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Castillo H, Hanna P, Sachs LM, Buisine N, Godoy F, Gilbert C, Aguilera F, Muñoz D, Boisvert C, Debiais-Thibaud M, Wan J, Spicuglia S, Marcellini S. Xenopus tropicalis osteoblast-specific open chromatin regions reveal promoters and enhancers involved in human skeletal phenotypes and shed light on early vertebrate evolution. Cells Dev 2024:203924. [PMID: 38692409 DOI: 10.1016/j.cdev.2024.203924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 04/18/2024] [Accepted: 04/26/2024] [Indexed: 05/03/2024]
Abstract
While understanding the genetic underpinnings of osteogenesis has far-reaching implications for skeletal diseases and evolution, a comprehensive characterization of the osteoblastic regulatory landscape in non-mammalian vertebrates is still lacking. Here, we compared the ATAC-Seq profile of Xenopus tropicalis (Xt) osteoblasts to a variety of non mineralizing control tissues, and identified osteoblast-specific nucleosome free regions (NFRs) at 527 promoters and 6747 distal regions. Sequence analyses, Gene Ontology, RNA-Seq and ChIP-Seq against four key histone marks confirmed that the distal regions correspond to bona fide osteogenic transcriptional enhancers exhibiting a shared regulatory logic with mammals. We report 425 regulatory regions conserved with human and globally associated to skeletogenic genes. Of these, 35 regions have been shown to impact human skeletal phenotypes by GWAS, including one trps1 enhancer and the runx2 promoter, two genes which are respectively involved in trichorhinophalangeal syndrome type I and cleidocranial dysplasia. Intriguingly, 60 osteoblastic NFRs also align to the genome of the elephant shark, a species lacking osteoblasts and bone tissue. To tackle this paradox, we chose to focus on dlx5 because its conserved promoter, known to integrate regulatory inputs during mammalian osteogenesis, harbours an osteoblast-specific NFR in both frog and human. Hence, we show that dlx5 is expressed in Xt and elephant shark odontoblasts, supporting a common cellular and genetic origin of bone and dentine. Taken together, our work (i) unravels the Xt osteogenic regulatory landscape, (ii) illustrates how cross-species comparisons harvest data relevant to human biology and (iii) reveals that a set of genes including bnc2, dlx5, ebf3, mir199a, nfia, runx2 and zfhx4 drove the development of a primitive form of mineralized skeletal tissue deep in the vertebrate lineage.
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Affiliation(s)
- Héctor Castillo
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile.
| | - Patricia Hanna
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile
| | - Laurent M Sachs
- UMR7221, Physiologie Moléculaire et Adaptation, CNRS, MNHN, Paris Cedex 05, France
| | - Nicolas Buisine
- UMR7221, Physiologie Moléculaire et Adaptation, CNRS, MNHN, Paris Cedex 05, France
| | - Francisco Godoy
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile
| | - Clément Gilbert
- Université Paris-Saclay, CNRS, IRD, UMR Évolution, Génomes, Comportement et Écologie, 12 route 128, 91190 Gif-sur-Yvette, France
| | - Felipe Aguilera
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile
| | - David Muñoz
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile
| | - Catherine Boisvert
- School of Molecular and Life Sciences, Curtin University, Perth, WA, Australia
| | - Mélanie Debiais-Thibaud
- Institut des Sciences de l'Evolution de Montpellier, ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France
| | - Jing Wan
- Aix-Marseille University, INSERM, TAGC, UMR 1090, Marseille, France; Equipe Labelisée LIGUE contre le Cancer, Marseille, France
| | - Salvatore Spicuglia
- Aix-Marseille University, INSERM, TAGC, UMR 1090, Marseille, France; Equipe Labelisée LIGUE contre le Cancer, Marseille, France
| | - Sylvain Marcellini
- Group for the Study of Developmental Processes (GDeP), School of Biological Sciences, University of Concepción, Chile.
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Hu P, Zhang G, Ba H, Ren J, Li J, Wang Z, Li C. Reciprocal negative feedback between Prrx1 and miR-140-3p regulates rapid chondrogenesis in the regenerating antler. Cell Mol Biol Lett 2024; 29:56. [PMID: 38643083 PMCID: PMC11031908 DOI: 10.1186/s11658-024-00573-x] [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: 11/07/2023] [Accepted: 04/05/2024] [Indexed: 04/22/2024] Open
Abstract
During growth phase, antlers exhibit a very rapid rate of chondrogenesis. The antler is formed from its growth center reserve mesenchyme (RM) cells, which have been found to be the derivatives of paired related homeobox 1 (Prrx1)-positive periosteal cells. However, the underlying mechanism that drives rapid chondrogenesis is not known. Herein, the miRNA expression profiles and chromatin states of three tissue layers (RM, precartilage, and cartilage) at different stages of differentiation within the antler growth center were analyzed by RNA-sequencing and ATAC-sequencing. We found that miR-140-3p was the miRNA that exhibited the greatest degree of upregulation in the rapidly growing antler, increasing from the RM to the cartilage layer. We also showed that Prrx1 was a key upstream regulator of miR-140-3p, which firmly confirmed by Prrx1 CUT&Tag sequencing of RM cells. Through multiple approaches (three-dimensional chondrogenic culture and xenogeneic antler model), we demonstrated that Prrx1 and miR-140-3p functioned as reciprocal negative feedback in the antler growth center, and downregulating PRRX1/upregulating miR-140-3p promoted rapid chondrogenesis of RM cells and xenogeneic antler. Thus, we conclude that the reciprocal negative feedback between Prrx1 and miR-140-3p is essential for balancing mesenchymal proliferation and chondrogenic differentiation in the regenerating antler. We further propose that the mechanism underlying chondrogenesis in the regenerating antler would provide a reference for helping understand the regulation of human cartilage regeneration and repair.
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Affiliation(s)
- Pengfei Hu
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China.
- Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, China.
| | - Guokun Zhang
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China
| | - Hengxing Ba
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China
| | - Jing Ren
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China
| | - Jiping Li
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China
| | - Zhen Wang
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China
| | - Chunyi Li
- Institute of Antler Science and Product Technology, Changchun Sci-Tech University, Changchun, China.
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3
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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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4
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Cox LA, Puppala S, Chan J, Zimmerman KD, Hamid Z, Ampong I, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Baxter MG, Shively C, Clarke GD, Register TC, Nathanielsz PW, Olivier M. Integrated multi-omics analysis of brain aging in female nonhuman primates reveals altered signaling pathways relevant to age-related disorders. Neurobiol Aging 2023; 132:109-119. [PMID: 37797463 PMCID: PMC10841409 DOI: 10.1016/j.neurobiolaging.2023.08.009] [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: 04/20/2023] [Revised: 08/25/2023] [Accepted: 08/27/2023] [Indexed: 10/07/2023]
Abstract
The prefrontal cortex (PFC) has been implicated as a key brain region responsible for age-related cognitive decline. Little is known about aging-related molecular changes in PFC that may mediate these effects. To date, no studies have used untargeted discovery methods with integrated analyses to determine PFC molecular changes in healthy female primates. We quantified PFC changes associated with healthy aging in female baboons by integrating multiple omics data types (transcriptomics, proteomics, metabolomics) from samples across the adult age span. Our integrated omics approach using unbiased weighted gene co-expression network analysis to integrate data and treat age as a continuous variable, revealed highly interconnected known and novel pathways associated with PFC aging. We found Gamma-aminobutyric acid (GABA) tissue content associated with these signaling pathways, providing 1 potential biomarker to assess PFC changes with age. These highly coordinated pathway changes during aging may represent early steps for aging-related decline in PFC functions, such as learning and memory, and provide potential biomarkers to assess cognitive status in humans.
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Affiliation(s)
- Laura A Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA; Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA; Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA.
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Kip D Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Zeeshan Hamid
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Isaac Ampong
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Hillary F Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Avinash Y L Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, USA
| | - Mark G Baxter
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Carol Shively
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Geoffrey D Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Thomas C Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Peter W Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, WY, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA; Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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5
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Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, Ball G, Hansson O, Hernandez LM, Mandal AS, Wagstyl K, Lombardo MV, Courchesne E, Glessner JT, Satterthwaite TD, Bethlehem RAI, Bernstock JD, Tasaki S, Ng B, Gaiteri C, Smoller JW, Ge T, Gur RE, Gandal MJ, Alexander-Bloch AF. The molecular genetic landscape of human brain size variation. Cell Rep 2023; 42:113439. [PMID: 37963017 DOI: 10.1016/j.celrep.2023.113439] [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: 11/09/2022] [Revised: 06/13/2023] [Accepted: 10/27/2023] [Indexed: 11/16/2023] Open
Abstract
Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.
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Affiliation(s)
- Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Jacob W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Younga H Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK; Department of Psychology, University of Cambridge, Cambridge CB2 1TN, UK
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Melbourne, VIC 3052, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö P663+Q9, Sweden; Memory Clinic, Skåne University Hospital, Malmö P663+Q9, Sweden
| | - Leanna M Hernandez
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Ayan S Mandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92093, USA
| | - Joseph T Glessner
- The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | | | - Joshua D Bernstock
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard University, Boston, MA 02115, USA; Department of Neurosurgery, Boston Children's Hospital, Harvard University, Boston, MA 02115, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Bernard Ng
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raquel E Gur
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael J Gandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
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Kabbej N, Ashby FJ, Riva A, Gamlin PD, Mandel RJ, Kunta A, Rouse CJ, Heldermon CD. Sex differences in brain transcriptomes of juvenile Cynomolgus macaques. RESEARCH SQUARE 2023:rs.3.rs-3422091. [PMID: 38045237 PMCID: PMC10690328 DOI: 10.21203/rs.3.rs-3422091/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Background: Behavioral, social, and physical characteristics are posited to distinguish the sexes, yet research on transcription-level sexual differences in the brain is limited. Here, we investigated sexually divergent brain transcriptomics in prepubertal cynomolgus macaques, a commonly used surrogate species to humans. Methods: A transcriptomic profile using RNA sequencing was generated for the temporal lobe, ventral midbrain, and cerebellum of 3 female and 3 male cynomolgus macaques previously treated with an Adeno-associated virus vector mix. Statistical analyses to determine differentially expressed protein-coding genes in all three lobes were conducted using DeSeq2 with a false discovery rate corrected P value of .05. Results: We identified target genes in the temporal lobe, ventral midbrain, and cerebellum with functions in translation, immunity, behavior, and neurological disorders that exhibited statistically significant sexually divergent expression. Conclusions: We provide potential mechanistic insights to the epidemiological differences observed between the sexes with regards to mental health and infectious diseases, such as COVID19. Our results provide pre-pubertal information on sexual differences in non-human primate brain transcriptomics and may provide insight to health disparities between the biological sexes in humans.
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Li L, Liu Z. Genetic Approaches for Neural Circuits Dissection in Non-human Primates. Neurosci Bull 2023; 39:1561-1576. [PMID: 37258795 PMCID: PMC10533465 DOI: 10.1007/s12264-023-01067-0] [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: 12/29/2022] [Accepted: 03/27/2023] [Indexed: 06/02/2023] Open
Abstract
Genetic tools, which can be used for the morphology study of specific neurons, pathway-selective connectome mapping, neuronal activity monitoring, and manipulation with a spatiotemporal resolution, have been widely applied to the understanding of complex neural circuit formation, interactions, and functions in rodents. Recently, similar genetic approaches have been tried in non-human primates (NHPs) in neuroscience studies for dissecting the neural circuits involved in sophisticated behaviors and clinical brain disorders, although they are still very preliminary. In this review, we introduce the progress made in the development and application of genetic tools for brain studies on NHPs. We also discuss the advantages and limitations of each approach and provide a perspective for using genetic tools to study the neural circuits of NHPs.
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Affiliation(s)
- Ling Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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8
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Wei J, Dai S, Yan Y, Li S, Yang P, Zhu R, Huang T, Li X, Duan Y, Wang Z, Ji W, Si W. Spatiotemporal proteomic atlas of multiple brain regions across early fetal to neonatal stages in cynomolgus monkey. Nat Commun 2023; 14:3917. [PMID: 37400444 PMCID: PMC10317979 DOI: 10.1038/s41467-023-39411-7] [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: 10/14/2022] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
Fetal stages are critical periods for brain development. However, the protein molecular signature and dynamics of the human brain remain unclear due to sampling difficulty and ethical limitations. Non-human primates present similar developmental and neuropathological features to humans. This study constructed a spatiotemporal proteomic atlas of cynomolgus macaque brain development from early fetal to neonatal stages. Here we showed that (1) the variability across stages was greater than that among brain regions, and comparisons of cerebellum vs. cerebrum and cortical vs. subcortical regions revealed region-specific dynamics across early fetal to neonatal stages; (2) fluctuations in abundance of proteins associated with neural disease suggest the risk of nervous disorder at early fetal stages; (3) cross-species analysis (human, monkey, and mouse) and comparison between proteomic and transcriptomic data reveal the proteomic specificity and genes with mRNA/protein discrepancy. This study provides insight into fetal brain development in primates.
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Affiliation(s)
- Jingkuan Wei
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Shaoxing Dai
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Yaping Yan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Shulin Li
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Pengpeng Yang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Ran Zhu
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Tianzhuang Huang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Xi Li
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Yanchao Duan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Zhengbo Wang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
- Chinese Primate Biomedical Research Alliance (CPBRA), 650500, Kunming, Yunnan, China.
| | - Wei Si
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
- Chinese Primate Biomedical Research Alliance (CPBRA), 650500, Kunming, Yunnan, China.
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9
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Lu Z, Li J, Lu Y, Li L, Wang W, Zhang C, Xu L, Nie Y, Gao C, Bian X, Liu Z, Wang GZ, Sun Q. Cynomolgus-rhesus hybrid macaques serve as a platform for imprinting studies. Innovation (N Y) 2023; 4:100436. [PMID: 37215523 PMCID: PMC10196704 DOI: 10.1016/j.xinn.2023.100436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 04/25/2023] [Indexed: 05/24/2023] Open
Abstract
Genomic imprinting can lead to allele-specific expression (ASE), where one allele is preferentially expressed more than the other. Perturbations in genomic imprinting or ASE genes have been widely observed across various neurological disorders, notably autism spectrum disorder (ASD). In this study, we crossed rhesus cynomolgus monkeys to produce hybrid monkeys and established a framework to evaluate their allele-specific gene expression patterns using the parental genomes as a reference. Our proof-of-concept analysis of the hybrid monkeys identified 353 genes with allele-biased expression in the brain, enabling us to determine the chromosomal locations of ASE clusters. Importantly, we confirmed a significant enrichment of ASE genes associated with neuropsychiatric disorders, including ASD, highlighting the potential of hybrid monkey models in advancing our understanding of genomic imprinting.
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Affiliation(s)
- Zongyang Lu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
| | - Jie Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Lu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ling Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
| | - Wei Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chenchen Zhang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Libing Xu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanhong Nie
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Changshan Gao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xinyan Bian
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qiang Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
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10
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Hawes CE, Elizaldi SR, Beckman D, Diniz GB, Shaan Lakshmanappa Y, Ott S, Durbin-Johnson BP, Dinasarapu AR, Gompers A, Morrison JH, Iyer SS. Neuroinflammatory transcriptional programs induced in rhesus pre-frontal cortex white matter during acute SHIV infection. J Neuroinflammation 2022; 19:250. [PMID: 36203187 PMCID: PMC9535930 DOI: 10.1186/s12974-022-02610-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 09/12/2022] [Indexed: 11/10/2022] Open
Abstract
Background Immunosurveillance of the central nervous system (CNS) is vital to resolve infection and injury. However, immune activation within the CNS in the setting of chronic viral infections, such as HIV-1, is strongly linked to progressive neurodegeneration and cognitive decline. Establishment of HIV-1 in the CNS early following infection underscores the need to delineate features of acute CNS immune activation, as these early inflammatory events may mediate neurodegenerative processes. Here, we focused on elucidating molecular programs of neuroinflammation in brain regions based on vulnerability to neuroAIDS and/or neurocognitive decline. To this end, we assessed transcriptional profiles within the subcortical white matter of the pre-frontal cortex (PFCw), as well as synapse dense regions from hippocampus, superior temporal cortex, and caudate nucleus, in rhesus macaques following infection with Simian/Human Immunodeficiency Virus (SHIV.C.CH505). Methods We performed RNA extraction and sequenced RNA isolated from 3 mm brain punches. Viral RNA was quantified in the brain and cerebrospinal fluid by RT-qPCR assays targeting SIV Gag. Neuroinflammation was assessed by flow cytometry and multiplex ELISA assays. Results RNA sequencing and flow cytometry data demonstrated immune surveillance of the rhesus CNS by innate and adaptive immune cells during homeostasis. Following SHIV infection, viral entry and integration within multiple brain regions demonstrated vulnerabilities of key cognitive and motor function brain regions to HIV-1 during the acute phase of infection. SHIV-induced transcriptional alterations were concentrated to the PFCw and STS with upregulation of gene expression pathways controlling innate and T-cell inflammatory responses. Within the PFCw, gene modules regulating microglial activation and T cell differentiation were induced at 28 days post-SHIV infection, with evidence for stimulation of immune effector programs characteristic of neuroinflammation. Furthermore, enrichment of pathways regulating mitochondrial respiratory capacity, synapse assembly, and oxidative and endoplasmic reticulum stress were observed. These acute neuroinflammatory features were substantiated by increased influx of activated T cells into the CNS. Conclusions Our data show pervasive immune surveillance of the rhesus CNS at homeostasis and reveal perturbations of important immune, neuronal, and synaptic pathways within key anatomic regions controlling cognition and motor function during acute HIV infection. These findings provide a valuable framework to understand early molecular features of HIV associated neurodegeneration. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02610-y.
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Affiliation(s)
- Chase E Hawes
- Graduate Group in Immunology, University of California, Davis, CA, 95616, USA.,Center for Immunology and Infectious Diseases, University of California, Davis, CA, 95616, USA
| | - Sonny R Elizaldi
- Graduate Group in Immunology, University of California, Davis, CA, 95616, USA.,Center for Immunology and Infectious Diseases, University of California, Davis, CA, 95616, USA
| | - Danielle Beckman
- California National Primate Research Center, University of California, Davis, CA, 95616, USA
| | - Giovanne B Diniz
- California National Primate Research Center, University of California, Davis, CA, 95616, USA
| | | | - Sean Ott
- California National Primate Research Center, University of California, Davis, CA, 95616, USA
| | - Blythe P Durbin-Johnson
- Division of Biostatistics, School of Medicine, University of California, Davis, CA, 95616, USA
| | | | - Andrea Gompers
- Center for Immunology and Infectious Diseases, University of California, Davis, CA, 95616, USA
| | - John H Morrison
- California National Primate Research Center, University of California, Davis, CA, 95616, USA. .,Department of Neurology, School of Medicine, University of California, Davis, CA, 95616, USA.
| | - Smita S Iyer
- Center for Immunology and Infectious Diseases, University of California, Davis, CA, 95616, USA. .,California National Primate Research Center, University of California, Davis, CA, 95616, USA. .,Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA.
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11
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Billon V, Sanchez-Luque FJ, Rasmussen J, Bodea GO, Gerhardt DJ, Gerdes P, Cheetham SW, Schauer SN, Ajjikuttira P, Meyer TJ, Layman CE, Nevonen KA, Jansz N, Garcia-Perez JL, Richardson SR, Ewing AD, Carbone L, Faulkner GJ. Somatic retrotransposition in the developing rhesus macaque brain. Genome Res 2022; 32:1298-1314. [PMID: 35728967 PMCID: PMC9341517 DOI: 10.1101/gr.276451.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/14/2022] [Indexed: 12/03/2022]
Abstract
The retrotransposon LINE-1 (L1) is central to the recent evolutionary history of the human genome and continues to drive genetic diversity and germline pathogenesis. However, the spatiotemporal extent and biological significance of somatic L1 activity are poorly defined and are virtually unexplored in other primates. From a single L1 lineage active at the divergence of apes and Old World monkeys, successive L1 subfamilies have emerged in each descendant primate germline. As revealed by case studies, the presently active human L1 subfamily can also mobilize during embryonic and brain development in vivo. It is unknown whether nonhuman primate L1s can similarly generate somatic insertions in the brain. Here we applied approximately 40× single-cell whole-genome sequencing (scWGS), as well as retrotransposon capture sequencing (RC-seq), to 20 hippocampal neurons from two rhesus macaques (Macaca mulatta). In one animal, we detected and PCR-validated a somatic L1 insertion that generated target site duplications, carried a short 5′ transduction, and was present in ∼7% of hippocampal neurons but absent from cerebellum and nonbrain tissues. The corresponding donor L1 allele was exceptionally mobile in vitro and was embedded in PRDM4, a gene expressed throughout development and in neural stem cells. Nanopore long-read methylome and RNA-seq transcriptome analyses indicated young retrotransposon subfamily activation in the early embryo, followed by repression in adult tissues. These data highlight endogenous macaque L1 retrotransposition potential, provide prototypical evidence of L1-mediated somatic mosaicism in a nonhuman primate, and allude to L1 mobility in the brain over the past 30 million years of human evolution.
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12
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Medalla M, Chang W, Ibañez S, Guillamon-Vivancos T, Nittmann M, Kapitonava A, Busch SE, Moore TL, Rosene DL, Luebke JI. Layer-specific pyramidal neuron properties underlie diverse anterior cingulate cortical motor and limbic networks. Cereb Cortex 2022; 32:2170-2196. [PMID: 34613380 PMCID: PMC9113240 DOI: 10.1093/cercor/bhab347] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 11/13/2022] Open
Abstract
The laminar cellular and circuit mechanisms by which the anterior cingulate cortex (ACC) exerts flexible control of motor and affective information for goal-directed behavior have not been elucidated. Using multimodal tract-tracing, in vitro patch-clamp recording and computational approaches in rhesus monkeys (M. mulatta), we provide evidence that specialized motor and affective network dynamics can be conferred by layer-specific biophysical and structural properties of ACC pyramidal neurons targeting two key downstream structures -the dorsal premotor cortex (PMd) and the amygdala (AMY). AMY-targeting neurons exhibited significant laminar differences, with L5 more excitable (higher input resistance and action potential firing rates) than L3 neurons. Between-pathway differences were found within L5, with AMY-targeting neurons exhibiting greater excitability, apical dendritic complexity, spine densities, and diversity of inhibitory inputs than PMd-targeting neurons. Simulations using a pyramidal-interneuron network model predict that these layer- and pathway-specific single-cell differences contribute to distinct network oscillatory dynamics. L5 AMY-targeting networks are more tuned to slow oscillations well-suited for affective and contextual processing timescales, while PMd-targeting networks showed strong beta/gamma synchrony implicated in rapid sensorimotor processing. These findings are fundamental to our broad understanding of how layer-specific cellular and circuit properties can drive diverse laminar activity found in flexible behavior.
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Affiliation(s)
- Maria Medalla
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Wayne Chang
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Sara Ibañez
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Teresa Guillamon-Vivancos
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Instituto de Neurociencias de Alicante, Alicante, Spain
| | - Mathias Nittmann
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- University of South Florida, Morsani College of Medicine, Tampa, FL, 33612, USA
| | - Anastasia Kapitonava
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Silas E Busch
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Department of Neurobiology, University of Chicago, Chicago, IL, 60637, USA
| | - Tara L Moore
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Douglas L Rosene
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Jennifer I Luebke
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, 02118, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA
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13
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Cheng L, Wang H, Maboh R, Mao G, Wu X, Chen H. LncRNA LINC00281/Annexin A2 Regulates Vascular Smooth Muscle Cell Phenotype Switching via the Nuclear Factor-Kappa B Signaling Pathway. J Cardiovasc Transl Res 2022; 15:971-984. [PMID: 35478454 DOI: 10.1007/s12265-022-10242-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 03/21/2022] [Indexed: 12/28/2022]
Abstract
Abnormal phenotype switch in vascular smooth muscle cells (VSMCs) plays an important role in the initiation and progression of vascular proliferative diseases. Annexin A2 (ANXA2), related to the pro-inflammatory response, contributes to the proliferation and migration of VSMCs. This study explored the mechanisms involved in the regulation of VSMC phenotype modulation via ANXA2. The results revealed that ANXA2 promotes the phosphorylation of p65 and co-translocates with p65 into the nucleus, resulting in VSMC proliferation, migration, and dedifferentiation. Based on bioinformatics predictions and RNA immunoprecipitation assays, LINC00281 was confirmed to be an upstream regulator of ANXA2. Taken together, ANXA2, which is negatively regulated by the long noncoding RNA (lncRNA) LINC00281, has significant importance in the regulation of VSMC proliferation, migration, and phenotype switching via the nuclear factor-kappa B (NF-кB) p65 signaling pathway. This indicates that the lncRNA LINC00281/ANXA2/NF-кB p65 signaling pathway might be a new therapeutic target for vascular proliferative diseases.
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Affiliation(s)
- Lan Cheng
- The Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
| | - Huan Wang
- Hypertension Laboratory, Fujian Provincial Cardiovascular Disease Institute, Fujian Provincial Hospital, Fuzhou, 350001, China
| | - ReneNfornah Maboh
- The Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
| | - Gaowei Mao
- The Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
| | - Xiaoying Wu
- Hypertension Laboratory, Fujian Provincial Cardiovascular Disease Institute, Fujian Provincial Hospital, Fuzhou, 350001, China
| | - Hui Chen
- The Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China. .,Hypertension Laboratory, Fujian Provincial Cardiovascular Disease Institute, Fujian Provincial Hospital, Fuzhou, 350001, China.
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14
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Qin T, Lee C, Li S, Cavalcante RG, Orchard P, Yao H, Zhang H, Wang S, Patil S, Boyle AP, Sartor MA. Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data. Genome Biol 2022; 23:105. [PMID: 35473573 PMCID: PMC9044877 DOI: 10.1186/s13059-022-02668-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 04/06/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks. RESULTS The top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs. CONCLUSIONS Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.
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Affiliation(s)
- Tingting Qin
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
| | - Christopher Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Biostatistics, School of Public Health, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Shiting Li
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Raymond G Cavalcante
- Biomedical Research Core Facilities, Epigenomics Core, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Heming Yao
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Hanrui Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Shuze Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Snehal Patil
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Alan P Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Maureen A Sartor
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
- Department of Biostatistics, School of Public Health, University of Michigan Medical School, Ann Arbor, MI, USA.
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15
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Mandino F, Vrooman RM, Foo HE, Yeow LY, Bolton TAW, Salvan P, Teoh CL, Lee CY, Beauchamp A, Luo S, Bi R, Zhang J, Lim GHT, Low N, Sallet J, Gigg J, Lerch JP, Mars RB, Olivo M, Fu Y, Grandjean J. A triple-network organization for the mouse brain. Mol Psychiatry 2022; 27:865-872. [PMID: 34650202 PMCID: PMC9054663 DOI: 10.1038/s41380-021-01298-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/21/2021] [Accepted: 09/08/2021] [Indexed: 01/21/2023]
Abstract
The triple-network model of psychopathology is a framework to explain the functional and structural neuroimaging phenotypes of psychiatric and neurological disorders. It describes the interactions within and between three distributed networks: the salience, default-mode, and central executive networks. These have been associated with brain disorder traits in patients. Homologous networks have been proposed in animal models, but their integration into a triple-network organization has not yet been determined. Using resting-state datasets, we demonstrate conserved spatio-temporal properties between triple-network elements in human, macaque, and mouse. The model predictions were also shown to apply in a mouse model for depression. To validate spatial homologies, we developed a data-driven approach to convert mouse brain maps into human standard coordinates. Finally, using high-resolution viral tracers in the mouse, we refined an anatomical model for these networks and validated this using optogenetics in mice and tractography in humans. Unexpectedly, we find serotonin involvement within the salience rather than the default-mode network. Our results support the existence of a triple-network system in the mouse that shares properties with that of humans along several dimensions, including a disease condition. Finally, we demonstrate a method to humanize mouse brain networks that opens doors to fully data-driven trans-species comparisons.
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Affiliation(s)
- Francesca Mandino
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore ,grid.5379.80000000121662407Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK ,grid.47100.320000000419368710Department of Radiology and Bioimaging Sciences, Yale School of Medicine, New Haven, CT USA
| | - Roël M. Vrooman
- grid.10417.330000 0004 0444 9382Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Heidi E. Foo
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore ,grid.1005.40000 0004 4902 0432Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, Sydney, NSW 2052 Australia
| | - Ling Yun Yeow
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Thomas A. W. Bolton
- grid.8515.90000 0001 0423 4662Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Piergiorgio Salvan
- grid.8348.70000 0001 2306 7492Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Chai Lean Teoh
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Chun Yao Lee
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Antoine Beauchamp
- grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Sarah Luo
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Renzhe Bi
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Jiayi Zhang
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore ,grid.59025.3b0000 0001 2224 0361Centre for Research and Development in Learning, Nanyang Technological University, 61 Nanyang Drive, Level 1, Singapore, 637460 Singapore
| | - Guan Hui Tricia Lim
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore ,grid.83440.3b0000000121901201University College London Medical School, University College London, London, UK
| | - Nathaniel Low
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Jerome Sallet
- grid.8348.70000 0001 2306 7492Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK ,grid.457382.fUniv Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - John Gigg
- grid.5379.80000000121662407Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Jason P. Lerch
- grid.8348.70000 0001 2306 7492Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Rogier B. Mars
- grid.8348.70000 0001 2306 7492Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Malini Olivo
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Yu Fu
- grid.452254.00000 0004 0393 4167Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667 Singapore
| | - Joanes Grandjean
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, Singapore, 138667, Singapore. .,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands. .,Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
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16
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He J, Kleyman M, Chen J, Alikaya A, Rothenhoefer KM, Ozturk BE, Wirthlin M, Bostan AC, Fish K, Byrne LC, Pfenning AR, Stauffer WR. Transcriptional and anatomical diversity of medium spiny neurons in the primate striatum. Curr Biol 2021; 31:5473-5486.e6. [PMID: 34727523 PMCID: PMC9359438 DOI: 10.1016/j.cub.2021.10.015] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/17/2021] [Accepted: 10/06/2021] [Indexed: 10/20/2022]
Abstract
Medium spiny neurons (MSNs) constitute the vast majority of striatal neurons and the principal interface between dopamine reward signals and functionally diverse cortico-basal ganglia circuits. Information processing in these circuits is dependent on distinct MSN types: cell types that are traditionally defined according to their projection targets or dopamine receptor expression. Single-cell transcriptional studies have revealed greater MSN heterogeneity than predicted by traditional circuit models, but the transcriptional landscape in the primate striatum remains unknown. Here, we set out to establish molecular definitions for MSN subtypes in Rhesus monkeys and to explore the relationships between transcriptionally defined subtypes and anatomical subdivisions of the striatum. Our results suggest at least nine MSN subtypes, including dorsal striatum subtypes associated with striosome and matrix compartments, ventral striatum subtypes associated with the nucleus accumbens shell and olfactory tubercle, and an MSN-like cell type restricted to μ-opioid receptor rich islands in the ventral striatum. Although each subtype was demarcated by discontinuities in gene expression, continuous variation within subtypes defined gradients corresponding to anatomical locations and, potentially, functional specializations. These results lay the foundation for achieving cell-type-specific transgenesis in the primate striatum and provide a blueprint for investigating circuit-specific information processing.
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Affiliation(s)
- Jing He
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Michael Kleyman
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
| | - Jianjiao Chen
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Aydin Alikaya
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Kathryn M Rothenhoefer
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Bilge Esin Ozturk
- Department of Ophthalmology, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Morgan Wirthlin
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
| | - Andreea C Bostan
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Kenneth Fish
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Leah C Byrne
- Department of Ophthalmology, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Andreas R Pfenning
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.
| | - William R Stauffer
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA.
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17
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Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, Feng T, Zhou L, Tang W, Zhan L, Fu X, Liu S, Bo X, Yu G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (N Y) 2021; 2:100141. [PMID: 34557778 PMCID: PMC8454663 DOI: 10.1016/j.xinn.2021.100141] [Citation(s) in RCA: 2512] [Impact Index Per Article: 837.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 06/29/2021] [Indexed: 12/15/2022] Open
Abstract
Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms. clusterProfiler supports exploring functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation It provides a universal interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions
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Affiliation(s)
- Tianzhi Wu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Erqiang Hu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Shuangbin Xu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Meijun Chen
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Pingfan Guo
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Zehan Dai
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Tingze Feng
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Lang Zhou
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Wenli Tang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Li Zhan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiaocong Fu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Shanshan Liu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiaochen Bo
- Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China
| | - Guangchuang Yu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.,Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.,Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
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18
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Evolutionary Changes in Pathways and Networks of Genes Expressed in the Brains of Humans and Macaques. J Mol Neurosci 2021; 71:1825-1837. [PMID: 34191269 DOI: 10.1007/s12031-021-01874-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/15/2021] [Indexed: 10/21/2022]
Abstract
As the key organ that separates humans from nonhuman primates, the brain has continuously evolved to adapt to environmental and climatic changes. Although humans share most genetic, molecular, and cellular features with other primates such as macaques, there are significant differences in the structure and function of the brain between humans and these species. Thus, exploring the differences between the brains of human and nonhuman primates in the context of evolution will provide insights into the development, functionality, and diseases of the human central nervous system (CNS). Since the genes involved in many aspects of the human brain are under common pressures of natural selection, their evolutionary features can be analyzed collectively at the pathway level. In this study, the molecular mechanisms underlying human brain capabilities were explored by comparing the evolution features of pathways enriched in genes expressed in the human brain and the macaque brain. We identified 31 pathways with differential evolutionary properties, including those related to neurological diseases, signal transduction, immunological response, and metabolic processes. By analyzing genes differentially expressed in brain regions or development stages between humans and macaques, 9 and 4 pathways with differential evolutionary properties were detected, respectively. We further performed crosstalk analysis on the pathways to obtain an intuitive correlation between the pathways, which is helpful in understanding the mechanisms of interaction between pathways. Our results provide on a comprehensive view of the evolutionary pathways of the human CNS and can serve as a reference for the study of human brain development.
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19
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Different Flavors of Astrocytes: Revising the Origins of Astrocyte Diversity and Epigenetic Signatures to Understand Heterogeneity after Injury. Int J Mol Sci 2021; 22:ijms22136867. [PMID: 34206710 PMCID: PMC8268487 DOI: 10.3390/ijms22136867] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 05/31/2021] [Accepted: 06/02/2021] [Indexed: 12/11/2022] Open
Abstract
Astrocytes are a specific type of neuroglial cells that confer metabolic and structural support to neurons. Astrocytes populate all regions of the nervous system and adopt a variety of phenotypes depending on their location and their respective functions, which are also pleiotropic in nature. For example, astrocytes adapt to pathological conditions with a specific cellular response known as reactive astrogliosis, which includes extensive phenotypic and transcriptional changes. Reactive astrocytes may lose some of their homeostatic functions and gain protective or detrimental properties with great impact on damage propagation. Different astrocyte subpopulations seemingly coexist in reactive astrogliosis, however, the source of such heterogeneity is not completely understood. Altered cellular signaling in pathological compared to healthy conditions might be one source fueling astrocyte heterogeneity. Moreover, diversity might also be encoded cell-autonomously, for example as a result of astrocyte subtype specification during development. We hypothesize and propose here that elucidating the epigenetic signature underlying the phenotype of each astrocyte subtype is of high relevance to understand another regulative layer of astrocyte heterogeneity, in general as well as after injury or as a result of other pathological conditions. High resolution methods should allow enlightening diverse cell states and subtypes of astrocyte, their adaptation to pathological conditions and ultimately allow controlling and manipulating astrocyte functions in disease states. Here, we review novel literature reporting on astrocyte diversity from a developmental perspective and we focus on epigenetic signatures that might account for cell type specification.
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20
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Egervari G. Chromatin accessibility in neuropsychiatric disorders. Neurobiol Learn Mem 2021; 181:107438. [PMID: 33845131 DOI: 10.1016/j.nlm.2021.107438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/02/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
Epigenetic mechanisms have recently emerged as critical regulators of brain function in health and disease. By controlling the accessibility and the expression of specific genes, these pathways can mediate transient and long-lasting changes in neuronal function in both physiological and pathological contexts. Due to the extreme complexity of the epigenetic regulatory landscape, emerging methods that directly assay chromatin accessibility are of particular interest. Here, I review recent insights gained on open and closed chromatin states in the brain, with emphasis on neuropsychiatric disorders. These advances generated an invaluable wealth of information that can help us better understand gene regulation in the brain and its impairments that contribute to the development of disease.
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Affiliation(s)
- Gabor Egervari
- Epigenetics Institute, Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.
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21
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Pei W, Fu L, Li SQ, Yu Y. Brain transcriptomics of nonhuman primates: A review. Neurosci Lett 2021; 753:135872. [PMID: 33812931 DOI: 10.1016/j.neulet.2021.135872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/29/2021] [Accepted: 03/29/2021] [Indexed: 11/12/2022]
Abstract
The brain is one of the most important and intricate organs in our bodies. Interpreting brain function and illustrating the changes and molecular mechanisms during physiological or pathological processes are essential but sometimes difficult to achieve. In addition to histology, ethology and pharmacology, the development of transcriptomics alleviates this condition by enabling high-throughput observation of the brain at various levels of anatomical specificity. Moreover, because human brain samples are scarce, the brains of nonhuman primates are important alternative models. Here in this review, we summarize the applications of transcriptomics in nonhuman primate brain studies, including investigations of brain development, aging, toxic effects and diseases. Overall, as a powerful tool with developmental potential, transcriptomics has been widely utilized in neuroscience.
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Affiliation(s)
- Wendi Pei
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology and Key Laboratory of Assisted Reproduction, Ministry of Education, Peking University Third Hospital, Beijing, 100191, China
| | - Lin Fu
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology and Key Laboratory of Assisted Reproduction, Ministry of Education, Peking University Third Hospital, Beijing, 100191, China
| | - Shui-Qing Li
- Department of Pain, Peking University Third Hospital, Beijing, 100191, China.
| | - Yang Yu
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology and Key Laboratory of Assisted Reproduction, Ministry of Education, Peking University Third Hospital, Beijing, 100191, China; Clinical Stem Cell Research Center, Peking University Third Hospital, Beijing, 100191, China.
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