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Berasain L, Beati P, Trigila AP, Rubinstein M, Franchini LF. Accelerated evolution in the human lineage led to gain and loss of transcriptional enhancers in the RBFOX1 locus. SCIENCE ADVANCES 2024; 10:eadl1049. [PMID: 38924416 DOI: 10.1126/sciadv.adl1049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 05/22/2024] [Indexed: 06/28/2024]
Abstract
A long-standing goal of evolutionary biology is to decode how changes in gene regulatory networks contribute to human-specific traits. Human accelerated regions (HARs) are prime candidates for driving gene regulatory modifications in human development. The RBFOX1 locus is densely populated with HARs, providing a set of potential regulatory elements that could have changed its expression in the human lineage. Here, we examined the role of RBFOX1-HARs using transgenic zebrafish reporter assays and identified 15 transcriptional enhancers that are active in the developing nervous system, 9 of which displayed differential activity between the human and chimpanzee sequences. The engineered loss of two selected RBFOX1-HARs in knockout mouse models modified Rbfox1 expression at specific developmental stages and tissues in the brain, influencing the expression and splicing of a high number of Rbfox1 target genes. Our results provided insight into the spatial and temporal changes in gene expression driven by RBFOX1-HARs.
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Affiliation(s)
- Lara Berasain
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI) "Dr. Hector N. Torres", Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428, Argentina
| | - Paula Beati
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI) "Dr. Hector N. Torres", Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428, Argentina
| | - Anabella P Trigila
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI) "Dr. Hector N. Torres", Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428, Argentina
| | - Marcelo Rubinstein
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI) "Dr. Hector N. Torres", Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428, Argentina
- Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina
| | - Lucía F Franchini
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI) "Dr. Hector N. Torres", Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428, Argentina
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2
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Iñiguez-Muñoz S, Llinàs-Arias P, Ensenyat-Mendez M, Bedoya-López AF, Orozco JIJ, Cortés J, Roy A, Forsberg-Nilsson K, DiNome ML, Marzese DM. Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements. Cell Mol Life Sci 2024; 81:274. [PMID: 38902506 DOI: 10.1007/s00018-024-05314-z] [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: 07/06/2023] [Revised: 12/07/2023] [Accepted: 06/06/2024] [Indexed: 06/22/2024]
Abstract
Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.
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Affiliation(s)
- Sandra Iñiguez-Muñoz
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Pere Llinàs-Arias
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Miquel Ensenyat-Mendez
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Andrés F Bedoya-López
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Javier I J Orozco
- Saint John's Cancer Institute, Providence Saint John's Health Center, Santa Monica, CA, USA
| | - Javier Cortés
- International Breast Cancer Center (IBCC), Pangaea Oncology, Quiron Group, 08017, Barcelona, Spain
- Medica Scientia Innovation Research SL (MEDSIR), 08018, Barcelona, Spain
- Faculty of Biomedical and Health Sciences, Department of Medicine, Universidad Europea de Madrid, 28670, Madrid, Spain
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- University of Nottingham Biodiscovery Institute, Nottingham, UK
| | - Maggie L DiNome
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Diego M Marzese
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain.
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA.
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3
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Mesaki K, Yamamoto H, Juvet S, Yeung J, Guan Z, Akhter A, Yao Y, Dickie C, Mangat H, Wang A, Wilson GW, Mariscal A, Hu J, Davidson AR, Kleinstiver BP, Cypel M, Liu M, Keshavjee S. CRISPR-Cas Genome Editing in Ex Vivo Human Lungs to Rewire the Translational Path of Genome-Targeting Therapeutics. Hum Gene Ther 2024; 35:374-387. [PMID: 38717950 DOI: 10.1089/hum.2023.223] [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: 05/24/2024] Open
Abstract
The ongoing advancements in CRISPR-Cas technologies can significantly accelerate the preclinical development of both in vivo and ex vivo organ genome-editing therapeutics. One of the promising applications is to genetically modify donor organs prior to implantation. The implantation of optimized donor organs with long-lasting immunomodulatory capacity holds promise for reducing the need for lifelong potent whole-body immunosuppression in recipients. However, assessing genome-targeting interventions in a clinically relevant manner prior to clinical trials remains a major challenge owing to the limited modalities available. This study introduces a novel platform for testing genome editing in human lungs ex vivo, effectively simulating preimplantation genetic engineering of donor organs. We identified gene regulatory elements whose disruption via Cas nucleases led to the upregulation of the immunomodulatory gene interleukin 10 (IL-10). We combined this approach with adenoviral vector-mediated IL-10 delivery to create favorable kinetics for early (immediate postimplantation) graft immunomodulation. Using ex vivo organ machine perfusion and precision-cut tissue slice technology, we demonstrated the feasibility of evaluating CRISPR genome editing in human lungs. To overcome the assessment limitations in ex vivo perfused human organs, we conducted an in vivo rodent study and demonstrated both early gene induction and sustained editing of the lung. Collectively, our findings lay the groundwork for a first-in-human-organ study to overcome the current translational barriers of genome-targeting therapeutics.
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Affiliation(s)
- Kumi Mesaki
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Haruchika Yamamoto
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Stephen Juvet
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Division of Respirology, Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Jonathan Yeung
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Division of Thoracic Surgery, Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Zehong Guan
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Akhi Akhter
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Yan Yao
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Cameron Dickie
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Henna Mangat
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Aizhou Wang
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Gavin W Wilson
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Andrea Mariscal
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
| | - Jim Hu
- Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Translation Medicine Program, the Hospital for Sick Children, Toronto, Canada
| | - Alan R Davidson
- Department of Biochemistry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Molecular Genetics, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Benjamin P Kleinstiver
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
| | - Marcelo Cypel
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Mingyao Liu
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Division of Thoracic Surgery, Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Shaf Keshavjee
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Division of Thoracic Surgery, Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
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4
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Yao D, Tycko J, Oh JW, Bounds LR, Gosai SJ, Lataniotis L, Mackay-Smith A, Doughty BR, Gabdank I, Schmidt H, Guerrero-Altamirano T, Siklenka K, Guo K, White AD, Youngworth I, Andreeva K, Ren X, Barrera A, Luo Y, Yardımcı GG, Tewhey R, Kundaje A, Greenleaf WJ, Sabeti PC, Leslie C, Pritykin Y, Moore JE, Beer MA, Gersbach CA, Reddy TE, Shen Y, Engreitz JM, Bassik MC, Reilly SK. Multicenter integrated analysis of noncoding CRISPRi screens. Nat Methods 2024; 21:723-734. [PMID: 38504114 PMCID: PMC11009116 DOI: 10.1038/s41592-024-02216-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/18/2024] [Indexed: 03/21/2024]
Abstract
The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.
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Affiliation(s)
- David Yao
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
| | - Jin Woo Oh
- Departments of Biomedical Engineering and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Lexi R Bounds
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Sager J Gosai
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Center for System Biology, Harvard University, Cambridge, MA, USA
- Harvard Graduate Program in Biological and Biomedical Science, Boston, MA, USA
| | - Lazaros Lataniotis
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
| | - Ava Mackay-Smith
- University Program in Genetics and Genomics, Duke University School of Medicine, Durham, NC, USA
| | | | - Idan Gabdank
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Henri Schmidt
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tania Guerrero-Altamirano
- University Program in Genetics and Genomics, Duke University School of Medicine, Durham, NC, USA
- Department of Biology, Duke University, Durham, NC, USA
| | - Keith Siklenka
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Katherine Guo
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Alexander D White
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | | | - Kalina Andreeva
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Xingjie Ren
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
| | - Alejandro Barrera
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Yunhai Luo
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | | | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Pardis C Sabeti
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Center for System Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christina Leslie
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yuri Pritykin
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Michael A Beer
- Departments of Biomedical Engineering and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Charles A Gersbach
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Timothy E Reddy
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Yin Shen
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jesse M Engreitz
- Department of Genetics, Stanford University, Stanford, CA, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, CA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steven K Reilly
- Department of Genetics, Yale University, New Haven, CT, USA.
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5
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Delihas N. Evolution of a Human-Specific De Novo Open Reading Frame and Its Linked Transcriptional Silencer. Int J Mol Sci 2024; 25:3924. [PMID: 38612733 PMCID: PMC11011693 DOI: 10.3390/ijms25073924] [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: 02/27/2024] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
In the human genome, two short open reading frames (ORFs) separated by a transcriptional silencer and a small intervening sequence stem from the gene SMIM45. The two ORFs show different translational characteristics, and they also show divergent patterns of evolutionary development. The studies presented here describe the evolution of the components of SMIM45. One ORF consists of an ultra-conserved 68 amino acid (aa) sequence, whose origins can be traced beyond the evolutionary age of divergence of the elephant shark, ~462 MYA. The silencer also has ancient origins, but it has a complex and divergent pattern of evolutionary formation, as it overlaps both at the 68 aa ORF and the intervening sequence. The other ORF consists of 107 aa. It develops during primate evolution but is found to originate de novo from an ancestral non-coding genomic region with root origins within the Afrothere clade of placental mammals, whose evolutionary age of divergence is ~99 MYA. The formation of the complete 107 aa ORF during primate evolution is outlined, whereby sequence development is found to occur through biased mutations, with disruptive random mutations that also occur but lead to a dead-end. The 107 aa ORF is of particular significance, as there is evidence to suggest it is a protein that may function in human brain development. Its evolutionary formation presents a view of a human-specific ORF and its linked silencer that were predetermined in non-primate ancestral species. The genomic position of the silencer offers interesting possibilities for the regulation of transcription of the 107 aa ORF. A hypothesis is presented with respect to possible spatiotemporal expression of the 107 aa ORF in embryonic tissues.
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Affiliation(s)
- Nicholas Delihas
- Department of Microbiology and Immunology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA
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6
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Toneyan S, Koo PK. Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.03.547592. [PMID: 37461616 PMCID: PMC10349992 DOI: 10.1101/2023.07.03.547592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with experimental perturbation assays, which provides insights into the generalization capabilities within the studied loci but offers a limited perspective of what drives their predictions. Moreover, existing model explainability tools focus mainly on motif analysis, which becomes complex when interpreting longer sequences. Here we introduce CREME, an in silico perturbation toolkit that interrogates large-scale DNNs to uncover rules of gene regulation that it learns. Using CREME, we investigate Enformer, a prominent DNN in gene expression prediction, revealing cis-regulatory elements (CREs) that directly enhance or silence target genes. We explore the intricate complexity of higher-order CRE interactions, the relationship between CRE distance from transcription start sites on gene expression, as well as the biochemical features of enhancers and silencers learned by Enformer. Moreover, we demonstrate the flexibility of CREME to efficiently uncover a higher-resolution view of functional sequence elements within CREs. This work demonstrates how CREME can be employed to translate the powerful predictions of large-scale DNNs to study open questions in gene regulation.
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7
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Chen XF, Duan YY, Jia YY, Dong QH, Shi W, Zhang Y, Dong SS, Li M, Liu Z, Chen F, Huang XT, Hao RH, Zhu DL, Jing RH, Guo Y, Yang TL. Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis. CELL GENOMICS 2024; 4:100501. [PMID: 38335956 PMCID: PMC10943593 DOI: 10.1016/j.xgen.2024.100501] [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: 05/16/2023] [Revised: 08/23/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.
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Affiliation(s)
- Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ying-Ying Jia
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Qian-Hua Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yan Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China
| | - Zhongbo Liu
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Fei Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Xiao-Ting Huang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ruo-Han Hao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Rui-Hua Jing
- Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710000, Shaanxi, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China; Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China.
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8
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Ando K, Ou J, Thompson JD, Welsby J, Bangru S, Shen J, Wei X, Diao Y, Poss KD. A screen for regeneration-associated silencer regulatory elements in zebrafish. Dev Cell 2024; 59:676-691.e5. [PMID: 38290519 PMCID: PMC10939760 DOI: 10.1016/j.devcel.2024.01.004] [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: 06/24/2023] [Revised: 11/03/2023] [Accepted: 01/08/2024] [Indexed: 02/01/2024]
Abstract
Regeneration involves gene expression changes explained in part by context-dependent recruitment of transcriptional activators to distal enhancers. Silencers that engage repressive transcriptional complexes are less studied than enhancers and more technically challenging to validate, but they potentially have profound biological importance for regeneration. Here, we identified candidate silencers through a screening process that examined the ability of DNA sequences to limit injury-induced gene expression in larval zebrafish after fin amputation. A short sequence (s1) on chromosome 5 near several genes that reduce expression during adult fin regeneration could suppress promoter activity in stable transgenic lines and diminish nearby gene expression in knockin lines. High-resolution analysis of chromatin organization identified physical associations of s1 with gene promoters occurring preferentially during fin regeneration, and genomic deletion of s1 elevated the expression of these genes after fin amputation. Our study provides methods to identify "tissue regeneration silencer elements" (TRSEs) with the potential to reduce unnecessary or deleterious gene expression during regeneration.
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Affiliation(s)
- Kazunori Ando
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Jianhong Ou
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - John D Thompson
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - John Welsby
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Sushant Bangru
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Jingwen Shen
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Xiaolin Wei
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Yarui Diao
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Kenneth D Poss
- Duke Regeneration Center and Department of Cell Biology, Duke University School of Medicine, Durham, NC 27710, USA.
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9
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Lim B, Domsch K, Mall M, Lohmann I. Canalizing cell fate by transcriptional repression. Mol Syst Biol 2024; 20:144-161. [PMID: 38302581 PMCID: PMC10912439 DOI: 10.1038/s44320-024-00014-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/28/2023] [Accepted: 12/15/2023] [Indexed: 02/03/2024] Open
Abstract
Precision in the establishment and maintenance of cellular identities is crucial for the development of multicellular organisms and requires tight regulation of gene expression. While extensive research has focused on understanding cell type-specific gene activation, the complex mechanisms underlying the transcriptional repression of alternative fates are not fully understood. Here, we provide an overview of the repressive mechanisms involved in cell fate regulation. We discuss the molecular machinery responsible for suppressing alternative fates and highlight the crucial role of sequence-specific transcription factors (TFs) in this process. Depletion of these TFs can result in unwanted gene expression and increased cellular plasticity. We suggest that these TFs recruit cell type-specific repressive complexes to their cis-regulatory elements, enabling them to modulate chromatin accessibility in a context-dependent manner. This modulation effectively suppresses master regulators of alternative fate programs and their downstream targets. The modularity and dynamic behavior of these repressive complexes enables a limited number of repressors to canalize and maintain major and minor cell fate decisions at different stages of development.
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Affiliation(s)
- Bryce Lim
- Cell Fate Engineering and Disease Modeling Group, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, 69120, Heidelberg, Germany
- HITBR Hector Institute for Translational Brain Research gGmbH, 69120, Heidelberg, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159, Mannheim, Germany
| | - Katrin Domsch
- Heidelberg University, Centre for Organismal Studies (COS) Heidelberg, Department of Developmental Biology and Cell Networks - Cluster of Excellence, Heidelberg, Germany
| | - Moritz Mall
- Cell Fate Engineering and Disease Modeling Group, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, 69120, Heidelberg, Germany.
- HITBR Hector Institute for Translational Brain Research gGmbH, 69120, Heidelberg, Germany.
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159, Mannheim, Germany.
| | - Ingrid Lohmann
- Heidelberg University, Centre for Organismal Studies (COS) Heidelberg, Department of Developmental Biology and Cell Networks - Cluster of Excellence, Heidelberg, Germany.
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10
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Farrow SL, Gokuladhas S, Schierding W, Pudjihartono M, Perry JK, Cooper AA, O'Sullivan JM. Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay. NPJ Parkinsons Dis 2024; 10:44. [PMID: 38413607 PMCID: PMC10899198 DOI: 10.1038/s41531-024-00659-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/12/2024] [Indexed: 02/29/2024] Open
Abstract
Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.
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Affiliation(s)
- Sophie L Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.
| | | | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
- Department of Ophthalmology, The University of Auckland, Auckland, New Zealand
| | | | - Jo K Perry
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Antony A Cooper
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia.
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore, Singapore.
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom.
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11
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Qiu K, Vu D, Wang L, Bookstaver A, Dinh TN, Goldfarb AN, Tenen DG, Trinh BQ. Chromatin structure and 3D architecture define differential functions of PU.1 cis regulatory elements in human blood cell lineages. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.01.573782. [PMID: 38260486 PMCID: PMC10802337 DOI: 10.1101/2024.01.01.573782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The precise spatio-temporal expression of the hematopoietic ETS transcription factor PU.1 that determines the hematopoietic cell fates is tightly regulated at the chromatin level. However, it remains elusive as to how chromatin signatures are linked to this dynamic expression pattern of PU.1 across blood cell lineages. Here we performed an unbiased and in-depth analysis of the relationship between human PU.1 expression, the presence of trans-acting factors, and 3D architecture at various cis-regulatory elements (CRE) proximal to the PU.1 locus. We identified multiple novel CREs at the upstream region of the gene following an integrative inspection for conserved DNA elements at the chromatin-accessible regions in primary human blood lineages. We showed that a subset of CREs localize within a 10 kb-wide cluster that exhibits that exhibit molecular features of a myeloid-specific super-enhancer involved in mediating PU.1 autoregulation, including open chromatin, unmethylated DNA, histone enhancer marks, transcription of enhancer RNAs, and occupancy of the PU.1 protein itself. Importantly, we revealed the presence of common 35-kb-wide CTCF-bound insulated neighborhood that contains the CRE cluster, forming the chromatin territory for lineage-specific and CRE-mediated chromatin interactions. These include functional CRE-promoter interactions in myeloid and B cells but not in erythroid and T cells. Our findings also provide mechanistic insights into the interplay between dynamic chromatin structure and 3D architecture in defining certain CREs as enhancers or silencers in chromatin regulation of PU.1 expression. The study lays the groundwork for further examination of PU.1 CREs as well as epigenetic regulation in malignant hematopoiesis.
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12
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Zu S, Li YE, Wang K, Armand EJ, Mamde S, Amaral ML, Wang Y, Chu A, Xie Y, Miller M, Xu J, Wang Z, Zhang K, Jia B, Hou X, Lin L, Yang Q, Lee S, Li B, Kuan S, Liu H, Zhou J, Pinto-Duarte A, Lucero J, Osteen J, Nunn M, Smith KA, Tasic B, Yao Z, Zeng H, Wang Z, Shang J, Behrens MM, Ecker JR, Wang A, Preissl S, Ren B. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature 2023; 624:378-389. [PMID: 38092917 PMCID: PMC10719105 DOI: 10.1038/s41586-023-06824-9] [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: 03/31/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.
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Affiliation(s)
- Songpeng Zu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Department of Neurosurgery and Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Kangli Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Maria Luisa Amaral
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yuelai Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Andre Chu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Jie Xu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Kai Zhang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bojing Jia
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Qian Yang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bin Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Samantha Kuan
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Jacinta Lucero
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia Osteen
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michael Nunn
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Zihan Wang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jingbo Shang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | | | - Joseph R Ecker
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA.
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13
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Edrei Y, Levy R, Kaye D, Marom A, Radlwimmer B, Hellman A. Methylation-directed regulatory networks determine enhancing and silencing of mutation disease driver genes and explain inter-patient expression variation. Genome Biol 2023; 24:264. [PMID: 38012713 PMCID: PMC10683314 DOI: 10.1186/s13059-023-03094-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 10/23/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Common diseases manifest differentially between patients, but the genetic origin of this variation remains unclear. To explore possible involvement of gene transcriptional-variation, we produce a DNA methylation-oriented, driver-gene-wide dataset of regulatory elements in human glioblastomas and study their effect on inter-patient gene expression variation. RESULTS In 175 of 177 analyzed gene regulatory domains, transcriptional enhancers and silencers are intermixed. Under experimental conditions, DNA methylation induces enhancers to alter their enhancing effects or convert into silencers, while silencers are affected inversely. High-resolution mapping of the association between DNA methylation and gene expression in intact genomes reveals methylation-related regulatory units (average size = 915.1 base-pairs). Upon increased methylation of these units, their target-genes either increased or decreased in expression. Gene-enhancing and silencing units constitute cis-regulatory networks of genes. Mathematical modeling of the networks highlights indicative methylation sites, which signified the effect of key regulatory units, and add up to make the overall transcriptional effect of the network. Methylation variation in these sites effectively describe inter-patient expression variation and, compared with DNA sequence-alterations, appears as a major contributor of gene-expression variation among glioblastoma patients. CONCLUSIONS We describe complex cis-regulatory networks, which determine gene expression by summing the effects of positive and negative transcriptional inputs. In these networks, DNA methylation induces both enhancing and silencing effects, depending on the context. The revealed mechanism sheds light on the regulatory role of DNA methylation, explains inter-individual gene-expression variation, and opens the way for monitoring the driving forces behind deferential courses of cancer and other diseases.
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Affiliation(s)
- Yifat Edrei
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, 9112102, Jerusalem, Israel
| | - Revital Levy
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, 9112102, Jerusalem, Israel
| | - Daniel Kaye
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, 9112102, Jerusalem, Israel
| | - Anat Marom
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, 9112102, Jerusalem, Israel
| | - Bernhard Radlwimmer
- Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Asaf Hellman
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, 9112102, Jerusalem, Israel.
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14
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Pan JH, Du PF. SilenceREIN: seeking silencers on anchors of chromatin loops by deep graph neural networks. Brief Bioinform 2023; 25:bbad494. [PMID: 38168841 PMCID: PMC10782921 DOI: 10.1093/bib/bbad494] [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: 07/30/2023] [Revised: 11/09/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024] Open
Abstract
Silencers are repressive cis-regulatory elements that play crucial roles in transcriptional regulation. Experimental methods for identifying silencers are always costly and time-consuming. Computational methods, which relies on genomic sequence features, have been introduced as alternative approaches. However, silencers do not have significant epigenomic signature. Therefore, we explore a new way to computationally identify silencers, by incorporating chromatin structural information. We propose the SilenceREIN method, which focuses on finding silencers on anchors of chromatin loops. By using graph neural networks, we extracted chromatin structural information from a regulatory element interaction network. SilenceREIN integrated the chromatin structural information with linear genomic signatures to find silencers. The predictive performance of SilenceREIN is comparable or better than other states-of-the-art methods. We performed a genome-wide scanning to systematically find silencers in human genome. Results suggest that silencers are widespread on anchors of chromatin loops. In addition, enrichment analysis of transcription factor binding motif support our prediction results. As far as we can tell, this is the first attempt to incorporate chromatin structural information in finding silencers. All datasets and source codes of SilenceREIN have been deposited in a GitHub repository (https://github.com/JianHPan/SilenceREIN).
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Affiliation(s)
- Jian-Hua Pan
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
| | - Pu-Feng Du
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
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15
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Rummel CK, Gagliardi M, Ahmad R, Herholt A, Jimenez-Barron L, Murek V, Weigert L, Hausruckinger A, Maidl S, Hauger B, Raabe FJ, Fürle C, Trastulla L, Turecki G, Eder M, Rossner MJ, Ziller MJ. Massively parallel functional dissection of schizophrenia-associated noncoding genetic variants. Cell 2023; 186:5165-5182.e33. [PMID: 37852259 DOI: 10.1016/j.cell.2023.09.015] [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: 06/18/2021] [Revised: 06/12/2023] [Accepted: 09/14/2023] [Indexed: 10/20/2023]
Abstract
Schizophrenia (SCZ) is a highly heritable mental disorder with thousands of associated genetic variants located mostly in the noncoding space of the genome. Translating these associations into insights regarding the underlying pathomechanisms has been challenging because the causal variants, their mechanisms of action, and their target genes remain largely unknown. We implemented a massively parallel variant annotation pipeline (MVAP) to perform SCZ variant-to-function mapping at scale in disease-relevant neural cell types. This approach identified 620 functional variants (1.7%) that operate in a highly developmental context and neuronal-activity-dependent manner. Multimodal integration of epigenomic and CRISPRi screening data enabled us to link these functional variants to target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a multistage prioritization strategy to map functional single-nucleotide polymorphism (SNP)-to-gene-to-endophenotype relations and offer biological insights into the context-dependent molecular processes modulated by SCZ-associated genetic variation.
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Affiliation(s)
- Christine K Rummel
- Max Planck Institute of Psychiatry, Munich 80804, Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich 80804, Germany
| | - Miriam Gagliardi
- Department of Psychiatry, University of Münster, Münster 48149, Germany
| | - Ruhel Ahmad
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Alexander Herholt
- Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU, Munich 80336, Germany; Systasy Bioscience GmbH, Munich 81669, Germany
| | - Laura Jimenez-Barron
- Max Planck Institute of Psychiatry, Munich 80804, Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich 80804, Germany
| | - Vanessa Murek
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Liesa Weigert
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | | | - Susanne Maidl
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Barbara Hauger
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Florian J Raabe
- Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU, Munich 80336, Germany
| | | | - Lucia Trastulla
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich 80804, Germany; Department of Psychiatry, University of Münster, Münster 48149, Germany; Technische Universität München Medical Graduate Center Experimental Medicine, Munich 80333, Germany
| | - Gustavo Turecki
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Matthias Eder
- Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Moritz J Rossner
- Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU, Munich 80336, Germany; Systasy Bioscience GmbH, Munich 81669, Germany
| | - Michael J Ziller
- Max Planck Institute of Psychiatry, Munich 80804, Germany; Department of Psychiatry, University of Münster, Münster 48149, Germany; Center for Soft Nanoscience, University of Münster, Münster 48149, Germany.
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16
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Milevskiy MJ, Coughlan HD, Kane SR, Johanson TM, Kordafshari S, Chan WF, Tsai M, Surgenor E, Wilcox S, Allan RS, Chen Y, Lindeman GJ, Smyth GK, Visvader JE. Three-dimensional genome architecture coordinates key regulators of lineage specification in mammary epithelial cells. CELL GENOMICS 2023; 3:100424. [PMID: 38020976 PMCID: PMC10667557 DOI: 10.1016/j.xgen.2023.100424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/20/2023] [Accepted: 09/20/2023] [Indexed: 12/01/2023]
Abstract
Although lineage-specific genes have been identified in the mammary gland, little is known about the contribution of the 3D genome organization to gene regulation in the epithelium. Here, we describe the chromatin landscape of the three major epithelial subsets through integration of long- and short-range chromatin interactions, accessibility, histone modifications, and gene expression. While basal genes display exquisite lineage specificity via distal enhancers, luminal-specific genes show widespread promoter priming in basal cells. Cell specificity in luminal progenitors is largely mediated through extensive chromatin interactions with super-enhancers in gene-body regions in addition to interactions with polycomb silencer elements. Moreover, lineage-specific transcription factors appear to be controlled through cell-specific chromatin interactivity. Finally, chromatin accessibility rather than interactivity emerged as a defining feature of the activation of quiescent basal stem cells. This work provides a comprehensive resource for understanding the role of higher-order chromatin interactions in cell-fate specification and differentiation in the adult mouse mammary gland.
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Affiliation(s)
- Michael J.G. Milevskiy
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Hannah D. Coughlan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Serena R. Kane
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Timothy M. Johanson
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Somayeh Kordafshari
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Wing Fuk Chan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Minhsuang Tsai
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Elliot Surgenor
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Stephen Wilcox
- Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Rhys S. Allan
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Yunshun Chen
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Geoffrey J. Lindeman
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC 3010, Australia
- Parkville Familial Cancer Centre and Department of Medical Oncology, The Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Parkville, VIC 3050, Australia
| | - Gordon K. Smyth
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Jane E. Visvader
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC 3010, Australia
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17
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Heuts BMH, Martens JHA. Understanding blood development and leukemia using sequencing-based technologies and human cell systems. Front Mol Biosci 2023; 10:1266697. [PMID: 37886034 PMCID: PMC10598665 DOI: 10.3389/fmolb.2023.1266697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/06/2023] [Indexed: 10/28/2023] Open
Abstract
Our current understanding of human hematopoiesis has undergone significant transformation throughout the years, challenging conventional views. The evolution of high-throughput technologies has enabled the accumulation of diverse data types, offering new avenues for investigating key regulatory processes in blood cell production and disease. In this review, we will explore the opportunities presented by these advancements for unraveling the molecular mechanisms underlying normal and abnormal hematopoiesis. Specifically, we will focus on the importance of enhancer-associated regulatory networks and highlight the crucial role of enhancer-derived transcription regulation. Additionally, we will discuss the unprecedented power of single-cell methods and the progression in using in vitro human blood differentiation system, in particular induced pluripotent stem cell models, in dissecting hematopoietic processes. Furthermore, we will explore the potential of ever more nuanced patient profiling to allow precision medicine approaches. Ultimately, we advocate for a multiparameter, regulatory network-based approach for providing a more holistic understanding of normal hematopoiesis and blood disorders.
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Affiliation(s)
- Branco M H Heuts
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, Netherlands
| | - Joost H A Martens
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, Netherlands
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18
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Allou L, Mundlos S. Disruption of regulatory domains and novel transcripts as disease-causing mechanisms. Bioessays 2023; 45:e2300010. [PMID: 37381881 DOI: 10.1002/bies.202300010] [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: 01/16/2023] [Revised: 05/24/2023] [Accepted: 06/06/2023] [Indexed: 06/30/2023]
Abstract
Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.
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Affiliation(s)
- Lila Allou
- RG Development & Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Mundlos
- RG Development & Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
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19
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Cui Y, Cao Q, Li Y, He M, Liu X. Advances in cis-element- and natural variation-mediated transcriptional regulation and applications in gene editing of major crops. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:5441-5457. [PMID: 37402253 DOI: 10.1093/jxb/erad248] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/28/2023] [Indexed: 07/06/2023]
Abstract
Transcriptional regulation is crucial to control of gene expression. Both spatio-temporal expression patterns and expression levels of genes are determined by the interaction between cis-acting elements and trans-acting factors. Numerous studies have focused on the trans-acting factors that mediate transcriptional regulatory networks. However, cis-acting elements, such as enhancers, silencers, transposons, and natural variations in the genome, are also vital for gene expression regulation and could be utilized by clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated gene editing to improve crop quality and yield. In this review, we discuss current understanding of cis-element-mediated transcriptional regulation in major crops, including rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays), as well as the latest advancements in gene editing techniques and their applications in crops to highlight prospective strategies for crop breeding.
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Affiliation(s)
- Yue Cui
- College of Teacher Education, Molecular and Cellular Postdoctoral Research Station, Hebei Normal University, Shijiazhuang 050024, China
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling, Hebei Research Center of the Basic Discipline Cell Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang 050024, China
| | - Qiao Cao
- Shijiazhuang Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei Province 050041, China
| | - Yongpeng Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling, Hebei Research Center of the Basic Discipline Cell Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang 050024, China
| | - Mingqi He
- Shijiazhuang Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei Province 050041, China
| | - Xigang Liu
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling, Hebei Research Center of the Basic Discipline Cell Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang 050024, China
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20
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Fazel-Najafabadi M, Looger LL, Reddy-Rallabandi H, Nath SK. A multilayered post-GWAS analysis pipeline defines functional variants and target genes for systemic lupus erythematosus (SLE). MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.07.23288295. [PMID: 37066327 PMCID: PMC10104240 DOI: 10.1101/2023.04.07.23288295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Objectives Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWAS) have revealed multiple SLE susceptibility loci and associated single nucleotide polymorphisms (SNPs), the precise causal variants, target genes, cell types, tissues, and mechanisms of action remain largely unknown. Methods Here, we report a comprehensive post-GWAS analysis using extensive bioinformatics, molecular modeling, and integrative functional genomic and epigenomic analyses to optimize fine-mapping. We compile and cross-reference immune cell-specific expression quantitative trait loci ( cis - and trans -eQTLs) with promoter-capture Hi-C, allele-specific chromatin accessibility, and massively parallel reporter assay data to define predisposing variants and target genes. We experimentally validate a predicted locus using CRISPR/Cas9 genome editing, qPCR, and Western blot. Results Anchoring on 452 index SNPs, we selected 9,931 high-linkage disequilibrium (r 2 >0.8) SNPs and defined 182 independent non-HLA SLE loci. 3,746 SNPs from 143 loci were identified as regulating 564 unique genes. Target genes are enriched in lupus-related tissues and associated with other autoimmune diseases. Of these, 329 SNPs (106 loci) showed significant allele-specific chromatin accessibility and/or enhancer activity, indicating regulatory potential. Using CRISPR/Cas9, we validated rs57668933 as a functional variant regulating multiple targets, including SLE risk gene ELF1 , in B-cells. Conclusion We demonstrate and validate post-GWAS strategies for utilizing multi-dimensional data to prioritize likely causal variants with cognate gene targets underlying SLE pathogenesis. Our results provide a catalog of significantly SLE-associated SNPs and loci, target genes, and likely biochemical mechanisms, to guide experimental characterization.
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21
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Gonçalves TM, Stewart CL, Baxley SD, Xu J, Li D, Gabel HW, Wang T, Avraham O, Zhao G. Towards a comprehensive regulatory map of Mammalian Genomes. RESEARCH SQUARE 2023:rs.3.rs-3294408. [PMID: 37841836 PMCID: PMC10571623 DOI: 10.21203/rs.3.rs-3294408/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Genome mapping studies have generated a nearly complete collection of genes for the human genome, but we still lack an equivalently vetted inventory of human regulatory sequences. Cis-regulatory modules (CRMs) play important roles in controlling when, where, and how much a gene is expressed. We developed a training data-free CRM-prediction algorithm, the Mammalian Regulatory MOdule Detector (MrMOD) for accurate CRM prediction in mammalian genomes. MrMOD provides genome position-fixed CRM models similar to the fixed gene models for the mouse and human genomes using only genomic sequences as the inputs with one adjustable parameter - the significance p-value. Importantly, MrMOD predicts a comprehensive set of high-resolution CRMs in the mouse and human genomes including all types of regulatory modules not limited to any tissue, cell type, developmental stage, or condition. We computationally validated MrMOD predictions used a compendium of 21 orthogonal experimental data sets including thousands of experimentally defined CRMs and millions of putative regulatory elements derived from hundreds of different tissues, cell types, and stimulus conditions obtained from multiple databases. In ovo transgenic reporter assay demonstrates the power of our prediction in guiding experimental design. We analyzed CRMs located in the chromosome 17 using unsupervised machine learning and identified groups of CRMs with multiple lines of evidence supporting their functionality, linking CRMs with upstream binding transcription factors and downstream target genes. Our work provides a comprehensive base pair resolution annotation of the functional regulatory elements and non-functional regions in the mammalian genomes.
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Affiliation(s)
| | | | | | - Jason Xu
- Missouri University of Science & Technology
| | - Daofeng Li
- Washington University School of Medicine
| | | | - Ting Wang
- Washington University School of Medicine
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22
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Zhang T, Li L, Sun H, Xu D, Wang G. DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome. Brief Bioinform 2023; 24:bbad316. [PMID: 37643374 DOI: 10.1093/bib/bbad316] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 07/25/2023] [Accepted: 08/11/2023] [Indexed: 08/31/2023] Open
Abstract
Silencers are noncoding DNA sequence fragments located on the genome that suppress gene expression. The variation of silencers in specific cells is closely related to gene expression and cancer development. Computational approaches that exclusively rely on DNA sequence information for silencer identification fail to account for the cell specificity of silencers, resulting in diminished accuracy. Despite the discovery of several transcription factors and epigenetic modifications associated with silencers on the genome, there is still no definitive biological signal or combination thereof to fully characterize silencers, posing challenges in selecting suitable biological signals for their identification. Therefore, we propose a sophisticated deep learning framework called DeepICSH, which is based on multiple biological data sources. Specifically, DeepICSH leverages a deep convolutional neural network to automatically capture biologically relevant signal combinations strongly associated with silencers, originating from a diverse array of biological signals. Furthermore, the utilization of attention mechanisms facilitates the scoring and visualization of these signal combinations, whereas the employment of skip connections facilitates the fusion of multilevel sequence features and signal combinations, thereby empowering the accurate identification of silencers within specific cells. Extensive experiments on HepG2 and K562 cell line data sets demonstrate that DeepICSH outperforms state-of-the-art methods in silencer identification. Notably, we introduce for the first time a deep learning framework based on multi-omics data for classifying strong and weak silencers, achieving favorable performance. In conclusion, DeepICSH shows great promise for advancing the study and analysis of silencers in complex diseases. The source code is available at https://github.com/lyli1013/DeepICSH.
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Affiliation(s)
- Tianjiao Zhang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Liangyu Li
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Hailong Sun
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Dali Xu
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Guohua Wang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
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23
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Kleinschmidt H, Xu C, Bai L. Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation. Chromosoma 2023; 132:167-189. [PMID: 37184694 PMCID: PMC10542970 DOI: 10.1007/s00412-023-00796-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/16/2023]
Abstract
Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.
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Affiliation(s)
- Holly Kleinschmidt
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Cheng Xu
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Lu Bai
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA.
- Department of Physics, The Pennsylvania State University, University Park, PA, 16802, USA.
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24
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Duan YY, Chen XF, Zhu RJ, Jia YY, Huang XT, Zhang M, Yang N, Dong SS, Zeng M, Feng Z, Zhu DL, Wu H, Jiang F, Shi W, Hu WX, Ke X, Chen H, Liu Y, Jing RH, Guo Y, Li M, Yang TL. High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes. Am J Hum Genet 2023; 110:1266-1288. [PMID: 37506691 PMCID: PMC10432149 DOI: 10.1016/j.ajhg.2023.07.002] [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: 04/25/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.
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Affiliation(s)
- Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ren-Jie Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ying-Ying Jia
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xiao-Ting Huang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Meng Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ning Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Mengqi Zeng
- Frontier Institute of Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Zhihui Feng
- Frontier Institute of Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Hao Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Feng Jiang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Wei-Xin Hu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xin Ke
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Hao Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA
| | - Rui-Hua Jing
- Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710000, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China; Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
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25
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Gaulton KJ, Preissl S, Ren B. Interpreting non-coding disease-associated human variants using single-cell epigenomics. Nat Rev Genet 2023; 24:516-534. [PMID: 37161089 PMCID: PMC10629587 DOI: 10.1038/s41576-023-00598-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 05/11/2023]
Abstract
Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.
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Affiliation(s)
- Kyle J Gaulton
- Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego School of Medicine, La Jolla, CA, USA.
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Bing Ren
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
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26
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Fan K, Pfister E, Weng Z. Toward a comprehensive catalog of regulatory elements. Hum Genet 2023; 142:1091-1111. [PMID: 36935423 DOI: 10.1007/s00439-023-02519-3] [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: 11/06/2022] [Accepted: 01/03/2023] [Indexed: 03/21/2023]
Abstract
Regulatory elements are the genomic regions that interact with transcription factors to control cell-type-specific gene expression in different cellular environments. A precise and complete catalog of functional elements encoded by the human genome is key to understanding mammalian gene regulation. Here, we review the current state of regulatory element annotation. We first provide an overview of assays for characterizing functional elements, including genome, epigenome, transcriptome, three-dimensional chromatin interaction, and functional validation assays. We then discuss computational methods for defining regulatory elements, including peak-calling and other statistical modeling methods. Finally, we introduce several high-quality lists of regulatory element annotations and suggest potential future directions.
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Affiliation(s)
- Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Edith Pfister
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA.
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27
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Rummel CK, Gagliardi M, Herholt A, Ahmad R, Murek V, Weigert L, Hausruckinger A, Maidl S, Jimenez-Barron L, Trastulla L, Eder M, Rossner M, Ziller MJ. Cell type and condition specific functional annotation of schizophrenia associated non-coding genetic variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.545266. [PMID: 37425902 PMCID: PMC10326990 DOI: 10.1101/2023.06.27.545266] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Schizophrenia (SCZ) is a highly polygenic disease and genome wide association studies have identified thousands of genetic variants that are statistically associated with this psychiatric disorder. However, our ability to translate these associations into insights on the disease mechanisms has been challenging since the causal genetic variants, their molecular function and their target genes remain largely unknown. In order to address these questions, we established a functional genomics pipeline in combination with induced pluripotent stem cell technology to functionally characterize ~35,000 non-coding genetic variants associated with schizophrenia along with their target genes. This analysis identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on a molecular level in a highly cell type and condition specific fashion. These results provide a high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulation dependent molecular processes modulated by SCZ associated genetic variation.
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Affiliation(s)
- Christine K. Rummel
- Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Miriam Gagliardi
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Alexander Herholt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Ruhel Ahmad
- Max Planck Institute of Psychiatry, Munich, Germany
| | | | | | | | | | - Laura Jimenez-Barron
- Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Lucia Trastulla
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Mathias Eder
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Moritz Rossner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Michael J. Ziller
- Max Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry, University of Münster, Münster, Germany
- Center for Soft Nanoscience, University of Münster, Münster, Germany
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28
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Hussain S, Sadouni N, van Essen D, Dao LTM, Ferré Q, Charbonnier G, Torres M, Gallardo F, Lecellier CH, Sexton T, Saccani S, Spicuglia S. Short tandem repeats are important contributors to silencer elements in T cells. Nucleic Acids Res 2023; 51:4845-4866. [PMID: 36929452 PMCID: PMC10250210 DOI: 10.1093/nar/gkad187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 02/26/2023] [Accepted: 03/15/2023] [Indexed: 03/18/2023] Open
Abstract
The action of cis-regulatory elements with either activation or repression functions underpins the precise regulation of gene expression during normal development and cell differentiation. Gene activation by the combined activities of promoters and distal enhancers has been extensively studied in normal and pathological contexts. In sharp contrast, gene repression by cis-acting silencers, defined as genetic elements that negatively regulate gene transcription in a position-independent fashion, is less well understood. Here, we repurpose the STARR-seq approach as a novel high-throughput reporter strategy to quantitatively assess silencer activity in mammals. We assessed silencer activity from DNase hypersensitive I sites in a mouse T cell line. Identified silencers were associated with either repressive or active chromatin marks and enriched for binding motifs of known transcriptional repressors. CRISPR-mediated genomic deletions validated the repressive function of distinct silencers involved in the repression of non-T cell genes and genes regulated during T cell differentiation. Finally, we unravel an association of silencer activity with short tandem repeats, highlighting the role of repetitive elements in silencer activity. Our results provide a general strategy for genome-wide identification and characterization of silencer elements.
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Affiliation(s)
- Saadat Hussain
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Nori Sadouni
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Dominic van Essen
- Institute for Research on Cancer and Ageing, IRCAN, 06107 Nice, France
| | - Lan T M Dao
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Quentin Ferré
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Guillaume Charbonnier
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Magali Torres
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Frederic Gallardo
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
| | - Charles-Henri Lecellier
- Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS, Montpellier, France
- LIRMM, University of Montpellier, CNRS, Montpellier, France
| | - Tom Sexton
- Institut de Génétique et de Biologie Moléculaire et Cellulaire – IGBMC (CNRS UMR 7104, INSERM U1258, Université de Strasbourg), 67404 Illkirch, France
| | - Simona Saccani
- Institute for Research on Cancer and Ageing, IRCAN, 06107 Nice, France
| | - Salvatore Spicuglia
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, Marseille, France
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29
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Pudjihartono N, Ho D, Golovina E, Fadason T, Kempa-Liehr AW, O'Sullivan JM. Juvenile idiopathic arthritis-associated genetic loci exhibit spatially constrained gene regulatory effects across multiple tissues and immune cell types. J Autoimmun 2023; 138:103046. [PMID: 37229810 DOI: 10.1016/j.jaut.2023.103046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/04/2023] [Accepted: 04/15/2023] [Indexed: 05/27/2023]
Abstract
Juvenile idiopathic arthritis (JIA) is an autoimmune, inflammatory joint disease with complex genetic etiology. Previous GWAS have found many genetic loci associated with JIA. However, the biological mechanism behind JIA remains unknown mainly because most risk loci are located in non-coding genetic regions. Interestingly, increasing evidence has found that regulatory elements in the non-coding regions can regulate the expression of distant target genes through spatial (physical) interactions. Here, we used information on the 3D genome organization (Hi-C data) to identify target genes that physically interact with SNPs within JIA risk loci. Subsequent analysis of these SNP-gene pairs using data from tissue and immune cell type-specific expression quantitative trait loci (eQTL) databases allowed the identification of risk loci that regulate the expression of their target genes. In total, we identified 59 JIA-risk loci that regulate the expression of 210 target genes across diverse tissues and immune cell types. Functional annotation of spatial eQTLs within JIA risk loci identified significant overlap with gene regulatory elements (i.e., enhancers and transcription factor binding sites). We found target genes involved in immune-related pathways such as antigen processing and presentation (e.g., ERAP2, HLA class I and II), the release of pro-inflammatory cytokines (e.g., LTBR, TYK2), proliferation and differentiation of specific immune cell types (e.g., AURKA in Th17 cells), and genes involved in physiological mechanisms related to pathological joint inflammation (e.g., LRG1 in arteries). Notably, many of the tissues where JIA-risk loci act as spatial eQTLs are not classically considered central to JIA pathology. Overall, our findings highlight the potential tissue and immune cell type-specific regulatory changes contributing to JIA pathogenesis. Future integration of our data with clinical studies can contribute to the development of improved JIA therapy.
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Affiliation(s)
- N Pudjihartono
- The Liggins Institute, The University of Auckland, Auckland, New Zealand.
| | - D Ho
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - E Golovina
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - T Fadason
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - A W Kempa-Liehr
- Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| | - J M O'Sullivan
- The Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand; MRC Lifecourse Epidemiology Unit, University of Southampton, United Kingdom; Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, New South Wales, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia; A*STAR Singapore Institute for Clinical Sciences, Singapore, Singapore.
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30
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Stefan K, Barski A. Cis-regulatory atlas of primary human CD4+ T cells. BMC Genomics 2023; 24:253. [PMID: 37170195 PMCID: PMC10173520 DOI: 10.1186/s12864-023-09288-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 03/31/2023] [Indexed: 05/13/2023] Open
Abstract
Cis-regulatory elements (CRE) are critical for coordinating gene expression programs that dictate cell-specific differentiation and homeostasis. Recently developed self-transcribing active regulatory region sequencing (STARR-Seq) has allowed for genome-wide annotation of functional CREs. Despite this, STARR-Seq assays are only employed in cell lines, in part, due to difficulties in delivering reporter constructs. Herein, we implemented and validated a STARR-Seq-based screen in human CD4+ T cells using a non-integrating lentiviral transduction system. Lenti-STARR-Seq is the first example of a genome-wide assay of CRE function in human primary cells, identifying thousands of functional enhancers and negative regulatory elements (NREs) in human CD4+ T cells. We find an unexpected difference in nucleosome organization between enhancers and NRE: enhancers are located between nucleosomes, whereas NRE are occupied by nucleosomes in their endogenous locations. We also describe chromatin modification, eRNA production, and transcription factor binding at both enhancers and NREs. Our findings support the idea of silencer repurposing as enhancers in alternate cell types. Collectively, these data suggest that Lenti-STARR-Seq is a successful approach for CRE screening in primary human cell types, and provides an atlas of functional CREs in human CD4+ T cells.
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Affiliation(s)
- Kurtis Stefan
- Division of Allergy & Immunology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7028, Cincinnati, OH, 45229-3026, USA
- Medical Scientist Training Program (MSTP), University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Artem Barski
- Division of Allergy & Immunology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7028, Cincinnati, OH, 45229-3026, USA.
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229-3026, USA.
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA.
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31
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Ouyang W, Zhang X, Guo M, Wang J, Wang X, Gao R, Ma M, Xiang X, Luan S, Xing F, Cao Z, Yan J, Li G, Li X. Haplotype mapping of H3K27me3-associated chromatin interactions defines topological regulation of gene silencing in rice. Cell Rep 2023; 42:112350. [PMID: 37071534 DOI: 10.1016/j.celrep.2023.112350] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 02/06/2023] [Accepted: 03/20/2023] [Indexed: 04/19/2023] Open
Abstract
Histone modification H3K27me3 is an important chromatin mark that plays vital roles in repressing expression of developmental genes. Here, we construct high-resolution 3D genome maps using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and characterize H3K27me3-associated chromatin interactions in an elite rice hybrid, Shanyou 63. We find that many H3K27me3-marked regions may function as silencer-like regulatory elements. The silencer-like elements can come into proximity with distal target genes via forming chromatin loops in 3D space of the nuclei, regulating gene silencing and plant traits. Natural and induced deletion of silencers upregulate expression of distal connected genes. Furthermore, we identify extensive allele-specific chromatin loops. We find that genetic variations alter allelic chromatin topology, thus modulating allelic gene imprinting in rice hybrids. In conclusion, the characterization of silencer-like regulatory elements and haplotype-resolved chromatin interaction maps provide insights into the understanding of molecular mechanisms underlying allelic gene silencing and plant trait controlling.
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Affiliation(s)
- Weizhi Ouyang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiwen Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Minrong Guo
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Jing Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaoting Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Runxin Gao
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Meng Ma
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xu Xiang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Shiping Luan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Feng Xing
- College of Life Science, Xinyang Normal University, Xinyang 464000, China
| | - Zhilin Cao
- Department of Resources and Environment, Henan University of Engineering, Zhengzhou 451191, China
| | - Jiapei Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Xingwang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
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32
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Dominguez-Alonso S, Carracedo A, Rodriguez-Fontenla C. The non-coding genome in Autism Spectrum Disorders. Eur J Med Genet 2023; 66:104752. [PMID: 37023975 DOI: 10.1016/j.ejmg.2023.104752] [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: 10/24/2022] [Revised: 03/10/2023] [Accepted: 03/19/2023] [Indexed: 04/08/2023]
Abstract
Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".
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Affiliation(s)
- S Dominguez-Alonso
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - C Rodriguez-Fontenla
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain.
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33
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Vermunt MW, Luan J, Zhang Z, Thrasher AJ, Huang A, Saari MS, Khandros E, Beagrie RA, Zhang S, Vemulamada P, Brilleman M, Lee K, Yano JA, Giardine BM, Keller CA, Hardison RC, Blobel GA. Gene silencing dynamics are modulated by transiently active regulatory elements. Mol Cell 2023; 83:715-730.e6. [PMID: 36868189 PMCID: PMC10719944 DOI: 10.1016/j.molcel.2023.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 12/05/2022] [Accepted: 02/03/2023] [Indexed: 03/05/2023]
Abstract
Transcriptional enhancers have been extensively characterized, but cis-regulatory elements involved in acute gene repression have received less attention. Transcription factor GATA1 promotes erythroid differentiation by activating and repressing distinct gene sets. Here, we study the mechanism by which GATA1 silences the proliferative gene Kit during murine erythroid cell maturation and define stages from initial loss of activation to heterochromatinization. We find that GATA1 inactivates a potent upstream enhancer but concomitantly creates a discrete intronic regulatory region marked by H3K27ac, short noncoding RNAs, and de novo chromatin looping. This enhancer-like element forms transiently and serves to delay Kit silencing. The element is ultimately erased via the FOG1/NuRD deacetylase complex, as revealed by the study of a disease-associated GATA1 variant. Hence, regulatory sites can be self-limiting by dynamic co-factor usage. Genome-wide analyses across cell types and species uncover transiently active elements at numerous genes during repression, suggesting that modulation of silencing kinetics is widespread.
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Affiliation(s)
- Marit W Vermunt
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
| | - Jing Luan
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhe Zhang
- Department of Biomedical and Health Informatics, The Children's Hospital of Pennsylvania, Philadelphia, PA 19104, USA
| | - A Josephine Thrasher
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Anran Huang
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Megan S Saari
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Eugene Khandros
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert A Beagrie
- Chromatin and Disease Group, Wellcome Centre for Human Genetics, Oxford OX3 7BN, UK
| | - Shiping Zhang
- Department of Biomedical and Health Informatics, The Children's Hospital of Pennsylvania, Philadelphia, PA 19104, USA
| | - Pranay Vemulamada
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matilda Brilleman
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kiwon Lee
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jennifer A Yano
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Belinda M Giardine
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Cheryl A Keller
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Ross C Hardison
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Gerd A Blobel
- Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
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34
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Gallego Romero I, Lea AJ. Leveraging massively parallel reporter assays for evolutionary questions. Genome Biol 2023; 24:26. [PMID: 36788564 PMCID: PMC9926830 DOI: 10.1186/s13059-023-02856-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 01/17/2023] [Indexed: 02/16/2023] Open
Abstract
A long-standing goal of evolutionary biology is to decode how gene regulation contributes to organismal diversity. Doing so is challenging because it is hard to predict function from non-coding sequence and to perform molecular research with non-model taxa. Massively parallel reporter assays (MPRAs) enable the testing of thousands to millions of sequences for regulatory activity simultaneously. Here, we discuss the execution, advantages, and limitations of MPRAs, with a focus on evolutionary questions. We propose solutions for extending MPRAs to rare taxa and those with limited genomic resources, and we underscore MPRA's broad potential for driving genome-scale, functional studies across organisms.
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Affiliation(s)
- Irene Gallego Romero
- Melbourne Integrative Genomics, University of Melbourne, Royal Parade, Parkville, Victoria, 3010, Australia. .,School of BioSciences, The University of Melbourne, Royal Parade, Parkville, 3010, Australia. .,The Centre for Stem Cell Systems, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, 30 Royal Parade, Parkville, Victoria, 3010, Australia. .,Center for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, Riia 23b, 51010, Tartu, Estonia.
| | - Amanda J. Lea
- grid.152326.10000 0001 2264 7217Department of Biological Sciences, Vanderbilt University, Nashville, TN 37240 USA ,grid.152326.10000 0001 2264 7217Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37240 USA ,grid.152326.10000 0001 2264 7217Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37240 USA ,Child and Brain Development Program, Canadian Institute for Advanced Study, Toronto, Canada
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35
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Kim S, Wysocka J. Deciphering the multi-scale, quantitative cis-regulatory code. Mol Cell 2023; 83:373-392. [PMID: 36693380 PMCID: PMC9898153 DOI: 10.1016/j.molcel.2022.12.032] [Citation(s) in RCA: 57] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/24/2023]
Abstract
Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.
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Affiliation(s)
- Seungsoo Kim
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Joanna Wysocka
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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36
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Mouri K, Dewey HB, Castro R, Berenzy D, Kales S, Tewhey R. Whole-genome functional characterization of RE1 silencers using a modified massively parallel reporter assay. CELL GENOMICS 2023; 3:100234. [PMID: 36777181 PMCID: PMC9903721 DOI: 10.1016/j.xgen.2022.100234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 09/12/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022]
Abstract
Both upregulation and downregulation by cis-regulatory elements help modulate precise gene expression. However, our understanding of repressive elements is far more limited than activating elements. To address this gap, we characterized RE1, a group of transcriptional silencers bound by REST, at genome-wide scale using a modified massively parallel reporter assay (MPRAduo). MPRAduo empirically defined a minimal binding strength of REST (REST motif-intrinsic value [m-value]), above which cofactors colocalize and silence transcription. We identified 1,500 human variants that alter RE1 silencing and found that their effect sizes are predictable when they overlap with REST-binding sites above the m-value. Additionally, we demonstrate that non-canonical REST-binding motifs exhibit silencer function only if they precisely align half sites with specific spacer lengths. Our results show mechanistic insights into RE1, which allow us to predict its activity and effect of variants on RE1, providing a paradigm for performing genome-wide functional characterization of transcription-factor-binding sites.
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Affiliation(s)
| | | | | | | | - Susan Kales
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
- Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
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37
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Zhou Q, Cheng S, Zheng S, Wang Z, Guan P, Zhu Z, Huang X, Zhou C, Li G. ChromLoops: a comprehensive database for specific protein-mediated chromatin loops in diverse organisms. Nucleic Acids Res 2023; 51:D57-D69. [PMID: 36243984 PMCID: PMC9825580 DOI: 10.1093/nar/gkac893] [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: 08/14/2022] [Revised: 09/14/2022] [Accepted: 10/03/2022] [Indexed: 01/29/2023] Open
Abstract
Chromatin loops (or chromatin interactions) are important elements of chromatin structures. Disruption of chromatin loops is associated with many diseases, such as cancer and polydactyly. A few methods, including ChIA-PET, HiChIP and PLAC-Seq, have been proposed to detect high-resolution, specific protein-mediated chromatin loops. With rapid progress in 3D genomic research, ChIA-PET, HiChIP and PLAC-Seq datasets continue to accumulate, and effective collection and processing for these datasets are urgently needed. Here, we developed a comprehensive, multispecies and specific protein-mediated chromatin loop database (ChromLoops, https://3dgenomics.hzau.edu.cn/chromloops), which integrated 1030 ChIA-PET, HiChIP and PLAC-Seq datasets from 13 species, and documented 1 491 416 813 high-quality chromatin loops. We annotated genes and regions overlapping with chromatin loop anchors with rich functional annotations, such as regulatory elements (enhancers, super-enhancers and silencers), variations (common SNPs, somatic SNPs and eQTLs), and transcription factor binding sites. Moreover, we identified genes with high-frequency chromatin interactions in the collected species. In particular, we identified genes with high-frequency interactions in cancer samples. We hope that ChromLoops will provide a new platform for studying chromatin interaction regulation in relation to biological processes and disease.
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Affiliation(s)
- Qiangwei Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Sheng Cheng
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Shanshan Zheng
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhenji Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Pengpeng Guan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhixian Zhu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Xingyu Huang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Cong Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.,Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, Key Laboratory of Smart Farming for Agricultural Animals, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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38
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Аpplication of massive parallel reporter analysis in biotechnology and medicine. КЛИНИЧЕСКАЯ ПРАКТИКА 2023. [DOI: 10.17816/clinpract115063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The development and functioning of an organism relies on tissue-specific gene programs. Genome regulatory elements play a key role in the regulation of such programs, and disruptions in their function can lead to the development of various pathologies, including cancers, malformations and autoimmune diseases. The emergence of high-throughput genomic studies has led to massively parallel reporter analysis (MPRA) methods, which allow the functional verification and identification of regulatory elements on a genome-wide scale. Initially MPRA was used as a tool to investigate fundamental aspects of epigenetics, but the approach also has great potential for clinical and practical biotechnology. Currently, MPRA is used for validation of clinically significant mutations, identification of tissue-specific regulatory elements, search for the most promising loci for transgene integration, and is an indispensable tool for creating highly efficient expression systems, the range of application of which extends from approaches for protein development and design of next-generation therapeutic antibody superproducers to gene therapy. In this review, the main principles and areas of practical application of high-throughput reporter assays will be discussed.
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39
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Alatawneh R, Salomon Y, Eshel R, Orenstein Y, Birnbaum RY. Deciphering transcription factors and their corresponding regulatory elements during inhibitory interneuron differentiation using deep neural networks. Front Cell Dev Biol 2023; 11:1034604. [PMID: 36891511 PMCID: PMC9986276 DOI: 10.3389/fcell.2023.1034604] [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: 09/01/2022] [Accepted: 01/23/2023] [Indexed: 02/22/2023] Open
Abstract
During neurogenesis, the generation and differentiation of neuronal progenitors into inhibitory gamma-aminobutyric acid-containing interneurons is dependent on the combinatorial activity of transcription factors (TFs) and their corresponding regulatory elements (REs). However, the roles of neuronal TFs and their target REs in inhibitory interneuron progenitors are not fully elucidated. Here, we developed a deep-learning-based framework to identify enriched TF motifs in gene REs (eMotif-RE), such as poised/repressed enhancers and putative silencers. Using epigenetic datasets (e.g., ATAC-seq and H3K27ac/me3 ChIP-seq) from cultured interneuron-like progenitors, we distinguished between active enhancer sequences (open chromatin with H3K27ac) and non-active enhancer sequences (open chromatin without H3K27ac). Using our eMotif-RE framework, we discovered enriched motifs of TFs such as ASCL1, SOX4, and SOX11 in the active enhancer set suggesting a cooperativity function for ASCL1 and SOX4/11 in active enhancers of neuronal progenitors. In addition, we found enriched ZEB1 and CTCF motifs in the non-active set. Using an in vivo enhancer assay, we showed that most of the tested putative REs from the non-active enhancer set have no enhancer activity. Two of the eight REs (25%) showed function as poised enhancers in the neuronal system. Moreover, mutated REs for ZEB1 and CTCF motifs increased their in vivo activity as enhancers indicating a repressive effect of ZEB1 and CTCF on these REs that likely function as repressed enhancers or silencers. Overall, our work integrates a novel framework based on deep learning together with a functional assay that elucidated novel functions of TFs and their corresponding REs. Our approach can be applied to better understand gene regulation not only in inhibitory interneuron differentiation but in other tissue and cell types.
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Affiliation(s)
- Rawan Alatawneh
- Department of Life Sciences, Faculty of Natural Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yahel Salomon
- School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Reut Eshel
- Department of Life Sciences, Faculty of Natural Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yaron Orenstein
- School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel.,The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Ramon Y Birnbaum
- Department of Life Sciences, Faculty of Natural Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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40
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Preissl S, Gaulton KJ, Ren B. Characterizing cis-regulatory elements using single-cell epigenomics. Nat Rev Genet 2023; 24:21-43. [PMID: 35840754 PMCID: PMC9771884 DOI: 10.1038/s41576-022-00509-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2022] [Indexed: 12/24/2022]
Abstract
Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.
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Affiliation(s)
- Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Kyle J Gaulton
- Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
| | - Bing Ren
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
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41
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Abstract
Injury to muscle brings about the activation of stem cells, which then generate new myocytes to replace damaged tissue. We demonstrate that this activation is accompanied by a dramatic change in the stem-cell methylation pattern that prepares them epigenetically for terminal myocyte differentiation. These de- and de novo methylation events occur at regulatory elements associated with genes involved in myogenesis and are necessary for activation and regeneration. Local injury of one muscle elicits an almost identical epigenetic change in satellite cells from other muscles in the body, in a process mediated by circulating factors. Furthermore, this same methylation state is also generated in muscle stem cells (MuSCs) of female animals following pregnancy, even in the absence of any injury. Unlike the activation-induced expression changes, which are transient, the induced methylation profile is stably maintained in resident MuSCs and thus represents a molecular memory of previous physiological events that is probably programmed to provide a mechanism for long-term adaptation.
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42
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Vespasiani DM, Jacobs GS, Cook LE, Brucato N, Leavesley M, Kinipi C, Ricaut FX, Cox MP, Gallego Romero I. Denisovan introgression has shaped the immune system of present-day Papuans. PLoS Genet 2022; 18:e1010470. [PMID: 36480515 PMCID: PMC9731433 DOI: 10.1371/journal.pgen.1010470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 10/10/2022] [Indexed: 12/13/2022] Open
Abstract
Modern humans have admixed with multiple archaic hominins. Papuans, in particular, owe up to 5% of their genome to Denisovans, a sister group to Neanderthals whose remains have only been identified in Siberia and Tibet. Unfortunately, the biological and evolutionary significance of these introgression events remain poorly understood. Here we investigate the function of both Denisovan and Neanderthal alleles characterised within a set of 56 genomes from Papuan individuals. By comparing the distribution of archaic and non-archaic variants we assess the consequences of archaic admixture across a multitude of different cell types and functional elements. We observe an enrichment of archaic alleles within cis-regulatory elements and transcribed regions of the genome, with Denisovan variants strongly affecting elements active within immune-related cells. We identify 16,048 and 10,032 high-confidence Denisovan and Neanderthal variants that fall within annotated cis-regulatory elements and with the potential to alter the affinity of multiple transcription factors to their cognate DNA motifs, highlighting a likely mechanism by which introgressed DNA can impact phenotypes. Lastly, we experimentally validate these predictions by testing the regulatory potential of five Denisovan variants segregating within Papuan individuals, and find that two are associated with a significant reduction of transcriptional activity in plasmid reporter assays. Together, these data provide support for a widespread contribution of archaic DNA in shaping the present levels of modern human genetic diversity, with different archaic ancestries potentially affecting multiple phenotypic traits within non-Africans.
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Affiliation(s)
- Davide M. Vespasiani
- Melbourne Integrative Genomics, University of Melbourne, Parkville, Australia
- School of Biosciences, University of Melbourne, Parkville, Australia
| | - Guy S. Jacobs
- Department of Archaeology, University of Cambridge, Cambridge, Uniteed Kingdom
| | - Laura E. Cook
- Melbourne Integrative Genomics, University of Melbourne, Parkville, Australia
- School of Biosciences, University of Melbourne, Parkville, Australia
| | - Nicolas Brucato
- Laboratoire de Evolution et Diversite Biologique, Université de Toulouse Midi-Pyrénées, Toulouse, France
| | - Matthew Leavesley
- School of Humanities and Social Sciences, University of Papua New Guinea, Port Moresby, Papua New Guinea
- College of Arts, Society and Education, James Cook University, Cairns, Australia
- ARC Centre of Excellence for Australian Biodiversity and Heritage, University of Wollongong, Wollongong, Australia
| | - Christopher Kinipi
- School of Humanities and Social Sciences, University of Papua New Guinea, Port Moresby, Papua New Guinea
| | - François-Xavier Ricaut
- Laboratoire de Evolution et Diversite Biologique, Université de Toulouse Midi-Pyrénées, Toulouse, France
| | - Murray P. Cox
- School of Natural Sciences, Massey University, Palmerston North, New Zealand
| | - Irene Gallego Romero
- Melbourne Integrative Genomics, University of Melbourne, Parkville, Australia
- School of Biosciences, University of Melbourne, Parkville, Australia
- Center for Stem Cell Systems, University of Melbourne, Parkville, Australia
- Center for Genomics, Evolution and Medicine, University of Tartu, Tartu, Estonia
- * E-mail:
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43
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Pang B, van Weerd JH, Hamoen FL, Snyder MP. Identification of non-coding silencer elements and their regulation of gene expression. Nat Rev Mol Cell Biol 2022; 24:383-395. [DOI: 10.1038/s41580-022-00549-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/29/2022] [Indexed: 11/09/2022]
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44
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Cooper YA, Guo Q, Geschwind DH. Multiplexed functional genomic assays to decipher the noncoding genome. Hum Mol Genet 2022; 31:R84-R96. [PMID: 36057282 PMCID: PMC9585676 DOI: 10.1093/hmg/ddac194] [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: 07/02/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 11/14/2022] Open
Abstract
Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.
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Affiliation(s)
- Yonatan A Cooper
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Qiuyu Guo
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California Los Angeles, Los Angeles, CA, USA
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45
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Xu J, Pratt HE, Moore JE, Gerstein MB, Weng Z. Building integrative functional maps of gene regulation. Hum Mol Genet 2022; 31:R114-R122. [PMID: 36083269 PMCID: PMC9585680 DOI: 10.1093/hmg/ddac195] [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: 07/17/2022] [Revised: 08/03/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Every cell in the human body inherits a copy of the same genetic information. The three billion base pairs of DNA in the human genome, and the roughly 50 000 coding and non-coding genes they contain, must thus encode all the complexity of human development and cell and tissue type diversity. Differences in gene regulation, or the modulation of gene expression, enable individual cells to interpret the genome differently to carry out their specific functions. Here we discuss recent and ongoing efforts to build gene regulatory maps, which aim to characterize the regulatory roles of all sequences in a genome. Many researchers and consortia have identified such regulatory elements using functional assays and evolutionary analyses; we discuss the results, strengths and shortcomings of their approaches. We also discuss new techniques the field can leverage and emerging challenges it will face while striving to build gene regulatory maps of ever-increasing resolution and comprehensiveness.
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Affiliation(s)
- Jinrui Xu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
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46
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Guo Y, Wang GG. Modulation of the high-order chromatin structure by Polycomb complexes. Front Cell Dev Biol 2022; 10:1021658. [PMID: 36274840 PMCID: PMC9579376 DOI: 10.3389/fcell.2022.1021658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The multi-subunit Polycomb Repressive Complex (PRC) 1 and 2 act, either independently or synergistically, to maintain and enforce a repressive state of the target chromatin, thereby regulating the processes of cell lineage specification and organismal development. In recent years, deep sequencing-based and imaging-based technologies, especially those tailored for mapping three-dimensional (3D) chromatin organization and structure, have allowed a better understanding of the PRC complex-mediated long-range chromatin contacts and DNA looping. In this review, we review current advances as for how Polycomb complexes function to modulate and help define the high-order chromatin structure and topology, highlighting the multi-faceted roles of Polycomb proteins in gene and genome regulation.
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Affiliation(s)
- Yiran Guo
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- *Correspondence: Yiran Guo, ; Gang Greg Wang,
| | - Gang Greg Wang
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
- *Correspondence: Yiran Guo, ; Gang Greg Wang,
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47
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Nair SJ, Suter T, Wang S, Yang L, Yang F, Rosenfeld MG. Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures. Trends Genet 2022; 38:1019-1047. [PMID: 35811173 PMCID: PMC9474616 DOI: 10.1016/j.tig.2022.05.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/05/2022] [Accepted: 05/31/2022] [Indexed: 02/08/2023]
Abstract
Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.
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Affiliation(s)
- Sreejith J Nair
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, USA.
| | - Tom Suter
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Susan Wang
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA; Cellular and Molecular Medicine Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Lu Yang
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Feng Yang
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michael G Rosenfeld
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
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48
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McAfee JC, Bell JL, Krupa O, Matoba N, Stein JL, Won H. Focus on your locus with a massively parallel reporter assay. J Neurodev Disord 2022; 14:50. [PMID: 36085003 PMCID: PMC9463819 DOI: 10.1186/s11689-022-09461-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 09/01/2022] [Indexed: 01/01/2023] Open
Abstract
A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.
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Affiliation(s)
- Jessica C. McAfee
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Jessica L. Bell
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Oleh Krupa
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Nana Matoba
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Jason L. Stein
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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49
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Hajheidari M, Huang SSC. Elucidating the biology of transcription factor-DNA interaction for accurate identification of cis-regulatory elements. CURRENT OPINION IN PLANT BIOLOGY 2022; 68:102232. [PMID: 35679803 PMCID: PMC10103634 DOI: 10.1016/j.pbi.2022.102232] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 05/03/2023]
Abstract
Transcription factors (TFs) play a critical role in determining cell fate decisions by integrating developmental and environmental signals through binding to specific cis-regulatory modules and regulating spatio-temporal specificity of gene expression patterns. Precise identification of functional TF binding sites in time and space not only will revolutionize our understanding of regulatory networks governing cell fate decisions but is also instrumental to uncover how genetic variations cause morphological diversity or disease. In this review, we discuss recent advances in mapping TF binding sites and characterizing the various parameters underlying the complexity of binding site recognition by TFs.
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Affiliation(s)
- Mohsen Hajheidari
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA
| | - Shao-Shan Carol Huang
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA.
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50
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Hansen TJ, Hodges E. ATAC-STARR-seq reveals transcription factor-bound activators and silencers across the chromatin accessible human genome. Genome Res 2022; 32:gr.276766.122. [PMID: 35858748 PMCID: PMC9435738 DOI: 10.1101/gr.276766.122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/11/2022] [Indexed: 11/26/2022]
Abstract
Massively parallel reporter assays (MPRAs) test the capacity of putative gene regulatory elements to drive transcription on a genome-wide scale. Most gene regulatory activity occurs within accessible chromatin, and recently described methods have combined assays that capture these regions, such as assay for transposase-accessible chromatin using sequencing (ATAC-seq), with self-transcribing active regulatory region sequencing (STARR-seq) to selectively assay the regulatory potential of accessible DNA (ATAC-STARR-seq). Here, we report an integrated approach that quantifies activating and silencing regulatory activity, chromatin accessibility, and transcription factor (TF) occupancy with one assay using ATAC-STARR-seq. Our strategy, including important updates to the ATAC-STARR-seq assay and workflow, enabled high-resolution testing of ~50 million unique DNA fragments tiling ~101,000 accessible chromatin regions in human lymphoblastoid cells. We discovered that 30% of all accessible regions contain an activator, a silencer or both. Although few MPRA studies have explored silencing activity, we demonstrate silencers occur at similar frequencies to activators, and they represent a distinct functional group enriched for unique TF motifs and repressive histone modifications. We further show that Tn5 cut-site frequencies are retained in the ATAC-STARR plasmid library compared to standard ATAC-seq, enabling TF occupancy to be ascertained from ATAC-STARR data. With this approach, we found that activators and silencers cluster by distinct TF footprint combinations and these groups of activity represent different gene regulatory networks of immune cell function. Altogether, these data highlight the multi-layered capabilities of ATAC-STARR-seq to comprehensively investigate the regulatory landscape of the human genome all from a single DNA fragment source.
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