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Yang JH, Hansen AS. Enhancer selectivity in space and time: from enhancer-promoter interactions to promoter activation. Nat Rev Mol Cell Biol 2024; 25:574-591. [PMID: 38413840 DOI: 10.1038/s41580-024-00710-6] [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] [Accepted: 01/30/2024] [Indexed: 02/29/2024]
Abstract
The primary regulators of metazoan gene expression are enhancers, originally functionally defined as DNA sequences that can activate transcription at promoters in an orientation-independent and distance-independent manner. Despite being crucial for gene regulation in animals, what mechanisms underlie enhancer selectivity for promoters, and more fundamentally, how enhancers interact with promoters and activate transcription, remain poorly understood. In this Review, we first discuss current models of enhancer-promoter interactions in space and time and how enhancers affect transcription activation. Next, we discuss different mechanisms that mediate enhancer selectivity, including repression, biochemical compatibility and regulation of 3D genome structure. Through 3D polymer simulations, we illustrate how the ability of 3D genome folding mechanisms to mediate enhancer selectivity strongly varies for different enhancer-promoter interaction mechanisms. Finally, we discuss how recent technical advances may provide new insights into mechanisms of enhancer-promoter interactions and how technical biases in methods such as Hi-C and Micro-C and imaging techniques may affect their interpretation.
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Affiliation(s)
- Jin H Yang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, Cambridge, MA, USA
| | - Anders S Hansen
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Koch Institute for Integrative Cancer Research, Cambridge, MA, USA.
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Thoms JAI, Koch F, Raei A, Subramanian S, Wong JH, Vafaee F, Pimanda J. BloodChIP Xtra: an expanded database of comparative genome-wide transcription factor binding and gene-expression profiles in healthy human stem/progenitor subsets and leukemic cells. Nucleic Acids Res 2024; 52:D1131-D1137. [PMID: 37870453 PMCID: PMC10767868 DOI: 10.1093/nar/gkad918] [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: 09/15/2023] [Revised: 10/04/2023] [Accepted: 10/09/2023] [Indexed: 10/24/2023] Open
Abstract
The BloodChIP Xtra database (http://bloodchipXtra.vafaeelab.com/) facilitates genome-wide exploration and visualization of transcription factor (TF) occupancy and chromatin configuration in rare primary human hematopoietic stem (HSC-MPP) and progenitor (CMP, GMP, MEP) cells and acute myeloid leukemia (AML) cell lines (KG-1, ME-1, Kasumi1, TSU-1621-MT), along with chromatin accessibility and gene expression data from these and primary patient AMLs. BloodChIP Xtra features significantly more datasets than our earlier database BloodChIP (two primary cell types and two cell lines). Improved methodologies for determining TF occupancy and chromatin accessibility have led to increased availability of data for rare primary cell types across the spectrum of healthy and AML hematopoiesis. However, there is a continuing need for these data to be integrated in an easily accessible manner for gene-based queries and use in downstream applications. Here, we provide a user-friendly database based around genome-wide binding profiles of key hematopoietic TFs and histone marks in healthy stem/progenitor cell types. These are compared with binding profiles and chromatin accessibility derived from primary and cell line AML and integrated with expression data from corresponding cell types. All queries can be exported to construct TF-gene and protein-protein networks and evaluate the association of genes with specific cellular processes.
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Affiliation(s)
- Julie A I Thoms
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
| | - Forrest C Koch
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Alireza Raei
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
| | - Shruthi Subramanian
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Jason W H Wong
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
- UNSW Data Science Hub, University of New South Wales, Sydney, Australia
| | - John E Pimanda
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
- Haematology Department, Prince of Wales Hospital, Sydney, Australia
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3
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Subramanian S, Thoms JAI, Huang Y, Cornejo-Páramo P, Koch FC, Jacquelin S, Shen S, Song E, Joshi S, Brownlee C, Woll PS, Chacon-Fajardo D, Beck D, Curtis DJ, Yehson K, Antonenas V, O'Brien T, Trickett A, Powell JA, Lewis ID, Pitson SM, Gandhi MK, Lane SW, Vafaee F, Wong ES, Göttgens B, Alinejad-Rokny H, Wong JWH, Pimanda JE. Genome-wide transcription factor-binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs. Blood 2023; 142:1448-1462. [PMID: 37595278 PMCID: PMC10651876 DOI: 10.1182/blood.2023021120] [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: 05/10/2023] [Revised: 07/06/2023] [Accepted: 07/25/2023] [Indexed: 08/20/2023] Open
Abstract
Hematopoietic stem and progenitor cells (HSPCs) rely on a complex interplay among transcription factors (TFs) to regulate differentiation into mature blood cells. A heptad of TFs (FLI1, ERG, GATA2, RUNX1, TAL1, LYL1, LMO2) bind regulatory elements in bulk CD34+ HSPCs. However, whether specific heptad-TF combinations have distinct roles in regulating hematopoietic differentiation remains unknown. We mapped genome-wide chromatin contacts (HiC, H3K27ac, HiChIP), chromatin modifications (H3K4me3, H3K27ac, H3K27me3) and 10 TF binding profiles (heptad, PU.1, CTCF, STAG2) in HSPC subsets (stem/multipotent progenitors plus common myeloid, granulocyte macrophage, and megakaryocyte erythrocyte progenitors) and found TF occupancy and enhancer-promoter interactions varied significantly across cell types and were associated with cell-type-specific gene expression. Distinct regulatory elements were enriched with specific heptad-TF combinations, including stem-cell-specific elements with ERG, and myeloid- and erythroid-specific elements with combinations of FLI1, RUNX1, GATA2, TAL1, LYL1, and LMO2. Furthermore, heptad-occupied regions in HSPCs were subsequently bound by lineage-defining TFs, including PU.1 and GATA1, suggesting that heptad factors may prime regulatory elements for use in mature cell types. We also found that enhancers with cell-type-specific heptad occupancy shared a common grammar with respect to TF binding motifs, suggesting that combinatorial binding of TF complexes was at least partially regulated by features encoded in DNA sequence motifs. Taken together, this study comprehensively characterizes the gene regulatory landscape in rare subpopulations of human HSPCs. The accompanying data sets should serve as a valuable resource for understanding adult hematopoiesis and a framework for analyzing aberrant regulatory networks in leukemic cells.
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Affiliation(s)
- Shruthi Subramanian
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Julie A. I. Thoms
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
| | - Yizhou Huang
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | | | - Forrest C. Koch
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
| | | | - Sylvie Shen
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Emma Song
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Swapna Joshi
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Chris Brownlee
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, Australia
| | - Petter S. Woll
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Diego Chacon-Fajardo
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - Dominik Beck
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - David J. Curtis
- Australian Centre for Blood Diseases, Monash University, Melbourne, VIC, Australia
| | - Kenneth Yehson
- Blood Transplant and Cell Therapies Laboratory, NSW Health Pathology, Westmead, NSW, Australia
| | - Vicki Antonenas
- Blood Transplant and Cell Therapies Laboratory, NSW Health Pathology, Westmead, NSW, Australia
| | | | - Annette Trickett
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Jason A. Powell
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
- Adelaide Medical School, The University of Adelaide, Adelaide, Australia
| | - Ian D. Lewis
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
| | - Stuart M. Pitson
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
| | - Maher K. Gandhi
- Blood Cancer Research Group, Mater Research, The University of Queensland, Brisbane, QLD, Australia
| | - Steven W. Lane
- Cancer Program, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
- UNSW Data Science Hub, University of New South Wales, Sydney, Australia
| | - Emily S. Wong
- Victor Chang Cardiac Research Institute, Sydney, Australia
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Hamid Alinejad-Rokny
- BioMedical Machine Learning Lab, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia
| | - Jason W. H. Wong
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - John E. Pimanda
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
- Haematology Department, Prince of Wales Hospital, Sydney, Australia
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Hehmeyer J, Spitz F, Marlow H. Shifting landscapes: the role of 3D genomic organizations in gene regulatory strategies. Curr Opin Genet Dev 2023; 81:102064. [PMID: 37390583 PMCID: PMC10547022 DOI: 10.1016/j.gde.2023.102064] [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: 03/04/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 07/02/2023]
Abstract
3D genome folding enables the physical storage of chromosomes into the compact volume of a cell's nucleus, allows for the accurate segregation of chromatin to daughter cells, and has been shown to be tightly coupled to the way in which genetic information is converted into transcriptional programs [1-3]. Importantly, this link between chromatin architecture and gene regulation is a selectable feature in which modifications to chromatin organization accompany, or perhaps even drive the establishment of new regulatory strategies with enduring impacts on animal body plan complexity. Here, we discuss the nature of different 3D genome folding systems found across the tree of life, with particular emphasis on metazoans, and the relative influence of these systems on gene regulation. We suggest how the properties of these folding systems have influenced regulatory strategies employed by different lineages and may have catalyzed the partitioning and specialization of genetic programs that enabled multicellularity and organ-grade body plan complexity.
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Affiliation(s)
- Jenks Hehmeyer
- Department of Organismal Biology and Anatomy, The University of Chicago, USA
| | - François Spitz
- Department of Human Genetics, The University of Chicago, USA
| | - Heather Marlow
- Department of Organismal Biology and Anatomy, The University of Chicago, USA.
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Smith GD, Ching WH, Cornejo-Páramo P, Wong ES. Decoding enhancer complexity with machine learning and high-throughput discovery. Genome Biol 2023; 24:116. [PMID: 37173718 PMCID: PMC10176946 DOI: 10.1186/s13059-023-02955-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their flexible organization and functional redundancies make deciphering their sequence-function relationships challenging. This article provides an overview of the current understanding of enhancer organization and evolution, with an emphasis on factors that influence these relationships. Technological advancements, particularly in machine learning and synthetic biology, are discussed in light of how they provide new ways to understand this complexity. Exciting opportunities lie ahead as we continue to unravel the intricacies of enhancer function.
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Affiliation(s)
- Gabrielle D Smith
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Wan Hern Ching
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
| | - Paola Cornejo-Páramo
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Emily S Wong
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia.
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia.
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