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Badal KK, Sadhu A, Raveendra BL, McCracken C, Lozano-Villada S, Shetty AC, Gillette P, Zhao Y, Stommes D, Fieber LA, Schmale MC, Mahurkar A, Hawkins RD, Puthanveettil SV. Single-neuron analysis of aging-associated changes in learning reveals impairments in transcriptional plasticity. Aging Cell 2024:e14228. [PMID: 38924663 DOI: 10.1111/acel.14228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Accepted: 05/02/2024] [Indexed: 06/28/2024] Open
Abstract
The molecular mechanisms underlying age-related declines in learning and long-term memory are still not fully understood. To address this gap, our study focused on investigating the transcriptional landscape of a singularly identified motor neuron L7 in Aplysia, which is pivotal in a specific type of nonassociative learning known as sensitization of the siphon-withdraw reflex. Employing total RNAseq analysis on a single isolated L7 motor neuron after short-term or long-term sensitization (LTS) training of Aplysia at 8, 10, and 12 months (representing mature, late mature, and senescent stages), we uncovered aberrant changes in transcriptional plasticity during the aging process. Our findings specifically highlight changes in the expression of messenger RNAs (mRNAs) that encode transcription factors, translation regulators, RNA methylation participants, and contributors to cytoskeletal rearrangements during learning and long noncoding RNAs (lncRNAs). Furthermore, our comparative gene expression analysis identified distinct transcriptional alterations in two other neurons, namely the motor neuron L11 and the giant cholinergic neuron R2, whose roles in LTS are not yet fully elucidated. Taken together, our analyses underscore cell type-specific impairments in the expression of key components related to learning and memory within the transcriptome as organisms age, shedding light on the complex molecular mechanisms driving cognitive decline during aging.
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Affiliation(s)
- Kerriann K Badal
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
- Integrated Biology Graduate Program, Florida Atlantic University, Jupiter, Florida, USA
| | - Abhishek Sadhu
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
| | - Bindu L Raveendra
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
| | - Carrie McCracken
- The Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Sebastian Lozano-Villada
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
- Harriet L. Wilkes Honors College, Florida Atlantic University, Jupiter, Florida, USA
| | - Amol C Shetty
- The Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Phillip Gillette
- National Resource for Aplysia, University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Sciences, Miami, Florida, USA
| | - Yibo Zhao
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
| | - Dustin Stommes
- National Resource for Aplysia, University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Sciences, Miami, Florida, USA
| | - Lynne A Fieber
- National Resource for Aplysia, University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Sciences, Miami, Florida, USA
| | - Michael C Schmale
- National Resource for Aplysia, University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Sciences, Miami, Florida, USA
| | - Anup Mahurkar
- The Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Robert D Hawkins
- Department of Neuroscience, Columbia University, New York, New York, USA
- New York State Psychiatric Institute, New York, New York, USA
| | - Sathyanarayanan V Puthanveettil
- Department of Neuroscience, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida, USA
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Zhuang XL, Shao Y, Chen CY, Zhou L, Yao YG, Cooper DN, Zhang GJ, Wang W, Wu DD. Divergent Evolutionary Rates of Primate Brain Regions as Revealed by Genomics and Transcriptomics. Genome Biol Evol 2024; 16:evae023. [PMID: 38314830 PMCID: PMC10881106 DOI: 10.1093/gbe/evae023] [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: 04/19/2023] [Revised: 01/05/2024] [Accepted: 01/30/2024] [Indexed: 02/07/2024] Open
Abstract
Although the primate brain contains numerous functionally distinct structures that have experienced diverse genetic changes during the course of evolution and development, these changes remain to be explored in detail. Here we utilize two classic metrics from evolutionary biology, the evolutionary rate index (ERI) and the transcriptome age index (TAI), to investigate the evolutionary alterations that have occurred in each area and developmental stage of the primate brain. We observed a higher evolutionary rate for those genes expressed in the non-cortical areas during primate evolution, particularly in human, with the highest rate of evolution being exhibited at brain developmental stages between late infancy and early childhood. Further, the transcriptome age of the non-cortical areas was lower than that of the cerebral cortex, with the youngest age apparent at brain developmental stages between late infancy and early childhood. Our exploration of the evolutionary patterns manifest in each brain area and developmental stage provides important reference points for further research into primate brain evolution.
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Affiliation(s)
- Xiao-Lin Zhuang
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
| | - Yong Shao
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
| | - Chun-Yan Chen
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710072, China
| | - Long Zhou
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310000, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou 310000, China
| | - Yong-Gang Yao
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Guo-Jie Zhang
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310000, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou 310000, China
| | - Wen Wang
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710072, China
| | - Dong-Dong Wu
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
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3
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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: 3] [Impact Index Per Article: 3.0] [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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4
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Ye Y, Yang K, Liu H, Yu Y, Song M, Huang D, Lei J, Zhang Y, Liu Z, Chu Q, Fan Y, Zhang S, Jing Y, Esteban CR, Wang S, Belmonte JCI, Qu J, Zhang W, Liu GH. SIRT2 counteracts primate cardiac aging via deacetylation of STAT3 that silences CDKN2B. NATURE AGING 2023; 3:1269-1287. [PMID: 37783815 DOI: 10.1038/s43587-023-00486-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 08/15/2023] [Indexed: 10/04/2023]
Abstract
Aging is a major risk factor contributing to pathophysiological changes in the heart, yet its intrinsic mechanisms have been largely unexplored in primates. In this study, we investigated the hypertrophic and senescence phenotypes in the hearts of aged cynomolgus monkeys as well as the transcriptomic and proteomic landscapes of young and aged primate hearts. SIRT2 was identified as a key protein decreased in aged monkey hearts, and engineered SIRT2 deficiency in human pluripotent stem cell-derived cardiomyocytes recapitulated key senescence features of primate heart aging. Further investigations revealed that loss of SIRT2 in human cardiomyocytes led to the hyperacetylation of STAT3, which transcriptionally activated CDKN2B and, in turn, triggered cardiomyocyte degeneration. Intra-myocardial injection of lentiviruses expressing SIRT2 ameliorated age-related cardiac dysfunction in mice. Taken together, our study provides valuable resources for decoding primate cardiac aging and identifies the SIRT2-STAT3-CDKN2B regulatory axis as a potential therapeutic target against human cardiac aging and aging-related cardiovascular diseases.
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Affiliation(s)
- Yanxia Ye
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Kuan Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China
| | - Haisong Liu
- School of Biomedical Sciences, Hunan University, Changsha, China
| | - Yang Yu
- Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology and Key Laboratory of Assisted Reproduction, Ministry of Education, Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
- Clinical Stem Cell Research Center, Peking University Third Hospital, Beijing, China
| | - Moshi Song
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Daoyuan Huang
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jinghui Lei
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yiyuan Zhang
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Zunpeng Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qun Chu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- The Fifth People's Hospital of Chongqing, Chongqing, China
| | - Yanling Fan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Sheng Zhang
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Brain-Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Yaobin Jing
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | | | - Si Wang
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China
- The Fifth People's Hospital of Chongqing, Chongqing, China
| | | | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Weiqi Zhang
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China.
| | - Guang-Hui Liu
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China.
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Chen X, Liu Y, Pu J, Gui S, Wang D, Zhong X, Tao W, Chen X, Chen W, Chen Y, Qiao R, Xie P. Multi-Omics Analysis Reveals Age-Related Microbial and Metabolite Alterations in Non-Human Primates. Microorganisms 2023; 11:2406. [PMID: 37894064 PMCID: PMC10609416 DOI: 10.3390/microorganisms11102406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/22/2023] [Accepted: 09/23/2023] [Indexed: 10/29/2023] Open
Abstract
Aging is a systemic physiological degenerative process, with alterations in gut microbiota and host metabolism. However, due to the interference of multiple confounding factors, aging-associated molecular characteristics have not been elucidated completely. Therefore, based on 16S ribosomal RNA (rRNA) gene sequencing and non-targeted metabolomic detection, our study systematically analyzed the composition and function of the gut microbiome, serum, and fecal metabolome of 36 male rhesus monkeys spanning from 3 to 26 years old, which completely covers juvenile, adult, and old stages. We observed significant correlations between 41 gut genera and age. Moreover, 86 fecal and 49 serum metabolites exhibited significant age-related correlations, primarily categorized into lipids and lipid-like molecules, organic oxygen compounds, organic acids and derivatives, and organoheterocyclic compounds. Further results suggested that aging is associated with significant downregulation of various amino acids constituting proteins, elevation of lipids, particularly saturated fatty acids, and steroids. Additionally, age-dependent changes were observed in multiple immune-regulatory molecules, antioxidant stress metabolites, and neurotransmitters. Notably, multiple age-dependent genera showed strong correlations in these changes. Together, our results provided new evidence for changing characteristics of gut microbes and host metabolism during aging. However, more research is needed in the future to verify our findings.
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Affiliation(s)
- Xiang Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yiyun Liu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Juncai Pu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Siwen Gui
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Dongfang Wang
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xiaogang Zhong
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Wei Tao
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xiaopeng Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Weiyi Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yue Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Renjie Qiao
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Peng Xie
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (X.C.)
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
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6
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Zhuang XL, Zhang JJ, Shao Y, Ye Y, Chen CY, Zhou L, Wang ZB, Luo X, Su B, Yao YG, Cooper DN, Hu BX, Wang L, Qi XG, Lin J, Zhang GJ, Wang W, Sheng N, Wu DD. Integrative Omics Reveals Rapidly Evolving Regulatory Sequences Driving Primate Brain Evolution. Mol Biol Evol 2023; 40:msad173. [PMID: 37494289 PMCID: PMC10404817 DOI: 10.1093/molbev/msad173] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/11/2023] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Although the continual expansion of the brain during primate evolution accounts for our enhanced cognitive capabilities, the drivers of brain evolution have scarcely been explored in these ancestral nodes. Here, we performed large-scale comparative genomic, transcriptomic, and epigenomic analyses to investigate the evolutionary alterations acquired by brain genes and provide comprehensive listings of innovatory genetic elements along the evolutionary path from ancestral primates to human. The regulatory sequences associated with brain-expressed genes experienced rapid change, particularly in the ancestor of the Simiiformes. Extensive comparisons of single-cell and bulk transcriptomic data between primate and nonprimate brains revealed that these regulatory sequences may drive the high expression of certain genes in primate brains. Employing in utero electroporation into mouse embryonic cortex, we show that the primate-specific brain-biased gene BMP7 was recruited, probably in the ancestor of the Simiiformes, to regulate neuronal proliferation in the primate ventricular zone. Our study provides a comprehensive listing of genes and regulatory changes along the brain evolution lineage of ancestral primates leading to human. These data should be invaluable for future functional studies that will deepen our understanding not only of the genetic basis of human brain evolution but also of inherited disease.
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Affiliation(s)
- Xiao-Lin Zhuang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Jin-Jin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yaxin Ye
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chun-Yan Chen
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an, Shaanxi, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Center of Evolutionary & Organismal Biology, and Women’s Hospital at Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - Zheng-bo Wang
- Yunnan Key Laboratory of Primate Biomedicine Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yong-Gang Yao
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, Yunnan, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, Wales, UK
| | - Ben-Xia Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Wang
- College of Life Sciences, Northwest University, Xi’an, Shaanxi, China
| | - Xiao-Guang Qi
- College of Life Sciences, Northwest University, Xi’an, Shaanxi, China
| | - Jiangwei Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Guo-Jie Zhang
- Center of Evolutionary & Organismal Biology, and Women’s Hospital at Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an, Shaanxi, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Nengyin Sheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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7
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Ho NJ, Chen X, Lei Y, Gu S. Decoding hereditary spastic paraplegia pathogenicity through transcriptomic profiling. Zool Res 2023; 44:650-662. [PMID: 37161652 PMCID: PMC10236304 DOI: 10.24272/j.issn.2095-8137.2022.281] [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: 12/30/2022] [Accepted: 05/10/2023] [Indexed: 05/11/2023] Open
Abstract
Hereditary spastic paraplegia (HSP) is a group of genetic motor neuron diseases resulting from length-dependent axonal degeneration of the corticospinal upper motor neurons. Due to the advancement of next-generation sequencing, more than 70 novel HSP disease-causing genes have been identified in the past decade. Despite this, our understanding of HSP physiopathology and the development of efficient management and treatment strategies remain poor. One major challenge in studying HSP pathogenicity is selective neuronal vulnerability, characterized by the manifestation of clinical symptoms that are restricted to specific neuronal populations, despite the presence of germline disease-causing variants in every cell of the patient. Furthermore, disease genes may exhibit ubiquitous expression patterns and involve a myriad of different pathways to cause motor neuron degeneration. In the current review, we explore the correlation between transcriptomic data and clinical manifestations, as well as the importance of interspecies models by comparing tissue-specific transcriptomic profiles of humans and mice, expression patterns of different genes in the brain during development, and single-cell transcriptomic data from related tissues. Furthermore, we discuss the potential of emerging single-cell RNA sequencing technologies to resolve unanswered questions related to HSP pathogenicity.
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Affiliation(s)
- Nicolas James Ho
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Xiao Chen
- Dr. Li Dak Sum-Yip Yio Chin Center for Stem Cells and Regenerative Medicine and Department of Orthopedic Surgery of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Tissue Engineering and Regenerative Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Zhejiang University-University of Edinburgh Institute & School of Basic Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Department of Sports Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- China Orthopedic Regenerative Medicine Group (CORMed), Hangzhou, Zhejiang, 310058 China
| | - Yong Lei
- School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong 518172, China
- The Chinese University of Hong Kong (Shenzhen), Shenzhen Futian Biomedical Innovation R&D Center, Shenzhen, Guangdong 518172, China. E-mail:
| | - Shen Gu
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Key Laboratory for Regenerative Medicine, Ministry of Education, School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Kunming Institute of Zoology Chinese Academy of Sciences, The Chinese University of Hong Kong Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Hong Kong SAR, China
- Hong Kong Branch of CAS Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong, Hong Kong SAR, China. E-mail:
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8
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Bo T, Li J, Hu G, Zhang G, Wang W, Lv Q, Zhao S, Ma J, Qin M, Yao X, Wang M, Wang GZ, Wang Z. Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys. Nat Commun 2023; 14:1499. [PMID: 36932104 PMCID: PMC10023667 DOI: 10.1038/s41467-023-37246-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] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 03/06/2023] [Indexed: 03/19/2023] Open
Abstract
Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.
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Affiliation(s)
- Tingting Bo
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, 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, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, 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, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Shaoling Zhao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Meng Qin
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xiaohui Yao
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao, Shandong, China
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, 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, China.
| | - Zheng Wang
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- School of Biomedical Engineering, Hainan University, Haikou, Hainan, China.
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9
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Current advances in primate genomics: novel approaches for understanding evolution and disease. Nat Rev Genet 2023; 24:314-331. [PMID: 36599936 DOI: 10.1038/s41576-022-00554-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/07/2022] [Indexed: 01/05/2023]
Abstract
Primate genomics holds the key to understanding fundamental aspects of human evolution and disease. However, genetic diversity and functional genomics data sets are currently available for only a few of the more than 500 extant primate species. Concerted efforts are under way to characterize primate genomes, genetic polymorphism and divergence, and functional landscapes across the primate phylogeny. The resulting data sets will enable the connection of genotypes to phenotypes and provide new insight into aspects of the genetics of primate traits, including human diseases. In this Review, we describe the existing genome assemblies as well as genetic variation and functional genomic data sets. We highlight some of the challenges with sample acquisition. Finally, we explore how technological advances in single-cell functional genomics and induced pluripotent stem cell-derived organoids will facilitate our understanding of the molecular foundations of primate biology.
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10
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Möller S, Saul N, Projahn E, Barrantes I, Gézsi A, Walter M, Antal P, Fuellen G. Gene co-expression analyses of health(span) across multiple species. NAR Genom Bioinform 2022; 4:lqac083. [PMID: 36458022 PMCID: PMC9706456 DOI: 10.1093/nargab/lqac083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 08/20/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022] Open
Abstract
Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-study of the resulting modules related to health(span), yielding a small set of literature backed health(span) candidate genes. For each experiment, WGCNA (weighted gene correlation network analysis) was used to infer modules of genes which correlate in their expression with a 'health phenotype score' and to determine the most-connected (hub) genes (and their interactions) for each such module. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler found an association with actin filament-based movement and associated organelles, as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).
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Affiliation(s)
- Steffen Möller
- To whom correspondence should be addressed. Tel: +49 381 494 7361; Fax: +49 381 494 7203;
| | - Nadine Saul
- Humboldt-University of Berlin, Institute of Biology, Berlin, Germany
| | - Elias Projahn
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
| | - Israel Barrantes
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
| | - András Gézsi
- Budapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary
| | - Michael Walter
- Rostock University Medical Center, Institute for Clinical Chemistry and Laboratory Medicine, Rostock, Germany
| | - Péter Antal
- Budapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary
| | - Georg Fuellen
- Rostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany
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11
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Xu J, Lan Y, Wang X, Shang K, Liu X, Wang J, Li J, Yue B, Shao M, Fan Z. Multi-omics analysis reveals the host-microbe interactions in aged rhesus macaques. Front Microbiol 2022; 13:993879. [PMID: 36238598 PMCID: PMC9551614 DOI: 10.3389/fmicb.2022.993879] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Aging is a complex multifactorial process that greatly affects animal health. Multi-omics analysis is widely applied in evolutionary biology and biomedical research. However, whether multi-omics can provide sufficient information to reveal comprehensive changes in aged non-human primates remains unclear. Here, we explored changes in host-microbe interactions with aging in Chinese rhesus macaques (Macaca mulatta lasiota, CRs) using multi-omics analysis. Results showed marked changes in the oral and gut microbiomes between young and aged CRs, including significantly reduced probiotic abundance and increased pathogenic bacterial abundance in aged CRs. Notably, the abundance of Lactobacillus, which can metabolize tryptophan to produce aryl hydrocarbon receptor (AhR) ligands, was decreased in aged CRs. Consistently, metabolomics detected a decrease in the plasma levels of AhR ligands. In addition, free fatty acid, acyl carnitine, heparin, 2-(4-hydroxyphenyl) propionic acid, and docosahexaenoic acid ethyl ester levels were increased in aged CRs, which may contribute to abnormal fatty acid metabolism and cardiovascular disease. Transcriptome analysis identified changes in the expression of genes associated with tryptophan metabolism and inflammation. In conclusion, many potential links among different omics were found, suggesting that aged CRs face multiple metabolic problems, immunological disorders, and oral and gut diseases. We determined that tryptophan metabolism is critical for the physiological health of aged CRs. Our findings demonstrate the value of multi-omics analyses in revealing host-microbe interactions in non-human primates and suggest that similar approaches could be applied in evolutionary and ecological research of other species.
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Affiliation(s)
- Jue Xu
- West China School of Public Health and West China Fourth Hospital, Chengdu, Sichuan, China
| | - Yue Lan
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
| | - Xinqi Wang
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
| | - Ke Shang
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
| | - Xu Liu
- Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu, China
| | - Jiao Wang
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
| | - Jing Li
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
| | - Bisong Yue
- Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu, China
| | - Meiying Shao
- West China School of Public Health and West China Fourth Hospital, Chengdu, Sichuan, China
| | - Zhenxin Fan
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, China
- Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu, China
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12
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Ruano CSM, Apicella C, Jacques S, Gascoin G, Gaspar C, Miralles F, Méhats C, Vaiman D. Alternative splicing in normal and pathological human placentas is correlated to genetic variants. Hum Genet 2021; 140:827-848. [PMID: 33433680 PMCID: PMC8052246 DOI: 10.1007/s00439-020-02248-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/14/2020] [Indexed: 12/11/2022]
Abstract
Two major obstetric diseases, preeclampsia (PE), a pregnancy-induced endothelial dysfunction leading to hypertension and proteinuria, and intra-uterine growth-restriction (IUGR), a failure of the fetus to acquire its normal growth, are generally triggered by placental dysfunction. Many studies have evaluated gene expression deregulations in these diseases, but none has tackled systematically the role of alternative splicing. In the present study, we show that alternative splicing is an essential feature of placental diseases, affecting 1060 and 1409 genes in PE vs controls and IUGR vs controls, respectively, many of those involved in placental function. While in IUGR placentas, alternative splicing affects genes specifically related to pregnancy, in preeclamptic placentas, it impacts a mix of genes related to pregnancy and brain diseases. Also, alternative splicing variations can be detected at the individual level as sharp splicing differences between different placentas. We correlate these variations with genetic variants to define splicing Quantitative Trait Loci (sQTL) in the subset of the 48 genes the most strongly alternatively spliced in placental diseases. We show that alternative splicing is at least partly piloted by genetic variants located either in cis (52 QTL identified) or in trans (52 QTL identified). In particular, we found four chromosomal regions that impact the splicing of genes in the placenta. The present work provides a new vision of placental gene expression regulation that warrants further studies.
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Affiliation(s)
- Camino S M Ruano
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France
| | - Clara Apicella
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France
| | - Sébastien Jacques
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France
| | - Géraldine Gascoin
- Unité Mixte de Recherche MITOVASC, Équipe Mitolab, CNRS 6015, INSERM U1083, Université d'Angers, Angers, France
- Réanimation et Médecine Néonatales, Centre Hospitalier Universitaire, Angers, France
| | - Cassandra Gaspar
- Sorbonne Université, Inserm, UMS Production et Analyse des Données en Sciences de la vie et en Santé, PASS, Plateforme Post-génomique de la Pitié-Salpêtrière, P3S, 75013, Paris, France
| | - Francisco Miralles
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France
| | - Céline Méhats
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France
| | - Daniel Vaiman
- Université de Paris, Institut Cochin, Inserm U1016, CNRS, 24 rue du Faubourg St Jacques, 75014, Paris, France.
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13
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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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14
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Feng L, Han CX, Cao SY, Zhang HM, Wu GY. Deficits in motor and cognitive functions in an adult mouse model of hypoxia-ischemia induced stroke. Sci Rep 2020; 10:20646. [PMID: 33244072 PMCID: PMC7692481 DOI: 10.1038/s41598-020-77678-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 11/13/2020] [Indexed: 11/25/2022] Open
Abstract
Ischemic strokes cause devastating brain damage and functional deficits with few treatments available. Previous studies have shown that the ischemia-hypoxia rapidly induces clinically similar thrombosis and neuronal loss, but any resulting behavioral changes are largely unknown. The goal of this study was to evaluate motor and cognitive deficits in adult HI mice. Following a previously established procedure, HI mouse models were induced by first ligating the right common carotid artery and followed by hypoxia. Histological data showed significant long-term neuronal losses and reactive glial cells in the ipsilateral striatum and hippocampus of the HI mice. Whereas the open field test and the rotarod test could not reliably distinguish between the sham and HI mice, in the tapered beam and wire-hanging tests, the HI mice showed short-term and long-term deficits, as evidenced by the increased number of foot faults and decreased hanging time respectively. In cognitive tests, the HI mice swam longer distances and needed more time to find the platform in the Morris water maze test and showed shorter freezing time in fear contextual tests after fear training. In conclusion, this study demonstrates that adult HI mice have motor and cognitive deficits and could be useful models for preclinical stroke research.
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Affiliation(s)
- Li Feng
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China.
| | - Chun-Xia Han
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China
| | - Shu-Yu Cao
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - He-Ming Zhang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China.
| | - Gang-Yi Wu
- School of Life Sciences, South China Normal University, Guangzhou, 510631, China
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15
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Chiou KL, Montague MJ, Goldman EA, Watowich MM, Sams SN, Song J, Horvath JE, Sterner KN, Ruiz-Lambides AV, Martínez MI, Higham JP, Brent LJN, Platt ML, Snyder-Mackler N. Rhesus macaques as a tractable physiological model of human ageing. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190612. [PMID: 32951555 DOI: 10.1098/rstb.2019.0612] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Research in the basic biology of ageing is increasingly identifying mechanisms and modifiers of ageing in short-lived organisms such as worms and mice. The ultimate goal of such work is to improve human health, particularly in the growing segment of the population surviving into old age. Thus far, few interventions have robustly transcended species boundaries in the laboratory, suggesting that changes in approach are needed to avoid costly failures in translational human research. In this review, we discuss both well-established and alternative model organisms for ageing research and outline how research in nonhuman primates is sorely needed, first, to translate findings from short-lived organisms to humans, and second, to understand key aspects of ageing that are unique to primate biology. We focus on rhesus macaques as a particularly promising model organism for ageing research owing to their social and physiological similarity to humans as well as the existence of key resources that have been developed for this species. As a case study, we compare gene regulatory signatures of ageing in the peripheral immune system between humans and rhesus macaques from a free-ranging study population in Cayo Santiago. We show that both mRNA expression and DNA methylation signatures of immune ageing are broadly shared between macaques and humans, indicating strong conservation of the trajectory of ageing in the immune system. We conclude with a review of key issues in the biology of ageing for which macaques and other nonhuman primates may uniquely contribute valuable insights, including the effects of social gradients on health and ageing. We anticipate that continuing research in rhesus macaques and other nonhuman primates will play a critical role in conjunction with the model organism and human biodemographic research in ultimately improving translational outcomes and extending health and longevity in our ageing population. This article is part of the theme issue 'Evolution of the primate ageing process'.
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Affiliation(s)
- Kenneth L Chiou
- Department of Psychology, University of Washington, Seattle, WA 98195, USA.,Department of Pathology, Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA 98195, USA.,Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA
| | - Michael J Montague
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | - Marina M Watowich
- Department of Biology, University of Washington, Seattle, WA 98195, USA
| | - Sierra N Sams
- Department of Psychology, University of Washington, Seattle, WA 98195, USA
| | - Jeff Song
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA
| | - Julie E Horvath
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA.,Research and Collections Section, North Carolina Museum of Natural Sciences, Raleigh, NC 27601, USA.,Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA.,Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Kirstin N Sterner
- Department of Anthropology, University of Oregon, Eugene, OR 97403, USA
| | - Angelina V Ruiz-Lambides
- Caribbean Primate Research Center, Unit of Comparative Medicine, University of Puerto Rico, San Juan, PR 00936, USA
| | - Melween I Martínez
- Caribbean Primate Research Center, Unit of Comparative Medicine, University of Puerto Rico, San Juan, PR 00936, USA
| | - James P Higham
- Department of Anthropology, New York University, New York, NY 10003, USA.,New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter EX4 4QG, UK
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Marketing, Wharton School of Business, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Noah Snyder-Mackler
- Department of Psychology, University of Washington, Seattle, WA 98195, USA.,Department of Pathology, Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA 98195, USA.,Department of Biology, University of Washington, Seattle, WA 98195, USA.,Center for Studies in Demography and Ecology, University of Washington, Seattle, WA 98195, USA.,Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA.,School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
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Li ML, Tang H, Shao Y, Wang MS, Xu HB, Wang S, Irwin DM, Adeola AC, Zeng T, Chen L, Li Y, Wu DD. Evolution and transition of expression trajectory during human brain development. BMC Evol Biol 2020; 20:72. [PMID: 32576137 PMCID: PMC7310562 DOI: 10.1186/s12862-020-01633-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 05/26/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND The remarkable abilities of the human brain are distinctive features that set us apart from other animals. However, our understanding of how the brain has changed in the human lineage remains incomplete, but is essential for understanding cognition, behavior, and brain disorders in humans. Here, we compared the expression trajectory in brain development between humans and rhesus macaques (Macaca mulatta) to explore their divergent transcriptome profiles. RESULTS Results showed that brain development could be divided into two stages, with a demarcation date in a range between 25 and 26 postconception weeks (PCW) for humans and 17-23PCWfor rhesus macaques, rather than birth time that have been widely used as a uniform demarcation time of neurodevelopment across species. Dynamic network biomarker (DNB) analysis revealed that the two demarcation dates were transition phases during brain development, after which the brain transcriptome profiles underwent critical transitions characterized by highly fluctuating DNB molecules. We also found that changes between early and later brain developmental stages (as defined by the demarcation points) were substantially greater in the human brain than in the macaque brain. To explore the molecular mechanism underlying prolonged timing during early human brain development, we carried out expression heterochrony tests. Results demonstrated that compared to macaques, more heterochronic genes exhibited neoteny during early human brain development, consistent with the delayed demarcation time in the human lineage, and proving that neoteny in human brain development could be traced to the prenatal period. We further constructed transcriptional networks to explore the profile of early human brain development and identified the hub gene RBFOX1 as playing an important role in regulating early brain development. We also found RBFOX1 evolved rapidly in its non-coding regions, indicating that this gene played an important role in human brain evolution. Our findings provide evidence that RBFOX1 is a likely key hub gene in early human brain development and evolution. CONCLUSIONS By comparing gene expression profiles between humans and macaques, we found divergent expression trajectories between the two species, which deepens our understanding of the evolution of the human brain.
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Affiliation(s)
- Ming-Li Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Hui Tang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Hai-Bo Xu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - David M Irwin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
- Banting and Best Diabetes Centre, University of Toronto, Toronto, Ontario, M5G 2C4, Canada
| | - Adeniyi C Adeola
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Tao Zeng
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Luonan Chen
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, 310024, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
| | - Yan Li
- State Key Laboratory for Conservation and Utilization of Bio-Resource, Yunnan University, Kunming, 650091, Yunnan, China.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
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17
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Branching out: what omics can tell us about primate evolution. Curr Opin Genet Dev 2020; 62:65-71. [DOI: 10.1016/j.gde.2020.06.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 06/02/2020] [Accepted: 06/04/2020] [Indexed: 12/25/2022]
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Author Correction: 547 transcriptomes from 44 brain areas reveal features of the aging brain in non-human primates. Genome Biol 2020; 21:46. [PMID: 32093779 PMCID: PMC7038610 DOI: 10.1186/s13059-020-01962-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Following publication of the original paper [1], the authors reported an error in the affiliation of Xin-Tian Hu, who is also affiliated with "Kunming Primate Research Center, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China".
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Li ML, Wu SH, Zhang JJ, Tian HY, Shao Y, Wang ZB, Irwin DM, Li JL, Hu XT, Wu DD. 547 transcriptomes from 44 brain areas reveal features of the aging brain in non-human primates. Genome Biol 2019; 20:258. [PMID: 31779658 PMCID: PMC6883628 DOI: 10.1186/s13059-019-1866-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 10/26/2019] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Brain aging is a complex process that depends on the precise regulation of multiple brain regions; however, the underlying molecular mechanisms behind this process remain to be clarified in non-human primates. RESULTS Here, we explore non-human primate brain aging using 547 transcriptomes originating from 44 brain areas in rhesus macaques (Macaca mulatta). We show that expression connectivity between pairs of cerebral cortex areas as well as expression symmetry between the left and right hemispheres both decrease after aging. Although the aging mechanisms across different brain areas are largely convergent, changes in gene expression and alternative splicing vary at diverse genes, reinforcing the complex multifactorial basis of aging. Through gene co-expression network analysis, we identify nine modules that exhibit gain of connectivity in the aged brain and uncovered a hub gene, PGLS, underlying brain aging. We further confirm the functional significance of PGLS in mice at the gene transcription, molecular, and behavioral levels. CONCLUSIONS Taken together, our study provides comprehensive transcriptomes on multiple brain regions in non-human primates and provides novel insights into the molecular mechanism of healthy brain aging.
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Affiliation(s)
- Ming-Li Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Shi-Hao Wu
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Jin-Jin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Hang-Yu Tian
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Zheng-Bo Wang
- Yunnan Key Laboratory of Primate Biomedicine Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China
| | - David M Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Jia-Li Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Xin-Tian Hu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
- National Research Facility for Phenotypic and Genetic Analysis of Model Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
- National Research Facility for Phenotypic and Genetic Analysis of Model Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
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