51
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Dong P, Song L, Bendl J, Misir R, Shao Z, Edelstien J, Davis DA, Haroutunian V, Scott WK, Acker S, Lawless N, Hoffman GE, Fullard JF, Roussos P. A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping. Nat Commun 2024; 15:10113. [PMID: 39578476 PMCID: PMC11584674 DOI: 10.1038/s41467-024-54448-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 11/08/2024] [Indexed: 11/24/2024] Open
Abstract
Brain region- and cell-specific transcriptomic and epigenomic features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression profiles in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions were strongly enriched for neuropsychiatric disease risk variants. Moreover, we built enhancer-promoter interactions at promoter-isoform resolution across different brain regions and highlighted the contribution of brain region-specific and promoter-isoform-specific regulation to neuropsychiatric disorders. Including promoter-isoform resolution uncovers additional distal elements implicated in the heritability of diseases, thereby increasing the power to fine-map risk genes. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and underscore the importance of considering isoform information in gene regulation.
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Affiliation(s)
- Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Liting Song
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth Misir
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zhiping Shao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jonathan Edelstien
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David A Davis
- Brain Endowment Bank, Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
| | - William K Scott
- Brain Endowment Bank, Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
- John P. Hussman Institute for Human Genomics and Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Susanne Acker
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany
| | - Nathan Lawless
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA.
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA.
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52
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Russo ML, Sousa AMM, Bhattacharyya A. Consequences of trisomy 21 for brain development in Down syndrome. Nat Rev Neurosci 2024; 25:740-755. [PMID: 39379691 PMCID: PMC11834940 DOI: 10.1038/s41583-024-00866-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2024] [Indexed: 10/10/2024]
Abstract
The appearance of cognitive deficits and altered brain morphology in newborns with Down syndrome (DS) suggests that these features are driven by disruptions at the earliest stages of brain development. Despite its high prevalence and extensively characterized cognitive phenotypes, relatively little is known about the cellular and molecular mechanisms that drive the changes seen in DS. Recent technical advances, such as single-cell omics and the development of induced pluripotent stem cell (iPSC) models of DS, now enable in-depth analyses of the biochemical and molecular drivers of altered brain development in DS. Here, we review the current state of knowledge on brain development in DS, focusing primarily on data from human post-mortem brain tissue. We explore the biological mechanisms that have been proposed to lead to intellectual disability in DS, assess the extent to which data from studies using iPSC models supports these hypotheses, and identify current gaps in the field.
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Affiliation(s)
- Matthew L Russo
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - André M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Anita Bhattacharyya
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
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53
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Okuda T, Kimoto S, Kawabata R, Bian Y, Tsubomoto M, Okamura K, Enwright JF, Kikuchi M, Lewis DA, Hashimoto T. Alterations in inhibitory neuron subtype-selective transcripts in the prefrontal cortex: comparisons across schizophrenia and mood disorders. Psychol Med 2024; 54:1-10. [PMID: 39478366 PMCID: PMC11578916 DOI: 10.1017/s0033291724002344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 07/19/2024] [Indexed: 11/24/2024]
Abstract
BACKGROUND In schizophrenia (SZ), impairments in cognitive functions, such as working memory, have been associated with alterations in certain types of inhibitory neurons that utilize the neurotransmitter γ-aminobutyric acid (GABA) in the dorsolateral prefrontal cortex (DLPFC). For example, GABA neurons that express parvalbumin (PV) or somatostatin (SST) have more prominent gene expression alterations than those that express vasoactive intestinal peptide (VIP). In bipolar disorder (BD) and major depression (MD), which exhibit similar, but less severe, cognitive impairments than SZ, alterations of transcript levels in GABA neurons have also been reported. However, the extent to which GABA neuron subtype-selective transcripts in the DLPFC are affected, and the relative magnitudes of the diagnosis-associated effects, have not been directly compared across SZ, BD, and MD in the same study. METHODS We used quantitative polymerase chain reaction to examine levels of GABA neuron subtype-selective transcripts (PV, potassium voltage-gated channel modifier subfamily-S member-3, SST, VIP, and calretinin mRNAs), as well as the pan-GABA neuron marker 67 kDa glutamate decarboxylase mRNA, in DLPFC total gray matter of 160 individuals, including those with SZ, BD, or MD and unaffected comparison (UC) individuals. RESULTS Relative to UC individuals, individuals with SZ exhibited large deficits in levels of all transcripts except for calretinin mRNA, whereas individuals with BD or MD showed a marked deficit only for PV or SST mRNAs, respectively. CONCLUSIONS These findings suggest that broader and more severe alterations in DLPFC GABA neurons might contribute to the greater cognitive impairments in SZ relative to BD and MD.
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Affiliation(s)
- Takeshi Okuda
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Sohei Kimoto
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japan
- Department of Neuropsychiatry, Wakayama Medical University School of Medicine, Wakayama, 641-8509, Japan
| | - Rika Kawabata
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Yufan Bian
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Makoto Tsubomoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Kazuya Okamura
- Department of Neuropsychiatry, Wakayama Medical University School of Medicine, Wakayama, 641-8509, Japan
| | - John F. Enwright
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Mitsuru Kikuchi
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
- Research Center for Child Development, Kanazawa University, Kanazawa 920-8640, Japan
| | - David A. Lewis
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Takanori Hashimoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Psychiatry, National Hospital Organization Hokuriku Hospital, Nanto, 939-1893, Japan
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54
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Lancaster MA. Unraveling mechanisms of human brain evolution. Cell 2024; 187:5838-5857. [PMID: 39423803 PMCID: PMC7617105 DOI: 10.1016/j.cell.2024.08.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 06/19/2024] [Accepted: 08/28/2024] [Indexed: 10/21/2024]
Abstract
Evolutionary changes in human brain structure and function have enabled our specialized cognitive abilities. How these changes have come about genetically and functionally has remained an open question. However, new methods are providing a wealth of information about the genetic, epigenetic, and transcriptomic differences that set the human brain apart. Combined with in vitro models that allow access to developing brain tissue and the cells of our closest living relatives, the puzzle pieces are now coming together to yield a much more complete picture of what is actually unique about the human brain. The challenge now will be linking these observations and making the jump from correlation to causation. However, elegant genetic manipulations are now possible and, when combined with model systems such as organoids, will uncover a mechanistic understanding of how evolutionary changes at the genetic level have led to key differences in development and function that enable human cognition.
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Affiliation(s)
- Madeline A Lancaster
- MRC Laboratory of Molecular Biology, Cambridge, UK; Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
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55
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Caglayan E, Konopka G. Evolutionary neurogenomics at single-cell resolution. Curr Opin Genet Dev 2024; 88:102239. [PMID: 39094380 DOI: 10.1016/j.gde.2024.102239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/20/2024] [Accepted: 07/22/2024] [Indexed: 08/04/2024]
Abstract
The human brain is composed of increasingly recognized heterogeneous cell types. Applying single-cell genomics to brain tissue can elucidate relative cell type proportions as well as differential gene expression and regulation among humans and other species. Here, we review recent studies that utilized high-throughput genomics approaches to compare brains among species at single-cell resolution. These studies identified genomic elements that are similar among species as well as evolutionary novelties on the human lineage. We focus on those human-relevant innovations and discuss the biological implications of these modifications. Finally, we discuss areas of comparative single-cell genomics that remain unexplored either due to needed technological advances or due to biological availability at the brain region or species level.
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Affiliation(s)
- Emre Caglayan
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Genevieve Konopka
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.
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56
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Doll HM, Risgaard RD, Thurston H, Chen RJ, Sousa AM. Evolutionary innovations in the primate dopaminergic system. Curr Opin Genet Dev 2024; 88:102236. [PMID: 39153332 PMCID: PMC11384322 DOI: 10.1016/j.gde.2024.102236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 07/12/2024] [Indexed: 08/19/2024]
Abstract
The human brain has evolved unique capabilities compared to other vertebrates. The mechanistic basis of these derived traits remains a fundamental question in biology due to its relevance to the origin of our cognitive abilities and behavioral repertoire, as well as to human-specific aspects of neuropsychiatric and neurodegenerative diseases. Comparisons of the human brain to those of nonhuman primates and other mammals have revealed that differences in the neuromodulatory systems, especially in the dopaminergic system, may govern some of these behavioral and cognitive alterations, including increased vulnerability to certain brain disorders. In this review, we highlight and discuss recent findings of human- and primate-specific alterations of the dopaminergic system, focusing on differences in anatomy, circuitry, and molecular properties.
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Affiliation(s)
- Hannah M Doll
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan D Risgaard
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Hailey Thurston
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Rachel J Chen
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - André Mm Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA.
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57
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Uribe-Salazar JM, Kaya G, Weyenberg K, Radke B, Hino K, Soto DC, Shiu JL, Zhang W, Ingamells C, Haghani NK, Xu E, Rosas J, Simó S, Miesfeld J, Glaser T, Baraban SC, Jao LE, Dennis MY. Zebrafish models of human-duplicated SRGAP2 reveal novel functions in microglia and visual system development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.11.612570. [PMID: 39314374 PMCID: PMC11418993 DOI: 10.1101/2024.09.11.612570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
The expansion of the human SRGAP2 family, resulting in a human-specific paralog SRGAP2C, likely contributed to altered evolutionary brain features. The introduction of SRGAP2C in mouse models is associated with changes in cortical neuronal migration, axon guidance, synaptogenesis, and sensory-task performance. Truncated SRGAP2C heterodimerizes with the full-length ancestral gene product SRGAP2A and antagonizes its functions. However, the significance of SRGAP2 duplication beyond neocortex development has not been elucidated due to the embryonic lethality of complete Srgap2 knockout in mice. Using zebrafish, we show that srgap2 knockout results in viable offspring and that these larvae phenocopy "humanized" SRGAP2C larvae, including altered morphometric features (i.e., reduced body length and inter-eye distance) and differential expression of synapse-, axonogenesis-, and vision-related genes. Through single-cell transcriptome analysis, we demonstrate a skewed balance of excitatory and inhibitory neurons that likely contribute to increased susceptibility to seizures displayed by Srgap2 mutant larvae, a phenotype resembling SRGAP2 loss-of-function in a child with early infantile epileptic encephalopathy. Single-cell data also shows strong endogenous expression of srgap2 in microglia with mutants exhibiting altered membrane dynamics and likely delayed maturation of microglial cells. Microglia cells expressing srgap2 were also detected in the developing eye together with altered expression of genes related to axonogenesis in mutant retinal cells. Consistent with the perturbed gene expression in the retina, we found that SRGAP2 mutant larvae exhibited increased sensitivity to broad and fine visual cues. Finally, comparing the transcriptomes of relevant cell types between human (+SRGAP2C) and non-human primates (-SRGAP2C) revealed significant overlaps of gene alterations with mutant cells in our zebrafish models; this suggests that SRGAP2C plays a similar role altering microglia and the visual system in modern humans. Together, our functional characterization of conserved ortholog Srgap2 and human SRGAP2C in zebrafish uncovered novel gene functions and highlights the strength of cross-species analysis in understanding the development of human-specific features.
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Affiliation(s)
- José M. Uribe-Salazar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Gulhan Kaya
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - KaeChandra Weyenberg
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Brittany Radke
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Keiko Hino
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Daniela C. Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Jia-Lin Shiu
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Wenzhu Zhang
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Cole Ingamells
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Nicholas K. Haghani
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Emily Xu
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
| | - Joseph Rosas
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Sergi Simó
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Joel Miesfeld
- Department of Ophthalmology and Visual Sciences, Medical College of Wisconsin, WI, USA
| | - Tom Glaser
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Scott C. Baraban
- Department of Neurological Surgery and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Li-En Jao
- Department of Cell Biology and Human Anatomy, University of California, Davis, CA, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
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Bian Y, Kawabata R, Enwright JF, Tsubomoto M, Okuda T, Kamikawa K, Kimoto S, Kikuchi M, Lewis DA, Hashimoto T. Expression of activity-regulated transcripts in pyramidal neurons across the cortical visuospatial working memory network in unaffected comparison individuals and individuals with schizophrenia. Psychiatry Res 2024; 339:116084. [PMID: 39033685 DOI: 10.1016/j.psychres.2024.116084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 07/23/2024]
Abstract
Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by multiple cortical regions including the primary (V1) and association (V2) visual, posterior parietal (PPC) and dorsolateral prefrontal (DLPFC) cortices. In these regions, parvalbumin (PV) or somatostatin (SST) GABA neurons are altered in SZ as reflected in lower levels of activity-regulated transcripts. As PV and SST neurons receive excitatory inputs from neighboring pyramidal neurons, we hypothesized that levels of activity-regulated transcripts are also lower in pyramidal neurons in these regions. Thus, we quantified levels of four activity-regulated, pyramidal neuron-selective transcripts, namely adenylate cyclase-activating polypeptide-1 (ADCYAP1), brain-derived neurotrophic factor (BDNF), neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs, in V1, V2, PPC and DLPFC from unaffected comparison and SZ individuals. In SZ, BDNF and NPTX2 mRNA levels were lower across all four regions, whereas ADCYAP1 and NRN1 mRNA levels were lower in V1 and V2. The regional pattern of deficits in BDNF and NPTX2 mRNAs was similar to that in transcripts in PV and SST neurons in SZ. These findings suggest that lower activity of pyramidal neurons expressing BDNF and/or NPTX2 mRNAs might contribute to alterations in PV and SST neurons across the vsWM network in SZ.
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Affiliation(s)
- Yufan Bian
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Rika Kawabata
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - John F Enwright
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Makoto Tsubomoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Takeshi Okuda
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Kohei Kamikawa
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japan
| | - Sohei Kimoto
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japan; Department of Neuropsychiatry, Wakayama Medical University School of Medicine, Wakayama, 641-8509, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan; Research Center for Child Development, Kanazawa University, Kanazawa 920-8640, Japan
| | - David A Lewis
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | - Takanori Hashimoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; National Hospital Organization Hokuriku Hospital, Nanto, 939-1893, Japan.
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Ludington SC, McKinney JE, Butler JM, Goolsby BC, Callan AA, Gaines-Richardson M, O’Connell LA. Activity of forkhead box P2-positive neurons is associated with tadpole begging behaviour. Biol Lett 2024; 20:20240395. [PMID: 39317327 PMCID: PMC11421926 DOI: 10.1098/rsbl.2024.0395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 08/30/2024] [Accepted: 09/02/2024] [Indexed: 09/26/2024] Open
Abstract
Motor function is a critical aspect of social behaviour in a wide range of taxa. The transcription factor forkhead box P2 (FoxP2) is well studied in the context of vocal communication in humans, mice and songbirds, but its role in regulating social behaviour in other vertebrate taxa is unclear. We examined the distribution and activity of FoxP2-positive neurons in tadpoles of the mimic poison frog (Ranitomeya imitator). In this species, tadpoles are reared in isolated plant nurseries and are aggressive to other tadpoles. Mothers provide unfertilized egg meals to tadpoles that perform a begging display by vigorously vibrating back and forth. We found that FoxP2 is widely distributed in the tadpole brain and parallels the brain distribution in mammals, birds and fishes. We then tested the hypothesis that FoxP2-positive neurons would have differential activity levels in begging or aggression contexts compared to non-social controls. We found that FoxP2-positive neurons showed increased activation in the striatum and cerebellum during begging and in the nucleus accumbens during aggression. Overall, these findings lay a foundation for testing the hypothesis that FoxP2 has a generalizable role in social behaviour beyond vocal communication across terrestrial vertebrates.
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Affiliation(s)
| | | | - Julie M. Butler
- Department of Biology, Stanford University, Stanford, CA94305, USA
| | | | - Ashlyn A. Callan
- Department of Biology, Stanford University, Stanford, CA94305, USA
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Dong J, Zhu XN, Zeng PM, Cao DD, Yang Y, Hu J, Luo ZG. A hominoid-specific signaling axis regulating the tempo of synaptic maturation. Cell Rep 2024; 43:114548. [PMID: 39052482 DOI: 10.1016/j.celrep.2024.114548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/15/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
Human cortical neurons (hCNs) exhibit high dendritic complexity and synaptic density, and the maturation process is greatly protracted. However, the molecular mechanism governing these specific features remains unclear. Here, we report that the hominoid-specific gene TBC1D3 promotes dendritic arborization and protracts the pace of synaptogenesis. Ablation of TBC1D3 in induced hCNs causes reduction of dendritic growth and precocious synaptic maturation. Forced expression of TBC1D3 in the mouse cortex protracts synaptic maturation while increasing dendritic growth. Mechanistically, TBC1D3 functions via interaction with MICAL1, a monooxygenase that mediates oxidation of actin filament. At the early stage of differentiation, the TBC1D3/MICAL1 interaction in the cytosol promotes dendritic growth via F-actin oxidation and enhanced actin dynamics. At late stages, TBC1D3 escorts MICAL1 into the nucleus and downregulates the expression of genes related with synaptic maturation through interaction with the chromatin remodeling factor ATRX. Thus, this study delineates the molecular mechanisms underlying human neuron development.
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Affiliation(s)
- Jian Dong
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Xiao-Na Zhu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Peng-Ming Zeng
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Dong-Dong Cao
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yang Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Ji Hu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Zhen-Ge Luo
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China.
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Hanson KL, Greiner DM, Schumann CM, Semendeferi K. Inhibitory Systems in Brain Evolution: Pathways of Vulnerability in Neurodevelopmental Disorders. BRAIN, BEHAVIOR AND EVOLUTION 2024; 100:29-48. [PMID: 39137740 PMCID: PMC11822052 DOI: 10.1159/000540865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 08/08/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND The evolution of the primate brain has been characterized by the reorganization of key structures and circuits underlying derived specializations in sensory systems, as well as social behavior and cognition. Among these, expansion and elaboration of the prefrontal cortex has been accompanied by alterations to the connectivity and organization of subcortical structures, including the striatum and amygdala, underlying advanced aspects of executive function, inhibitory behavioral control, and socioemotional cognition seen in our lineages. At the cellular level, the primate brain has further seen an increase in the diversity and number of inhibitory GABAergic interneurons. A prevailing hypothesis holds that disruptions in the balance of excitatory to inhibitory activity in the brain underlies the pathophysiology of many neurodevelopmental and psychiatric disorders. SUMMARY This review highlights the evolution of inhibitory brain systems and circuits and suggests that recent evolutionary modifications to GABAergic circuitry may provide the substrate for vulnerability to aberrant neurodevelopment. We further discuss how modifications to primate and human social organization and life history may shape brain development in ways that contribute to neurodivergence and the origins of neurodevelopmental disorders. KEY MESSAGES Many brain systems have seen functional reorganization in the mammalian, primate, and human brain. Alterations to inhibitory circuitry in frontostriatal and frontoamygdalar systems support changes in social behavior and cognition. Increased complexity of inhibitory systems may underlie vulnerabilities to neurodevelopmental and psychiatric disorders, including autism and schizophrenia. Changes observed in Williams syndrome may further elucidate the mechanisms by which alterations in inhibitory systems lead to changes in behavior and cognition. Developmental processes, including altered neuroimmune function and age-related vulnerability of inhibitory cells and synapses, may lead to worsening symptomatology in neurodevelopmental and psychiatric disorders. BACKGROUND The evolution of the primate brain has been characterized by the reorganization of key structures and circuits underlying derived specializations in sensory systems, as well as social behavior and cognition. Among these, expansion and elaboration of the prefrontal cortex has been accompanied by alterations to the connectivity and organization of subcortical structures, including the striatum and amygdala, underlying advanced aspects of executive function, inhibitory behavioral control, and socioemotional cognition seen in our lineages. At the cellular level, the primate brain has further seen an increase in the diversity and number of inhibitory GABAergic interneurons. A prevailing hypothesis holds that disruptions in the balance of excitatory to inhibitory activity in the brain underlies the pathophysiology of many neurodevelopmental and psychiatric disorders. SUMMARY This review highlights the evolution of inhibitory brain systems and circuits and suggests that recent evolutionary modifications to GABAergic circuitry may provide the substrate for vulnerability to aberrant neurodevelopment. We further discuss how modifications to primate and human social organization and life history may shape brain development in ways that contribute to neurodivergence and the origins of neurodevelopmental disorders. KEY MESSAGES Many brain systems have seen functional reorganization in the mammalian, primate, and human brain. Alterations to inhibitory circuitry in frontostriatal and frontoamygdalar systems support changes in social behavior and cognition. Increased complexity of inhibitory systems may underlie vulnerabilities to neurodevelopmental and psychiatric disorders, including autism and schizophrenia. Changes observed in Williams syndrome may further elucidate the mechanisms by which alterations in inhibitory systems lead to changes in behavior and cognition. Developmental processes, including altered neuroimmune function and age-related vulnerability of inhibitory cells and synapses, may lead to worsening symptomatology in neurodevelopmental and psychiatric disorders.
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Affiliation(s)
- Kari L. Hanson
- Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, Sacramento, CA, USA
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, USA
| | - Demi M.Z. Greiner
- Department of Anthropology, University of California San Diego, La Jolla, CA, USA
| | - Cynthia M. Schumann
- Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, Sacramento, CA, USA
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, USA
| | - Katerina Semendeferi
- Department of Anthropology, University of California San Diego, La Jolla, CA, USA
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Zhang B, Zhang S, Zhang S. Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign. Nat Commun 2024; 15:6302. [PMID: 39080277 PMCID: PMC11289418 DOI: 10.1038/s41467-024-50608-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 07/10/2024] [Indexed: 08/02/2024] Open
Abstract
The increasing utilization of mouse models in human neuroscience research places higher demands on computational methods to translate findings from the mouse brain to the human one. In this study, we develop BrainAlign, a self-supervised learning approach, for the whole brain alignment of spatial transcriptomics (ST) between humans and mice. BrainAlign encodes spots and genes simultaneously in two separated shared embedding spaces by a heterogeneous graph neural network. We demonstrate that BrainAlign could integrate cross-species spots into the embedding space and reveal the conserved brain regions supported by ST information, which facilitates the detection of homologous regions between humans and mice. Genomic analysis further presents gene expression connections between humans and mice and reveals similar expression patterns for marker genes. Moreover, BrainAlign can accurately map spatially similar homologous regions or clusters onto a unified spatial structural domain while preserving their relative positions.
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Affiliation(s)
- Biao Zhang
- School of Mathematical Sciences, Fudan University, Shanghai, China
| | - Shuqin Zhang
- School of Mathematical Sciences, Fudan University, Shanghai, China.
- Key Laboratory of Mathematics for Nonlinear Science, Fudan University, Ministry of Education, Shanghai, China.
- Shanghai Key Laboratory for Contemporary Applied Mathematics, Fudan University, Shanghai, China.
| | - Shihua Zhang
- NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China.
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Corrigan EK, DeBerardine M, Poddar A, Turrero García M, Schmitz MT, Harwell CC, Paredes MF, Krienen FM, Pollen AA. Conservation, alteration, and redistribution of mammalian striatal interneurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.29.605664. [PMID: 39131311 PMCID: PMC11312536 DOI: 10.1101/2024.07.29.605664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Mammalian brains vary in size, structure, and function, but the extent to which evolutionarily novel cell types contribute to this variation remains unresolved1-4. Recent studies suggest there is a primate-specific population of striatal inhibitory interneurons, the TAC3 interneurons5. However, there has not yet been a detailed analysis of the spatial and phylogenetic distribution of this population. Here, we profile single cell gene expression in the developing pig (an ungulate) and ferret (a carnivore), representing 94 million years divergence from primates, and assign newborn inhibitory neurons to initial classes first specified during development6. We find that the initial class of TAC3 interneurons represents an ancestral striatal population that is also deployed towards the cortex in pig and ferret. In adult mouse, we uncover a rare population expressing Tac2, the ortholog of TAC3, in ventromedial striatum, prompting a reexamination of developing mouse striatal interneuron initial classes by targeted enrichment of their precursors. We conclude that the TAC3 interneuron initial class is conserved across Boreoeutherian mammals, with the mouse population representing Th striatal interneurons, a subset of which expresses Tac2. This study suggests that initial classes of telencephalic inhibitory neurons are largely conserved and that during evolution, neuronal types in the mammalian brain change through redistribution and fate refinement, rather than by derivation of novel precursors early in development.
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Affiliation(s)
- Emily K. Corrigan
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | | | - Aunoy Poddar
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Miguel Turrero García
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | | | - Corey C. Harwell
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub San Francisco, San Francisco, CA
| | - Mercedes F. Paredes
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Fenna M. Krienen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Alex A. Pollen
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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Zhang Y, Lu H, Ren X, Zhang J, Wang Y, Zhang C, Zhao X. Immediate and long-term brain activation of acupuncture on ischemic stroke patients: an ALE meta-analysis of fMRI studies. Front Neurosci 2024; 18:1392002. [PMID: 39099634 PMCID: PMC11294246 DOI: 10.3389/fnins.2024.1392002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/11/2024] [Indexed: 08/06/2024] Open
Abstract
Background Acupuncture, as an alternative and complementary therapy recommended by the World Health Organization for stroke treatment, holds potential in ameliorating neurofunctional deficits induced by ischemic stroke (IS). Understanding the immediate and long-term effects of acupuncture and their interrelation would contribute to a better comprehension of the mechanisms underlying acupuncture efficacy. Methods Activation likelihood estimation (ALE) meta-analysis was used to analyze the brain activation patterns reported in 21 relevant functional neuroimaging studies. Among these studies, 12 focused on the immediate brain activation and 9 on the long-term activation. Single dataset analysis were employed to identify both immediate and long-term brain activation of acupuncture treatment in IS patients, while contrast and conjunction analysis were utilized to explore distinctions and connections between the two. Results According to the ALE analysis, immediately after acupuncture treatment, IS patients exhibited an enhanced cluster centered around the right precuneus (PCUN) and a reduced cluster centered on the left middle frontal gyrus (MFG). After long-term acupuncture treatment, IS patients showed an enhanced cluster in the left PCUN, along with two reduced clusters in the right insula (INS) and hippocampus (HIP), respectively. Additionally, in comparison to long-term acupuncture treatment, the right angular gyrus (ANG) demonstrated higher ALE scores immediately after acupuncture, whereas long-term acupuncture resulted in higher scores in the left superior parietal gyrus (SPG). The intersecting cluster activated by both of them was located in the left cuneus (CUN). Conclusion The findings provide initial insights into both the immediate and long-term brain activation patterns of acupuncture treatment for IS, as well as the intricate interplay between them. Both immediate and long-term acupuncture treatments showed distinct patterns of brain activation, with the left CUN emerging as a crucial regulatory region in their association. Systematic Review Registration https://www.crd.york.ac.uk/prospero/, CRD42023480834.
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Affiliation(s)
- Yuan Zhang
- Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Graduate College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Hai Lu
- Department of Traditional Chinese Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xuesong Ren
- Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Junfeng Zhang
- Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Graduate College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Yu Wang
- Department of Rehabilitation, Second Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Chunhong Zhang
- Department of Acupuncture and Moxibustion, Baoan Pure Traditional Chinese Medicine Treatment Hospital, Shenzhen, China
| | - Xiaofeng Zhao
- Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
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Chen J, Chen Z, Zhang Y, Fan X, Zhang C, Zhu J, Song C, Zhang S, Zhang D, Tang L, Li B, Yang W, Hu Q. Effective alleviation of depressive and anxious symptoms and sleep disorders in benzodiazepine-dependent patients through repetitive transcranial magnetic stimulation. Addict Biol 2024; 29:e13425. [PMID: 39051484 PMCID: PMC11270051 DOI: 10.1111/adb.13425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 03/15/2024] [Accepted: 06/13/2024] [Indexed: 07/27/2024]
Abstract
Benzodiazepine (BZD) dependence poses a significant challenge in mental health, prompting the exploration of treatments like repetitive transcranial magnetic stimulation (rTMS). This research aims to assess the impact of rTMS on alleviating symptoms of BZD dependence. A randomized control trial was employed to study 40 BZD-dependent inpatients. Their symptoms were quantified using the Hamilton Anxiety Rating Scale (HAMA), Montgomery-Åsberg Depression Rating Scale (MADRS) and Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a conventional treatment group (daily diazepam with gradual tapering) with supportive psychotherapy and another group receiving the same treatment supplemented with rTMS (five weekly sessions for 2 weeks). Significant improvements were observed in both groups over baseline in MADRS, HAMA and PSQI scores at the 2nd, 4th, 8th and 12th week assessments (p < 0.05). The group receiving rTMS in addition to conventional treatment exhibited superior improvements in all measures at the 8th and 12th weeks. The addition of rTMS to conventional treatment methods for BZD dependence significantly betters the recovery in terms of depression, anxiety and sleep quality, highlighting the role of rTMS as an effective adjunct therapy.
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Affiliation(s)
- Jinbo Chen
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Zixuan Chen
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Yanli Zhang
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Xiaohe Fan
- Department of PsychiatryHongqi Hospital Affiliated to Mudanjiang Medical UniversityMudanjiangChina
| | - Changchun Zhang
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Jun Zhu
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Chuanfu Song
- Department of PsychiatryThe Fourth People's Hospital of WuhuWuhuChina
| | | | - Danwei Zhang
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Lijuan Tang
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Benhan Li
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
| | - Weibian Yang
- Department of PsychiatryHongqi Hospital Affiliated to Mudanjiang Medical UniversityMudanjiangChina
| | - Qiang Hu
- Department of PsychiatryZhenjiang Mental Health CenterZhenjiangChina
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Baum ML, Wilton DK, Fox RG, Carey A, Hsu YHH, Hu R, Jäntti HJ, Fahey JB, Muthukumar AK, Salla N, Crotty W, Scott-Hewitt N, Bien E, Sabatini DA, Lanser TB, Frouin A, Gergits F, Håvik B, Gialeli C, Nacu E, Lage K, Blom AM, Eggan K, McCarroll SA, Johnson MB, Stevens B. CSMD1 regulates brain complement activity and circuit development. Brain Behav Immun 2024; 119:317-332. [PMID: 38552925 DOI: 10.1016/j.bbi.2024.03.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/29/2024] [Accepted: 03/26/2024] [Indexed: 04/16/2024] Open
Abstract
Complement proteins facilitate synaptic elimination during neurodevelopmental pruning, but neural complement regulation is not well understood. CUB and Sushi Multiple Domains 1 (CSMD1) can regulate complement activity in vitro, is expressed in the brain, and is associated with increased schizophrenia risk. Beyond this, little is known about CSMD1 including whether it regulates complement activity in the brain or otherwise plays a role in neurodevelopment. We used biochemical, immunohistochemical, and proteomic techniques to examine the regional, cellular, and subcellular distribution as well as protein interactions of CSMD1 in the brain. To evaluate whether CSMD1 is involved in complement-mediated synapse elimination, we examined Csmd1-knockout mice and CSMD1-knockout human stem cell-derived neurons. We interrogated synapse and circuit development of the mouse visual thalamus, a process that involves complement pathway activity. We also quantified complement deposition on synapses in mouse visual thalamus and on cultured human neurons. Finally, we assessed uptake of synaptosomes by cultured microglia. We found that CSMD1 is present at synapses and interacts with complement proteins in the brain. Mice lacking Csmd1 displayed increased levels of complement component C3, an increased colocalization of C3 with presynaptic terminals, fewer retinogeniculate synapses, and aberrant segregation of eye-specific retinal inputs to the visual thalamus during the critical period of complement-dependent refinement of this circuit. Loss of CSMD1 in vivo enhanced synaptosome engulfment by microglia in vitro, and this effect was dependent on activity of the microglial complement receptor, CR3. Finally, human stem cell-derived neurons lacking CSMD1 were more vulnerable to complement deposition. These data suggest that CSMD1 can function as a regulator of complement-mediated synapse elimination in the brain during development.
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Affiliation(s)
- Matthew L Baum
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; MD-PhD Program of Harvard & MIT, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel K Wilton
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Rachel G Fox
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alanna Carey
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yu-Han H Hsu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ruilong Hu
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Henna J Jäntti
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jaclyn B Fahey
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Allie K Muthukumar
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nikkita Salla
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - William Crotty
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Nicole Scott-Hewitt
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Elizabeth Bien
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - David A Sabatini
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Toby B Lanser
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Arnaud Frouin
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Frederick Gergits
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Chrysostomi Gialeli
- Division of Medical Protein Chemistry, Department of Translational Medicine, Lund University, S-214 28 Malmö, Sweden; Cardiovascular Research - Translational Studies Research Group, Department of Clinical Sciences, Lund University, S-214 28 Malmö, Sweden
| | - Eugene Nacu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kasper Lage
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Anna M Blom
- Division of Medical Protein Chemistry, Department of Translational Medicine, Lund University, S-214 28 Malmö, Sweden
| | - Kevin Eggan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matthew B Johnson
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Beth Stevens
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Howard Hughes Medical Institute, USA.
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Wang Y, Cheng L, Li D, Lu Y, Wang C, Wang Y, Gao C, Wang H, Vanduffel W, Hopkins WD, Sherwood CC, Jiang T, Chu C, Fan L. Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.03.597252. [PMID: 38895242 PMCID: PMC11185649 DOI: 10.1101/2024.06.03.597252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.
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Affiliation(s)
- Yufan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Luqi Cheng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yaping Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Chaohong Gao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - William D. Hopkins
- Department of Comparative Medicine, University of Texas MD Anderson Cancer Center, Bastrop, TX 78602, USA
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
- School of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266000, China
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Liu Q, Liu Z, Xie W, Li Y, Wang H, Zhang S, Wang W, Hao J, Geng D, Yang J, Wang L. Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP. Front Aging Neurosci 2024; 16:1390310. [PMID: 38952478 PMCID: PMC11215054 DOI: 10.3389/fnagi.2024.1390310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/03/2024] [Indexed: 07/03/2024] Open
Abstract
Background N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated. Methods Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized. Results Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1. Conclusion Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.
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Affiliation(s)
- Qing Liu
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Ziyu Liu
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Wenmeng Xie
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yibo Li
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Hongfang Wang
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Sanbing Zhang
- Department of Hand and Foot Surgery, The Third Hospital of Shijiazhuang, Shijiazhuang, Hebei, China
| | - Wenyu Wang
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Jiaxin Hao
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Dandan Geng
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
- Neuroscience Research Center, Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Key Laboratory of Neurodegenerative Disease Mechanism, Shijiazhuang, Hebei, China
| | - Jing Yang
- Zhejiang Provincial Key Laboratory of Aging and Cancer Biology, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Lei Wang
- Department of Human Anatomy, Hebei Medical University, Shijiazhuang, Hebei, China
- Department of Hand and Foot Surgery, The Third Hospital of Shijiazhuang, Shijiazhuang, Hebei, China
- Neuroscience Research Center, Hebei Medical University, Shijiazhuang, Hebei, China
- The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang, Hebei, China
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Sandoval SO, Méndez-Albelo NM, Xu Z, Zhao X. From wings to whiskers to stem cells: why every model matters in fragile X syndrome research. J Neurodev Disord 2024; 16:30. [PMID: 38872088 PMCID: PMC11177515 DOI: 10.1186/s11689-024-09545-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/21/2024] [Indexed: 06/15/2024] Open
Abstract
Fragile X syndrome (FXS) is caused by epigenetic silencing of the X-linked fragile X messenger ribonucleoprotein 1 (FMR1) gene located on chromosome Xq27.3, which leads to the loss of its protein product, fragile X messenger ribonucleoprotein (FMRP). It is the most prevalent inherited form of intellectual disability and the highest single genetic cause of autism. Since the discovery of the genetic basis of FXS, extensive studies using animal models and human pluripotent stem cells have unveiled the functions of FMRP and mechanisms underlying FXS. However, clinical trials have not yielded successful treatment. Here we review what we have learned from commonly used models for FXS, potential limitations of these models, and recommendations for future steps.
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Affiliation(s)
- Soraya O Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Natasha M Méndez-Albelo
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Molecular Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Zhiyan Xu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Graduate Program in Cell and Molecular Biology, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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Gonzalez Burgos G, Miyamae T, Nishihata Y, Krimer OL, Wade K, Fish KN, Arion D, Cai ZL, Xue M, Stauffer WR, Lewis DA. Synaptic alterations in pyramidal cells following genetic manipulation of neuronal excitability in monkey prefrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.12.598658. [PMID: 38915638 PMCID: PMC11195287 DOI: 10.1101/2024.06.12.598658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
In schizophrenia, layer 3 pyramidal neurons (L3PNs) in the dorsolateral prefrontal cortex (DLPFC) are thought to receive fewer excitatory synaptic inputs and to have lower expression levels of activity-dependent genes and of genes involved in mitochondrial energy production. In concert, these findings from previous studies suggest that DLPFC L3PNs are hypoactive in schizophrenia, disrupting the patterns of activity that are crucial for working memory, which is impaired in the illness. However, whether lower PN activity produces alterations in inhibitory and/or excitatory synaptic strength has not been tested in the primate DLPFC. Here, we decreased PN excitability in rhesus monkey DLPFC in vivo using adeno-associated viral vectors (AAVs) to produce Cre recombinase-mediated overexpression of Kir2.1 channels, a genetic silencing tool that efficiently decreases neuronal excitability. In acute slices prepared from DLPFC 7-12 weeks post-AAV microinjections, Kir2.1-overexpressing PNs had a significantly reduced excitability largely attributable to highly specific effects of the AAV-encoded Kir2.1 channels. Moreover, recordings of synaptic currents showed that Kir2.1-overexpressing DLPFC PNs had reduced strength of excitatory synapses whereas inhibitory synaptic inputs were not affected. The decrease in excitatory synaptic strength was not associated with changes in dendritic spine number, suggesting that excitatory synapse quantity was unaltered in Kir2.1-overexpressing DLPFC PNs. These findings suggest that, in schizophrenia, the excitatory synapses on hypoactive L3PNs are weaker and thus might represent a substrate for novel therapeutic interventions. Significance Statement In schizophrenia, dorsolateral prefrontal cortex (DLPFC) pyramidal neurons (PNs) have both transcriptional and structural alterations that suggest they are hypoactive. PN hypoactivity is thought to produce synaptic alterations in schizophrenia, however the effects of lower neuronal activity on synaptic function in primate DLPFC have not been examined. Here, we used, for the first time in primate neocortex, adeno-associated viral vectors (AAVs) to reduce PN excitability with Kir2.1 channel overexpression and tested if this manipulation altered the strength of synaptic inputs onto the Kir2.1-overexpressing PNs. Recordings in DLPFC slices showed that Kir2.1 overexpression depressed excitatory (but not inhibitory), synaptic currents, suggesting that, in schizophrenia, the hypoactivity of PNs might be exacerbated by reduced strength of the excitatory synapses they receive.
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Sandoval SO, Cappuccio G, Kruth K, Osenberg S, Khalil SM, Méndez-Albelo NM, Padmanabhan K, Wang D, Niciu MJ, Bhattacharyya A, Stein JL, Sousa AMM, Waxman EA, Buttermore ED, Whye D, Sirois CL, Williams A, Maletic-Savatic M, Zhao X. Rigor and reproducibility in human brain organoid research: Where we are and where we need to go. Stem Cell Reports 2024; 19:796-816. [PMID: 38759644 PMCID: PMC11297560 DOI: 10.1016/j.stemcr.2024.04.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 05/19/2024] Open
Abstract
Human brain organoid models have emerged as a promising tool for studying human brain development and function. These models preserve human genetics and recapitulate some aspects of human brain development, while facilitating manipulation in an in vitro setting. Despite their potential to transform biology and medicine, concerns persist about their fidelity. To fully harness their potential, it is imperative to establish reliable analytic methods, ensuring rigor and reproducibility. Here, we review current analytical platforms used to characterize human forebrain cortical organoids, highlight challenges, and propose recommendations for future studies to achieve greater precision and uniformity across laboratories.
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Affiliation(s)
- Soraya O Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Gerarda Cappuccio
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Karina Kruth
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA
| | - Sivan Osenberg
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Saleh M Khalil
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Natasha M Méndez-Albelo
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA; Molecular Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Krishnan Padmanabhan
- Department of Neuroscience, Center for Visual Science, Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester NY 14642, USA
| | - Daifeng Wang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Departments of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Mark J Niciu
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA
| | - Anita Bhattacharyya
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - André M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Elisa A Waxman
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Center for Epilepsy and NeuroDevelopmental Disorders (ENDD), The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Elizabeth D Buttermore
- Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA; F.M. Kirby Neurobiology Department, Boston Children's Hospital, Boston, MA, USA
| | - Dosh Whye
- Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA; F.M. Kirby Neurobiology Department, Boston Children's Hospital, Boston, MA, USA
| | - Carissa L Sirois
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Aislinn Williams
- Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA.
| | - Mirjana Maletic-Savatic
- Department of Pediatrics-Neurology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA; Center for Drug Discovery, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA.
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Wei W, Ma S, Fu B, Song R, Guo H. Human-specific insights into candidate genes and boosted discoveries of novel loci illuminate roles of neuroglia in reading disorders. GENES, BRAIN, AND BEHAVIOR 2024; 23:e12899. [PMID: 38752599 PMCID: PMC11097622 DOI: 10.1111/gbb.12899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/29/2024] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
Reading disorders (RD) are human-specific neuropsychological conditions associated with decoding printed words and/or reading comprehension. So far only a handful of candidate genes segregated in families and 42 loci from genome-wide association study (GWAS) have been identified that jointly provided little clues of pathophysiology. Leveraging human-specific genomic information, we critically assessed the RD candidates for the first time and found substantial human-specific features within. The GWAS candidates (i.e., population signals) were distinct from the familial counterparts and were more likely pleiotropic in neuropsychiatric traits and to harbor human-specific regulatory elements (HSREs). Candidate genes associated with human cortical morphology indeed showed human-specific expression in adult brain cortices, particularly in neuroglia likely regulated by HSREs. Expression levels of candidate genes across human brain developmental stages showed a clear pattern of uplifted expression in early brain development crucial to RD development. Following the new insights and loci pleiotropic in cognitive traits, we identified four novel genes from the GWAS sub-significant associations (i.e., FOXO3, MAPT, KMT2E and HTT) and the Semaphorin gene family with functional priors (i.e., SEMA3A, SEMA3E and SEMA5B). These novel genes were related to neuronal plasticity and disorders, mostly conserved the pattern of uplifted expression in early brain development and had evident expression in cortical neuroglial cells. Our findings jointly illuminated the association of RD with neuroglia regulation-an emerging hotspot in studying neurodevelopmental disorders, and highlighted the need of improving RD phenotyping to avoid jeopardizing future genetic studies of RD.
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Affiliation(s)
- Wen‐Hua Wei
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary CareThe University of ManchesterManchesterUK
| | - Shaowei Ma
- Hebei Key Laboratory of Children's Cognition and Digital Education and School of Foreign LanguagesLangfang Normal UniversityLangfangChina
| | - Bo Fu
- School of Data ScienceFudan UniversityShanghaiChina
| | - Ranran Song
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Hui Guo
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary CareThe University of ManchesterManchesterUK
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Zhang P, Gao C, Guo Q, Yang D, Zhang G, Lu H, Zhang L, Zhang G, Li D. Single-cell RNA sequencing reveals the evolution of the immune landscape during perihematomal edema progression after intracerebral hemorrhage. J Neuroinflammation 2024; 21:140. [PMID: 38807233 PMCID: PMC11131315 DOI: 10.1186/s12974-024-03113-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/26/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Perihematomal edema (PHE) after post-intracerebral hemorrhage (ICH) has complex pathophysiological mechanisms that are poorly understood. The complicated immune response in the post-ICH brain constitutes a crucial component of PHE pathophysiology. In this study, we aimed to characterize the transcriptional profiles of immune cell populations in human PHE tissue and explore the microscopic differences between different types of immune cells. METHODS 9 patients with basal ganglia intracerebral hemorrhage (hematoma volume 50-100 ml) were enrolled in this study. A multi-stage profile was developed, comprising Group1 (n = 3, 0-6 h post-ICH, G1), Group2 (n = 3, 6-24 h post-ICH, G2), and Group3 (n = 3, 24-48 h post-ICH, G3). A minimal quantity of edematous tissue surrounding the hematoma was preserved during hematoma evacuation. Single cell RNA sequencing (scRNA-seq) was used to map immune cell populations within comprehensively resected PHE samples collected from patients at different stages after ICH. RESULTS We established, for the first time, a comprehensive landscape of diverse immune cell populations in human PHE tissue at a single-cell level. Our study identified 12 microglia subsets and 5 neutrophil subsets in human PHE tissue. What's more, we discovered that the secreted phosphoprotein-1 (SPP1) pathway served as the basis for self-communication between microglia subclusters during the progression of PHE. Additionally, we traced the trajectory branches of different neutrophil subtypes. Finally, we also demonstrated that microglia-produced osteopontin (OPN) could regulate the immune environment in PHE tissue by interacting with CD44-positive cells. CONCLUSIONS As a result of our research, we have gained valuable insight into the immune-microenvironment within PHE tissue, which could potentially be used to develop novel treatment modalities for ICH.
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Affiliation(s)
- Peng Zhang
- Department of Clinical Medicine, Jining Medical University, Jining, China
| | - Cong Gao
- Department of Clinical Medicine, Jining Medical University, Jining, China
| | - Qiang Guo
- Department of Emergency Stroke, Affiliated Hospital of Jining Medical University, Jining, China
| | - Dongxu Yang
- Department of Emergency Stroke, Affiliated Hospital of Jining Medical University, Jining, China
| | - Guangning Zhang
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, China
| | - Hao Lu
- Department of Emergency Stroke, Affiliated Hospital of Jining Medical University, Jining, China
| | - Liman Zhang
- Department of Pathology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Guorong Zhang
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Daojing Li
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, China.
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. Science 2024; 384:eadi5199. [PMID: 38781369 PMCID: PMC11365579 DOI: 10.1126/science.adi5199] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Chicago, IL 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597 Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, USA
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75
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Huuki-Myers LA, Spangler A, Eagles NJ, Montgomery KD, Kwon SH, Guo B, Grant-Peters M, Divecha HR, Tippani M, Sriworarat C, Nguyen AB, Ravichandran P, Tran MN, Seyedian A, Hyde TM, Kleinman JE, Battle A, Page SC, Ryten M, Hicks SC, Martinowich K, Collado-Torres L, Maynard KR. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science 2024; 384:eadh1938. [PMID: 38781370 PMCID: PMC11398705 DOI: 10.1126/science.adh1938] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 12/06/2023] [Indexed: 05/25/2024]
Abstract
The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.
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Affiliation(s)
- Louise A Huuki-Myers
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Abby Spangler
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Nicholas J Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Kelsey D Montgomery
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Boyi Guo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Melissa Grant-Peters
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Heena R Divecha
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Chaichontat Sriworarat
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Annie B Nguyen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Prashanthi Ravichandran
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
| | - Matthew N Tran
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Arta Seyedian
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Stephanie C Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London WC1N 1EH, UK
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD 21218, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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76
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Gao Y, Dong Q, Arachchilage KH, Risgaard R, Sheng J, Syed M, Schmidt DK, Jin T, Liu S, Knaack SA, Doherty D, Glass I, Levine JE, Wang D, Chang Q, Zhao X, Sousa AM. Multimodal analyses reveal genes driving electrophysiological maturation of neurons in the primate prefrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.02.543460. [PMID: 37398253 PMCID: PMC10312516 DOI: 10.1101/2023.06.02.543460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The prefrontal cortex (PFC) is critical for myriad high-cognitive functions and is associated with several neuropsychiatric disorders. Here, using Patch-seq and single-nucleus multiomic analyses, we identified genes and regulatory networks governing the maturation of distinct neuronal populations in the PFC of rhesus macaque. We discovered that specific electrophysiological properties exhibited distinct maturational kinetics and identified key genes underlying these properties. We unveiled that RAPGEF4 is important for the maturation of resting membrane potential and inward sodium current in both macaque and human. We demonstrated that knockdown of CHD8, a high-confidence autism risk gene, in human and macaque organotypic slices led to impaired maturation, via downregulation of key genes, including RAPGEF4. Restoring the expression of RAPGEF4 rescued the proper electrophysiological maturation of CHD8-deficient neurons. Our study revealed regulators of neuronal maturation during a critical period of PFC development in primates and implicated such regulators in molecular processes underlying autism.
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77
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Lee CY, Riffle D, Xiong Y, Momtaz N, Lei Y, Pariser JM, Sikdar D, Hwang A, Duan Z, Zhang J. Characterizing dysregulations via cell-cell communications in Alzheimer's brains using single-cell transcriptomes. BMC Neurosci 2024; 25:24. [PMID: 38741048 PMCID: PMC11089696 DOI: 10.1186/s12868-024-00867-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 04/01/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains. RESULTS Specifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFβ, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons. CONCLUSIONS In summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.
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Affiliation(s)
- Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Dylan Riffle
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Yifeng Xiong
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Nadia Momtaz
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yutong Lei
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Joseph M Pariser
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Diptanshu Sikdar
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, USA.
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78
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Wang X, Luo P, Zhang L, Sun J, Cao J, Lei Z, Yang H, Lv X, Liu J, Yao X, Li S, Fang J. Altered functional brain activity in first-episode major depressive disorder treated with electro-acupuncture: A resting-state functional magnetic resonance imaging study. Heliyon 2024; 10:e29613. [PMID: 38681626 PMCID: PMC11053281 DOI: 10.1016/j.heliyon.2024.e29613] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/27/2024] [Accepted: 04/10/2024] [Indexed: 05/01/2024] Open
Abstract
Background Previous studies have found electroacupuncture could improve the clinical symptoms of first-episode major depressive disorder (MDD), but the exact neural mechanism of action needs to be further elucidated. Methods Twenty-eight first-episode MDD patients were randomly divided into 14 electro-acupuncture stimulation (EAS) groups and 14 sham-acupuncture stimulation (SAS) groups, and clinical symptoms were assessed and functional magnetic resonance imaging (fMRI) scans were done in both groups. Amplitude of low-frequency fluctuations (ALFF) was used to observe the changes between the pre-treatment and post-treatment in the two groups, and the altered brain areas were selected as region of interest (ROI) to observe the FC changes. Meanwhile, the correlation between the altered clinical symptoms and the altered ALFF and FC of brain regions in the two groups was analyzed. Results The EAS significantly decreased the HAMD-24 and HAMA-14 scores of MDD than SAS group. The imaging results revealed that both groups were able to increase the ALFF of the left middle temporal gyrus and the left cerebellar posterior lobe. When using the left middle temporal gyrus and the left posterior cerebellar lobe as ROIs, EAS group increased the FC between the left middle temporal gyrus with the left superior frontal gyrus, the left middle frontal gyrus, and the left hippocampus, and decreased the FC between the left posterior cerebellar lobe and the left calcarine gyrus, while SAS group only increased the FC between the left middle temporal gyrus with the left superior frontal gyrus. The alternations in clinical symptoms after EAS treatment were positively correlated with the altered ALFF values in the left middle temporal gyrus and the altered FC values in the left middle temporal gyrus and the left middle frontal gyrus. Conclusion EA demonstrates modulation of functional activity in the default mode network (DMN), sensorimotor network (SMN), cognitive control network (CCN), limbic system, and visual network (VN) for the treatment of the first-episode MDD. Our findings contribute to the neuroimaging evidence for the efficacy of EAS.
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Affiliation(s)
- XiaoLing Wang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ping Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ling Zhang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - JiFei Sun
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - JiuDong Cao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhang Lei
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Hong Yang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - XueYu Lv
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jun Liu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - XiaoYan Yao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - ShanShan Li
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - JiLiang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
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79
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吴 瀚, 高 洁. [Identifying spatial domains from spatial transcriptome by graph attention network]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2024; 41:246-252. [PMID: 38686404 PMCID: PMC11058491 DOI: 10.7507/1001-5515.202304030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 12/01/2023] [Indexed: 05/02/2024]
Abstract
Due to the high dimensionality and complexity of the data, the analysis of spatial transcriptome data has been a challenging problem. Meanwhile, cluster analysis is the core issue of the analysis of spatial transcriptome data. In this article, a deep learning approach is proposed based on graph attention networks for clustering analysis of spatial transcriptome data. Our method first enhances the spatial transcriptome data, then uses graph attention networks to extract features from nodes, and finally uses the Leiden algorithm for clustering analysis. Compared with the traditional non-spatial and spatial clustering methods, our method has better performance in data analysis through the clustering evaluation index. The experimental results show that the proposed method can effectively cluster spatial transcriptome data and identify different spatial domains, which provides a new tool for studying spatial transcriptome data.
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Affiliation(s)
- 瀚文 吴
- 江南大学(江苏无锡 214122)Jiangnan University, Wuxi, Jiangsu 214122, P. R. China
| | - 洁 高
- 江南大学(江苏无锡 214122)Jiangnan University, Wuxi, Jiangsu 214122, P. R. China
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80
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Casey C, Fullard JF, Sleator RD. Unravelling the genetic basis of Schizophrenia. Gene 2024; 902:148198. [PMID: 38266791 DOI: 10.1016/j.gene.2024.148198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/07/2023] [Accepted: 01/19/2024] [Indexed: 01/26/2024]
Abstract
Neuronal development is a highly regulated mechanism that is central to organismal function in animals. In humans, disruptions to this process can lead to a range of neurodevelopmental phenotypes, including Schizophrenia (SCZ). SCZ has a significant genetic component, whereby an individual with an SCZ affected family member is eight times more likely to develop the disease than someone with no family history of SCZ. By examining a combination of genomic, transcriptomic and epigenomic datasets, large-scale 'omics' studies aim to delineate the relationship between genetic variation and abnormal cellular activity in the SCZ brain. Herein, we provide a brief overview of some of the key omics methods currently being used in SCZ research, including RNA-seq, the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and high-throughput chromosome conformation capture (3C) approaches (e.g., Hi-C), as well as single-cell/nuclei iterations of these methods. We also discuss how these techniques are being employed to further our understanding of the genetic basis of SCZ, and to identify associated molecular pathways, biomarkers, and candidate drug targets.
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Affiliation(s)
- Clara Casey
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - Roy D Sleator
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland.
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81
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Zhang S, Xu N, Fu L, Yang X, Li Y, Yang Z, Feng Y, Ma K, Jiang X, Han J, Hu R, Zhang L, de Gennaro L, Ryabov F, Meng D, He Y, Wu D, Yang C, Paparella A, Mao Y, Bian X, Lu Y, Antonacci F, Ventura M, Shepelev VA, Miga KH, Alexandrov IA, Logsdon GA, Phillippy AM, Su B, Zhang G, Eichler EE, Lu Q, Shi Y, Sun Q, Mao Y. Comparative genomics of macaques and integrated insights into genetic variation and population history. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588379. [PMID: 38645259 PMCID: PMC11030432 DOI: 10.1101/2024.04.07.588379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.
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82
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Zhou Y, He W, Hou W, Zhu Y. Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics. Nat Commun 2024; 15:2848. [PMID: 38565531 PMCID: PMC11271244 DOI: 10.1038/s41467-024-47152-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/20/2024] [Indexed: 04/04/2024] Open
Abstract
Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots' biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics annotation based on marker genes. Comprehensive evaluations underscore Pianno's remarkable prowess in precisely annotating a wide array of spatial semantics, ranging from diverse anatomical structures to intricate tumor microenvironments, as well as in estimating cell type distributions, across data generated from various spatial transcriptomics platforms. Furthermore, Pianno, in conjunction with clustering approaches, uncovers a region- and species-specific excitatory neuron subtype in the deep layer 3 of the human neocortex, shedding light on cellular evolution in the human neocortex. Overall, Pianno equips researchers with a robust and efficient tool for annotating diverse biological structures, offering new perspectives on spatial transcriptomics data.
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Affiliation(s)
- Yuqiu Zhou
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Wei He
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Weizhen Hou
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
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83
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Boisserand LSB, Geraldo LH, Bouchart J, El Kamouh MR, Lee S, Sanganahalli BG, Spajer M, Zhang S, Lee S, Parent M, Xue Y, Skarica M, Yin X, Guegan J, Boyé K, Saceanu Leser F, Jacob L, Poulet M, Li M, Liu X, Velazquez SE, Singhabahu R, Robinson ME, Askenase MH, Osherov A, Sestan N, Zhou J, Alitalo K, Song E, Eichmann A, Sansing LH, Benveniste H, Hyder F, Thomas JL. VEGF-C prophylaxis favors lymphatic drainage and modulates neuroinflammation in a stroke model. J Exp Med 2024; 221:e20221983. [PMID: 38442272 PMCID: PMC10913814 DOI: 10.1084/jem.20221983] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 11/13/2023] [Accepted: 01/25/2024] [Indexed: 03/07/2024] Open
Abstract
Meningeal lymphatic vessels (MLVs) promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelial growth factor-C (VEGF-C) regulates MLV development and maintenance and has therapeutic potential for treating neurological disorders. Herein, we investigated the effects of VEGF-C overexpression on brain fluid drainage and ischemic stroke outcomes in mice. Intracerebrospinal administration of an adeno-associated virus expressing mouse full-length VEGF-C (AAV-mVEGF-C) increased CSF drainage to the deep cervical lymph nodes (dCLNs) by enhancing lymphatic growth and upregulated neuroprotective signaling pathways identified by single nuclei RNA sequencing of brain cells. In a mouse model of ischemic stroke, AAV-mVEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage, associated with mitigated microglia-mediated inflammation and increased BDNF signaling in brain cells. Neuroprotective effects of VEGF-C were lost upon cauterization of the dCLN afferent lymphatics and not mimicked by acute post-stroke VEGF-C injection. We conclude that VEGF-C prophylaxis promotes multiple vascular, immune, and neural responses that culminate in a protection against neurological damage in acute ischemic stroke.
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Affiliation(s)
| | - Luiz Henrique Geraldo
- Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Jean Bouchart
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Marie-Renee El Kamouh
- Paris Brain Institute, Université Pierre et Marie Curie Paris 06 UMRS1127, Sorbonne Université, Paris, France
| | - Seyoung Lee
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | | | - Myriam Spajer
- Paris Brain Institute, Université Pierre et Marie Curie Paris 06 UMRS1127, Sorbonne Université, Paris, France
| | - Shenqi Zhang
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | - Sungwoon Lee
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Maxime Parent
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Yuechuan Xue
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Mario Skarica
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Xiangyun Yin
- Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Justine Guegan
- Paris Brain Institute, Université Pierre et Marie Curie Paris 06 UMRS1127, Sorbonne Université, Paris, France
| | - Kevin Boyé
- Paris Cardiovascular Research Center, INSERM U970, Paris, France
| | - Felipe Saceanu Leser
- Paris Cardiovascular Research Center, INSERM U970, Paris, France
- Glial Cell Biology Laboratory, Biomedical Sciences Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Laurent Jacob
- Paris Cardiovascular Research Center, INSERM U970, Paris, France
| | - Mathilde Poulet
- Paris Cardiovascular Research Center, INSERM U970, Paris, France
| | - Mingfeng Li
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Xiaodan Liu
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Sofia E. Velazquez
- Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Ruchith Singhabahu
- Paris Brain Institute, Université Pierre et Marie Curie Paris 06 UMRS1127, Sorbonne Université, Paris, France
| | - Mark E. Robinson
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | | | - Artem Osherov
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale School of Medicine, New Haven, CT, USA
| | - Jiangbing Zhou
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | - Kari Alitalo
- Faculty of Medicine, Wihuri Research Institute and Translational Cancer Biology Program, University of Helsinki, Helsinki, Finland
| | - Eric Song
- Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Anne Eichmann
- Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT, USA
- Paris Cardiovascular Research Center, INSERM U970, Paris, France
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT, USA
| | - Lauren H. Sansing
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, CT, USA
| | - Helene Benveniste
- Department of Anesthesiology, Yale School of Medicine, New Haven, CT, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Jean-Leon Thomas
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Paris Brain Institute, Université Pierre et Marie Curie Paris 06 UMRS1127, Sorbonne Université, Paris, France
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84
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Shen Y, Shao M, Hao ZZ, Huang M, Xu N, Liu S. Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity. Neurosci Bull 2024; 40:517-532. [PMID: 38194157 PMCID: PMC11003949 DOI: 10.1007/s12264-023-01160-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 09/23/2023] [Indexed: 01/10/2024] Open
Abstract
Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.
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Affiliation(s)
- Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mingting Shao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mengyao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
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85
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585576. [PMID: 38562822 PMCID: PMC10983939 DOI: 10.1101/2024.03.18.585576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Opthalmology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Inc., Chicago, IL, 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA, 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Michael Margolis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Manman Shi
- Tempus Labs, Inc., Chicago, IL, 60654, USA
| | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT, 06520, USA
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86
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Zito A, Lee JT. Variable expression of MECP2, CDKL5, and FMR1 in the human brain: Implications for gene restorative therapies. Proc Natl Acad Sci U S A 2024; 121:e2312757121. [PMID: 38386709 PMCID: PMC10907246 DOI: 10.1073/pnas.2312757121] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 12/28/2023] [Indexed: 02/24/2024] Open
Abstract
MECP2, CDKL5, and FMR1 are three X-linked neurodevelopmental genes associated with Rett, CDKL5-, and fragile-X syndrome, respectively. These syndromes are characterized by distinct constellations of severe cognitive and neurobehavioral anomalies, reflecting the broad but unique expression patterns of each of the genes in the brain. As these disorders are not thought to be neurodegenerative and may be reversible, a major goal has been to restore expression of the functional proteins in the patient's brain. Strategies have included gene therapy, gene editing, and selective Xi-reactivation methodologies. However, tissue penetration and overall delivery to various regions of the brain remain challenging for each strategy. Thus, gaining insights into how much restoration would be required and what regions/cell types in the brain must be targeted for meaningful physiological improvement would be valuable. As a step toward addressing these questions, here we perform a meta-analysis of single-cell transcriptomics data from the human brain across multiple developmental stages, in various brain regions, and in multiple donors. We observe a substantial degree of expression variability for MECP2, CDKL5, and FMR1 not only across cell types but also between donors. The wide range of expression may help define a therapeutic window, with the low end delineating a minimum level required to restore physiological function and the high end informing toxicology margin. Finally, the inter-cellular and inter-individual variability enable identification of co-varying genes and will facilitate future identification of biomarkers.
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Affiliation(s)
- Antonino Zito
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA02114
- Department of Genetics, The Blavatnik Institute, Harvard Medical School, Boston, MA02114
| | - Jeannie T. Lee
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA02114
- Department of Genetics, The Blavatnik Institute, Harvard Medical School, Boston, MA02114
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87
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Choi TY, Jeon H, Jeong S, Kim EJ, Kim J, Jeong YH, Kang B, Choi M, Koo JW. Distinct prefrontal projection activity and transcriptional state conversely orchestrate social competition and hierarchy. Neuron 2024; 112:611-627.e8. [PMID: 38086372 DOI: 10.1016/j.neuron.2023.11.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 09/20/2023] [Accepted: 11/13/2023] [Indexed: 02/24/2024]
Abstract
Social animals compete for limited resources, resulting in a social hierarchy. Although different neuronal subpopulations in the medial prefrontal cortex (mPFC), which has been mechanistically implicated in social dominance behavior, encode distinct social competition behaviors, their identities and associated molecular underpinnings have not yet been identified. In this study, we found that mPFC neurons projecting to the nucleus accumbens (mPFC-NAc) encode social winning behavior, whereas mPFC neurons projecting to the ventral tegmental area (mPFC-VTA) encode social losing behavior. High-throughput single-cell transcriptomic analysis and projection-specific genetic manipulation revealed that the expression level of POU domain, class 3, transcription factor 1 (Pou3f1) in mPFC-VTA neurons controls social hierarchy. Optogenetic activation of mPFC-VTA neurons increases Pou3f1 expression and lowers social rank. Together, these data demonstrate that discrete activity and gene expression in separate mPFC projections oppositely orchestrate social competition and hierarchy.
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Affiliation(s)
- Tae-Yong Choi
- Emotion, Cognition and Behavior Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Hyoungseok Jeon
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Sejin Jeong
- Emotion, Cognition and Behavior Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea; Department of Life Sciences, Yeungnam University, Gyeongsan 38541, Republic of Korea
| | - Eum Ji Kim
- Emotion, Cognition and Behavior Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Jeongseop Kim
- Emotion, Cognition and Behavior Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea; Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology, Daegu 41988, Republic of Korea
| | - Yun Ha Jeong
- Neurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Byungsoo Kang
- Sysoft R&D Center, Daegu 41065, Republic of Korea; Neurovascular Unit Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Murim Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
| | - Ja Wook Koo
- Emotion, Cognition and Behavior Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea; Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology, Daegu 41988, Republic of Korea.
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88
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Dehay C, Huttner WB. Development and evolution of the primate neocortex from a progenitor cell perspective. Development 2024; 151:dev199797. [PMID: 38369736 DOI: 10.1242/dev.199797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The generation of neurons in the developing neocortex is a major determinant of neocortex size. Crucially, the increase in cortical neuron numbers in the primate lineage, notably in the upper-layer neurons, contributes to increased cognitive abilities. Here, we review major evolutionary changes affecting the apical progenitors in the ventricular zone and focus on the key germinal zone constituting the foundation of neocortical neurogenesis in primates, the outer subventricular zone (OSVZ). We summarize characteristic features of the OSVZ and its key stem cell type, the basal (or outer) radial glia. Next, we concentrate on primate-specific and human-specific genes, expressed in OSVZ-progenitors, the ability of which to amplify these progenitors by targeting the regulation of the cell cycle ultimately underlies the evolutionary increase in upper-layer neurons. Finally, we address likely differences in neocortical development between present-day humans and Neanderthals that are based on human-specific amino acid substitutions in proteins operating in cortical progenitors.
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Affiliation(s)
- Colette Dehay
- Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, F-69500 Bron, France
| | - Wieland B Huttner
- Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany
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89
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Wang B, Starr AL, Fraser HB. Cell-type-specific cis-regulatory divergence in gene expression and chromatin accessibility revealed by human-chimpanzee hybrid cells. eLife 2024; 12:RP89594. [PMID: 38358392 PMCID: PMC10942608 DOI: 10.7554/elife.89594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024] Open
Abstract
Although gene expression divergence has long been postulated to be the primary driver of human evolution, identifying the genes and genetic variants underlying uniquely human traits has proven to be quite challenging. Theory suggests that cell-type-specific cis-regulatory variants may fuel evolutionary adaptation due to the specificity of their effects. These variants can precisely tune the expression of a single gene in a single cell-type, avoiding the potentially deleterious consequences of trans-acting changes and non-cell type-specific changes that can impact many genes and cell types, respectively. It has recently become possible to quantify human-specific cis-acting regulatory divergence by measuring allele-specific expression in human-chimpanzee hybrid cells-the product of fusing induced pluripotent stem (iPS) cells of each species in vitro. However, these cis-regulatory changes have only been explored in a limited number of cell types. Here, we quantify human-chimpanzee cis-regulatory divergence in gene expression and chromatin accessibility across six cell types, enabling the identification of highly cell-type-specific cis-regulatory changes. We find that cell-type-specific genes and regulatory elements evolve faster than those shared across cell types, suggesting an important role for genes with cell-type-specific expression in human evolution. Furthermore, we identify several instances of lineage-specific natural selection that may have played key roles in specific cell types, such as coordinated changes in the cis-regulation of dozens of genes involved in neuronal firing in motor neurons. Finally, using novel metrics and a machine learning model, we identify genetic variants that likely alter chromatin accessibility and transcription factor binding, leading to neuron-specific changes in the expression of the neurodevelopmentally important genes FABP7 and GAD1. Overall, our results demonstrate that integrative analysis of cis-regulatory divergence in chromatin accessibility and gene expression across cell types is a promising approach to identify the specific genes and genetic variants that make us human.
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Affiliation(s)
- Ban Wang
- Department of Biology, Stanford UniversityStanfordUnited States
| | | | - Hunter B Fraser
- Department of Biology, Stanford UniversityStanfordUnited States
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90
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Rickelton K, Zintel TM, Pizzollo J, Miller E, Ely JJ, Raghanti MA, Hopkins WD, Hof PR, Sherwood CC, Bauernfeind AL, Babbitt CC. Tempo and mode of gene expression evolution in the brain across primates. eLife 2024; 13:e70276. [PMID: 38275218 PMCID: PMC10876213 DOI: 10.7554/elife.70276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 01/25/2024] [Indexed: 01/27/2024] Open
Abstract
Primate evolution has led to a remarkable diversity of behavioral specializations and pronounced brain size variation among species (Barton, 2012; DeCasien and Higham, 2019; Powell et al., 2017). Gene expression provides a promising opportunity for studying the molecular basis of brain evolution, but it has been explored in very few primate species to date (e.g. Khaitovich et al., 2005; Khrameeva et al., 2020; Ma et al., 2022; Somel et al., 2009). To understand the landscape of gene expression evolution across the primate lineage, we generated and analyzed RNA-seq data from four brain regions in an unprecedented eighteen species. Here, we show a remarkable level of variation in gene expression among hominid species, including humans and chimpanzees, despite their relatively recent divergence time from other primates. We found that individual genes display a wide range of expression dynamics across evolutionary time reflective of the diverse selection pressures acting on genes within primate brain tissue. Using our samples that represent a 190-fold difference in primate brain size, we identified genes with variation in expression most correlated with brain size. Our study extensively broadens the phylogenetic context of what is known about the molecular evolution of the brain across primates and identifies novel candidate genes for the study of genetic regulation of brain evolution.
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Affiliation(s)
- Katherine Rickelton
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
- Molecular and Cellular Biology Graduate Program, University of Massachusetts AmherstAmherstUnited States
| | - Trisha M Zintel
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
- Molecular and Cellular Biology Graduate Program, University of Massachusetts AmherstAmherstUnited States
| | - Jason Pizzollo
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
- Molecular and Cellular Biology Graduate Program, University of Massachusetts AmherstAmherstUnited States
| | - Emily Miller
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
| | - John J Ely
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington UniversityWashingtonUnited States
- MAEBIOS Epidemiology UnitAlamogordoUnited States
| | - Mary Ann Raghanti
- Department of Anthropology, School of Biomedical Sciences, and Brain Health Research Institute, Kent State UniversityKentUnited States
| | - William D Hopkins
- Department of Comparative Medicine, Michale E. Keeling Center for Comparative Medicine,The University of Texas M D Anderson Cancer CentreBastropUnited States
| | - Patrick R Hof
- New York Consortium in Evolutionary PrimatologyNew YorkUnited States
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Chet C Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington UniversityWashingtonUnited States
| | - Amy L Bauernfeind
- Department of Neuroscience, Washington University School of MedicineSt. LouisUnited States
- Department of Anthropology, Washington University in St. LouisSt. LouisUnited States
| | - Courtney C Babbitt
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
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91
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Yang YT, Gan Z, Zhang J, Zhao X, Yang Y, Han S, Wu W, Zhao XM. STAB2: an updated spatio-temporal cell atlas of the human and mouse brain. Nucleic Acids Res 2024; 52:D1033-D1041. [PMID: 37904591 PMCID: PMC10767951 DOI: 10.1093/nar/gkad955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/30/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023] Open
Abstract
The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.
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Affiliation(s)
- Yucheng T Yang
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Ziquan Gan
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Jinglong Zhang
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Xingzhong Zhao
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Yifan Yang
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Shuwen Han
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
| | - Wei Wu
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
| | - Xing-Ming Zhao
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai 200032, China
- International Human Phenome Institutes (Shanghai), Shanghai 200433, China
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92
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Abstract
Brain development in humans is achieved through precise spatiotemporal genetic control, the mechanisms of which remain largely elusive. Recently, integration of technological advances in human stem cell-based modelling with genome editing has emerged as a powerful platform to establish causative links between genotypes and phenotypes directly in the human system. Here, we review our current knowledge of complex genetic regulation of each key step of human brain development through the lens of evolutionary specialization and neurodevelopmental disorders and highlight the use of human stem cell-derived 2D cultures and 3D brain organoids to investigate human-enriched features and disease mechanisms. We also discuss opportunities and challenges of integrating new technologies to reveal the genetic architecture of human brain development and disorders.
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Affiliation(s)
- Yi Zhou
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, USA
- The Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Guo-Li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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93
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Libé-Philippot B, Lejeune A, Wierda K, Louros N, Erkol E, Vlaeminck I, Beckers S, Gaspariunaite V, Bilheu A, Konstantoulea K, Nyitrai H, De Vleeschouwer M, Vennekens KM, Vidal N, Bird TW, Soto DC, Jaspers T, Dewilde M, Dennis MY, Rousseau F, Comoletti D, Schymkowitz J, Theys T, de Wit J, Vanderhaeghen P. LRRC37B is a human modifier of voltage-gated sodium channels and axon excitability in cortical neurons. Cell 2023; 186:5766-5783.e25. [PMID: 38134874 PMCID: PMC10754148 DOI: 10.1016/j.cell.2023.11.028] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/28/2023] [Accepted: 11/27/2023] [Indexed: 12/24/2023]
Abstract
The enhanced cognitive abilities characterizing the human species result from specialized features of neurons and circuits. Here, we report that the hominid-specific gene LRRC37B encodes a receptor expressed in human cortical pyramidal neurons (CPNs) and selectively localized to the axon initial segment (AIS), the subcellular compartment triggering action potentials. Ectopic expression of LRRC37B in mouse CPNs in vivo leads to reduced intrinsic excitability, a distinctive feature of some classes of human CPNs. Molecularly, LRRC37B binds to the secreted ligand FGF13A and to the voltage-gated sodium channel (Nav) β-subunit SCN1B. LRRC37B concentrates inhibitory effects of FGF13A on Nav channel function, thereby reducing excitability, specifically at the AIS level. Electrophysiological recordings in adult human cortical slices reveal lower neuronal excitability in human CPNs expressing LRRC37B. LRRC37B thus acts as a species-specific modifier of human neuron excitability, linking human genome and cell evolution, with important implications for human brain function and diseases.
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Affiliation(s)
- Baptiste Libé-Philippot
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Amélie Lejeune
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Keimpe Wierda
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Electrophysiology Unit, VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium
| | - Nikolaos Louros
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Emir Erkol
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Ine Vlaeminck
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Electrophysiology Unit, VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium
| | - Sofie Beckers
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Vaiva Gaspariunaite
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Angéline Bilheu
- Université Libre de Bruxelles (ULB), Institute for Interdisciplinary Research (IRIBHM), 1070 Brussels, Belgium
| | - Katerina Konstantoulea
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Hajnalka Nyitrai
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Matthias De Vleeschouwer
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Kristel M Vennekens
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Niels Vidal
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Thomas W Bird
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand
| | - Daniela C Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, Davis, CA 95616, USA
| | - Tom Jaspers
- Laboratory for Therapeutic and Diagnostic Antibodies, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Maarten Dewilde
- Laboratory for Therapeutic and Diagnostic Antibodies, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Megan Y Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, Davis, CA 95616, USA
| | - Frederic Rousseau
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Davide Comoletti
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand; Child Health Institute of New Jersey, Rutgers University, New Brunswick, NJ 08901, USA
| | - Joost Schymkowitz
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Tom Theys
- KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium; Research Group Experimental Neurosurgery and Neuroanatomy, KUL, 3000 Leuven, Belgium
| | - Joris de Wit
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
| | - Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium; Université Libre de Bruxelles (ULB), Institute for Interdisciplinary Research (IRIBHM), 1070 Brussels, Belgium.
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94
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Akula SK, Exposito-Alonso D, Walsh CA. Shaping the brain: The emergence of cortical structure and folding. Dev Cell 2023; 58:2836-2849. [PMID: 38113850 PMCID: PMC10793202 DOI: 10.1016/j.devcel.2023.11.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 04/08/2023] [Accepted: 11/10/2023] [Indexed: 12/21/2023]
Abstract
The cerebral cortex-the brain's covering and largest region-has increased in size and complexity in humans and supports higher cognitive functions such as language and abstract thinking. There is a growing understanding of the human cerebral cortex, including the diversity and number of cell types that it contains, as well as of the developmental mechanisms that shape cortical structure and organization. In this review, we discuss recent progress in our understanding of molecular and cellular processes, as well as mechanical forces, that regulate the folding of the cerebral cortex. Advances in human genetics, coupled with experimental modeling in gyrencephalic species, have provided insights into the central role of cortical progenitors in the gyrification and evolutionary expansion of the cerebral cortex. These studies are essential for understanding the emergence of structural and functional organization during cortical development and the pathogenesis of neurodevelopmental disorders associated with cortical malformations.
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Affiliation(s)
- Shyam K Akula
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| | - David Exposito-Alonso
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| | - Christopher A Walsh
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA.
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95
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Klarić TS, Gudelj I, Santpere G, Novokmet M, Vučković F, Ma S, Doll HM, Risgaard R, Bathla S, Karger A, Nairn AC, Luria V, Bečeheli I, Sherwood CC, Ely JJ, Hof PR, Sousa AM, Josić D, Lauc G, Sestan N. Human-specific features and developmental dynamics of the brain N-glycome. SCIENCE ADVANCES 2023; 9:eadg2615. [PMID: 38055821 PMCID: PMC10699788 DOI: 10.1126/sciadv.adg2615] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 11/07/2023] [Indexed: 12/08/2023]
Abstract
Comparative "omics" studies have revealed unique aspects of human neurobiology, yet an evolutionary perspective of the brain N-glycome is lacking. We performed multiregional characterization of rat, macaque, chimpanzee, and human brain N-glycomes using chromatography and mass spectrometry and then integrated these data with complementary glycotranscriptomic data. We found that, in primates, the brain N-glycome has diverged more rapidly than the underlying transcriptomic framework, providing a means for rapidly generating additional interspecies diversity. Our data suggest that brain N-glycome evolution in hominids has been characterized by an overall increase in complexity coupled with a shift toward increased usage of α(2-6)-linked N-acetylneuraminic acid. Moreover, interspecies differences in the cell type expression pattern of key glycogenes were identified, including some human-specific differences, which may underpin this evolutionary divergence. Last, by comparing the prenatal and adult human brain N-glycomes, we uncovered region-specific neurodevelopmental pathways that lead to distinct spatial N-glycosylation profiles in the mature brain.
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Affiliation(s)
- Thomas S. Klarić
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Ivan Gudelj
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Department of Biotechnology, University of Rijeka, Rijeka, Croatia
| | - Gabriel Santpere
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Hospital del Mar Research Institute, Barcelona, Catalonia, Spain
| | | | | | - Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Hannah M. Doll
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan Risgaard
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Shveta Bathla
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Amir Karger
- IT Research Computing, Harvard Medical School, Boston, MA, USA
| | - Angus C. Nairn
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, USA
| | | | - Chet C. Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - John J. Ely
- Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
- MAEBIOS, Alamogordo, NM, USA
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - André M. M. Sousa
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Djuro Josić
- Department of Biotechnology, University of Rijeka, Rijeka, Croatia
- Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- University of Zagreb Faculty of Pharmacy and Biochemistry, Zagreb, Croatia
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Departments of Genetics and Comparative Medicine, Kavli Institute for Neuroscience, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
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96
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Zemke NR, Armand EJ, Wang W, Lee S, Zhou J, Li YE, Liu H, Tian W, Nery JR, Castanon RG, Bartlett A, Osteen JK, Li D, Zhuo X, Xu V, Chang L, Dong K, Indralingam HS, Rink JA, Xie Y, Miller M, Krienen FM, Zhang Q, Taskin N, Ting J, Feng G, McCarroll SA, Callaway EM, Wang T, Lein ES, Behrens MM, Ecker JR, Ren B. Conserved and divergent gene regulatory programs of the mammalian neocortex. Nature 2023; 624:390-402. [PMID: 38092918 PMCID: PMC10719095 DOI: 10.1038/s41586-023-06819-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Divergence of cis-regulatory elements drives species-specific traits1, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes. We find that conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome. Transposable elements contribute to nearly 80% of the human-specific candidate cis-regulatory elements in cortical cells. Through machine learning, we develop sequence-based predictors of candidate cis-regulatory elements in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Finally, we show that epigenetic conservation combined with sequence similarity helps to uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.
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Affiliation(s)
- Nathan R Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Wenliang Wang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jingtian Zhou
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia K Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Xiaoyu Zhuo
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Vincent Xu
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hannah S Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jonathan A Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Fenna M Krienen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Genetics, Harvard Medical School, Boston, USA
| | - Qiangge Zhang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Naz Taskin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Guoping Feng
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Edward M Callaway
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Institute of Genomic Medicine, Moores Cancer Center, School of Medicine, University of California San Diego, La Jolla, CA, USA.
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97
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Li P, Wei J, Zhu Y. CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation. Brief Bioinform 2023; 25:bbad417. [PMID: 37995133 PMCID: PMC10790717 DOI: 10.1093/bib/bbad417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/09/2023] [Accepted: 10/29/2023] [Indexed: 11/25/2023] Open
Abstract
Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this limitation, we introduced CellGO. CellGO tackles this challenge by leveraging the visible neural network (VNN) and single-cell gene expressions to mimic cell-type-specific signaling propagation along the Gene Ontology tree within a cell. This design enables a novel scoring system to calculate the cell-type-specific gene-pathway paired active scores, based on which, CellGO is able to identify cell-type-specific active pathways associated with single genes. In addition, by aggregating the activities of single genes, CellGO extends its capability to identify cell-type-specific active pathways for a given gene set. To enhance biological interpretation, CellGO offers additional features, including the identification of significantly active cell types and driver genes and community analysis of pathways. To validate its performance, CellGO was assessed using a gene set comprising mixed cell-type markers, confirming its ability to discern active pathways across distinct cell types. Subsequent benchmarking analyses demonstrated CellGO's superiority in effectively identifying cell types and their corresponding cell-type-specific pathways affected by gene knockouts, using either single genes or sets of genes differentially expressed between knockout and control samples. Moreover, CellGO demonstrated its ability to infer cell-type-specific pathogenesis for disease risk genes. Accessible as a Python package, CellGO also provides a user-friendly web interface, making it a versatile and accessible tool for researchers in the field.
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Affiliation(s)
- Peilong Li
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
| | - Junfeng Wei
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
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98
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Zhang R, Quan H, Wang Y, Luo F. Neurogenesis in primates versus rodents and the value of non-human primate models. Natl Sci Rev 2023; 10:nwad248. [PMID: 38025664 PMCID: PMC10659238 DOI: 10.1093/nsr/nwad248] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/21/2023] [Accepted: 09/10/2023] [Indexed: 12/01/2023] Open
Abstract
Neurogenesis, the process of generating neurons from neural stem cells, occurs during both embryonic and adult stages, with each stage possessing distinct characteristics. Dysfunction in either stage can disrupt normal neural development, impair cognitive functions, and lead to various neurological disorders. Recent technological advancements in single-cell multiomics and gene-editing have facilitated investigations into primate neurogenesis. Here, we provide a comprehensive overview of neurogenesis across rodents, non-human primates, and humans, covering embryonic development to adulthood and focusing on the conservation and diversity among species. While non-human primates, especially monkeys, serve as valuable models with closer neural resemblance to humans, we highlight the potential impacts and limitations of non-human primate models on both physiological and pathological neurogenesis research.
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Affiliation(s)
- Runrui Zhang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Hongxin Quan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Yinfeng Wang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Fucheng Luo
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
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99
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Konopka G, Bhaduri A. Functional genomics and systems biology in human neuroscience. Nature 2023; 623:274-282. [PMID: 37938705 PMCID: PMC11465930 DOI: 10.1038/s41586-023-06686-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 09/27/2023] [Indexed: 11/09/2023]
Abstract
Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.
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Affiliation(s)
- Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, USA.
- Peter O'Donnell Jr Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Aparna Bhaduri
- Department of Biological Chemistry, University of California, Los Angeles, CA, USA.
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100
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Meng X, Lin Q, Zeng X, Jiang J, Li M, Luo X, Chen K, Wu H, Hu Y, Liu C, Su B. Brain developmental and cortical connectivity changes in transgenic monkeys carrying the human-specific duplicated gene SRGAP2C. Natl Sci Rev 2023; 10:nwad281. [PMID: 38090550 PMCID: PMC10712708 DOI: 10.1093/nsr/nwad281] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/18/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024] Open
Abstract
Human-specific duplicated genes contributed to phenotypic innovations during the origin of our own species, such as an enlarged brain and highly developed cognitive abilities. While prior studies on transgenic mice carrying the human-specific SRGAP2C gene have shown enhanced brain connectivity, the relevance to humans remains unclear due to the significant evolutionary gap between humans and rodents. In this study, to investigate the phenotypic outcome and underlying genetic mechanism of SRGAP2C, we generated transgenic cynomolgus macaques (Macaca fascicularis) carrying the human-specific SRGAP2C gene. Longitudinal MRI imaging revealed delayed brain development with region-specific volume changes, accompanied by altered myelination levels in the temporal and occipital regions. On a cellular level, the transgenic monkeys exhibited increased deep-layer neurons during fetal neurogenesis and delayed synaptic maturation in adolescence. Moreover, transcriptome analysis detected neotenic expression in molecular pathways related to neuron ensheathment, synaptic connections, extracellular matrix and energy metabolism. Cognitively, the transgenic monkeys demonstrated improved motor planning and execution skills. Together, our findings provide new insights into the mechanisms by which the newly evolved gene shapes the unique development and circuitry of the human brain.
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Affiliation(s)
- Xiaoyu Meng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Jin Jiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Min Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Kaimin Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Haixu Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Cirong Liu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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