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Spatio-temporal transcriptome of the human brain
Open accessAbstract
Brain development and function depend on the precise regulation of gene expression. However, our understanding of the complexity and dynamics of the transcriptome of the human brain is incomplete. Here we report the generation and analysis of exon-level transcriptome and associated genotyping data, representing males and females of different ethnicities, from multiple brain regions and neocortical areas of developing and adult post-mortem human brains. We found that 86 per cent of the genes analysed were expressed, and that 90 per cent of these were differentially regulated at the whole-transcript or exon level across brain regions and/or time. The majority of these spatio-temporal differences were detected before birth, with subsequent increases in the similarity among regional transcriptomes. The transcriptome is organized into distinct co-expression networks, and shows sex-biased gene expression and exon usage. We also profiled trajectories of genes associated with neurobiological categories and diseases, and identified associations between single nucleotide polymorphisms and gene expression. This study provides a comprehensive data set on the human brain transcriptome and insights into the transcriptional foundations of human neurodevelopment.
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“In particular, these approaches have implicated the projection neurons in the prefrontal and primary motor-somatosensory cortex during mid-fetal development in autism spectrum disorder and the frontal cortex during fetal development in schizophrenia (Gulsuner et al., 2013; Kang et al., 2011; Lin et al., 2015; Parikshak et al., 2013; State and Sestan, 2012; Willsey et al., 2013).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Surprisingly, it turned out that transcription profiles in the adult neocortex are relatively homogeneous throughout the cortex, although a certain level of heterogeneity still does exist (Hawrylycz et al., 2012; Kang et al., 2011; Pletikos et al., 2014)”
From Genetic Changes Shaping the Human Brain (2015) · cites this paper as Kang et al., 2011
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In the citing paper
“We chose dorsal frontal cortex (DFC) and CBC for our analyses because both regions have been implicated in DS neuropathology (Hartley et al., 2014; Haydar and Reeves, 2012; Letourneau et al., 2014; Lott, 2012) and exhibit diverse transcriptional profiles over the course of development (Kang et al., 2011; Tebbenkamp et al., 2014).”
From Down Syndrome Developmental Brain Transcriptome Reveals Defective Oligodendrocyte Differentiation and Myelination (2016) · cites this paper as Kang et al., 2011
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In the citing paper
“NaV1.2 is widely expressed throughout the human central nervous system, but not in peripheral tissues [7,8].”
From Progress in Understanding and Treating SCN2A-Mediated Disorders (2018) · cites this paper as [8]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“SCN2A expression begins early in gestation [8], and channel dysfunction may alter brain development.”
From Progress in Understanding and Treating SCN2A-Mediated Disorders (2018) · cites this paper as [8]
Experimental — accuracy not yet measured
In the citing paper
“Developmental stages 5 and 6 represent mid-gestation, the period during which upper layer neurons are generated and neuronal differentiation including axonogenesis and dendritic arborization takes place12,13.”
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 [12]
In the citing paper
“Studies of the human brain transcriptome have shown that genes associated with synaptic functions may be expressed early during intrauterine development (3-6 months gestational age) 3 .”
From Progress toward treatments for synaptic defects in autism (2013) · cites this paper as [3]
In the citing paper
“In contrast, in humans, the genes involved in dendrite and synapse formation are switched on very early in utero , and the amounts of transcripts reach a plateau at 6-9 months of fetal life 3 .”
From Progress toward treatments for synaptic defects in autism (2013) · cites this paper as [3]
In the citing paper
“Recent important advances include the evaluation of spatial and temporal transcriptomes by the Allen Brain Institute and BrainSpan8,11–13”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [13]
In the citing paper
“Network approaches are particularly useful for relating whole-tissue-level changes to data from these high-resolution experiments11–13,26 (FIG. 2a).”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [13]
In the citing paper
“Data was generated across eight studies (2, 19, 20), uniformly processed, and combined through a consolidated genomic data processing pipeline ((21); Fig S1), yielding a total of 2188 samples passing quality control (QC) for this analysis, representing frontal and temporal cerebral cortex from 1695 unique subjects across the lifespan, including 279 technical replicates (Fig S2).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [20]
In the citing paper
“The NMDA receptor changes in composition during prenatal to postnatal neurodevelopment with GRIN2A predominantly expressed during late childhood and adolescence, recapitulating expected epidemiological observations on schizophrenia age-ofonset (Supplementary Information, Figure 3B) 27 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [27]
In the citing paper
“Developed from neuropharmacological and neuropathological observations, the glutamatergic hypothesis postulates that the hypofunction of glutamatergic signaling through NMDA receptors is a possible mechanism of disease28 (Supplementary Note).”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [28]
In the citing paper
“Several important recent studies have begun to analyse transcriptional dynamics during human brain development4, 5, although only in a small number of relatively coarse brain regions.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [4]
In the citing paper
“this high degree of similarity is suggestive of a strong underlying common blueprint for the human brain transcriptome and is consistent with other recent studies of human neocortical gene expression4, 5”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [4]
In the citing paper
“Several recent studies have assayed a limited set of brain structures1,3–5 and layers2 from prenatal human brain.”
From Transcriptional landscape of the prenatal human brain (2014) · cites this paper as [4]
In the citing paper
“The astroglial population is likely largely non-proliferative and fully differentiated by the end of the first postnatal year (Kang et al., 2011; Sanai et al., 2011)”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“Of these, nine out of ten genes were differentially expressed or spliced across brain regions and/or time (Kang et al., 2011; Mazin et al., 2013).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“This work has revealed that the great majority of protein coding genes (at least 86% according to Kang et al., 2011) and an ever-expanding number of non-coding genes (see Box 3) are used at some point in the building of the human CNS.”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“In Kang et al., 2011, the expression trajectories of the two largest modules comprising genes that are co-regulated across brain regions and time, indicate that many transcriptional processes are shared and coordinated across different regions as the brain develops (Figures 3C and D).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“The expression trajectories of the modules, which can be summarized using the module eigengene or an intramodular hub gene, often exhibit dynamic expression patterns across development, consistent with their roles in distinct biological processes (Johnson et al., 2009; Kang et al., 2011; Miller et al., 2014; Parikshak et al., 2013; Willsey et al., 2013).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“In particular, the module enriched for genes associated with neuronal specification is most highly expressed embryonically and early fetally (Figure 3C), while the module enriched for genes associated with synaptic function and ion channels begins to rise late fetally and plateaus in early childhood (Figure 3D).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“When compared with dorsal pallial structures (amygdala, hippocampus and neocortex), the cerebellum is the most transcriptionally distinctive region in the developing brain, followed by thalamus and striatum (Figure 3B) (Kang et al., 2011; Numata et al., 2012).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“Robust inter-areal transcriptional differences were particularly prominent during early and mid-fetal development and included specific transcriptional signatures associated with prospective prefrontal and perisylvian areas (Johnson et al., 2009; Kang et al., 2011; Miller et al., 2014; Pletikos et al., 2014), which are involved in some of the most distinctly human aspects of cognition and behavior”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“Interestingly, these regional/areal transcriptional profiles were largely bilaterally symmetrical across the two hemispheres at the population-level during fetal, early postnatal development and in adulthood (Johnson et al., 2009; Kang et al., 2011; Lambert et al., 2011; Miller et al., 2014; Pletikos et al., 2014).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“Recent transcriptome studies have identified substantial regional/areal differences in the developing human neocortex (Johnson et al., 2009; Kang et al., 2011; Lambert et al., 2011; Miller et al., 2014; Pletikos et al., 2014).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Kang et al., 2011
In the citing paper
“The transcriptome of the developing, prenatal human neocortex, however, is quite heterogeneous across different cortical areas (Johnson et al., 2009; Kang et al., 2011; Miller et al., 2014).”
From Genetic Changes Shaping the Human Brain (2015) · cites this paper as Kang et al., 2011
In the citing paper
“RFX and GPR56 expression patterns are correlated (fig. S5, A and B) (15), with RFX3 and RFX7 most prominent in human ventrolateral prefrontal cortex, the region affected in perisylvian polymicrogyria”
From Evolutionarily Dynamic Alternative Splicing of GPR56 Regulates Regional Cerebral Cortical Patterning (2014) · cites this paper as [15]
In the citing paper
“Each have reinforced findings of significant differences in the transcriptome between neuronal cell-types, brain regions, developmental stages, and species.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [10]
In the citing paper
“Existing whole-tissue analyses10, even combined with careful manual dissection are not sensitive to inter- or intra-cellular variability and, as a result, functional genomic information is ‘diluted’ amongst different classes of intermixed neurons and the high proportion of glial cells.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [10]
In the citing paper
“This finding is opposite previously described patterns of mRNA expression, which has been shown to become more globally similar between brain regions over development (2).”
From Identification of differentially expressed microRNAs across the developing human brain (2014) · cites this paper as [2]
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Citations
Cites
A 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
Bardo, M. T., & Hammer, R. P. (1991) · Neuroscience · doi:10.1016/0306-4522(91)90226-e · Cited by 3,229
Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia
Joutel, A., Corpechot, C., Ducros, A., Vahedi, K., Chabriat, H., Mouton, P., Alamowitch, S., Domenga, V., Cécillion, M., Maréchal, E., et al. (1996) · Nature · doi:10.1038/383707a0 · Cited by 2,068
Mutations of the X-linked genes encoding neuroligins NLGN3 and NLGN4 are associated with autism
Study, P. A. R. I. S., Jamain, S., Quach, H., Betancur, C., Råstam, M., Colineaux, C., Gillberg, I. C., Soderstrom, H., Giros, B., Leboyer, M., et al. (2003) · Nature Genetics · doi:10.1038/ng1136 · Cited by 1,851
Neuroligins and neurexins link synaptic function to cognitive disease
Südhof, T. C. (2008) · Nature · doi:10.1038/nature07456 · Cited by 1,849
Insel, T. R. (2010) · Nature · doi:10.1038/nature09552 · Cited by 1,783
Common variants conferring risk of schizophrenia
†Genetic Risk and Outcome in Psychosis (GROUP), Stefansson, H., Ophoff, R. A., Steinberg, S., Andreassen, O. A., Cichon, S., Rujescu, D., Werge, T., Pietiläinen, O. P. H., Mors, O., et al. (2009) · Nature · doi:10.1038/nature08186 · Cited by 1,677
Evolution of the neocortex: a perspective from developmental biology
Rakic, P. (2009) · Nature reviews. Neuroscience · doi:10.1038/nrn2719 · Cited by 1,565
Intermediate phenotypes and genetic mechanisms of psychiatric disorders
Meyer-Lindenberg, A., & Weinberger, D. R. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1993 · Cited by 1,216
Self-citationSchizophrenia as a Disorder of Neurodevelopment
Lewis, D. A., & Levitt, P. (2002) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.25.112701.142754 · Cited by 1,163
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Sathe, G. J., Albert, M., Darrow, J. A., Saito, A., Troncoso, J. C., Pandey, A., & Moghekar, A. (2020) · Journal of Neurochemistry · doi:10.1111/jnc.15116 · Cited by 65
Functional transcriptomics in the post-ENCODE eraPreprint
Mudge, J. M., Frankish, A., & Harrow, J. (2013) · Genome Research · doi:10.1101/gr.161315.113 · Cited by 64
Decoding neuroproteomics: integrating the genome, translatome and functional anatomy
Kitchen, R. R., Rozowsky, J. S., Gerstein, M. B., & Nairn, A. C. (2014) · Nature Neuroscience · doi:10.1038/nn.3829 · Cited by 63
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Bralten, J., Mota, N. R., Klemann, C. J. H. M., Witte, W. D., Laing, E., Collier, D. A., de Kluiver, H., Bauduin, S., Arango, C., Ayuso‐Mateos, J. L., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01044-z · Cited by 63
Chen, J., Lambo, M. E., Ge, X., Dearborn, J. T., Liu, Y., McCullough, K. B., Swift, R. G., Tabachnick, D. R., Tian, L., Noguchi, K., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.09.009 · Cited by 65
Feng, H., Zhang, X., & Zhang, C. (2015) · Nature Communications · doi:10.1038/ncomms8816 · Cited by 63
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Chen, P. B., Kawaguchi, R., Blum, C., Achiro, J. M., Coppola, G., O’Dell, T. J., & Martin, K. C. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00039 · Cited by 63
Hoftman, G. D., Dienel, S. J., Bazmi, H. H., Zhang, Y., Chen, K., & Lewis, D. A. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.029 · Cited by 63
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Sekar, S., & Liang, W. S. (2019) · Non-coding RNA Research · doi:10.1016/j.ncrna.2019.01.001 · Cited by 64
Forsyth, J. K., Nachun, D. C., Gandal, M. J., Geschwind, D. H., Anderson, A., Coppola, G., & Bearden, C. E. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.06.029 · Cited by 62
Sjöstedt, E., Fagerberg, L., Hallström, B. M., Månberg, A., Mitsios, N., Nilsson, P., Pontén, F., Hökfelt, T. G. M., Uhlén, M., & Mulder, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130028 · Cited by 62
Mahfouz, A. E., Ziats, M. N., Rennert, O. M., Lelieveldt, B. P. F., & Reinders, M. J. T. (2015) · Journal of Molecular Neuroscience · doi:10.1007/s12031-015-0641-3 · Cited by 63
Xu, K., Zhang, Y., Xiong, W., Zhang, Z., Wang, Z., Lv, L., Liu, C., Hu, Z., Zheng, Y., Lü, L., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17435-7 · Cited by 62
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Klin, A. J., Micheletti, M., Klaiman, C., Shultz, S., Constantino, J. N., & JONES, W. R. (2020) · Development and Psychopathology · doi:10.1017/s0954579420000802 · Cited by 63
Boulting, G. L., Durresi, E., Ataman, B., Sherman, M. A., Mei, K., Harmin, D. A., Carter, A. C., Hochbaum, D. R., Granger, A. J., Engreitz, J., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00786-1 · Cited by 62
Georgiev, D., Arion, D., Enwright, J. F., Kikuchi, M., Minabe, Y., Corradi, J. P., Lewis, D. A., & Hashimoto, T. (2014) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2013.13040468 · Cited by 61
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Chen, Y.-C., Sudre, G. P., Sharp, W. S., Donovan, F. X., Chandrasekharappa, S. C., Hansen, N. F., Elnitski, L. L., & Shaw, P. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.45 · Cited by 61
Schultz, C. C., Mühleisen, T. W., Nenadic, I., Koch, K., Wagner, G., Schachtzabel, C., Siedek, F., Nöthen, M. M., Rietschel, M., Deufel, T., et al. (2014) · Psychological Medicine · doi:10.1017/s0033291713001414 · Cited by 60
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Zhang, K., Wang, Y., Fan, T., Zeng, C., & Sun, Z. S. (2020) · Protein & Cell · doi:10.1007/s13238-020-00812-9 · Cited by 60
Beletskiy, A., Chesnokova, E., & Bal, N. V. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22041849 · Cited by 60
Pers, T. H., Timshel, P. N., Ripke, S., Sullivan, P. F., O’Donovan, M. C., Franke, L., & Hirschhorn, J. N. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw007 · Cited by 60
Schenk, S., Bannister, S. C., Sedlazeck, F. J., Anrather, D., Minh, B. Q., Bileck, A., Hartl, M., von Haeseler, A., Gerner, C., Raible, F., et al. (2019) · eLife · doi:10.7554/elife.41556 · Cited by 59
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Paus, T. (2013) · Hormones and Behavior · doi:10.1016/j.yhbeh.2013.04.004 · Cited by 59
Human assembloids reveal the consequences of CACNA1G gene variants in the thalamocortical pathway
Kim, J.-I., Miura, Y., Li, M.-Y., Revah, O., Selvaraj, S., Birey, F., Meng, X., Thete, M. V., Pavlov, S. D., Andersen, J., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.09.020 · Cited by 59
Self-citationNeuroendocrine Aspects of Tourette Syndrome
Martino, D., Macerollo, A., & Leckman, J. F. (2013) · International review of neurobiology · doi:10.1016/b978-0-12-411546-0.00009-3 · Cited by 59
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Aldaz, C. M., & Hussain, T. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21238922 · Cited by 59
Ma, Y., Liu, S., Gao, J., Chen, C., Zhang, X., Yuan, H., Chen, Z., Yin, X., Sun, C., Mao, Y., et al. (2021) · Developmental Cell · doi:10.1016/j.devcel.2020.12.019 · Cited by 59
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Zuk, J., Yu, X., Sanfilippo, J. S., Figuccio, M. J., Dunstan, J., Carruthers, C., Sideridis, G. D., Turesky, T. K., Gagoski, B. A., Grant, P. E., et al. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.100973 · Cited by 59
Impact of alcohol exposure on neural development and network formation in human cortical organoids
Adams, J. W., Negraes, P. D., Truong, J., Tran, T. H., Szeto, R. A., Guerra, B. S., Herai, R. H., Teodorof‐Diedrich, C., Spector, S. A., Campo, M. D., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01862-7 · Cited by 59
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Zhao, H., & Haddad, G. G. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1351734 · Cited by 60
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Hughes, D. A., Kircher, M., He, Z., Guo, S., Fairbrother, G. L., Moreno, C. S., Khaitovich, P., & Stoneking, M. (2015) · Genome biology · doi:10.1186/s13059-015-0627-z · Cited by 59
Individual differences in developmental plasticity: A role for early androgens?
Giudice, M. D., Barrett, E. S., Belsky, J., Hartman, S., Martel, M. M., Sangenstedt, S., & Kuzawa, C. W. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.02.025 · Cited by 59
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Goyal, M. S., Iannotti, L. L., & Raichle, M. E. (2018) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-082117-051652 · Cited by 59
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Playfoot, C. J., Duc, J., Sheppard, S., Joye, S., Coudray, A., Planet, E., & Trono, D. (2021) · Genome Research · doi:10.1101/gr.275133.120 · Cited by 59
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Mitchell, A., Bharadwaj, R. A., Whittle, C., Krueger, W. H., Mirnics, K., Hurd, Y. L., Rasmussen, T. P., & Akbarian, S. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.07.015 · Cited by 58
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Collado‐Torres, L., Nellore, A., Frazee, A. C., Wilks, C., Love, M. I., Langmead, B., Irizarry, R. A., Leek, J. T., & Jaffe, A. E. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw852 · Cited by 58
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Skene, N., Roy, M. M., & Grant, S. G. N. (2017) · eLife · doi:10.7554/elife.17915 · Cited by 58
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Manoli, D. S., & Tollkühn, J. (2018) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13564 · Cited by 58
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Arnatkevičiūtė, A., Fulcher, B., Bellgrove, M. A., & Fornito, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118570 · Cited by 60
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Bettencourt, C., Ryten, M., Forabosco, P., Schorge, S., Hersheson, J., Hardy, J., & Houlden, H. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.756 · Cited by 57
Sipahi, L., Wildman, D. E., Aiello, A. E., Koenen, K. C., Galea, S., Abbas, A., & Uddin, M. (2014) · Psychological Medicine · doi:10.1017/s0033291714000968 · Cited by 57
Duarte, R. R. R., Troakes, C., Nolan, M., Srivastava, D. P., Murray, R. M., & Bray, N. J. (2016) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32445 · Cited by 57
Drange, O. K., Smeland, O. B., Shadrin, A. A., Finseth, P. I., Witoelar, A., & Frei, O. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00220 · Cited by 57
Genetic mechanisms of regression in autism spectrum disorder
Tammimies, K. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.04.022 · Cited by 57
Next‐generation disease modeling with direct conversion: a new path to old neurons
Traxler, L., Edenhofer, F., & Mertens, J. (2019) · FEBS Letters · doi:10.1002/1873-3468.13678 · Cited by 57
Emerging Methods and Resources for Biological Interrogation of Neuropsychiatric Polygenic Signal
Uffelmann, E., & Posthuma, D. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.05.022 · Cited by 57
Kim, S. S., Truong, B., Jagadeesh, K., Dey, K. K., Shen, A. Z., Raychaudhuri, S., Kellis, M., & Price, A. L. (2024) · Nature Communications · doi:10.1038/s41467-024-44742-0 · Cited by 56
Primiani, C. T., Ryan, V. H., Rao, J. S., Cam, M. C., Ahn, K., Modi, H. R., & Rapoport, S. I. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110972 · Cited by 56
Transcriptome-wide association study identifies new susceptibility genes and pathways for depression
Li, X., Su, X., Liu, J., Li, H., Li, M., Li, W., & Luo, X. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01411-w · Cited by 56
Self-citationJia, X., Zhang, S., Tan, S., Du, B., He, M. L., Qin, H., Chen, J., Duan, X., Luo, J., Chen, F., et al. (2022) · Science Advances · doi:10.1126/sciadv.abo7112 · Cited by 56
Fiksinski, A., Hoftman, G. D., Vorstman, J. A. S., & Bearden, C. E. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01783-5 · Cited by 56
A shifting role of thalamocortical connectivity in the emergence of cortical functional organization
Park, S., Haak, K. V., Oldham, S., Cho, H., Byeon, K., Park, B., Thomson, P., Chen, H., Gao, W., Xu, T., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01679-3 · Cited by 56
Kostović, I., Sedmak, G., Vukšić, M., & Judáš, M. (2014) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12333 · Cited by 56
Self-citationConvergent lines of evidence support CAMKK2 as a schizophrenia susceptibility gene
Luo, X.-J., Mei, L. I., Huang, L., Steinberg, S., Mattheisen, M., Liang, G., Donohoe, G. J., Shi, Y., Chen, C., Yue, W., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.103 · Cited by 56
Self-citationEising, E., Huisman, S. M. H., Mahfouz, A. E., Vijfhuizen, L. S., Anttila, V., Winsvold, B. S., Kurth, T., Ikram, M. A., Freilinger, T. M., Kaprio, J. A., et al. (2016) · Human Genetics · doi:10.1007/s00439-016-1638-x · Cited by 56
The Molecular Basis of Human Brain Evolution
Enard, W. (2016) · Current Biology · doi:10.1016/j.cub.2016.09.030 · Cited by 55
DNA methylation markers in the postnatal developing rat brain
Simmons, R. K., Stringfellow, S. A., Glover, M. E., Wagle, A. A., & Clinton, S. M. (2013) · Brain Research · doi:10.1016/j.brainres.2013.08.005 · Cited by 55
Soong, B., Huang, Y., Tsai, P., Huang, C., Pan, H.-C., Lu, Y., Chien, H.-J., Liu, T.-T., Chang, M.-H., Lin, K., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.01.014 · Cited by 55
Hauberg, M. E., Fullard, J. F., Zhu, L., Cohain, A. T., Giambartolomei, C., Misir, R., Reach, S. M., Johnson, J., Wang, M., Mattheisen, M., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0059-8 · Cited by 55
Vallianatos, C. N., Raines, B., Porter, R. S., Bonefas, K. M., Wu, M. C., Garay, P. M., Collette, K. M., Seo, Y. A., Dou, Y., Keegan, C. E., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-1001-6 · Cited by 55
Rødevand, L. N., Bahrami, S., Frei, O., Chu, Y., Shadrin, A. A., O’Connell, K. S., Smeland, O. B., Elvsåshagen, T., Hindley, G., Djurovic, S., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01527-z · Cited by 55
Mutations in NKX6-2 Cause Progressive Spastic Ataxia and Hypomyelination
Chelban, V., Patel, N., Vandrovcová, J., Zanetti, M. N., Lynch, D. S., Ryten, M., Botía, J. A., Bello, O. D., Tribollet, E., Efthymiou, S., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.05.009 · Cited by 55
Foxp1 regulation of neonatal vocalizations via cortical developmentPreprint
Usui, N., Araujo, D. J., Kulkarni, A., Co, M., Ellegood, J., Harper, M. J., Toriumi, K., Lerch, J. P., & Konopka, G. (2017) · Genes & Development · doi:10.1101/gad.305037.117 · Cited by 55
Bonora, E., Graziano, C., Minopoli, F., Bacchelli, E., Magini, P., Diquigiovanni, C., Lomartire, S., Bianco, F., Vargiolu, M., Parchi, P., et al. (2014) · EMBO Molecular Medicine · doi:10.1002/emmm.201303235 · Cited by 54
the TIC Genetics Collaborative Group, Dietrich, A., Fernandez, T. V., King, R. A., State, M. W., Tischfield, J. A., Hoekstra, P. J., & Heiman, G. A. (2014) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-014-0543-x · Cited by 54
Proteomic Atlas of the Human Brain in Alzheimer’s Disease
McKetney, J., Runde, R. M., Hebert, A. S., Salamat, S. M., Roy, S., & Coon, J. J. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00004 · Cited by 54
Ball, G., Seidlitz, J., O’Muircheartaigh, J., Dimitrova, R., Fenchel, D., Makropoulos, A., Christiaens, D., Schuh, A., Passerat‐Palmbach, J., Hutter, J. M., et al. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3000976 · Cited by 54
Zhu, D., Yuan, T., Gao, J., Xu, Q., Xue, K., Zhu, W., Tang, J., Liu, F., Wang, J., & Yu, C. (2021) · Human Brain Mapping · doi:10.1002/hbm.25362 · Cited by 54
Temporal changes in the gene expression heterogeneity during brain development and aging
Işıldak, U., Somel, M., Thornton, J. M., & Dönertaş, H. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-60998-0 · Cited by 53
Zhou, Y., Dong, F., Lanz, T. A., Reinhart, V., Li, M., Liu, L., Zou, J., Xi, H. S., & Mao, Y. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.166 · Cited by 53
Self-citationAgboola, O. S., Hu, X., Shan, Z., Wu, Y., & Lei, L. (2021) · Stem Cell Research & Therapy · doi:10.1186/s13287-021-02369-8 · Cited by 53
Pintacuda, G., Hsu, Y.-H. H., Tsafou, K., Li, K. W., Martín, J. M., Riseman, J., Biagini, J. C., Ching, J. K. T., Mena, D., Gonzalez‐Lozano, M. A., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2022.100250 · Cited by 53
Pagliaro, A., Finger, R., Zoutendijk, I., Bunschuh, S., Clevers, H. C., Hendriks, D. F. G., & Artegiani, B. (2023) · Nature Communications · doi:10.1038/s41467-023-43141-1 · Cited by 53
Kraushar, M. L., Viljetić, B., Wijeratne, H. R. S., Thompson, K., Jiao, X., Pike, J. W., Medvedeva, V. P., Groszer, M., Kiledjian, M., Hart, R. P., et al. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0601-15.2015 · Cited by 53
Satoh, J.-I., Yamamoto, Y., Asahina, N., Kitano, S., & Kino, Y. (2014) · Disease Markers · doi:10.1155/2014/123165 · Cited by 53
Luo, X., Mattheisen, M., Li, M., Huang, L., Rietschel, M., Børglum, A. D., Als, T. D., van den Oord, E. J. C. G., Åberg, K. A., Mors, O. N., et al. (2015) · Schizophrenia Bulletin · doi:10.1093/schbul/sbv017 · Cited by 54
Self-citationA novel disorder reveals clathrin heavy chain-22 is essential for human pain and touch development
Nahorski, M. S., Al‐Gazali, L., Hertecant, J., Owen, D. J., Borner, G. H. H., Chen, Y., Benn, C., Carvalho, O. P., Shaikh, S. S., Phelan, A., et al. (2015) · Brain · doi:10.1093/brain/awv149 · Cited by 53
Systematic noise degrades gene co-expression signals but can be corrected
Freytag, S., Gagnon-Bartsch, J. A., Speed, T. P., & Bahlo, M. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0745-3 · Cited by 53
Harkin, L. F., Gerrelli, D., Diaz, D. G., Santos, C., Alzu’bi, A., Austin, C. A., & Clowry, G. J. (2015) · Journal of Anatomy · doi:10.1111/joa.12416 · Cited by 53
Neuropeptide Regulation of Social Attachment: The Prairie Vole Model
Tabbaa, M., Paedae, B., Liu, Y., & Wang, Z. (2016) · Comprehensive physiology · doi:10.1002/cphy.c150055 · Cited by 53
Leveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders
Searles, V. B., Wang, B., & State, M. W. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0768-y · Cited by 53
Transcriptomic evidence for immaturity of the prefrontal cortex in patients with schizophrenia
Hagihara, H., Ohira, K., Takao, K., & Miyakawa, T. (2014) · Molecular Brain · doi:10.1186/1756-6606-7-41 · Cited by 52
Principles of GABAergic signaling in developing cortical network dynamics
Kirmse, K., & Zhang, C. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110568 · Cited by 52
Osete, J. R., Akkouh, I. A., Ievglevskyi, O., Vandenberghe, M., de Assis, D. R., Ueland, T., Kondratskaya, E., Holen, B., Szabó, A., Hughes, T., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01944-0 · Cited by 52
Patani, R., Lewis, P. A., Trabzuni, D., Puddifoot, C. A., Wyllie, D. J. A., WALKER, R. E., Smith, C., Hardingham, G. E., Weale, M. E., Hardy, J., et al. (2012) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2012.07825.x · Cited by 52
Kang, S. K., Markowitz, G. J., Kim, S. T., Johnston, M. V., & Kadam, S. D. (2015) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2015.00173 · Cited by 52
Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier
Culibrk, L., Croft, C. A., & Tebbutt, S. J. (2016) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2015.0185 · Cited by 52
Adult Neurogenesis and Gliogenesis: Possible Mechanisms for Neurorestoration
Rusznák, Z., Henskens, W., Schofield, E. C., Kim, W. S., & Fu, Y. (2016) · Experimental Neurobiology · doi:10.5607/en.2016.25.3.103 · Cited by 52
Schizophrenia and neurogenesis: A stem cell approach
Iannitelli, A., Quartini, A., Tirassa, P., & Bersani, G. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.06.010 · Cited by 52
Neural correlates of prenatal stress in young women
Favaro, A., Tenconi, E., Degortes, D., Manara, R., & Santonastaso, P. (2015) · Psychological Medicine · doi:10.1017/s003329171500046x · Cited by 51
Patterns of cilia gene dysregulations in major psychiatric disorders
Alhassen, W., Chen, S., Vawter, M. P., Robbins, B., Nguyen, H. N., Myint, T., Saito, Y., Schulmann, A., Nauli, S. M., Civelli, O., et al. (2021) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2021.110255 · Cited by 51
Lindeman, B., Johansson, Y., Andreassen, M., Husøy, T., Dirven, H. A. A. M., Hofer, T., Knutsen, H. K., Caspersen, I. H., Vejrup, K., Paulsen, R. E., et al. (2021) · Reproductive Toxicology · doi:10.1016/j.reprotox.2021.02.006 · Cited by 51
Metadata
- Authors
- Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., Guennel, T., Shin, Y., Johnson, M. B., Krsnik, Ž., Mayer, S., Fertuzinhos, S., Umlauf, S., Lisgo, S. N., Vortmeyer, A., Weinberger, D. R., Mane, S., Hyde, T. M., Huttner, A., Reimers, M., Kleinman, J. E., & Šestan, N.
- Affiliations
- Yale University (US)
- Universidade do Porto (PT)
- University of Zagreb (HR)
- Virginia Commonwealth University (US)
- Centre for Life (GB)
- National Institutes of Health (US)
- Corresponding author
- Šestan, Nenad
- ORCID
- Kang, Hyo Jung
- Kawasawa, Yuka Imamura
- Cheng, Feng
- Zhu, Ying
- Xu, Xuming
- Li, Mingfeng
- Sousa, André M. M.
- Pletikos, Mihovil
- Sedmak, Goran
- Shin, Yurae
- Johnson, Matthew B.
- Krsnik, Željka
- Mayer, Simone
- Fertuzinhos, Sofia
- Umlauf, Sheila
- Lisgo, Steven N.
- Vortmeyer, Alexander
- Weinberger, Daniel R.
- Mane, Shrikant
- Hyde, Thomas M.
- Huttner, Anita
- Kleinman, Joel E.
- Šestan, Nenad
- Venue
- Nature
- Published
- 2011-10
- Volume
- 478
- Issue
- 7370
- Pages
- 483-489
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3566780
- OpenAlex
- W2022689242
- Cited by
- 2,084
- References
- 53
- Citations by year
- 2026: 115 · 2025: 128 · 2024: 156 · 2023: 146 · 2022: 149 · 2021: 181 · 2020: 175 · 2019: 163 · 2018: 135 · 2017: 133 · 2016: 144 · 2015: 141 · 2014: 126 · 2013: 104 · 2012: 82
- FWCI
- 40.99
- 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)
- RePEc: Research Papers in Economics (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Funders
- Wellcome Trust (GR082557)
- Medical Research Council
- National Institute of Mental Health (RC2MH089929, MH081896, MH089929, U01MH081896)
- National Institute on Drug Abuse (DA-026119, R25DA026119)
- National Institute of Neurological Disorders and Stroke (R01NS054273, U24NS051869, NS 054273)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD000836, R24HD000836)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- human brain transcriptome, spatiotemporal gene expression, brain development, postmortem brain, sex-biased gene expression, exon usage, co-expression network, single nucleotide polymorphisms, gene expression trajectories, prefrontal cortex, neocortex, brain aging
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Brain, Child, Child, Preschool, Exons, Female, Fetus, Humans, Infant, Male, Middle Aged, Quality Control, Sex Characteristics, Time Factors, Gene Expression Regulation, Developmental, Gene Expression Profiling, Quantitative Trait Loci, Gene Regulatory Networks, Young Adult, Transcriptome
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