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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
DFC and CBC were chosen for analyses because both regions have been implicated in DS neuropathology and exhibit diverse transcriptional profiles over development.
“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
NaV1.2 is widely expressed throughout the human central nervous system but not in peripheral tissues.
“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]
The Global transcriptome dynamics section describes gene expression across human brain regions, but the passages in our copy do not address NaV1.2 or its distribution outside the brain. Searches for NaV1.2, SCN2A, and peripheral-tissue expression found no passage supporting the claimed CNS-versus-peripheral distinction. (LLM, conf=0.75)
Experimental — accuracy not yet measuredSCN2A expression begins early in gestation, and channel dysfunction may alter brain development.
“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]
The citation is attached to the claim that SCN2A expression begins early in gestation, not to the subsequent statement about channel dysfunction. The Expression trajectories of neurodevelopment and Spatiotemporal gene expression sections discuss prenatal gene expression, but the passages found by searching for SCN2A and early fetal sodium-channel expression do not identify SCN2A or establish its onset. (LLM, conf=0.73)
Experimental — accuracy not yet measuredDevelopmental stages 5 and 6 represent mid-gestation, when upper layer neurons are generated and neuronal differentiation including axonogenesis and dendritic arborization occurs.
“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]
Genes associated with synaptic functions may be expressed early during intrauterine development (3-6 months gestational age).
“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 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.
“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]
The Allen Brain Institute and BrainSpan have evaluated spatial and temporal transcriptomes.
“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]
Network approaches are particularly useful for relating whole-tissue-level changes to high-resolution experiments.
“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]
The study combined RNA-seq data from eight studies through a uniform processing pipeline, yielding 2188 samples that passed QC, from 1695 unique subjects, including 279 technical replicates.
“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]
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-of-onset.
“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]
The glutamatergic hypothesis postulates that hypofunction of NMDA receptor signaling is a possible mechanism of schizophrenia.
“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]
Recent studies had analysed transcriptional dynamics during human brain development only in a small number of relatively coarse brain regions.
“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]
The high degree of similarity between the two brains is suggestive of a strong underlying common blueprint for the human brain transcriptome and is consistent with other recent studies of human neocortical gene expression.
“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]
Prior studies have examined only a restricted subset of prenatal human brain regions and cortical layers.
“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]
The astroglial population is likely largely non-proliferative and fully differentiated by the end of the first postnatal year.
“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
Nine out of ten genes are differentially expressed or spliced across brain regions and/or time.
“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
At least 86% of protein-coding genes are used at some point during human CNS development.
“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
The two largest modules in Kang et al., 2011 indicate that many transcriptional processes are shared and coordinated across different regions as the brain develops.
“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
Expression trajectories of modules exhibit dynamic patterns across development, consistent with roles in distinct biological processes.
“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
The module enriched for neuronal specification genes is most highly expressed embryonically and early fetally, while the module enriched for synaptic function and ion channel genes rises late fetally and plateaus in early childhood.
“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
The cerebellum is the most transcriptionally distinctive region in the developing brain, followed by thalamus and striatum.
“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
Approaches integrating spatio-temporal transcriptome with gene mutation discoveries have implicated projection neurons in prefrontal and primary motor-somatosensory cortex during mid-fetal development in autism spectrum disorder and frontal cortex during fetal development in schizophrenia.
“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
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.
“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
Regional/areal transcriptional profiles were largely bilaterally symmetrical across the two hemispheres at population-level during fetal, early postnatal development and adulthood.
“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
Recent transcriptome studies have identified substantial regional/areal differences in the developing human neocortex.
“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
The transcriptome of the developing prenatal human neocortex is quite heterogeneous across different cortical areas.
“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
Transcription profiles in the adult neocortex are relatively homogeneous throughout the cortex, although some heterogeneity exists.
“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
RFX and GPR56 expression patterns are correlated, with RFX3 and RFX7 most prominent in human ventrolateral prefrontal cortex, the region affected in perisylvian polymicrogyria.
“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 <i>GPR56</i> Regulates Regional Cerebral Cortical Patterning (2014) · cites this paper as [15]
RNA expression studies across the mammalian brain have shown significant differences in the transcriptome between neuronal cell types, brain regions, developmental stages, and species.
“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]
Existing whole-tissue analyses, even with careful manual dissection, are not sensitive to inter- or intra-cellular variability, and functional genomic information is diluted among different classes of intermixed neurons and high proportion of glial cells.
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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 · see citing works
Bardo, M. T., & Hammer, R. P. (1991) · Neuroscience · doi:10.1016/0306-4522(91)90226-e · Cited by 3,229 · see citing works
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 · see citing works
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 · see citing works
Neuroligins and neurexins link synaptic function to cognitive disease
Südhof, T. C. (2008) · Nature · doi:10.1038/nature07456 · Cited by 1,849 · see citing works
Insel, T. R. (2010) · Nature · doi:10.1038/nature09552 · Cited by 1,783 · see citing works
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 · see citing works
Evolution of the neocortex: a perspective from developmental biology
Rakic, P. (2009) · Nature reviews. Neuroscience · doi:10.1038/nrn2719 · Cited by 1,565 · see citing works
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 · see citing works
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 · see citing works
Hemizygosity at the elastin locus in a developmental disorder, Williams syndrome
Ewart, A. K., Morris, C. A., Atkinson, D., Jin, W., Sternes, K., Spallone, P., Stock, A. D., Leppert, M., & Keating, M. T. (1993) · Nature Genetics · doi:10.1038/ng0993-11 · Cited by 1,138 · see citing works
Population genomics of human gene expression
Stranger, B. E., Nica, A. C., Forrest, M. S., Dimas, A. S., Bird, C., Beazley, C., Ingle, C., Dunning, M., Flicek, P., Koller, D., et al. (2007) · Nature Genetics · doi:10.1038/ng2142 · Cited by 1,132 · see citing works
Alternative Splicing: New Insights from Global Analyses
Blencowe, B. J. (2006) · Cell · doi:10.1016/j.cell.2006.06.023 · Cited by 1,122 · see citing works
Tbr1 regulates differentiation of the preplate and layer 6
Hevner, R. F., Shi, L., Justice, N., Hsueh, Y.-P., Sheng, M., Smiga, S., Bulfone, A., Goffinet, A. M., Campagnoni, A. T., & Rubenstein, J. L. R. (2001) · Neuron · doi:10.1016/s0896-6273(01)00211-2 · Cited by 857 · see citing works
Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain
Gibbs, J. R., van der Brug, M. P., Hernandez, D. G., Traynor, B. J., Nalls, M. A., Lai, S.-L., Arepalli, S., Dillman, A., Rafferty, I. P., Troncoso, J., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000952 · Cited by 769 · see citing works
Patterns of neural stem and progenitor cell division may underlie evolutionary cortical expansion
Kriegstein, A., Noctor, S., & Martínez-Cerdeño, V. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn2008 · Cited by 738 · see citing works
Temporal dynamics and genetic control of transcription in the human prefrontal cortex
Colantuoni, C., Lipska, B. K., Ye, T., Hyde, T. M., Tao, R., Leek, J. T., Colantuoni, E. A., Elkahloun, A. G., Herman, M. M., Weinberger, D. R., et al. (2011) · Nature · doi:10.1038/nature10524 · Cited by 685 · see citing works
Self-citationMurine features of neurogenesis in the human hippocampus across the lifespan from 0 to 100 years
Knoth, R., Singec, I., Ditter, M., Pantazis, G., Capetian, P., Meyer, R. P., Horvat, V., Volk, B., & Kempermann, G. (2010) · PLoS ONE · doi:10.1371/journal.pone.0008809 · Cited by 650 · see citing works
The cerebrospinal fluid provides a proliferative niche for neural progenitor cells
Lehtinen, M. K., Zappaterra, M. W., Chen, X., Yang, Y. J., Hill, A. D., Lun, M., Maynard, T., Gonzalez, D., Kim, S., Ye, P., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.01.023 · Cited by 648 · see citing works
Johnson, M. B., Kawasawa, Y. I., Mason, C. E., Krsnik, Ž., Coppola, G., Bogdanović, D., Geschwind, D. H., Mane, S. M., State, M. W., & Šestan, N. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.027 · Cited by 603 · see citing works
Self-citationAlterations in 5-HT <sub>1B</sub> Receptor Function by p11 in Depression-Like States
Svenningsson, P., Chergui, K., Rachleff, I., Flajolet, M., Zhang, X., Yacoubi, M. E., Vaugeois, J.-M., Nomikos, G. G., & Greengard, P. (2006) · Science · doi:10.1126/science.1117571 · Cited by 572 · see citing works
Fezl Is Required for the Birth and Specification of Corticospinal Motor Neurons
Molyneaux, B. J., Arlotta, P., Hirata, T., Hibi, M., & Macklis, J. D. (2005) · Neuron · doi:10.1016/j.neuron.2005.08.030 · Cited by 481 · see citing works
A survey of genetic human cortical gene expression
Myers, A. J., Gibbs, J. R., Webster, J. A., Rohrer, K., Zhao, A., Marlowe, L., Kaleem, M., Leung, D., Bryden, L., Nath, P., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.16 · Cited by 479 · see citing works
FOXG1 Is Responsible for the Congenital Variant of Rett Syndrome
Ariani, F., Hayek, G., Rondinella, D., Artuso, R., Mencarelli, M. A., Rosseto, A. S., Pollazzon, M., Buoni, S., Spiga, O., Ricciardi, S., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.05.015 · Cited by 432 · see citing works
A critical role for IGF-II in memory consolidation and enhancement
Chen, D. Y., Stern, S. A., García‐Osta, A., Saunier-Rebori, B., Pollonini, G., Bambah-Mukku, D., Blitzer, R. D., & Alberini, C. M. (2011) · Nature · doi:10.1038/nature09667 · Cited by 421 · see citing works
Chen, B., Schaevitz, L. R., & McConnell, S. K. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0508732102 · Cited by 353 · see citing works
Early Asymmetry of Gene Transcription in Embryonic Human Left and Right Cerebral Cortex
Sun, T., Patoine, C., Abu‐Khalil, A., Visvader, J. E., Sum, E. Y. M., Cherry, T. J., Orkin, S. H., Geschwind, D. H., & Walsh, C. A. (2005) · Science · doi:10.1126/science.1110324 · Cited by 352 · see citing works
Molecular approaches to brain asymmetry and handedness
Sun, T., & Walsh, C. A. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1930 · Cited by 339 · see citing works
Genetic Control of Human Brain Transcript Expression in Alzheimer Disease
Webster, J. A., Gibbs, J. R., Clarke, J., Ray, M., Zhang, W., Holmans, P., Rohrer, K., Zhao, A., Marlowe, L., Kaleem, M., et al. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.03.011 · Cited by 304 · see citing works
MicroRNA, mRNA, and protein expression link development and aging in human and macaque brain
Somel, M., Guo, S., Fu, N., Yan, Z., Hu, H. Y., Xu, Y., Yuan, Y., Ning, Z., Hu, Y., Menzel, C., et al. (2010) · Genome Research · doi:10.1101/gr.106849.110 · Cited by 285 · see citing works
Petanjek, Z., Judas, M., Kostovic, I., & Uylings, H. B. M. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm124 · Cited by 273 · see citing works
Kwan, K. Y., Lam, M. M. S., Krsnik, Ž., Kawasawa, Y. I., Lefebvre, V., & Šestan, N. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806791105 · Cited by 271 · see citing works
Self-citationTissue-Specific Genetic Control of Splicing: Implications for the Study of Complex Traits
Heinzen, E. L., Ge, D., Cronin, K. D., Maia, J. M., Shianna, K. V., Gabriel, W. N., Welsh-Bohmer, K. A., Hulette, C. M., Denny, T. N., & Goldstein, D. B. (2008) · PLoS Biology · doi:10.1371/journal.pbio.1000001 · Cited by 269 · see citing works
McKenna, W. L., Betancourt, J., Larkin, K. A., Abrams, B., Guo, C., Rubenstein, J. L. R., & Chen, B. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4131-10.2011 · Cited by 252 · see citing works
Splicing Regulation in Neurologic Disease
Licatalosi, D. D., & Darnell, R. B. (2006) · Neuron · doi:10.1016/j.neuron.2006.09.017 · Cited by 250 · see citing works
Huffaker, S. J., Chen, J., Nicodemus, K. K., Sambataro, F., Yang, F., Mattay, V. S., Lipska, B. K., Hyde, T. M., Song, J., Rujescu, D., et al. (2009) · Nature Medicine · doi:10.1038/nm.1962 · Cited by 249 · see citing works
Self-citationChen, J.-G., Rašin, M.-R., Kwan, K. Y., & Šestan, N. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509032102 · Cited by 246 · see citing works
Self-citationHuman brain evolution: insights from microarrays
Preuss, T. M., Cáceres, M., Oldham, M. C., & Geschwind, D. H. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1469 · Cited by 215 · see citing works
Molecular insights into human brain evolution
Hill, R. S., & Walsh, C. A. (2005) · Nature · doi:10.1038/nature04103 · Cited by 208 · see citing works
Han, W., Kwan, K. Y., Shim, S., Lam, M. M. S., Shin, Y., Xu, X., Zhu, Y., Li, M., & Šestan, N. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016723108 · Cited by 206 · see citing works
Self-citationGender-Specific Gene Expression in Post-Mortem Human Brain: Localization to Sex Chromosomes
Vawter, M. P., Evans, S. J., Choudary, P. V., Tomita, H., Meador-Woodruff, J., Molnar, M., Li, J. Z., López, J. F., Myers, R. M., Cox, D. R., et al. (2003) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300337 · Cited by 204 · see citing works
Genome-wide analyses of human perisylvian cerebral cortical patterning
Abrahams, B. S., Tentler, D., Perederiy, J. V., Oldham, M. C., Coppola, G., & Geschwind, D. H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706128104 · Cited by 198 · see citing works
Rubenstein, J. L. R. (2010) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2010.02307.x · Cited by 170 · see citing works
The genetics of child psychiatric disorders: focus on autism and Tourette syndrome
State, M. W. (2010) · Neuron · doi:10.1016/j.neuron.2010.10.004 · Cited by 162 · see citing works
Kostović, I., & Judáš, M. (2006) · Developmental Medicine & Child Neurology · doi:10.1017/s0012162206000831 · Cited by 150 · see citing works
Deriving Excitatory Neurons of the Neocortex from Pluripotent Stem Cells
Hansen, D. V., Rubenstein, J. L. R., & Kriegstein, A. R. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.006 · Cited by 116 · see citing works
Perroud, N. A., Uher, R., Ng, M., Guipponi, M., Hauser, J., Henigsberg, N., Maier, W., Mors, O. N., Gennarelli, M., Rietschel, M., et al. (2010) · The Pharmacogenomics Journal · doi:10.1038/tpj.2010.70 · Cited by 113 · see citing works
Transcriptome analysis of male–female differences in prefrontal cortical development
Weickert, C. S., Elashoff, M. R., Richards, A., Sinclair, D., Bahn, S., Pääbo, S., Khaitovich, P., & Webster, M. J. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.5 · Cited by 86 · see citing works
Whole-genome association mapping of gene expression in the human prefrontal cortex
Liu, C., Cheng, L., Badner, J. A., Zhang, D., Craig, D. W., Redman, M., & Gershon, E. S. (2010) · Molecular Psychiatry · doi:10.1038/mp.2009.128 · Cited by 63 · see citing works
Prenatal sex differences in the human brain
Reinius, B., & JAZIN, E. E. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.79 · Cited by 63 · see citing works
Investigating gradients of gene expression involved in early human cortical development
Ip, B. K., Wappler, I., Peters, H., Lindsay, S., Clowry, G. J., & Bayatti, N. (2010) · Journal of Anatomy · doi:10.1111/j.1469-7580.2010.01259.x · Cited by 56 · see citing works
Identification and characterization of RTVP1/GLIPR1-like genes, a novel p53 target gene cluster
Ren, C., Ren, C. H., Li, L., Goltsov, A. A., & Thompson, T. C. (2006) · Genomics · doi:10.1016/j.ygeno.2006.03.021 · Cited by 45 · see citing works
Huttenlocher (1997) · doi:10.1002/(sici)1096-9861(19971020)387:2
Flagged first, then by citations
Cited by
Sorted by citations
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083 · see citing works
The contribution of de novo coding mutations to autism spectrum disorder
Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., et al. (2014) · Nature · doi:10.1038/nature13908 · Cited by 2,585 · see citing works
Self-citationIdentification 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-citationZhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295 · see citing works
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321 · see citing works
“To estimate the partial co-expression network, we used the BrainSpan microarray dataset (https://developinghumanbrain.org/; Kang et al., 2011).”
MethodSelf-citation23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470 · see citing works
De novo mutations revealed by whole-exome sequencing are strongly associated with autism
Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084 · see citing works
Self-citationBrain charts for the human lifespan
Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., et al. (2022) · Nature · doi:10.1038/s41586-022-04554-y · Cited by 1,794 · see citing works
Lord, C., Brugha, T. S., Charman, T., Cusack, J., Dumas, G., Frazier, T., Jones, E. J. H., Jones, R. M., Pickles, A., State, M. W., et al. (2020) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0138-4 · Cited by 1,859 · see citing works
Conserved cell types with divergent features in human versus mouse cortex
Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775 · see citing works
Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture
Paşca, A. M., Sloan, S. A., Clarke, L. E., Tian, Y., Makinson, C. D., Huber, N., Kim, C. H., Park, J.-Y., O'Rourke, N. A., Nguyen, K. D., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3415 · Cited by 1,609 · see citing works
The microglial sensome revealed by direct RNA sequencing
Hickman, S. E., Kingery, N. D., Ohsumi, T. K., Borowsky, M. L., Wang, L.-C., Means, T. K., & El Khoury, J. (2013) · Nature Neuroscience · doi:10.1038/nn.3554 · Cited by 1,511 · see citing works
Genomic 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
“(B) Brain developmental expression trajectory displayed for the three groups of genes based on (Kang et al., 2011) The 146 genome-wide significant loci from the cross-disorder meta analysis were clustered into three groups based on predicted disorder-specific associations: (1) no-pleiotopy; (2) pleiotropy = 2; and (3)…”
BackgroundHuman hippocampal neurogenesis drops sharply in children to undetectable levels in adults
Sorrells, S. F., Paredes, M. F., Cebrian-Silla, A., Sandoval, K., Qi, D., Kelley, K. W., James, D., Mayer, S., Chang, J., Auguste, K. I., et al. (2018) · Nature · doi:10.1038/nature25975 · Cited by 1,422 · see citing works
Self-citationTranscriptional 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 meta-analysis of sex differences in human brain structure
Ruigrok, A. N. V., Salimi-Khorshidi, G., Lai, M.-C., Baron-Cohen, S., Lombardo, M. V., Tait, R. J., & Suckling, J. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.12.004 · Cited by 1,192 · see citing works
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247 · see citing works
Self-citationFOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders
Mariani, J., Coppola, G., Zhang, P., Abyzov, A., Provini, L., Tomasini, L., Amenduni, M., Szekely, A., Palejev, D., Wilson, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.034 · Cited by 1,149 · see citing works
Sex/Gender Differences and Autism: Setting the Scene for Future Research
Lai, M.-C., Lombardo, M. V., Auyeung, B., Chakrabarti, B., & Baron-Cohen, S. (2015) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2014.10.003 · Cited by 1,120 · 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
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-citationNeuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957 · see citing works
Willsey, A. J., Sanders, S. J., Li, M., Dong, S., Tebbenkamp, A. T., Muhle, R. A., Reilly, S. K., Lin, L., Fertuzinhos, S., Miller, J. A., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.020 · Cited by 934 · see citing works
Self-citationRare coding variants in ten genes confer substantial risk for schizophrenia
Singh, T., Poterba, T., Curtis, D., Akil, H., Al Eissa, M., Barchas, J. D., Bass, N., Bigdeli, T. B., Breen, G., Bromet, E. J., et al. (2022) · Nature · doi:10.1038/s41586-022-04556-w · Cited by 983 · see citing works
Self-citationNeurogenesis in the striatum of the adult human brain
Ernst, A., Alkass, K., Bernard, S., Salehpour, M., Perl, S., Tisdale, J., Possnert, G., Druid, H., & Frisén, J. (2014) · Cell · doi:10.1016/j.cell.2014.01.044 · Cited by 937 · 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-citationThe Cellular and Molecular Landscapes of the Developing Human Central Nervous System
Silbereis, J. C., Pochareddy, S., Zhu, Y., Li, M., & Sestan, N. (2016) · Neuron · doi:10.1016/j.neuron.2015.12.008 · Cited by 818 · see citing works
Self-citationCell type- and brain region-resolved mouse brain proteome
Sharma, K., Schmitt, S., Bergner, C. G., Tyanova, S., Kannaiyan, N., Manrique-Hoyos, N., Kongi, K., Cantuti, L., Hanisch, U.-K., Philips, M.-A., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4160 · Cited by 871 · see citing works
Common genetic variants influence human subcortical brain structures
Initiative, T. A. D. N., Hibar, D. P., The CHARGE Consortium, EPIGEN, IMAGEN, SYS, Stein, J. L., Renteria, M. E., Arias-Vasquez, A., Desrivières, S., et al. (2015) · Nature · doi:10.1038/nature14101 · Cited by 858 · see citing works
Self-citationPsychiatric 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
Neurodevelopmental model of schizophrenia: update 2012
Rapoport, J. L., Giedd, J. N., & Gogtay, N. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.23 · Cited by 790 · see citing works
Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · see citing works
“…test P value for a difference between these two distributions is reported. e , Approach to training the elastic net model on BrainSpan 49,50 frontal cortex and temporal cortex samples and application of the model to 123 cortical samples in this study. f – h , Results of learned…”
Dang, J., Tiwari, S. K., Lichinchi, G., Qin, Y., Patil, V. S., Eroshkin, A. M., & Rana, T. M. (2016) · Cell Stem Cell · doi:10.1016/j.stem.2016.04.014 · Cited by 731 · see citing works
Prolonged myelination in human neocortical evolution
Miller, D. J., Duka, T., Stimpson, C. D., Schapiro, S. J., Baze, W. B., McArthur, M. J., Fobbs, A. J., Sousa, A. M. M., Šestan, N., Wildman, D. E., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117943109 · Cited by 699 · 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
Canonical genetic signatures of the adult human brain
Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., Jegga, A. G., Aronow, B. J., Lee, C.-K., Bernard, A., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4171 · Cited by 663 · see citing works
Buss, C., Davis, E. P., Shahbaba, B., Pruessner, J. C., Head, K., & Sandman, C. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201295109 · Cited by 652 · see citing works
Sloan, S. A., Darmanis, S., Huber, N., Khan, T. A., Birey, F., Caneda, C., Reimer, R., Quake, S. R., Barres, B. A., & Paşca, S. P. (2017) · Neuron · doi:10.1016/j.neuron.2017.07.035 · Cited by 593 · see citing works
Widespread macromolecular interaction perturbations in human genetic disorders
Sahni, N., Yi, S., Taipale, M., Fuxman Bass, J. I., Coulombe-Huntington, J., Yang, F., Peng, J., Weile, J., Karras, G. I., Wang, Y., et al. (2015) · Cell · doi:10.1016/j.cell.2015.04.013 · Cited by 594 · 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
Paediatric and adult glioblastoma: multiform (epi)genomic culprits emerge
Sturm, D., Bender, S., Jones, D. T. W., Lichter, P., Grill, J., Becher, O., Hawkins, C., Majewski, J., Jones, C., Costello, J. F., et al. (2014) · Nature Reviews Cancer · doi:10.1038/nrc3655 · Cited by 555 · see citing works
Trevino, A. E., Müller, F., Andersen, J., Sundaram, L., Kathiria, A., Shcherbina, A., Farh, K., Chang, H. Y., Pașca, A. M., Kundaje, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.039 · Cited by 478 · see citing works
Modeling human cortical development in vitro using induced pluripotent stem cells
Mariani, J., Simonini, M. V., Palejev, D., Tomasini, L., Coppola, G., Szekely, A. M., Horvath, T. L., & Vaccarino, F. M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1202944109 · Cited by 526 · see citing works
Evolution of the Human Nervous System Function, Structure, and Development
Sousa, A. M. M., Meyer, K. A., Santpere, G., Gulden, F. O., & Sestan, N. (2017) · Cell · doi:10.1016/j.cell.2017.06.036 · Cited by 517 · see citing works
Self-citationReynolds, R. M. (2013) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2012.08.012 · Cited by 497 · see citing works
Akbarian, S., Liu, C., Knowles, J. A., Vaccarino, F. M., Farnham, P. J., Crawford, G. E., Jaffe, A. E., Pinto, D., Dracheva, S., Geschwind, D. H., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4156 · Cited by 451 · see citing works
Self-citationSystems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · see citing works
Elevated fetal steroidogenic activity in autism
Baron-Cohen, S., Auyeung, B., Nørgaard-Pedersen, B., Hougaard, D. M., Abdallah, M. W., Melgaard, L., Cohen, A. S., Chakrabarti, B., Ruta, L., & Lombardo, M. V. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.48 · Cited by 471 · see citing works
Aerobic glycolysis in the human brain is associated with development and neotenous gene expression
Goyal, M. S., Hawrylycz, M., Miller, J. A., Snyder, A. Z., & Raichle, M. E. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2013.11.020 · Cited by 459 · see citing works
“Regions are named according to the BSS (Kang et al., 2011): CBC, cerebellum; MD, thalamus; AMY, amygdala; HIP, hippocampus; ITC, inferior temporal cortex; STR, striatum; V1C, primary visual cortex; STC, superior temporal cortex; A1C, auditory cortex; IPC, inferior parietal cortex; M1C, primary motor cortex; S1C, prima…”
InfluentialSomatic activation of AKT3 causes hemispheric developmental brain malformations
Poduri, A., Evrony, G. D., Cai, X., Elhosary, P. C., Beroukhim, R., Lehtinen, M. K., Hills, L. B., Heinzen, E. L., Hill, A., Hill, R. S., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.010 · Cited by 478 · see citing works
De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia
Xu, B., Ionita-Laza, I., Roos, J. L., Boone, B., Woodrick, S., Sun, Y., Levy, S., Gogos, J. A., & Karayiorgou, M. (2012) · Nature Genetics · doi:10.1038/ng.2446 · Cited by 442 · see citing works
Development and arealization of the cerebral cortex
Cadwell, C. R., Bhaduri, A., Mostajo-Radji, M. A., Keefe, M. G., & Nowakowski, T. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.009 · Cited by 408 · see citing works
The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing
Lein, E., Borm, L. E., & Linnarsson, S. (2017) · Science · doi:10.1126/science.aan6827 · Cited by 383 · see citing works
Rapid and Pervasive Changes in Genome-wide Enhancer Usage during Mammalian Development
Nord, A. S., Blow, M. J., Attanasio, C., Akiyama, J. A., Holt, A., Hosseini, R., Phouanenavong, S., Plajzer-Frick, I., Shoukry, M., Afzal, V., et al. (2013) · Cell · doi:10.1016/j.cell.2013.11.033 · Cited by 375 · see citing works
Cerebral Organoids Recapitulate Epigenomic Signatures of the Human Fetal Brain
Luo, C., Lancaster, M. A., Castanon, R., Nery, J. R., Knoblich, J. A., & Ecker, J. R. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.12.001 · Cited by 370 · 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
Frontotemporal dementia and its subtypes: a genome-wide association study
Ferrari, R., Hernandez, D. G., Nalls, M. A., Rohrer, J. D., Ramasamy, A., Kwok, J. B. J., Dobson-Stone, C., Brooks, W. S., Schofield, P. R., Halliday, G. M., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70065-1 · Cited by 383 · see citing works
Nativio, R., Lan, Y., Donahue, G., Sidoli, S., Berson, A., Srinivasan, A. R., Shcherbakova, O., Amlie-Wolf, A., Nie, J., Cui, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0696-0 · Cited by 380 · see citing works
Cotney, J., Muhle, R. A., Sanders, S. J., Liu, L., Willsey, A. J., Niu, W., Liu, W., Klei, L., Lei, J., Yin, J., et al. (2015) · Nature Communications · doi:10.1038/ncomms7404 · Cited by 350 · see citing works
Self-citationCHD8 haploinsufficiency results in autistic-like phenotypes in mice
Katayama, Y., Nishiyama, M., Shoji, H., Ohkawa, Y., Kawamura, A., Sato, T., Suyama, M., Takumi, T., Miyakawa, T., & Nakayama, K. I. (2016) · Nature · doi:10.1038/nature19357 · Cited by 353 · see citing works
Mechanisms of sex differences in Alzheimer’s disease
Lopez-Lee, C., Torres, E. R. S., Carling, G., & Gan, L. (2024) · Neuron · doi:10.1016/j.neuron.2024.01.024 · Cited by 376 · see citing works
Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder
An, J.-Y., Lin, K., Zhu, L., Werling, D. M., Dong, S., Brand, H., Wang, H. Z., Zhao, X., Schwartz, G. B., Collins, R. L., et al. (2018) · Science · doi:10.1126/science.aat6576 · Cited by 316 · see citing works
DNA methylation signatures in development and aging of the human prefrontal cortex
Numata, S., Ye, T., Hyde, T. M., Guitart-Navarro, X., Tao, R., Wininger, M., Colantuoni, C., Weinberger, D. R., Kleinman, J. E., & Lipska, B. K. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.12.020 · Cited by 364 · see citing works
Self-citationProgress in Understanding and Treating SCN2A-Mediated Disorders
Sanders, S. J., Campbell, A. J., Cottrell, J. R., Moller, R. S., Wagner, F. F., Auldridge, A. L., Bernier, R. A., Catterall, W. A., Chung, W. K., Empfield, J. R., et al. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.03.011 · Cited by 338 · see citing works
“SCN2A expression begins early in gestation [8], and channel dysfunction may alter brain development.”
BackgroundUntangling the brain’s neuroinflammatory and neurodegenerative transcriptional responses
Srinivasan, K., Friedman, B. A., Larson, J. L., Lauffer, B. E., Goldstein, L. D., Appling, L. L., Borneo, J., Poon, C., Ho, T., Cai, F., et al. (2016) · Nature Communications · doi:10.1038/ncomms11295 · Cited by 336 · see citing works
Genome-wide association study reveals two new risk loci for bipolar disorder
Mühleisen, T. W., Leber, M., Schulze, T. G., Strohmaier, J., Degenhardt, F., Treutlein, J., Mattheisen, M., Forstner, A. J., Schumacher, J., Breuer, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms4339 · Cited by 346 · see citing works
Subcortical origins of human and monkey neocortical interneurons
Ma, T., Wang, C., Wang, L., Zhou, X., Tian, M., Zhang, Q., Zhang, Y., Li, J., Liu, Z., Cai, Y., et al. (2013) · Nature Neuroscience · doi:10.1038/nn.3536 · Cited by 322 · see citing works
Gabory, A., Roseboom, T. J., Moore, T., Moore, L. G., & Junien, C. (2013) · Biology of Sex Differences · doi:10.1186/2042-6410-4-5 · Cited by 344 · see citing works
A Synergistic Core for Human Brain Evolution and Cognition
Luppi, A. I., Mediano, P. A. M., Rosas, F. E., Holland, N., Fryer, T. D., O’Brien, J. T., Rowe, J. B., Menon, D. K., Bor, D., & Stamatakis, E. A. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01070-0 · Cited by 314 · see citing works
Gene expression in human brain implicates sexually dimorphic pathways in autism spectrum disorders
Werling, D. M., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Communications · doi:10.1038/ncomms10717 · Cited by 296 · see citing works
Multivariate genome-wide analyses of the well-being spectrum
BIOS consortium, Baselmans, B. M. L., Social Science Genetic Association Consortium, Jansen, R., Ip, H. F., van Dongen, J., Abdellaoui, A., van de Weijer, M. P., Bao, Y., Smart, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0320-8 · Cited by 320 · see citing works
Franjic, D., Skarica, M., Ma, S., Arellano, J. I., Tebbenkamp, A. T. N., Choi, J., Xu, C., Li, Q., Morozov, Y. M., Andrijevic, D., et al. (2022) · Neuron · doi:10.1016/j.neuron.2021.10.036 · Cited by 308 · 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
Onorati, M., Li, Z., Liu, F., Sousa, A. M. M., Nakagawa, N., Li, M., Dell’Anno, M. T., Gulden, F. O., Pochareddy, S., Tebbenkamp, A. T. N., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.08.038 · Cited by 292 · see citing works
Self-citationSingle-cell analysis reveals transcriptional heterogeneity of neural progenitors in human cortex
Johnson, M. B., Wang, P. P., Atabay, K. D., Murphy, E. A., Doan, R. N., Hecht, J. L., & Walsh, C. A. (2015) · Nature Neuroscience · doi:10.1038/nn.3980 · Cited by 288 · see citing works
Self-citationGaiteri, C., Ding, Y., French, B., Tseng, G. C., & Sibille, E. (2014) · Genes, Brain and Behavior · doi:10.1111/gbb.12106 · Cited by 289 · see citing works
Lim, E. T., Raychaudhuri, S., Sanders, S. J., Stevens, C., Sabo, A., MacArthur, D. G., Neale, B. M., Kirby, A., Ruderfer, D. M., Fromer, M., et al. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.029 · Cited by 266 · see citing works
Molecular and cellular reorganization of neural circuits in the human lineage
Sousa, A. M. M., Zhu, Y., Raghanti, M. A., Kitchen, R. R., Onorati, M., Tebbenkamp, A. T. N., Stutz, B., Meyer, K. A., Li, M., Kawasawa, Y. I., et al. (2017) · Science · doi:10.1126/science.aan3456 · Cited by 253 · see citing works
Self-citationGlobal Prefrontal and Fronto-Amygdala Dysconnectivity in Bipolar I Disorder with Psychosis History
Anticevic, A., Brumbaugh, M. S., Winkler, A. M., Lombardo, L. E., Barrett, J., Corlett, P. R., Kober, H., Gruber, J., Repovs, G., Cole, M. W., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.07.031 · Cited by 263 · 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
Temporal Specification and Bilaterality of Human Neocortical Topographic Gene Expression
Pletikos, M., Sousa, A. M. M., Sedmak, G., Meyer, K. A., Zhu, Y., Cheng, F., Li, M., Kawasawa, Y. I., & Šestan, N. (2014) · Neuron · doi:10.1016/j.neuron.2013.11.018 · Cited by 228 · see citing works
Self-citationChd8 mediates cortical neurogenesis via transcriptional regulation of cell cycle and Wnt signaling
Durak, O., Gao, F., Kaeser-Woo, Y. J., Rueda, R., Martorell, A. J., Nott, A., Liu, C. Y., Watson, L. A., & Tsai, L.-H. (2016) · Nature Neuroscience · doi:10.1038/nn.4400 · Cited by 243 · see citing works
Bayés, À., Collins, M. O., Croning, M. D. R., van de Lagemaat, L. N., Choudhary, J. S., & Grant, S. G. N. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046683 · Cited by 216 · see citing works
An epigenetic barrier sets the timing of human neuronal maturation
Ciceri, G., Baggiolini, A., Cho, H. S., Kshirsagar, M., Benito-Kwiecinski, S., Walsh, R. M., Aromolaran, K. A., Gonzalez-Hernandez, A. J., Munguba, H., Koo, S. Y., et al. (2024) · Nature · doi:10.1038/s41586-023-06984-8 · Cited by 240 · see citing works
Olmos-Serrano, J. L., Kang, H. J., Tyler, W. A., Silbereis, J. C., Cheng, F., Zhu, Y., Pletikos, M., Jankovic-Rapan, L., Cramer, N. P., Galdzicki, Z., et al. (2016) · Neuron · doi:10.1016/j.neuron.2016.01.042 · Cited by 239 · see citing works
“We collected 58 paired tissue samples from 15 euploid control and 15 DS brains ranging in age from 14 post conception weeks (pcw) to 42 years old (Table S2), and we then allocated them into groups based on a previously described timeline that divides human brain development and adulthood into 15 periods (Kang et al.,…”
InfluentialSelf-citationBae, B.-I., Tietjen, I., Atabay, K. D., Evrony, G. D., Johnson, M. B., Asare, E., Wang, P. P., Murayama, A. Y., Im, K., Lisgo, S. N., et al. (2014) · Science · doi:10.1126/science.1244392 · Cited by 229 · see citing works
Self-citationThe road to precision psychiatry: translating genetics into disease mechanisms
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4409 · Cited by 223 · 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
Progress toward treatments for synaptic defects in autism
Delorme, R., Ey, E., Toro, R., Leboyer, M., Gillberg, C., & Bourgeron, T. (2013) · Nature Medicine · doi:10.1038/nm.3193 · Cited by 218 · see citing works
A 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
Transcriptional Architecture of the Primate Neocortex
Bernard, A., Lubbers, L. S., Tanis, K. Q., Luo, R., Podtelezhnikov, A. A., Finney, E. M., McWhorter, M. M. E., Serikawa, K., Lemon, T., Morgan, R., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.002 · Cited by 224 · see citing works
Sandman, C. A., Buss, C., Head, K., & Davis, E. P. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.06.025 · Cited by 219 · see citing works
Groeneweg, S., van Geest, F. S., Peeters, R. P., Heuer, H., & Visser, W. E. (2020) · Endocrine Reviews · doi:10.1210/endrev/bnz008 · Cited by 216 · see citing works
Genotype to phenotype relationships in autism spectrum disorders
Chang, J., Gilman, S. R., Chiang, A. H., Sanders, S. J., & Vitkup, D. (2015) · Nature Neuroscience · doi:10.1038/nn.3907 · Cited by 197 · see citing works
Identification of differentially expressed microRNAs across the developing human brain
Ziats, M. N., & Rennert, O. M. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.93 · Cited by 214 · see citing works
Brain adaptation and alternative developmental trajectories
Johnson, M. H., Jones, E. J. H., & Gliga, T. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000073 · Cited by 213 · see citing works
Self-citationAtlas of the aging mouse brain reveals white matter as vulnerable foci
Hahn, O., Foltz, A. G., Atkins, M., Kedir, B., Moran-Losada, P., Guldner, I. H., Munson, C., Kern, F., Pálovics, R., Lu, N., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.027 · Cited by 213 · see citing works
Provençal, N., Arloth, J., Cattaneo, A., Anacker, C., Cattane, N., Wiechmann, T., Röh, S., Ködel, M., Klengel, T., Czamara, D., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820842116 · Cited by 209 · see citing works
Rethinking schizophrenia in the context of normal neurodevelopment
Catts, V. S., Fung, S. J., Long, L. E., Joshi, D., Vercammen, A., Allen, K. M., Fillman, S. G., Rothmond, D. A., Sinclair, D., Tiwari, Y., et al. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00060 · Cited by 206 · see citing works
- 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
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review