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Chang TY, Waxman DJ. HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.10.598329. [PMID: 38915578 PMCID: PMC11195054 DOI: 10.1101/2024.06.10.598329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues. Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3). HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.
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Affiliation(s)
- Ting-Ya Chang
- Departments of Biology and Biomedical Engineering, and Bioinformatics program, Boston University, Boston, MA 02215
| | - David J Waxman
- Departments of Biology and Biomedical Engineering, and Bioinformatics program, Boston University, Boston, MA 02215
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Ben-Simon Y, Hooper M, Narayan S, Daigle T, Dwivedi D, Way SW, Oster A, Stafford DA, Mich JK, Taormina MJ, Martinez RA, Opitz-Araya X, Roth JR, Allen S, Ayala A, Bakken TE, Barcelli T, Barta S, Bendrick J, Bertagnolli D, Bowlus J, Boyer G, Brouner K, Casian B, Casper T, Chakka AB, Chakrabarty R, Chance RK, Chavan S, Departee M, Donadio N, Dotson N, Egdorf T, Gabitto M, Gary A, Gasperini M, Goldy J, Gore BB, Graybuck L, Greisman N, Haeseleer F, Halterman C, Helback O, Hockemeyer D, Huang C, Huff S, Hunker A, Johansen N, Juneau Z, Kalmbach B, Khem S, Kutsal R, Larsen R, Lee C, Lee AY, Leibly M, Lenz GH, Liang E, Lusk N, Malone J, Mollenkopf T, Morin E, Newman D, Ng L, Ngo K, Omstead V, Oyama A, Pham T, Pom CA, Potekhina L, Ransford S, Rette D, Rimorin C, Rocha D, Ruiz A, Sanchez REA, Sedeno-Cortes A, Sevigny JP, Shapovalova N, Shulga L, Sigler AR, Siverts LA, Somasundaram S, Stewart K, Tieu M, Trader C, van Velthoven CTJ, Walker M, Weed N, Wirthlin M, Wood T, Wynalda B, Yao Z, Zhou T, Ariza J, Dee N, Reding M, Ronellenfitch K, Mufti S, Sunkin SM, Smith KA, Esposito L, Waters J, Thyagarajan B, Yao S, Lein ES, Zeng H, Levi BP, Ngai J, Ting J, Tasic B. A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.10.597244. [PMID: 38915722 PMCID: PMC11195086 DOI: 10.1101/2024.06.10.597244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The mammalian cortex is comprised of cells with different morphological, physiological, and molecular properties that can be classified according to shared properties into cell types. Defining the contribution of each cell type to the computational and cognitive processes that are guided by the cortex is essential for understanding its function in health and disease. We use transcriptomic and epigenomic cortical cell type taxonomies from mice and humans to define marker genes and enhancers, and to build genetic tools for cortical cell types. Here, we present a large toolkit for selective targeting of cortical populations, including mouse transgenic lines and recombinant adeno-associated virus (AAV) vectors containing genomic enhancers. We report evaluation of fifteen new transgenic driver lines and over 680 different enhancer AAVs covering all major subclasses of cortical cells, with many achieving a high degree of specificity, comparable with existing transgenic lines. We find that the transgenic lines based on marker genes can provide exceptional specificity and completeness of cell type labeling, but frequently require generation of a triple-transgenic cross for best usability/specificity. On the other hand, enhancer AAVs are easy to screen and use, and can be easily modified to express diverse cargo, such as recombinases. However, their use depends on many factors, such as viral titer and route of administration. The tools reported here as well as the scaled process of tool creation provide an unprecedented resource that should enable diverse experimental strategies towards understanding mammalian cortex and brain function.
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Zhang J, Wang Q, Qi S, Duan Y, Liu Z, Liu J, Zhang Z, Li C. An oncogenic enhancer promotes melanoma progression via regulating ETV4 expression. J Transl Med 2024; 22:547. [PMID: 38849954 PMCID: PMC11157841 DOI: 10.1186/s12967-024-05356-8] [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: 04/13/2024] [Accepted: 05/29/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND Enhancers are important gene regulatory elements that promote the expression of critical genes in development and disease. Aberrant enhancer can modulate cancer risk and activate oncogenes that lead to the occurrence of various cancers. However, the underlying mechanism of most enhancers in cancer remains unclear. Here, we aim to explore the function and mechanism of a crucial enhancer in melanoma. METHODS Multi-omics data were applied to identify an enhancer (enh17) involved in melanoma progression. To evaluate the function of enh17, CRISPR/Cas9 technology were applied to knockout enh17 in melanoma cell line A375. RNA-seq, ChIP-seq and Hi-C data analysis integrated with luciferase reporter assay were performed to identify the potential target gene of enh17. Functional experiments were conducted to further validate the function of the target gene ETV4. Multi-omics data integrated with CUT&Tag sequencing were performed to validate the binding profile of the inferred transcription factor STAT3. RESULTS An enhancer, named enh17 here, was found to be aberrantly activated and involved in melanoma progression. CRISPR/Cas9-mediated deletion of enh17 inhibited cell proliferation, migration, and tumor growth of melanoma both in vitro and in vivo. Mechanistically, we identified ETV4 as a target gene regulated by enh17, and functional experiments further support ETV4 as a target gene that is involved in cancer-associated phenotypes. In addition, STAT3 acts as a transcription factor binding with enh17 to regulate the transcription of ETV4. CONCLUSIONS Our findings revealed that enh17 plays an oncogenic role and promotes tumor progression in melanoma, and its transcriptional regulatory mechanisms were fully elucidated, which may open a promising window for melanoma prevention and treatment.
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Affiliation(s)
- Junyou Zhang
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Qilin Wang
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Sihan Qi
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Yingying Duan
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Zhaoshuo Liu
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Jiaxin Liu
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Ziyi Zhang
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Chunyan Li
- School of Engineering Medicine, Beihang University, Beijing, 100191, China.
- Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), Beihang University, Beijing, 100191, China.
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China.
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, 100191, China.
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Pacalin NM, Steinhart Z, Shi Q, Belk JA, Dorovskyi D, Kraft K, Parker KR, Shy BR, Marson A, Chang HY. Bidirectional epigenetic editing reveals hierarchies in gene regulation. Nat Biotechnol 2024:10.1038/s41587-024-02213-3. [PMID: 38760566 DOI: 10.1038/s41587-024-02213-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/19/2024] [Indexed: 05/19/2024]
Abstract
CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.
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Affiliation(s)
- Naomi M Pacalin
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zachary Steinhart
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Quanming Shi
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Julia A Belk
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Dmytro Dorovskyi
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Katerina Kraft
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Kevin R Parker
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA
- Cartography Biosciences, Inc., South San Francisco, CA, USA
| | - Brian R Shy
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander Marson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA
- Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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Le DJ, Hafner A, Gaddam S, Wang KC, Boettiger AN. Super-enhancer interactomes from single cells link clustering and transcription. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.593251. [PMID: 38766104 PMCID: PMC11100725 DOI: 10.1101/2024.05.08.593251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Regulation of gene expression hinges on the interplay between enhancers and promoters, traditionally explored through pairwise analyses. Recent advancements in mapping genome folding, like GAM, SPRITE, and multi-contact Hi-C, have uncovered multi-way interactions among super-enhancers (SEs), spanning megabases, yet have not measured their frequency in single cells or the relationship between clustering and transcription. To close this gap, here we used multiplexed imaging to map the 3D positions of 376 SEs across thousands of mammalian nuclei. Notably, our single-cell images reveal that while SE-SE contacts are rare, SEs often form looser associations we termed "communities". These communities, averaging 4-5 SEs, assemble cooperatively under the combined effects of genomic tethers, Pol2 clustering, and nuclear compartmentalization. Larger communities are associated with more frequent and larger transcriptional bursts. Our work provides insights about the SE interactome in single cells that challenge existing hypotheses on SE clustering in the context of transcriptional regulation.
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Affiliation(s)
- Derek J. Le
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- Cancer Biology Program, Stanford University, Stanford, CA, United States
- Department of Dermatology, Stanford University, Stanford, CA, United States
- These authors contributed equally
| | - Antonina Hafner
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- These authors contributed equally
| | - Sadhana Gaddam
- Department of Dermatology, Stanford University, Stanford, CA, United States
| | - Kevin C. Wang
- Department of Dermatology, Stanford University, Stanford, CA, United States
| | - Alistair N. Boettiger
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- Lead contact
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6
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Toneyan S, Koo PK. Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.03.547592. [PMID: 37461616 PMCID: PMC10349992 DOI: 10.1101/2023.07.03.547592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with experimental perturbation assays, which provides insights into the generalization capabilities within the studied loci but offers a limited perspective of what drives their predictions. Moreover, existing model explainability tools focus mainly on motif analysis, which becomes complex when interpreting longer sequences. Here we introduce CREME, an in silico perturbation toolkit that interrogates large-scale DNNs to uncover rules of gene regulation that it learns. Using CREME, we investigate Enformer, a prominent DNN in gene expression prediction, revealing cis-regulatory elements (CREs) that directly enhance or silence target genes. We explore the intricate complexity of higher-order CRE interactions, the relationship between CRE distance from transcription start sites on gene expression, as well as the biochemical features of enhancers and silencers learned by Enformer. Moreover, we demonstrate the flexibility of CREME to efficiently uncover a higher-resolution view of functional sequence elements within CREs. This work demonstrates how CREME can be employed to translate the powerful predictions of large-scale DNNs to study open questions in gene regulation.
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7
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Garza AB, Garcia R, Solis LM, Halfon MS, Girgis HZ. EnhancerTracker: Comparing cell-type-specific enhancer activity of DNA sequence triplets via an ensemble of deep convolutional neural networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573198. [PMID: 38187673 PMCID: PMC10769370 DOI: 10.1101/2023.12.23.573198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Motivation Transcriptional enhancers - unlike promoters - are unrestrained by distance or strand orientation with respect to their target genes, making their computational identification a challenge. Further, there are insufficient numbers of confirmed enhancers for many cell types, preventing robust training of machine-learning-based models for enhancer prediction for such cell types. Results We present EnhancerTracker , a novel tool that leverages an ensemble of deep separable convolutional neural networks to identify cell-type-specific enhancers with the need of only two confirmed enhancers. EnhancerTracker is trained, validated, and tested on 52,789 putative enhancers obtained from the FANTOM5 Project and control sequences derived from the human genome. Unlike available tools, which accept one sequence at a time, the input to our tool is three sequences; the first two are enhancers active in the same cell type. EnhancerTracker outputs 1 if the third sequence is an enhancer active in the same cell type(s) where the first two enhancers are active. It outputs 0 otherwise. On a held-out set (15%), EnhancerTracker achieved an accuracy of 64%, a specificity of 93%, a recall of 35%, a precision of 84%, and an F1 score of 49%. Availability and implementation https://github.com/BioinformaticsToolsmith/EnhancerTracker. Contact hani.girgis@tamuk.edu.
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8
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Blayney JW, Francis H, Rampasekova A, Camellato B, Mitchell L, Stolper R, Cornell L, Babbs C, Boeke JD, Higgs DR, Kassouf M. Super-enhancers include classical enhancers and facilitators to fully activate gene expression. Cell 2023; 186:5826-5839.e18. [PMID: 38101409 PMCID: PMC10858684 DOI: 10.1016/j.cell.2023.11.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 07/06/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023]
Abstract
Super-enhancers are compound regulatory elements that control expression of key cell identity genes. They recruit high levels of tissue-specific transcription factors and co-activators such as the Mediator complex and contact target gene promoters with high frequency. Most super-enhancers contain multiple constituent regulatory elements, but it is unclear whether these elements have distinct roles in activating target gene expression. Here, by rebuilding the endogenous multipartite α-globin super-enhancer, we show that it contains bioinformatically equivalent but functionally distinct element types: classical enhancers and facilitator elements. Facilitators have no intrinsic enhancer activity, yet in their absence, classical enhancers are unable to fully upregulate their target genes. Without facilitators, classical enhancers exhibit reduced Mediator recruitment, enhancer RNA transcription, and enhancer-promoter interactions. Facilitators are interchangeable but display functional hierarchy based on their position within a multipartite enhancer. Facilitators thus play an important role in potentiating the activity of classical enhancers and ensuring robust activation of target genes.
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Affiliation(s)
- Joseph W Blayney
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Helena Francis
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Alexandra Rampasekova
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Brendan Camellato
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY 10016, USA
| | - Leslie Mitchell
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY 10016, USA
| | - Rosa Stolper
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Lucy Cornell
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Christian Babbs
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK
| | - Jef D Boeke
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY 10016, USA; Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA.
| | - Douglas R Higgs
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK; Chinese Academy of Medical Sciences Oxford Institute, Oxford OX3 7BN, UK.
| | - Mira Kassouf
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK.
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Barsoum M, Sayadi-Boroujeni R, Stenzel AT, Bussmann P, Lüscher-Firzlaff J, Lüscher B. Sequential deregulation of histone marks, chromatin accessibility and gene expression in response to PROTAC-induced degradation of ASH2L. Sci Rep 2023; 13:22565. [PMID: 38114530 PMCID: PMC10730889 DOI: 10.1038/s41598-023-49284-x] [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: 09/15/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023] Open
Abstract
The trithorax protein ASH2L is essential for organismal and tissue development. As a subunit of COMPASS/KMT2 complexes, ASH2L is necessary for methylation of histone H3 lysine 4 (H3K4). Mono- and tri-methylation at this site mark active enhancers and promoters, respectively, although the functional relevance of H3K4 methylation is only partially understood. ASH2L has a long half-life, which results in a slow decrease upon knockout. This has made it difficult to define direct consequences. To overcome this limitation, we employed a PROTAC system to rapidly degrade ASH2L and address direct effects. ASH2L loss resulted in inhibition of proliferation of mouse embryo fibroblasts. Shortly after ASH2L degradation H3K4me3 decreased with its half-life varying between promoters. Subsequently, H3K4me1 increased at promoters and decreased at some enhancers. H3K27ac and H3K27me3, histone marks closely linked to H3K4 methylation, were affected with considerable delay. In parallel, chromatin compaction increased at promoters. Of note, nascent gene transcription was not affected early but overall RNA expression was deregulated late after ASH2L loss. Together, these findings suggest that downstream effects are ordered but relatively slow, despite the rapid loss of ASH2L and inactivation of KMT2 complexes. It appears that the systems that control gene transcription are well buffered and strong effects are only beginning to unfold after considerable delay.
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Affiliation(s)
- Mirna Barsoum
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
| | - Roksaneh Sayadi-Boroujeni
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
- Bayer AG, Crop Science Division, R&D, Pest Control, 40789, Monheim am Rhein, Germany
| | - Alexander T Stenzel
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
- Institute of Human Genetics, Faculty of Medicine, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Philip Bussmann
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
| | - Juliane Lüscher-Firzlaff
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
| | - Bernhard Lüscher
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
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10
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Owen DM, Kwon M, Huang X, Nagari A, Nandu T, Kraus WL. Genome-wide identification of transcriptional enhancers during human placental development and association with function, differentiation, and disease†. Biol Reprod 2023; 109:965-981. [PMID: 37694817 PMCID: PMC10724456 DOI: 10.1093/biolre/ioad119] [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: 01/28/2023] [Revised: 08/07/2023] [Accepted: 09/09/2023] [Indexed: 09/12/2023] Open
Abstract
The placenta is a dynamic organ that must perform a remarkable variety of functions during its relatively short existence in order to support a developing fetus. These functions include nutrient delivery, gas exchange, waste removal, hormone production, and immune barrier protection. Proper placenta development and function are critical for healthy pregnancy outcomes, but the underlying genomic regulatory events that control this process remain largely unknown. We hypothesized that mapping sites of transcriptional enhancer activity and associated changes in gene expression across gestation in human placenta tissue would identify genomic loci and predicted transcription factor activity related to critical placenta functions. We used a suite of genomic assays [i.e., RNA-sequencing (RNA-seq), Precision run-on-sequencing (PRO-seq), and Chromatin immunoprecipitation-sequencing (ChIP-seq)] and computational pipelines to identify a set of >20 000 enhancers that are active at various time points in gestation. Changes in the activity of these enhancers correlate with changes in gene expression. In addition, some of these enhancers encode risk for adverse pregnancy outcomes. We further show that integrating enhancer activity, transcription factor motif analysis, and transcription factor expression can identify distinct sets of transcription factors predicted to be more active either in early pregnancy or at term. Knockdown of selected identified transcription factors in a trophoblast stem cell culture model altered the expression of key placental marker genes. These observations provide a framework for future mechanistic studies of individual enhancer-transcription factor-target gene interactions and have the potential to inform genetic risk prediction for adverse pregnancy outcomes.
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Affiliation(s)
- David M Owen
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of General Obstetrics and Gynecology, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Minjung Kwon
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xuan Huang
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Anusha Nagari
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tulip Nandu
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - W Lee Kraus
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
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11
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Thomas HF, Buecker C. What is an enhancer? Bioessays 2023; 45:e2300044. [PMID: 37256273 DOI: 10.1002/bies.202300044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 06/01/2023]
Abstract
Tight control of the transcription process is essential for the correct spatial and temporal gene expression pattern during development and in homeostasis. Enhancers are at the core of correct transcriptional activation. The original definition of an enhancer is straightforward: a DNA sequence that activates transcription independent of orientation and direction. Dissection of numerous enhancer loci has shown that many enhancer-like elements might not conform to the original definition, suggesting that enhancers and enhancer-like elements might use multiple different mechanisms to contribute to transcriptional activation. Here, we review methodologies to identify enhancers and enhancer-like elements and discuss pitfalls and consequences for our understanding of transcriptional regulation.
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12
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Kleinschmidt H, Xu C, Bai L. Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation. Chromosoma 2023; 132:167-189. [PMID: 37184694 PMCID: PMC10542970 DOI: 10.1007/s00412-023-00796-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/16/2023]
Abstract
Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.
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Affiliation(s)
- Holly Kleinschmidt
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Cheng Xu
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Lu Bai
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA.
- Department of Physics, The Pennsylvania State University, University Park, PA, 16802, USA.
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13
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Wang L, Wei C, Wang Y, Huang N, Zhang T, Dai Y, Xue L, Lin S, Wu ZB. Identification of the enhancer RNAs related to tumorgenesis of pituitary neuroendocrine tumors. Front Endocrinol (Lausanne) 2023; 14:1149997. [PMID: 37534217 PMCID: PMC10393250 DOI: 10.3389/fendo.2023.1149997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 06/27/2023] [Indexed: 08/04/2023] Open
Abstract
Background Pituitary neuroendocrine tumors (PitNETs), which originate from the pituitary gland, account for 10%-15% of all intracranial neoplasms. Recent studies have indicated that enhancer RNAs (eRNAs) exert regulatory effects on tumor growth. However, the mechanisms underlying the eRNA-mediated tumorigenesis of PitNETs have not been elucidated. Methods Normal pituitary and PitNETs tissues were used to identify the differentially expressed eRNAs (DEEs). Immune gene sets and hallmarks of cancer gene sets were quantified based on single sample gene set enrichment analysis (ssGSEA) algorithm using GSVA. The perspective of immune cells among all samples was calculated by the CIBERSORT algorithm. Moreover, the regulatory network composed of key DEEs, target genes of eRNAs, hallmarks of cancer gene sets, differentially expressed TF, immune cells and immune gene sets were constructed by Pearson correlation analysis. Small molecular anti-PitNETs drugs were explored by CMap analysis and the accuracy of the study was verified by in vitro and in vivo experiments, ATAC-seq and ChIP-seq. Results In this study, data of 134 PitNETs and 107 non-tumorous pituitary samples were retrieved from a public database to identify differentially expressed genes. In total, 1128 differentially expressed eRNAs (DEEs) (494 upregulated eRNAs and 634 downregulated eRNAs) were identified. Next, the correlation of DEEs with cancer-related and immune-related gene signatures was examined to establish a co-expression regulatory network comprising 18 DEEs, 50 potential target genes of DEEs, 5 cancer hallmark gene sets, 2 differentially expressed transcription factors, 4 immune cell types, and 4 immune gene sets. Based on this network, the following four therapeutics for PitNETs were identified using Connectivity Map analysis: ciclopirox, bepridil, clomipramine, and alexidine. The growth-inhibitory effects of these therapeutics were validated using in vitro experiments. Ciclopirox exerted potential growth-inhibitory effects on PitNETs. Among the DEEs, GNLY, HOXB7, MRPL33, PRDM16, TCF7, and ZNF26 were determined to be potential diagnostic and therapeutic biomarkers for PitNETs. Conclusion This study illustrated the significant influence of eRNAs on the occurrence and development of PitNETs. By constructing the co-expression regulation network, GNLY, HOXB6, MRPL33, PRDM16, TCF7, and ZNF26 were identified as relatively significant DEEs which were considered as the novel biomarkers of diagnosis and treatment of PitNETs. This study demonstrated the roles of eRNAs in the occurrence and development of PitNETs and revealed that ciclopirox was a potential therapeutic for pituitary adenomas.
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Affiliation(s)
- Liangbo Wang
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chenlu Wei
- Center for Reproductive Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Wang
- Department of Neurosurgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Huang
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Tao Zhang
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yuting Dai
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li Xue
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shaojian Lin
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhe Bao Wu
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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14
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de Boer E, Marcelis C, Neveling K, van Beusekom E, Hoischen A, Klein WM, de Leeuw N, Mantere T, Melo US, van Reeuwijk J, Smeets D, Spielmann M, Kleefstra T, van Bokhoven H, Vissers LE. A complex structural variant near SOX3 causes X-linked split-hand/foot malformation. HGG ADVANCES 2023; 4:100200. [PMID: 37216008 PMCID: PMC10196709 DOI: 10.1016/j.xhgg.2023.100200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 04/13/2023] [Indexed: 05/24/2023] Open
Abstract
Split-hand/foot malformation (SHFM) is a congenital limb defect most typically presenting with median clefts in hands and/or feet, that can occur in a syndromic context as well as in isolated form. SHFM is caused by failure to maintain normal apical ectodermal ridge function during limb development. Although several genes and contiguous gene syndromes are implicated in the monogenic etiology of isolated SHFM, the disorder remains genetically unexplained for many families and associated genetic loci. We describe a family with isolated X-linked SHFM, for which the causative variant could be detected after a diagnostic journey of 20 years. We combined well-established approaches including microarray-based copy number variant analysis and fluorescence in situ hybridization coupled with optical genome mapping and whole genome sequencing. This strategy identified a complex structural variant (SV) comprising a 165-kb gain of 15q26.3 material ([GRCh37/hg19] chr15:99795320-99960362dup) inserted in inverted position at the site of a 38-kb deletion on Xq27.1 ([GRCh37/hg19] chrX:139481061-139518989del). In silico analysis suggested that the SV disrupts the regulatory framework on the X chromosome and may lead to SOX3 misexpression. We hypothesize that SOX3 dysregulation in the developing limb disturbed the fine balance between morphogens required for maintaining AER function, resulting in SHFM in this family.
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Affiliation(s)
- Elke de Boer
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Carlo Marcelis
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
| | - Kornelia Neveling
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Ellen van Beusekom
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Willemijn M. Klein
- Department of Medical Imaging, Radiology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Nicole de Leeuw
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
| | - Tuomo Mantere
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Uirá S. Melo
- Max Planck Institute for Molecular Genetics, RG Development & Disease, Berlin, Germany
- Institute for Medical and Human Genetics, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jeroen van Reeuwijk
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Dominique Smeets
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
| | - Malte Spielmann
- Max Planck Institute for Molecular Genetics, RG Development & Disease, Berlin, Germany
- Institute of Human Genetics, University Hospitals Schleswig-Holstein, University of Lübeck and Kiel University, 23562 Lübeck, Kiel, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Tjitske Kleefstra
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
- Center of Excellence for Neuropsychiatry, Vincent van Gogh Institute for Psychiatry, Venray, the Netherlands
| | - Hans van Bokhoven
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboudumc, Nijmegen, the Netherlands
| | - Lisenka E.L.M. Vissers
- Department of Human Genetics, Radboudumc University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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15
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Htet M, Lei S, Bajpayi S, Zoitou A, Chamakioti M, Tampakakis E. The role of noncoding genetic variants in cardiomyopathy. Front Cardiovasc Med 2023; 10:1116925. [PMID: 37283586 PMCID: PMC10239966 DOI: 10.3389/fcvm.2023.1116925] [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: 12/06/2022] [Accepted: 05/04/2023] [Indexed: 06/08/2023] Open
Abstract
Cardiomyopathies remain one of the leading causes of morbidity and mortality worldwide. Environmental risk factors and genetic predisposition account for most cardiomyopathy cases. As with all complex diseases, there are significant challenges in the interpretation of the molecular mechanisms underlying cardiomyopathy-associated genetic variants. Given the technical improvements and reduced costs of DNA sequence technologies, an increasing number of patients are now undergoing genetic testing, resulting in a continuously expanding list of novel mutations. However, many patients carry noncoding genetic variants, and although emerging evidence supports their contribution to cardiac disease, their role in cardiomyopathies remains largely understudied. In this review, we summarize published studies reporting on the association of different types of noncoding variants with various types of cardiomyopathies. We focus on variants within transcriptional enhancers, promoters, intronic sites, and untranslated regions that are likely associated with cardiac disease. Given the broad nature of this topic, we provide an overview of studies that are relatively recent and have sufficient evidence to support a significant degree of causality. We believe that more research with additional validation of noncoding genetic variants will provide further mechanistic insights on the development of cardiac disease, and noncoding variants will be increasingly incorporated in future genetic screening tests.
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Affiliation(s)
- Myo Htet
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
| | - Shunyao Lei
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Sheetal Bajpayi
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
| | - Asimina Zoitou
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | | | - Emmanouil Tampakakis
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, United States
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16
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Chan YC, Kienle E, Oti M, Di Liddo A, Mendez-Lago M, Aschauer DF, Peter M, Pagani M, Arnold C, Vonderheit A, Schön C, Kreuz S, Stark A, Rumpel S. An unbiased AAV-STARR-seq screen revealing the enhancer activity map of genomic regions in the mouse brain in vivo. Sci Rep 2023; 13:6745. [PMID: 37185990 PMCID: PMC10130037 DOI: 10.1038/s41598-023-33448-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 04/12/2023] [Indexed: 05/17/2023] Open
Abstract
Enhancers are important cis-regulatory elements controlling cell-type specific expression patterns of genes. Furthermore, combinations of enhancers and minimal promoters are utilized to construct small, artificial promoters for gene delivery vectors. Large-scale functional screening methodology to construct genomic maps of enhancer activities has been successfully established in cultured cell lines, however, not yet applied to terminally differentiated cells and tissues in a living animal. Here, we transposed the Self-Transcribing Active Regulatory Region Sequencing (STARR-seq) technique to the mouse brain using adeno-associated-viruses (AAV) for the delivery of a highly complex screening library tiling entire genomic regions and covering in total 3 Mb of the mouse genome. We identified 483 sequences with enhancer activity, including sequences that were not predicted by DNA accessibility or histone marks. Characterizing the expression patterns of fluorescent reporters controlled by nine candidate sequences, we observed differential expression patterns also in sparse cell types. Together, our study provides an entry point for the unbiased study of enhancer activities in organisms during health and disease.
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Affiliation(s)
- Ya-Chien Chan
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Eike Kienle
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Martin Oti
- Institute of Molecular Biology GmbH (IMB), Mainz, Germany
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an Der Riß, Germany
| | | | | | - Dominik F Aschauer
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Manuel Peter
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Michaela Pagani
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
| | - Cosmas Arnold
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
- CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, Vienna, Austria
| | | | - Christian Schön
- Research Beyond Borders, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an Der Riß, Germany
| | - Sebastian Kreuz
- Research Beyond Borders, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an Der Riß, Germany
| | - Alexander Stark
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
- Medical University of Vienna, Vienna BioCenter (VBC), 1030, Vienna, Austria
| | - Simon Rumpel
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany.
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17
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Harden TT, Vincent BJ, DePace AH. Transcriptional activators in the early Drosophila embryo perform different kinetic roles. Cell Syst 2023; 14:258-272.e4. [PMID: 37080162 PMCID: PMC10473017 DOI: 10.1016/j.cels.2023.03.006] [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: 03/08/2021] [Revised: 06/26/2022] [Accepted: 03/21/2023] [Indexed: 04/22/2023]
Abstract
Combinatorial regulation of gene expression by transcription factors (TFs) may in part arise from kinetic synergy-wherein TFs regulate different steps in the transcription cycle. Kinetic synergy requires that TFs play distinguishable kinetic roles. Here, we used live imaging to determine the kinetic roles of three TFs that activate transcription in the Drosophila embryo-Zelda, Bicoid, and Stat92E-by introducing their binding sites into the even-skipped stripe 2 enhancer. These TFs influence different sets of kinetic parameters, and their influence can change over time. All three TFs increased the fraction of transcriptionally active nuclei; Zelda also shortened the first-passage time into transcription and regulated the interval between transcription events. Stat92E also increased the lifetimes of active transcription. Different TFs can therefore play distinct kinetic roles in activating the transcription. This has consequences for understanding the composition and flexibility of regulatory DNA sequences and the biochemical function of TFs. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Timothy T Harden
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Ben J Vincent
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Angela H DePace
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
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18
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Reiter F, de Almeida BP, Stark A. Enhancers display constrained sequence flexibility and context-specific modulation of motif function. Genome Res 2023; 33:346-358. [PMID: 36941077 PMCID: PMC10078294 DOI: 10.1101/gr.277246.122] [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: 08/26/2022] [Accepted: 02/14/2023] [Indexed: 03/23/2023]
Abstract
The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, whereas the enhancer syntax, that is, the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remains poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important TF motifs by all possible 65,536 eight-nucleotide-long sequences and (2) paste eight important TF motif types into 763 positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but these are only a fraction of all possible sequences and motif types. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, the presence and diversity of other motif types, and the distance between motifs), such that not all motif types can work in all positions. The context-specific modulation of motif function is also a hallmark of human enhancers, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution, and in disease.
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Affiliation(s)
- Franziska Reiter
- Research Institute of Molecular Pathology, Vienna BioCenter, Campus-Vienna-BioCenter 1, 1030 Vienna, Austria
- Vienna BioCenter PhD Program, Doctoral School of the University of Vienna and Medical University of Vienna, 1030 Vienna, Austria
| | - Bernardo P de Almeida
- Research Institute of Molecular Pathology, Vienna BioCenter, Campus-Vienna-BioCenter 1, 1030 Vienna, Austria
- Vienna BioCenter PhD Program, Doctoral School of the University of Vienna and Medical University of Vienna, 1030 Vienna, Austria
| | - Alexander Stark
- Research Institute of Molecular Pathology, Vienna BioCenter, Campus-Vienna-BioCenter 1, 1030 Vienna, Austria;
- Medical University of Vienna, Vienna BioCenter, 1030 Vienna, Austria
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19
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Barsoum M, Stenzel AT, Bochyńska A, Kuo CC, Tsompanidis A, Sayadi-Boroujeni R, Bussmann P, Lüscher-Firzlaff J, Costa IG, Lüscher B. Loss of the Ash2l subunit of histone H3K4 methyltransferase complexes reduces chromatin accessibility at promoters. Sci Rep 2022; 12:21506. [PMID: 36513698 PMCID: PMC9747801 DOI: 10.1038/s41598-022-25881-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 12/06/2022] [Indexed: 12/15/2022] Open
Abstract
Changes in gene expression programs are intimately linked to cell fate decisions. Post-translational modifications of core histones contribute to control gene expression. Methylation of lysine 4 of histone H3 (H3K4) correlates with active promoters and gene transcription. This modification is catalyzed by KMT2 methyltransferases, which require interaction with 4 core subunits, WDR5, RBBP5, ASH2L and DPY30, for catalytic activity. Ash2l is necessary for organismal development and for tissue homeostasis. In mouse embryo fibroblasts (MEFs), Ash2l loss results in gene repression, provoking a senescence phenotype. We now find that upon knockout of Ash2l both H3K4 mono- and tri-methylation (H3K4me1 and me3, respectively) were deregulated. In particular, loss of H3K4me3 at promoters correlated with gene repression, especially at CpG island promoters. Ash2l loss resulted in increased loading of histone H3 and reduced chromatin accessibility at promoters, accompanied by an increase of repressing and a decrease of activating histone marks. Moreover, we observed altered binding of CTCF upon Ash2l loss. Lost and gained binding was noticed at promoter-associated and intergenic sites, respectively. Thus, Ash2l loss and reduction of H3K4me3 correlate with altered chromatin accessibility and transcription factor binding. These findings contribute to a more detailed understanding of mechanistic consequences of H3K4me3 loss and associated repression of gene transcription and thus of the observed cellular consequences.
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Affiliation(s)
- Mirna Barsoum
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Alexander T. Stenzel
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Agnieszka Bochyńska
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Chao-Chung Kuo
- grid.1957.a0000 0001 0728 696XInstitute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany ,grid.1957.a0000 0001 0728 696XInterdisciplinary Center for Clinical Research (IZKF), Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Alexander Tsompanidis
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Roksaneh Sayadi-Boroujeni
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Philip Bussmann
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Juliane Lüscher-Firzlaff
- grid.1957.a0000 0001 0728 696XInstitute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Ivan G. Costa
- grid.1957.a0000 0001 0728 696XInstitute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Bernhard Lüscher
- Institute of Biochemistry and Molecular Biology, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
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20
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Identification and functional validation of super-enhancers in Arabidopsis thaliana. Proc Natl Acad Sci U S A 2022; 119:e2215328119. [PMID: 36409894 PMCID: PMC9860255 DOI: 10.1073/pnas.2215328119] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Super-enhancers (SEs) are exceptionally large enhancers and are recognized to play prominent roles in cell identity in mammalian species. We surveyed the genomic regions containing large clusters of accessible chromatin regions (ACRs) marked by deoxyribonuclease (DNase) I hypersensitivity in Arabidopsis thaliana. We identified a set of 749 putative SEs, which have a minimum length of 1.5 kilobases and represent the top 2.5% of the largest ACR clusters. We demonstrate that the genomic regions associating with these SEs were more sensitive to DNase I than other nonpromoter ACRs. The SEs were preferentially associated with topologically associating domains. Furthermore, the SEs and their predicted cognate genes were frequently associated with organ development and tissue identity in A. thaliana. Therefore, the A. thaliana SEs and their cognate genes mirror the functional characteristics of those reported in mammalian species. We developed CRISPR/Cas-mediated deletion lines of a 3,578-bp SE associated with the thalianol biosynthetic gene cluster (BGC). Small deletions (131-157 bp) within the SE resulted in distinct phenotypic changes and transcriptional repression of all five thalianol genes. In addition, T-DNA insertions in the SE region resulted in transcriptional alteration of all five thalianol genes. Thus, this SE appears to play a central role in coordinating the operon-like expression pattern of the thalianol BGC.
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21
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Matsumura T, Totani H, Gunji Y, Fukuda M, Yokomori R, Deng J, Rethnam M, Yang C, Tan TK, Karasawa T, Kario K, Takahashi M, Osato M, Sanda T, Suda T. A Myb enhancer-guided analysis of basophil and mast cell differentiation. Nat Commun 2022; 13:7064. [PMID: 36400777 PMCID: PMC9674656 DOI: 10.1038/s41467-022-34906-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 11/10/2022] [Indexed: 11/19/2022] Open
Abstract
The transcription factor MYB is a crucial regulator of hematopoietic stem and progenitor cells. However, the nature of lineage-specific enhancer usage of the Myb gene is largely unknown. We identify the Myb -68 enhancer, a regulatory element which marks basophils and mast cells. Using the Myb -68 enhancer activity, we show a population of granulocyte-macrophage progenitors with higher potential to differentiate into basophils and mast cells. Single cell RNA-seq demonstrates the differentiation trajectory is continuous from progenitors to mature basophils in vivo, characterizes bone marrow cells with a gene signature of mast cells, and identifies LILRB4 as a surface marker of basophil maturation. Together, our study leads to a better understanding of how MYB expression is regulated in a lineage-associated manner, and also shows how a combination of lineage-related reporter mice and single-cell transcriptomics can overcome the rarity of target cells and enhance our understanding of gene expression programs that control cell differentiation in vivo.
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Affiliation(s)
- Takayoshi Matsumura
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore ,grid.410804.90000000123090000Division of Inflammation Research, Center for Molecular Medicine, Jichi Medical University, Tochigi, Japan ,grid.410804.90000000123090000Division of Cardiovascular Medicine, Department of Medicine, Jichi Medical University School of Medicine, Tochigi, Japan
| | - Haruhito Totani
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Yoshitaka Gunji
- grid.410804.90000000123090000Division of Inflammation Research, Center for Molecular Medicine, Jichi Medical University, Tochigi, Japan
| | - Masahiro Fukuda
- grid.428397.30000 0004 0385 0924Signature Program in Neuroscience and Behavioral Disorders, Duke-NUS Medical School, Singapore, Singapore ,grid.274841.c0000 0001 0660 6749International Research Center for Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Rui Yokomori
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Jianwen Deng
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Malini Rethnam
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Chong Yang
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Tze King Tan
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Tadayoshi Karasawa
- grid.410804.90000000123090000Division of Inflammation Research, Center for Molecular Medicine, Jichi Medical University, Tochigi, Japan
| | - Kazuomi Kario
- grid.410804.90000000123090000Division of Cardiovascular Medicine, Department of Medicine, Jichi Medical University School of Medicine, Tochigi, Japan
| | - Masafumi Takahashi
- grid.410804.90000000123090000Division of Inflammation Research, Center for Molecular Medicine, Jichi Medical University, Tochigi, Japan
| | - Motomi Osato
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Takaomi Sanda
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore ,grid.4280.e0000 0001 2180 6431Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Toshio Suda
- grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore ,grid.274841.c0000 0001 0660 6749International Research Center for Medical Sciences, Kumamoto University, Kumamoto, Japan ,grid.4280.e0000 0001 2180 6431Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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22
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Pang B, van Weerd JH, Hamoen FL, Snyder MP. Identification of non-coding silencer elements and their regulation of gene expression. Nat Rev Mol Cell Biol 2022; 24:383-395. [DOI: 10.1038/s41580-022-00549-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/29/2022] [Indexed: 11/09/2022]
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23
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Leung AKY, Yao L, Yu H. Functional genomic assays to annotate enhancer-promoter interactions genome wide. Hum Mol Genet 2022; 31:R97-R104. [PMID: 36018818 PMCID: PMC9585677 DOI: 10.1093/hmg/ddac204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/16/2022] [Accepted: 08/17/2022] [Indexed: 11/14/2022] Open
Abstract
Enhancers are pivotal for regulating gene transcription that occurs at promoters. Identification of the interacting enhancer-promoter pairs and understanding the mechanisms behind how they interact and how enhancers modulate transcription can provide fundamental insight into gene regulatory networks. Recently, advances in high-throughput methods in three major areas-chromosome conformation capture assay, such as Hi-C to study basic chromatin architecture, ectopic reporter experiments such as self-transcribing active regulatory region sequencing (STARR-seq) to quantify promoter and enhancer activity, and endogenous perturbations such as clustered regularly interspaced short palindromic repeat interference (CRISPRi) to identify enhancer-promoter compatibility-have further our knowledge about transcription. In this review, we will discuss the major method developments and key findings from these assays.
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Affiliation(s)
- Alden King-Yung Leung
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
- Center for Genomics and Proteomics Technology Development (CGPT), Cornell University, Ithaca NY 14853, USA
| | - Li Yao
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
- Center for Genomics and Proteomics Technology Development (CGPT), Cornell University, Ithaca NY 14853, USA
| | - Haiyuan Yu
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
- Center for Genomics and Proteomics Technology Development (CGPT), Cornell University, Ithaca NY 14853, USA
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24
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Ni P, Wilson D, Su Z. A map of cis-regulatory modules and constituent transcription factor binding sites in 80% of the mouse genome. BMC Genomics 2022; 23:714. [PMID: 36261804 PMCID: PMC9583556 DOI: 10.1186/s12864-022-08933-7] [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: 08/07/2022] [Accepted: 10/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mouse is probably the most important model organism to study mammal biology and human diseases. A better understanding of the mouse genome will help understand the human genome, biology and diseases. However, despite the recent progress, the characterization of the regulatory sequences in the mouse genome is still far from complete, limiting its use to understand the regulatory sequences in the human genome. RESULTS Here, by integrating binding peaks in ~ 9,000 transcription factor (TF) ChIP-seq datasets that cover 79.9% of the mouse mappable genome using an efficient pipeline, we were able to partition these binding peak-covered genome regions into a cis-regulatory module (CRM) candidate (CRMC) set and a non-CRMC set. The CRMCs contain 912,197 putative CRMs and 38,554,729 TF binding sites (TFBSs) islands, covering 55.5% and 24.4% of the mappable genome, respectively. The CRMCs tend to be under strong evolutionary constraints, indicating that they are likely cis-regulatory; while the non-CRMCs are largely selectively neutral, indicating that they are unlikely cis-regulatory. Based on evolutionary profiles of the genome positions, we further estimated that 63.8% and 27.4% of the mouse genome might code for CRMs and TFBSs, respectively. CONCLUSIONS Validation using experimental data suggests that at least most of the CRMCs are authentic. Thus, this unprecedentedly comprehensive map of CRMs and TFBSs can be a good resource to guide experimental studies of regulatory genomes in mice and humans.
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Affiliation(s)
- Pengyu Ni
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - David Wilson
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
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25
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Ni P, Moe J, Su Z. Accurate prediction of functional states of cis-regulatory modules reveals common epigenetic rules in humans and mice. BMC Biol 2022; 20:221. [PMID: 36199141 PMCID: PMC9535988 DOI: 10.1186/s12915-022-01426-9] [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: 04/12/2022] [Accepted: 09/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Predicting cis-regulatory modules (CRMs) in a genome and their functional states in various cell/tissue types of the organism are two related challenging computational tasks. Most current methods attempt to simultaneously achieve both using data of multiple epigenetic marks in a cell/tissue type. Though conceptually attractive, they suffer high false discovery rates and limited applications. To fill the gaps, we proposed a two-step strategy to first predict a map of CRMs in the genome, and then predict functional states of all the CRMs in various cell/tissue types of the organism. We have recently developed an algorithm for the first step that was able to more accurately and completely predict CRMs in a genome than existing methods by integrating numerous transcription factor ChIP-seq datasets in the organism. Here, we presented machine-learning methods for the second step. RESULTS We showed that functional states in a cell/tissue type of all the CRMs in the genome could be accurately predicted using data of only 1~4 epigenetic marks by a variety of machine-learning classifiers. Our predictions are substantially more accurate than the best achieved so far. Interestingly, a model trained on a cell/tissue type in humans can accurately predict functional states of CRMs in different cell/tissue types of humans as well as of mice, and vice versa. Therefore, epigenetic code that defines functional states of CRMs in various cell/tissue types is universal at least in humans and mice. Moreover, we found that from tens to hundreds of thousands of CRMs were active in a human and mouse cell/tissue type, and up to 99.98% of them were reutilized in different cell/tissue types, while as small as 0.02% of them were unique to a cell/tissue type that might define the cell/tissue type. CONCLUSIONS Our two-step approach can accurately predict functional states in any cell/tissue type of all the CRMs in the genome using data of only 1~4 epigenetic marks. Our approach is also more cost-effective than existing methods that typically use data of more epigenetic marks. Our results suggest common epigenetic rules for defining functional states of CRMs in various cell/tissue types in humans and mice.
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Affiliation(s)
- Pengyu Ni
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Joshua Moe
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
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26
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Cao N, Lan C, Chen C, Xu Z, Luo H, Zheng S, Gong X, Ren H, Li Z, Qu S, Yu C, Yang J, Jose PA, Chen Y, Wu G, Hu C, Yu J, Zeng C. Prenatal Lipopolysaccharides Exposure Induces Transgenerational Inheritance of Hypertension. Circulation 2022; 146:1082-1095. [PMID: 36004643 PMCID: PMC9529859 DOI: 10.1161/circulationaha.122.059891] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/26/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND Adverse environmental exposure during the prenatal period can lead to diseases in the offspring, including hypertension. Whether or not the hypertensive phenotype can be transgenerationally transmitted is not known. METHODS Pregnant Sprague Dawley rats were intraperitoneally injected with lipopolysaccharide (LPS) on gestation days 6, 8, 10, and 12 to generate the prenatal LPS exposure model. Blood pressure was monitored by both telemetry and tail-cuff method. RNA sequencing was performed to analyze transcriptome alteration in the kidney of the third generation. Tempol and spironolactone were used to test the potential preventative and therapeutic effect of targeting reactive oxygen species and mineralocorticoid receptor signaling, respectively. Molecular biological experiments were performed to illustrate the mechanism of epigenetic and transcription regulation. RESULTS Prenatal LPS exposure can impair the ability to excrete a salt load and induce hypertension from the first to the third generations, with the fourth and fifth generations, inducing salt-sensitive hypertension. Compared with control pups, the transcriptome in the kidney of the hypertensive third-generation prenatal LPS-exposed offspring have upregulation of the Ras-related C3 botulinum toxin substrate 1 (Rac1) gene and activation of mineralocorticoid receptor signaling. Furthermore, we found that LPS exposure during pregnancy triggered oxidative stress that upregulated KDM3B (histone lysine demethylase 3B) in the oocytes of first-generation female rats, leading to an inheritable low level of H3K9me2 (histone H3 lysine 9 dimethylation), resulting in the transgenerational upregulation of Rac1. Based on these findings, we treated the LPS-exposed pregnant rats with the reactive oxygen species scavenger, tempol, which successfully prevented hypertension in the first-generation offspring and the transgenerational inheritance of hypertension. CONCLUSIONS These findings show that adverse prenatal exposure induces transgenerational hypertension through an epigenetic-regulated mechanism and identify potentially preventive and therapeutic strategies for hypertension.
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Affiliation(s)
- Nian Cao
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
- Department of Cardiology, the Sixth Medical Centre, Chinese PLA General Hospital, Beijing, P.R. China
| | - Cong Lan
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Caiyu Chen
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Zaicheng Xu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Hao Luo
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Shuo Zheng
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Xue Gong
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
- Department of Cardiology, the Sixth Medical Centre, Chinese PLA General Hospital, Beijing, P.R. China
| | - Hongmei Ren
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Zhuxin Li
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Shuang Qu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Cheng Yu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Jining Yang
- Research Center for Nutrition and Food Safety, Chongqing Key Laboratory of Nutrition and Food Safety, Institute of Military Preventive Medicine, The Third Military Medical University, Chongqing, P.R. China
| | - Pedro A. Jose
- Division of Renal Diseases and Hypertension, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Yundai Chen
- Department of Cardiology, the Sixth Medical Centre, Chinese PLA General Hospital, Beijing, P.R. China
| | - Gengze Wu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Cuimei Hu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Junyi Yu
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
| | - Chunyu Zeng
- Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, P.R. China
- Chongqing Key Laboratory for Hypertension Research, Chongqing Cardiovascular Clinical Research Center, Chongqing Institute of Cardiology, Chongqing, P. R. China
- State Key Laboratory of Trauma, Burns and Combined Injury, Daping Hospital, The Third Military Medical University, Chongqing, P. R. China
- Heart Center of Fujian Province, Union Hospital, Fujian Medical University, Fuzhou, P.R. China
- Department of Cardiology, Chongqing General Hospital, Chongqing, P. R. China
- Cardiovascular Research Center of Chongqing College, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Chongqing, P. R. China
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27
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Dong P, Hoffman GE, Apontes P, Bendl J, Rahman S, Fernando MB, Zeng B, Vicari JM, Zhang W, Girdhar K, Townsley KG, Misir R, Brennand KJ, Haroutunian V, Voloudakis G, Fullard JF, Roussos P. Population-level variation in enhancer expression identifies disease mechanisms in the human brain. Nat Genet 2022; 54:1493-1503. [PMID: 36163279 PMCID: PMC9547946 DOI: 10.1038/s41588-022-01170-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 07/25/2022] [Indexed: 02/06/2023]
Abstract
Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding population-level variation in enhancer function in the human brain. Besides regulating tissue-specific and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. By jointly analyzing large-scale cell-type-specific transcriptome and regulome data, we cataloged 30,795 neuronal and 23,265 non-neuronal candidate transcribed enhancers. Examination of the transcriptome in 1,382 brain samples identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified expression quantitative trait loci (eQTLs) for both genes and enhancers and found that enhancer eQTLs mediate a substantial fraction of neuropsychiatric trait heritability. Inclusion of enhancer eQTLs in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the gene-enhancer regulome and genetic mechanisms in the human cortex in both healthy and diseased states.
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Affiliation(s)
- Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pasha Apontes
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, New York, NY, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael B Fernando
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Biao Zeng
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - James M Vicari
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wen Zhang
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kayla G Townsley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth Misir
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen J Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, New York, NY, USA.
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
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Typical Enhancers, Super-Enhancers, and Cancers. Cancers (Basel) 2022; 14:cancers14184375. [PMID: 36139535 PMCID: PMC9496678 DOI: 10.3390/cancers14184375] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/29/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
Simple Summary The cancer genome has been exhaustively studied upon the advent of Next-Generation Sequencing technologies. Coding and non-coding sequences have been defined as hotspots of genomic variations that affect the naïve gene expression programs established in normal cells, thus working as endogenous drivers of carcinogenesis. In this review, we comprehensively summarize fundamental aspects of gene expression regulation, with emphasis on the impact of sequence and structural variations mapped across non-coding cis-acting elements of genes encoding for tumor-related transcription factors. Chromatin architecture, epigenome reprogramming, transcriptional enhancers and Super-enhancers, oncogene regulation, cutting-edge technologies, and pharmacological treatment are substantially highlighted. Abstract Non-coding segments of the human genome are enriched in cis-regulatory modules that constitute functional elements, such as transcriptional enhancers and Super-enhancers. A hallmark of cancer pathogenesis is the dramatic dysregulation of the “archetype” gene expression profiles of normal human cells. Genomic variations can promote such deficiencies when occurring across enhancers and Super-enhancers, since they affect their mechanistic principles, their functional capacity and specificity, and the epigenomic features of the chromatin microenvironment across which these regulatory elements reside. Here, we comprehensively describe: fundamental mechanisms of gene expression dysregulation in cancers that involve genomic abnormalities within enhancers’ and Super-enhancers’ (SEs) sequences, which alter the expression of oncogenic transcription factors (TFs); cutting-edge technologies applied for the analysis of variation-enriched hotspots of the cancer genome; and pharmacological approaches for the treatment of Super-enhancers’ aberrant function. Finally, we provide an intratumor meta-analysis, which highlights that genomic variations in transcription-factor-driven tumors are accompanied overexpression of genes, a portion of which encodes for additional cancer-related transcription factors.
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Khateb M, Perovanovic J, Ko KD, Jiang K, Feng X, Acevedo-Luna N, Chal J, Ciuffoli V, Genzor P, Simone J, Haase AD, Pourquié O, Dell'Orso S, Sartorelli V. Transcriptomics, regulatory syntax, and enhancer identification in mesoderm-induced ESCs at single-cell resolution. Cell Rep 2022; 40:111219. [PMID: 35977485 DOI: 10.1016/j.celrep.2022.111219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 06/11/2022] [Accepted: 07/25/2022] [Indexed: 11/03/2022] Open
Abstract
Embryonic stem cells (ESCs) can adopt lineage-specific gene-expression programs by stepwise exposure to defined factors, resulting in the generation of functional cell types. Bulk and single-cell-based assays were employed to catalog gene expression, histone modifications, chromatin conformation, and accessibility transitions in ESC populations and individual cells acquiring a presomitic mesoderm fate and undergoing further specification toward myogenic and neurogenic lineages. These assays identified cis-regulatory regions and transcription factors presiding over gene-expression programs occurring at defined ESC transitions and revealed the presence of heterogeneous cell populations within discrete ESC developmental stages. The datasets were employed to identify previously unappreciated genomic elements directing the initial activation of Pax7 and myogenic and neurogenic gene-expression programs. This study provides a resource for the discovery of genomic and transcriptional features of pluripotent, mesoderm-induced ESCs and ESC-derived cell lineages.
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Affiliation(s)
- Mamduh Khateb
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Jelena Perovanovic
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Kyung Dae Ko
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Kan Jiang
- Biodata Mining and Discovery Section, NIAMS, NIH, Bethesda, MD, USA
| | - Xuesong Feng
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Natalia Acevedo-Luna
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Jérome Chal
- Department of Genetics, Harvard Medical School, Boston, MA, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Stem Cell Institute, Boston, MA, USA
| | - Veronica Ciuffoli
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA
| | - Pavol Genzor
- National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA
| | - James Simone
- FlowCytometry Section, NIAMS, NIH, Bethesda, MD, USA
| | - Astrid D Haase
- National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA
| | - Olivier Pourquié
- Department of Genetics, Harvard Medical School, Boston, MA, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Stem Cell Institute, Boston, MA, USA
| | | | - Vittorio Sartorelli
- Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), NIH, Bethesda, MD, USA.
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30
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Hou TY, Kraus WL. Analysis of estrogen-regulated enhancer RNAs identifies a functional motif required for enhancer assembly and gene expression. Cell Rep 2022; 39:110944. [PMID: 35705040 PMCID: PMC9246336 DOI: 10.1016/j.celrep.2022.110944] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 04/12/2022] [Accepted: 05/20/2022] [Indexed: 11/03/2022] Open
Abstract
To better understand the functions of non-coding enhancer RNAs (eRNAs), we annotated the estrogen-regulated eRNA transcriptome in estrogen receptor α (ERα)-positive breast cancer cells using PRO-cap and RNA sequencing. We then cloned a subset of the eRNAs identified, fused them to single guide RNAs, and targeted them to their ERα enhancers of origin using CRISPR/dCas9. Some of the eRNAs tested modulated the expression of cognate, but not heterologous, target genes after estrogen treatment by increasing ERα recruitment and stimulating p300-catalyzed H3K27 acetylation at the enhancer. We identified a ∼40 nucleotide functional eRNA regulatory motif (FERM) present in many eRNAs that was necessary and sufficient to modulate gene expression, but not the specificity of activation, after estrogen treatment. The FERM interacted with BCAS2, an RNA-binding protein amplified in breast cancers. The ectopic expression of a targeted eRNA controlling the expression of an oncogene resulted in increased cell proliferation, demonstrating the regulatory potential of eRNAs in breast cancer.
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Affiliation(s)
- Tim Y Hou
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA
| | - W Lee Kraus
- Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.
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31
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Mu W, Murcia NS, Smith KN, Menon DU, Yee D, Magnuson T. RBBP4 dysfunction reshapes the genomic landscape of H3K27 methylation and acetylation and disrupts gene expression. G3 (BETHESDA, MD.) 2022; 12:jkac082. [PMID: 35416979 PMCID: PMC9157164 DOI: 10.1093/g3journal/jkac082] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 03/31/2022] [Indexed: 12/24/2022]
Abstract
RBBP4 is a subunit of the chromatin remodeling complexes known as Polycomb repressive complex 2 and histone deacetylase 1/2-containing complexes. These complexes are responsible for histone H3 lysine 27 methylation and deacetylation, respectively. How RBBP4 modulates the functions of these complexes remains largely unknown. We generated viable Rbbp4 mutant alleles in mouse embryonic stem cell lines by CRISPR-Cas9. The mutations disrupted Polycomb repressive complex 2 assembly and H3K27me3 establishment on target chromatin and altered histone H3 lysine 27 acetylation genome wide. Moreover, Rbbp4 mutant cells underwent dramatic changes in transcriptional profiles closely tied to the deregulation of H3K27ac. The alteration of H3K27ac due to RBBP4 dysfunction occurred on numerous cis-regulatory elements, especially putative enhancers. These data suggest that RBBP4 plays a central role in regulating histone H3 lysine 27 methylation and acetylation to modulate gene expression.
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Affiliation(s)
- Weipeng Mu
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
| | - Noel S Murcia
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
| | - Keriayn N Smith
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
| | - Debashish U Menon
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
| | - Della Yee
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
| | - Terry Magnuson
- Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
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32
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Mulero Hernández J, Fernández-Breis JT. Analysis of the landscape of human enhancer sequences in biological databases. Comput Struct Biotechnol J 2022; 20:2728-2744. [PMID: 35685360 PMCID: PMC9168495 DOI: 10.1016/j.csbj.2022.05.045] [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: 03/28/2022] [Revised: 05/20/2022] [Accepted: 05/21/2022] [Indexed: 12/01/2022] Open
Abstract
The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns. In turn, gene transcription is mainly controlled by regulatory events that occur at promoters and enhancers. Several studies are focused on analyzing the contribution of enhancers in the development of diseases and their possible use as therapeutic targets. The study of regulatory elements has advanced rapidly in recent years with the development and use of next generation sequencing techniques. All this information has generated a large volume of information that has been transferred to a growing number of public repositories that store this information. In this article, we analyze the content of those public repositories that contain information about human enhancers with the aim of detecting whether the knowledge generated by scientific research is contained in those databases in a way that could be computationally exploited. The analysis will be based on three main aspects identified in the literature: types of enhancers, type of evidence about the enhancers, and methods for detecting enhancer-promoter interactions. Our results show that no single database facilitates the optimal exploitation of enhancer data, most types of enhancers are not represented in the databases and there is need for a standardized model for enhancers. We have identified major gaps and challenges for the computational exploitation of enhancer data.
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Affiliation(s)
- Juan Mulero Hernández
- Dept. Informática y Sistemas, Universidad de Murcia, CEIR Campus Mare Nostrum, IMIB-Arrixaca, Spain
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DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers. Nat Genet 2022; 54:613-624. [PMID: 35551305 DOI: 10.1038/s41588-022-01048-5] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/08/2022] [Indexed: 02/06/2023]
Abstract
Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood, and de novo enhancer design has been challenging. Here, we built a deep-learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally nonequivalent instances of the same TF motif that are determined by motif-flanking sequence and intermotif distances. We validated these rules experimentally and demonstrated that they can be generalized to humans by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.
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34
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Wan L, Li W, Meng Y, Hou Y, Chen M, Xu B. Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects. Front Immunol 2022; 13:849451. [PMID: 35514959 PMCID: PMC9063412 DOI: 10.3389/fimmu.2022.849451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.
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Affiliation(s)
- Lilin Wan
- Medical School, Southeast University, Nanjing, China
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Wenchao Li
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Yuan Meng
- Department of Urology, Nanjing Lishui District People’s Hospital, Zhongda Hospital, Southeast University, Nanjing, China
| | - Yue Hou
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, China
| | - Ming Chen
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
- Department of Urology, Nanjing Lishui District People’s Hospital, Zhongda Hospital, Southeast University, Nanjing, China
| | - Bin Xu
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
- Department of Urology, Nanjing Lishui District People’s Hospital, Zhongda Hospital, Southeast University, Nanjing, China
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35
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Canton M, Farinati S, Forestan C, Joseph J, Bonghi C, Varotto S. An efficient chromatin immunoprecipitation (ChIP) protocol for studying histone modifications in peach reproductive tissues. PLANT METHODS 2022; 18:43. [PMID: 35361223 PMCID: PMC8973749 DOI: 10.1186/s13007-022-00876-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/15/2022] [Indexed: 05/12/2023]
Abstract
BACKGROUND Perennial fruit trees display a growth behaviour characterized by annual cycling between growth and dormancy, with complex physiological features. Rosaceae fruit trees represent excellent models for studying not only the fruit growth/patterning but also the progression of the reproductive cycle depending upon the impact of climate conditions. Additionally, current developments in high-throughput technologies have impacted Rosaceae tree research while investigating genome structure and function as well as (epi)genetic mechanisms involved in important developmental and environmental response processes during fruit tree growth. Among epigenetic mechanisms, chromatin remodelling mediated by histone modifications and other chromatin-related processes play a crucial role in gene modulation, controlling gene expression. Chromatin immunoprecipitation is an effective technique to investigate chromatin dynamics in plants. This technique is generally applied for studies on chromatin states and enrichment of post-transcriptional modifications (PTMs) in histone proteins. RESULTS Peach is considered a model organism among climacteric fruits in the Rosaceae family for studies on bud formation, dormancy, and organ differentiation. In our work, we have primarily established specific protocols for chromatin extraction and immunoprecipitation in reproductive tissues of peach (Prunus persica). Subsequently, we focused our investigations on the role of two chromatin marks, namely the trimethylation of histone H3 at lysine in position 4 (H3K4me3) and trimethylation of histone H3 at lysine 27 (H3K27me3) in modulating specific gene expression. Bud dormancy and fruit growth were investigated in a nectarine genotype called Fantasia as our model system. CONCLUSIONS We present general strategies to optimize ChIP protocols for buds and mesocarp tissues of peach and analyze the correlation between gene expression and chromatin mark enrichment/depletion. The procedures proposed may be useful to evaluate any involvement of histone modifications in the regulation of gene expression during bud dormancy progression and core ripening in fruits.
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Affiliation(s)
- Monica Canton
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, PD Italy
| | - Silvia Farinati
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, PD Italy
| | - Cristian Forestan
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna, Bologna, Italy
| | - Justin Joseph
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, PD Italy
| | - Claudio Bonghi
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, PD Italy
| | - Serena Varotto
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, PD Italy
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36
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Huang Y, Yang J, Liu X, Wang X, Zhu K, Ling Z, Zeng B, Chen N, Liu S, Wei F. Cationic Polymer Brush-Modified Carbon Nanotube-Meditated eRNA LINC02569 Silencing Attenuates Nucleus Pulposus Degeneration by Blocking NF-κB Signaling Pathway and Alleviate Cell Senescence. Front Cell Dev Biol 2022; 9:837777. [PMID: 35111765 PMCID: PMC8802762 DOI: 10.3389/fcell.2021.837777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 12/27/2021] [Indexed: 12/15/2022] Open
Abstract
Enhancer RNAs (eRNAs) are noncoding RNAs that synthesized at active enhancers. eRNAs have important regulatory characteristics and appear to be significant for maintenance of cell identity and information processing. Series of functional eRNAs have been identified as potential therapeutic targets for multiple diseases. Nevertheless, the role of eRNAs on intervertebral disc degeneration (IDD) is still unknown yet. Herein, we utilized the nucleus pulposus samples of patients and identified a key eRNA (LINC02569) with the Arraystar eRNA Microarray. LINC02569 mostly locates in nucleus and plays an important role in the progress of IDD by activating nuclear factor kappa-B (NF-κB) signaling pathway. We used a cationic polymer brush coated carbon nanotube (oCNT-pb)-based siRNA delivery platform that we previously designed, to transport LINC02569 siRNA (si-02569) to nucleus pulposus cells. The siRNA loaded oCNT-pb accumulated in nucleus pulposus cells with lower toxicity and higher transfection efficiency, compared with the traditional siRNA delivery system. Moreover, the results showed that the delivery of si-02569 significantly alleviated the inflammatory response in the nucleus pulposus cells via inhibiting P65 phosphorylation and preventing its transfer into the nucleus, and meanwhile alleviated cell senescence by decreasing the expression of P21. Altogether, our results highlight that eRNA (LINC02569) plays important role in the progression of IDD and could be a potential therapeutic target for alleviation of IDD.
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Affiliation(s)
- Yulin Huang
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Jiaming Yang
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Xizhe Liu
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology/Orthopaedic Research Institute, Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiaoshuai Wang
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Kai Zhu
- Orthopaedic Section II, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, China
| | - Zemin Ling
- Guangdong Provincial Key Laboratory of Orthopedics and Traumatology, Department of Spinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Baozhu Zeng
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Ningning Chen
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Shaoyu Liu
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Fuxin Wei
- Department of Orthopedics Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
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37
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Kitchen P, Gaston K, Jayaraman PS. Transcription Factor Chromatin Immunoprecipitation in Endothelial Cells. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2441:257-275. [PMID: 35099743 DOI: 10.1007/978-1-0716-2059-5_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Interactions between DNA and proteins are crucial for the regulation of gene expression. Chromatin immunoprecipitation (ChIP) is a powerful technique that allows the study of specific protein-DNA interactions in cultured cells and fresh or fixed tissue. Chromatin is isolated and sheared, and antibodies against the protein(s) of interest are used to isolate specific protein-DNA complexes. Subsequent analysis by real-time polymerase chain reaction (qPCR) or next-generation sequencing (NGS) allows identification and quantification of the co-purified DNA fragments, and NGS also gives insight into the genomic binding sites of a protein. Here we describe a cross-linking ChIP (X-ChIP) protocol, based around the example of a myc-tagged Proline-Rich Homeodomain (PRH) protein expressed in human umbilical vein endothelial cells. We also describe how to analyse specific known or suspected binding sites using quantitative PCR as well as how to analyse genome-wide binding from ChIP sequencing data.
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Affiliation(s)
- Philip Kitchen
- College of Health and Life Sciences, Aston University, Birmingham, UK
| | - Kevin Gaston
- Biodiscovery Institute and Division of Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Padma-Sheela Jayaraman
- Biodiscovery Institute and Division of Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
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Common Themes and Future Challenges in Understanding Gene Regulatory Network Evolution. Cells 2022; 11:cells11030510. [PMID: 35159319 PMCID: PMC8834487 DOI: 10.3390/cells11030510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/26/2022] [Accepted: 01/29/2022] [Indexed: 12/18/2022] Open
Abstract
A major driving force behind the evolution of species-specific traits and novel structures is alterations in gene regulatory networks (GRNs). Comprehending evolution therefore requires an understanding of the nature of changes in GRN structure and the responsible mechanisms. Here, we review two insect pigmentation GRNs in order to examine common themes in GRN evolution and to reveal some of the challenges associated with investigating changes in GRNs across different evolutionary distances at the molecular level. The pigmentation GRN in Drosophila melanogaster and other drosophilids is a well-defined network for which studies from closely related species illuminate the different ways co-option of regulators can occur. The pigmentation GRN for butterflies of the Heliconius species group is less fully detailed but it is emerging as a useful model for exploring important questions about redundancy and modularity in cis-regulatory systems. Both GRNs serve to highlight the ways in which redeployment of trans-acting factors can lead to GRN rewiring and network co-option. To gain insight into GRN evolution, we discuss the importance of defining GRN architecture at multiple levels both within and between species and of utilizing a range of complementary approaches.
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Deshpande N, Jordan R, Henderson Pozzi M, Bryk M. Histone 3 lysine 4 monomethylation supports activation of transcription in S. cerevisiae during nutrient stress. Curr Genet 2022; 68:181-194. [PMID: 35041077 PMCID: PMC8976815 DOI: 10.1007/s00294-022-01226-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 12/17/2021] [Accepted: 12/31/2021] [Indexed: 12/11/2022]
Abstract
Mono-methylation of the fourth lysine on the N-terminal tail of histone H3 was found to support the induction of RNA polymerase II transcription in S. cerevisiae during nutrient stress. In S. cerevisiae, the mono-, di- and tri-methylation of lysine 4 on histone H3 (H3K4) is catalyzed by the protein methyltransferase, Set1. The three distinct methyl marks on H3K4 act in discrete ways to regulate transcription. Nucleosomes enriched with tri-methylated H3K4 are usually associated with active transcription whereas di-methylated H3K4 is associated with gene repression. Mono-methylated H3K4 has been shown to repress gene expression in S. cerevisiae and is detected at enhancers and promoters in eukaryotes. S. cerevisiae set1Δ mutants unable to methylate H3K4 exhibit growth defects during histidine starvation. The growth defects are rescued by either a wild-type allele of SET1 or partial-function alleles of set1, including a mutant that predominantly generates H3K4me1 and not H3K4me3. Rescue of the growth defect is associated with induction of the HIS3 gene. Growth defects observed when set1Δ cultures were starved for isoleucine and valine were also rescued by wild-type SET1 or partial-function set1 alleles. The results show that H3K4me1, in the absence of H3K4me3, supports transcription of the HIS3 gene and expression of one or more of the genes required for biosynthesis of isoleucine and valine during nutrient stress. Set1-like methyltransferases are evolutionarily conserved, and research has linked their functions to developmental gene regulation and several cancers in higher eukaryotes. Identification of mechanisms of H3K4me1-mediated activation of transcription in budding yeast will provide insight into gene regulation in all eukaryotes.
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Affiliation(s)
- Neha Deshpande
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, TX, 77843, USA
| | - Rachel Jordan
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, TX, 77843, USA
- iBio, 8800 HSC Blvd, Bryan, TX, 77807, USA
| | - Michelle Henderson Pozzi
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, TX, 77843, USA
| | - Mary Bryk
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, TX, 77843, USA.
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40
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Byers C, Spruce C, Fortin HJ, Hartig EI, Czechanski A, Munger SC, Reinholdt LG, Skelly DA, Baker CL. Genetic control of the pluripotency epigenome determines differentiation bias in mouse embryonic stem cells. EMBO J 2022; 41:e109445. [PMID: 34931323 PMCID: PMC8762565 DOI: 10.15252/embj.2021109445] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 11/01/2021] [Accepted: 11/16/2021] [Indexed: 02/03/2023] Open
Abstract
Genetically diverse pluripotent stem cells display varied, heritable responses to differentiation cues. Here, we harnessed these disparities through derivation of mouse embryonic stem cells from the BXD genetic reference panel, along with C57BL/6J (B6) and DBA/2J (D2) parental strains, to identify loci regulating cell state transitions. Upon transition to formative pluripotency, B6 stem cells quickly dissolved naïve networks adopting gene expression modules indicative of neuroectoderm lineages, whereas D2 retained aspects of naïve pluripotency. Spontaneous formation of embryoid bodies identified divergent differentiation where B6 showed a propensity toward neuroectoderm and D2 toward definitive endoderm. Genetic mapping identified major trans-acting loci co-regulating chromatin accessibility and gene expression in both naïve and formative pluripotency. These loci distally modulated occupancy of pluripotency factors at hundreds of regulatory elements. One trans-acting locus on Chr 12 primarily impacted chromatin accessibility in embryonic stem cells, while in epiblast-like cells, the same locus subsequently influenced expression of genes enriched for neurogenesis, suggesting early chromatin priming. These results demonstrate genetically determined biases in lineage commitment and identify major regulators of the pluripotency epigenome.
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Affiliation(s)
- Candice Byers
- The Jackson LaboratoryBar HarborMEUSA,Graduate School of Biomedical SciencesTufts UniversityBostonMAUSA
| | | | - Haley J Fortin
- The Jackson LaboratoryBar HarborMEUSA,Graduate School of Biomedical SciencesTufts UniversityBostonMAUSA
| | - Ellen I Hartig
- The Jackson LaboratoryBar HarborMEUSA,Graduate School of Biomedical SciencesTufts UniversityBostonMAUSA
| | | | - Steven C Munger
- The Jackson LaboratoryBar HarborMEUSA,Graduate School of Biomedical SciencesTufts UniversityBostonMAUSA
| | | | | | - Christopher L Baker
- The Jackson LaboratoryBar HarborMEUSA,Graduate School of Biomedical SciencesTufts UniversityBostonMAUSA
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41
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Osterwalder M, Tran S, Hunter RD, Meky EM, von Maydell K, Harrington AN, Godoy J, Novak CS, Plajzer-Frick I, Zhu Y, Akiyama JA, Afzal V, Kvon EZ, Pennacchio LA, Dickel DE, Visel A. Characterization of Mammalian In Vivo Enhancers Using Mouse Transgenesis and CRISPR Genome Editing. Methods Mol Biol 2022; 2403:147-186. [PMID: 34913122 DOI: 10.1007/978-1-0716-1847-9_11] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Embryonic morphogenesis is strictly dependent on tight spatiotemporal control of developmental gene expression, which is typically achieved through the concerted activity of multiple enhancers driving cell type-specific expression of a target gene. Mammalian genomes are organized in topologically associated domains, providing a preferred environment and framework for interactions between transcriptional enhancers and gene promoters. While epigenomic profiling and three-dimensional chromatin conformation capture have significantly increased the accuracy of identifying enhancers, assessment of subregional enhancer activities via transgenic reporter assays in mice remains the gold standard for assigning enhancer activity in vivo. Once this activity is defined, the ideal method to explore the functional necessity of a transcriptional enhancer and its contribution to target gene dosage and morphological or physiological processes is deletion of the enhancer sequence from the mouse genome. Here we present detailed protocols for efficient introduction of enhancer-reporter transgenes and CRISPR-mediated genomic deletions into the mouse genome, including a step-by-step guide for pronuclear microinjection of fertilized mouse eggs. We provide instructions for the assembly and genomic integration of enhancer-reporter cassettes that have been used for validation of thousands of putative enhancer sequences accessible through the VISTA enhancer browser, including a recently published method for robust site-directed transgenesis at the H11 safe-harbor locus. Together, these methods enable rapid and large-scale assessment of enhancer activities and sequence variants in mice, which is essential to understand mammalian genome function and genetic diseases.
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Affiliation(s)
- Marco Osterwalder
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department for BioMedical Research (DBMR), University of Bern, Bern, Switzerland
| | - Stella Tran
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Riana D Hunter
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Eman M Meky
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Kianna von Maydell
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Anne N Harrington
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Janeth Godoy
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Catherine S Novak
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ingrid Plajzer-Frick
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Yiwen Zhu
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Jennifer A Akiyama
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Veena Afzal
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Evgeny Z Kvon
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA.
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- US Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- School of Natural Sciences, University of California, Merced, Merced, CA, USA.
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42
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Giacopuzzi E, Popitsch N, Taylor JC. OUP accepted manuscript. Nucleic Acids Res 2022; 50:2522-2535. [PMID: 35234913 PMCID: PMC8934622 DOI: 10.1093/nar/gkac130] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 02/02/2022] [Accepted: 02/14/2022] [Indexed: 11/25/2022] Open
Abstract
Non-coding variants have long been recognized as important contributors to common disease risks, but with the expansion of clinical whole genome sequencing, examples of rare, high-impact non-coding variants are also accumulating. Despite recent advances in the study of regulatory elements and the availability of specialized data collections, the systematic annotation of non-coding variants from genome sequencing remains challenging. Here, we propose a new framework for the prioritization of non-coding regulatory variants that integrates information about regulatory regions with prediction scores and HPO-based prioritization. Firstly, we created a comprehensive collection of annotations for regulatory regions including a database of 2.4 million regulatory elements (GREEN-DB) annotated with controlled gene(s), tissue(s) and associated phenotype(s) where available. Secondly, we calculated a variation constraint metric and showed that constrained regulatory regions associate with disease-associated genes and essential genes from mouse knock-outs. Thirdly, we compared 19 non-coding impact prediction scores providing suggestions for variant prioritization. Finally, we developed a VCF annotation tool (GREEN-VARAN) that can integrate all these elements to annotate variants for their potential regulatory impact. In our evaluation, we show that GREEN-DB can capture previously published disease-associated non-coding variants as well as identify additional candidate disease genes in trio analyses.
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Affiliation(s)
- Edoardo Giacopuzzi
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford OX4 2PG, UK
| | - Niko Popitsch
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Max Perutz Labs, University of Vienna, Dr. Bohr-Gasse 9, 1030 Vienna, Austria
| | - Jenny C Taylor
- To whom correspondence should be addressed. Tel: +44 01865 287631;
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43
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Karr JP, Ferrie JJ, Tjian R, Darzacq X. The transcription factor activity gradient (TAG) model: contemplating a contact-independent mechanism for enhancer-promoter communication. Genes Dev 2022; 36:7-16. [PMID: 34969825 PMCID: PMC8763055 DOI: 10.1101/gad.349160.121] [Citation(s) in RCA: 67] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
How distal cis-regulatory elements (e.g., enhancers) communicate with promoters remains an unresolved question of fundamental importance. Although transcription factors and cofactors are known to mediate this communication, the mechanism by which diffusible molecules relay regulatory information from one position to another along the chromosome is a biophysical puzzle-one that needs to be revisited in light of recent data that cannot easily fit into previous solutions. Here we propose a new model that diverges from the textbook enhancer-promoter looping paradigm and offer a synthesis of the literature to make a case for its plausibility, focusing on the coactivator p300.
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Affiliation(s)
- Jonathan P Karr
- University of California at Berkeley, Berkeley, California 94720, USA
| | - John J Ferrie
- University of California at Berkeley, Berkeley, California 94720, USA
- Howard Hughes Medical Institute, Berkeley, California 94720, USA
| | - Robert Tjian
- University of California at Berkeley, Berkeley, California 94720, USA
- Howard Hughes Medical Institute, Berkeley, California 94720, USA
| | - Xavier Darzacq
- University of California at Berkeley, Berkeley, California 94720, USA
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44
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Miller EC, Wilczek A, Bello NA, Tom S, Wapner R, Suh Y. Pregnancy, preeclampsia and maternal aging: From epidemiology to functional genomics. Ageing Res Rev 2022; 73:101535. [PMID: 34871806 PMCID: PMC8827396 DOI: 10.1016/j.arr.2021.101535] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 11/15/2021] [Accepted: 12/01/2021] [Indexed: 01/03/2023]
Abstract
Women live longer than men but experience greater disability and a longer period of illness as they age. Despite clear sex differences in aging, the impact of pregnancy and its complications, such as preeclampsia, on aging is an underexplored area of geroscience. This review summarizes our current knowledge about the complex links between pregnancy and age-related diseases, including evidence from epidemiology, clinical research, and genetics. We discuss the relationship between normal and pathological pregnancy and maternal aging, using preeclampsia as a primary example. We review the results of human genetics studies of preeclampsia, including genome wide association studies (GWAS), and attempted to catalog genes involved in preeclampsia as a gateway to mechanisms underlying an increased risk of later life cardio- and neuro- vascular events. Lastly, we discuss challenges in interpreting the GWAS of preeclampsia and provide a functional genomics framework for future research needed to fully realize the promise of GWAS in identifying targets for geroprotective prevention and therapeutics against preeclampsia.
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Affiliation(s)
- Eliza C. Miller
- Department of Neurology, Division of Stroke and Cerebrovascular Disease, Columbia University Irving Medical Center, New York, NY, USA
| | - Ashley Wilczek
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA
| | - Natalie A. Bello
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sarah Tom
- Department of Neurology, Division of Neurology Clinical Outcomes Research and Population Science and the Department of Epidemiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA.
| | - Yousin Suh
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA.
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45
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Farrell CM, Goldfarb T, Rangwala SH, Astashyn A, Ermolaeva OD, Hem V, Katz KS, Kodali VK, Ludwig F, Wallin CL, Pruitt KD, Murphy TD. RefSeq Functional Elements as experimentally assayed nongenic reference standards and functional interactions in human and mouse. Genome Res 2021; 32:175-188. [PMID: 34876495 PMCID: PMC8744684 DOI: 10.1101/gr.275819.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 12/02/2021] [Indexed: 11/25/2022]
Abstract
Eukaryotic genomes contain many nongenic elements that function in gene regulation, chromosome organization, recombination, repair, or replication, and mutation of those elements can affect genome function and cause disease. Although numerous epigenomic studies provide high coverage of gene regulatory regions, those data are not usually exposed in traditional genome annotation and can be difficult to access and interpret without field-specific expertise. The National Center for Biotechnology Information (NCBI) therefore provides RefSeq Functional Elements (RefSeqFEs), which represent experimentally validated human and mouse nongenic elements derived from the literature. The curated data set is comprised of richly annotated sequence records, descriptive records in the NCBI Gene database, reference genome feature annotation, and activity-based interactions between nongenic regions, target genes, and each other. The data set provides succinct functional details and transparent experimental evidence, leverages data from multiple experimental sources, is readily accessible and adaptable, and uses a flexible data model. The data have multiple uses for basic functional discovery, bioinformatics studies, genetic variant interpretation; as known positive controls for epigenomic data evaluation; and as reference standards for functional interactions. Comparisons to other gene regulatory data sets show that the RefSeqFE data set includes a wider range of feature types representing more areas of biology, but it is comparatively smaller and subject to data selection biases. RefSeqFEs thus provide an alternative and complementary resource for experimentally assayed functional elements, with future data set growth expected.
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Affiliation(s)
- Catherine M Farrell
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Tamara Goldfarb
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Sanjida H Rangwala
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Alexander Astashyn
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Olga D Ermolaeva
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Vichet Hem
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Kenneth S Katz
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Vamsi K Kodali
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Frank Ludwig
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Craig L Wallin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Kim D Pruitt
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Terence D Murphy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
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46
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Klöppel C, Hildebrandt K, Kolb D, Fürst N, Bley I, Karlowatz RJ, Walldorf U. Functional analysis of enhancer elements regulating the expression of the Drosophila homeodomain transcription factor DRx by gene targeting. Hereditas 2021; 158:42. [PMID: 34736520 PMCID: PMC8569992 DOI: 10.1186/s41065-021-00210-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 10/18/2021] [Indexed: 11/17/2022] Open
Abstract
Background The Drosophila brain is an ideal model system to study stem cells, here called neuroblasts, and the generation of neural lineages. Many transcriptional activators are involved in formation of the brain during the development of Drosophila melanogaster. The transcription factor Drosophila Retinal homeobox (DRx), a member of the 57B homeobox gene cluster, is also one of these factors for brain development. Results In this study a detailed expression analysis of DRx in different developmental stages was conducted. We show that DRx is expressed in the embryonic brain in the protocerebrum, in the larval brain in the DM and DL lineages, the medulla and the lobula complex and in the central complex of the adult brain. We generated a DRx enhancer trap strain by gene targeting and reintegration of Gal4, which mimics the endogenous expression of DRx. With the help of eight existing enhancer-Gal4 strains and one made by our group, we mapped various enhancers necessary for the expression of DRx during all stages of brain development from the embryo to the adult. We made an analysis of some larger enhancer regions by gene targeting. Deletion of three of these enhancers showing the most prominent expression patterns in the brain resulted in specific temporal and spatial loss of DRx expression in defined brain structures. Conclusion Our data show that DRx is expressed in specific neuroblasts and defined neural lineages and suggest that DRx is another important factor for Drosophila brain development. Supplementary Information The online version contains supplementary material available at 10.1186/s41065-021-00210-z.
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Affiliation(s)
- Christine Klöppel
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
| | - Kirsten Hildebrandt
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
| | - Dieter Kolb
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
| | - Nora Fürst
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany.,Present address: Genetics/Epigenetics, Saarland University, Building A2.4, 66123, Saarbrücken, Germany
| | - Isabelle Bley
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany.,Present address: Research Institute Children's Cancer Center Hamburg, Building N63, Martinistr. 52, 20251, Hamburg, Germany
| | | | - Uwe Walldorf
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany.
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47
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Hildebrandt K, Kübel S, Minet M, Fürst N, Klöppel C, Steinmetz E, Walldorf U. Enhancer analysis of the Drosophila zinc finger transcription factor Earmuff by gene targeting. Hereditas 2021; 158:41. [PMID: 34732265 PMCID: PMC8567707 DOI: 10.1186/s41065-021-00209-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 10/08/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Many transcription factors are involved in the formation of the brain during the development of Drosophila melanogaster. The transcription factor Earmuff (Erm), a member of the forebrain embryonic zinc finger family (Fezf), is one of these important factors for brain development. One major function of Earmuff is the regulation of proliferation within type II neuroblast lineages in the brain; here, Earmuff is expressed in intermediate neural progenitor cells (INPs) and balances neuronal differentiation versus stem cell maintenance. Erm expression during development is regulated by several enhancers. RESULTS In this work we show a functional analysis of erm and some of its enhancers. We generated a new erm mutant allele by gene targeting and reintegrated Gal4 to make an erm enhancer trap strain that could also be used on an erm mutant background. The deletion of three of the previously analysed enhancers showing the most prominent expression patterns of erm by gene targeting resulted in specific temporal and spatial defects in defined brain structures. These defects were already known but here could be assigned to specific enhancer regions. CONCLUSION This analysis is to our knowledge the first systematic analysis of several large enhancer deletions of a Drosophila gene by gene targeting and will enable deeper analysis of erm enhancer functions in the future.
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Affiliation(s)
- Kirsten Hildebrandt
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
| | - Sabrina Kübel
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
- Present address: Clinical and Molecular Virology, Friedrich-Alexander University, 91054, Erlangen, Germany
| | - Marie Minet
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
- Present address: Human Genetics, Saarland University, Building 60, 66421, Homburg/Saar, Germany
| | - Nora Fürst
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
- Present address: Genetics/Epigenetics, Saarland University, Building A2.4, 66123, Saarbrücken, Germany
| | - Christine Klöppel
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
| | - Eva Steinmetz
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany
- Present address: Zoology and Physiology, Saarland University, Building B2.1, 66123, Saarbrücken, Germany
| | - Uwe Walldorf
- Developmental Biology, Saarland University, Building 61, 66421, Homburg/Saar, Germany.
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48
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The non-coding genome in genetic brain disorders: new targets for therapy? Essays Biochem 2021; 65:671-683. [PMID: 34414418 PMCID: PMC8564736 DOI: 10.1042/ebc20200121] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 07/12/2021] [Accepted: 07/26/2021] [Indexed: 11/30/2022]
Abstract
The non-coding genome, consisting of more than 98% of all genetic information in humans and once judged as ‘Junk DNA’, is increasingly moving into the spotlight in the field of human genetics. Non-coding regulatory elements (NCREs) are crucial to ensure correct spatio-temporal gene expression. Technological advancements have allowed to identify NCREs on a large scale, and mechanistic studies have helped to understand the biological mechanisms underlying their function. It is increasingly becoming clear that genetic alterations of NCREs can cause genetic disorders, including brain diseases. In this review, we concisely discuss mechanisms of gene regulation and how to investigate them, and give examples of non-coding alterations of NCREs that give rise to human brain disorders. The cross-talk between basic and clinical studies enhances the understanding of normal and pathological function of NCREs, allowing better interpretation of already existing and novel data. Improved functional annotation of NCREs will not only benefit diagnostics for patients, but might also lead to novel areas of investigations for targeted therapies, applicable to a wide panel of genetic disorders. The intrinsic complexity and precision of the gene regulation process can be turned to the advantage of highly specific treatments. We further discuss this exciting new field of ‘enhancer therapy’ based on recent examples.
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49
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Global patterns of enhancer activity during sea urchin embryogenesis assessed by eRNA profiling. Genome Res 2021; 31:1680-1692. [PMID: 34330790 PMCID: PMC8415375 DOI: 10.1101/gr.275684.121] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 07/28/2021] [Indexed: 11/25/2022]
Abstract
We used capped analysis of gene expression with sequencing (CAGE-seq) to profile eRNA expression and enhancer activity during embryogenesis of a model echinoderm: the sea urchin, Strongylocentrotus purpuratus. We identified more than 18,000 enhancers that were active in mature oocytes and developing embryos and documented a burst of enhancer activation during cleavage and early blastula stages. We found that a large fraction (73.8%) of all enhancers active during the first 48 h of embryogenesis were hyperaccessible no later than the 128-cell stage and possibly even earlier. Most enhancers were located near gene bodies, and temporal patterns of eRNA expression tended to parallel those of nearby genes. Furthermore, enhancers near lineage-specific genes contained signatures of inputs from developmental gene regulatory networks deployed in those lineages. A large fraction (60%) of sea urchin enhancers previously shown to be active in transgenic reporter assays was associated with eRNA expression. Moreover, a large fraction (50%) of a representative subset of enhancers identified by eRNA profiling drove tissue-specific gene expression in isolation when tested by reporter assays. Our findings provide an atlas of developmental enhancers in a model sea urchin and support the utility of eRNA profiling as a tool for enhancer discovery and regulatory biology. The data generated in this study are available at Echinobase, the public database of information related to echinoderm genomics.
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50
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Meng F, Zhao H, Zhu B, Zhang T, Yang M, Li Y, Han Y, Jiang J. Genomic editing of intronic enhancers unveils their role in fine-tuning tissue-specific gene expression in Arabidopsis thaliana. THE PLANT CELL 2021; 33:1997-2014. [PMID: 33764459 PMCID: PMC8290289 DOI: 10.1093/plcell/koab093] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 03/23/2021] [Indexed: 05/22/2023]
Abstract
Enhancers located in introns are abundant and play a major role in the regulation of gene expression in mammalian species. By contrast, the functions of intronic enhancers in plants have largely been unexplored and only a handful of plant intronic enhancers have been reported. We performed a genome-wide prediction of intronic enhancers in Arabidopsis thaliana using open chromatin signatures based on DNase I sequencing. We identified 941 candidate intronic enhancers associated with 806 genes in seedling tissue and 1,271 intronic enhancers associated with 1,069 genes in floral tissue. We validated the function of 15 of 21 (71%) of the predicted intronic enhancers in transgenic assays using a reporter gene. We also created deletion lines of three intronic enhancers associated with two different genes using CRISPR/Cas. Deletion of these enhancers, which span key transcription factor binding sites, did not abolish gene expression but caused varying levels of transcriptional repression of their cognate genes. Remarkably, the transcriptional repression of the deletion lines occurred at specific developmental stages and resulted in distinct phenotypic effects on plant morphology and development. Clearly, these three intronic enhancers are important in fine-tuning tissue- and development-specific expression of their cognate genes.
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Affiliation(s)
- Fanli Meng
- Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin 150030, China
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Hainan Zhao
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Bo Zhu
- Department of Biological Science, College of Life Sciences, Sichuan Normal University, Chengdu, Sichuan 610101, China
| | - Tao Zhang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of Ministry of Education, Yangzhou University, Yangzhou, Jiangsu 225009, China
| | - Mingyu Yang
- Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin 150030, China
| | - Yang Li
- Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin 150030, China
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, Harbin 150030, China
| | - Jiming Jiang
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
- Department of Horticulture, Michigan State University, East Lansing, MI 48824, USA
- Michigan State University AgBioResearch, East Lansing, MI 48824, USA
- Author for correspondence:
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