Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants
Open accessAbstract
Effects of allele-specific open chromatin: Genetic variants in noncoding regions of the genome may underlie the development of disease. However, we are just beginning to tease apart the function of such variants associated with neuropsychiatric disease. Using five types of neural progenitor cells derived from 20 human induced pluripotent stem cell lines, Zhang et al. looked at allele-specific open chromatin (ASoC) variants. Many ASoC variants overlapped with genomic elements, such as transcription factor binding sites, and loci identified in genome-wide association studies for neurological traits. From the experimental and computational analyses, they identified single-nucleotide polymorphisms and illuminate how one schizophrenia-associated variant affects neurodevelopment. Science , this issue p. 561
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eSNP-karyotyping was performed for all cell lines used to eliminate potential chromosomal abnormalities.
“eSNP-karyotyping was performed for all cell lines used to eliminate potential chromosomal abnormalities, as previously described20,21.”
From PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia (2025) · cites this paper as [20]
The paper’s passage describing the 20 iPSC lines and their assays (section labeled Abstract, page unavailable) does not say they underwent eSNP-karyotyping. Searches for eSNP-karyotyping and chromosomal-abnormality screening found only a reference to a separate chromosomal-aberration assay, not a statement that this procedure was performed on all cell lines. (LLM, conf=0.72)
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The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · 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
Genome engineering using the CRISPR-Cas9 system
Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A., & Zhang, F. (2013) · Nature Protocols · doi:10.1038/nprot.2013.143 · Cited by 11,133 · see citing works
Near-optimal probabilistic RNA-seq quantification
Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016) · Nature Biotechnology · doi:10.1038/nbt.3519 · Cited by 9,723 · see citing works
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · 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
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
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
Davey Smith, G., & Hemani, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu328 · Cited by 4,677 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · 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
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
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
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
Self-citationLiao, Y., Smyth, G. K., & Shi, W. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz114 · Cited by 2,965 · 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
Liu, J. Z., van Sommeren, S., Huang, H., Ng, S. C., Alberts, R., Takahashi, A., Ripke, S., Lee, J. C., Jostins, L., Shah, T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3359 · Cited by 2,603 · 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
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
Quantifying similarity between motifs
Gupta, S., Stamatoyannopoulos, J. A., Bailey, T. L., & Noble, W. S. (2007) · Genome Biology · doi:10.1186/gb-2007-8-2-r24 · Cited by 2,058 · see citing works
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912 · see citing works
The NIH Roadmap Epigenomics Mapping Consortium
Bernstein, B. E., Stamatoyannopoulos, J. A., Costello, J. F., Ren, B., Milosavljevic, A., Meissner, A., Kellis, M., Marra, M. A., Beaudet, A. L., Ecker, J. R., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1045 · Cited by 1,892 · see citing works
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
Rapid single-step induction of functional neurons from human pluripotent stem cells
Zhang, Y., Pak, C., Han, Y., Ahlenius, H., Zhang, Z., Chanda, S., Marro, S., Patzke, C., Acuna, C., Covy, J., et al. (2013) · Neuron · doi:10.1016/j.neuron.2013.05.029 · Cited by 1,644 · see citing works
Genome-wide association study identifies 30 loci associated with bipolar disorder
eQTLGen Consortium, Stahl, E. A., BIOS Consortium, the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., Trubetskoy, V., Mattheisen, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0397-8 · Cited by 1,519 · 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-citationGenome-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-citationCommon variants on chromosome 6p22.1 are associated with schizophrenia
Shi, J., Levinson, D. F., Duan, J., Sanders, A. R., Zheng, Y., Pe’er, I., Dudbridge, F., Holmans, P., Whittemore, A. S., Mowry, B. J., et al. (2009) · Nature · doi:10.1038/nature08192 · Cited by 1,154 · see citing works
Self-citationA simple new approach to variable selection in regression, with application to genetic fine mapping
Wang, G., Sarkar, A., Carbonetto, P., & Stephens, M. (2020) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12388 · Cited by 1,121 · see citing works
Self-citationPooled CRISPR screening with single-cell transcriptome readout.
Datlinger, P., Rendeiro, A. F., Schmidl, C., Krausgruber, T., Traxler, P., Klughammer, J., Schuster, L. C., Kuchler, A., Alpar, D., & Bock, C. (2017) · Nature Methods · doi:10.1038/nmeth.4177 · Cited by 1,096 · 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
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
Bentham, J., Morris, D. L., Graham, D. S. C., Pinder, C. L., Tombleson, P., Behrens, T. W., Martin, J. J., Fairfax, B. P., Knight, J. C., Chen, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3434 · Cited by 990 · see citing works
The UCSC genome browser and associated tools
Kuhn, R. M., Haussler, D., & Kent, W. J. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs038 · Cited by 883 · see citing works
Nagel, M., Jansen, P. R., Stringer, S., Watanabe, K., de Leeuw, C., Bryois, J., Savage, J. E., Hammerschlag, A. R., Skene, N., Muñoz‐Manchado, A. B., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0151-7 · Cited by 806 · see citing works
Bias, robustness and scalability in single-cell differential expression analysis
Soneson, C., & Robinson, M. D. (2018) · Nature Methods · doi:10.1038/nmeth.4612 · Cited by 770 · see citing works
Mapping cis- and trans-regulatory effects across multiple tissues in twins
The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Grundberg, E., Small, K. S., Hedman, Å. K., Nica, A. C., Buil, A., Keildson, S., Bell, J. T., Yang, T.-P., Meduri, E., et al. (2012) · Nature Genetics · doi:10.1038/ng.2394 · Cited by 729 · 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
Chromosome conformation elucidates regulatory relationships in developing human brain
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., et al. (2016) · Nature · doi:10.1038/nature19847 · Cited by 584 · see citing works
WASP: allele-specific software for robust molecular quantitative trait locus discovery
van de Geijn, B., McVicker, G., Gilad, Y., & Pritchard, J. K. (2015) · Nature Methods · doi:10.1038/nmeth.3582 · Cited by 575 · see citing works
Synaptic dysregulation in a human iPS cell model of mental disorders
Wen, Z., Nguyen, H. N., Guo, Z., Lalli, M. A., Wang, X., Su, Y., Kim, N.-S., Yoon, K.-J., Shin, J., Zhang, C., et al. (2014) · Nature · doi:10.1038/nature13716 · Cited by 549 · see citing works
Ring, K. L., Tong, L. M., Balestra, M. E., Javier, R., Andrews-Zwilling, Y. S., Li, G., Walker, D., Zhang, W. R., Kreitzer, A. C., & Huang, Y. (2012) · Cell stem cell · doi:10.1016/j.stem.2012.05.018 · Cited by 540 · see citing works
Démenais, F., Margaritte‐Jeannin, P., Barnes, K. C., Cookson, W., Altmüller, J., Ang, W., Barr, R. G., Beaty, T. H., Becker, A. B., Beilby, J. P., et al. (2017) · Nature Genetics · doi:10.1038/s41588-017-0014-7 · Cited by 535 · see citing works
Approximately independent linkage disequilibrium blocks in human populations
Berisa, T., & Pickrell, J. K. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv546 · Cited by 534 · see citing works
Jun, G., Flickinger, M., Hetrick, K. N., Romm, J. M., Doheny, K. F., Abecasis, G. R., Boehnke, M., & Kang, H. M. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.09.004 · Cited by 484 · see citing works
Tewhey, R., Kotliar, D., Park, D. S., Liu, B., Winnicki, S., Reilly, S. K., Andersen, K. G., Mikkelsen, T. S., Lander, E. S., Schaffner, S. F., et al. (2016) · Cell · doi:10.1016/j.cell.2016.04.027 · Cited by 480 · see citing works
An enhanced CRISPR repressor for targeted mammalian gene regulation
Yeo, N. C., Chavez, A., Lance‐Byrne, A., Chan, Y., Menn, D. J., Milanova, D., Kuo, C., Guo, X., Sharma, S., Tung, A., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0048-5 · Cited by 472 · see citing works
An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome
Ng, B., White, C. C., Klein, H.-U., Sieberts, S. K., McCabe, C., Patrick, E., Xu, J., Yu, L., Gaiteri, C., Bennett, D. A., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4632 · Cited by 452 · see citing works
A bioinformatic assay for pluripotency in human cells
Müller, F.-J., Schuldt, B. M., Williams, R. M., Mason, D., Altun, G., Papapetrou, E. P., Danner, S., Goldmann, J. E., Herbst, A., Schmidt, N. O., et al. (2011) · Nature Methods · doi:10.1038/nmeth.1580 · Cited by 446 · see citing works
Identification of Genetic Variants That Affect Histone Modifications in Human Cells
McVicker, G., van de Geijn, B., Degner, J. F., Cain, C. E., Banovich, N. E., Raj, A., Lewellen, N., Myrthil, M., Gilad, Y., & Pritchard, J. K. (2013) · Science · doi:10.1126/science.1242429 · Cited by 443 · see citing works
Levinson, D. F., Duan, J., Oh, S., Wang, K., Sanders, A. R., Shi, J., Zhang, N., Mowry, B. J., Olincy, A., Amin, F., et al. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.10060876 · Cited by 434 · see citing works
Self-citationLarge multiallelic copy number variations in humans
Handsaker, R. E., Doren, V. V., Berman, J. R., Genovese, G., Kashin, S., Boettger, L. M., & McCarroll, S. A. (2015) · Nature Genetics · doi:10.1038/ng.3200 · Cited by 382 · 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
Large-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
Multiplexed Engineering and Analysis of Combinatorial Enhancer Activity in Single Cells
Xie, S., Duan, J., Li, B., Zhou, P., & Hon, G. C. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.03.007 · Cited by 334 · see citing works
Self-citationTranscriptome 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
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
ANP32E is a histone chaperone that removes H2A.Z from chromatin
Obri, A., Ouararhni, K., Papin, C., Diebold, M.-L., Padmanabhan, K., Marek, M., Stoll, I., Roy, L., Reilly, P., Mak, T., et al. (2014) · Nature · doi:10.1038/nature12922 · Cited by 257 · see citing works
Chromatin Accessibility Dynamics during iPSC Reprogramming
Li, D., Liu, J., Yang, X., Zhou, C., Guo, J., Wu, C., Qin, Y., Guo, L., He, J., Yu, S., et al. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.10.012 · Cited by 251 · see citing works
Neuron-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
How Tlg2p/syntaxin 16 'snares’ Vps45
Dulubova, I., Yamaguchi, T., Gao, Y., Min, S., Huryeva, I., Südhof, T. C., & Rizo, J. (2002) · The EMBO Journal · doi:10.1093/emboj/cdf381 · Cited by 204 · see citing works
Takata, A., Matsumoto, N., & Kato, T. (2017) · Nature Communications · doi:10.1038/ncomms14519 · Cited by 184 · see citing works
An atlas of chromatin accessibility in the adult human brainPreprint
Fullard, J. F., Hauberg, M. E., Bendl, J. M., Egervári, G., Cirnaru, M., Reach, S. M., Motl, J., Ehrlich, M. E., Hurd, Y. L., & Roussos, P. (2018) · Genome Research · doi:10.1101/gr.232488.117 · Cited by 180 · see citing works
Iwaki, H., Blauwendraat, C., Leonard, H. L., Kim, J. J., Liu, G., Maple‐Grødem, J., Corvol, J., Pihlstrøm, L., van Nimwegen, M., Hutten, S. J., et al. (2019) · Movement Disorders · doi:10.1002/mds.27845 · Cited by 175 · see citing works
Song, M., Yang, X.-Y., Ren, X.-J., Maliskova, L., Li, B.-K., Jones, I. R., Wang, C., Jacob, F., Wu, K. Y., Traglia, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0472-1 · Cited by 172 · 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
DNase Footprint Signatures Are Dictated by Factor Dynamics and DNA Sequence
Sung, M., Guertin, M. J., Baek, S., & Hager, G. L. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.08.016 · Cited by 158 · see citing works
Hoffman, G. E., Hartley, B. J., Flaherty, E. K., Ladran, I., Gochman, P., Ruderfer, D. M., Stahl, E. A., Rapoport, J. L., Sklar, P. B., & Brennand, K. (2017) · Nature Communications · doi:10.1038/s41467-017-02330-5 · Cited by 158 · see citing works
Analysis of computational footprinting methods for DNase sequencing experiments
Gusmao, E. G., Allhoff, M., Zenke, M., & Costa, I. G. (2016) · Nature Methods · doi:10.1038/nmeth.3772 · Cited by 152 · see citing works
Nab proteins are essential for peripheral nervous system myelination
Le, N., Nagarajan, R., Wang, J. Y. T., Svaren, J. P., Daniels, C. M. L., Araki, T., Schmidt, R. E., & Milbrandt, J. (2005) · Nature Neuroscience · doi:10.1038/nn1490 · Cited by 130 · see citing works
Common variants at 12q15 and 12q24 are associated with infant head circumference
Taal, H. R., Pourcain, B. S., Thiering, E., Das, S., Mook‐Kanamori, D. O., Warrington, N. M., Kaakinen, M., Kreiner‐Møller, E., Bradfield, J. P., Freathy, R. M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2238 · Cited by 129 · see citing works
A hybridization-chain-reaction-based method for amplifying immunosignals
Lin, R., Feng, Q., Li, P., Zhou, P., Wang, R., Liu, Z., Wang, Z., Qi, X., Tang, N., Shao, F., et al. (2018) · Nature Methods · doi:10.1038/nmeth.4611 · Cited by 125 · see citing works
Genomic DISC1 Disruption in hiPSCs Alters Wnt Signaling and Neural Cell Fate
Srikanth, P., Han, K., Callahan, D. G., Makovkina, E., Muratore, C., Lalli, M. A., Zhou, H., Boyd, J. D., Kosik, K. S., Selkoe, D. J., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.07.061 · Cited by 118 · see citing works
Forrest, M. P., Zhang, H., Moy, W., McGowan, H., Leites, C., Dionisio, L. E., Xu, Z., Shi, J., Sanders, A. R., Greenleaf, W. J., et al. (2017) · Cell stem cell · doi:10.1016/j.stem.2017.07.008 · Cited by 118 · see citing works
Self-citationWen, X. (2016) · The Annals of Applied Statistics · doi:10.1214/16-aoas952 · Cited by 101 · see citing works
Allele-specific epigenome maps reveal sequence-dependent stochastic switching at regulatory loci
Onuchic, V., Lurie, E., Carrero, I., Pawliczek, P., Patel, R. Y., Rozowsky, J. S., Galeev, T. R., Huang, Z., Altshuler, R. C., Zhang, Z., et al. (2018) · Science · doi:10.1126/science.aar3146 · Cited by 99 · see citing works
Landscape of monoallelic DNA accessibility in mouse embryonic stem cells and neural progenitor cells
Xu, J., Carter, A. C., Gendrel, A.-V., Attia, M., Loftus, J. R., Greenleaf, W. J., Tibshirani, R. J., Heard, É., & Chang, H. Y. (2017) · Nature Genetics · doi:10.1038/ng.3769 · Cited by 97 · see citing works
Modeling psychiatric disorders with patient-derived iPSCs
Wen, Z., Christian, K. M., Song, H., & Ming, G.-L. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.11.003 · Cited by 84 · see citing works
Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq
Weissbein, U., Schachter, M., Egli, D., & Benvenisty, N. (2016) · Nature Communications · doi:10.1038/ncomms12144 · Cited by 64 · see citing works
Deriving dopaminergic neurons for clinical use. A practical approach
Gonzalez, R., Garitaonandia, I., Abramihina, T., Wambua, G. K., Ostrowska, A., Brock, M., Noskov, A., Boscolo, F. S., Craw, J. S., Laurent, L. C., et al. (2013) · Scientific Reports · doi:10.1038/srep01463 · Cited by 56 · see citing works
Structural Insights into SHARPIN-Mediated Activation of HOIP for the Linear Ubiquitin Chain Assembly
Liu, J., Wang, Y., Gong, Y., Fu, T., Hu, S., Zhou, Z., & Pan, L. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.09.031 · Cited by 50 · see citing works
ASCL1- and DLX2-induced GABAergic neurons from hiPSC-derived NPCs
Barretto, N., Zhang, H., Powell, S. K., Fernando, M. B., Zhang, S., Flaherty, E. K., Ho, S., Slesinger, P. A., Duan, J., & Brennand, K. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108548 · Cited by 47 · see citing works
Self-citationHaslinger, D., Waltes, R., Yousaf, A., Lindlar, S., Schneider, I., Lim, C. K., Tsai, M., Garvalov, B. K., Acker‐Palmer, A., Krezdorn, N., et al. (2018) · Molecular Autism · doi:10.1186/s13229-018-0239-z · Cited by 41 · see citing works
Uğur, B., Bao, H., Stawarski, M., Duraine, L., Zuo, Z., Qi, L. Y., Neely, G. G., Macleod, G. T., Chapman, E. R., & Bellen, H. J. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.12.005 · Cited by 40 · 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
Park, S. M., Littleton, J. T., Park, H. R., & Lee, J. (2016) · Experimental Neurobiology · doi:10.5607/en.2016.25.1.33 · Cited by 27 · see citing works
Allele-specific transcription factor binding as a benchmark for assessing variant impact predictorsPreprint
Wagih, O., Merico, D., Delong, A., & Frey, B. J. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/253427 · Cited by 19 · see citing works
Amyloid β perturbs elevated heme flux induced with neuronal development
Vidal, C., Daescu, K., FitzGerald, K. E., Starokadomska, A., Борисович, Б. И., & Li, Z. (2019) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2018.12.003 · Cited by 11 · see citing works
Evolving a pathogen to be protective
d’Enfert, C. (2018) · Science · doi:10.1126/science.aav3374 · Cited by 4 · see citing works
Endeneon, Zhou, Y., & M. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.3728036 · Cited by 1 · see citing works
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- [70]Willer CJ, Discovery and refinement of loci associated with lipid levels. Nat Genet 45, 1274– 1283 (2013). 24097068 PMC3838666
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Sorted by citations
BIN1 is a key regulator of proinflammatory and neurodegeneration-related activation in microglia
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00535-x · Cited by 107 · see citing works
Self-citationShi, X., Li, Y., Yuan, Q., Tang, S., Guo, S., Zhang, Y., He, J., Zhang, X., Han, M., Liu, Z., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29857-6 · Cited by 101 · see citing works
Global discovery of lupus genetic risk variant allelic enhancer activity
Lu, X., Chen, X., Forney, C. R., Donmez, O. A., Miller, D., Parameswaran, S., Hong, T., Huang, Y., Pujato, M. A., Cazares, T. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21854-5 · Cited by 74 · see citing works
Perspectives on Allele-Specific Expression
Cleary, S., & Seoighe, C. (2021) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-021621-122219 · Cited by 67 · see citing works
Seah, C., Breen, M. S., Rusielewicz, T., Bader, H. N., Xu, C., Hunter, C. J., McCarthy, B., Deans, P. J. M., Chattopadhyay, M., Goldberg, J., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01161-y · Cited by 67 · 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
Brain Lipids and Lipid Droplet Dysregulation in Alzheimer’s Disease and Neuropsychiatric Disorders
Zhao, X., Zhang, S., Sanders, A. R., & Duan, J. (2023) · Complex Psychiatry · doi:10.1159/000535131 · Cited by 54 · see citing works
Self-citationMassively parallel techniques for cataloguing the regulome of the human brain
Townsley, K. G., Brennand, K., & Huckins, L. M. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00740-1 · Cited by 52 · see citing works
PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia
Kozlova, A., Zhang, S., Sudwarts, A., Zhang, H., Smirnou, S., Byeon, S. K., Thapa, C., Sun, X., Stephenson, K., Zhao, X., et al. (2025) · Nature · doi:10.1038/s41586-025-09486-x · Cited by 53 · see citing works
“…identify functional LOAD GWAS risk variants, we performed an assay for transposase-accessible chromatin using sequencing (ATAC–seq) and ascertained the allelic imbalance of chromatin accessibility (that is, ASoC) 20,21 at heterozygous LOAD-risk single-nucleotide polymorphism (SNP) sites (Fig.”
InfluentialSelf-citationWang, L., Mirabella, V. R., Dai, R., Su, X. Y., Xu, R., Jadali, A., Bernabucci, M., Singh, I., Chen, Y., Tian, J., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01834-x · Cited by 52 · see citing works
Self-citationSystematic investigation of allelic regulatory activity of schizophrenia-associated common variants
McAfee, J. C., Lee, S., Lee, J., Bell, J., Krupa, O., Davis, J. E., Insigne, K. D., Bond, M. L., Zhao, N., Boyle, A. P., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100404 · Cited by 49 · see citing works
Li, M., Li, Y., Qin, H., Tubbs, J. D., Li, M., Qiao, C., Lin, J., Li, Q., Fan, F., Gou, M., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-00968-0 · Cited by 46 · see citing works
Massively parallel functional dissection of schizophrenia-associated noncoding genetic variants
Rummel, C. K., Gagliardi, M., Ahmad, R., Herholt, A., Jiménez-Barrón, L. T., Murek, V., Weigert, L., Hausruckinger, A., Maidl, S., Hauger, B., et al. (2023) · Cell · doi:10.1016/j.cell.2023.09.015 · Cited by 48 · see citing works
Genetic regulation of cell type–specific chromatin accessibility shapes brain disease etiology
Zeng, B., Bendl, J. M., Deng, C., Lee, D., Misir, R., Reach, S. M., Kleopoulos, S. P., Auluck, P. K., Marenco, S., Lewis, D. A., et al. (2024) · Science · doi:10.1126/science.adh4265 · Cited by 44 · see citing works
Targeting epigenetic dysregulation in autism spectrum disorders
Herrera, M. L., Paraíso‐Luna, J., Bustos-Martínez, I., & Barco, Á. (2024) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2024.06.004 · Cited by 43 · see citing works
Focus on your locus with a massively parallel reporter assay
McAfee, J. C., Bell, J., Krupa, O., Matoba, N., Stein, J. L., & Won, H. (2022) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-022-09461-x · Cited by 39 · see citing works
Publicly Available hiPSC Lines with Extreme Polygenic Risk Scores for Modeling Schizophrenia
Dobrindt, K., Zhang, H., Das, D., Abdollahi, S., Prorok, T., Ghosh, S. D., Weintraub, S. J., Genovese, G., Powell, S. K., Lund, A. N., et al. (2020) · Complex Psychiatry · doi:10.1159/000512716 · Cited by 32 · see citing works
Self-citationHu, W., Jiang, C., Kim, M., Yang, W., Zhu, K., Guan, D., Lv, W., Xiao, Y., Wilson, J. R., Rader, D. J., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.06.004 · Cited by 36 · see citing works
Evaluating brain structure traits as endophenotypes using polygenicity and discoverability
Matoba, N., Love, M. I., & Stein, J. L. (2020) · Human Brain Mapping · doi:10.1002/hbm.25257 · Cited by 32 · see citing works
Functional characterization of human genomic variation linked to polygenic diseases
Fabo, T., & Khavari, P. A. (2023) · Trends in Genetics · doi:10.1016/j.tig.2023.02.014 · Cited by 31 · see citing works
Chang, H., Cai, X. M., Li, H., Liu, W.-P., Zhao, L., Zhang, C., Wang, J., Liu, J.-W., Ma, X.-L., Wang, L., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.09.016 · Cited by 29 · see citing works
Sey, N. Y. A., Hu, B., Iskhakova, M., Lee, S., Sun, H., Shokrian, N., Hutta, G. B., Marks, J. A., Quach, B. C., Johnson, E. O., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01558-y · Cited by 27 · see citing works
Zhang, B., Zhang, Z., Koeken, V. A. C. M., Kumar, S., Aillaud, M., Tsay, H.-C., Liu, Z., Kraft, A. R. M., Soon, C. F., Odak, I., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100232 · Cited by 26 · see citing works
Zhang, S., Zhang, H., Forrest, M. P., Zhou, Y., Sun, X., Bagchi, V. A., Kozlova, A., Santos, M. D., Piguel, N. H., Dionisio, L. E., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100399 · Cited by 26 · see citing works
Self-citationKozlova, A., Zhang, S., Kotlar, A., Jamison, B., Zhang, H., Shi, S. Q. Z., Forrest, M. P., McDaid, J., Cutler, D. J., Epstein, M. P., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.07.001 · Cited by 24 · see citing works
Self-citationLi, Q., Wang, Z., Zong, L., Ye, L., Ye, J., Ou, H., Jiang, T., Guo, B., Yang, Q., Liang, W., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01126-w · Cited by 24 · see citing works
Silveira, P. P., & Meaney, M. J. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106008 · Cited by 24 · see citing works
Guo, M., Reynolds, D., Ang, C., Liu, Y.-F., Zhao, Y., Donohue, L., Siprashvili, Z., Yang, X., Yoo, Y., Mondal, S., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01533-5 · Cited by 21 · 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
Lewis, E. M. A., Kaushik, K., Sandoval, L. A., Antony, I., Dietmann, S., & Kroll, K. L. (2021) · Neurochemistry International · doi:10.1016/j.neuint.2021.105039 · Cited by 22 · see citing works
Clay, S. M., Schoettler, N., Goldstein, A. M., Carbonetto, P. S., Dapas, M., Altman, M. C., Rosasco, M. G., Gern, J. E., Jackson, D. J., Im, H. K., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01058-2 · Cited by 20 · see citing works
Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis
Shook, M., Lu, X., Chen, X., Parameswaran, S., Edsall, L., Trimarchi, M. P., Ernst, K., Granitto, M., Forney, C. R., Donmez, O. A., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.12.008 · Cited by 19 · see citing works
Yao, Y., Guo, W., Zhang, S., Yu, H., Yan, H., Zhang, H., Sanders, A. R., Yue, W., & Duan, J. (2021) · iScience · doi:10.1016/j.isci.2021.102785 · Cited by 18 · see citing works
Self-citationGedik, H., Nguyen, T. H., Peterson, R. E., Chatzinakos, C., Riley, B. P., Vladimirov, V. I., & Bacanu, S. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1191264 · Cited by 16 · see citing works
Choi, W., Hwang, J.-H., Cho, A., Lee, A., Jung, I., Cho, S., Kim, L. K., & Kim, Y.-J. (2020) · Molecules and Cells · doi:10.14348/molcells.2020.0207 · Cited by 17 · see citing works
Zhao, X., Li, Y., Zhang, S., Sudwarts, A., Zhang, H., Kozlova, A., Moulton, M. J., Goodman, L. D., Pang, Z. P., Sanders, A. R., et al. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00840-1 · Cited by 18 · see citing works
Self-citationZhang, H., McCarroll, A., Peyton, L., de León‐Guerrero, S. D., Zhang, S., Gowda, P., Sirkin, D., ElAchwah, M., Duhe, A., Wood, W., et al. (2024) · Stem Cell Reports · doi:10.1016/j.stemcr.2024.08.003 · Cited by 15 · see citing works
Self-citationHighly sensitive single-cell chromatin accessibility assay and transcriptome coassay with METATAC
Wu, H., Li, X., Jian, F., Yisimayi, A., Zheng, Y., Tan, L., Xing, D., & Xie, X. S. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2206450119 · Cited by 15 · see citing works
Zhang, Y., Day, K., & Absher, D. M. (2022) · eLife · doi:10.7554/elife.72837 · Cited by 15 · see citing works
Ma, Y., Bendl, J. M., Hartley, B. J., Fullard, J. F., Abdelaal, R., Ho, S., Kosoy, R., Gochman, P., Rapoport, J. L., Hoffman, G. E., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.07.003 · Cited by 13 · see citing works
Wang, B., Starr, A. L., & Fraser, H. B. (2024) · eLife · doi:10.7554/elife.89594.3 · Cited by 14 · see citing works
Epigenetic and transcriptional dysregulation in CD4+ T cells in patients with atopic dermatitis
Eapen, A., Parameswaran, S., Forney, C. R., Edsall, L., Miller, D., Donmez, O., Dunn, K. A., Lu, X., Granitto, M., Rowden, H., et al. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1009973 · Cited by 14 · see citing works
Wang, B., Starr, A. L., & Fraser, H. B. (2023) · eLife · doi:10.7554/elife.89594 · Cited by 33 · see citing works
Uncovering Divergence in Gene Expression Regulation in the Adaptation of Yeast to Nitrogen Scarcity
Villarroel, C. A., Bastías, M., Canessa, P., & Cubillos, F. A. (2021) · mSystems · doi:10.1128/msystems.00466-21 · Cited by 14 · see citing works
Ye, J., Huang, Z., Li, Q., Li, Z., Lan, Y., Wang, Z., Ni, C., Wu, X., Jiang, T., Li, Y., et al. (2023) · BMC Medicine · doi:10.1186/s12916-023-03177-y · Cited by 12 · see citing works
The non-coding genome in genetic brain disorders: new targets for therapy?
Salsench, E. M., Karkala, F., Lanko, K., & Barakat, T. S. (2021) · Essays in Biochemistry · doi:10.1042/ebc20200121 · Cited by 11 · see citing works
Epigenome rewiring in human pluripotent stem cells
Yan, J., & Huangfu, D. (2021) · Trends in Cell Biology · doi:10.1016/j.tcb.2021.12.001 · Cited by 9 · see citing works
Muhtaseb, A. W., & Duan, J. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.04.003 · Cited by 11 · see citing works
Self-citationLai, B., Qian, S., Zhang, H., Zhang, S., Kozlova, A., Duan, J., He, X., & Xu, J. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010011 · Cited by 13 · see citing works
Self-citationConvergent and non-additive impact of schizophrenia risk genes in human neuronsPreprint
Deans, P. M., Townsley, K. G., Li, A., Seah, C., Johnson, J., García‐González, J., Cao, E., Schrode, N., Yu, A., Cartwright, S., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.29.486286 · Cited by 12 · see citing works
DeepGWAS: Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural NetworkPreprint
Li, Y., Wen, J., Li, G., Chen, J. C., Sun, Q., Liu, W., Guan, W., Lai, B., Szatkiewicz, J., He, X., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2399024/v1 · Cited by 10 · see citing works
Self-citationGenetic transcriptional regulation profiling of cartilage reveals pathogenesis of osteoarthritis
Tian, W., Dong, S.-S., Jiang, F., Zhang, J.-Q., Wang, C., He, C.-Y., Hu, S.-Y., Hao, R.-H., Song, H., Gao, H.-W., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105821 · Cited by 11 · see citing works
García, M. F., Townsley, K. G., Pruitt, A., Davidson, E., Balafkan, N., Warrell, J., Huang, T.-C., Kibowen, A., Chu, Z., Dai, Y., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02247-7 · Cited by 10 · see citing works
Kozlova, A., Butler, R. R., Zhang, S., Ujas, T. A., Zhang, H., Steidl, S., Sanders, A. R., Pang, Z. P., Vezina, P., & Duan, J. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01027-0 · Cited by 9 · see citing works
Self-citationNon-additive effects of schizophrenia risk genes reflect convergent downstream functionPreprint
Deans, P. M., Seah, C., Johnson, J., García‐González, J., Townsley, K. G., Cao, E., Schrode, N., Stahl, E. A., O’Reilly, P. F., Huckins, L. M., et al. (2023) · medRxiv · doi:10.1101/2023.03.20.23287497 · Cited by 9 · see citing works
Identification, Design, and Application of Noncoding Cis-Regulatory Elements
Xu, L., & Liu, Y. (2024) · Biomolecules · doi:10.3390/biom14080945 · Cited by 9 · see citing works
Mutations of schizophrenia risk gene SETD1A dysregulate synaptic function in human neurons
Su, X. Y., Zhang, H., Yan, H., Yang, Q., Wang, L., Le, T. T., Liu, J., Cheruvu, L., Labour, E., Zhang, S., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03246-z · Cited by 9 · see citing works
Self-citationSEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty
Wu, E. Y., Singh, N. P., Choi, K., Zakeri, M., Vincent, M., Churchill, G., Ackert-Bicknell, C., Patro, R., & Love, M. (2023) · Genome Biology · doi:10.1186/s13059-023-03003-x · Cited by 6 · see citing works
Anderson, A. G., Moyers, B. A., Loupe, J. M., Rodríguez-Nunez, I., Felker, S. A., Lawlor, J. M. J., Bunney, W. E., Bunney, B. G., Cartagena, P. M., Sequeira, A., et al. (2024) · Genome Research · doi:10.1101/gr.278601.123 · Cited by 8 · see citing works
Dynamic convergence of neurodevelopmental disorder risk genes across neurodevelopmentPreprint
García, M. F., Townsley, K. G., Pruitt, A., Davidson, E., Balafkan, N., Warrell, J., Huang, T.-C., Kibowen, A., Chu, Z., Dai, Y., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.23.609190 · Cited by 9 · see citing works
Allele-specific expression analysis: pipelines, applications, challenges, and unmet needs
Mattevi, S., Mazzarotto, F., & Martini, P. G. V. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110890 · Cited by 7 · see citing works
Davis, K. N., Qu, P., Ma, S., Lin, L., Plastini, M. J., Dahl, N., Plazzi, G., Pizza, F., O'Hara, R. M., Wong, W. H., et al. (2023) · Human Molecular Genetics · doi:10.1093/hmg/ddad123 · Cited by 7 · see citing works
Detera‐Wadleigh, S. D., Kassem, L., Besancon, E., Lopes, F. L., Akula, N., Sung, H., Blattner, M., Sheridan, L., Lacbawan, L. N., Garcia, J., et al. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02641-w · Cited by 7 · see citing works
Michalski, C., & Wen, Z. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1291115 · Cited by 7 · see citing works
Implications of gene × environment interactions in post-traumatic stress disorder risk and treatment
Seah, C., Sidamon‐Eristoff, A. E., Huckins, L. M., & Brennand, K. (2025) · Journal of Clinical Investigation · doi:10.1172/jci185102 · Cited by 7 · see citing works
dbBIP: a comprehensive bipolar disorder database for genetic research
Li, X., Ma, S., Yan, W., Wu, Y. Q., Kong, H., Zhang, M., Luo, X., & Xia, J. (2022) · Database · doi:10.1093/database/baac049 · Cited by 6 · see citing works
Gedik, H., Peterson, R. E., Riley, B. P., Vladimirov, V. I., & Bacanu, S. (2023) · Complex Psychiatry · doi:10.1159/000530223 · Cited by 6 · see citing works
Modeling PTSD neuronal stress responses in a dish
Zhang, S., Sanders, A. R., & Duan, J. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01172-9 · Cited by 6 · see citing works
Self-citationSequence and parent-of-origin dependent m6A contribute to allele-specific gene expression
Zhang, Y., Zhang, Z., Chen, H.-X., Liu, C., Liu, B.-D., Lan, Y.-L., Xie, Y.-Y., Chen, T., Chen, S., Feng, G., et al. (2025) · The EMBO Journal · doi:10.1038/s44318-025-00476-3 · Cited by 5 · see citing works
CRISPR/Cas9-mediated Precise SNP Editing in Human iPSC Lines
Zhang, H., & Zhang, S. (2021) · BIO-PROTOCOL · doi:10.21769/bioprotoc.4051 · Cited by 5 · see citing works
Self-citationDifferential Allelic Expression among Long Non-Coding RNAs
Heskett, M. B., Spellman, P. T., & Thayer, M. J. (2021) · Non-Coding RNA · doi:10.3390/ncrna7040066 · Cited by 5 · see citing works
Rummel, C. K., Gagliardi, M., Herholt, A., Ahmad, R., Murek, V., Weigert, L., Hausruckinger, A., Maidl, S., Jiménez-Barrón, L. T., Trastulla, L., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.27.545266 · Cited by 5 · see citing works
Ward, T. R., Qu, P.-P., Leung, L. C., Zhou, B., Muench, K. L., Khechaduri, A., Plastini, M. J., Charlton, C. A., Pattni, R., Ho, S. S., et al. (2025) · European Journal of Human Genetics · doi:10.1038/s41431-025-01856-3 · Cited by 5 · see citing works
Lee, D., Seo, J., Jeong, H. C., Lee, H., & Lee, S. B. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.756613 · Cited by 6 · see citing works
Genome-wide discovery of SLE genetic risk variant allelic enhancer activityPreprint
Lu, X., Chen, X., Forney, C., Donmez, O. A., Miller, D., Parameswaran, S., Hong, T., Huang, Y., Pujato, M., Cazares, T., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.20.906701 · Cited by 4 · see citing works
3D genetic architecture of schizophrenia risk across three neuronal subtypes
Powell, S. K., Liao, W., Ghorbani, S., Rigat, R., O’Shea, C. P., Kammourh, S., Elahi, R., Infante, D., Deans, P. M., Le, D. J., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03352-y · Cited by 4 · see citing works
Functional implications of polygenic risk for schizophrenia in human neurons
Deans, P. M., Townsley, K. G., Li, A., Seah, C., Johnson, J., García‐González, J., Cao, E., Schrode, N., Yu, A., Cartwright, S., et al. (2026) · Nature Communications · doi:10.1038/s41467-025-67959-z · Cited by 4 · see citing works
Leveraging allelic imbalance in accessible chromatin to prioritize putative causal variants
Morilla, L. M., Amoaning, R. E., Luo, S., Moharam, R. G., Huang, C., & Yip, S. P. (2026) · Trends in Genetics · doi:10.1016/j.tig.2025.12.008 · Cited by 3 · see citing works
Single-cell multiomics of neuron activation reveals context-specific genetics of brain disorders
Liang, L., Zhang, S., Wang, Z., Zhang, H., Li, C., Thapa, C., Oh, E., Sirkin, D., Sun, X., Barishman, A., et al. (2026) · Science · doi:10.1126/science.adw3949 · Cited by 3 · see citing works
Self-citationEpigenetic and Transcriptional Dysregulation in T cells of Patients with Atopic Dermatitis
Eapen, A., Parameswaran, S., Forney, C. R., Edsall, L., Miller, D., Donmez, O. A., Dunn, K., Lu, X., Granitto, M., Rowden, H., et al. (2022) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2021.12.059 · Cited by 3 · see citing works
Gregg, C. J. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.693781 · Cited by 4 · see citing works
Yu, Z., Qian, F., Fang, Q.-L., Meng, X., Li, Y., Feng, C., Li, L., Li, B., Feng, Y.-R., Jiang, H., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1112 · Cited by 2 · see citing works
Shen, J., & Xiao, C. (2025) · Schizophrenia · doi:10.1038/s41537-025-00705-y · Cited by 2 · see citing works
Developmental reprogramming underlies chemotherapy resistance in favorable-histology Wilms tumor
Fleming, A., Jablonowski, C. M., Jin, H.-J., Zhang, S.-W., Sona, S., Lee, H. W., Dieseldorff-Jones, K., Cheng, C.-D., Xu, B.-S., Morton, C. L., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117063 · Cited by 2 · see citing works
Self-citationRethinking disomy: Autosomal expression bias
Bogunovic, D. (2026) · The Journal of Experimental Medicine · doi:10.1084/jem.20241044 · Cited by 2 · see citing works
Lai, B., Qian, S., Zhang, H., Zhang, S., Kozlova, A., Duan, J., He, X., & Xu, J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.02.429064 · Cited by 2 · see citing works
Self-citationDeepGWAS: Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural NetworkPreprint
Wen, J., Li, G., Chen, J. C., Sun, Q., Liu, W., Guan, W., Lai, B., Zhou, H., Szatkiewicz, J., He, X., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.20.521277 · Cited by 2 · see citing works
Self-citationSchizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal SubtypesPreprint
Powell, S. K., Liao, W., O’Shea, C. P., Kammourh, S., Ghorbani, S., Rigat, R., Elahi, R., Deans, P. M., Le, D. J., Agarwal, P., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.17.549339 · Cited by 2 · see citing works
Zhao, X., Li, Y., Zhang, S., Sudwarts, A., Zhang, H., Kozlova, A., Moulton, M. J., Goodman, L. D., Pang, Z. P., Sanders, A. R., et al. (2024) · medRxiv · doi:10.1101/2024.08.14.24312009 · Cited by 2 · see citing works
Self-citationHuman stem cell modeling of neuropsychiatric disorders: from polygenicity to convergence
Duan, J. (2023) · Medical Review · doi:10.1515/mr-2023-0016 · Cited by 1 · see citing works
Self-citationBetter together: Non-additive interactions between schizophrenia risk genes
Deans, P. J. M., & Brennand, K. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100403 · Cited by 1 · see citing works
Kono, M., Hatano, H., Asahara, K., Nakano, M., Bagherzadeh, R., Kawashima, T., Arakawa, T., Sato, M., Inokuchi, H., Nishino, T., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-75767-2 · Cited by 1 · see citing works
ATAC-seq and psychiatric disorders
Fullard, J. F., Bendl, J. M., & Roussos, P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823577-5.00036-2 · Cited by 1 · see citing works
Introduction to epigenetics in psychiatry
Lee, R. S., & Avramopoulos, D. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823577-5.00009-x · Cited by 1 · see citing works
Self-citationSey, N. Y. A., Hu, B., Iskhakova, M., Sun, H., Shokrian, N., Hutta, G. B., Marks, J. A., Quach, B. C., Johnson, E. O., Hancock, D. B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.18.436046 · Cited by 1 · see citing works
Uncovering divergence in gene expression regulation in the adaptation of yeast to nitrogen scarcityPreprint
Villarroel, C. A., Bastías, M., Canessa, P., & Cubillos, F. A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.15.440091 · Cited by 1 · see citing works
Zhang, S., Zhang, H., Forrest, M. P., Zhou, Y., Bagchi, V. A., Kozlova, A., Santos, M. D., Piguel, N. H., Dionisio, L. E., Sanders, A. R., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.11.472229 · Cited by 1 · see citing works
Self-citationWang, B., Starr, A. L., & Fraser, H. B. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.22.541747 · Cited by 1 · see citing works
Wang, B., Starr, A. L., & Fraser, H. B. (2023) · eLife · doi:10.7554/elife.89594.1 · Cited by 1 · see citing works
Wang, B., Starr, A. L., & Fraser, H. B. (2024) · eLife · doi:10.7554/elife.89594.2 · Cited by 1 · see citing works
- Authors
- Zhang, S., Zhang, H., Zhou, Y., Qiao, M., Zhao, S., Kozlova, A., Shi, J., Sanders, A. R., Wang, G., Luo, K., Sengupta, S., West, S., Qian, S., Streit, M., Avramopoulos, D., Cowan, C. A., Chen, M., Pang, Z. P., Gejman, P. V., He, X., & Duan, J.
- Affiliations
- Endeavor Health (US)
- University of Chicago (US)
- National Cancer Institute (US)
- Johns Hopkins University (US)
- Harvard University (US)
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Zhang, Siwei
- Zhang, Hanwen
- Zhou, Yifan
- Qiao, Min
- Zhao, Siming
- He, Xin
- Duan, Jubao
- ORCID
- Venue
- Science
- Published
- 2020-07-31
- Volume
- 369
- Issue
- 6503
- Pages
- 561-565
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7773145
- OpenAlex
- W3046891017
- Cited by
- 127
- References
- 88
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 17 · 2023: 25 · 2022: 30 · 2021: 20 · 2020: 8
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH Office of the Director (R01MH106575, R01MH116281, R01AG063175, R01MH110531, R01AA023797, R01MH113215)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- non-coding variants, chromatin accessibility, iPSC-derived neurons, brain development, transcription factor binding, enhancers, expression quantitative trait loci, chromatin interactions
- MeSH terms
- Alleles, Brain, Chromatin, Enhancer Elements, Genetic, Humans, Risk, Schizophrenia, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Induced Pluripotent Stem Cells
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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.
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