1
|
Xu Y, Das P, McCord RP, Shen T. Node features of chromosome structure networks and their connections to genome annotation. Comput Struct Biotechnol J 2024; 23:2240-2250. [PMID: 38827231 PMCID: PMC11140560 DOI: 10.1016/j.csbj.2024.05.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/04/2024] Open
Abstract
The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.
Collapse
Affiliation(s)
- Yingjie Xu
- Graduate School of Genome Science & Technology, University of Tennessee, Knoxville, TN 37996, USA
| | - Priyojit Das
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Rachel Patton McCord
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Tongye Shen
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| |
Collapse
|
2
|
Stankey CT, Bourges C, Haag LM, Turner-Stokes T, Piedade AP, Palmer-Jones C, Papa I, Silva Dos Santos M, Zhang Q, Cameron AJ, Legrini A, Zhang T, Wood CS, New FN, Randzavola LO, Speidel L, Brown AC, Hall A, Saffioti F, Parkes EC, Edwards W, Direskeneli H, Grayson PC, Jiang L, Merkel PA, Saruhan-Direskeneli G, Sawalha AH, Tombetti E, Quaglia A, Thorburn D, Knight JC, Rochford AP, Murray CD, Divakar P, Green M, Nye E, MacRae JI, Jamieson NB, Skoglund P, Cader MZ, Wallace C, Thomas DC, Lee JC. A disease-associated gene desert directs macrophage inflammation through ETS2. Nature 2024:10.1038/s41586-024-07501-1. [PMID: 38839969 DOI: 10.1038/s41586-024-07501-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 05/01/2024] [Indexed: 06/07/2024]
Abstract
Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2, highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22-which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu's arteritis3-6-we identify that the causal gene, ETS2, is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures7, we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.
Collapse
Affiliation(s)
- C T Stankey
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
- Department of Immunology and Inflammation, Imperial College London, London, UK
- Washington University School of Medicine, St Louis, MO, USA
| | - C Bourges
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
| | - L M Haag
- Division of Gastroenterology, Infectious Diseases and Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - T Turner-Stokes
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
- Department of Immunology and Inflammation, Imperial College London, London, UK
| | - A P Piedade
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
| | - C Palmer-Jones
- Department of Gastroenterology, Royal Free Hospital, London, UK
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
| | - I Papa
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
| | | | - Q Zhang
- Genomics of Inflammation and Immunity Group, Human Genetics Programme, Wellcome Sanger Institute, Hinxton, UK
| | - A J Cameron
- Wolfson Wohl Cancer Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - A Legrini
- Wolfson Wohl Cancer Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - T Zhang
- Wolfson Wohl Cancer Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - C S Wood
- Wolfson Wohl Cancer Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - F N New
- NanoString Technologies, Seattle, WA, USA
| | - L O Randzavola
- Department of Immunology and Inflammation, Imperial College London, London, UK
| | - L Speidel
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
- Genetics Institute, University College London, London, UK
| | - A C Brown
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - A Hall
- The Sheila Sherlock Liver Centre, Royal Free Hospital, London, UK
- Department of Cellular Pathology, Royal Free Hospital, London, UK
| | - F Saffioti
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
- The Sheila Sherlock Liver Centre, Royal Free Hospital, London, UK
| | - E C Parkes
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK
| | - W Edwards
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
| | - H Direskeneli
- Department of Internal Medicine, Division of Rheumatology, Marmara University, Istanbul, Turkey
| | - P C Grayson
- Systemic Autoimmunity Branch, NIAMS, National Institutes of Health, Bethesda, MD, USA
| | - L Jiang
- Department of Rheumatology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - P A Merkel
- Division of Rheumatology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Epidemiology, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - G Saruhan-Direskeneli
- Department of Physiology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - A H Sawalha
- Division of Rheumatology, Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Lupus Center of Excellence, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - E Tombetti
- Department of Biomedical and Clinical Sciences, Milan University, Milan, Italy
- Internal Medicine and Rheumatology, ASST FBF-Sacco, Milan, Italy
| | - A Quaglia
- Department of Cellular Pathology, Royal Free Hospital, London, UK
- UCL Cancer Institute, London, UK
| | - D Thorburn
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
- The Sheila Sherlock Liver Centre, Royal Free Hospital, London, UK
| | - J C Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
| | - A P Rochford
- Department of Gastroenterology, Royal Free Hospital, London, UK
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
| | - C D Murray
- Department of Gastroenterology, Royal Free Hospital, London, UK
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK
| | - P Divakar
- NanoString Technologies, Seattle, WA, USA
| | - M Green
- Experimental Histopathology STP, The Francis Crick Institute, London, UK
| | - E Nye
- Experimental Histopathology STP, The Francis Crick Institute, London, UK
| | - J I MacRae
- Metabolomics STP, The Francis Crick Institute, London, UK
| | - N B Jamieson
- Wolfson Wohl Cancer Centre, School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - P Skoglund
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - M Z Cader
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - C Wallace
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
| | - D C Thomas
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - J C Lee
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK.
- Department of Gastroenterology, Royal Free Hospital, London, UK.
- Institute for Liver and Digestive Health, Division of Medicine, University College London, London, UK.
| |
Collapse
|
3
|
Roberts BS, Anderson AG, Partridge EC, Cooper GM, Myers RM. Probabilistic association of differentially expressed genes with cis-regulatory elements. Genome Res 2024; 34:620-632. [PMID: 38631728 PMCID: PMC11146588 DOI: 10.1101/gr.278598.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 04/11/2024] [Indexed: 04/19/2024]
Abstract
Differential gene expression in response to perturbations is mediated at least in part by changes in binding of transcription factors (TFs) and other proteins at specific genomic regions. Association of these cis-regulatory elements (CREs) with their target genes is a challenging task that is essential to address many biological and mechanistic questions. Many current approaches rely on chromatin conformation capture techniques or single-cell correlational methods to establish CRE-to-gene associations. These methods can be effective but have limitations, including resolution, gaps in detectable association distances, and cost. As an alternative, we have developed DegCre, a nonparametric method that evaluates correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations. It has several unique features, including the ability to use any type of CRE activity measurement, yield probabilistic scores for CRE-to-gene pairs, and assess CRE-to-gene pairings across a wide range of sequence distances. We apply DegCre to six data sets, each using different perturbations and containing a variety of regulatory signal measurements, including chromatin openness, histone modifications, and TF occupancy. To test their efficacy, we compare DegCre associations to Hi-C loop calls and CRISPR-validated CRE-to-gene associations, establishing good performance by DegCre that is comparable or superior to competing methods. DegCre is a novel approach to the association of CREs to genes from a perturbation-differential perspective, with strengths that are complementary to existing approaches and allow for new insights into gene regulation.
Collapse
Affiliation(s)
- Brian S Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
- Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, Alabama 35899, USA
| | - Ashlyn G Anderson
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | | | - Gregory M Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
| |
Collapse
|
4
|
Qi T, Song L, Guo Y, Chen C, Yang J. From genetic associations to genes: methods, applications, and challenges. Trends Genet 2024:S0168-9525(24)00095-7. [PMID: 38734482 DOI: 10.1016/j.tig.2024.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 05/13/2024]
Abstract
Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.
Collapse
Affiliation(s)
- Ting Qi
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
| | - Liyang Song
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Yazhou Guo
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Chang Chen
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Jian Yang
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
| |
Collapse
|
5
|
Gilchrist JJ, Fang H, Danielli S, Tomkova M, Nassiri I, Ng E, Tong O, Taylor C, Muldoon D, Cohen LRZ, Al-Mossawi H, Lau E, Neville M, Schuster-Boeckler B, Knight JC, Fairfax BP. Characterization of the genetic determinants of context-specific DNA methylation in primary monocytes. CELL GENOMICS 2024; 4:100541. [PMID: 38663408 PMCID: PMC11099345 DOI: 10.1016/j.xgen.2024.100541] [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: 05/17/2023] [Revised: 11/24/2023] [Accepted: 03/27/2024] [Indexed: 05/12/2024]
Abstract
To better understand inter-individual variation in sensitivity of DNA methylation (DNAm) to immune activity, we characterized effects of inflammatory stimuli on primary monocyte DNAm (n = 190). We find that monocyte DNAm is site-dependently sensitive to lipopolysaccharide (LPS), with LPS-induced demethylation occurring following hydroxymethylation. We identify 7,359 high-confidence immune-modulated CpGs (imCpGs) that differ in genomic localization and transcription factor usage according to whether they represent a gain or loss in DNAm. Demethylated imCpGs are profoundly enriched for enhancers and colocalize to genes enriched for disease associations, especially cancer. DNAm is age associated, and we find that 24-h LPS exposure triggers approximately 6 months of gain in epigenetic age, directly linking epigenetic aging with innate immune activity. By integrating LPS-induced changes in DNAm with genetic variation, we identify 234 imCpGs under local genetic control. Exploring shared causal loci between LPS-induced DNAm responses and human disease traits highlights examples of disease-associated loci that modulate imCpG formation.
Collapse
Affiliation(s)
- James J Gilchrist
- Department of Paediatrics, University of Oxford, Oxford OX3 9DU, UK; MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Hai Fang
- Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Sara Danielli
- Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Marketa Tomkova
- Ludwig Cancer Research Oxford, University of Oxford, Oxford OX3 7DQ, UK
| | - Isar Nassiri
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK; Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Esther Ng
- Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford OX3 7LD, UK
| | - Orion Tong
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Chelsea Taylor
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Dylan Muldoon
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Lea R Z Cohen
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Hussein Al-Mossawi
- Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford OX3 7LD, UK
| | - Evelyn Lau
- Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Matt Neville
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford OX3 7LE, UK
| | | | - Julian C Knight
- Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Benjamin P Fairfax
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK; Department of Oncology, University of Oxford, Oxford OX3 9DS, UK.
| |
Collapse
|
6
|
Gómez Acuña LI, Flyamer I, Boyle S, Friman ET, Bickmore WA. Transcription decouples estrogen-dependent changes in enhancer-promoter contact frequencies and spatial proximity. PLoS Genet 2024; 20:e1011277. [PMID: 38781242 DOI: 10.1371/journal.pgen.1011277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 06/05/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
How enhancers regulate their target genes in the context of 3D chromatin organization is extensively studied and models which do not require direct enhancer-promoter contact have recently emerged. Here, we use the activation of estrogen receptor-dependent enhancers in a breast cancer cell line to study enhancer-promoter communication at two loci. This allows high temporal resolution tracking of molecular events from hormone stimulation to efficient gene activation. We examine how both enhancer-promoter spatial proximity assayed by DNA fluorescence in situ hybridization, and contact frequencies resulting from chromatin in situ fragmentation and proximity ligation, change dynamically during enhancer-driven gene activation. These orthogonal methods produce seemingly paradoxical results: upon enhancer activation enhancer-promoter contact frequencies increase while spatial proximity decreases. We explore this apparent discrepancy using different estrogen receptor ligands and transcription inhibitors. Our data demonstrate that enhancer-promoter contact frequencies are transcription independent whereas altered enhancer-promoter proximity depends on transcription. Our results emphasize that the relationship between contact frequencies and physical distance in the nucleus, especially over short genomic distances, is not always a simple one.
Collapse
Affiliation(s)
- Luciana I Gómez Acuña
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| | - Ilya Flyamer
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| | - Shelagh Boyle
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| | - Elias T Friman
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| | - Wendy A Bickmore
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| |
Collapse
|
7
|
Bhattarai KR, Mobley RJ, Barnett KR, Ferguson DC, Hansen BS, Diedrich JD, Bergeron BP, Yoshimura S, Yang W, Crews KR, Manring CS, Jabbour E, Paietta E, Litzow MR, Kornblau SM, Stock W, Inaba H, Jeha S, Pui CH, Cheng C, Pruett-Miller SM, Relling MV, Yang JJ, Evans WE, Savic D. Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment. Nat Commun 2024; 15:3681. [PMID: 38693155 PMCID: PMC11063049 DOI: 10.1038/s41467-024-48124-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
Defining genetic factors impacting chemotherapy failure can help to better predict response and identify drug resistance mechanisms. However, there is limited understanding of the contribution of inherited noncoding genetic variation on inter-individual differences in chemotherapy response in childhood acute lymphoblastic leukemia (ALL). Here we map inherited noncoding variants associated with treatment outcome and/or chemotherapeutic drug resistance to ALL cis-regulatory elements and investigate their gene regulatory potential and target gene connectivity using massively parallel reporter assays and three-dimensional chromatin looping assays, respectively. We identify 54 variants with transcriptional effects and high-confidence gene connectivity. Additionally, functional interrogation of the top variant, rs1247117, reveals changes in chromatin accessibility, PU.1 binding affinity and gene expression, and deletion of the genomic interval containing rs1247117 sensitizes cells to vincristine. Together, these data demonstrate that noncoding regulatory variants associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to antileukemic agents.
Collapse
Affiliation(s)
- Kashi Raj Bhattarai
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Robert J Mobley
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kelly R Barnett
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel C Ferguson
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Baranda S Hansen
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jonathan D Diedrich
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Brennan P Bergeron
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Satoshi Yoshimura
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Advanced Pediatric Medicine, Tohoku University School of Medicine, Tokyo, Japan
| | - Wenjian Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kristine R Crews
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Christopher S Manring
- Alliance Hematologic Malignancy Biorepository; Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH, 43210, USA
| | - Elias Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Mark R Litzow
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wendy Stock
- Comprehensive Cancer Center, University of Chicago Medicine, Chicago, IL, USA
| | - Hiroto Inaba
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Sima Jeha
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ching-Hon Pui
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Cheng Cheng
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Shondra M Pruett-Miller
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Mary V Relling
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jun J Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - William E Evans
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel Savic
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| |
Collapse
|
8
|
Liaw YC, Matsuda K, Liaw YP. Identification of an novel genetic variant associated with osteoporosis: insights from the Taiwan Biobank Study. JBMR Plus 2024; 8:ziae028. [PMID: 38655459 PMCID: PMC11037432 DOI: 10.1093/jbmrpl/ziae028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 02/18/2024] [Accepted: 03/01/2024] [Indexed: 04/26/2024] Open
Abstract
Purpose The purpose of this study was to identify new independent significant SNPs associated with osteoporosis using data from the Taiwan Biobank (TWBB). Material and Methods The dataset was divided into discovery (60%) and replication (40%) subsets. Following data quality control, genome-wide association study (GWAS) analysis was performed, adjusting for sex, age, and the top 5 principal components, employing the Scalable and Accurate Implementation of the Generalized mixed model approach. This was followed by a meta-analysis of TWBB1 and TWBB2. The Functional Mapping and Annotation (FUMA) platform was used to identify osteoporosis-associated loci. Manhattan and quantile-quantile plots were generated using the FUMA platform to visualize the results. Independent significant SNPs were selected based on genome-wide significance (P < 5 × 10-8) and independence from each other (r2 < 0.6) within a 1 Mb window. Positional, eQTL(expression quantitative trait locus), and Chromatin interaction mapping were used to map SNPs to genes. Results A total of 29 084 individuals (3154 osteoporosis cases and 25 930 controls) were used for GWAS analysis (TWBB1 data), and 18 918 individuals (1917 cases and 17 001 controls) were utilized for replication studies (TWBB2 data). We identified a new independent significant SNP for osteoporosis in TWBB1, with the lead SNP rs76140829 (minor allele frequency = 0.055, P-value = 1.15 × 10-08). Replication of the association was performed in TWBB2, yielding a P-value of 6.56 × 10-3. The meta-analysis of TWBB1 and TWBB2 data demonstrated a highly significant association for SNP rs76140829 (P-value = 7.52 × 10-10). In the positional mapping of rs76140829, 6 genes (HABP2, RP11-481H12.1, RNU7-165P, RP11-139 K1.2, RP11-57H14.3, and RP11-214 N15.5) were identified through chromatin interaction mapping in mesenchymal stem cells. Conclusions Our GWAS analysis using the Taiwan Biobank dataset unveils rs76140829 in the VTI1A gene as a key risk variant associated with osteoporosis. This finding expands our understanding of the genetic basis of osteoporosis and highlights the potential regulatory role of this SNP in mesenchymal stem cells.
Collapse
Affiliation(s)
- Yi-Ching Liaw
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo 108-8639, Japan
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung 40201, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
| |
Collapse
|
9
|
Peralta-Alvarez CA, Núñez-Martínez HN, Cerecedo-Castillo ÁJ, Poot-Hernández AC, Tapia-Urzúa G, Garza-Manero S, Guerrero G, Recillas-Targa F. A Bidirectional Non-Coding RNA Promoter Mediates Long-Range Gene Expression Regulation. Genes (Basel) 2024; 15:549. [PMID: 38790178 PMCID: PMC11120797 DOI: 10.3390/genes15050549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
Recent evidence suggests that human gene promoters display gene expression regulatory mechanisms beyond the typical single gene local transcription modulation. In mammalian genomes, genes with an associated bidirectional promoter are abundant; bidirectional promoter architecture serves as a regulatory hub for a gene pair expression. However, it has been suggested that its contribution to transcriptional regulation might exceed local transcription initiation modulation. Despite their abundance, the functional consequences of bidirectional promoter architecture remain largely unexplored. This work studies the long-range gene expression regulatory role of a long non-coding RNA gene promoter using chromosome conformation capture methods. We found that this particular bidirectional promoter contributes to distal gene expression regulation in a target-specific manner by establishing promoter-promoter interactions. In particular, we validated that the promoter-promoter interactions of this regulatory element with the promoter of distal gene BBX contribute to modulating the transcription rate of this gene; removing the bidirectional promoter from its genomic context leads to a rearrangement of BBX promoter-enhancer interactions and to increased gene expression. Moreover, long-range regulatory functionality is not directly dependent on its associated non-coding gene pair expression levels.
Collapse
Affiliation(s)
- Carlos Alberto Peralta-Alvarez
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
- Instituto de Fisiología Celular, Unidad de Bioinformática y Manejo de la Información, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
| | - Hober Nelson Núñez-Martínez
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| | - Ángel Josué Cerecedo-Castillo
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| | - Augusto César Poot-Hernández
- Instituto de Fisiología Celular, Unidad de Bioinformática y Manejo de la Información, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
| | - Gustavo Tapia-Urzúa
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| | - Sylvia Garza-Manero
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| | - Georgina Guerrero
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| | - Félix Recillas-Targa
- Instituto de Fisiología Celular, Departaménto de Genética Molecular, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (C.A.P.-A.); (H.N.N.-M.)
| |
Collapse
|
10
|
James C, Trevisan-Herraz M, Juan D, Rico D. Evolutionary analysis of gene ages across TADs associates chromatin topology with whole-genome duplications. Cell Rep 2024; 43:113895. [PMID: 38517894 DOI: 10.1016/j.celrep.2024.113895] [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: 08/20/2022] [Revised: 11/03/2023] [Accepted: 02/16/2024] [Indexed: 03/24/2024] Open
Abstract
Topologically associated domains (TADs) are interaction subnetworks of chromosomal regions in 3D genomes. TAD boundaries frequently coincide with genome breaks while boundary deletion is under negative selection, suggesting that TADs may facilitate genome rearrangements and evolution. We show that genes co-localize by evolutionary age in humans and mice, resulting in TADs having different proportions of younger and older genes. We observe a major transition in the age co-localization patterns between the genes born during vertebrate whole-genome duplications (WGDs) or before and those born afterward. We also find that genes recently duplicated in primates and rodents are more frequently essential when they are located in old-enriched TADs and interact with genes that last duplicated during the WGD. Therefore, the evolutionary relevance of recent genes may increase when located in TADs with established regulatory networks. Our data suggest that TADs could play a role in organizing ancestral functions and evolutionary novelty.
Collapse
Affiliation(s)
- Caelinn James
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK; Scotland's Rural College (SRUC), The Roslin Institute Building, Easter Bush, Midlothian, UK
| | - Marco Trevisan-Herraz
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - David Juan
- Institut de Biologia Evolutiva, Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain; Systems Biology Department, Spanish National Centre for Biotechnology (CNB-CSIC), Madrid, Spain
| | - Daniel Rico
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK; Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), CSIC-Universidad de Sevilla-Universidad Pablo de Olavide-Junta de Andalucía, Seville, Spain.
| |
Collapse
|
11
|
Pletenev IA, Bazarevich M, Zagirova DR, Kononkova AD, Cherkasov AV, Efimova OI, Tiukacheva EA, Morozov KV, Ulianov KA, Komkov D, Tvorogova AV, Golimbet VE, Kondratyev NV, Razin SV, Khaitovich P, Ulianov SV, Khrameeva EE. Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome. Nucleic Acids Res 2024:gkae271. [PMID: 38647066 DOI: 10.1093/nar/gkae271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/21/2024] [Accepted: 04/06/2024] [Indexed: 04/25/2024] Open
Abstract
Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.
Collapse
Affiliation(s)
- Ilya A Pletenev
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Maria Bazarevich
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Diana R Zagirova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
- A.A. Kharkevich Institute for Information Transmission Problems, Moscow 127051, Russia
| | - Anna D Kononkova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Alexander V Cherkasov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Olga I Efimova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Eugenia A Tiukacheva
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow 141700, Russia
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- CNRS UMR9018, Institut Gustave Roussy, Villejuif 94805, France
- Koltzov Institute of Developmental Biology, Russian Academy of Sciences, Moscow 119334, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Kirill V Morozov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Kirill A Ulianov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Dmitriy Komkov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Anna V Tvorogova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Vera E Golimbet
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow 115522, Russia
| | - Nikolay V Kondratyev
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow 115522, Russia
| | - Sergey V Razin
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Philipp Khaitovich
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Sergey V Ulianov
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Ekaterina E Khrameeva
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| |
Collapse
|
12
|
Jakubek YA, Ma X, Stilp AM, Yu F, Bacon J, Wong JW, Aguet F, Ardlie K, Arnett D, Barnes K, Bis JC, Blackwell T, Becker LC, Boerwinkle E, Bowler RP, Budoff MJ, Carson AP, Chen J, Cho MH, Coresh J, Cox N, de Vries PS, DeMeo DL, Fardo DW, Fornage M, Guo X, Hall ME, Heard-Costa N, Hidalgo B, Irvin MR, Johnson AD, Kenny EE, Levy D, Li Y, Lima JA, Liu Y, Loos RJF, Machiela MJ, Mathias RA, Mitchell BD, Murabito J, Mychaleckyj JC, North K, Orchard P, Parker SC, Pershad Y, Peyser PA, Pratte KA, Psaty BM, Raffield LM, Redline S, Rich SS, Rotter JI, Shah SJ, Smith JA, Smith AP, Smith A, Taub M, Tiwari HK, Tracy R, Tuftin B, Bick AG, Sankaran VG, Reiner AP, Scheet P, Auer PL. Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.16.24305851. [PMID: 38699360 PMCID: PMC11065036 DOI: 10.1101/2024.04.16.24305851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.
Collapse
|
13
|
Yuan Q, Duren Z. Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data. Nat Biotechnol 2024:10.1038/s41587-024-02182-7. [PMID: 38609714 DOI: 10.1038/s41587-024-02182-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 02/26/2024] [Indexed: 04/14/2024]
Abstract
Existing methods for gene regulatory network (GRN) inference rely on gene expression data alone or on lower resolution bulk data. Despite the recent integration of chromatin accessibility and RNA sequencing data, learning complex mechanisms from limited independent data points still presents a daunting challenge. Here we present LINGER (Lifelong neural network for gene regulation), a machine-learning method to infer GRNs from single-cell paired gene expression and chromatin accessibility data. LINGER incorporates atlas-scale external bulk data across diverse cellular contexts and prior knowledge of transcription factor motifs as a manifold regularization. LINGER achieves a fourfold to sevenfold relative increase in accuracy over existing methods and reveals a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes. Following the GRN inference from reference single-cell multiome data, LINGER enables the estimation of transcription factor activity solely from bulk or single-cell gene expression data, leveraging the abundance of available gene expression data to identify driver regulators from case-control studies.
Collapse
Affiliation(s)
- Qiuyue Yuan
- Center for Human Genetics, Department of Genetics and Biochemistry, Clemson University, Greenwood, SC, USA
| | - Zhana Duren
- Center for Human Genetics, Department of Genetics and Biochemistry, Clemson University, Greenwood, SC, USA.
| |
Collapse
|
14
|
Abnizova I, Stapel C, Boekhorst RT, Lee JTH, Hemberg M. Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation. BMC Biol 2024; 22:78. [PMID: 38600550 PMCID: PMC11005181 DOI: 10.1186/s12915-024-01869-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 03/14/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND Regulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging. RESULTS Here we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes. We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters. CONCLUSION Based on these associations of (linearly) distal genes' transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.
Collapse
Affiliation(s)
- Irina Abnizova
- Epigenetics Programme, Babraham Institute, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Carine Stapel
- Epigenetics Programme, Babraham Institute, Cambridge, UK
| | | | | | - Martin Hemberg
- Wellcome Sanger Institute, Hinxton, UK.
- The Gene Lay Institute of Immunology and Inflammation Brigham & Women's Hospital and Harvard Medical School, Boston, USA.
| |
Collapse
|
15
|
Mitra S, Malik R, Wong W, Rahman A, Hartemink AJ, Pritykin Y, Dey KK, Leslie CS. Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis. Nat Genet 2024; 56:627-636. [PMID: 38514783 PMCID: PMC11018525 DOI: 10.1038/s41588-024-01689-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 02/14/2024] [Indexed: 03/23/2024]
Abstract
We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.
Collapse
Affiliation(s)
- Sneha Mitra
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | | | - Wilfred Wong
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York City, NY, USA
| | - Afsana Rahman
- Hunter College, City University of New York, New York City, NY, USA
| | - Alexander J Hartemink
- Department of Computer Science, Duke University, Durham, NC, USA
- Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Yuri Pritykin
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Kushal K Dey
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
| | - Christina S Leslie
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
| |
Collapse
|
16
|
Sakaue S, Weinand K, Isaac S, Dey KK, Jagadeesh K, Kanai M, Watts GFM, Zhu Z, Brenner MB, McDavid A, Donlin LT, Wei K, Price AL, Raychaudhuri S. Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles. Nat Genet 2024; 56:615-626. [PMID: 38594305 DOI: 10.1038/s41588-024-01682-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/07/2024] [Indexed: 04/11/2024]
Abstract
Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.
Collapse
Affiliation(s)
- Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kathryn Weinand
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Shakson Isaac
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kushal K Dey
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Karthik Jagadeesh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Gerald F M Watts
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhu Zhu
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew McDavid
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
17
|
Serra F, Nieto-Aliseda A, Fanlo-Escudero L, Rovirosa L, Cabrera-Pasadas M, Lazarenkov A, Urmeneta B, Alcalde-Merino A, Nola EM, Okorokov AL, Fraser P, Graupera M, Castillo SD, Sardina JL, Valencia A, Javierre BM. p53 rapidly restructures 3D chromatin organization to trigger a transcriptional response. Nat Commun 2024; 15:2821. [PMID: 38561401 PMCID: PMC10984980 DOI: 10.1038/s41467-024-46666-1] [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: 06/15/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Activation of the p53 tumor suppressor triggers a transcriptional program to control cellular response to stress. However, the molecular mechanisms by which p53 controls gene transcription are not completely understood. Here, we uncover the critical role of spatio-temporal genome architecture in this process. We demonstrate that p53 drives direct and indirect changes in genome compartments, topologically associating domains, and DNA loops prior to one hour of its activation, which escort the p53 transcriptional program. Focusing on p53-bound enhancers, we report 340 genes directly regulated by p53 over a median distance of 116 kb, with 74% of these genes not previously identified. Finally, we showcase that p53 controls transcription of distal genes through newly formed and pre-existing enhancer-promoter loops in a cohesin dependent manner. Collectively, our findings demonstrate a previously unappreciated architectural role of p53 as regulator at distinct topological layers and provide a reliable set of new p53 direct target genes that may help designs of cancer therapies.
Collapse
Affiliation(s)
- François Serra
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | | | | | - Mónica Cabrera-Pasadas
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | | | - Blanca Urmeneta
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | | | - Emanuele M Nola
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Andrei L Okorokov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Mariona Graupera
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
- CIBERONC, Instituto de Salud Carlos III, Madrid, Spain
| | | | - Jose L Sardina
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Biola M Javierre
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain.
- Institute for Health Science Research Germans Trias i Pujol, Barcelona, Spain.
| |
Collapse
|
18
|
Liu R, Xu R, Yan S, Li P, Jia C, Sun H, Sheng K, Wang Y, Zhang Q, Guo J, Xin X, Li X, Guo D. Hi-C, a chromatin 3D structure technique advancing the functional genomics of immune cells. Front Genet 2024; 15:1377238. [PMID: 38586584 PMCID: PMC10995239 DOI: 10.3389/fgene.2024.1377238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 03/13/2024] [Indexed: 04/09/2024] Open
Abstract
The functional performance of immune cells relies on a complex transcriptional regulatory network. The three-dimensional structure of chromatin can affect chromatin status and gene expression patterns, and plays an important regulatory role in gene transcription. Currently available techniques for studying chromatin spatial structure include chromatin conformation capture techniques and their derivatives, chromatin accessibility sequencing techniques, and others. Additionally, the recently emerged deep learning technology can be utilized as a tool to enhance the analysis of data. In this review, we elucidate the definition and significance of the three-dimensional chromatin structure, summarize the technologies available for studying it, and describe the research progress on the chromatin spatial structure of dendritic cells, macrophages, T cells, B cells, and neutrophils.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Dianhao Guo
- School of Clinical and Basic Medical Sciences, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| |
Collapse
|
19
|
Lin Y, Li J, Gu Y, Jin L, Bai J, Zhang J, Wang Y, Liu P, Long K, He M, Li D, Liu C, Han Z, Zhang Y, Li X, Zeng B, Lu L, Kong F, Sun Y, Fan Y, Wang X, Wang T, Jiang A, Ma J, Shen L, Zhu L, Jiang Y, Tang G, Fan X, Liu Q, Li H, Wang J, Chen L, Ge L, Li X, Tang Q, Li M. Haplotype-resolved 3D chromatin architecture of the hybrid pig. Genome Res 2024; 34:310-325. [PMID: 38479837 PMCID: PMC10984390 DOI: 10.1101/gr.278101.123] [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: 05/16/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
In diploid mammals, allele-specific three-dimensional (3D) genome architecture may lead to imbalanced gene expression. Through ultradeep in situ Hi-C sequencing of three representative somatic tissues (liver, skeletal muscle, and brain) from hybrid pigs generated by reciprocal crosses of phenotypically and physiologically divergent Berkshire and Tibetan pigs, we uncover extensive chromatin reorganization between homologous chromosomes across multiple scales. Haplotype-based interrogation of multi-omic data revealed the tissue dependence of 3D chromatin conformation, suggesting that parent-of-origin-specific conformation may drive gene imprinting. We quantify the effects of genetic variations and histone modifications on allelic differences of long-range promoter-enhancer contacts, which likely contribute to the phenotypic differences between the parental pig breeds. We also observe the fine structure of somatically paired homologous chromosomes in the pig genome, which has a functional implication genome-wide. This work illustrates how allele-specific chromatin architecture facilitates concomitant shifts in allele-biased gene expression, as well as the possible consequential phenotypic changes in mammals.
Collapse
Affiliation(s)
- Yu Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jing Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
| | - Yiren Gu
- College of Animal and Veterinary Sciences, Southwest Minzu University, Chengdu 610041, China
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jingyi Bai
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yujie Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Pengliang Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Keren Long
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Mengnan He
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Diyan Li
- School of Pharmacy, Chengdu University, Chengdu 610106, China
| | - Can Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Ziyin Han
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yu Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaokai Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Bo Zeng
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Lu Lu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Fanli Kong
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Ying Sun
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
- Institute of Geriatric Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yongliang Fan
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xun Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Tao Wang
- School of Pharmacy, Chengdu University, Chengdu 610106, China
| | - An'an Jiang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jideng Ma
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Linyuan Shen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Li Zhu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yanzhi Jiang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Guoqing Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaolan Fan
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Qingyou Liu
- Animal Molecular Design and Precise Breeding Key Laboratory of Guangdong Province, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Hua Li
- Animal Molecular Design and Precise Breeding Key Laboratory of Guangdong Province, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Jinyong Wang
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Li Chen
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Liangpeng Ge
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Xuewei Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Qianzi Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
| |
Collapse
|
20
|
Balasubramanian D, Borges Pinto P, Grasso A, Vincent S, Tarayre H, Lajoignie D, Ghavi-Helm Y. Enhancer-promoter interactions can form independently of genomic distance and be functional across TAD boundaries. Nucleic Acids Res 2024; 52:1702-1719. [PMID: 38084924 PMCID: PMC10899756 DOI: 10.1093/nar/gkad1183] [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: 04/25/2023] [Revised: 11/21/2023] [Accepted: 11/29/2023] [Indexed: 02/29/2024] Open
Abstract
Topologically Associating Domains (TADs) have been suggested to facilitate and constrain enhancer-promoter interactions. However, the role of TAD boundaries in effectively restricting these interactions remains unclear. Here, we show that a significant proportion of enhancer-promoter interactions are established across TAD boundaries in Drosophila embryos, but that developmental genes are strikingly enriched in intra- but not inter-TAD interactions. We pursued this observation using the twist locus, a master regulator of mesoderm development, and systematically relocated one of its enhancers to various genomic locations. While this developmental gene can establish inter-TAD interactions with its enhancer, the functionality of these interactions remains limited, highlighting the existence of topological constraints. Furthermore, contrary to intra-TAD interactions, the formation of inter-TAD enhancer-promoter interactions is not solely driven by genomic distance, with distal interactions sometimes favored over proximal ones. These observations suggest that other general mechanisms must exist to establish and maintain specific enhancer-promoter interactions across large distances.
Collapse
Affiliation(s)
- Deevitha Balasubramanian
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
- Indian Institute of Science Education and Research (IISER) Tirupati; Tirupati 517507 Andhra Pradesh, India
| | - Pedro Borges Pinto
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| | - Alexia Grasso
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| | - Séverine Vincent
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| | - Hélène Tarayre
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| | - Damien Lajoignie
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| | - Yad Ghavi-Helm
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Centre National de la Recherche Scientifique UMR5242, Université Claude Bernard-Lyon 1; 69364 Lyon, France
| |
Collapse
|
21
|
Fazel-Najafabadi M, Looger LL, Rallabandi HR, Nath SK. A Multilayered Post-Genome-Wide Association Study Analysis Pipeline Defines Functional Variants and Target Genes for Systemic Lupus Erythematosus. Arthritis Rheumatol 2024. [PMID: 38369936 DOI: 10.1002/art.42829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/31/2024] [Accepted: 02/14/2024] [Indexed: 02/20/2024]
Abstract
OBJECTIVE Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWASs) 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-expression quantitative trait loci) with promoter capture high-throughput capture chromatin conformation (PCHi-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, quantitative polymerase chain reaction, and Western blot. RESULTS Anchoring on 452 index SNPs, we selected 9,931 high linkage disequilibrium (r2 > 0.8) SNPs and defined 182 independent non-human leukocyte antigen (HLA) SLE loci. The 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 reference SNP identifier 57668933 (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 using multidimensional 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.
Collapse
|
22
|
Zhang Z, Wang S, Jiang L, Wei J, Lu C, Li S, Diao Y, Fang Z, He S, Tan T, Yang Y, Zou K, Shi J, Lin J, Chen L, Bao C, Fei J, Fang H. Priority index for critical Covid-19 identifies clinically actionable targets and drugs. Commun Biol 2024; 7:189. [PMID: 38366110 PMCID: PMC10873402 DOI: 10.1038/s42003-024-05897-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 02/07/2024] [Indexed: 02/18/2024] Open
Abstract
While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.
Collapse
Affiliation(s)
- Zhiqiang Zhang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Shan Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Lulu Jiang
- Translational Health Sciences, University of Bristol, Bristol, BS1 3NY, UK
| | - Jianwen Wei
- Network and Information Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Chang Lu
- MRC London Institute of Medical Sciences, Imperial College London, London, W12 0HS, UK
| | - Shengli Li
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620, China
| | - Yizhu Diao
- College of Finance and Statistics, Hunan University, Changsha, 410079, Hunan, China
| | - Zhongcheng Fang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Shuo He
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Tingting Tan
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yisheng Yang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Kexin Zou
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jiantao Shi
- Key Laboratory of RNA Science and Engineering, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, 200031, China
| | - James Lin
- Network and Information Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Liye Chen
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, OX3 7LD, UK.
| | - Chaohui Bao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Department of General Surgery, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, 200020, China.
| | - Jian Fei
- Department of General Surgery, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, 200020, China.
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Hai Fang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| |
Collapse
|
23
|
Liu S, Zhong H, Zhu J, Wu Y, Deng Y, Wu L. Regulome-wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk. Int J Cancer 2024; 154:670-678. [PMID: 37850323 PMCID: PMC10842605 DOI: 10.1002/ijc.34761] [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: 05/18/2023] [Revised: 09/04/2023] [Accepted: 09/21/2023] [Indexed: 10/19/2023]
Abstract
Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.
Collapse
Affiliation(s)
- Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Yong Wu
- Division of Cancer Research and Training, Department of Internal Medicine, Charles Drew University of Medicine and Science, David Geffen School of Medicine at UCLA
| | - Youping Deng
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| |
Collapse
|
24
|
Baptista A, Brière G, Baudot A. Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond. BMC Bioinformatics 2024; 25:70. [PMID: 38355439 PMCID: PMC10865648 DOI: 10.1186/s12859-024-05683-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: 10/18/2023] [Accepted: 01/29/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural way to integrate diverse and multi-scale data sources into a common framework. Recently, we developed MultiXrank, a Random Walk with Restart algorithm able to explore such multilayer networks. MultiXrank outputs scores reflecting the proximity between an initial set of seed node(s) and all the other nodes in the multilayer network. We illustrate here the versatility of bioinformatics tasks that can be performed using MultiXrank. RESULTS We first show that MultiXrank can be used to prioritise genes and drugs of interest by exploring multilayer networks containing interactions between genes, drugs, and diseases. In a second study, we illustrate how MultiXrank scores can also be used in a supervised strategy to train a binary classifier to predict gene-disease associations. The classifier performance are validated using outdated and novel gene-disease association for training and evaluation, respectively. Finally, we show that MultiXrank scores can be used to compute diffusion profiles and use them as disease signatures. We computed the diffusion profiles of more than 100 immune diseases using a multilayer network that includes cell-type specific genomic information. The clustering of the immune disease diffusion profiles reveals shared shared phenotypic characteristics. CONCLUSION Overall, we illustrate here diverse applications of MultiXrank to showcase its versatility. We expect that this can lead to further and broader bioinformatics applications.
Collapse
Affiliation(s)
- Anthony Baptista
- School of Mathematical Sciences, Queen Mary University of London, London, UK.
- The Alan Turing Institute, London, UK.
| | | | - Anaïs Baudot
- INSERM, MMG, Turing Center for Living Systems, Aix-Marseille Univ, Marseille, France.
- Barcelona Supercomputing Center, Barcelona, Spain.
| |
Collapse
|
25
|
Alda-Catalinas C, Ibarra-Soria X, Flouri C, Gordillo JE, Cousminer D, Hutchinson A, Sun B, Pembroke W, Ullrich S, Krejci A, Cortes A, Acevedo A, Malla S, Fishwick C, Drewes G, Rapiteanu R. Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens. Genome Biol 2024; 25:42. [PMID: 38308274 PMCID: PMC10835965 DOI: 10.1186/s13059-024-03176-z] [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: 06/18/2023] [Accepted: 01/18/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND Drug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions. RESULTS To identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci. CONCLUSIONS We describe "primary T cell crisprQTL" - a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Bin Sun
- Genomic Sciences, GSK, Stevenage, UK
| | | | | | | | | | | | | | | | - Gerard Drewes
- Genomic Sciences, GSK, Stevenage, UK
- Genomic Sciences, GSK, Collegeville, PA, USA
| | | |
Collapse
|
26
|
Breen C, Papale LA, Clark LR, Bergmann PE, Madrid A, Asthana S, Johnson SC, Keleş S, Alisch RS, Hogan KJ. Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in late-onset dementia due to Alzheimer's disease. Alzheimers Dement 2024; 20:1050-1062. [PMID: 37856321 PMCID: PMC10916976 DOI: 10.1002/alz.13514] [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: 06/23/2023] [Revised: 08/17/2023] [Accepted: 09/25/2023] [Indexed: 10/21/2023]
Abstract
INTRODUCTION DNA microarray-based studies report differentially methylated positions (DMPs) in blood between late-onset dementia due to Alzheimer's disease (AD) and cognitively unimpaired individuals, but interrogate < 4% of the genome. METHODS We used whole genome methylation sequencing (WGMS) to quantify DNA methylation levels at 25,409,826 CpG loci in 281 blood samples from 108 AD and 173 cognitively unimpaired individuals. RESULTS WGMS identified 28,038 DMPs throughout the human methylome, including 2707 differentially methylated genes (e.g., SORCS3, GABA, and PICALM) encoding proteins in biological pathways relevant to AD such as synaptic membrane, cation channel complex, and glutamatergic synapse. One hundred seventy-three differentially methylated blood-specific enhancers interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD. DISCUSSION WGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without AD. HIGHLIGHTS Whole genome DNA methylation levels were quantified in blood from persons with and without Alzheimer's disease (AD). Twenty-eight thousand thirty-eight differentially methylated positions (DMPs) were identified. Two thousand seven hundred seven genes comprise DMPs. Forty-eight of 75 independent genetic risk loci for AD have DMPs. One thousand five hundred sixty-eight blood-specific enhancers comprise DMPs, 173 of which interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.
Collapse
Affiliation(s)
- Coleman Breen
- Department of StatisticsUniversity of Wisconsin, Medical Sciences CenterMadisonWisconsinUSA
| | - Ligia A. Papale
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Lindsay R. Clark
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Phillip E. Bergmann
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Andy Madrid
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sanjay Asthana
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sündüz Keleş
- Department of StatisticsUniversity of Wisconsin, Medical Sciences CenterMadisonWisconsinUSA
- Department of Biostatistics and Medical InformaticsUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Reid S. Alisch
- Department of Neurological SurgeryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Kirk J. Hogan
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of AnesthesiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| |
Collapse
|
27
|
Yu J, Leng J, Hou Z, Sun D, Wu LY. Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis. Brief Bioinform 2024; 25:bbae093. [PMID: 38493346 PMCID: PMC10944575 DOI: 10.1093/bib/bbae093] [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: 09/21/2023] [Revised: 12/22/2023] [Accepted: 02/20/2024] [Indexed: 03/18/2024] Open
Abstract
Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties. Here, we proposed a novel network diffusion-based computational method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). SCARP formulates the Network Refinement diffusion method under the graph theory framework to aggregate information from different network orders, effectively compensating for missing signals in the scATAC-seq data. By incorporating distance information between adjacent peaks on the genome, SCARP also contributes to depicting the co-accessibility of peaks. These two innovations empower SCARP to obtain lower-dimensional representations for both cells and peaks more effectively. We have demonstrated through sufficient experiments that SCARP facilitated superior analyses of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance, enabling better elucidation of cell heterogeneity and the discovery of new biologically significant cell subpopulations. Additionally, SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation. Consequently, SCARP identified genes that were involved in key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to diseases and predicted reliable cis-regulatory interactions. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data.
Collapse
Affiliation(s)
- Jiating Yu
- School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China
- IAM, MADIS, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiacheng Leng
- IAM, MADIS, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Zhejiang Lab, Hangzhou 311121, China
| | - Zhichao Hou
- IAM, MADIS, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Duanchen Sun
- School of Mathematics, Shandong University, Jinan 250100, China
| | - Ling-Yun Wu
- IAM, MADIS, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
28
|
Lin S, Wu S, Zhao W, Fang Z, Kang H, Liu X, Pan S, Yu F, Bao Y, Jia P. TargetGene: a comprehensive database of cell-type-specific target genes for genetic variants. Nucleic Acids Res 2024; 52:D1072-D1081. [PMID: 37870478 PMCID: PMC10767789 DOI: 10.1093/nar/gkad901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/24/2023] Open
Abstract
Annotating genetic variants to their target genes is of great importance in unraveling the causal variants and genetic mechanisms that underlie complex diseases. However, disease-associated genetic variants are often located in non-coding regions and manifest context-specific effects, making it challenging to accurately identify the target genes and regulatory mechanisms. Here, we present TargetGene (https://ngdc.cncb.ac.cn/targetgene/), a comprehensive database reporting target genes for human genetic variants from various aspects. Specifically, we collected a comprehensive catalog of multi-omics data at the single-cell and bulk levels and from various human tissues, cell types and developmental stages. To facilitate the identification of Single Nucleotide Polymorphism (SNP)-to-gene connections, we have implemented multiple analytical tools based on chromatin co-accessibility, 3D interaction, enhancer activities and quantitative trait loci, among others. We applied the pipeline to evaluate variants from nearly 1300 Genome-wide association studies (GWAS) and assembled a comprehensive atlas of multiscale regulation of genetic variants. TargetGene is equipped with user-friendly web interfaces that enable intuitive searching, navigation and browsing through the results. Overall, TargetGene provides a unique resource to empower researchers to study the regulatory mechanisms of genetic variants in complex human traits.
Collapse
Affiliation(s)
- Shiqi Lin
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Song Wu
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Wei Zhao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Zhanjie Fang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongen Kang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fudong Yu
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China
| | - Yiming Bao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
29
|
Fok ET, Moorlag SJCFM, Negishi Y, Groh LA, Dos Santos JC, Gräwe C, Monge VV, Craenmehr DDD, van Roosmalen M, da Cunha Jolvino DP, Migliorini LB, Neto AS, Severino P, Vermeulen M, Joosten LAB, Netea MG, Fanucchi S, Mhlanga MM. A chromatin-regulated biphasic circuit coordinates IL-1β-mediated inflammation. Nat Genet 2024; 56:85-99. [PMID: 38092881 DOI: 10.1038/s41588-023-01598-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 10/26/2023] [Indexed: 12/23/2023]
Abstract
Inflammation is characterized by a biphasic cycle consisting initially of a proinflammatory phase that is subsequently resolved by anti-inflammatory processes. Interleukin-1β (IL-1β) is a master regulator of proinflammation and is encoded within the same topologically associating domain (TAD) as IL-37, which is an anti-inflammatory cytokine that opposes the function of IL-1β. Within this TAD, we identified a long noncoding RNA called AMANZI, which negatively regulates IL-1β expression and trained immunity through the induction of IL37 transcription. We found that the activation of IL37 occurs through the formation of a dynamic long-range chromatin contact that leads to the temporal delay of anti-inflammatory responses. The common variant rs16944 present in AMANZI augments this regulatory circuit, predisposing individuals to enhanced proinflammation or immunosuppression. Our work illuminates a chromatin-mediated biphasic circuit coordinating expression of IL-1β and IL-37, thereby regulating two functionally opposed states of inflammation from within a single TAD.
Collapse
Affiliation(s)
- Ezio T Fok
- Department of Cell Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, the Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
- Lemba Therapeutics, Nijmegen, the Netherlands
| | - Simone J C F M Moorlag
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Yutaka Negishi
- Department of Cell Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, the Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Laszlo A Groh
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jéssica Cristina Dos Santos
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Cathrin Gräwe
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University, Nijmegen, the Netherlands
| | | | | | | | - David Pablo da Cunha Jolvino
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, Brazil
- Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Victoria, Australia
| | - Letícia Busato Migliorini
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Ary Serpa Neto
- Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Patricia Severino
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University, Nijmegen, the Netherlands
- Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Leo A B Joosten
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Musa M Mhlanga
- Department of Cell Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, the Netherlands.
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.
| |
Collapse
|
30
|
Xu LL, Zhou XJ, Zhang H. An Update on the Genetics of IgA Nephropathy. J Clin Med 2023; 13:123. [PMID: 38202130 PMCID: PMC10780034 DOI: 10.3390/jcm13010123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/15/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
Immunoglobulin A (IgA) nephropathy (IgAN), the most common form of glomerulonephritis, is one of the leading causes of end-stage kidney disease (ESKD). It is widely believed that genetic factors play a significant role in the development of IgAN. Previous studies of IgAN have provided important insights to unravel the genetic architecture of IgAN and its potential pathogenic mechanisms. The genome-wide association studies (GWASs) together have identified over 30 risk loci for IgAN, which emphasizes the importance of IgA production and regulation in the pathogenesis of IgAN. Follow-up fine-mapping studies help to elucidate the candidate causal variant and the potential pathogenic molecular pathway and provide new potential therapeutic targets. With the rapid development of next-generation sequencing technologies, linkage studies based on whole-genome sequencing (WGS)/whole-exome sequencing (WES) also identify rare variants associated with IgAN, accounting for some of the missing heritability. The complexity of pathogenesis and phenotypic variability may be better understood by integrating genetics, epigenetics, and environment. We have compiled a review summarizing the latest advancements in genetic studies on IgAN. We similarly summarized relevant studies examining the involvement of epigenetics in the pathogenesis of IgAN. Future directions and challenges in this field are also proposed.
Collapse
Affiliation(s)
- Lin-Lin Xu
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| |
Collapse
|
31
|
Chen YH, van Zon S, Adams A, Schmidt-Arras D, Laurence ADJ, Uhlig HH. The Human GP130 Cytokine Receptor and Its Expression-an Atlas and Functional Taxonomy of Genetic Variants. J Clin Immunol 2023; 44:30. [PMID: 38133879 PMCID: PMC10746620 DOI: 10.1007/s10875-023-01603-7] [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: 03/21/2023] [Accepted: 10/30/2023] [Indexed: 12/23/2023]
Abstract
Genetic variants in IL6ST encoding the shared cytokine receptor for the IL-6 cytokine family GP130 have been associated with a diverse number of clinical phenotypes and disorders. We provide a molecular classification for 59 reported rare IL6ST pathogenic or likely pathogenic variants and additional polymorphisms. Based on loss- or gain-of-function, cytokine selectivity, mono- and biallelic associations, and variable cellular mosaicism, we grade six classes of IL6ST variants and explore the potential for additional variants. We classify variants according to the American College of Medical Genetics and Genomics criteria. Loss-of-function variants with (i) biallelic complete loss of GP130 function that presents with extended Stüve-Wiedemann Syndrome; (ii) autosomal recessive hyper-IgE syndrome (HIES) caused by biallelic; and (iii) autosomal dominant HIES caused by monoallelic IL6ST variants both causing selective IL-6 and IL-11 cytokine loss-of-function defects; (iv) a biallelic cytokine-specific variant that exclusively impairs IL-11 signaling, associated with craniosynostosis and tooth abnormalities; (v) somatic monoallelic mosaic constitutively active gain-of-function variants in hepatocytes that present with inflammatory hepatocellular adenoma; and (vi) mosaic constitutively active gain-of-function variants in hematopoietic and non-hematopoietic cells that are associated with an immune dysregulation syndrome. In addition to Mendelian IL6ST coding variants, there are common non-coding cis-acting variants that modify gene expression, which are associated with an increased risk of complex immune-mediated disorders and trans-acting variants that affect GP130 protein function. Our taxonomy highlights IL6ST as a gene with particularly strong functional and phenotypic diversity due to the combinatorial biology of the IL-6 cytokine family and predicts additional genotype-phenotype associations.
Collapse
Affiliation(s)
- Yin-Huai Chen
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Sarah van Zon
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Alex Adams
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Dirk Schmidt-Arras
- Department of Biosciences and Medical Biology, University of Salzburg, Salzburg, Austria
| | | | - Holm H Uhlig
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK.
- Biomedical Research Centre, University of Oxford, Oxford, UK.
- Department of Paediatrics, University of Oxford, Oxford, UK.
| |
Collapse
|
32
|
Tutino M, Hankinson J, Murray C, Lowe L, Kerry G, Rattray M, Custovic A, Johnston SL, Shi C, Orozco G, Eyre S, Martin P, Simpson A, Curtin JA. Identification of differences in CD4 + T-cell gene expression between people with asthma and healthy controls. Sci Rep 2023; 13:22796. [PMID: 38129444 PMCID: PMC10739740 DOI: 10.1038/s41598-023-49135-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4+ T-cells play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4+ T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data, we identified PTPRC, a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).
Collapse
Affiliation(s)
- Mauro Tutino
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK.
| | - Jenny Hankinson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - Clare Murray
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Lesley Lowe
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Gina Kerry
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Magnus Rattray
- Division of Informatics, Imaging and Data Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Adnan Custovic
- National Heart and Lung Institute, Asthma UK Centre in Allergic Mechanisms of Asthma, Imperial College London, London, UK
| | - Sebastian L Johnston
- National Heart and Lung Institute, Asthma UK Centre in Allergic Mechanisms of Asthma, Imperial College London, London, UK
| | - Chenfu Shi
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Gisela Orozco
- Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Stephen Eyre
- Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Paul Martin
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- The Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Angela Simpson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - John A Curtin
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| |
Collapse
|
33
|
Josserand M, Rubanova N, Stefanutti M, Roumeliotis S, Espenel M, Marshall OJ, Servant N, Gervais L, Bardin AJ. Chromatin state transitions in the Drosophila intestinal lineage identify principles of cell-type specification. Dev Cell 2023; 58:3048-3063.e6. [PMID: 38056452 DOI: 10.1016/j.devcel.2023.11.005] [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: 02/06/2023] [Revised: 07/20/2023] [Accepted: 11/10/2023] [Indexed: 12/08/2023]
Abstract
Tissue homeostasis relies on rewiring of stem cell transcriptional programs into those of differentiated cells. Here, we investigate changes in chromatin occurring in a bipotent adult stem cells. Combining mapping of chromatin-associated factors with statistical modeling, we identify genome-wide transitions during differentiation in the adult Drosophila intestinal stem cell (ISC) lineage. Active, stem-cell-enriched genes transition to a repressive heterochromatin protein-1-enriched state more prominently in enteroendocrine cells (EEs) than in enterocytes (ECs), in which the histone H1-enriched Black state is preeminent. In contrast, terminal differentiation genes associated with metabolic functions follow a common path from a repressive, primed, histone H1-enriched Black state in ISCs to active chromatin states in EE and EC cells. Furthermore, we find that lineage priming has an important function in adult ISCs, and we identify histone H1 as a mediator of this process. These data define underlying principles of chromatin changes during adult multipotent stem cell differentiation.
Collapse
Affiliation(s)
- Manon Josserand
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France
| | - Natalia Rubanova
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France; Institut Curie Bioinformatics Core Facility, PSL Research University, INSERM U900, MINES ParisTech, Paris 75005, France
| | - Marine Stefanutti
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France
| | - Spyridon Roumeliotis
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France
| | - Marion Espenel
- Institut Curie, PSL University, ICGex Next-Generation Sequencing Platform, 75005 Paris, France
| | - Owen J Marshall
- Menzies Institute for Medical Research, University of Tasmania, Hobart 7000, Australia
| | - Nicolas Servant
- Institut Curie Bioinformatics Core Facility, PSL Research University, INSERM U900, MINES ParisTech, Paris 75005, France
| | - Louis Gervais
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France.
| | - Allison J Bardin
- Institut Curie, PSL Research University, Sorbonne University, CNRS UMR 3215, INSERM U934, Genetics and Developmental Biology Department, 75248 Paris, France.
| |
Collapse
|
34
|
Armaos A, Serra F, Núñez-Carpintero I, Seo JH, Baca SC, Gustincich S, Valencia A, Freedman ML, Cirillo D, Giambartolomei C, Tartaglia GG. The PENGUIN approach to reconstruct protein interactions at enhancer-promoter regions and its application to prostate cancer. Nat Commun 2023; 14:8084. [PMID: 38057321 PMCID: PMC10700545 DOI: 10.1038/s41467-023-43767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 11/18/2023] [Indexed: 12/08/2023] Open
Abstract
We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ .
Collapse
Affiliation(s)
- Alexandros Armaos
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy
| | - François Serra
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain
- Josep Carreras Leukaemia Research Institute, Ctra de Can Ruti, Camí de les Escoles, 08916, Badalona, Barcelona, Spain
| | | | - Ji-Heui Seo
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
| | - Sylvan C Baca
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
| | - Stefano Gustincich
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain
- ICREA - Institució Catalana de Recerca I Estudis Avançats, Pg. Lluís Companys 23, 08010, Barcelona, Spain
| | - Matthew L Freedman
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
- Eli and Edythe L. Broad Institute, 415 Main St., Cambridge, MA, 02142, USA
| | - Davide Cirillo
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain.
| | - Claudia Giambartolomei
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy.
- Health Data Science Centre, Human Technopole, Milan, Italy.
| | - Gian Gaetano Tartaglia
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy.
- ICREA - Institució Catalana de Recerca I Estudis Avançats, Pg. Lluís Companys 23, 08010, Barcelona, Spain.
- Istituto Italiano di Tecnologia, CNLS@Sapienza, Viale Regina Elena, 00161, Rome, Italy.
| |
Collapse
|
35
|
Wang M, He B, Hao Y, Srinivasan D, Shrinet J, Fraser P. Cellular reprogramming is driven by widespread rewiring of promoter-enhancer interactions. BMC Biol 2023; 21:264. [PMID: 37981682 PMCID: PMC10658794 DOI: 10.1186/s12915-023-01766-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 11/09/2023] [Indexed: 11/21/2023] Open
Abstract
BACKGROUND Long-range interactions between promoters and cis-regulatory elements, such as enhancers, play critical roles in gene regulation. However, the role of three-dimensional (3D) chromatin structure in orchestrating changes in transcriptional regulation during direct cell reprogramming is not fully understood. RESULTS Here, we performed integrated analyses of chromosomal architecture, epigenetics, and gene expression using Hi-C, promoter Capture Hi-C (PCHi-C), ChIP-seq, and RNA-seq during trans-differentiation of Pre-B cells into macrophages with a β-estradiol inducible C/EBPαER transgene. Within 1h of β-estradiol induction, C/EBPα translocated from the cytoplasm to the nucleus, binding to thousands of promoters and putative regulatory elements, resulting in the downregulation of Pre-B cell-specific genes and induction of macrophage-specific genes. Hi-C results were remarkably consistent throughout trans-differentiation, revealing only a small number of TAD boundary location changes, and A/B compartment switches despite significant changes in the expression of thousands of genes. PCHi-C revealed widespread changes in promoter-anchored loops with decreased interactions in parallel with decreased gene expression, and new and increased promoter-anchored interactions in parallel with increased expression of macrophage-specific genes. CONCLUSIONS Overall, our data demonstrate that C/EBPα-induced trans-differentiation involves few changes in genome architecture at the level of TADs and A/B compartments, in contrast with widespread reorganization of thousands of promoter-anchored loops in association with changes in gene expression and cell identity.
Collapse
Affiliation(s)
- Miao Wang
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Bing He
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Yueling Hao
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Divyaa Srinivasan
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Jatin Shrinet
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, USA.
| |
Collapse
|
36
|
Wang C, Manders F, Groh L, Oldenkamp R, Logie C. Corticosteroid-induced chromatin loop dynamics at the FKBP5 gene. Ann N Y Acad Sci 2023; 1529:109-119. [PMID: 37796452 DOI: 10.1111/nyas.15064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
FKBP5 is a 115-kb-long glucocorticoid-inducible gene implicated in psychiatric disorders. To investigate the complexities of chromatin interaction frequencies at the FKBP5 topologically associated domain (TAD), we deployed 15 one-to-all chromatin capture viewpoints near gene promoters, enhancers, introns, and CTCF-loop anchors. This revealed a "one-TAD-one-gene" structure encompassing the FKBP5 promoter and its enhancers. The FKBP5 promoter and its two glucocorticoid-stimulated enhancers roam the entire TAD while displaying subtle cell type-specific interactomes. The FKBP5 TAD consists of two nested CTCF loops that are coordinated by one CTCF site in the eighth intron of FKBP5 and another beyond its polyadenylation site, 61 kb further. Loop extension correlates with transcription increases through the intronic CTCF site. This is efficiently compensated for, since the short loop is restored even under high transcription regimes. The boundaries of the FKBP5 TAD consist of divergent CTCF site patterns, harbor multiple smaller genes, and are resilient to glucocorticoid stimulation. Interestingly, both FKBP5 TAD boundaries harbor H3K27me3-marked heterochromatin blocks that may reinforce them. We propose that cis-acting genetic and epigenetic polymorphisms underlying FKBP5 expression variation are likely to reside within a 240-kb region that consists of the FKBP5 TAD, its left sub-TAD, and both its boundaries.
Collapse
Affiliation(s)
- Cheng Wang
- Department of Molecular Biology, Radboud Institute for Molecular Science, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - Freek Manders
- Department of Molecular Biology, Radboud Institute for Molecular Science, Faculty of Science, Radboud University, Nijmegen, The Netherlands
- Gendx, Utrecht, The Netherlands
| | - Laszlo Groh
- Department of Molecular Biology, Radboud Institute for Molecular Science, Faculty of Science, Radboud University, Nijmegen, The Netherlands
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Amsterdam, The Netherlands
| | - Roel Oldenkamp
- Department of Molecular Biology, Radboud Institute for Molecular Science, Faculty of Science, Radboud University, Nijmegen, The Netherlands
- Division of Cell Biology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Colin Logie
- Department of Molecular Biology, Radboud Institute for Molecular Science, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| |
Collapse
|
37
|
Mulet-Lazaro R, Delwel R. From Genotype to Phenotype: How Enhancers Control Gene Expression and Cell Identity in Hematopoiesis. Hemasphere 2023; 7:e969. [PMID: 37953829 PMCID: PMC10635615 DOI: 10.1097/hs9.0000000000000969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 09/11/2023] [Indexed: 11/14/2023] Open
Abstract
Blood comprises a wide array of specialized cells, all of which share the same genetic information and ultimately derive from the same precursor, the hematopoietic stem cell (HSC). This diversity of phenotypes is underpinned by unique transcriptional programs gradually acquired in the process known as hematopoiesis. Spatiotemporal regulation of gene expression depends on many factors, but critical among them are enhancers-sequences of DNA that bind transcription factors and increase transcription of genes under their control. Thus, hematopoiesis involves the activation of specific enhancer repertoires in HSCs and their progeny, driving the expression of sets of genes that collectively determine morphology and function. Disruption of this tightly regulated process can have catastrophic consequences: in hematopoietic malignancies, dysregulation of transcriptional control by enhancers leads to misexpression of oncogenes that ultimately drive transformation. This review attempts to provide a basic understanding of enhancers and their role in transcriptional regulation, with a focus on normal and malignant hematopoiesis. We present examples of enhancers controlling master regulators of hematopoiesis and discuss the main mechanisms leading to enhancer dysregulation in leukemia and lymphoma.
Collapse
Affiliation(s)
- Roger Mulet-Lazaro
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Ruud Delwel
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| |
Collapse
|
38
|
Weinstock JS, Arce MM, Freimer JW, Ota M, Marson A, Battle A, Pritchard JK. Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.17.557749. [PMID: 37745614 PMCID: PMC10516010 DOI: 10.1101/2023.09.17.557749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes in cis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. Mapping trans-regulators based on natural genetic variation, including eQTL mapping, has been challenging due to small effects. Experimental perturbation approaches offer a complementary and powerful approach to mapping trans-regulators. We used CRISPR knockouts of 84 genes in primary CD4+ T cells to perturb an immune cell gene network, targeting both inborn error of immunity (IEI) disease transcription factors (TFs) and background TFs matched in constraint and expression level, but without a known immune disease association. We developed a novel Bayesian structure learning method called Linear Latent Causal Bayes (LLCB) to estimate the gene regulatory network from perturbation data and observed 211 directed edges among the genes which could not be detected in existing CD4+ trans-eQTL data. We used LLCB to characterize the differences between the IEI and background TFs, finding that the gene groups were highly interconnected, but that IEI TFs were much more likely to regulate immune cell specific pathways and immune GWAS genes. We further characterized nine coherent gene programs based on downstream effects of the TFs and linked these modules to regulation of GWAS genes, finding that canonical JAK-STAT family members are regulated by KMT2A, a global epigenetic regulator. These analyses reveal the trans-regulatory cascade from upstream epigenetic regulator to intermediate TFs to downstream effector cytokines and elucidate the logic linking immune GWAS genes to key signaling pathways.
Collapse
Affiliation(s)
- Joshua S. Weinstock
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
- Department of Genetics, Stanford University, Stanford, CA
| | - Maya M. Arce
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA
- Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Jacob W. Freimer
- Department of Genetics, Stanford University, Stanford, CA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA
| | - Mineto Ota
- Department of Genetics, Stanford University, Stanford, CA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA
| | - Alexander Marson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA
- Department of Medicine, University of California, San Francisco, San Francisco, CA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720
- Institute for Human Genetics (IHG), University of California, San Francisco, San Francisco, CA, 94143
- Diabetes Center, University of California, San Francisco, San Francisco, CA, 94143
- Parker Institute for Cancer Immunotherapy, University of California, San Francisco, San Francisco, CA, 94129
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, 94143
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94158
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD
- Department of Computer Science, Johns Hopkins University, Baltimore, MD
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD
| | - Jonathan K. Pritchard
- Department of Genetics, Stanford University, Stanford, CA
- Department of Biology, Stanford University, Stanford, CA
| |
Collapse
|
39
|
Tsai MJ, Jeong S, Yu F, Chen TF, Li PH, Juan HF, Huang JH, Hsu YH. Translating GWAS Findings to Inform Drug Repositioning Strategies for COVID-19 Treatment. RESEARCH SQUARE 2023:rs.3.rs-3443080. [PMID: 37886583 PMCID: PMC10602133 DOI: 10.21203/rs.3.rs-3443080/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: 10/28/2023]
Abstract
We developed a computational framework that integrates Genome-Wide Association Studies (GWAS) and post-GWAS analyses, designed to facilitate drug repurposing for COVID-19 treatment. The comprehensive approach combines transcriptomic-wide associations, polygenic priority scoring, 3D genomics, viral-host protein-protein interactions, and small-molecule docking. Through GWAS, we identified nine druggable host genes associated with COVID-19 severity and SARS-CoV-2 infection, all of which show differential expression in COVID-19 patients. These genes include IFNAR1, IFNAR2, TYK2, IL10RB, CXCR6, CCR9, and OAS1. We performed an extensive molecular docking analysis of these targets using 553 small molecules derived from five therapeutically enriched categories, namely antibacterials, antivirals, antineoplastics, immunosuppressants, and anti-inflammatories. This analysis, which comprised over 20,000 individual docking analyses, enabled the identification of several promising drug candidates. All results are available via the DockCoV2 database (https://dockcov2.org/drugs/). The computational framework ultimately identified nine potential drug candidates: Peginterferon alfa-2b, Interferon alfa-2b, Interferon beta-1b, Ruxolitinib, Dactinomycin, Rolitetracycline, Irinotecan, Vinblastine, and Oritavancin. While its current focus is on COVID-19, our proposed computational framework can be applied more broadly to assist in drug repurposing efforts for a variety of diseases. Overall, this study underscores the potential of human genetic studies and the utility of a computational framework for drug repurposing in the context of COVID-19 treatment, providing a valuable resource for researchers in this field.
Collapse
|
40
|
Kassouf M, Ford S, Blayney J, Higgs D. Understanding fundamental principles of enhancer biology at a model locus: Analysing the structure and function of an enhancer cluster at the α-globin locus. Bioessays 2023; 45:e2300047. [PMID: 37404089 DOI: 10.1002/bies.202300047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/03/2023] [Accepted: 05/05/2023] [Indexed: 07/06/2023]
Abstract
Despite ever-increasing accumulation of genomic data, the fundamental question of how individual genes are switched on during development, lineage-specification and differentiation is not fully answered. It is widely accepted that this involves the interaction between at least three fundamental regulatory elements: enhancers, promoters and insulators. Enhancers contain transcription factor binding sites which are bound by transcription factors (TFs) and co-factors expressed during cell fate decisions and maintain imposed patterns of activation, at least in part, via their epigenetic modification. This information is transferred from enhancers to their cognate promoters often by coming into close physical proximity to form a 'transcriptional hub' containing a high concentration of TFs and co-factors. The mechanisms underlying these stages of transcriptional activation are not fully explained. This review focuses on how enhancers and promoters are activated during differentiation and how multiple enhancers work together to regulate gene expression. We illustrate the currently understood principles of how mammalian enhancers work and how they may be perturbed in enhanceropathies using expression of the α-globin gene cluster during erythropoiesis, as a model.
Collapse
Affiliation(s)
- Mira Kassouf
- Laboratory of Gene Regulation, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Seren Ford
- Laboratory of Gene Regulation, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Joseph Blayney
- Laboratory of Gene Regulation, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Doug Higgs
- Laboratory of Gene Regulation, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| |
Collapse
|
41
|
Signal B, Pérez Suárez TG, Taberlay PC, Woodhouse A. Cellular specificity is key to deciphering epigenetic changes underlying Alzheimer's disease. Neurobiol Dis 2023; 186:106284. [PMID: 37683959 DOI: 10.1016/j.nbd.2023.106284] [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: 05/01/2023] [Revised: 08/23/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023] Open
Abstract
Different cell types in the brain play distinct roles in Alzheimer's disease (AD) progression. Late onset AD (LOAD) is a complex disease, with a large genetic component, but many risk loci fall in non-coding genome regions. Epigenetics implicates the non-coding genome with control of gene expression. The epigenome is highly cell-type specific and dynamically responds to the environment. Therefore, epigenetic mechanisms are well placed to explain genetic and environmental factors that are associated with AD. However, given this cellular specificity, purified cell populations or single cells need to be profiled to avoid effect masking. Here we review the current state of cell-type specific genome-wide profiling in LOAD, covering DNA methylation (CpG, CpH, and hydroxymethylation), histone modifications, and chromatin changes. To date, these data reveal that distinct cell types contribute and react differently to AD progression through epigenetic alterations. This review addresses the current gap in prior bulk-tissue derived work by spotlighting cell-specific changes that govern the complex interplay of cells throughout disease progression and are critical in understanding and developing effective treatments for AD.
Collapse
Affiliation(s)
- Brandon Signal
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia.
| | | | - Phillippa C Taberlay
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia
| | - Adele Woodhouse
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, TAS, Australia
| |
Collapse
|
42
|
Zhang B, Upadhyay R, Hao Y, Samanovic MI, Herati RS, Blair JD, Axelrad J, Mulligan MJ, Littman DR, Satija R. Multimodal single-cell datasets characterize antigen-specific CD8 + T cells across SARS-CoV-2 vaccination and infection. Nat Immunol 2023; 24:1725-1734. [PMID: 37735591 PMCID: PMC10522491 DOI: 10.1038/s41590-023-01608-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/31/2023] [Indexed: 09/23/2023]
Abstract
The immune response to SARS-CoV-2 antigen after infection or vaccination is defined by the durable production of antibodies and T cells. Population-based monitoring typically focuses on antibody titer, but there is a need for improved characterization and quantification of T cell responses. Here, we used multimodal sequencing technologies to perform a longitudinal analysis of circulating human leukocytes collected before and after immunization with the mRNA vaccine BNT162b2. Our data indicated distinct subpopulations of CD8+ T cells, which reliably appeared 28 days after prime vaccination. Using a suite of cross-modality integration tools, we defined their transcriptome, accessible chromatin landscape and immunophenotype, and we identified unique biomarkers within each modality. We further showed that this vaccine-induced population was SARS-CoV-2 antigen-specific and capable of rapid clonal expansion. Moreover, we identified these CD8+ T cell populations in scRNA-seq datasets from COVID-19 patients and found that their relative frequency and differentiation outcomes were predictive of subsequent clinical outcomes.
Collapse
Affiliation(s)
- Bingjie Zhang
- New York Genome Center, New York, NY, USA
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Department of Cell Biology, New York University Grossman School of Medicine, New York, NY, USA
| | - Rabi Upadhyay
- Department of Cell Biology, New York University Grossman School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University Langone Health, New York, NY, USA
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Yuhan Hao
- New York Genome Center, New York, NY, USA
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Marie I Samanovic
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
- New York University Langone Vaccine Center, New York, NY, USA
| | - Ramin S Herati
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
- New York University Langone Vaccine Center, New York, NY, USA
| | - John D Blair
- New York Genome Center, New York, NY, USA
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Jordan Axelrad
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Mark J Mulligan
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
- New York University Langone Vaccine Center, New York, NY, USA
| | - Dan R Littman
- Department of Cell Biology, New York University Grossman School of Medicine, New York, NY, USA.
- Perlmutter Cancer Center, New York University Langone Health, New York, NY, USA.
- Howard Hughes Medical Institute, New York, NY, USA.
| | - Rahul Satija
- New York Genome Center, New York, NY, USA.
- Center for Genomics and Systems Biology, New York University, New York, NY, USA.
| |
Collapse
|
43
|
Malfait J, Wan J, Spicuglia S. Epromoters are new players in the regulatory landscape with potential pleiotropic roles. Bioessays 2023; 45:e2300012. [PMID: 37246247 DOI: 10.1002/bies.202300012] [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: 01/17/2023] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 05/30/2023]
Abstract
Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.
Collapse
Affiliation(s)
- Juliette Malfait
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Jing Wan
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| | - Salvatore Spicuglia
- Aix-Marseille University, Inserm, TAGC, UMR1090, Marseille, France
- Equipe Labélisée Ligue Contre le Cancer, LIGUE, Marseille, France
| |
Collapse
|
44
|
Wei X, Tran D, Diao Y. HiCAR: Analysis of Open Chromatin Associated Long-range Chromatin Interaction Using Low-Input Materials. Curr Protoc 2023; 3:e899. [PMID: 37818863 PMCID: PMC10575683 DOI: 10.1002/cpz1.899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Cis-regulatory elements (cREs) and their long-range interactions are crucial for spatial-temporal gene regulation. While cREs can be characterized as accessible chromatin sequences, comprehensively identifying their spatial interactions remains a challenge. We recently developed a method, HiCAR (Hi-C on Accessible Regulatory DNA), which combines Tn5 transposase and chromatin proximity ligation to analyze open chromatin-anchored interactions in low-input cells. Application of HiCAR in human embryonic stem cells and lymphoblastoid cells reveals high-resolution chromatin contacts with efficiency comparable to in situ Hi-C across various distance ranges. Moreover, HiCAR was successfully applied to 30,000 primary human muscle stem cells, showcasing its potential for analyzing chromatin accessibility and looping in low-input primary cells and clinical samples. Here, we provide a detailed step-by-step protocol to perform the updated HiCAR experiments. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Tn5 Transposase Assembly Basic Protocol 2: HiCAR Library Preparation.
Collapse
Affiliation(s)
- Xiaolin Wei
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Duc Tran
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Yarui Diao
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
- Duke Regeneration Center, Duke University Medical Center, Durham, NC 27710, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
- Department of Orthopaedics Surgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
| |
Collapse
|
45
|
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.
Collapse
|
46
|
Dileep V, Boix CA, Mathys H, Marco A, Welch GM, Meharena HS, Loon A, Jeloka R, Peng Z, Bennett DA, Kellis M, Tsai LH. Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration. Cell 2023; 186:4404-4421.e20. [PMID: 37774679 PMCID: PMC10697236 DOI: 10.1016/j.cell.2023.08.038] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 04/02/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.
Collapse
Affiliation(s)
- Vishnu Dileep
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hansruedi Mathys
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Asaf Marco
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gwyneth M Welch
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hiruy S Meharena
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anjanet Loon
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ritika Jeloka
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| |
Collapse
|
47
|
Xu D, Forbes AN, Cohen S, Palladino A, Karadimitriou T, Khurana E. Recapitulation of patient-specific 3D chromatin conformation using machine learning. CELL REPORTS METHODS 2023; 3:100578. [PMID: 37673071 PMCID: PMC10545938 DOI: 10.1016/j.crmeth.2023.100578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 04/05/2023] [Accepted: 08/10/2023] [Indexed: 09/08/2023]
Abstract
Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.
Collapse
Affiliation(s)
- Duo Xu
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andre Neil Forbes
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Sandra Cohen
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Ann Palladino
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA
| | | | - Ekta Khurana
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
| |
Collapse
|
48
|
Lee L, Yu M, Li X, Zhu C, Zhang Y, Yu H, Chen Z, Mishra S, Ren B, Li Y, Hu M. SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data. Brief Bioinform 2023; 24:bbad315. [PMID: 37649383 PMCID: PMC10516352 DOI: 10.1093/bib/bbad315] [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: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 09/01/2023] Open
Abstract
Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.
Collapse
Affiliation(s)
- Lindsay Lee
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Miao Yu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xiaoqi Li
- Carolina Health Informatics Program, University of North Carolina, Chapel Hill, NC, USA
| | - Chenxu Zhu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- New York Genome Center, New York, NY, USA
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- Westlake University, Hangzhou, Zhejiang, China
| | - Hongyu Yu
- Department of Statistics, University of Wisconsin Madison, Madison, WI, USA
- Department of Biochemistry, University of Wisconsin Madison, Madison, WI, USA
| | - Ziyin Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Shreya Mishra
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- Center for Epigenomics & Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| |
Collapse
|
49
|
Zhang S, Zhang H, Forrest MP, Zhou Y, Sun X, Bagchi VA, Kozlova A, Santos MD, Piguel NH, Dionisio LE, Sanders AR, Pang ZP, He X, Penzes P, Duan J. Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons. CELL GENOMICS 2023; 3:100399. [PMID: 37719141 PMCID: PMC10504676 DOI: 10.1016/j.xgen.2023.100399] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 05/22/2023] [Accepted: 08/07/2023] [Indexed: 09/19/2023]
Abstract
The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.
Collapse
Affiliation(s)
- Siwei Zhang
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| | - Hanwen Zhang
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Marc P. Forrest
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
| | - Yifan Zhou
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Xiaotong Sun
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Vikram A. Bagchi
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
| | - Alena Kozlova
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Marc Dos Santos
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
| | - Nicolas H. Piguel
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
| | - Leonardo E. Dionisio
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
| | - Alan R. Sanders
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| | - Zhiping P. Pang
- Department of Neuroscience and Cell Biology, Child Health Institute of New Jersey, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA
| | - Xin He
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Peter Penzes
- Department of Neuroscience, Northwestern University, Chicago, IL 60611, USA
- Center for Autism and Neurodevelopment, Northwestern University, Chicago, IL 60611, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| |
Collapse
|
50
|
Liu H, Ma Y, Yu J, Chen X, Wang S, Jia Y, Ding N, Jin X, Zhang Y, Xu J, Li X. Insight into the regulatory mechanism of dynamic chromatin 3D interactions during cardiomyocyte differentiation in human. MOLECULAR THERAPY. NUCLEIC ACIDS 2023; 33:629-641. [PMID: 37650118 PMCID: PMC10462852 DOI: 10.1016/j.omtn.2023.07.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 07/28/2023] [Indexed: 09/01/2023]
Abstract
Cardiogenesis is an extremely complicated process involved with DNA regulatory elements, and trans factors regulate gene expression pattern spatiotemporally. Enhancers, as the well-known DNA elements, activate target gene expression by transcription factors (TFs) occupied to organize dynamic three-dimensional (3D) interactions, which when affected or interrupted might cause heart defects or diseases. In this study, we integrated transcriptome, 3D genome, and regulatome to reorganize the global 3D genome in cardiomyogenesis, showing a gradually decreased trend of both chromatin interactions and topological associating domains (TADs) during cardiomyocyte differentiation. And almost all of the chromatin interactions occurred within the same or between adjacent TADs involved with enhancers, indicating that dynamical rewiring of enhancer-related chromatin interactions in the continuous expansive TADs is closely correlated to cardiogenesis. Moreover, we found stage-specific interactions activate stage-specific expression to be involved within corresponding biological functions, and the stage-specific combined regulations of enhancers and binding TFs form connected networks to control stage-specific expression and biological processes, which promote cardiomyocyte differentiation. Finally, we identified markers based on regulatory networks, which might drive cardiac development. This study demonstrates the power of enhancer interactome combined with active TFs to reveal insights into transcriptional regulatory networks during cardiomyogenesis.
Collapse
Affiliation(s)
- Hui Liu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yingying Ma
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Jiaxin Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Xiang Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Shuyuan Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yijie Jia
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Na Ding
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Xiaoyan Jin
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yunpeng Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| |
Collapse
|