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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The HAR202-Npas3 promoter interaction was not observed in Hi-C experiments from adult human dorsolateral prefrontal cortex or developing human cerebral cortex at mid-gestation.
“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 <i>NPAS3</i> Expression in the Developing Forebrain Displaying Differential Enhancer Activity Between Modern and Archaic Human Sequences (2024) · cites this paper as Won et al. 2016
MAGMA assigns SNPs to nearest genes, which has the pitfall that non-coding SNPs can regulate distal genes via long-range (>10 kb) regulatory interactions.
“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]
3D chromatin loops are highly tissue-specific.
“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]
SCZ and BD-associated genes were enriched for acetylcholinergic signaling.
“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]
Hi-C and single-cell sequencing had not been fully integrated at scale with brain genomics data.
“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]
Only about 31% of interactions in adult Hi-C data were detected in the fetal dataset.
“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]
Regulatory relationships often do not follow linear genome organization.
“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]
Brain Hi-C data detected a direct interaction between the cross-disorder association region and NOX4 in adult and fetal brain (p = 3.2 × 10^-16 and 9.3 × 10^-6).
“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
Recent studies show that genes located far outside a locus are often implicated.
“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
Assigning well-annotated genomic regions to specific genes is not as simple as choosing the closest gene or genes containing variation highly correlated with associated SNPs.
“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
Around half of non-coding regions have regulatory functions 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.
“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
Disease-associated SNPs in non-coding areas of the genome influence genes associated with diseases including Alzheimer's Disease (AD).
“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]
There are 187,674 promoter-based interactions in NeuN+ cells and 167,551 in NeuN− cells.
“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]
24,544 unique loops were identified from published Hi-C data created in human brain tissue derived from the germinal zone and cortical plate.
“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]
Enhancers often regulate distal genes.
“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]
Merging cortical plate and germinal zone loops created a master set of 24,544 loops spanning the two brain tissues.
“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]
A similar increase in insulation around SOX11 was observed in human cortical development.
“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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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 · see citing works
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 · see citing works
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 · see citing works
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
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 · 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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Partitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604 · see citing works
An atlas of active enhancers across human cell types and tissues
The FANTOM Consortium, Andersson, R., Gebhard, C., Miguel-Escalada, I., Hoof, I., Bornholdt, J., Boyd, M., Chen, Y., Zhao, X., Schmidl, C., et al. (2014) · Nature · doi:10.1038/nature12787 · Cited by 2,550 · see citing works
Widespread transcription at neuronal activity-regulated enhancers
Kim, T.-K., Hemberg, M., Gray, J. M., Costa, A. M., Bear, D. M., Wu, J., Harmin, D. A., Laptewicz, M., Barbara-Haley, K., Kuersten, S., et al. (2010) · Nature · doi:10.1038/nature09033 · Cited by 2,450 · see citing works
A promoter-level mammalian expression atlas
The FANTOM Consortium and the RIKEN PMI and CLST (DGT) (2014) · Nature · doi:10.1038/nature13182 · Cited by 1,982 · see citing works
Chromatin architecture reorganization during stem cell differentiation
Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., Ye, Z., Kim, A., Rajagopal, N., Xie, W., et al. (2015) · Nature · doi:10.1038/nature14222 · Cited by 1,646 · see citing works
De novo mutations in schizophrenia implicate synaptic networks
Fromer, M., Pocklington, A. J., Kavanagh, D. H., Williams, H. J., Dwyer, S., Gormley, P., Georgieva, L., Rees, E., Palta, P., Ruderfer, D. M., et al. (2014) · Nature · doi:10.1038/nature12929 · Cited by 1,617 · see citing works
The long-range interaction landscape of gene promoters
Sanyal, A., Lajoie, B. R., Jain, G., & Dekker, J. (2012) · Nature · doi:10.1038/nature11279 · Cited by 1,489 · see citing works
Iterative correction of Hi-C data reveals hallmarks of chromosome organization
Imakaev, M., Fudenberg, G., McCord, R. P., Naumova, N., Goloborodko, A., Lajoie, B. R., Dekker, J., & Mirny, L. A. (2012) · Nature Methods · doi:10.1038/nmeth.2148 · Cited by 1,423 · see citing works
SOX2 Functions to Maintain Neural Progenitor Identity
Graham, V., Khudyakov, J. I., Ellis, P., & Pevny, L. (2003) · Neuron · doi:10.1016/s0896-6273(03)00497-5 · Cited by 1,344 · see citing works
Transcriptional landscape of the prenatal human brain
Miller, J. A., Ding, S.-L., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Ebbert, A., Riley, Z. L., Royall, J. J., Aiona, K., et al. (2014) · Nature · doi:10.1038/nature13185 · Cited by 1,325 · see citing works
Self-citationA high-resolution map of the three-dimensional chromatin interactome in human cells
Jin, F., Li, Y., Dixon, J. R., Selvaraj, S., Ye, Z., Lee, A. Y., Yen, C.-A., Schmitt, A. D., Espinoza, C. A., & Ren, B. (2013) · Nature · doi:10.1038/nature12644 · Cited by 1,208 · see citing works
Gene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091 · see citing works
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039 · see citing works
Self-citationMapping long-range promoter contacts in human cells with high-resolution capture Hi-C
Mifsud, B., Tavares-Cadete, F., Young, A. N., Sugar, R., Schoenfelder, S., Ferreira, L., Wingett, S. W., Andrews, S., Grey, W., Ewels, P. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3286 · Cited by 990 · see citing works
The evolution of lncRNA repertoires and expression patterns in tetrapods
Necsulea, A., Soumillon, M., Warnefors, M., Liechti, A., Daish, T., Zeller, U., Baker, J. C., Grützner, F., & Kaessmann, H. (2014) · Nature · doi:10.1038/nature12943 · Cited by 984 · see citing works
Mapping complex disease traits with global gene expression
Cookson, W., Liang, L., Abecasis, G., Moffatt, M., & Lathrop, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2537 · Cited by 849 · see citing works
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium (2015) · Nature Neuroscience · doi:10.1038/nn.3922 · Cited by 755 · see citing works
Self-citationGenetic variability in the regulation of gene expression in ten regions of the human brain
UK Brain Expression Consortium, Ramasamy, A., North American Brain Expression Consortium, Trabzuni, D., Guelfi, S., Varghese, V., Smith, C., Walker, R., De, T., Coin, L., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3801 · Cited by 644 · see citing works
Human-specific gene <i>ARHGAP11B</i> promotes basal progenitor amplification and neocortex expansion
Florio, M., Albert, M., Taverna, E., Namba, T., Brandl, H., Lewitus, E., Haffner, C., Sykes, A., Wong, F. K., Peters, J., et al. (2015) · Science · doi:10.1126/science.aaa1975 · Cited by 632 · see citing works
Removing technical variability in RNA-seq data using conditional quantile normalization
Hansen, K. D., Irizarry, R. A., & WU, Z. (2012) · Biostatistics · doi:10.1093/biostatistics/kxr054 · Cited by 607 · see citing works
ASPM is a major determinant of cerebral cortical size
Bond, J., Roberts, E., Mochida, G. H., Hampshire, D. J., Scott, S., Askham, J. M., Springell, K., Mahadevan, M., Crow, Y. J., Markham, A. F., et al. (2002) · Nature Genetics · doi:10.1038/ng995 · Cited by 581 · see citing works
Gulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Braff, D., Cadenhead, K. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.049 · Cited by 536 · see citing works
Cortical Evolution: Judge the Brain by Its Cover
Geschwind, D. H., & Rakic, P. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.045 · Cited by 519 · see citing works
Self-citationDivergence of human and mouse brain transcriptome highlights Alzheimer disease pathways
Miller, J. A., Horvath, S., & Geschwind, D. H. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914257107 · Cited by 480 · see citing works
Self-citationIdentifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, F., Kostem, E., Kang, E. Y., Pasaniuc, B., & Eskin, E. (2014) · Genetics · doi:10.1534/genetics.114.167908 · Cited by 465 · see citing works
Self-citationLarge-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues
Ernst, J., & Kellis, M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3157 · Cited by 352 · see citing works
Self-citationMcCarthy, S. E., Gillis, J. A., Kramer, M., Lihm, J., Yoon, S. C., Berstein, Y., Mistry, M., Pavlidis, P., Solomon, R., Ghiban, E., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.29 · Cited by 332 · see citing works
Evolutionary changes in promoter and enhancer activity during human corticogenesis
Reilly, S. K., Yin, J., Ayoub, A. E., Emera, D., Leng, J., Cotney, J., Sarro, R., Rakic, P., & Noonan, J. P. (2015) · Science · doi:10.1126/science.1260943 · Cited by 297 · see citing works
A Role for Noncoding Variation in Schizophrenia
Roussos, P., Mitchell, A. C., Voloudakis, G., Fullard, J. F., Pothula, V. M., Tsang, J., Stahl, E. A., Georgakopoulos, A., Ruderfer, D. M., Charney, A., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.10.015 · Cited by 251 · see citing works
Kortüm, F., Das, S., Flindt, M., Morris-Rosendahl, D. J., Stefanova, I., Goldstein, A. C., Horn, D., Klopocki, E., Kluger, G. J., Martin, P., et al. (2011) · Journal of Medical Genetics · doi:10.1136/jmg.2010.087528 · Cited by 239 · see citing works
Jones, C. K., Byun, N. E., & Bubser, M. (2011) · Neuropsychopharmacology · doi:10.1038/npp.2011.199 · Cited by 228 · see citing works
van de Leemput, J., Boles, N. C., Kiehl, T. R., Corneo, B., Lederman, P. L., Menon, V., Lee, C., Martinez, R. A., Levi, B. P., Thompson, C. L., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.013 · Cited by 207 · see citing works
Self-citationA Quantitative Framework to Evaluate Modeling of Cortical Development by Neural Stem Cells
Stein, J. L., de la Torre-Ubieta, L., Tian, Y., Parikshak, N. N., Hernández, I. A., Marchetto, M. C., Baker, D. K., Lu, D., Hinman, C. R., Lowe, J. K., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.035 · Cited by 201 · see citing works
Self-citationOldham, M. C., Langfelder, P., & Horvath, S. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-63 · Cited by 154 · see citing works
Coexpression networks identify brain region–specific enhancer RNAs in the human brain
Yao, P., Lin, P., Gokoolparsadh, A., Assareh, A. A., Thang, M. W. C., & Voineagu, I. (2015) · Nature Neuroscience · doi:10.1038/nn.4063 · Cited by 91 · see citing works
Self-citationHigher-order chromatin domains link eQTLs with the expression of far-away genes
Duggal, G., Wang, H., & Kingsford, C. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt857 · Cited by 53 · see citing works
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Functional mapping and annotation of genetic associations with FUMA
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083 · see citing works
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 · see citing works
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
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
“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 · 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
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 · see citing works
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 · see citing works
Integrative functional genomic analysis of human brain development and neuropsychiatric risks
Li, M., Santpere, G., Imamura Kawasawa, Y., Evgrafov, O. V., Gulden, F. O., Pochareddy, S., Sunkin, S. M., Li, Z., Shin, Y., Zhu, Y., et al. (2018) · Science · doi:10.1126/science.aat7615 · Cited by 810 · see citing works
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 · see citing works
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 552 · see citing works
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 493 · see citing works
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 · see citing works
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 · see citing works
“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 · see citing works
New insights into the development of the human cerebral cortex
Molnár, Z., Clowry, G. J., Šestan, N., Alzu’bi, A., Bakken, T. E., Hevner, R. F., Hüppi, P. S., Kostović, I., RAKIC, P. T., Anton, E. S., et al. (2019) · Journal of Anatomy · doi:10.1111/joa.13055 · Cited by 401 · see citing works
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 366 · see citing works
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 367 · see citing works
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 · see citing works
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 · see citing works
Transcriptome and epigenome landscape of human cortical development modeled in organoids
Amiri, A., Coppola, G., Scuderi, S., Wu, F., Roychowdhury, T., Liu, F., Pochareddy, S., Shin, Y., Safi, A., Song, L., et al. (2018) · Science · doi:10.1126/science.aat6720 · Cited by 302 · see citing works
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 · see citing works
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 · see citing works
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 267 · see citing works
Convergence of placenta biology and genetic risk for schizophrenia
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 266 · see citing works
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 266 · see citing works
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 265 · see citing works
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 259 · see citing works
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 259 · see citing works
Chromatin accessibility dynamics in a model of human forebrain development
Trevino, A. E., Sinnott-Armstrong, N., Andersen, J., Yoon, S.-J., Huber, N., Pritchard, J. K., Chang, H. Y., Greenleaf, W. J., & Pașca, S. P. (2020) · Science · doi:10.1126/science.aay1645 · Cited by 251 · see citing works
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 · see citing works
“, 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 233 · see citing works
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 · see citing works
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 226 · see citing works
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 · see citing works
Self-citationNeuron-specific signatures in the chromosomal connectome associated with schizophrenia risk
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 · see citing works
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 217 · see citing works
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. (2018) · Cell · doi:10.1016/j.cell.2019.01.048 · Cited by 205 · see citing works
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 205 · see citing works
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 201 · see citing works
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 · see citing works
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 · see citing works
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 190 · see citing works
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 176 · see citing works
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 170 · see citing works
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 · see citing works
Song, M., Yang, X., Ren, X., Maliskova, L., Li, B., Jones, I. R., Wang, C., Jacob, F., Wu, K. K.-Y., Traglia, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0472-1 · Cited by 167 · see citing works
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 · see citing works
The methyltransferase SETDB1 regulates a large neuron-specific topological chromatin domain
Jiang, Y., Loh, Y. E., Rajarajan, P., Hirayama, T., Liao, W., Kassim, B. S., Javidfar, B., Hartley, B. J., Kleofas, L., Park, R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3906 · Cited by 162 · see citing works
Genetics and epigenetics of autism: A Review
Waye, M. M. Y., & Cheng, H. Y. (2017) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12606 · Cited by 153 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Cell-type-specific 3D epigenomes in the developing human cortex
Song, M., Pebworth, M.-P., Yang, X., Abnousi, A., Fan, C., Wen, J., Rosen, J. D., Choudhary, M. N. K., Cui, X., Jones, I. R., et al. (2020) · Nature · doi:10.1038/s41586-020-2825-4 · Cited by 143 · see citing works
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 · see citing works
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 139 · see citing works
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 137 · see citing works
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 134 · see citing works
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 133 · see citing works
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 132 · see citing works
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 · see citing works
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 · see citing works
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 130 · see citing works
The three-dimensional genome: regulating gene expression during pluripotency and development
Andrey, G., & Mundlos, S. (2017) · Development · doi:10.1242/dev.148304 · Cited by 129 · see citing works
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 · see citing works
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 125 · see citing works
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 122 · see citing works
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 120 · see citing works
Self-citationClinical application of next-generation sequencing to the practice of neurology
Rexach, J. E., Lee, H.-N., Martinez-Agosto, J., Nemeth, A., & Fogel, B. (2019) · Lancet Neurology · doi:10.1016/s1474-4422(19)30033-x · Cited by 101 · see citing works
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 · see citing works
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 113 · see citing works
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 113 · see citing works
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 113 · see citing works
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 113 · see citing works
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 112 · see citing works
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 111 · see citing works
Brain-derived neurotrophic factor and schizophrenia
Di Carlo, P., Punzi, G., & Ursini, G. (2019) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000237 · Cited by 110 · see citing works
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 109 · see citing works
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 109 · see citing works
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 109 · see citing works
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 109 · see citing works
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 105 · see citing works
The genetics of neuropsychiatric disorders
Bray, N. J., & O’Donovan, M. C. (2018) · Brain and Neuroscience Advances · doi:10.1177/2398212818799271 · Cited by 105 · see citing works
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 · see citing works
Self-citationNeurobiological functions of transcriptional enhancers
Nord, A. S., & West, A. E. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0538-5 · Cited by 100 · see citing works
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 97 · see citing works
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 · see citing works
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 95 · see citing works
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 · see citing works
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 91 · see citing works
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 · see citing works
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 90 · see citing works
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 · see citing works
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 89 · see citing works
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 · see citing works
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 87 · see citing works
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 · see citing works
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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