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Chromosome conformation elucidates regulatory relationships in developing human brain
Open accessAbstract
Three-dimensional physical interactions within chromosomes dynamically regulate gene expression in a tissue-specific manner. However, the 3D organization of chromosomes during human brain development and its role in regulating gene networks dysregulated in neurodevelopmental disorders, such as autism or schizophrenia, are unknown. Here we generate high-resolution 3D maps of chromatin contacts during human corticogenesis, permitting large-scale annotation of previously uncharacterized regulatory relationships relevant to the evolution of human cognition and disease. Our analyses identify hundreds of genes that physically interact with enhancers gained on the human lineage, many of which are under purifying selection and associated with human cognitive function. We integrate chromatin contacts with non-coding variants identified in schizophrenia genome-wide association studies (GWAS), highlighting multiple candidate schizophrenia risk genes and pathways, including transcription factors involved in neurogenesis, and cholinergic signalling molecules, several of which are supported by independent expression quantitative trait loci and gene expression analyses. Genome editing in human neural progenitors suggests that one of these distal schizophrenia GWAS loci regulates FOXG1 expression, supporting its potential role as a schizophrenia risk gene. This work provides a framework for understanding the effect of non-coding regulatory elements on human brain development and the evolution of cognition, and highlights novel mechanisms underlying neuropsychiatric disorders.
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“In contrast, this interaction was not observed in Hi-C experiments performed in cells neither from adult human dorsolateral prefrontal cortex (Schmitt et al. 2016; supplementary fig. S9, Supplementary Material online) nor from developing human cerebral cortex at mid-gestation (Won et al. 2016; supplementary fig. S10, Supplementary Material online).”
From The Human Accelerated Region HAR202 Controls NPAS3 Expression in the Developing Forebrain Displaying Differential Enhancer Activity Between Modern and Archaic Human Sequences (2024) · cites this paper as Won et al. 2016
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In the citing paper
“new methodologies, such as Hi-C and single-cell sequencing, have yet to be fully integrated at scale with brain genomics data (13–16).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [13]
Experimental — accuracy not yet measuredIn the citing paper
“MAGMA assigns SNPs to the nearest genes, which has two major pitfalls. First, it is becoming increasingly recognized that non-coding SNPs can regulate distal genes via long range (>10 kb) regulatory interactions, whereby distal enhancers are brought into contact with the gene promoter3,4.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [4]
In the citing paper
“Since 3D chromatin loops are highly tissue-specific4, it is important to decide which Hi-C datasets are appropriate to identify target genes for each disorder.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [4]
In the citing paper
“SCZ and BD-associated genes were also enriched for acetylcholinergic signaling, supporting previous studies that altered cholinergic signaling contributes to SCZ and BD pathogenesis4,22.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [4]
In the citing paper
“Only ~31% of the interactions in our adult Hi-C data were detected in the fetal dataset (figs. S39 and S40) (13).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [13]
In the citing paper
“The majority of SCZ genes were not even in LD with the index SNPs (~67%, or 748 of 1111 genes with r2 < 0.6) (fig. S45), consistent with the fact that regulatory relationships often do not follow linear genome organization (13).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [13]
In the citing paper
“Brain Hi-C data (Wang et al., 2018; Won et al., 2016) detected a direct interaction of the cross-disorder association region with NOX4 in both adult and fetal brain (interaction p = 3.2 3 10 16 and 9.3 3 10 6 , respectively).”
From Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders (2019) · cites this paper as Won et al., 2016
In the citing paper
“Crucially, recent studies have shown that genes located far outside of a locus are often implicated (see functional architecture section below) (Wang et al., 2018a; Won et al., 2016).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Won et al., 2016
In the citing paper
“assigning even well-annotated genomic regions to specific genes is not as simple as choosing the closest gene or genes containing variation that is highly correlated with the associated SNPs which is usually the default approach (Whalen et al., 2016; Won et al., 2016)”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Won et al., 2016
In the citing paper
“around half of non-coding regions have regulatory functions that are shared across tissues meaning that half of the regulatory elements in a given tissue may be relatively specific to a tissue, cell type, or developmental stage (Liu et al., 2017a; Roadmap Epigenomics Consortium, 2015; Won et al., 2016)”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Won et al., 2016
In the citing paper
“disease-associated SNPs in non-coding areas of the genome influence genes associated with diseases including Alzheimer’s Disease (AD)”
From Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration (2023) · cites this paper as [46]
In the citing paper
“We detected 187,674 and 167,551 promoter-based interactions3,4 from NeuN+ and NeuN− cells, respectively (Fig. 2a).”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [4]
In the citing paper
“We identified 24,544 unique loops from published Hi-C data created in human brain tissue derived from the germinal zone and cortical plate41”
From Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression (2020) · cites this paper as [41]
In the citing paper
“We and others have shown that enhancers often regulate distal genes4,15,16”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [4]
In the citing paper
“Cortical plate and germinal zone loops were then merged to create a master set of 24,544 loops spanning the two brain tissues.”
From Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression (2020) · cites this paper as [41]
In the citing paper
“we observed a similar increase in insulation around SOX11 (Figure S3M).”
From Multiscale 3D Genome Rewiring during Mouse Neural Development (2017) · cites this paper as Won et al., 2016
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Citations
Cites
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
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
Self-citationA General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
Synaptic, transcriptional and chromatin genes disrupted in autism
Study, T. D., De Rubeis, S., Autism, H. M. C. F., UK10K Consortium, The Autism Sequencing Consortium, He, X., Goldberg, A. P., Poultney, C. S., Samocha, K., Ercument Cicek, A., et al. (2014) · Nature · doi:10.1038/nature13772 · Cited by 2,746
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679
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Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083
10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719
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
Identification 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
Self-citationADHD 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
Self-citationGERAD1 Consortium, Pardiñas, A. F., CRESTAR Consortium, Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., Legge, S. E., Bishop, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0059-2 · Cited by 1,552
Self-citationGenomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
Lee, P. H., Anttila, V., Won, H., Feng, Y.-C. A., Rosenthal, J., Zhu, Z., Tucker-Drob, E. M., Nivard, M. G., Grotzinger, A. D., Posthuma, D., et al. (2019) · Cell · doi:10.1016/j.cell.2019.11.020 · Cited by 1,381
“We used an array of functional genomics resources, including brain eQTL and Hi-C data (Wang et al., 2018; Won et al., 2016) to prioritize potential candidate genes to the identified regions (STAR Methods; Figure 2B).”
BackgroundMethodInfluentialSelf-citationMultiscale 3D Genome Rewiring during Mouse Neural Development
Bonev, B., Mendelson Cohen, N., Szabo, Q., Fritsch, L., Papadopoulos, G. L., Lubling, Y., Xu, X., Lv, X., Hugnot, J.-P., Tanay, A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.043 · Cited by 1,338
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
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965
Self-citationThe genetic architecture of the human cerebral cortex
Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., et al. (2020) · Science · doi:10.1126/science.aay6690 · Cited by 876
Self-citationIntegrative 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
Self-citationPsychiatric Genomics: An Update and an Agenda
Sullivan, P. F., Agrawal, A., Bulik, C. M., Andreassen, O. A., Børglum, A. D., Breen, G., Cichon, S., Edenberg, H. J., Faraone, S. V., Gelernter, J., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.17030283 · Cited by 676
Wang, Y., Song, F., Zhang, B., Zhang, L., Xu, J., Kuang, D., Li, D., Choudhary, M. N. K., Li, Y., Hu, M., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1519-9 · Cited by 559
Genetic insights into the neurodevelopmental origins of schizophrenia
Birnbaum, R., & Weinberger, D. R. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.125 · Cited by 509
Gusev, A., Mancuso, N., Won, H., Kousi, M., Finucane, H. K., Reshef, Y., Song, L., Safi, A., Schizophrenia Working Group of the Psychiatric Genomics Consortium, McCarroll, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0092-1 · Cited by 491
Self-citationDefining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
Sullivan, P. F., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.01.015 · Cited by 452
“Crucially, recent studies have shown that genes located far outside of a locus are often implicated (see Functional Architecture section below) (Wang et al., 2018a; Won et al., 2016).”
BackgroundInfluentialSelf-citationThe Role of m6A/m-RNA Methylation in Stress Response Regulation
Engel, M., Eggert, C., Kaplick, P. M., Eder, M., Röh, S., Tietze, L., Namendorf, C., Arloth, J., Weber, P., Rex-Haffner, M., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.07.009 · Cited by 411
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 426
The Three-Dimensional Organization of Mammalian Genomes
Yu, M., & Ren, B. (2017) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100616-060531 · Cited by 373
Zhang, Y., Li, T., Preißl, S., Amaral, M. L., Grinstein, J. D., Farah, E. N., Destici, E., Qiu, Y., Hu, R., Lee, A. Y., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0479-7 · Cited by 384
The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis
de la Torre-Ubieta, L., Stein, J. L., Won, H., Opland, C. K., Liang, D., Lu, D., & Geschwind, D. H. (2018) · Cell · doi:10.1016/j.cell.2017.12.014 · Cited by 353
Self-citationKarlsson Linnér, R., Mallard, T. T., Barr, P. B., Sanchez-Roige, S., Madole, J. W., Driver, M. N., Poore, H. E., de Vlaming, R., Grotzinger, A. D., Tielbeek, J. J., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00908-3 · Cited by 317
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 308
Self-citationSey, N. Y. A., Hu, B., Mah, W., Fauni, H., McAfee, J. C., Rajarajan, P., Brennand, K. J., Akbarian, S., & Won, H. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0603-0 · Cited by 297
Self-citationDe novo mutations in regulatory elements in neurodevelopmental disorders
Short, P. J., McRae, J. F., Gallone, G., Sifrim, A., Won, H., Geschwind, D. H., Wright, C. F., Firth, H. V., FitzPatrick, D. R., Barrett, J. C., et al. (2018) · Nature · doi:10.1038/nature25983 · Cited by 274
Self-citationKlein, H., Aubin, C., Gjoneska, E., Sullivan, S. E., Kaskow, B. J., Tang, A. Y., Smith, R. V., Xu, J., Pfenning, A. R., Bernstein, B., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0291-1 · Cited by 283
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Ursini, G., Punzi, G., Chen, Q., Marenco, S., Robinson, J. F., Porcelli, A., Hamilton, E. G., Mitjans, M., Maddalena, G., Begemann, M., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0021-y · Cited by 276
Single-cell epigenomics reveals mechanisms of human cortical development
Ziffra, R. S., Kim, C. N., Ross, J. M., Wilfert, A. B., Turner, T. N., Haeussler, M., Casella, A. M., Przytycki, P. F., Keough, K. C., Shin, D. S., et al. (2021) · Nature · doi:10.1038/s41586-021-03209-8 · Cited by 272
Mancuso, N., Shi, H., Goddard, P. C., Kichaev, G., Gusev, A., & Paşaniuc, B. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.01.031 · Cited by 266
Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms
Walker, R. L., Ramaswami, G., Hartl, C., Mancuso, N., Gandal, M. J., de la Torre-Ubieta, L., Paşaniuc, B., Stein, J. L., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.09.021 · Cited by 262
Self-citationDifferent mutational rates and mechanisms in human cells at pregastrulation and neurogenesis
Bae, T., Tomasini, L., Mariani, J., Zhou, B., Roychowdhury, T., Franjic, D., Pletikos, M., Pattni, R., Chen, B.-J., Venturini, E., et al. (2017) · Science · doi:10.1126/science.aan8690 · Cited by 267
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
Disease-Associated Short Tandem Repeats Co-localize with Chromatin Domain Boundaries
Sun, J. H., Zhou, L., Emerson, D. J., Phyo, S. A., Titus, K. R., Gong, W., Gilgenast, T. G., Beagan, J. A., Davidson, B. L., Tassone, F., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.005 · Cited by 249
“, 2015) and human fetal cortical plate tissue (Won et al., 2016).”
BackgroundResultHuman 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 244
Marzi, S. J., Leung, S. K., Ribarska, T., Hannon, E., Smith, A. R., Pishva, E., Poschmann, J., Moore, K., Troakes, C., Al-Sarraj, S., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0253-7 · Cited by 232
Aneichyk, T., Hendriks, W. T. J., Yadav, R., Shin, D. S., Gao, D., Vaine, C. A., Collins, R. L., Domingo, A., Currall, B., Stortchevoi, A., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.011 · Cited by 236
Schork, A. J., Won, H., Appadurai, V., Nudel, R., Gandal, M., Delaneau, O., Revsbech Christiansen, M., Hougaard, D. M., Bækved-Hansen, M., Bybjerg-Grauholm, J., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0320-0 · Cited by 223
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Rajarajan, P., Borrman, T., Liao, W., Schrode, N., Flaherty, E., Casiño, C., Powell, S., Yashaswini, C., LaMarca, E. A., Kassim, B., et al. (2018) · Science · doi:10.1126/science.aat4311 · Cited by 219
Self-citationCommon genetic variation influencing human white matter microstructure
Zhao, B., Li, T., Yang, Y., Wang, X., Luo, T., Shan, Y., Zhu, Z., Xiong, D., Hauberg, M. E., Bendl, J. M., et al. (2021) · Science · doi:10.1126/science.abf3736 · Cited by 222
Self-citationPhenotypic Landscape of Schizophrenia-Associated Genes Defines Candidates and Their Shared Functions
Thyme, S. B., Pieper, L. M., Li, E. H., Pandey, S., Wang, Y., Morris, N. S., Sha, C., Choi, J. W., Herrera, K. J., Soucy, E. R., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.048 · Cited by 220
Cell-type specialization is encoded by specific chromatin topologies
Winick‐Ng, W., Kukalev, A., Harabula, I., Zea-Redondo, L., Szabó, D., Meijer, M., Serebreni, L., Zhang, Y., Bianco, S., Chiariello, A. M., et al. (2021) · Nature · doi:10.1038/s41586-021-04081-2 · Cited by 214
Johnson, E. C., Border, R., Melroy-Greif, W. E., de Leeuw, C., Ehringer, M. A., & Keller, M. C. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.06.033 · Cited by 210
Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions
Girskis, K. M., Stergachis, A. B., DeGennaro, E. M., Doan, R. N., Qian, X., Johnson, M. B., Wang, P. P., Sejourne, G. M., Nagy, M. A., Pollina, E. A., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.08.005 · Cited by 193
Human Models Are Needed for Studying Human Neurodevelopmental Disorders
Zhao, X., & Bhattacharyya, A. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.10.009 · Cited by 192
Tan, L., Ma, W., Wu, H., Zheng, Y., Xing, D., Chen, R., Li, X., Daley, N., Deisseroth, K. A., & Xie, X. S. (2021) · Cell · doi:10.1016/j.cell.2020.12.032 · Cited by 193
Mapping the genetic landscape across 14 psychiatric disorders
Grotzinger, A. D., Werme, J., Peyrot, W. J., Frei, O., de Leeuw, C., Bicks, L. K., Guo, Q., Margolis, M. P., Coombes, B. J., Batzler, A. J., et al. (2025) · Nature · doi:10.1038/s41586-025-09820-3 · Cited by 195
Self-citationLu, L., Liu, X., Huang, W., Giusti‐Rodríguez, P., Cui, J., Zhang, S., Xu, W., Wen, Z., Ma, S., Rosen, J. D., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.06.007 · Cited by 175
Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia
Bryois, J., Garrett, M. E., Song, L., Safi, A., Giusti-Rodriguez, P., Johnson, G. D., Shieh, A. W., Buil, A., Fullard, J. F., Roussos, P., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05379-y · Cited by 167
Song, M., Yang, X., Ren, X., Maliskova, L., Li, B., Jones, I. R., Wang, C., Jacob, F., Wu, K., Traglia, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0472-1 · Cited by 167
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Jiang, Y., Loh, Y., Rajarajan, P., Hirayama, T., Liao, W., Kassim, B. S., Javidfar, B., Hartley, B., Kleofas, L., Park, R. B., et al. (2017) · Nature Genetics · doi:10.1038/ng.3906 · Cited by 128
Gazal, S., Loh, P.-R., Finucane, H. K., Ganna, A., Schoech, A., Sunyaev, S., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0231-8 · Cited by 154
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Waye, M. M. Y., & Cheng, H. Y. (2017) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12606 · Cited by 164
Detecting hierarchical genome folding with network modularity
Norton, H. K., Emerson, D. J., Huang, H., Kim, J., Titus, K. R., Gu, S., Bassett, D. S., & Phillips-Cremins, J. E. (2018) · Nature Methods · doi:10.1038/nmeth.4560 · Cited by 146
Gasperini, M., Findlay, G. M., McKenna, A., Milbank, J. H., Lee, C., Zhang, M. D., Cusanovich, D. A., & Shendure, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.010 · Cited by 143
Self-citationBeagan, J. A., Pastuzyn, E. D., Fernandez, L. R., Guo, M. H., Feng, K., Titus, K. R., Chandrashekar, H., Shepherd, J. D., & Phillips-Cremins, J. E. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0634-6 · Cited by 143
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 145
Fang, J., Zhang, P., Wang, Q., Chiang, C.-W., Zhou, Y., Hou, Y., Xu, J., Chen, R., Zhang, B., Lewis, S. J., et al. (2022) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00951-z · Cited by 140
Won, H., Huang, J. I., Opland, C. K., Hartl, C., & Geschwind, D. H. (2019) · Nature Communications · doi:10.1038/s41467-019-10248-3 · Cited by 140
Self-citation3D Genome of macaque fetal brain reveals evolutionary innovations during primate corticogenesis
Luo, X., Liu, Y., Dang, D., Hu, T., Hou, Y., Meng, X., Zhang, F., Li, T., Wang, C., Li, M., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.001 · Cited by 140
Greenwald, W. W. Y., Li, H., Benaglio, P., Jakubosky, D. A., Matsui, H., Schmitt, A. D., Selvaraj, S., D’Antonio, M., D’Antonio‐Chronowska, A., Smith, E. N., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08940-5 · Cited by 144
Genome-wide association study implicates CHRNA2 in cannabis use disorder
Demontis, D., Rajagopal, V. M., Thorgeirsson, T. E., Als, T. D., Grove, J., Leppälä, K., Gudbjartsson, D. F., Pallesen, J., Hjorthøj, C. R., Reginsson, G. W., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0416-1 · Cited by 137
DNA Methylation and Susceptibility to Autism Spectrum Disorder
Tremblay, M. W., & Jiang, Y. (2019) · Annual Review of Medicine · doi:10.1146/annurev-med-120417-091431 · Cited by 139
Cohesin-dependence of neuronal gene expression relates to chromatin loop length
Calderon, L., Weiss, F. D., Beagan, J. A., Oliveira, M. S., Georgieva, R., Wang, Y.-F., Carroll, T. S., Dharmalingam, G., Gong, W., Tossell, K., et al. (2022) · eLife · doi:10.7554/elife.76539 · Cited by 132
Dileep, V., Boix, C. A., Mathys, H., Marco, A., Welch, G. M., Meharena, H. S., Loon, A., Jeloka, R., Peng, Z., Bennett, D. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.038 · Cited by 130
Wang, Q., Chen, R., Cheng, F., Wei, Q., Ji, Y., Hai, Y., Zhong, X. Y., Tao, R., Wen, Z., Sutcliffe, J. S., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0382-7 · Cited by 134
The three-dimensional genome: regulating gene expression during pluripotency and development
Andrey, G., & Mundlos, S. (2017) · Development · doi:10.1242/dev.148304 · Cited by 134
Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants
Zhang, S., Zhang, H., Zhou, Y., Qiao, M., Zhao, S., Kozlova, A., Shi, J., Sanders, A. R., Wang, G., Luo, K., et al. (2020) · Science · doi:10.1126/science.aay3983 · Cited by 127
Whole genome sequencing in psychiatric disorders: the WGSPD consortium
(WGSPD), W. G. S. F. P. D., Sanders, S., Neale, B. M., Huang, H., Werling, D. M., An, J., Dong, S., Abecasis, G. R., Arguello, P. A., Blangero, J., et al. (2017) · Nature Neuroscience · doi:10.1038/s41593-017-0017-9 · Cited by 128
Self-citationRegulatory functions of the Mediator kinases CDK8 and CDK19
Fant, C. B., & Taatjes, D. J. (2018) · Transcription · doi:10.1080/21541264.2018.1556915 · Cited by 131
Functional regulatory variants implicate distinct transcriptional networks in dementia
Cooper, Y. A., Teyssier, N., Dräger, N. M., Guo, Q., Davis, J. E., Sattler, S. M., Yang, Z., Patel, A. M., Wu, S. J., Kosuri, S., et al. (2022) · Science · doi:10.1126/science.abi8654 · Cited by 121
Self-citationClinical application of next-generation sequencing to the practice of neurology
Rexach, J. E., Lee, H., Martínez-Agosto, J. A., Nemeth, A. H., & Fogel, B. L. (2019) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30033-x · Cited by 117
Three-dimensional genome rewiring in loci with human accelerated regions
Keough, K. C., Whalen, S., Inoue, F., Przytycki, P. F., Fair, T., Deng, C., Steyert, M., Ryu, H., Lindblad-Toh, K., Karlsson, E., et al. (2023) · Science · doi:10.1126/science.abm1696 · Cited by 113
Chen, J., Chen, Z., Won, H., Huang, A., Lowe, J. K., Wojta, K. J., Yokoyama, J. S., Bensimon, G., Leigh, P. N., Payan, C., et al. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0270-8 · Cited by 117
Self-citationHou, Q.-L., Wang, Y., Li, Y., Chen, D., Yang, F., & Wang, S. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00182 · Cited by 115
Semick, S. A., Bharadwaj, R. A., Collado‐Torres, L., Tao, R., Shin, J. H., Deep‐Soboslay, A., Weiss, J. R., Weinberger, D. R., Hyde, T. M., Kleinman, J. E., et al. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-01966-5 · Cited by 121
Greenwald, W. W. Y., Chiou, J., Yan, J., Qiu, Y., Dai, N., Wang, A., Nariai, N., Aylward, A., Han, J. Y., Kadakia, N., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09975-4 · Cited by 114
Evolution of DNA methylation in the human brain
Jeong, H., Mendizabal, I., Berto, S., Chatterjee, P., Layman, T. S., Usui, N., Toriumi, K., Douglas, C., Singh, D., Huh, I., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21917-7 · Cited by 114
Massively parallel discovery of human-specific substitutions that alter enhancer activity
Uebbing, S., Gockley, J., Reilly, S. K., Kocher, A. A., Geller, E. T., Gandotra, N., Scharfe, C., Cotney, J. L., & Noonan, J. P. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2007049118 · Cited by 113
Brain-derived neurotrophic factor and schizophrenia
Di Carlo, P., Punzi, G., & Ursini, G. (2019) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000237 · Cited by 110
Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci
Cannon, M. E., & Mohlke, K. L. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.10.001 · Cited by 111
Song, J. H. T., Lowe, C. B., & Kingsley, D. M. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.07.011 · Cited by 112
Machine learning dissection of human accelerated regions in primate neurodevelopment
Whalen, S., Inoue, F., Ryu, H., Fair, T., Markenscoff-Papadimitriou, E., Keough, K. C., Kircher, M., Martin, B., Alvarado, B., Elor, O., et al. (2023) · Neuron · doi:10.1016/j.neuron.2022.12.026 · Cited by 114
A Dementia-Associated Risk Variant near TMEM106B Alters Chromatin Architecture and Gene Expression
Gallagher, M. D., Posavi, M., Huang, P., Unger, T. L., Berlyand, Y., Gruenewald, A. L., Chesi, A., Manduchi, E., Wells, A. D., Grant, S. F. A., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.09.004 · Cited by 112
Comprehensive integrative analyses identify GLT8D1 and CSNK2B as schizophrenia risk genes
Yang, C., Li, X., Wu, Y., Shen, Q., Zeng, Y., Xiong, Q., Wei, M., Chen, C., Liu, J., Huo, Y., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03247-3 · Cited by 106
The genetics of neuropsychiatric disorders
Bray, N. J., & O’Donovan, M. C. (2018) · Brain and Neuroscience Advances · doi:10.1177/2398212818799271 · Cited by 113
Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders
Hu, B., Won, H., Mah, W., Park, R. B., Kassim, B., Spiess, K., Kozlenkov, A., Crowley, C. A., Pochareddy, S., The PsychENCODE Consortium, et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24243-0 · Cited by 103
Self-citationNeurobiological functions of transcriptional enhancers
Nord, A. S., & West, A. E. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0538-5 · Cited by 106
3C and 3C-based techniques: the powerful tools for spatial genome organization deciphering
Han, J., Zhang, Z., & Wang, K. (2018) · Molecular Cytogenetics · doi:10.1186/s13039-018-0368-2 · Cited by 104
Epigenetics and epitranscriptomics in temporal patterning of cortical neural progenitor competence
Yoon, K., Vissers, C. B., Ming, G., & Song, H. (2018) · The Journal of Cell Biology · doi:10.1083/jcb.201802117 · Cited by 96
Matoba, N., Liang, D., Sun, H., Aygün, N., McAfee, J. C., Davis, J. E., Raffield, L. M., Qian, H., Piven, J., Li, Y., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00953-9 · Cited by 97
Self-citationSocial and non-social autism symptoms and trait domains are genetically dissociable
Warrier, V., Toro, R., Won, H., Leblond, C. S., Cliquet, F., Delorme, R., De Witte, W., Bralten, J., Chakrabarti, B., Børglum, A. D., et al. (2019) · Communications Biology · doi:10.1038/s42003-019-0558-4 · Cited by 94
Self-citationFOXG1 Orchestrates Neocortical Organization and Cortico-Cortical Connections
Cargnin, F., Kwon, J.-S., Katzman, S. J., Chen, B., Lee, J. W., & Lee, S. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.016 · Cited by 92
OnTAD: hierarchical domain structure reveals the divergence of activity among TADs and boundaries
An, L., Yang, T., Yang, J., Nuebler, J., Xiang, G., Hardison, R. C., Li, Q., & Zhang, Y. (2019) · Genome biology · doi:10.1186/s13059-019-1893-y · Cited by 91
Evolutionary conservation and conversion of Foxg1 function in brain development
Kumamoto, T., & Hanashima, C. (2017) · Development Growth & Differentiation · doi:10.1111/dgd.12367 · Cited by 92
Common risk variants identified in autism spectrum disorder
Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., et al. (2017) · doi:10.1101/224774 · Cited by 89
Self-citationFadason, T., Ekblad, C., Ingram, J. R., Schierding, W. S., & O'Sullivan, J. M. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00150 · Cited by 90
Nucleome Dynamics during Retinal Development
Norrie, J. L., Lupo, M. S., Xu, B., Aldiri, I., Valentine, M. B., Putnam, D. K., Griffiths, L. M., Zhang, J., Johnson, D. A., Easton, J. B., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.002 · Cited by 87
A Chromatin Accessibility Atlas of the Developing Human Telencephalon
Markenscoff-Papadimitriou, E., Whalen, S., Przytycki, P. F., Thomas, R., Binyameen, F., Nowakowski, T. J., Kriegstein, A. R., Sanders, S., State, M. W., Pollard, K. S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.002 · Cited by 91
Pai, S., Li, P., Killinger, B. A., Marshall, L. L., Jia, P., Liao, J., Petronis, A., Szabó, P. E., & Labrie, V. (2019) · Nature Communications · doi:10.1038/s41467-019-09786-7 · Cited by 86
Metadata
- Authors
- Won, H., de la Torre-Ubieta, L., Stein, J. L., Parikshak, N. N., Huang, J., Opland, C. K., Gandal, M. J., Sutton, G. J., Hormozdiari, F., Lu, D., Lee, C., Eskin, E., Voineagu, I., Ernst, J., & Geschwind, D. H.
- Affiliations
- University of California, Los Angeles (US)
- UNSW Sydney (AU)
- Corresponding author
- Geschwind, Daniel H.
- ORCID
- Venue
- Nature
- Published
- 2016-10
- Volume
- 538
- Issue
- 7626
- Pages
- 523-527
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5358922
- OpenAlex
- W2534005127
- Cited by
- 584
- References
- 46
- Citations by year
- 2026: 24 · 2025: 45 · 2024: 51 · 2023: 45 · 2022: 62 · 2021: 79 · 2020: 78 · 2019: 76 · 2018: 72 · 2017: 46 · 2016: 3
- FWCI
- 34.12
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UNC Libraries
- Funders
- National Science Foundation (1254200, CAREER)
- National Research Foundation
- National Research Foundation of Korea
- National Institutes of Health (TG2-01169, 5r01mh094714-04, AI028697)
- Center for AIDS Research, University of Washington (5P30AI028697, AI028697)
- National Health and Medical Research Council (1062510)
- National Institute of Mental Health (K99MH102357, U01MH103339, R01-MH094714, F30MH099886, R01MH110927, R01MH100027, R01MH101782, U01MH105991, R01MH060233, R00MH102357, T32MH073526, R37MH060233)
- National Institute of Allergy and Infectious Diseases (P30AI028697)
- National Institute of Environmental Health Sciences (R01ES022282, R01ES024995)
- Center for AIDS Research, University of California Los Angeles (AI028697)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- chromosome conformation, 3D genome organization, human brain development, cortical development, enhancer-promoter interactions, non-coding variants, schizophrenia risk genes, autism spectrum disorder, neurodevelopmental disorders, FOXG1, purifying selection, human cognitive evolution, neural progenitor cells, Hi-C, gene regulatory networks
- MeSH terms
- Brain, Chromatin, Chromosomes, Human, Cognition, Enhancer Elements, Genetic, Humans, Nerve Tissue Proteins, Nucleic Acid Conformation, Organ Specificity, Promoter Regions, Genetic, Schizophrenia, Reproducibility of Results, Gene Expression Regulation, Developmental, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Epigenesis, Genetic, Forkhead Transcription Factors, Genome-Wide Association Study, Neurogenesis, Neural Stem Cells
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