences in the mouse genome
Shen, Y., Yue, F., McCleary, D. F., Ye, Z., Edsall, L., Kuan, S., Wagner, U., Dixon, J., Lee, L., Lobanenkov, V. V., et al. (2012) · Nature · doi:10.1038/nature11243 · Cited by 1,361 · cited 1× · see citing works
“Current catalogs of candidate regulatory sequences in the human genome, most notably those generated by the ENCODE andEpigenomeRoadmap consortia (6, 7, 18, 19), still lack the information about cell-type–specific activities of each element, especially those identified from brain tissues, because conventional assays pe…”
BackgroundSelf-citationmixtools : An R Package for Analyzing Finite Mixture Models
Benaglia, T., Chauveau, D., Hunter, D. R., & Young, D. S. (2009) · Journal of Statistical Software · doi:10.18637/jss.v032.i06 · Cited by 1,351 · see citing works
Frankish, A., Diekhans, M., Jungreis, I., Lagarde, J., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J., Barnes, I., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1087 · Cited by 1,334 · see citing works
Effective gene expression prediction from sequence by integrating long-range interactions
Avsec, Ž., Agarwal, V., Visentin, D., Ledsam, J. R., Grabska-Barwinska, A., Taylor, K. R., Assael, Y., Jumper, J., Kohli, P., & Kelley, D. R. (2021) · Nature Methods · doi:10.1038/s41592-021-01252-x · Cited by 1,326 · see citing works
Genome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297 · see citing works
Self-citationOligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system
Marques, S., Zeisel, A., Codeluppi, S., van Bruggen, D., Mendanha Falcão, A., Xiao, L., Li, H., Häring, M., Hochgerner, H., Romanov, R. A., et al. (2016) · Science · doi:10.1126/science.aaf6463 · Cited by 1,246 · see citing works
Self-citationThe 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-citationA rapid and robust method for single cell chromatin accessibility profiling
Chen, X., Miragaia, R. J., Natarajan, K. N., & Teichmann, S. A. (2018) · Nature Communications · doi:10.1038/s41467-018-07771-0 · Cited by 1,147 · see citing works
Interneuron cell types are fit to function
Kepecs, A., & Fishell, G. (2014) · Nature · doi:10.1038/nature12983 · Cited by 1,110 · see citing works
Initiative, A. N. G., Watson, H. J., Eating Disorders Working Group of the Psychiatric Genomics Consortium, Yilmaz, Z., Thornton, L. M., Hübel, C., Coleman, J. R. I., Gaspar, H. A., Bryois, J., Hinney, A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0439-2 · Cited by 1,109 · see citing works
VISTA Enhancer Browser—a database of tissue-specific human enhancers
Visel, A., Minovitsky, S., Dubchak, I., & Pennacchio, L. A. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl822 · Cited by 1,080 · see citing works
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation
Yao, Z., van Velthoven, C. T. J., Nguyen, T. N., Goldy, J., Sedeno-Cortes, A. E., Baftizadeh, F., Bertagnolli, D., Casper, T., Chiang, M., Crichton, K., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.021 · Cited by 1,065 · see citing works
Self-citationIntegrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
Lake, B. B., Chen, S., Sos, B. C., Fan, J., Kaeser, G. E., Yung, Y. C., Duong, T. E., Gao, D., Chun, J., Kharchenko, P. V., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4038 · Cited by 983 · see citing works
Kim, H., & Park, H. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm134 · Cited by 865 · see citing works
Jansen, P. R., Watanabe, K., Stringer, S., Skene, N., Bryois, J., Hammerschlag, A. R., de Leeuw, C., Benjamins, J. S., Muñoz‐Manchado, A. B., Nagel, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0333-3 · Cited by 839 · see citing works
Transcriptomic diversity of cell types across the adult human brain
Siletti, K., Hodge, R., Mossi Albiach, A., Lee, K. W., Ding, S.-L., Hu, L., Lönnerberg, P., Bakken, T., Casper, T., Clark, M., et al. (2023) · Science · doi:10.1126/science.add7046 · Cited by 832 · see citing works
Self-citationEnhancer Evolution across 20 Mammalian Species
Villar, D., Berthelot, C., Aldridge, S., Rayner, T. F., Lukk, M., Pignatelli, M., Park, T. J., Deaville, R., Erichsen, J. T., Jasinska, A. J., et al. (2015) · Cell · doi:10.1016/j.cell.2015.01.006 · Cited by 825 · see citing works
Brain cell type–specific enhancer–promoter interactome maps and disease <b>-</b> risk association
Nott, A., Holtman, I. R., Coufal, N. G., Schlachetzki, J. C. M., Yu, M., Hu, R., Han, C. Z., Pena, M., Xiao, J., Wu, Y., et al. (2019) · Science · doi:10.1126/science.aay0793 · Cited by 823 · see citing works
Self-citationComparative 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
Self-citationAlzheimer's disease: experimental models and reality
Drummond, E., & Wisniewski, T. (2017) · Acta Neuropathologica · doi:10.1007/s00401-016-1662-x · Cited by 810 · see citing works
Identification of region-specific astrocyte subtypes at single cell resolution
Batiuk, M. Y., Martirosyan, A., Wahis, J., de Vin, F., Marneffe, C., Kusserow, C., Koeppen, J., Viana, J. F., Oliveira, J. F., Voet, T., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-14198-8 · Cited by 805 · see citing works
A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk
Yang, A. C., Vest, R. T., Kern, F., Lee, D. P., Agam, M., Maat, C. A., Losada, P. M., Chen, M. B., Schaum, N., Khoury, N., et al. (2022) · Nature · doi:10.1038/s41586-021-04369-3 · Cited by 797 · 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
A brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
Jones, S. E., Lane, J. M., Wood, A. R., van Hees, V. T., Tyrrell, J., Beaumont, R. N., Jeffries, A. R., Dashti, H. S., Hillsdon, M., Ruth, K. S., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08259-7 · Cited by 691 · see citing works
Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior
Yap, E.-L., & Greenberg, M. E. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.013 · Cited by 626 · see citing works
Microglial regional heterogeneity and its role in the brain
Tan, Y.-L., Yuan, Y., & Tian, L. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0609-8 · Cited by 571 · see citing works
Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex
Luo, C., Keown, C. L., Kurihara, L., Zhou, J., He, Y., Li, J., Castanon, R., Lucero, J., Nery, J. R., Sandoval, J. P., et al. (2017) · Science · doi:10.1126/science.aan3351 · Cited by 545 · see citing works
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BRAIN Initiative Cell Census Network (BICCN), BRAIN Initiative Cell Census Network (BICCN) Corresponding authors, Callaway, E. M., Dong, H.-W., Ecker, J. R., Hawrylycz, M. J., Huang, Z. J., Lein, E. S., Ngai, J., Osten, P., et al. (2021) · Nature · doi:10.1038/s41586-021-03950-0 · Cited by 522 · see citing works
Self-citationA 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
Self-citationSingle-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex
Hrvatin, S., Hochbaum, D. R., Nagy, M. A., Cicconet, M., Robertson, K., Cheadle, L., Zilionis, R., Ratner, A., Borges-Monroy, R., Klein, A. M., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-017-0029-5 · Cited by 497 · see citing works
Comprehensive analysis of single cell ATAC-seq data with SnapATAC
Fang, R., Preissl, S., Li, Y., Hou, X., Lucero, J., Wang, X., Motamedi, A., Shiau, A. K., Zhou, X., Xie, F., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21583-9 · Cited by 455 · see citing works
Self-citationComprehensive cellular‐resolution atlas of the adult human brain
Ding, S., Royall, J. J., Sunkin, S. M., Ng, L., Facer, B. A. C., Lesnar, P., Guillozet‐Bongaarts, A., McMurray, B., Szafer, A., Dolbeare, T. A., et al. (2016) · Journal of Comparative Neurology · doi:10.1002/cne.24080 · Cited by 447 · cited 4× · see citing works
“We dissected 42 brain regions from the human cortex (CTX), hippocampus (HIP), basal nuclei (BN), midbrain (MB), thalamus (THM), cerebellum (CB), and pons (PN) [according to the Allen Brain Reference Atlas (27)] from three neurotypical male donors (D1, D2, and D4), ages 29, 42, and 58, respectively (Fig.”
MethodInfluentialSelf-citationDroplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility
Lareau, C. A., Duarte, F. M., Chew, J. G., Kartha, V. K., Burkett, Z. D., Kohlway, A. S., Pokholok, D., Aryee, M. J., Steemers, F. J., Lebofsky, R., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0147-6 · Cited by 444 · see citing works
A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
Yao, Z., Liu, H., Xie, F., Fischer, S., Adkins, R. S., Aldridge, A. I., Ament, S. A., Bartlett, A., Behrens, M. M., Van den Berge, K., et al. (2021) · Nature · doi:10.1038/s41586-021-03500-8 · Cited by 398 · see citing works
Self-citationLuciano, M., Hagenaars, S. P., Davies, G., Hill, W. D., Clarke, T.-K., Shirali, M., Harris, S. E., Marioni, R. E., Liewald, D. C., Fawns-Ritchie, C., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0013-8 · Cited by 391 · see citing works
Jones, S. E., Tyrrell, J., Wood, A. R., Beaumont, R. N., Ruth, K. S., Tuke, M. A., Yaghootkar, H., Hu, Y., Teder-Laving, M., Hayward, C., et al. (2016) · PLOS Genetics · doi:10.1371/journal.pgen.1006125 · Cited by 388 · see citing works
A human cell atlas of fetal chromatin accessibility
Domcke, S., Hill, A. J., Daza, R. M., Cao, J., O’Day, D. R., Pliner, H. A., Aldinger, K. A., Pokholok, D., Zhang, F., Milbank, J. H., et al. (2020) · Science · doi:10.1126/science.aba7612 · Cited by 375 · see citing works
Corces, M. R., Shcherbina, A., Kundu, S., Gloudemans, M. J., Frésard, L., Granja, J. M., Louie, B. H., Eulalio, T., Shams, S., Bagdatli, S. T., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00721-x · Cited by 358 · see citing works
Simultaneous profiling of 3D genome structure and DNA methylation in single human cells
Lee, D.-S., Luo, C., Zhou, J., Chandran, S., Rivkin, A., Bartlett, A., Nery, J. R., Fitzpatrick, C., O’Connor, C., Dixon, J. R., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0547-z · Cited by 340 · see citing works
Self-citationPreissl, S., Fang, R., Huang, H., Zhao, Y., Raviram, R., Gorkin, D. U., Zhang, Y., Sos, B. C., Afzal, V., Dickel, D. E., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0079-3 · Cited by 332 · see citing works
Self-citationIndex and biological spectrum of human DNase I hypersensitive sites
Meuleman, W., Muratov, A., Rynes, E., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Teodosiadis, A., et al. (2020) · Nature · doi:10.1038/s41586-020-2559-3 · Cited by 331 · see citing works
GLU Variants Improve Transformer
Shazeer, N. (2020) · arXiv · doi:10.48550/arxiv.2002.05202 · Cited by 303 · see citing works
Joint profiling of histone modifications and transcriptome in single cells from mouse brain
Zhu, C., Zhang, Y., Li, Y. E., Lucero, J., Behrens, M. M., & Ren, B. (2021) · Nature Methods · doi:10.1038/s41592-021-01060-3 · Cited by 301 · see citing works
Self-citationConservation and divergence of cortical cell organization in human and mouse revealed by MERFISH
Fang, R., Xia, C., Close, J. L., Zhang, M., He, J., Huang, Z., Halpern, A. R., Long, B., Miller, J. A., Lein, E. S., et al. (2022) · Science · doi:10.1126/science.abm1741 · Cited by 277 · see citing works
Self-citationThe UCSC Genome Browser database: 2022 update
Lee, B. T., Barber, G. P., Benet-Pagès, A., Casper, J., Clawson, H., Diekhans, M., Fischer, C., Gonzalez, J. N., Hinrichs, A. S., Lee, C. M., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab959 · Cited by 273 · see citing works
Philentropy: Information Theory and Distance Quantification with R
Drost, H. (2018) · The Journal of Open Source Software · doi:10.21105/joss.00765 · Cited by 257 · see citing works
Ecker, J. R., Geschwind, D. H., Kriegstein, A. R., Ngai, J., Osten, P., Polioudakis, D., Regev, A., Šestan, N., Wickersham, I. R., & Zeng, H. (2017) · Neuron · doi:10.1016/j.neuron.2017.10.007 · Cited by 254 · see citing works
Self-citationSchumann, G., Liu, C., O’Reilly, P., Gao, H., Song, P., Xu, B., Ruggeri, B., Amin, N., Jia, T., Preis, S., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1611243113 · Cited by 241 · see citing works
Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells
Barakat, T. S., Halbritter, F., Zhang, M., Rendeiro, A. F., Perenthaler, E., Bock, C., & Chambers, I. (2018) · Cell stem cell · doi:10.1016/j.stem.2018.06.014 · Cited by 214 · see citing works
Hou, L., Bergen, S. E., Akula, N., Song, J., Hultman, C. M., Landén, M., Adli, M., Alda, M., Ardau, R., Arias, B., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw181 · Cited by 209 · see citing works
ATACseqQC: a Bioconductor package for post-alignment quality assessment of ATAC-seq data
Ou, J., Liu, H., Yu, J., Kelliher, M. A., Castilla, L. H., Lawson, N. D., & Zhu, L. J. (2018) · BMC Genomics · doi:10.1186/s12864-018-4559-3 · Cited by 209 · see citing works
Scotland, G., van den Berg, S. M., de Moor, M. H. M., Verweij, K. J. H., Krueger, R. F., Luciano, M., Vásquez, A. A., Matteson, L. K., Derringer, J. L., Esko, T., et al. (2015) · Behavior Genetics · doi:10.1007/s10519-015-9735-5 · Cited by 206 · see citing works
Self-citationMacrophage-specific gene functions in Spi1-directed innate immunity
Zakrzewska, A., Cui, C., Stockhammer, O. W., Benard, E. L., Spaink, H. P., & Meijer, A. H. (2010) · Blood · doi:10.1182/blood-2010-01-262873 · Cited by 199 · see citing works
Enhancer viruses for combinatorial cell-subclass-specific labeling
Graybuck, L. T., Daigle, T. L., Sedeño-Cortés, A. E., Walker, M., Kalmbach, B., Lenz, G. H., Morin, E., Nguyen, T. N., Garren, E., Bendrick, J. L., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.011 · Cited by 187 · see citing works
Self-citationgkmSVM: an R package for gapped-kmer SVM
Ghandi, M., Mohammad-Noori, M., Ghareghani, N., Lee, D., Garraway, L. A., & Beer, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw203 · Cited by 186 · see citing works
An atlas of gene regulatory elements in adult mouse cerebrum
Li, Y. E., Preissl, S., Hou, X., Zhang, Z., Zhang, K., Qiu, Y., Poirion, O. B., Li, B., Chiou, J., Liu, H., et al. (2021) · Nature · doi:10.1038/s41586-021-03604-1 · Cited by 185 · cited 6× · see citing works
“About 1000 nuclei were sufficient to identify >80% of the accessible regions in a cell type, consistent with our previous finding (28) (fig.”
BackgroundMethodResultInfluentialSelf-citationIto, J., Sugimoto, R., Nakaoka, H., YAMADA, S., Kimura, T., Hayano, T., & Inoue, I. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006883 · Cited by 179 · see citing works
The Role of Transposable Elements in Health and Diseases of the Central Nervous System
Reilly, M. T., Faulkner, G. J., Dubnau, J., Ponomarev, I., & Gage, F. H. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.3369-13.2013 · Cited by 175 · see citing works
Genetics of the human microglia regulome refines Alzheimer’s disease risk loci
Kosoy, R., Fullard, J. F., Zeng, B., Bendl, J., Dong, P., Rahman, S., Kleopoulos, S. P., Shao, Z., Girdhar, K., Humphrey, J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01149-1 · Cited by 168 · see citing works
Single nucleus multi-omics identifies human cortical cell regulatory genome diversity
Luo, C., Liu, H., Xie, F., Armand, E. J., Siletti, K., Bakken, T. E., Fang, R., Doyle, W. I., Stuart, T., Hodge, R. D., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100107 · Cited by 167 · see citing works
Self-citationLogue, M. W., Amstadter, A. B., Baker, D. G., Duncan, L. E., Koenen, K. C., Liberzon, I., Miller, M. W., Morey, R. A., Nievergelt, C. M., Ressler, K. J., et al. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.118 · Cited by 159 · see citing works
Self-citationSingle-cell DNA methylation and 3D genome architecture in the human brain
Tian, W., Zhou, J., Bartlett, A., Zeng, Q., Liu, H., Castanon, R. G., Kenworthy, M., Altshul, J., Valadon, C., Aldridge, A., et al. (2023) · Science · doi:10.1126/science.adf5357 · Cited by 154 · see citing works
Self-citationHigh-throughput chromatin accessibility profiling at single-cell resolution
Mezger, A., Klemm, S. L., Mann, I. K., Brower, K. K., Mir, A. A., Bostick, M. L., Farmer, A. A., Fordyce, P. M., Linnarsson, S., & Greenleaf, W. J. (2018) · Nature Communications · doi:10.1038/s41467-018-05887-x · Cited by 149 · see citing works
Self-citationDeniz, Ö., Ahmed, M., Todd, C. D., Rio‐Machín, A., Dawson, M. A., & Branco, M. R. (2020) · Nature Communications · doi:10.1038/s41467-020-17206-4 · Cited by 135 · see citing works
Axonal Endoplasmic Reticulum Dynamics and Its Roles in Neurodegeneration
Öztürk, Z., O’Kane, C. J., & Pérez-Moreno, J. J. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00048 · Cited by 127 · see citing works
Cross-species analysis of enhancer logic using deep learning
Minnoye, L., Taskiran, I. I., Mauduit, D., Fazio, M., Van Aerschot, L., Hulselmans, G., Christiaens, V., Makhzami, S., Seltenhammer, M., Karras, P., et al. (2020) · Genome Research · doi:10.1101/gr.260844.120 · Cited by 116 · see citing works
Species differences in the generation of reactive oxygen species by microglia
Colton, C. A., Wilt, S. G., Gilbert, D. L., Chernyshev, O. N., Snell, J. C., & Dubois-Dalcq, M. E. (1996) · Molecular and Chemical Neuropathology · doi:10.1007/bf02815200 · Cited by 104 · see citing works
Kim, Y. R., Kim, Y. M., Lee, J., Park, J., Lee, J. E., & Hyun, Y. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.613733 · Cited by 82 · see citing works
Functional characterization of Alzheimer’s disease genetic variants in microglia
Yang, X., Wen, J., Yang, H., Jones, I. R., Zhu, X., Liu, W., Li, B., Clelland, C. D., Luo, W., Wong, M. Y., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01506-8 · Cited by 71 · see citing works
Self-citationThe accessible chromatin landscape of the murine hippocampus at single-cell resolutionPreprint
Sinnamon, J. R., Torkenczy, K. A., Linhoff, M. W., Vitak, S. A., Mulqueen, R. M., Pliner, H. A., Trapnell, C., Steemers, F. J., Mandel, G., & Adey, A. (2019) · Genome Research · doi:10.1101/gr.243725.118 · Cited by 70 · see citing works
Genetic contributions to self-reported tiredness
International Consortium for Blood Pressure GWAS, Deary, V, CHARGE Consortium Aging and Longevity Group, CHARGE Consortium Inflammation Group, Hagenaars, S. P., Harris, S. E., Hill, W. D., Davies, G., Liewald, D. C. M., McIntosh, A. M., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.5 · Cited by 61 · see citing works
Playfoot, C. J., Duc, J., Sheppard, S., Joye, S., Coudray, A., Planet, E., & Trono, D. (2021) · Genome Research · doi:10.1101/gr.275133.120 · Cited by 57 · see citing works
Oproescu, A.-M., Han, S., & Schuurmans, C. J. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.642016 · Cited by 51 · see citing works
Spi‐B can functionally replace PU.1 in myeloid but not lymphoid development
Dahl, R. E., Ramírez‐Bergeron, D. L., Rao, S., & Simon, M. C. (2002) · The EMBO Journal · doi:10.1093/emboj/21.9.2220 · Cited by 49 · see citing works
The Molecular Pathway Regulating Bergmann Glia and Folia Generation in the Cerebellum
Leung, A. W., & Li, J. Y. H. (2017) · The Cerebellum · doi:10.1007/s12311-017-0904-3 · Cited by 46 · see citing works
Transposable elements in brain health and disease
Ahmadi, A., Toma, I. D., Vilor‐Tejedor, N., Ghamsari, M. R. E., & Sadeghi, I. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101153 · Cited by 45 · see citing works
Li, Y. E., Xiao, M., Shi, B., Yang, Y., Wang, D., Wang, F., Marcia, M., & Lu, Z. J. (2017) · Genome biology · doi:10.1186/s13059-017-1298-8 · Cited by 43 · see citing works
Self-citationUncovering the impact of noncoding variants in neurodegenerative brain diseases
Frydas, A., Wauters, E., van der Zee, J., & Broeckhoven, C. V. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.08.010 · Cited by 42 · see citing works
Marballi, K. K., & Gallitano, A. L. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00023 · Cited by 40 · see citing works
van Bree, E. J., Guimarães, R. L. F. P., Lundberg, M., Blujdea, E. R., Rosenkrantz, J. L., White, F. T. G., Poppinga, J., Ferrer‐Raventós, P., Schneider, A.-F. E., Clayton, I., et al. (2022) · Genome Research · doi:10.1101/gr.275515.121 · Cited by 29 · see citing works
Impact of IL-21-associated peripheral and brain crosstalk on the Alzheimer’s disease neuropathology
Agrawal, S., Baulch, J. E., Madan, S., Salah, S., Cheeks, S. N., Krattli, R. P., Subramanian, V. S., Acharya, M. M., & Agrawal, A. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04347-6 · Cited by 25 · see citing works
Crazy Little Thing Called Sox—New Insights in Oligodendroglial Sox Protein Function
Wittstatt, J., Reiprich, S., & Küspert, M. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20112713 · Cited by 22 · see citing works
Nelson, J. E., Baronia, R. B., Comiskey, G. E., & McGovern, T. F. (2017) · Alcoholism Treatment Quarterly · doi:10.1080/07347324.2017.1361763 · Cited by 21 · see citing works
Perdomo-Sabogal, Á., & Nowick, K. (2019) · Genome Biology and Evolution · doi:10.1093/gbe/evz131 · Cited by 20 · see citing works
Liu, B.-X., & Montgomery, S. (2019) · Human Genetics · doi:10.1007/s00439-019-02044-2 · Cited by 19 · see citing works
Comprehensive cellular‐resolution atlas of the adult human brain
Ding, S., Royall, J. J., Sunkin, S. M., Ng, L., Facer, B. A. C., Lesnar, P., Guillozet‐Bongaarts, A., McMurray, B., Szafer, A., Dolbeare, T. A., et al. (2016) · The Journal of Comparative Neurology · doi:10.1002/cne.24097 · Cited by 14 · see citing works
Self-citationFoxO1 Controls Redox Regulation and Cellular Physiology of BV-2 Microglial Cells
Seong, C., Kim, H. J., Byun, J., Kim, Y., & Kim, D. (2022) · Inflammation · doi:10.1007/s10753-022-01771-5 · Cited by 11 · see citing works
Functional characterization of Alzheimer's disease genetic variants in microglia
Yang, X., & Shen, Y. (2023) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.8206583 · Cited by 7 · see citing works
Self-Attention with Relative Position Representations
Shaw, P., Uszkoreit, J., & Vaswani, A. (2018) · arXiv · doi:10.48550/arxiv.1803.02155
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- [75]Hodge RD, Bakken TE, Miller JA, Smith KA, Barkan ER, Graybuck LT, Close JL, Long B, Johansen N, Penn O, Yao Z, Eggermont J, Höllt T, Levi BP, Shehata SI, Aevermann B, Beller A, Bertagnolli D, Brouner K, Casper T, Cobbs C, Dalley R, Dee N, Ding S-L, Ellenbogen RG, Fong O, Garren E, Goldy J, Gwinn RP, Hirschstein D, Keene CD, Keshk M, Ko AL, Lathia K, Mahfouz A, Maltzer Z, McGraw M, Nguyen TN, Nyhus J, Ojemann JG, Oldre A, Parry S, Reynolds S, Rimorin C, Shapovalova NV, Somasundaram S, Szafer A, Thomsen ER, Tieu M, Quon G, Scheuermann RH, Yuste R, Sunkin SM, Lelieveldt B, Feng D, Ng L, Bernard A, Hawrylycz M, Phillips JW, Tasic B, Zeng H, Jones AR, Koch C, Lein ES, Conserved cell types with divergent features in human versus mouse cortex. Nature. 573, 61– 68 (2019). 31435019 PMC6919571
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Gabitto, M. I., Travaglini, K. J., Rachleff, V. M., Kaplan, E. S., Long, B., Ariza, J., Ding, Y., Mahoney, J. T., Dee, N., Goldy, J., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01774-5 · Cited by 397 · see citing works
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Linder, J., Srivastava, D., Yuan, H., Agarwal, V., & Kelley, D. R. (2025) · Nature Genetics · doi:10.1038/s41588-024-02053-6 · Cited by 265 · see citing works
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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
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Ben‐Simon, Y., Hooper, M. J., Narayan, S., Daigle, T. L., Dwivedi, D., Way, S. W., Oster, A., Stafford, D. A., Mich, J. K., Taormina, M. J., et al. (2025) · Cell · doi:10.1016/j.cell.2025.05.002 · Cited by 81 · see citing works
Self-citationAdvances and applications in single-cell and spatial genomics
Wang, J., Ye, F., Chai, H., Jiang, Y., Wang, T., Ran, X., Xia, Q., Xu, Z., Fu, Y., Zhang, G., et al. (2024) · Science China Life Sciences · doi:10.1007/s11427-024-2770-x · Cited by 69 · 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
Self-citationLiu, Z., Zhang, S., James, B. T., Galani, K., Mangan, R. J., Fass, S. B., Liang, C., Wagle, M. M., Boix, C. A., Tanigawa, Y., et al. (2025) · Cell · doi:10.1016/j.cell.2025.06.031 · Cited by 65 · see citing works
Schizophrenia genomics: genetic complexity and functional insights
Sullivan, P. F., Yao, S., & Hjerling‐Leffler, J. (2024) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00837-7 · Cited by 62 · see citing works
Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium
Hecker, N., Kempynck, N., Mauduit, D., Abaffyová, D., Vandepoel, R., Dieltiens, S., Borm, L. E., Sarropoulos, I., González‐Blas, C. B., Man, J. D., et al. (2025) · Science · doi:10.1126/science.adp3957 · Cited by 44 · see citing works
Genomics of schizophrenia, bipolar disorder and major depressive disorder
Owen, M. J., Bray, N. J., Walters, J., & O’Donovan, M. C. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00843-0 · Cited by 42 · see citing works
From morphology to single-cell molecules: high-resolution 3D histology in biomedicine
Xu, X., Su, J., Zhu, R., Li, K., Zhao, X., Fan, J., & Mao, F. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02240-x · Cited by 41 · see citing works
An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases
Oguchi, A., Suzuki, A., Komatsu, S., Yoshitomi, H., Bhagat, S., Son, R., Bonnal, R. J. P., Kojima, S., Koido, M., Takeuchi, K., et al. (2024) · Science · doi:10.1126/science.add8394 · Cited by 37 · see citing works
Epigenomic insights into common human disease pathology
Bell, C. G. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05206-2 · Cited by 32 · see citing works
Human brain vascular multi-omics elucidates disease-risk associations
Reid, M. M., Menon, S., Liu, H., Zhou, H., Hu, Z., Frerich, S., Ding, B., Oveisgharan, S., Zhang, Z., Nelson, S., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.07.001 · Cited by 33 · see citing works
Microglial intervention in ischemic stroke: Roles and intervention strategies
Ji, C., Sheng, L., Han, K., Yuan, P., Li, W., Chen, L., & Gao, Y. (2025) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-24-01166 · Cited by 27 · see citing works
Abdel-Rasol, M. A., & El-Sayed, W. M. (2025) · European journal of medical research · doi:10.1186/s40001-025-03073-6 · Cited by 27 · see citing works
Chinese Immune Multi-Omics Atlas
Yin, J., Zheng, Y., Huang, Z., Zhou, W., Yuan, Y., Cai, P., Bai, Y., Yang, S., Gao, Y., Duan, S., et al. (2026) · Science · doi:10.1126/science.adt3130 · Cited by 34 · see citing works
Self-citationAre we there yet? Exploring astrocyte heterogeneity one cell at a time
O’Dea, M. R., & Hasel, P. (2024) · Glia · doi:10.1002/glia.24621 · Cited by 27 · 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
Self-citationEmergence of phase clusters and coexisting states reveals the structure-function relationship
Yu, D., Wu, Y., Ding, Q., Li, T., & Jia, Y. (2024) · Physical review. E · doi:10.1103/physreve.109.054312 · Cited by 25 · see citing works
Scalable high-performance single cell data analysis with BPCellsPreprint
Parks, B. E., & Greenleaf, W. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.27.645853 · Cited by 23 · see citing works
Gerstner, N., Fröhlich, A. S., Matosin, N., Gagliardi, M., Cruceanu, C., Ködel, M., Rex‐Haffner, M., Tu, X., Mostafavi, S., Ziller, M. J., et al. (2025) · Science Advances · doi:10.1126/sciadv.adq2290 · Cited by 23 · see citing works
Organism-wide cellular dynamics and epigenomic remodeling in mammalian aging
Lu, Z., Zhang, Z., Xu, Z., Abdulraouf, A., Zhou, W. Y., & Cao, J. (2026) · Science · doi:10.1126/science.adw6273 · Cited by 27 · see citing works
Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes
Maury, E. A., Jones, A., Seplyarskiy, V., Nguyen, T. T., Rosenbluh, C., Bae, T., Wang, Y., Abyzov, A., Khoshkhoo, S., Chahine, Y., et al. (2024) · Science · doi:10.1126/science.adq1456 · Cited by 18 · see citing works
Modelling and design of transcriptional enhancers
Winter, S. D., Konstantakos, V., & Aerts, S. (2025) · Nature Reviews Bioengineering · doi:10.1038/s44222-025-00280-y · Cited by 20 · see citing works
The neuroscience of mental illness: Building toward the future
Gordon, J. A., Dzirasa, K., & Petzschner, F. H. (2024) · Cell · doi:10.1016/j.cell.2024.09.028 · Cited by 20 · see citing works
CREsted: modeling genomic and synthetic cell-type-specific enhancers across tissues and species
Kempynck, N., Winter, S. D., Blaauw, C. H., Konstantakos, V., Ekşi, E. C., Dieltiens, S., Abaffyová, D., Bercier, V., Taskiran, I. I., Hulselmans, G. J., et al. (2026) · Nature Methods · doi:10.1038/s41592-026-03057-2 · Cited by 24 · see citing works
Biomimic and bioinspired soft neuromorphic tactile sensory system
Kang, K., Kim, K., Baek, J. H., Lee, D. J., & Yu, K. J. (2024) · Applied Physics Reviews · doi:10.1063/5.0204104 · Cited by 18 · see citing works
Community modularity structure promotes the evolution of phase clusters and chimeralike states
Yu, D., Li, X., Wang, X., Huang, W., Hu, X., & Jia, Y. (2025) · Physical review. E · doi:10.1103/physreve.111.034311 · Cited by 18 · see citing works
Multiomic single-cell profiling identifies critical regulators of postnatal brain
Clarence, T., Bendl, J. M., Cao, X. D., Wang, X., Zheng, S., Hoffman, G. E., Kozlenkov, A., Hong, A., Iskhakova, M., Jaiswal, M. K., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02083-8 · Cited by 20 · see citing works
Just a SNP away: The future of in vivo massively parallel reporter assay
Degner, K. N., Bell, J., Jones, S. D., & Won, H. (2024) · Cell Insight · doi:10.1016/j.cellin.2024.100214 · Cited by 13 · see citing works
Zhang, S., Shu, H., Zhou, J., Rubin-Sigler, J., Yang, X. J., Liu, Y., Cooper‐Knock, J., Monte, E., Zhu, C., Tu, S., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02725-6 · Cited by 19 · see citing works
Self-citationWei, X., Xu, Y.-Y., Yang, D.-C., Kim, K., Yi, L., Luo, W.-Z., Lin, X., Xiang, Y., Williams, A. B., Wang, X.-T., et al. (2026) · Nature Biotechnology · doi:10.1038/s41587-026-03013-7 · Cited by 16 · see citing works
Self-citationYang, H., Sun, W., Li, J., & Zhang, X. (2025) · Annals of General Psychiatry · doi:10.1186/s12991-025-00557-x · Cited by 16 · see citing works
An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional RegulationPreprint
Moore, J. E., Pratt, H., Fan, K., Phalke, N. N., Fisher, J., Elhajjajy, S. I., Andrews, G., Gao, M., Shedd, N., Fu, Y., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.26.629296 · Cited by 13 · see citing works
Shevade, K., Yang, Y. A., Feng, K., Mader, K., Sevi̇m, V., Parsons, J., Arora, G., Elfawy, H. A., Mace, R., Federman, S., et al. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101222 · Cited by 15 · see citing works
State-specific enhancer landscapes govern microglial plasticity
Hamagami, N., Kapadia, D., Barclay, K. M., Yanlong, H., Abduljawad, N., Cheng, Z., McLaughlin, L., Singhania, D., Ding, X., Yang, J., et al. (2026) · Immunity · doi:10.1016/j.immuni.2025.11.023 · Cited by 20 · see citing works
Stress Molecular Signaling in Interaction With Cognition
Lugenbühl, J. F., Viho, E. M. G., Binder, E. B., & Daskalakis, N. P. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.09.023 · Cited by 12 · see citing works
Dong, P., Song, L., Bendl, J. M., Misir, R., Shao, Z., Edelstien, J., Davis, D. A., Haroutunian, V. H., Scott, W. K., Acker, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54448-y · Cited by 12 · see citing works
Identification and application of cell-type-specific enhancers for the macaque brain
Li, L., Huang, Y., Lu, D., Fu, J., Wu, L., Chen, Z., Liao, H., Zhang, J., Li, L., Gu, T., et al. (2025) · Cell · doi:10.1016/j.cell.2025.06.040 · Cited by 12 · see citing works
Learning the cellular origins across cancers using single-cell chromatin landscapes
Bairakdar, M. D., Lee, W., Giotti, B., Kumar, A., Štancl, P., Wagenblast, E., Hambardzumyan, D., Polak, P. P., Karlić, R., & Tsankov, A. M. (2025) · Nature Communications · doi:10.1038/s41467-025-63957-3 · Cited by 13 · see citing works
Neuronal Circuit Evolution: From Development to Structure and Adaptive SignificancePreprint
Konstantinides, N., & Desplan, C. (2024) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a041493 · Cited by 12 · see citing works
Epigenetic Changes Associated With Obesity-related Metabolic Comorbidities
Sandovici, I., Morais, T., Constância, M., & Monteiro, M. P. (2025) · Journal of the Endocrine Society · doi:10.1210/jendso/bvaf129 · Cited by 14 · see citing works
Mapping human brain cell type origin and diseases through single-cell transcriptomics
Soorajkumar, A., Balan, B., Nassir, N., Akter, H., Shahin, Z., Berdiev, B. K., Woodbury‐Smith, M., Khalil, R., Cisse, B., Benamer, H. T. S., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03562-6 · Cited by 13 · see citing works
Liu, A., Citu, C., Enduru, N., Chen, X., Tung, C.-H., Sinha, T., Sepulveda, S. E., Manuel, A. M., Gorski, D., Fernandes, B. S., et al. (2025) · Science Advances · doi:10.1126/sciadv.adw4917 · Cited by 14 · see citing works
Transcriptomic and genetic analysis suggests a role for mitochondrial dysregulation in schizophreniaPreprint
Bast, L., Yao, S., Martínez‐López, J. A., Memic, F., French, H., Valiukonyte, M., Karlsson, R., Wen, J., Song, J., Zhang, R., et al. (2025) · medRxiv · doi:10.1101/2025.03.14.25323827 · Cited by 11 · see citing works
Cross-species consensus atlas of the primate basal gangliaPreprint
Johansen, N., Fu, Y., Schmitz, M. T., Dubuc, A., Kempynck, N., Wirthlin, M. E., Garcia, A. D., Hewitt, M. N., Turner, M. A., Seeman, S. C., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.15.694496 · Cited by 17 · see citing works
Self-citationMaintenance of delay-period activity in working memory task is modulated by local network structure
Yu, D., Li, T., Ding, Q., Wu, Y., Fu, Z., Zhan, X., Yang, L., & Jia, Y. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012415 · Cited by 10 · see citing works
Functional genomics and systems biology in human neuroscience
Konopka, G., & Bhaduri, A. (2023) · Nature · doi:10.1038/s41586-023-06686-1 · Cited by 10 · see citing works
Human Body Single-Cell Atlas of 3D Genome Organization and DNA MethylationPreprint
Zhou, J., Wu, Y., Liu, H., Tian, W., Castanon, R., Bartlett, A., Zhang, Z., Yao, G., Shi, D., Clock, B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.23.644697 · Cited by 10 · see citing works
Self-citationHu, B., Zhuang, X.-L., Zhou, L., Zhang, G., Cooper, D. N., & Wu, D. (2024) · Molecular Biology and Evolution · doi:10.1093/molbev/msae001 · Cited by 8 · see citing works
Dwivedi, A. K., Mahesh, A., Sanfeliu, A., Larkin, J., Siwicki, R. A., Sweeney, K. J., O’Brien, D. F., Widdess‐Walsh, P., Picelli, S., Henshall, D. C., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.184518 · Cited by 9 · see citing works
Wu, L., Sun, Y., Wu, Z., Liu, R., Yin, Y., Wong, N.-L., Ju, W.-Z., & Zhang, H. (2024) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2024.117746 · Cited by 9 · see citing works
Chromatin accessibility provides a window into the genetic etiology of human brain disease
Bendl, J. M., Fullard, J. F., Girdhar, K., Dong, P., Kosoy, R., Zeng, B., Hoffman, G. E., & Roussos, P. (2025) · Trends in Genetics · doi:10.1016/j.tig.2025.01.001 · Cited by 9 · see citing works
Human-scATAC-Corpus: a comprehensive database of scATAC-seq data
Chen, X., Gao, Z., Li, K., Wang, Z., Jiang, Q., Cui, X., Li, Z., & Jiang, R. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1216 · Cited by 10 · see citing works
Self-citationThis is the largest map of the human brain ever made
Conroy, G. (2023) · Nature · doi:10.1038/d41586-023-03192-2 · Cited by 9 · see citing works
Human body single-cell atlas of three-dimensional genome organization and DNA methylation
Zhou, J., Wu, Y., Liu, H., Tian, W., Castanon, R., Bartlett, A., Zhang, Z., Yao, G., Shi, D., Clock, B., et al. (2026) · Science · doi:10.1126/science.adx0673 · Cited by 21 · see citing works
Self-citationSpatially resolved mapping of cells associated with human complex traitsPreprint
Song, L., Chen, W., Hou, J., Guo, M., & Yang, J. (2024) · medRxiv · doi:10.1101/2024.10.31.24316538 · Cited by 8 · see citing works
Zhang, Q., Sun, F., Zhang, R., Zhao, D., Zhu, R., Cheng, X., Long, X., Hou, X., Yan, R., Cao, Y., et al. (2024) · Life Medicine · doi:10.1093/lifemedi/lnae028 · Cited by 6 · see citing works
Dynamics of chromatin accessibility during human first-trimester neurodevelopmentPreprint
Mannens, C. C. A., Hu, L., Lönnerberg, P., Schipper, M., Reagor, C. C., Li, X., He, X., Barker, R. A., Sundström, E., Danielle Posthuma, B., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.18.553878 · Cited by 7 · see citing works
Self-citationHe, Y., & Wu, H. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1728091 · Cited by 5 · see citing works
Kabbe, M., Agirre, E., Carlström, K. E., Dumral, Ö., Lor, Y. K., Pohl, F. B., Ruffin, N., van Bruggen, D., Meijer, M., Seeker, L. A., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02208-0 · Cited by 10 · see citing works
Ancient regulatory evolution shapes individual language abilities in present-day humans
Casten, L. G., Koomar, T., Thomas, T., Koh, J., Hofammann, D., Thenuwara, S., Momany, A. M., O’Brien, M., Murray, J. C., Tomblin, J. B., et al. (2026) · Science Advances · doi:10.1126/sciadv.aed5260 · Cited by 5 · see citing works
Single-cell and spatial omics: exploring hypothalamic heterogeneity
Junaid, M., Lee, E. J., & Lim, S. B. (2024) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-24-00231 · Cited by 6 · see citing works
Zhang, S., Shu, H., Zhou, J., Rubin-Sigler, J., Yang, X. J., Liu, Y., Cooper‐Knock, J., Monte, E., Zhu, C., Tu, S., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.14.594252 · Cited by 5 · see citing works
Self-citationSingle-nucleus multiome analysis of human cerebellum in Alzheimer’s disease-related dementiaPreprint
Cheng, F., Feng, Y., Flanagan, M. E., Bonakdarpour, B., Jamshidi, P., Castellani, R. J., Mao, Q., Chu, X., Gao, H., Liu, Y., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4871032/v1 · Cited by 5 · see citing works
EpiAgent: Foundation model for single-cell epigenomic dataPreprint
Chen, X., Li, K., Cui, X., Wang, Z., Jiang, Q., Lin, J., Li, Z., Gao, Z., & Jiang, R. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.19.629312 · Cited by 5 · see citing works
Self-citationMicroglial plasticity governed by state-specific enhancer landscapesPreprint
Hamagami, N., Kapadia, D., Abduljawad, N., Cheng, Z., McLaughlin, L., Singhania, D., Barclay, K. M., Jin, Y., Sun, Z., Bayguinov, P. O., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.30.635595 · Cited by 5 · see citing works
Li, A., Allen, P. C., Wang, Y., Cui, H., Lin, T., Sun, Y., Wang, X. M., Tan, X., Walker, A., Wang, S., et al. (2025) · medRxiv · doi:10.1101/2025.05.24.25328275 · Cited by 5 · see citing works
scBlood: A comprehensive single-cell accessible chromatin database of blood cells
Zhao, Y., Yu, Z.-M., Cui, T., Li, L.-D., Li, Y.-Y., Qian, F., Zhou, L.-W., Li, Y., Fang, Q.-L., Huang, X., et al. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.06.015 · Cited by 4 · see citing works
Self-citationUnique and divergent features of human brain development
Salamon, I., Doyle, D. Z., Bandler, R. C., Pattabiraman, K., & Šestan, N. (2025) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2025.103133 · Cited by 5 · see citing works
Zhou, H., Verma, V., Li, X., Li, Z., Shedd, N., Li, T. C., Yang, H., Zhang, A., Borsari, B., Buyske, S. G., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1217 · Cited by 4 · see citing works
Single‐cell digital twins identify drug targets and repurposable medicine in Alzheimer’s disease
Ren, Y., Hu, M., Li, Y. E., Pieper, A. A., Cummings, J. L., & Cheng, F. (2025) · Alzheimer s & Dementia · doi:10.1002/alz70859_102982 · Cited by 4 · see citing works
Self-citationXiang, Y., Zhang, S., Huang, Y., Zheng, Z., Sun, J., Zhao, Q., Zhou, P., Qi, X., Li, J., Xiong, F., et al. (2025) · BMC Biology · doi:10.1186/s12915-025-02263-2 · Cited by 4 · see citing works
Kabbe, M., Agirre, E., Carlström, K. E., Pohl, F. B., Ruffin, N., van Bruggen, D., Meijer, M., Seeker, L., Bestard-Cuche, N., Lederer, A. R., et al. (2024) · bioRxiv · doi:10.1101/2024.04.15.589512 · Cited by 1 · see citing works
Leone, M. J., van de Weerd, R., Brown, A. R., Noh, M., Phan, B. N., Wang, A. Z., Corrigan, K. A., Yeramosu, D., Sestili, H. H., Arokiaraj, C. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.20.660790 · Cited by 4 · see citing works
Self-citationPluripotent stem cells-based neural organoids for modelling human brain development and diseases
Tong, L., Tian, P., Wang, R., Niu, S., Wang, R., Ye, Y., Wu, Y., Zhang, W., Wang, Y., Foggetti, A., et al. (2025) · Cell & Bioscience · doi:10.1186/s13578-025-01515-6 · Cited by 3 · see citing works
Uemura, K., Hiro, S., Attachaipanich, S., Du, R., Yusof, N. I. S. M., Kinoshita, M., Hikosaka, M., & Ohtsuki, G. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2025.1669272 · Cited by 5 · see citing works
Catching, A., Weller, C. A., Hu, F., Bromberek, S., Abbas, S., Daida, K., Malik, L., Baker, B., Auluck, P. K., Screven, L. A., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117110 · Cited by 4 · see citing works
Progress in biomedical engineering during 2023 in China
Yu, Z., Song, Z., Xu, H., Wang, J., Wang, C., & Zhao, G. (2024) · EngMedicine · doi:10.1016/j.engmed.2024.100039 · Cited by 3 · see citing works
Zhao, G., & Lai, B. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf123 · Cited by 3 · see citing works
Fusco, D., Marinelli, C., André, M., Troiani, L., Noè, M., Pizzagalli, F., Marnetto, D., & Provero, P. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011658 · Cited by 3 · see citing works
Decoding cnidarian cell type gene regulation
Elek, A., Iglesias, M., Mahieu, L., Zolotarov, G., Grau‐Bové, X., Aerts, S., & Sebé-Pedrós, A. (2025) · Nature Ecology & Evolution · doi:10.1038/s41559-025-02906-1 · Cited by 3 · see citing works
Single-cell multiomic human brain atlas reveals regulatory drivers of cortical regionality
Palmer, C. R., Song, J., Yang, B., Chen, C.-J., Diep, D. H., Conklin, K. Y., Plongthongkum, N., Indralingam, H. S., Liu, C. S., Kurtz, J. S., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-69368-2 · Cited by 3 · see citing works
Self-citationFrom Cells to Selves and Back: Human Neurodiversity at Single-Cell Resolution
Lessi, M., Caporale, N., & Testa, G. (2025) · Physiology · doi:10.1152/physiol.00010.2025 · Cited by 3 · see citing works
Zhao, Z., Liu, A., Citu, C., Enduru, N., Chen, X., Manuel, A. M., Sinha, T., Gorski, D., Fernandes, B. S., Yu, M., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4622123/v1 · Cited by 3 · see citing works
Single-cell Characterization of DNA Hydroxymethylation of the Mouse Brain During AgingPreprint
Bai, Y., Yuan, T., Ren, L., Huan, Y., Yang, F., Li, Y., Zhang, A., Liu, Y., Tian, T., Kang, N., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.29.656780 · Cited by 3 · see citing works
Self-citationPredicting cell type-specific coverage profiles from DNA sequencePreprint
Linder, J., Yuan, H., & Kelley, D. R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.10.658961 · Cited by 3 · see citing works
Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal GangliaPreprint
Chang, L., Li, K., Xie, Y., Zhong, G., Rink, J. A., Báez-Becerra, C. T., Lie, A., Indralingam, H. S., Dong, K., Loe, T. H., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.03.703645 · Cited by 4 · see citing works
Self-citationFrom identity to function: unveiling the cellular complexity of hypothalamic feeding circuits
Littleton, S. H., Tadross, J. A., & Yeo, G. S. H. (2025) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-025-10004-7 · Cited by 2 · see citing works
Denoising spatial epigenomic data via deep matrix factorization
Wang, S. S., Xu, H., Wang, J., Xiao, Y., Dai, S., Lu, J., Cao, R., Chen, X., & Qu, K. (2026) · Nature Computational Science · doi:10.1038/s43588-025-00941-3 · Cited by 2 · see citing works
Single-nucleus multiple-organ chromatin accessibility landscape in the adult rat
Li, R., Duan, S., Deng, Q., Ma, W., Liu, C., Gao, P., Li, L., & Yuan, Y. (2026) · GigaScience · doi:10.1093/gigascience/giag013 · Cited by 1 · see citing works
Eyring, K. W., Liu, C., Elhajjaoui, N., Abuhanna, K. D., Zhang, Y., von Behren, Z., Tsai, M. J., Eskin, E., Geschwind, D. H., & Luo, C. (2026) · Cell Genomics · doi:10.1016/j.xgen.2026.101278 · Cited by 6 · see citing works
- Authors
- Li, Y. E., Preissl, S., Miller, M., Johnson, N. D., Wang, Z., Jiao, H., Zhu, C., Wang, Z., Xie, Y., Poirion, O., Kern, C., Pinto-Duarte, A., Tian, W., Siletti, K., Emerson, N., Osteen, J., Lucero, J., Lin, L., Yang, Q., Zhu, Q., Zemke, N., Espinoza, S., Yanny, A. M., Nyhus, J., Dee, N., Casper, T., Shapovalova, N., Hirschstein, D., Hodge, R. D., Linnarsson, S., Bakken, T., Levi, B., Keene, C. D., Shang, J., Lein, E., Wang, A., Behrens, M. M., Ecker, J. R., & Ren, B.
- Affiliations
- University of California San Diego (US)
- Salk Institute for Biological Studies (US)
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
- Karolinska Institutet (SE)
- Allen Institute for Brain Science (US)
- University of Washington (US)
- Corresponding author
- Ren, Bing
- ORCID
- Li, Yang Eric
- Preissl, Sebastian
- Miller, Michael
- Johnson, Nicholas D.
- Wang, Zihan
- Zhu, Chenxu
- Wang, Zhaoning
- Xie, Yang
- Poirion, Olivier
- Kern, Colin
- Pinto-Duarte, Antonio
- Tian, Wei
- Siletti, Kimberly
- Emerson, Nora
- Osteen, Julia
- Lucero, Jacinta
- Yang, Qian
- Zhu, Quan
- Zemke, Nathan
- Espinoza, Sarah
- Yanny, Anna Marie
- Nyhus, Julie
- Dee, Nick
- Casper, Tamara
- Shapovalova, Nadiya
- Hirschstein, Daniel
- Hodge, Rebecca D.
- Linnarsson, Sten
- Bakken, Trygve
- Levi, Boaz
- Keene, C. Dirk
- Shang, Jingbo
- Lein, Ed
- Wang, Allen
- Behrens, M. Margarita
- Ecker, Joseph R.
- Ren, Bing
- Venue
- Science
- Published
- 2023-10-13
- Volume
- 382
- Issue
- 6667
- Pages
- eadf7044-eadf7044
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC10852054
- OpenAlex
- W4387568435
- Cited by
- 173
- References
- 140
- Citations by year
- 2026: 55 · 2025: 68 · 2024: 43 · 2023: 7
- FWCI
- 15.42
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (2040727)
- Nancy and Buster Alvord Endowment
- University of Washington
- Life Sciences Research Foundation
- National Institutes of Health (5u01mh114812-03, 1s10od026929-01, Bridge2AI, U01MH114812)
- University of California, San Diego (#S10 OD026929)
- Department of Laboratory Medicine and Pathology, University of Washington
- National Institute of Mental Health (U01MH114828, U01MH114812, UM1MH130994)
- National Human Genome Research Institute (U54HG012510)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- single-cell chromatin accessibility, human brain, snATAC-seq, brain cell types, neuropsychiatric disorders, schizophrenia, bipolar disorder, Alzheimer's disease, major depressive disorder, deep learning prediction
- MeSH terms
- Animals, Atlases as Topic, Brain, Chromatin, DNA, Humans, Neurons, Regulatory Sequences, Nucleic Acid, Mice, Single-Cell Analysis
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