1
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Zhou B, Hu P, Liu G, Chang Z, Dong Z, Li Z, Yin Y, Tian Z, Han G, Wang W, Li X. Evolutionary patterns and functional effects of 3D chromatin structures in butterflies with extensive genome rearrangements. Nat Commun 2024; 15:6303. [PMID: 39060230 PMCID: PMC11282110 DOI: 10.1038/s41467-024-50529-0] [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: 11/28/2023] [Accepted: 07/11/2024] [Indexed: 07/28/2024] Open
Abstract
Chromosome rearrangements may distort 3D chromatin architectures and thus change gene regulation, yet how 3D chromatin structures evolve in insects is largely unknown. Here, we obtain chromosome-level genomes for four butterfly species, Graphium cloanthus, Graphium sarpedon, Graphium eurypylus with 2n = 30, 40, and 60, respectively, and Papilio bianor with 2n = 60. Together with large-scale Hi-C data, we find that inter-chromosome rearrangements very rarely disrupted the pre-existing 3D chromatin structure of ancestral chromosomes. However, some intra-chromosome rearrangements changed 3D chromatin structures compared to the ancestral configuration. We find that new TADs and subTADs have emerged across the rearrangement sites where their adjacent compartments exhibit uniform types. Two intra-chromosome rearrangements altered Rel and lft regulation, potentially contributing to wing patterning differentiation and host plant choice. Notably, butterflies exhibited chromatin loops between Hox gene cluster ANT-C and BX-C, unlike Drosophila. Our CRISPR-Cas9 experiments in butterflies confirm that knocking out the CTCF binding site of the loops in BX-C affected the phenotypes regulated by Antp in ANT-C, resulting in legless larva. Our results reveal evolutionary patterns of insect 3D chromatin structures and provide evidence that 3D chromatin structure changes can play important roles in the evolution of traits.
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Affiliation(s)
- Botong Zhou
- School of Ecology and Environment, New Cornerstone Science Laboratory, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Ping Hu
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China
| | - Guichun Liu
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China
| | - Zhou Chang
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China
| | - Zhiwei Dong
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China
| | - Zihe Li
- School of Ecology and Environment, New Cornerstone Science Laboratory, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Yuan Yin
- NHC Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, China
| | - Zunzhe Tian
- School of Ecology and Environment, New Cornerstone Science Laboratory, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Ge Han
- School of Ecology and Environment, New Cornerstone Science Laboratory, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Wen Wang
- School of Ecology and Environment, New Cornerstone Science Laboratory, Northwestern Polytechnical University, Xi'an, 710072, China.
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Xueyan Li
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Kunming, 650223, China.
- Yunnan Key Laboratory of Biodiversity Information, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
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2
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Vietri Rudan M, Sipilä KH, Philippeos C, Ganier C, Bhosale PG, Negri VA, Watt FM. Neutral evolution of snoRNA Host Gene long non-coding RNA affects cell fate control. EMBO J 2024:10.1038/s44318-024-00172-8. [PMID: 39054371 DOI: 10.1038/s44318-024-00172-8] [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: 02/23/2024] [Revised: 06/15/2024] [Accepted: 07/01/2024] [Indexed: 07/27/2024] Open
Abstract
A fundamental challenge in molecular biology is to understand how evolving genomes can acquire new functions. Actively transcribed, non-coding parts of the genome provide a potential platform for the development of new functional sequences, but their biological and evolutionary roles remain largely unexplored. Here, we show that a set of neutrally evolving long non-coding RNAs (lncRNAs) whose introns encode small nucleolar RNAs (snoRNA Host Genes, SNHGs) are highly expressed in skin and dysregulated in inflammatory conditions. Using SNHG7 and human epidermal keratinocytes as a model, we describe a mechanism by which these lncRNAs can increase self-renewal and inhibit differentiation. The activity of SNHG7 lncRNA has been recently acquired in the primate lineage and depends on a short sequence required for microRNA binding. Taken together, our results highlight the importance of understanding the role of fast-evolving transcripts in normal and diseased epithelia, and show how poorly conserved, actively transcribed non-coding sequences can participate in the evolution of genomic functionality.
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Affiliation(s)
- Matteo Vietri Rudan
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Kalle H Sipilä
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Christina Philippeos
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Clarisse Ganier
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Priyanka G Bhosale
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Victor A Negri
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK
| | - Fiona M Watt
- Centre for Gene Therapy and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London, SE1 9RT, UK.
- Directors' Unit, EMBL, Meyerhofstr. 1, 69117, Heidelberg, Germany.
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3
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Dong J, Zhu XN, Zeng PM, Cao DD, Yang Y, Hu J, Luo ZG. A hominoid-specific signaling axis regulating the tempo of synaptic maturation. Cell Rep 2024; 43:114548. [PMID: 39052482 DOI: 10.1016/j.celrep.2024.114548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/15/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
Human cortical neurons (hCNs) exhibit high dendritic complexity and synaptic density, and the maturation process is greatly protracted. However, the molecular mechanism governing these specific features remains unclear. Here, we report that the hominoid-specific gene TBC1D3 promotes dendritic arborization and protracts the pace of synaptogenesis. Ablation of TBC1D3 in induced hCNs causes reduction of dendritic growth and precocious synaptic maturation. Forced expression of TBC1D3 in the mouse cortex protracts synaptic maturation while increasing dendritic growth. Mechanistically, TBC1D3 functions via interaction with MICAL1, a monooxygenase that mediates oxidation of actin filament. At the early stage of differentiation, the TBC1D3/MICAL1 interaction in the cytosol promotes dendritic growth via F-actin oxidation and enhanced actin dynamics. At late stages, TBC1D3 escorts MICAL1 into the nucleus and downregulates the expression of genes related with synaptic maturation through interaction with the chromatin remodeling factor ATRX. Thus, this study delineates the molecular mechanisms underlying human neuron development.
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Affiliation(s)
- Jian Dong
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Xiao-Na Zhu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Peng-Ming Zeng
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Dong-Dong Cao
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yang Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Ji Hu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Zhen-Ge Luo
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China.
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4
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Sun D, Zhu Y, Peng W, Zheng S, Weng J, Dong S, Li J, Chen Q, Ge C, Liao L, Dong Y, Liu Y, Meng W, Jiang Y. SETDB1 regulates short interspersed nuclear elements and chromatin loop organization in mouse neural precursor cells. Genome Biol 2024; 25:175. [PMID: 38961490 PMCID: PMC11221086 DOI: 10.1186/s13059-024-03327-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/28/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND Transposable elements play a critical role in maintaining genome architecture during neurodevelopment. Short Interspersed Nuclear Elements (SINEs), a major subtype of transposable elements, are known to harbor binding sites for the CCCTC-binding factor (CTCF) and pivotal in orchestrating chromatin organization. However, the regulatory mechanisms controlling the activity of SINEs in the developing brain remains elusive. RESULTS In our study, we conduct a comprehensive genome-wide epigenetic analysis in mouse neural precursor cells using ATAC-seq, ChIP-seq, whole genome bisulfite sequencing, in situ Hi-C, and RNA-seq. Our findings reveal that the SET domain bifurcated histone lysine methyltransferase 1 (SETDB1)-mediated H3K9me3, in conjunction with DNA methylation, restricts chromatin accessibility on a selective subset of SINEs in neural precursor cells. Mechanistically, loss of Setdb1 increases CTCF access to these SINE elements and contributes to chromatin loop reorganization. Moreover, de novo loop formation contributes to differential gene expression, including the dysregulation of genes enriched in mitotic pathways. This leads to the disruptions of cell proliferation in the embryonic brain after genetic ablation of Setdb1 both in vitro and in vivo. CONCLUSIONS In summary, our study sheds light on the epigenetic regulation of SINEs in mouse neural precursor cells, suggesting their role in maintaining chromatin organization and cell proliferation during neurodevelopment.
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Affiliation(s)
- Daijing Sun
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Yueyan Zhu
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Wenzhu Peng
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Shenghui Zheng
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Jie Weng
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Shulong Dong
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China
| | - Jiaqi Li
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Qi Chen
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Chuanhui Ge
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Liyong Liao
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Yuhao Dong
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Yun Liu
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China
| | - Weida Meng
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China
| | - Yan Jiang
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China.
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5
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Nehme R, Pietiläinen O, Barrett LE. Genomic, molecular, and cellular divergence of the human brain. Trends Neurosci 2024; 47:491-505. [PMID: 38897852 DOI: 10.1016/j.tins.2024.05.009] [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: 02/29/2024] [Revised: 04/29/2024] [Accepted: 05/21/2024] [Indexed: 06/21/2024]
Abstract
While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.
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Affiliation(s)
- Ralda Nehme
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Olli Pietiläinen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Lindy E Barrett
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
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6
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Kaplan SJ, Wong W, Yan J, Pulecio J, Cho HS, Li Q, Zhao J, Leslie-Iyer J, Kazakov J, Murphy D, Luo R, Dey KK, Apostolou E, Leslie CS, Huangfu D. CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.591412. [PMID: 38746154 PMCID: PMC11092487 DOI: 10.1101/2024.04.26.591412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, since coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.
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7
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Palmisano I, Liu T, Gao W, Zhou L, Merkenschlager M, Müller F, Chadwick J, Rivolta RT, Kong G, King JWD, Al-jibury E, Yan Y, Carlino A, Collison B, De Vitis E, Gongala S, De Virgiliis F, Wang Z, Di Giovanni S. Three-dimensional chromatin mapping of sensory neurons reveals that cohesin-dependent genomic domains are required for axonal regeneration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.09.597974. [PMID: 38895406 PMCID: PMC11185766 DOI: 10.1101/2024.06.09.597974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The in vivo three-dimensional genomic architecture of adult mature neurons at homeostasis and after medically relevant perturbations such as axonal injury remains elusive. Here we address this knowledge gap by mapping the three-dimensional chromatin architecture and gene expression programme at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C and RNA-seq. We find that cohesin is required for the full induction of the regenerative transcriptional program, by organising 3D genomic domains required for the activation of regenerative genes. Importantly, loss of cohesin results in disruption of chromatin architecture at regenerative genes and severely impaired nerve regeneration. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent chromatin interactions in neuronal regeneration.
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Affiliation(s)
- Ilaria Palmisano
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Tong Liu
- Department of Computer Science, University of Miami, 330M Ungar Building, 1365 Memorial Drive, Coral Gables, FL 33124-4245 Miami, FL, USA
| | - Wei Gao
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Luming Zhou
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | | | - Franziska Müller
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Jessica Chadwick
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Rebecca Toscano Rivolta
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Guiping Kong
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - James WD King
- MRC LMS, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Ediem Al-jibury
- MRC LMS, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Yuyang Yan
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Alessandro Carlino
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Bryce Collison
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Eleonora De Vitis
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Sree Gongala
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Francesco De Virgiliis
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Zheng Wang
- Department of Computer Science, University of Miami, 330M Ungar Building, 1365 Memorial Drive, Coral Gables, FL 33124-4245 Miami, FL, USA
| | - Simone Di Giovanni
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
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8
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Long Y, Wendel JF, Zhang X, Wang M. Evolutionary insights into the organization of chromatin structure and landscape of transcriptional regulation in plants. TRENDS IN PLANT SCIENCE 2024; 29:638-649. [PMID: 38061928 DOI: 10.1016/j.tplants.2023.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/06/2023] [Accepted: 11/09/2023] [Indexed: 06/09/2024]
Abstract
Development of complex traits necessitates the functioning and coordination of intricate regulatory networks involving multiple genes. Understanding 3D chromatin structure can facilitate insight into the regulation of gene expression by regulatory elements. This potential, of visualizing the role of chromatin organization in the evolution and function of regulatory elements, remains largely unexplored. Here, we describe new perspectives that arise from the dual considerations of sequence variation of regulatory elements and chromatin structure, with a special focus on whole-genome doubling or polyploidy. We underscore the significance of hierarchical chromatin organization in gene regulation during evolution. In addition, we describe strategies for exploring chromatin organization in future investigations of regulatory evolution in plants, enabling insights into the evolutionary influence of regulatory elements on gene expression and, hence, phenotypes.
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Affiliation(s)
- Yuexuan Long
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Jonathan F Wendel
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
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9
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Yu H, Li Y, Han W, Bao L, Liu F, Ma Y, Pu Z, Zeng Q, Zhang L, Bao Z, Wang S. Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach. Nat Protoc 2024; 19:1623-1678. [PMID: 38514839 DOI: 10.1038/s41596-024-00966-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 12/20/2023] [Indexed: 03/23/2024]
Abstract
The forthcoming massive genome data generated by the Earth BioGenome Project will open up a new era of comparative genomics, for which genome synteny analysis provides an important framework. Profiling genome synteny represents an essential step in elucidating genome architecture, regulatory blocks/elements and their evolutionary history. Here we describe PanSyn, ( https://github.com/yhw320/PanSyn ), the most comprehensive and up-to-date genome synteny pipeline, providing step-by-step instructions and application examples to demonstrate its usage. PanSyn inherits both basic and advanced functions from existing popular tools, offering a user-friendly, highly customized approach for genome macrosynteny analysis and integrated pan-evolutionary and regulatory analysis of genome architecture, which are not yet available in public synteny software or tools. The advantages of PanSyn include: (i) advanced microsynteny analysis by functional profiling of microsynteny genes and associated regulatory elements; (ii) comprehensive macrosynteny analysis, including the inference of karyotype evolution from ancestors to extant species; and (iii) functional integration of microsynteny and macrosynteny for pan-evolutionary profiling of genome architecture and regulatory blocks, as well as integration with external functional genomics datasets from three- or four-dimensional genome and ENCODE projects. PanSyn requires basic knowledge of the Linux environment and Perl programming language and the ability to access a computer cluster, especially for large-scale genomic comparisons. Our protocol can be easily implemented by a competent graduate student or postdoc and takes several days to weeks to execute for dozens to hundreds of genomes. PanSyn provides yet the most comprehensive and powerful tool for integrated evolutionary and functional genomics.
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Affiliation(s)
- Hongwei Yu
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Yuli Li
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China.
- Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao, China.
| | - Wentao Han
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Lisui Bao
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao, China
| | - Fuyun Liu
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Yuanting Ma
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Zhongqi Pu
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Qifan Zeng
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Lingling Zhang
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao, China
| | - Zhenmin Bao
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China
- Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China
- Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya, China
- Laboratory for Marine Fisheries and Aquaculture, Laoshan Laboratory, Qingdao, China
| | - Shi Wang
- Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China.
- Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao, China.
- Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China.
- Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya, China.
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10
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Hong Y, Bie L, Zhang T, Yan X, Jin G, Chen Z, Wang Y, Li X, Pei G, Zhang Y, Hong Y, Gong L, Li P, Xie W, Zhu Y, Shen X, Liu N. SAFB restricts contact domain boundaries associated with L1 chimeric transcription. Mol Cell 2024; 84:1637-1650.e10. [PMID: 38604171 DOI: 10.1016/j.molcel.2024.03.021] [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: 10/31/2023] [Revised: 02/05/2024] [Accepted: 03/19/2024] [Indexed: 04/13/2024]
Abstract
Long interspersed element-1 (LINE-1 or L1) comprises 17% of the human genome, continuously generates genetic variations, and causes disease in certain cases. However, the regulation and function of L1 remain poorly understood. Here, we uncover that L1 can enrich RNA polymerase IIs (RNA Pol IIs), express L1 chimeric transcripts, and create contact domain boundaries in human cells. This impact of L1 is restricted by a nuclear matrix protein scaffold attachment factor B (SAFB) that recognizes transcriptionally active L1s by binding L1 transcripts to inhibit RNA Pol II enrichment. Acute inhibition of RNA Pol II transcription abolishes the domain boundaries associated with L1 chimeric transcripts, indicating a transcription-dependent mechanism. Deleting L1 impairs domain boundary formation, and L1 insertions during evolution have introduced species-specific domain boundaries. Our data show that L1 can create RNA Pol II-enriched regions that alter genome organization and that SAFB regulates L1 and RNA Pol II activity to preserve gene regulation.
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Affiliation(s)
- Yaqiang Hong
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Luyao Bie
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Tao Zhang
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xiaohan Yan
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Guangpu Jin
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Zhuo Chen
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yang Wang
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xiufeng Li
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Gaofeng Pei
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yongyan Zhang
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yantao Hong
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Liang Gong
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou 311121, China
| | - Pilong Li
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Wei Xie
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yanfen Zhu
- International Institutes of Medicine, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu 322000, China
| | - Xiaohua Shen
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Nian Liu
- Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China.
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11
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Ding W, Li X, Zhang J, Ji M, Zhang M, Zhong X, Cao Y, Liu X, Li C, Xiao C, Wang J, Li T, Yu Q, Mo F, Zhang B, Qi J, Yang JC, Qi J, Tian L, Xu X, Peng Q, Zhou WZ, Liu Z, Fu A, Zhang X, Zhang JJ, Sun Y, Hu B, An NA, Zhang L, Li CY. Adaptive functions of structural variants in human brain development. SCIENCE ADVANCES 2024; 10:eadl4600. [PMID: 38579006 DOI: 10.1126/sciadv.adl4600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/01/2024] [Indexed: 04/07/2024]
Abstract
Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.
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Affiliation(s)
- Wanqiu Ding
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xiangshang Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jie Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mingjun Ji
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mengling Zhang
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Xiaoming Zhong
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Center of Excellence for Leukemia Studies, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119S Fourth Ring Rd W, Fengtai District, Beijing, China
| | - Xiaoge Liu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Chunqiong Li
- Chinese Institute for Brain Research, Beijing, China
| | - Chunfu Xiao
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jiaxin Wang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Ting Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qing Yu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Fan Mo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Boya Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jianhuan Qi
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jie-Chun Yang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Juntian Qi
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Lu Tian
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xinwei Xu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qi Peng
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Wei-Zhen Zhou
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhijin Liu
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Aisi Fu
- Wuhan Dgensee Clinical Laboratory, Wuhan, China
| | - Xiuqin Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jian-Jun Zhang
- Shanxi Key Laboratory of Chinese Medicine Encephalopathy, National International Joint Research Center for Molecular Chinese Medicine, Shanxi University of Chinese Medicine, Jinzhong, China
| | - Yujie Sun
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Baoyang Hu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Ni A An
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing, China
| | - Chuan-Yun Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
- Southwest United Graduate School, Kunming 650092, China
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12
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Fleck K, Luria V, Garag N, Karger A, Hunter T, Marten D, Phu W, Nam KM, Sestan N, O’Donnell-Luria AH, Erceg J. Functional associations of evolutionarily recent human genes exhibit sensitivity to the 3D genome landscape and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.17.585403. [PMID: 38559085 PMCID: PMC10980080 DOI: 10.1101/2024.03.17.585403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genome organization is intricately tied to regulating genes and associated cell fate decisions. In this study, we examine the positioning and functional significance of human genes, grouped by their evolutionary age, within the 3D organization of the genome. We reveal that genes of different evolutionary origin have distinct positioning relationships with both domains and loop anchors, and remarkably consistent relationships with boundaries across cell types. While the functional associations of each group of genes are primarily cell type-specific, such associations of conserved genes maintain greater stability across 3D genomic features and disease than recently evolved genes. Furthermore, the expression of these genes across various tissues follows an evolutionary progression, such that RNA levels increase from young genes to ancient genes. Thus, the distinct relationships of gene evolutionary age, function, and positioning within 3D genomic features contribute to tissue-specific gene regulation in development and disease.
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Affiliation(s)
- Katherine Fleck
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
| | - Nitanta Garag
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA 02115
| | - Trevor Hunter
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
| | - Daniel Marten
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
| | - William Phu
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
| | - Kee-Myoung Nam
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06510
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510
| | - Anne H. O’Donnell-Luria
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115
| | - Jelena Erceg
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030
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13
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Xu L, Yuan Z, Zhou J, Zhao Y, Liu W, Lu S, He Z, Qiang B, Shu P, Chen Y, Peng X. Temporal transcriptomic dynamics in developing macaque neocortex. eLife 2024; 12:RP90325. [PMID: 38415809 PMCID: PMC10911584 DOI: 10.7554/elife.90325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024] Open
Abstract
Despite intense research on mice, the transcriptional regulation of neocortical neurogenesis remains limited in humans and non-human primates. Cortical development in rhesus macaque is known to recapitulate multiple facets of cortical development in humans, including the complex composition of neural stem cells and the thicker supragranular layer. To characterize temporal shifts in transcriptomic programming responsible for differentiation from stem cells to neurons, we sampled parietal lobes of rhesus macaque at E40, E50, E70, E80, and E90, spanning the full period of prenatal neurogenesis. Single-cell RNA sequencing produced a transcriptomic atlas of developing parietal lobe in rhesus macaque neocortex. Identification of distinct cell types and neural stem cells emerging in different developmental stages revealed a terminally bifurcating trajectory from stem cells to neurons. Notably, deep-layer neurons appear in the early stages of neurogenesis, while upper-layer neurons appear later. While these different lineages show overlap in their differentiation program, cell fates are determined post-mitotically. Trajectories analysis from ventricular radial glia (vRGs) to outer radial glia (oRGs) revealed dynamic gene expression profiles and identified differential activation of BMP, FGF, and WNT signaling pathways between vRGs and oRGs. These results provide a comprehensive overview of the temporal patterns of gene expression leading to different fates of radial glial progenitors during neocortex layer formation.
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Affiliation(s)
- Longjiang Xu
- Institute of Medical Biology Chinese Academy of Medical Sciences, Chinese Academy of Medical Science and Peking Union Medical CollegeKunmingChina
| | - Zan Yuan
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, College of Informatics, Huazhong Agricultural UniversityWuhanChina
| | - Jiafeng Zhou
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Common Mechanism Research for Major Diseases, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
| | - Yuan Zhao
- Institute of Medical Biology Chinese Academy of Medical Sciences, Chinese Academy of Medical Science and Peking Union Medical CollegeKunmingChina
| | - Wei Liu
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Common Mechanism Research for Major Diseases, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
| | - Shuaiyao Lu
- Institute of Medical Biology Chinese Academy of Medical Sciences, Chinese Academy of Medical Science and Peking Union Medical CollegeKunmingChina
| | - Zhanlong He
- Institute of Medical Biology Chinese Academy of Medical Sciences, Chinese Academy of Medical Science and Peking Union Medical CollegeKunmingChina
| | - Boqin Qiang
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Common Mechanism Research for Major Diseases, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
| | - Pengcheng Shu
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Common Mechanism Research for Major Diseases, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
| | - Yang Chen
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Common Mechanism Research for Major Diseases, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
| | - Xiaozhong Peng
- Institute of Medical Biology Chinese Academy of Medical Sciences, Chinese Academy of Medical Science and Peking Union Medical CollegeKunmingChina
- Department of Molecular Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBeijingChina
- State Key Laboratory of Respiratory Health and Multimorbidity, Chinese Academy of Medical Sciences, Peking Union Medical CollegeBeijingChina
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
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14
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Fukuda K. The role of transposable elements in human evolution and methods for their functional analysis: current status and future perspectives. Genes Genet Syst 2024; 98:289-304. [PMID: 37866889 DOI: 10.1266/ggs.23-00140] [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] [Indexed: 10/24/2023] Open
Abstract
Transposable elements (TEs) are mobile DNA sequences that can insert themselves into various locations within the genome, causing mutations that may provide advantages or disadvantages to individuals and species. The insertion of TEs can result in genetic variation that may affect a wide range of human traits including genetic disorders. Understanding the role of TEs in human biology is crucial for both evolutionary and medical research. This review discusses the involvement of TEs in human traits and disease susceptibility, as well as methods for functional analysis of TEs.
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Affiliation(s)
- Kei Fukuda
- Integrative Genomics Unit, The University of Melbourne
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15
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Mañes-García J, Marco-Ferreres R, Beccari L. Shaping gene expression and its evolution by chromatin architecture and enhancer activity. Curr Top Dev Biol 2024; 159:406-437. [PMID: 38729683 DOI: 10.1016/bs.ctdb.2024.01.001] [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] [Indexed: 05/12/2024]
Abstract
Transcriptional regulation plays a pivotal role in orchestrating the intricate genetic programs governing embryonic development. The expression of developmental genes relies on the combined activity of several cis-regulatory elements (CREs), such as enhancers and silencers, which can be located at long linear distances from the genes that they regulate and that interact with them through establishment of chromatin loops. Mutations affecting their activity or interaction with their target genes can lead to developmental disorders and are thought to have importantly contributed to the evolution of the animal body plan. The income of next-generation-sequencing approaches has allowed identifying over a million of sequences with putative regulatory potential in the human genome. Characterizing their function and establishing gene-CREs maps is essential to decode the logic governing developmental gene expression and is one of the major challenges of the post-genomic era. Chromatin 3D organization plays an essential role in determining how CREs specifically contact their target genes while avoiding deleterious off-target interactions. Our understanding of these aspects has greatly advanced with the income of chromatin conformation capture techniques and fluorescence microscopy approaches to visualize the organization of DNA elements in the nucleus. Here we will summarize relevant aspects of how the interplay between CRE activity and chromatin 3D organization regulates developmental gene expression and how it relates to pathological conditions and the evolution of animal body plan.
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Affiliation(s)
| | | | - Leonardo Beccari
- Centro de Biología Molecular Severo Ochoa, CSIC-UAM, Madrid, Spain.
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16
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Hu B, Zhuang XL, Zhou L, Zhang G, Cooper DN, Wu DD. Deciphering the Role of Rapidly Evolving Conserved Elements in Primate Brain Development and Exploring Their Potential Involvement in Alzheimer's Disease. Mol Biol Evol 2024; 41:msae001. [PMID: 38175672 PMCID: PMC10798191 DOI: 10.1093/molbev/msae001] [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: 08/30/2023] [Revised: 12/27/2023] [Accepted: 12/29/2023] [Indexed: 01/05/2024] Open
Abstract
Although previous studies have identified human-specific accelerated regions as playing a key role in the recent evolution of the human brain, the characteristics and cellular functions of rapidly evolving conserved elements (RECEs) in ancestral primate lineages remain largely unexplored. Here, based on large-scale primate genome assemblies, we identify 888 RECEs that have been highly conserved in primates that exhibit significantly accelerated substitution rates in the ancestor of the Simiiformes. This primate lineage exhibits remarkable morphological innovations, including an expanded brain mass. Integrative multiomic analyses reveal that RECEs harbor sequences with potential cis-regulatory functions that are activated in the adult human brain. Importantly, genes linked to RECEs exhibit pronounced expression trajectories in the adult brain relative to the fetal stage. Furthermore, we observed an increase in the chromatin accessibility of RECEs in oligodendrocytes from individuals with Alzheimer's disease (AD) compared to that of a control group, indicating that these RECEs may contribute to brain aging and AD. Our findings serve to expand our knowledge of the genetic underpinnings of brain function during primate evolution.
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Affiliation(s)
- Benxia Hu
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - 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, Yunnan, China
| | - Long Zhou
- Center of Evolutionary and Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - Guojie Zhang
- Center of Evolutionary and Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - 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, Yunnan, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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17
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Abstract
Brain development in humans is achieved through precise spatiotemporal genetic control, the mechanisms of which remain largely elusive. Recently, integration of technological advances in human stem cell-based modelling with genome editing has emerged as a powerful platform to establish causative links between genotypes and phenotypes directly in the human system. Here, we review our current knowledge of complex genetic regulation of each key step of human brain development through the lens of evolutionary specialization and neurodevelopmental disorders and highlight the use of human stem cell-derived 2D cultures and 3D brain organoids to investigate human-enriched features and disease mechanisms. We also discuss opportunities and challenges of integrating new technologies to reveal the genetic architecture of human brain development and disorders.
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Affiliation(s)
- Yi Zhou
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, USA
- The Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Guo-Li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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18
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Okhovat M, VanCampen J, Nevonen KA, Harshman L, Li W, Layman CE, Ward S, Herrera J, Wells J, Sheng RR, Mao Y, Ndjamen B, Lima AC, Vigh-Conrad KA, Stendahl AM, Yang R, Fedorov L, Matthews IR, Easow SA, Chan DK, Jan TA, Eichler EE, Rugonyi S, Conrad DF, Ahituv N, Carbone L. TAD evolutionary and functional characterization reveals diversity in mammalian TAD boundary properties and function. Nat Commun 2023; 14:8111. [PMID: 38062027 PMCID: PMC10703881 DOI: 10.1038/s41467-023-43841-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 11/21/2023] [Indexed: 12/18/2023] Open
Abstract
Topological associating domains (TADs) are self-interacting genomic units crucial for shaping gene regulation patterns. Despite their importance, the extent of their evolutionary conservation and its functional implications remain largely unknown. In this study, we generate Hi-C and ChIP-seq data and compare TAD organization across four primate and four rodent species and characterize the genetic and epigenetic properties of TAD boundaries in correspondence to their evolutionary conservation. We find 14% of all human TAD boundaries to be shared among all eight species (ultraconserved), while 15% are human-specific. Ultraconserved TAD boundaries have stronger insulation strength, CTCF binding, and enrichment of older retrotransposons compared to species-specific boundaries. CRISPR-Cas9 knockouts of an ultraconserved boundary in a mouse model lead to tissue-specific gene expression changes and morphological phenotypes. Deletion of a human-specific boundary near the autism-related AUTS2 gene results in the upregulation of this gene in neurons. Overall, our study provides pertinent TAD boundary evolutionary conservation annotations and showcases the functional importance of TAD evolution.
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Affiliation(s)
- Mariam Okhovat
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA.
| | - Jake VanCampen
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Kimberly A Nevonen
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Lana Harshman
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Weiyu Li
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Cora E Layman
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Samantha Ward
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Jarod Herrera
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Jackson Wells
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Rory R Sheng
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Blaise Ndjamen
- Histology and Light Microscopy Core Facility, Gladstone Institutes, San Francisco, CA, USA
| | - Ana C Lima
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
| | | | - Alexandra M Stendahl
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
| | - Ran Yang
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
| | - Lev Fedorov
- OHSU Transgenic Mouse Models Core Lab, Oregon Health and Science University, Portland, OR, USA
| | - Ian R Matthews
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, CA, USA
| | - Sarah A Easow
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, CA, USA
| | - Dylan K Chan
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, CA, USA
| | - Taha A Jan
- Department of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA
| | - Sandra Rugonyi
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA
| | - Donald F Conrad
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA.
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA.
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA.
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA.
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19
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Yan Y, Tian Y, Wu Z, Zhang K, Yang R. Interchromosomal Colocalization with Parental Genes Is Linked to the Function and Evolution of Mammalian Retrocopies. Mol Biol Evol 2023; 40:msad265. [PMID: 38060983 PMCID: PMC10733166 DOI: 10.1093/molbev/msad265] [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: 07/13/2023] [Revised: 10/25/2023] [Accepted: 11/29/2023] [Indexed: 12/22/2023] Open
Abstract
Retrocopies are gene duplicates arising from reverse transcription of mature mRNA transcripts and their insertion back into the genome. While long being regarded as processed pseudogenes, more and more functional retrocopies have been discovered. How the stripped-down retrocopies recover expression capability and become functional paralogs continually intrigues evolutionary biologists. Here, we investigated the function and evolution of retrocopies in the context of 3D genome organization. By mapping retrocopy-parent pairs onto sequencing-based and imaging-based chromatin contact maps in human and mouse cell lines and onto Hi-C interaction maps in 5 other mammals, we found that retrocopies and their parental genes show a higher-than-expected interchromosomal colocalization frequency. The spatial interactions between retrocopies and parental genes occur frequently at loci in active subcompartments and near nuclear speckles. Accordingly, colocalized retrocopies are more actively transcribed and translated and are more evolutionarily conserved than noncolocalized ones. The active transcription of colocalized retrocopies may result from their permissive epigenetic environment and shared regulatory elements with parental genes. Population genetic analysis of retroposed gene copy number variants in human populations revealed that retrocopy insertions are not entirely random in regard to interchromosomal interactions and that colocalized retroposed gene copy number variants are more likely to reach high frequencies, suggesting that both insertion bias and natural selection contribute to the colocalization of retrocopy-parent pairs. Further dissection implies that reduced selection efficacy, rather than positive selection, contributes to the elevated allele frequency of colocalized retroposed gene copy number variants. Overall, our results hint a role of interchromosomal colocalization in the "resurrection" of initially neutral retrocopies.
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Affiliation(s)
- Yubin Yan
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yuhan Tian
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Zefeng Wu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Kunling Zhang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Ruolin Yang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
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20
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Rogers TF, Simakov O. Emerging questions on the mechanisms and dynamics of 3D genome evolution in spiralians. Brief Funct Genomics 2023; 22:533-542. [PMID: 37815133 PMCID: PMC10658181 DOI: 10.1093/bfgp/elad043] [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: 04/29/2023] [Revised: 08/17/2023] [Accepted: 09/12/2023] [Indexed: 10/11/2023] Open
Abstract
Information on how 3D genome topology emerged in animal evolution, how stable it is during development, its role in the evolution of phenotypic novelties and how exactly it affects gene expression is highly debated. So far, data to address these questions are lacking with the exception of a few key model species. Several gene regulatory mechanisms have been proposed, including scenarios where genome topology has little to no impact on gene expression, and vice versa. The ancient and diverse clade of spiralians may provide a crucial testing ground for such mechanisms. Sprialians have followed distinct evolutionary trajectories, with some clades experiencing genome expansions and/or large-scale genome rearrangements, and others undergoing genome contraction, substantially impacting their size and organisation. These changes have been associated with many phenotypic innovations in this clade. In this review, we describe how emerging genome topology data, along with functional tools, allow for testing these scenarios and discuss their predicted outcomes.
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Affiliation(s)
- Thea F Rogers
- Department of Neuroscience and Developmental Biology, Division of Molecular Evolution and Development, University of Vienna, Vienna, Austria
| | - Oleg Simakov
- Department of Neuroscience and Developmental Biology, Division of Molecular Evolution and Development, University of Vienna, Vienna, Austria
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21
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Li Y, Zeng PM, Wu J, Luo ZG. Advances and Applications of Brain Organoids. Neurosci Bull 2023; 39:1703-1716. [PMID: 37222855 PMCID: PMC10603019 DOI: 10.1007/s12264-023-01065-2] [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: 01/18/2023] [Accepted: 04/02/2023] [Indexed: 05/25/2023] Open
Abstract
Understanding the fundamental processes of human brain development and diseases is of great importance for our health. However, existing research models such as non-human primate and mouse models remain limited due to their developmental discrepancies compared with humans. Over the past years, an emerging model, the "brain organoid" integrated from human pluripotent stem cells, has been developed to mimic developmental processes of the human brain and disease-associated phenotypes to some extent, making it possible to better understand the complex structures and functions of the human brain. In this review, we summarize recent advances in brain organoid technologies and their applications in brain development and diseases, including neurodevelopmental, neurodegenerative, psychiatric diseases, and brain tumors. Finally, we also discuss current limitations and the potential of brain organoids.
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Affiliation(s)
- Yang Li
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Peng-Ming Zeng
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Jian Wu
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Zhen-Ge Luo
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
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22
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Meng X, Lin Q, Zeng X, Jiang J, Li M, Luo X, Chen K, Wu H, Hu Y, Liu C, Su B. Brain developmental and cortical connectivity changes in transgenic monkeys carrying the human-specific duplicated gene SRGAP2C. Natl Sci Rev 2023; 10:nwad281. [PMID: 38090550 PMCID: PMC10712708 DOI: 10.1093/nsr/nwad281] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/18/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024] Open
Abstract
Human-specific duplicated genes contributed to phenotypic innovations during the origin of our own species, such as an enlarged brain and highly developed cognitive abilities. While prior studies on transgenic mice carrying the human-specific SRGAP2C gene have shown enhanced brain connectivity, the relevance to humans remains unclear due to the significant evolutionary gap between humans and rodents. In this study, to investigate the phenotypic outcome and underlying genetic mechanism of SRGAP2C, we generated transgenic cynomolgus macaques (Macaca fascicularis) carrying the human-specific SRGAP2C gene. Longitudinal MRI imaging revealed delayed brain development with region-specific volume changes, accompanied by altered myelination levels in the temporal and occipital regions. On a cellular level, the transgenic monkeys exhibited increased deep-layer neurons during fetal neurogenesis and delayed synaptic maturation in adolescence. Moreover, transcriptome analysis detected neotenic expression in molecular pathways related to neuron ensheathment, synaptic connections, extracellular matrix and energy metabolism. Cognitively, the transgenic monkeys demonstrated improved motor planning and execution skills. Together, our findings provide new insights into the mechanisms by which the newly evolved gene shapes the unique development and circuitry of the human brain.
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Affiliation(s)
- Xiaoyu Meng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Jin Jiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Min Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Kaimin Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Haixu Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Cirong Liu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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23
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Liu H, Tsai H, Yang M, Li G, Bian Q, Ding G, Wu D, Dai J. Three-dimensional genome structure and function. MedComm (Beijing) 2023; 4:e326. [PMID: 37426677 PMCID: PMC10329473 DOI: 10.1002/mco2.326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 05/31/2023] [Accepted: 06/09/2023] [Indexed: 07/11/2023] Open
Abstract
Linear DNA undergoes a series of compression and folding events, forming various three-dimensional (3D) structural units in mammalian cells, including chromosomal territory, compartment, topologically associating domain, and chromatin loop. These structures play crucial roles in regulating gene expression, cell differentiation, and disease progression. Deciphering the principles underlying 3D genome folding and the molecular mechanisms governing cell fate determination remains a challenge. With advancements in high-throughput sequencing and imaging techniques, the hierarchical organization and functional roles of higher-order chromatin structures have been gradually illuminated. This review systematically discussed the structural hierarchy of the 3D genome, the effects and mechanisms of cis-regulatory elements interaction in the 3D genome for regulating spatiotemporally specific gene expression, the roles and mechanisms of dynamic changes in 3D chromatin conformation during embryonic development, and the pathological mechanisms of diseases such as congenital developmental abnormalities and cancer, which are attributed to alterations in 3D genome organization and aberrations in key structural proteins. Finally, prospects were made for the research about 3D genome structure, function, and genetic intervention, and the roles in disease development, prevention, and treatment, which may offer some clues for precise diagnosis and treatment of related diseases.
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Affiliation(s)
- Hao Liu
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
- School of StomatologyWeifang Medical UniversityWeifangChina
| | - Hsiangyu Tsai
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Maoquan Yang
- School of Clinical MedicineWeifang Medical UniversityWeifangChina
| | - Guozhi Li
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Qian Bian
- Shanghai Institute of Precision MedicineShanghaiChina
| | - Gang Ding
- School of StomatologyWeifang Medical UniversityWeifangChina
| | - Dandan Wu
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Jiewen Dai
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
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24
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Zhang G, Li Y, Wei G. Multi-omic analysis reveals dynamic changes of three-dimensional chromatin architecture during T cell differentiation. Commun Biol 2023; 6:773. [PMID: 37488215 PMCID: PMC10366224 DOI: 10.1038/s42003-023-05141-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 07/13/2023] [Indexed: 07/26/2023] Open
Abstract
Cell differentiation results in widespread changes in transcriptional programs as well as multi-level remodeling of three-dimensional genome architecture. Nonetheless, few synthetically investigate the chromatin higher-order landscapes in different T helper (Th) cells. Using RNA-Seq, ATAC-Seq and Hi-C assays, we characterize dynamic changes in chromatin organization at different levels during Naive CD4+ T cells differentiation into T helper 17 (Th17) and T helper 1 (Th1) cells. Upon differentiation, we observe decreased short-range and increased extra-long-range chromatin interactions. Although there is no apparent global switch in the A/B compartments, Th cells display the weaker compartmentalization. A portion of topologically associated domains are rearranged. Furthermore, we identify cell-type specific enhancer-promoter loops, many of which are associated with functional genes in Th cells, such as Rorc facilitating Th17 differentiation and Hif1a responding to intracellular oxygen levels in Th1. Taken together, these results uncover the general patterns of chromatin reorganization and epigenetic landscapes of gene regulation during T helper cell differentiation.
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Affiliation(s)
- Ge Zhang
- 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
| | - Ying 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.
| | - Gang Wei
- 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.
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25
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Zhou Y, Zhan X, Jin J, Zhou L, Bergman J, Li X, Rousselle MMC, Belles MR, Zhao L, Fang M, Chen J, Fang Q, Kuderna L, Marques-Bonet T, Kitayama H, Hayakawa T, Yao YG, Yang H, Cooper DN, Qi X, Wu DD, Schierup MH, Zhang G. Eighty million years of rapid evolution of the primate Y chromosome. Nat Ecol Evol 2023; 7:1114-1130. [PMID: 37268856 DOI: 10.1038/s41559-022-01974-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 12/15/2022] [Indexed: 06/04/2023]
Abstract
The Y chromosome usually plays a critical role in determining male sex and comprises sequence classes that have experienced unique evolutionary trajectories. Here we generated 19 new primate sex chromosome assemblies, analysed them with 10 existing assemblies and report rapid evolution of the Y chromosome across primates. The pseudoautosomal boundary has shifted at least six times during primate evolution, leading to the formation of a Simiiformes-specific evolutionary stratum and to the independent start of young strata in Catarrhini and Platyrrhini. Different primate lineages experienced different rates of gene loss and structural and chromatin change on their Y chromosomes. Selection on several Y-linked genes has contributed to the evolution of male developmental traits across the primates. Additionally, lineage-specific expansions of ampliconic regions have further increased the diversification of the structure and gene composition of the Y chromosome. Overall, our comprehensive analysis has broadened our knowledge of the evolution of the primate Y chromosome.
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Affiliation(s)
| | | | | | - Long Zhou
- Centre for Evolutionary & Organismal Biology, and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
| | - Juraj Bergman
- Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University, Aarhus C., Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus C., Denmark
| | - Xuemei Li
- BGI-Shenzhen, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | - Lan Zhao
- College of Life Sciences, Northwest University, Xi'an, China
| | | | | | - Qi Fang
- BGI-Shenzhen, Shenzhen, China
| | - Lukas Kuderna
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Barcelona, Spain
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Haruka Kitayama
- Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
| | - Takashi Hayakawa
- Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan
- Japan Monkey Centre, Inuyama, Japan
| | - Yong-Gang Yao
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming, 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, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 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, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- James D. Watson Institute of Genome Sciences, Hangzhou, China
- Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, BGI-Shenzhen, Shenzhen, China
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Xiaoguang Qi
- College of Life Sciences, Northwest University, Xi'an, China
| | - Dong-Dong Wu
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 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, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | | | - Guojie Zhang
- Centre for Evolutionary & Organismal Biology, and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China.
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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26
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Shao Y, Zhou L, Li F, Zhao L, Zhang BL, Shao F, Chen JW, Chen CY, Bi X, Zhuang XL, Zhu HL, Hu J, Sun Z, Li X, Wang D, Rivas-González I, Wang S, Wang YM, Chen W, Li G, Lu HM, Liu Y, Kuderna LFK, Farh KKH, Fan PF, Yu L, Li M, Liu ZJ, Tiley GP, Yoder AD, Roos C, Hayakawa T, Marques-Bonet T, Rogers J, Stenson PD, Cooper DN, Schierup MH, Yao YG, Zhang YP, Wang W, Qi XG, Zhang G, Wu DD. Phylogenomic analyses provide insights into primate evolution. Science 2023; 380:913-924. [PMID: 37262173 DOI: 10.1126/science.abn6919] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 01/26/2023] [Indexed: 06/03/2023]
Abstract
Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution.
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Affiliation(s)
- 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 650201, China
| | - Long Zhou
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Fang Li
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Institute of Animal Sex and Development, ZhejiangWanli University, Ningbo 315100, China
| | - Lan Zhao
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Bao-Lin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Feng Shao
- Key Laboratory of Freshwater Fish Reproduction and Development (Ministry of Education), Southwest University School of Life Sciences, Chongqing 400715, China
| | | | - Chun-Yan Chen
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xupeng Bi
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
| | - 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 650201, China
- Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650204, China
| | | | - Jiang Hu
- Grandomics Biosciences, Beijing 102206, China
| | - Zongyi Sun
- Grandomics Biosciences, Beijing 102206, China
| | - Xin Li
- Grandomics Biosciences, Beijing 102206, China
| | - Depeng Wang
- Grandomics Biosciences, Beijing 102206, China
| | | | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Yun-Mei Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Wu Chen
- Guangzhou Zoo & Guangzhou Wildlife Research Center, Guangzhou 510070, China
| | - Gang Li
- College of Life Sciences, Shaanxi Normal University, Xi'an 710119, China
| | - Hui-Meng Lu
- School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yang Liu
- College of Life Sciences, Shaanxi Normal University, Xi'an 710119, China
| | - Lukas F K Kuderna
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA 92122, USA
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA 92122, USA
| | - Peng-Fei Fan
- School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Li Yu
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Ming Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhi-Jin Liu
- College of Life Sciences, Capital Normal University, Beijing 100048, China
| | - George P Tiley
- Department of Biology, Duke University, Durham, NC 27708, USA
| | - Anne D Yoder
- Department of Biology, Duke University, Durham, NC 27708, USA
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Takashi Hayakawa
- Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan
- Japan Monkey Centre, Inuyama, Aichi 484-0081, Japan
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Jeffrey Rogers
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Peter D Stenson
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | | | - Yong-Gang Yao
- 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 650201, China
- Center for Excellence in Animal Evolution and Genetics, 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 650107, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center for Excellence in Animal Evolution and Genetics, 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 650107, 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 650201, China
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710072, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiao-Guang Qi
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
- Center of Evolutionary & Organismal Biology, and Women's Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou 311121, 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 650201, China
- Center for Excellence in Animal Evolution and Genetics, 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 650107, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650204, China
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27
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Liu P, Li D, Zhang J, He M, Gao D, Wang Y, Lin Y, Pan D, Li P, Wang T, Li J, Kong F, Zeng B, Lu L, Ma J, Long K, Li G, Tang Q, Jin L, Li M. Comparative three-dimensional genome architectures of adipose tissues provide insight into human-specific regulation of metabolic homeostasis. J Biol Chem 2023; 299:104757. [PMID: 37116707 PMCID: PMC10245122 DOI: 10.1016/j.jbc.2023.104757] [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: 10/25/2022] [Revised: 03/22/2023] [Accepted: 04/19/2023] [Indexed: 04/30/2023] Open
Abstract
Elucidating the regulatory mechanisms of human adipose tissues (ATs) evolution is essential for understanding human-specific metabolic regulation, but the functional importance and evolutionary dynamics of three-dimensional (3D) genome organizations of ATs are not well defined. Here, we compared the 3D genome architectures of anatomically distinct ATs from humans and six representative mammalian models. We recognized evolutionarily conserved and human-specific chromatin conformation in ATs at multiple scales, including compartmentalization, topologically associating domain (TAD), and promoter-enhancer interactions (PEI), which have not been described previously. We found PEI are much more evolutionarily dynamic with respect to compartmentalization and topologically associating domain. Compared to conserved PEIs, human-specific PEIs are enriched for human-specific sequence, and the binding motifs of their potential mediators (transcription factors) are less conserved. Our data also demonstrated that genes involved in the evolutionary dynamics of chromatin organization have weaker transcriptional conservation than those associated with conserved chromatin organization. Furthermore, the genes involved in energy metabolism and the maintenance of metabolic homeostasis are enriched in human-specific chromatin organization, while housekeeping genes, health-related genes, and genetic variations are enriched in evolutionarily conserved compared to human-specific chromatin organization. Finally, we showed extensively divergent human-specific 3D genome organizations among one subcutaneous and three visceral ATs. Together, these findings provide a global overview of 3D genome architecture dynamics between ATs from human and mammalian models and new insights into understanding the regulatory evolution of human ATs.
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Affiliation(s)
- Pengliang Liu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Diyan Li
- School of Pharmacy, Chengdu University, Chengdu, Sichuan, China.
| | - Jiaman Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Mengnan He
- Wildlife Conservation Research Department, Chengdu Research Base of Giant Panda Breeding, Chengdu, Sichuan, China
| | - Dengfeng Gao
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yujie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yu Lin
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Dengke Pan
- Institute of Organ Transplantation, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan, China
| | - Penghao Li
- Jinxin Research Institute for Reproductive Medicine & Genetics, Chengdu Xi'nan Gynecology Hospital, Chengdu, Sichuan, China
| | - Tao Wang
- School of Pharmacy, Chengdu University, Chengdu, Sichuan, China
| | - Jing Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Fanli Kong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Bo Zeng
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lu Lu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jideng Ma
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Keren Long
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Guisen Li
- Renal Department & Nephrology Institute, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China
| | - Qianzi Tang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Long Jin
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Mingzhou Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China.
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28
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Fan S, Dang D, Ye Y, Zhang SW, Gao L, Zhang S. scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking. J Mol Cell Biol 2023; 15:mjad003. [PMID: 36708167 PMCID: PMC10308180 DOI: 10.1093/jmcb/mjad003] [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: 04/01/2022] [Revised: 09/18/2022] [Accepted: 01/25/2023] [Indexed: 01/29/2023] Open
Abstract
Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells. However, high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis. Here, we developed a single-cell Hi-C simulator (scHi-CSim) that generates high-fidelity data for benchmarking. scHi-CSim merges neighboring cells to overcome the sparseness of data, samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells, and estimates the empirical distribution of restriction fragments to generate simulated data. We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data. Furthermore, scHi-CSim is flexible to change sequencing depth and the number of simulated replicates. We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains. We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.
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Affiliation(s)
- Shichen Fan
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Dachang Dang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yusen Ye
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Shao-Wu Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lin Gao
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Shihua Zhang
- NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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29
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Wang L, Wang X, Liu C, Xu W, Kuang W, Bu Q, Li H, Zhao Y, Jiang L, Chen Y, Qin F, Li S, Wei Q, Liu X, Liu B, Chen Y, Dai Y, Wang H, Tian J, Cao G, Zhao Y, Cen X. Morphine Re-arranges Chromatin Spatial Architecture of Primate Cortical Neurons. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:551-572. [PMID: 37209997 PMCID: PMC10787020 DOI: 10.1016/j.gpb.2023.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 05/22/2023]
Abstract
The expression of linear DNA sequence is precisely regulated by the three-dimensional (3D) architecture of chromatin. Morphine-induced aberrant gene networks of neurons have been extensively investigated; however, how morphine impacts the 3D genomic architecture of neurons is still unknown. Here, we applied digestion-ligation-only high-throughput chromosome conformation capture (DLO Hi-C) technology to investigate the effects of morphine on the 3D chromatin architecture of primate cortical neurons. After receiving continuous morphine administration for 90 days on rhesus monkeys, we discovered that morphine re-arranged chromosome territories, with a total of 391 segmented compartments being switched. Morphine altered over half of the detected topologically associated domains (TADs), most of which exhibited a variety of shifts, followed by separating and fusing types. Analysis of the looping events at kilobase-scale resolution revealed that morphine increased not only the number but also the length of differential loops. Moreover, all identified differentially expressed genes from the RNA sequencing data were mapped to the specific TAD boundaries or differential loops, and were further validated for changed expression. Collectively, an altered 3D genomic architecture of cortical neurons may regulate the gene networks associated with morphine effects. Our finding provides critical hubs connecting chromosome spatial organization and gene networks associated with the morphine effects in humans.
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Affiliation(s)
- Liang Wang
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xiaojie Wang
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Chunqi Liu
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Xu
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China; Shenzhen Key Laboratory of Drug Addiction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qian Bu
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hongchun Li
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ying Zhao
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Linhong Jiang
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yaxing Chen
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Feng Qin
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Shu Li
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qinfan Wei
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xiaocong Liu
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Bin Liu
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuanyuan Chen
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yanping Dai
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hongbo Wang
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China
| | - Jingwei Tian
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China
| | - Gang Cao
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Yinglan Zhao
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xiaobo Cen
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China.
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30
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Keough KC, Whalen S, Inoue F, Przytycki PF, Fair T, Deng C, Steyert M, Ryu H, Lindblad-Toh K, Karlsson E, Nowakowski T, Ahituv N, Pollen A, Pollard KS. Three-dimensional genome rewiring in loci with human accelerated regions. Science 2023; 380:eabm1696. [PMID: 37104607 PMCID: PMC10999243 DOI: 10.1126/science.abm1696] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 03/01/2023] [Indexed: 04/29/2023]
Abstract
Human accelerated regions (HARs) are conserved genomic loci that evolved at an accelerated rate in the human lineage and may underlie human-specific traits. We generated HARs and chimpanzee accelerated regions with an automated pipeline and an alignment of 241 mammalian genomes. Combining deep learning with chromatin capture experiments in human and chimpanzee neural progenitor cells, we discovered a significant enrichment of HARs in topologically associating domains containing human-specific genomic variants that change three-dimensional (3D) genome organization. Differential gene expression between humans and chimpanzees at these loci suggests rewiring of regulatory interactions between HARs and neurodevelopmental genes. Thus, comparative genomics together with models of 3D genome folding revealed enhancer hijacking as an explanation for the rapid evolution of HARs.
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Affiliation(s)
- Kathleen C Keough
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Sean Whalen
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
| | - Fumitaka Inoue
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Pawel F Przytycki
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
| | - Tyler Fair
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California San Francisco, San Francisco, CA, USA
| | - Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Marilyn Steyert
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA
| | - Hane Ryu
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elinor Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Tomasz Nowakowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Alex Pollen
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics and Bakar Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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31
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Ni L, Tian Z. Toward cis-regulation in soybean: a 3D genome scope. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:28. [PMID: 37313524 PMCID: PMC10248674 DOI: 10.1007/s11032-023-01374-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/25/2023] [Indexed: 06/15/2023]
Abstract
In eukaryotic cells, 3D genome plays an important role in the regulation of gene spatiotemporal expression, which is essential for the biological and developmental processes in a life cycle. In the past decade, the development of high-throughput technologies greatly enhances our ability to map the 3D genome organization, identifies multiple 3D genome structures, and investigates the functional role of 3D genome organization in gene regulation, which facilitates our understandings of cis-regulatory landscape and biological development. Comparing with the comprehensive analyses of 3D genome in mammals and model plants, the progress in soybean is much less. Future development and application of tools to precisely manipulate 3D genome structure at different levels will significantly strengthen the functional genome study and molecular breeding in soybean. Here, we review the recent progresses in 3D genome study and discuss future directions, which may help to improve soybean 3D functional genome study and molecular breeding.
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Affiliation(s)
- Lingbin Ni
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agriculture Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agriculture Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
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32
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Van Belleghem SM, Ruggieri AA, Concha C, Livraghi L, Hebberecht L, Rivera ES, Ogilvie JG, Hanly JJ, Warren IA, Planas S, Ortiz-Ruiz Y, Reed R, Lewis JJ, Jiggins CD, Counterman BA, McMillan WO, Papa R. High level of novelty under the hood of convergent evolution. Science 2023; 379:1043-1049. [PMID: 36893249 PMCID: PMC11000492 DOI: 10.1126/science.ade0004] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 02/08/2023] [Indexed: 03/11/2023]
Abstract
Little is known about the extent to which species use homologous regulatory architectures to achieve phenotypic convergence. By characterizing chromatin accessibility and gene expression in developing wing tissues, we compared the regulatory architecture of convergence between a pair of mimetic butterfly species. Although a handful of color pattern genes are known to be involved in their convergence, our data suggest that different mutational paths underlie the integration of these genes into wing pattern development. This is supported by a large fraction of accessible chromatin being exclusive to each species, including the de novo lineage-specific evolution of a modular optix enhancer. These findings may be explained by a high level of developmental drift and evolutionary contingency that occurs during the independent evolution of mimicry.
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Affiliation(s)
- Steven M. Van Belleghem
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
- Ecology, Evolution and Conservation Biology, Biology Department, KU Leuven, Leuven, Belgium
| | - Angelo A. Ruggieri
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
| | - Carolina Concha
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
| | - Luca Livraghi
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- Department of Biological Sciences, The George Washington University, Washington, DC, USA
| | - Laura Hebberecht
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- School of Biological Sciences, Bristol University, Bristol, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Edgardo Santiago Rivera
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- Department of Biomaterials, Universität Bayreuth, Bayreuth, Germany
| | - James G. Ogilvie
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- Department of Biological Sciences, Auburn University, Auburn, Alabama, USA
| | - Joseph J. Hanly
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- Department of Biological Sciences, The George Washington University, Washington, DC, USA
| | - Ian A. Warren
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Silvia Planas
- Molecular Sciences and Research Center, University of Puerto Rico, San Juan, Puerto Rico
| | - Yadira Ortiz-Ruiz
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
- Molecular Sciences and Research Center, University of Puerto Rico, San Juan, Puerto Rico
| | - Robert Reed
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
| | - James J. Lewis
- Department of Genetics and Biochemistry, Clemson University, Clemson, South Carolina, USA
| | | | | | - W. Owen McMillan
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
| | - Riccardo Papa
- Department of Biology, University of Puerto Rico, Rio Piedras, Puerto Rico
- Molecular Sciences and Research Center, University of Puerto Rico, San Juan, Puerto Rico
- Comprehensive Cancer Center, University of Puerto Rico, San Juan, Puerto Rico
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33
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Okhovat M, VanCampen J, Lima AC, Nevonen KA, Layman CE, Ward S, Herrera J, Stendahl AM, Yang R, Harshman L, Li W, Sheng RR, Mao Y, Fedorov L, Ndjamen B, Vigh-Conrad KA, Matthews IR, Easow SA, Chan DK, Jan TA, Eichler EE, Rugonyi S, Conrad DF, Ahituv N, Carbone L. TAD Evolutionary and functional characterization reveals diversity in mammalian TAD boundary properties and function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531534. [PMID: 36945527 PMCID: PMC10028908 DOI: 10.1101/2023.03.07.531534] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
Topological associating domains (TADs) are self-interacting genomic units crucial for shaping gene regulation patterns. Despite their importance, the extent of their evolutionary conservation and its functional implications remain largely unknown. In this study, we generate Hi-C and ChIP-seq data and compare TAD organization across four primate and four rodent species, and characterize the genetic and epigenetic properties of TAD boundaries in correspondence to their evolutionary conservation. We find that only 14% of all human TAD boundaries are shared among all eight species (ultraconserved), while 15% are human-specific. Ultraconserved TAD boundaries have stronger insulation strength, CTCF binding, and enrichment of older retrotransposons, compared to species-specific boundaries. CRISPR-Cas9 knockouts of two ultraconserved boundaries in mouse models leads to tissue-specific gene expression changes and morphological phenotypes. Deletion of a human-specific boundary near the autism-related AUTS2 gene results in upregulation of this gene in neurons. Overall, our study provides pertinent TAD boundary evolutionary conservation annotations, and showcase the functional importance of TAD evolution.
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Quan Y, Zhang KX, Zhang HY. The gut microbiota links disease to human genome evolution. Trends Genet 2023; 39:451-461. [PMID: 36872184 DOI: 10.1016/j.tig.2023.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 02/03/2023] [Accepted: 02/13/2023] [Indexed: 03/06/2023]
Abstract
A large number of studies have established a causal relationship between the gut microbiota and human disease. In addition, the composition of the microbiota is substantially influenced by the human genome. Modern medical research has confirmed that the pathogenesis of various diseases is closely related to evolutionary events in the human genome. Specific regions of the human genome known as human accelerated regions (HARs) have evolved rapidly over several million years since humans diverged from a common ancestor with chimpanzees, and HARs have been found to be involved in some human-specific diseases. Furthermore, the HAR-regulated gut microbiota has undergone rapid changes during human evolution. We propose that the gut microbiota may serve as an important mediator linking diseases to human genome evolution.
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Affiliation(s)
- Yuan Quan
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, PR China; Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
| | - Ke-Xin Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
| | - Hong-Yu Zhang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, PR China; Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China.
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35
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Dang D, Zhang SW, Duan R, Zhang S. Defining the separation landscape of topological domains for decoding consensus domain organization of the 3D genome. Genome Res 2023; 33:386-400. [PMID: 36894325 PMCID: PMC10078287 DOI: 10.1101/gr.277187.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 02/23/2023] [Indexed: 03/11/2023]
Abstract
Topologically associating domains (TADs) have emerged as basic structural and functional units of genome organization and have been determined by many computational methods from Hi-C contact maps. However, the TADs obtained by different methods vary greatly, which makes the accurate determination of TADs a challenging issue and hinders subsequent biological analyses about their organization and functions. Obvious inconsistencies among the TADs identified by different methods indeed make the statistical and biological properties of TADs overly depend on the chosen method rather than on the data. To this end, we use the consensus structural information captured by these methods to define the TAD separation landscape for decoding the consensus domain organization of the 3D genome. We show that the TAD separation landscape could be used to compare domain boundaries across multiple cell types for discovering conserved and divergent topological structures, decipher three types of boundary regions with diverse biological features, and identify consensus TADs (ConsTADs). We illustrate that these analyses could deepen our understanding of the relationships between the topological domains and chromatin states, gene expression, and DNA replication timing.
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Affiliation(s)
- Dachang Dang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shao-Wu Zhang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an 710072, China;
| | - Ran Duan
- Department of Software Engineering, Yunnan University, Kunming 650500, China
| | - Shihua Zhang
- NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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36
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Ye Y, Zhang S, Gao L, Zhu Y, Zhang J. Deciphering Hierarchical Chromatin Domains and Preference of Genomic Position Forming Boundaries in Single Mouse Embryonic Stem Cells. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205162. [PMID: 36658736 PMCID: PMC10015865 DOI: 10.1002/advs.202205162] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/15/2022] [Indexed: 06/17/2023]
Abstract
The exploration of single-cell 3D genome maps reveals that chromatin domains are indeed physical structures presenting in single cells, and domain boundaries vary from cell to cell. However, systematic analysis of the association between regulatory factor binding and elements and the formation of chromatin domains in single cells has not yet emerged. To this end, a hierarchical chromatin domain structure identification algorithm (named as HiCS) is first developed from individual single-cell Hi-C maps, with superior performance in both accuracy and efficiency. The results suggest that in addition to the known CTCF-cohesin complex, Polycomb, TrxG, pluripotent protein families, and other multiple factors also contribute to shaping chromatin domain boundaries in single embryonic stem cells. Different cooperation patterns of these regulatory factors drive genomic position categories with differential preferences forming boundaries, and the most extensive six types of retrotransposons are differentially distributed in these genomic position categories with preferential localization. The above results suggest that these different retrotransposons within genomic regions interplay with regulatory factors navigating the preference of genomic positions forming boundaries, driving the formation of higher-order chromatin structures, and thus regulating cell functions in single mouse embryonic stem cells.
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Affiliation(s)
- Yusen Ye
- School of Computer Science and TechnologyXidian UniversityXi'anShaanxi710071P. R. China
| | - Shihua Zhang
- NCMISCEMSRCSDSAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190P. R. China
- School of Mathematical SciencesUniversity of Chinese Academy of SciencesBeijing100049P. R. China
- Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunming650223P. R. China
| | - Lin Gao
- School of Computer Science and TechnologyXidian UniversityXi'anShaanxi710071P. R. China
| | - Yuqing Zhu
- Center for Stem Cell and Translational MedicineSchool of Life SciencesAnhui UniversityHefeiAnhui230601P. R. China
| | - Jin Zhang
- Center for Stem Cell and Regenerative MedicineDepartment of Basic Medical Sciences, and Bone Marrow Transplantation Center of the First Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang310003P. R. China
- Zhejiang Laboratory for Systems and Precision MedicineZhejiang University Medical CenterHangzhouZhejiang311121P. R. China
- Institute of HematologyZhejiang UniversityHangzhouZhejiang310058P. R. China
- Center of Gene/Cell Engineering and Genome MedicineHangzhouZhejiang310058P. R. China
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37
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Li S, Hannenhalli S, Ovcharenko I. De novo human brain enhancers created by single-nucleotide mutations. SCIENCE ADVANCES 2023; 9:eadd2911. [PMID: 36791193 PMCID: PMC9931207 DOI: 10.1126/sciadv.add2911] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 01/12/2023] [Indexed: 05/30/2023]
Abstract
Advanced human cognition is attributed to increased neocortex size and complexity, but the underlying evolutionary and regulatory mechanisms are largely unknown. Using human and macaque embryonic neocortical H3K27ac data coupled with a deep learning model of enhancers, we identified ~4000 enhancer gains in humans, which, per our model, can often be attributed to single-nucleotide essential mutations. Our analyses suggest that functional gains in embryonic brain development are associated with de novo enhancers whose putative target genes exhibit increased expression in progenitor cells and interneurons and partake in critical neural developmental processes. Essential mutations alter enhancer activity through altered binding of key transcription factors (TFs) of embryonic neocortex, including ISL1, POU3F2, PITX1/2, and several SOX TFs, and are associated with central nervous system disorders. Overall, our results suggest that essential mutations lead to gain of embryonic neocortex enhancers, which orchestrate expression of genes involved in critical developmental processes associated with human cognition.
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Affiliation(s)
- Shan Li
- Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20892, USA
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sridhar Hannenhalli
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ivan Ovcharenko
- Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20892, USA
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38
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Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
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Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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39
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Acemel RD, Lupiáñez DG. Evolution of 3D chromatin organization at different scales. Curr Opin Genet Dev 2023; 78:102019. [PMID: 36603519 DOI: 10.1016/j.gde.2022.102019] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/30/2022] [Accepted: 12/03/2022] [Indexed: 01/04/2023]
Abstract
Most animal genomes fold in 3D chromatin domains called topologically associated domains (TADs) that facilitate interactions between cis-regulatory elements (CREs) and promoters. Owing to their critical role in the control of developmental gene expression, we explore how TADs have shaped animal evolution. In the light of recent studies that profile TADs in disparate animal lineages, we discuss their phylogenetic distribution and the mechanisms that underlie their formation. We present evidence indicating that TADs are plastic entities composed of genomic strata of different ages: ancient cores are combined with newer regions and brought into extant TADs through genomic rearrangements. We highlight that newly incorporated TAD strata enable the establishment of new CRE-promoter interactions and in turn new expression patterns that can drive phenotypical innovation. We further highlight how subtle changes in chromatin folding may fine-tune the expression levels of developmental genes and hold a potential for evolutionary significance.
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40
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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: 14] [Impact Index Per Article: 14.0] [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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41
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Levchenko A, Gusev F, Rogaev E. The evolutionary origin of psychosis. Front Psychiatry 2023; 14:1115929. [PMID: 36741116 PMCID: PMC9894884 DOI: 10.3389/fpsyt.2023.1115929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/05/2023] [Indexed: 01/21/2023] Open
Abstract
Imagination, the driving force of creativity, and primary psychosis are human-specific, since we do not observe behaviors in other species that would convincingly suggest they possess the same traits. Both these traits have been linked to the function of the prefrontal cortex, which is the most evolutionarily novel region of the human brain. A number of evolutionarily novel genetic and epigenetic changes that determine the human brain-specific structure and function have been discovered in recent years. Among them are genomic loci subjected to increased rates of single nucleotide substitutions in humans, called human accelerated regions. These mostly regulatory regions are involved in brain development and sometimes contain genetic variants that confer a risk for schizophrenia. On the other hand, neuroimaging data suggest that mind wandering and related phenomena (as a proxy of imagination) are in many ways similar to rapid eye movement dreaming, a function also present in non-human species. Furthermore, both functions are similar to psychosis in several ways: for example, the same brain areas are activated both in dreams and visual hallucinations. In the present Perspective we hypothesize that imagination is an evolutionary adaptation of dreaming, while primary psychosis results from deficient control by higher-order brain areas over imagination. In the light of this, human accelerated regions might be one of the key drivers in evolution of human imagination and the pathogenesis of psychotic disorders.
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Affiliation(s)
- Anastasia Levchenko
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Fedor Gusev
- Center for Genetics and Life Sciences, Department of Genetics, Sirius University of Science and Technology, Sochi, Russia.,Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Evgeny Rogaev
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Department of Psychiatry, UMass Chan Medical School, Shrewsbury, MA, United States
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42
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Wang M, Li J, Qi Z, Long Y, Pei L, Huang X, Grover CE, Du X, Xia C, Wang P, Liu Z, You J, Tian X, Ma Y, Wang R, Chen X, He X, Fang DD, Sun Y, Tu L, Jin S, Zhu L, Wendel JF, Zhang X. Genomic innovation and regulatory rewiring during evolution of the cotton genus Gossypium. Nat Genet 2022; 54:1959-1971. [PMID: 36474047 DOI: 10.1038/s41588-022-01237-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 10/20/2022] [Indexed: 12/13/2022]
Abstract
Phenotypic diversity and evolutionary innovation ultimately trace to variation in genomic sequence and rewiring of regulatory networks. Here, we constructed a pan-genome of the Gossypium genus using ten representative diploid genomes. We document the genomic evolutionary history and the impact of lineage-specific transposon amplification on differential genome composition. The pan-3D genome reveals evolutionary connections between transposon-driven genome size variation and both higher-order chromatin structure reorganization and the rewiring of chromatin interactome. We linked changes in chromatin structures to phenotypic differences in cotton fiber and identified regulatory variations that decode the genetic basis of fiber length, the latter enabled by sequencing 1,005 transcriptomes during fiber development. We showcase how pan-genomic, pan-3D genomic and genetic regulatory data serve as a resource for delineating the evolutionary basis of spinnable cotton fiber. Our work provides insights into the evolution of genome organization and regulation and will inform cotton improvement by enabling regulome-based approaches.
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Affiliation(s)
- Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Jianying Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Zhengyang Qi
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Yuexuan Long
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Liuling Pei
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xianhui Huang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Corrinne E Grover
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Chunjiao Xia
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Pengcheng Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Zhenping Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Jiaqi You
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xuehan Tian
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Yizan Ma
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Ruipeng Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xinyuan Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xin He
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, USA
| | - Yuqiang Sun
- Zhejiang Sci-Tech University College of Life Sciences, Zhejiang, Hangzhou, China
| | - Lili Tu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Shuangxia Jin
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Longfu Zhu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Jonathan F Wendel
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA.
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
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43
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Bi XA, Mao Y, Luo S, Wu H, Zhang L, Luo X, Xu L. A novel generation adversarial network framework with characteristics aggregation and diffusion for brain disease classification and feature selection. Brief Bioinform 2022; 23:6762742. [PMID: 36259367 DOI: 10.1093/bib/bbac454] [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: 05/25/2022] [Revised: 09/01/2022] [Accepted: 09/23/2022] [Indexed: 12/14/2022] Open
Abstract
Imaging genetics provides unique insights into the pathological studies of complex brain diseases by integrating the characteristics of multi-level medical data. However, most current imaging genetics research performs incomplete data fusion. Also, there is a lack of effective deep learning methods to analyze neuroimaging and genetic data jointly. Therefore, this paper first constructs the brain region-gene networks to intuitively represent the association pattern of pathogenetic factors. Second, a novel feature information aggregation model is constructed to accurately describe the information aggregation process among brain region nodes and gene nodes. Finally, a deep learning method called feature information aggregation and diffusion generative adversarial network (FIAD-GAN) is proposed to efficiently classify samples and select features. We focus on improving the generator with the proposed convolution and deconvolution operations, with which the interpretability of the deep learning framework has been dramatically improved. The experimental results indicate that FIAD-GAN can not only achieve superior results in various disease classification tasks but also extract brain regions and genes closely related to AD. This work provides a novel method for intelligent clinical decisions. The relevant biomedical discoveries provide a reliable reference and technical basis for the clinical diagnosis, treatment and pathological analysis of disease.
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Affiliation(s)
- Xia-An Bi
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, and College of Information Science and Engineering in Hunan Normal University, Changsha, P.R. China
| | - Yuhua Mao
- Department of Computing, School of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Sheng Luo
- Department of Computing, School of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Hao Wu
- Department of Computing, School of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Lixia Zhang
- School of Information Science and Engineering, Hunan Normal University, Changsha, P.R. China
| | - Xun Luo
- College of Information Science and Engineering in Hunan Normal University, Changsha, P.R. China
| | - Luyun Xu
- College of Business in Hunan Normal University, Changsha, P.R. China
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44
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Plaza-Jennings A, Valada A, Akbarian S. 3D Genome Plasticity in Normal and Diseased Neurodevelopment. Genes (Basel) 2022; 13:1999. [PMID: 36360237 PMCID: PMC9690570 DOI: 10.3390/genes13111999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/18/2022] [Accepted: 10/26/2022] [Indexed: 10/17/2023] Open
Abstract
Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre- and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions carry the potential to disrupt the broader epigenomic and transcriptional landscape far beyond the boundaries of the site-specific variation, highlighting the critical importance of long-range intra- and inter-chromosomal contacts for neuronal and glial function.
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Affiliation(s)
- Amara Plaza-Jennings
- Graduate School of Biomedical Sciences, Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aditi Valada
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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45
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Yan H, Wang R, Ma S, Huang D, Wang S, Ren J, Lu C, Chen X, Lu X, Zheng Z, Zhang W, Qu J, Zhou Y, Liu GH. Lineage Landscape: a comprehensive database that records lineage commitment across species. Nucleic Acids Res 2022; 51:D1061-D1066. [PMID: 36305824 PMCID: PMC9825468 DOI: 10.1093/nar/gkac951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 09/23/2022] [Accepted: 10/11/2022] [Indexed: 01/30/2023] Open
Abstract
Commitment to specific cell lineages is critical for mammalian embryonic development. Lineage determination, differentiation, maintenance, and organogenesis result in diverse life forms composed of multiple cell types. To understand the formation and maintenance of living individuals, including human beings, a comprehensive database that integrates multi-omic information underlying lineage differentiation across multiple species is urgently needed. Here, we construct Lineage Landscape, a database that compiles, analyzes and visualizes transcriptomic and epigenomic information related to lineage development in a collection of species. This landscape draws together datasets that capture the ongoing changes in cell lineages from classic model organisms to human beings throughout embryonic, fetal, adult, and aged stages, providing comprehensive, open-access information that is useful to researchers of a broad spectrum of life science disciplines. Lineage Landscape contains single-cell gene expression and bulk transcriptomic, DNA methylation, histone modifications, and chromatin accessibility profiles. Using this database, users can explore genes of interest that exhibit dynamic expression patterns at the transcriptional or epigenetic levels at different stages of lineage development. Lineage Landscape currently includes over 6.6 million cells, 15 million differentially expressed genes and 36 million data entries across 10 species and 34 organs. Lineage Landscape is free to access, browse, search, and download at http://data.iscr.ac.cn/lineage/#/home.
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Affiliation(s)
| | | | | | | | | | | | - Changfa Lu
- Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Xin Chen
- Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoyong Lu
- University of Chinese Academy of Sciences, Beijing 100049, China,China National Center for Bioinformation, Beijing 100101, China,CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zikai Zheng
- University of Chinese Academy of Sciences, Beijing 100049, China,China National Center for Bioinformation, Beijing 100101, China,CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Weiqi Zhang
- Correspondence may also be addressed to Weiqi Zhang. Tel: +86 10 8409 7838;
| | - Jing Qu
- Correspondence may also be addressed to Jing Qu. Tel: +86 10 6480 7768;
| | - Yuanchun Zhou
- Correspondence may also be addressed to Yuanchun Zhou. Tel: +86 10 5881 2561;
| | - Guang-Hui Liu
- To whom correspondence should be addressed. Tel: +86 10 6480 7583;
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46
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Hu L, Long J, Lin Y, Gu Z, Su H, Dong X, Lin Z, Xiao Q, Batbayar N, Bold B, Deutschová L, Ganusevich S, Sokolov V, Sokolov A, Patel HR, Waters PD, Graves JAM, Dixon A, Pan S, Zhan X. Arctic introgression and chromatin regulation facilitated rapid Qinghai-Tibet Plateau colonization by an avian predator. Nat Commun 2022; 13:6413. [PMID: 36302769 PMCID: PMC9613686 DOI: 10.1038/s41467-022-34138-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 10/14/2022] [Indexed: 12/25/2022] Open
Abstract
The Qinghai-Tibet Plateau (QTP), possesses a climate as cold as that of the Arctic, and also presents uniquely low oxygen concentrations and intense ultraviolet (UV) radiation. QTP animals have adapted to these extreme conditions, but whether they obtained genetic variations from the Arctic during cold adaptation, and how genomic mutations in non-coding regions regulate gene expression under hypoxia and intense UV environment, remain largely unknown. Here, we assemble a high-quality saker falcon genome and resequence populations across Eurasia. We identify female-biased hybridization with Arctic gyrfalcons in the last glacial maximum, that endowed eastern sakers with alleles conveying larger body size and changes in fat metabolism, predisposing their QTP cold adaptation. We discover that QTP hypoxia and UV adaptations mainly involve independent changes in non-coding genomic variants. Our study highlights key roles of gene flow from Arctic relatives during QTP hypothermia adaptation, and cis-regulatory elements during hypoxic response and UV protection.
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Affiliation(s)
- Li Hu
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China
| | - Juan Long
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China
| | - Yi Lin
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China
| | - Zhongru Gu
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China
| | - Han Su
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China
| | - Xuemin Dong
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China
| | - Zhenzhen Lin
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China
| | - Qian Xiao
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China ,grid.20513.350000 0004 1789 9964Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, 100875 Beijing, China
| | - Nyambayar Batbayar
- Wildlife Science and Conservation Center, Union Building B-802, Ulaanbaatar, 14210 Mongolia
| | - Batbayar Bold
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China ,Wildlife Science and Conservation Center, Union Building B-802, Ulaanbaatar, 14210 Mongolia
| | - Lucia Deutschová
- grid.455051.0Raptor Protection of Slovakia, Trhová 54, SK-841 01, Bratislava, Slovakia
| | - Sergey Ganusevich
- Wild Animal Rescue Centre, Krasnostudencheskiy pr., 21-45, Moscow, 125422 Russia
| | - Vasiliy Sokolov
- grid.426536.00000 0004 1760 306XInstitute of Plant and Animal Ecology, Ural Division Russian Academy of Sciences, 202-8 Marta Street, Ekaterinburg, 620144 Russia
| | - Aleksandr Sokolov
- Arctic Research Station of the Institute of Plant and Animal Ecology, Ural Division Russian Academy of Sciences, 21 Zelenaya Gorka, Labytnangi, Yamalo-Nenetski District 629400 Russia
| | - Hardip R. Patel
- grid.1001.00000 0001 2180 7477The John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601 Australia
| | - Paul D. Waters
- grid.1005.40000 0004 4902 0432School of Biotechnology and Biomolecular Science, Faculty of Science, UNSW Sydney, Sydney, NSW 2052 Australia
| | | | - Andrew Dixon
- Emirates Falconers’ Club, Al Mamoura Building (A), P.O. Box 47716, Muroor Road, Abu Dhabi, UAE ,grid.511767.30000 0004 5895 0922International Wildlife Consultants, P.O. Box 19, Carmarthen, SA33 5YL UK
| | - Shengkai Pan
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China
| | - Xiangjiang Zhan
- grid.9227.e0000000119573309Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China ,grid.9227.e0000000119573309Cardiff University - Institute of Zoology Joint Laboratory for Biocomplexity Research, Chinese Academy of Sciences, 100101 Beijing, China ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, 100049 Beijing, China ,grid.9227.e0000000119573309Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223 China
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47
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Fujita Y, Pather SR, Ming GL, Song H. 3D spatial genome organization in the nervous system: From development and plasticity to disease. Neuron 2022; 110:2902-2915. [PMID: 35777365 PMCID: PMC9509413 DOI: 10.1016/j.neuron.2022.06.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 03/15/2022] [Accepted: 06/03/2022] [Indexed: 01/03/2023]
Abstract
Chromatin is organized into multiscale three-dimensional structures, including chromosome territories, A/B compartments, topologically associating domains, and chromatin loops. This hierarchically organized genomic architecture regulates gene transcription, which, in turn, is essential for various biological processes during brain development and adult plasticity. Here, we review different aspects of spatial genome organization and their functions in regulating gene expression in the nervous system, as well as their dysregulation in brain disorders. We also highlight new technologies to probe and manipulate chromatin architecture and discuss how investigating spatial genome organization can lead to a better understanding of the nervous system and associated disorders.
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Affiliation(s)
- Yuki Fujita
- Department of Neuroscience, Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Developmental Biology, Faculty of Medicine, Shimane University, Izumo City, Shimane 693-8501, Japan.
| | - Sarshan R Pather
- Department of Neuroscience, Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Cell and Molecular Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Guo-Li Ming
- Department of Neuroscience, Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hongjun Song
- Department of Neuroscience, Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; The Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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48
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Wu Z, Wang L, Fan L, Tang H, Zuo X, Gu D, Lu X, Li Y, Wu J, Qin S, Xia Y, Zhu H, Wang L, Xu W, Li J, Jin H. Exploring the significance of PAK1 through chromosome conformation signatures in ibrutinib-resistant chronic lymphocytic leukaemia. Mol Oncol 2022; 16:2920-2935. [PMID: 35811334 PMCID: PMC9394240 DOI: 10.1002/1878-0261.13281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 06/06/2022] [Accepted: 07/07/2022] [Indexed: 11/17/2022] Open
Abstract
Ibrutinib exerts promising anticancer effects in chronic lymphocytic leukaemia (CLL). However, acquired resistance occurs during treatment, necessitating the exploration of underlying mechanisms. Although three‐dimensional genome organization has been identified as a major player in the development and progression of cancer, including drug resistance, little is known regarding its role in CLL. Therefore, we investigated the molecular mechanisms underlying ibrutinib resistance through multi‐omics analysis, including high‐throughput chromosome conformation capture (Hi‐C) technology. We demonstrated that the therapeutic response to ibrutinib is associated with the expression of p21‐activated kinase 1 (PAK1). PAK1, which was up‐regulated in CLL and associated with patients' survival, was involved in cell proliferation, glycolysis and oxidative phosphorylation. Furthermore, the PAK1 inhibitor IPA‐3 exerted an anti‐tumour effect and its combination with ibrutinib exhibited a synergistic effect in ibrutinib‐sensitive and ‐resistant cells. These findings suggest the oncogenic role of PAK1 in CLL progression and drug resistance, highlighting PAK1 as a potential diagnostic marker and therapeutic target in CLL including ibrutinib‐resistant CLL.
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Affiliation(s)
- Zijuan Wu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Luqiao Wang
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Lei Fan
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Hanning Tang
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Xiaoling Zuo
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Danling Gu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Xueying Lu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Yue Li
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Jiazhu Wu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Shuchao Qin
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Yi Xia
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Huayuan Zhu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Li Wang
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Wei Xu
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China
| | - Jianyong Li
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China.,National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hui Jin
- Department of Hematology, Pukou CLL Center, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, China.,Key Laboratory of Hematology of Nanjing Medical University, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, China.,National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Suzhou, China
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49
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Chen L, Li J, Yuan R, Wang Y, Zhang J, Lin Y, Wang L, Zhu X, Zhu W, Bai J, Kong F, Zeng B, Lu L, Ma J, Long K, Jin L, Huang Z, Huo J, Gu Y, Wang D, Mo D, Li D, Tang Q, Li X, Wu J, Chen Y, Li M. Dynamic 3D genome reorganization during development and metabolic stress of the porcine liver. Cell Discov 2022; 8:56. [PMID: 35701393 PMCID: PMC9197842 DOI: 10.1038/s41421-022-00416-z] [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: 12/07/2021] [Accepted: 04/28/2022] [Indexed: 11/28/2022] Open
Abstract
Liver development is a complex process that is regulated by a series of signaling pathways. Three-dimensional (3D) chromatin architecture plays an important role in transcriptional regulation; nonetheless, its dynamics and role in the rapid transition of core liver functions during development and obesity-induced metabolic stress remain largely unexplored. To investigate the dynamic chromatin architecture during liver development and under metabolic stress, we generated high-resolution maps of chromatin architecture for porcine livers across six major developmental stages (from embryonic day 38 to the adult stage) and under a high-fat diet-induced obesity. The characteristically loose chromatin architecture supports a highly plastic genome organization during early liver development, which fundamentally contributes to the rapid functional transitions in the liver after birth. We reveal the multi-scale reorganization of chromatin architecture and its influence on transcriptional regulation of critical signaling processes during liver development, and show its close association with transition in hepatic functions (i.e., from hematopoiesis in the fetus to metabolism and immunity after birth). The limited changes in chromatin structure help explain the observed metabolic adaptation to excessive energy intake in pigs. These results provide a global overview of chromatin architecture dynamics associated with the transition of physiological liver functions between prenatal development and postnatal maturation, and a foundational resource that allows for future in-depth functional characterization.
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Affiliation(s)
- Luxi Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Renqiang Yuan
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yujie Wang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jiaman Zhang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yu Lin
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lina Wang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China.,Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Xingxing Zhu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Wei Zhu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jingyi Bai
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Fanli Kong
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Bo Zeng
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lu Lu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jideng Ma
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Keren Long
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Long Jin
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Zhiqing Huang
- Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jinlong Huo
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yiren Gu
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, Sichuan, China
| | - Danyang Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, China
| | - Delin Mo
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Diyan Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Qianzi Tang
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Xuewei Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Jiangwei Wu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China.
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
| | - Mingzhou Li
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, China.
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50
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Espinós A, Fernández‐Ortuño E, Negri E, Borrell V. Evolution of genetic mechanisms regulating cortical neurogenesis. Dev Neurobiol 2022; 82:428-453. [PMID: 35670518 PMCID: PMC9543202 DOI: 10.1002/dneu.22891] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/26/2022] [Accepted: 05/24/2022] [Indexed: 11/20/2022]
Abstract
The size of the cerebral cortex increases dramatically across amniotes, from reptiles to great apes. This is primarily due to different numbers of neurons and glial cells produced during embryonic development. The evolutionary expansion of cortical neurogenesis was linked to changes in neural stem and progenitor cells, which acquired increased capacity of self‐amplification and neuron production. Evolution works via changes in the genome, and recent studies have identified a small number of new genes that emerged in the recent human and primate lineages, promoting cortical progenitor proliferation and increased neurogenesis. However, most of the mammalian genome corresponds to noncoding DNA that contains gene‐regulatory elements, and recent evidence precisely points at changes in expression levels of conserved genes as key in the evolution of cortical neurogenesis. Here, we provide an overview of basic cellular mechanisms involved in cortical neurogenesis across amniotes, and discuss recent progress on genetic mechanisms that may have changed during evolution, including gene expression regulation, leading to the expansion of the cerebral cortex.
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Affiliation(s)
- Alexandre Espinós
- Instituto de Neurociencias CSIC ‐ UMH, 03550 Sant Joan d'Alacant Spain
| | | | - Enrico Negri
- Instituto de Neurociencias CSIC ‐ UMH, 03550 Sant Joan d'Alacant Spain
| | - Víctor Borrell
- Instituto de Neurociencias CSIC ‐ UMH, 03550 Sant Joan d'Alacant Spain
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