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Zhang Y, Li D, Cai Y, Zou R, Zhang Y, Deng X, Wang Y, Tang T, Ma Y, Wu F, Xie Y. Astrocyte allocation during brain development is controlled by Tcf4-mediated fate restriction. EMBO J 2024:10.1038/s44318-024-00218-x. [PMID: 39300210 DOI: 10.1038/s44318-024-00218-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/22/2024] Open
Abstract
Astrocytes in the brain exhibit regional heterogeneity contributing to regional circuits involved in higher-order brain functions, yet the mechanisms controlling their distribution remain unclear. Here, we show that the precise allocation of astrocytes to specific brain regions during development is achieved through transcription factor 4 (Tcf4)-mediated fate restriction based on their embryonic origin. Loss of Tcf4 in ventral telencephalic neural progenitor cells alters the fate of oligodendrocyte precursor cells to transient intermediate astrocyte precursor cells, resulting in mislocalized astrocytes in the dorsal neocortex. These ectopic astrocytes engage with neocortical neurons and acquire features reminiscent of dorsal neocortical astrocytes. Furthermore, Tcf4 functions as a suppressor of astrocyte fate during the differentiation of oligodendrocyte precursor cells derived from the ventral telencephalon, thereby restricting the fate to the oligodendrocyte lineage in the dorsal neocortex. Together, our findings highlight a previously unappreciated role for Tcf4 in regulating astrocyte allocation, offering additional insights into the mechanisms underlying neurodevelopmental disorders linked to Tcf4 mutations.
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Affiliation(s)
- Yandong Zhang
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Dan Li
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuqun Cai
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Rui Zou
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yilan Zhang
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xin Deng
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yafei Wang
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Tianxiang Tang
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuanyuan Ma
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Feizhen Wu
- Laboratory of Epi-Informatics, Intelligent Medicine Institute of Fudan University, Shanghai, 200032, China
| | - Yunli Xie
- Department of Anesthesia, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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2
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Ocampo D, Damon LJ, Sanford L, Holtzen SE, Jones T, Allen MA, Dowell RD, Palmer AE. Cellular zinc status alters chromatin accessibility and binding of p53 to DNA. Life Sci Alliance 2024; 7:e202402638. [PMID: 38969365 PMCID: PMC11231577 DOI: 10.26508/lsa.202402638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/07/2024] Open
Abstract
Zn2+ is an essential metal required by approximately 850 human transcription factors. How these proteins acquire their essential Zn2+ cofactor and whether they are sensitive to changes in the labile Zn2+ pool in cells remain open questions. Using ATAC-seq to profile regions of accessible chromatin coupled with transcription factor enrichment analysis, we examined how increases and decreases in the labile zinc pool affect chromatin accessibility and transcription factor enrichment. We found 685 transcription factor motifs were differentially enriched, corresponding to 507 unique transcription factors. The pattern of perturbation and the types of transcription factors were notably different at promoters versus intergenic regions, with zinc-finger transcription factors strongly enriched in intergenic regions in elevated Zn2+ To test whether ATAC-seq and transcription factor enrichment analysis predictions correlate with changes in transcription factor binding, we used ChIP-qPCR to profile six p53 binding sites. We found that for five of the six targets, p53 binding correlates with the local accessibility determined by ATAC-seq. These results demonstrate that changes in labile zinc alter chromatin accessibility and transcription factor binding to DNA.
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Affiliation(s)
- Daniel Ocampo
- Department of Biochemistry, University of Colorado, Boulder, CO, USA
| | - Leah J Damon
- Department of Biochemistry, University of Colorado, Boulder, CO, USA
| | - Lynn Sanford
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Samuel E Holtzen
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Taylor Jones
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Mary A Allen
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, CO, USA
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Robin D Dowell
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, CO, USA
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Amy E Palmer
- Department of Biochemistry, University of Colorado, Boulder, CO, USA
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
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3
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Lu Z, Xiao X, Zheng Q, Wang X, Xu L. Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets. Brief Bioinform 2024; 25:bbae366. [PMID: 39082650 PMCID: PMC11289684 DOI: 10.1093/bib/bbae366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 06/21/2024] [Accepted: 07/18/2024] [Indexed: 08/03/2024] Open
Abstract
This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.
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Affiliation(s)
- Zeyu Lu
- Department of Statistics and Data Science, Moody School of Graduate and Advanced Studies, Southern Methodist University, 3225 Daniel Ave., P.O. Box 750332, Dallas, TX, United States
| | - Xue Xiao
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, United States
| | - Qiang Zheng
- Division of Data Science, College of Science, University of Texas at Arlington, 501 S. Nedderman Dr., Arlington, TX 76019, United States
| | - Xinlei Wang
- Division of Data Science, College of Science, University of Texas at Arlington, 501 S. Nedderman Dr., Arlington, TX 76019, United States
- Department of Mathematics, University of Texas at Arlington, 411 S. Nedderman Dr., Arlington, TX 76019, United States
| | - Lin Xu
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, United States
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States
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4
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Farzad N, Enninful A, Bao S, Zhang D, Deng Y, Fan R. Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue. Nat Protoc 2024:10.1038/s41596-024-01013-y. [PMID: 38943021 DOI: 10.1038/s41596-024-01013-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 04/11/2024] [Indexed: 06/30/2024]
Abstract
Spatial epigenetic mapping of tissues enables the study of gene regulation programs and cellular functions with the dependency on their local tissue environment. Here we outline a complete procedure for two spatial epigenomic profiling methods: spatially resolved genome-wide profiling of histone modifications using in situ cleavage under targets and tagmentation (CUT&Tag) chemistry (spatial-CUT&Tag) and transposase-accessible chromatin sequencing (spatial-ATAC-sequencing) for chromatin accessibility. Both assays utilize in-tissue Tn5 transposition to recognize genomic DNA loci followed by microfluidic deterministic barcoding to incorporate spatial address codes. Furthermore, these two methods do not necessitate prior knowledge of the transcription or epigenetic markers for a given tissue or cell type but permit genome-wide unbiased profiling pixel-by-pixel at the 10 μm pixel size level and single-base resolution. To support the widespread adaptation of these methods, details are provided in five general steps: (1) sample preparation; (2) Tn5 transposition in spatial-ATAC-sequencing or antibody-controlled pA-Tn5 tagmentation in CUT&Tag; (3) library preparation; (4) next-generation sequencing; and (5) data analysis using our customed pipelines available at: https://github.com/dyxmvp/Spatial_ATAC-seq and https://github.com/dyxmvp/spatial-CUT-Tag . The whole procedure can be completed on four samples in 2-3 days. Familiarity with basic molecular biology and bioinformatics skills with access to a high-performance computing environment are required. A rudimentary understanding of pathology and specimen sectioning, as well as deterministic barcoding in tissue-specific skills (e.g., design of a multiparameter barcode panel and creation of microfluidic devices), are also advantageous. In this protocol, we mainly focus on spatial profiling of tissue region-specific epigenetic landscapes in mouse embryos and mouse brains using spatial-ATAC-sequencing and spatial-CUT&Tag, but these methods can be used for other species with no need for species-specific probe design.
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Affiliation(s)
- Negin Farzad
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Archibald Enninful
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Shuozhen Bao
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Di Zhang
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Yanxiang Deng
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Pennsylvania, PA, USA
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
- Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT, USA.
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5
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Lu Z, Xiao X, Zheng Q, Wang X, Xu L. Assessing NGS-based computational methods for predicting transcriptional regulators with query gene sets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578316. [PMID: 38562775 PMCID: PMC10983863 DOI: 10.1101/2024.02.01.578316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
This article provides an in-depth review of computational methods for predicting transcriptional regulators with query gene sets. Identification of transcriptional regulators is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement. Key points An introduction to available computational methods for predicting functional TRs from a query gene set.A detailed walk-through along with practical concerns and limitations.A systematic benchmark of NGS-based methods in terms of accuracy, sensitivity, coverage, and usability, using 570 TR perturbation-derived gene sets.NGS-based methods outperform motif-based methods. Among NGS methods, those utilizing larger databases and adopting region-centric approaches demonstrate favorable performance. BART, ChIP-Atlas, and Lisa are recommended as these methods have overall better performance in evaluated scenarios.
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6
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Pappas MP, Kawakami H, Corcoran D, Chen KQ, Scott EP, Wong J, Gearhart MD, Nishinakamura R, Nakagawa Y, Kawakami Y. Sall4 regulates posterior trunk mesoderm development by promoting mesodermal gene expression and repressing neural genes in the mesoderm. Development 2024; 151:dev202649. [PMID: 38345319 PMCID: PMC10946440 DOI: 10.1242/dev.202649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 01/30/2024] [Indexed: 03/05/2024]
Abstract
The trunk axial skeleton develops from paraxial mesoderm cells. Our recent study demonstrated that conditional knockout of the stem cell factor Sall4 in mice by TCre caused tail truncation and a disorganized axial skeleton posterior to the lumbar level. Based on this phenotype, we hypothesized that, in addition to the previously reported role of Sall4 in neuromesodermal progenitors, Sall4 is involved in the development of the paraxial mesoderm tissue. Analysis of gene expression and SALL4 binding suggests that Sall4 directly or indirectly regulates genes involved in presomitic mesoderm differentiation, somite formation and somite differentiation. Furthermore, ATAC-seq in TCre; Sall4 mutant posterior trunk mesoderm shows that Sall4 knockout reduces chromatin accessibility. We found that Sall4-dependent open chromatin status drives activation and repression of WNT signaling activators and repressors, respectively, to promote WNT signaling. Moreover, footprinting analysis of ATAC-seq data suggests that Sall4-dependent chromatin accessibility facilitates CTCF binding, which contributes to the repression of neural genes within the mesoderm. This study unveils multiple mechanisms by which Sall4 regulates paraxial mesoderm development by directing activation of mesodermal genes and repression of neural genes.
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Affiliation(s)
- Matthew P. Pappas
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Hiroko Kawakami
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
- Stem Cell Institute, University of Minnesota, Minneapolis, MN 55455, USA
- Developmental Biology Center, University of Minnesota, Minneapolis, MN 55455, USA
| | - Dylan Corcoran
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Katherine Q. Chen
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Earl Parker Scott
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Julia Wong
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Micah D. Gearhart
- Developmental Biology Center, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Obstetrics, Gynecology and Women's Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Ryuichi Nishinakamura
- Department of Kidney Development, Institute of Molecular Embryology and Genetics, Kumamoto University, Kumamoto 860-0811, Japan
| | - Yasushi Nakagawa
- Stem Cell Institute, University of Minnesota, Minneapolis, MN 55455, USA
- Developmental Biology Center, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Yasuhiko Kawakami
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
- Stem Cell Institute, University of Minnesota, Minneapolis, MN 55455, USA
- Developmental Biology Center, University of Minnesota, Minneapolis, MN 55455, USA
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7
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Damon LJ, Ocampo D, Sanford L, Jones T, Allen MA, Dowell RD, Palmer AE. Cellular zinc status alters chromatin accessibility and binding of transcription factor p53 to genomic sites. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.20.567954. [PMID: 38045276 PMCID: PMC10690171 DOI: 10.1101/2023.11.20.567954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Zinc (Zn2+) is an essential metal required by approximately 2500 proteins. Nearly half of these proteins act on DNA, including > 850 human transcription factors, polymerases, DNA damage response factors, and proteins involved in chromatin architecture. How these proteins acquire their essential Zn2+ cofactor and whether they are sensitive to changes in the labile Zn2+ pool in cells remain open questions. Here, we examine how changes in the labile Zn2+ pool affect chromatin accessibility and transcription factor binding to DNA. We observed both increases and decreases in accessibility in different chromatin regions via ATAC-seq upon treating MCF10A cells with elevated Zn2+ or the Zn2+-specific chelator tris(2-pyridylmethyl)amine (TPA). Transcription factor enrichment analysis was used to correlate changes in chromatin accessibility with transcription factor motifs, revealing 477 transcription factor motifs that were differentially enriched upon Zn2+ perturbation. 186 of these transcription factor motifs were enriched in Zn2+ and depleted in TPA, and the majority correspond to Zn2+ finger transcription factors. We selected TP53 as a candidate to examine how changes in motif enrichment correlate with changes in transcription factor occupancy by ChIP-qPCR. Using publicly available ChIP-seq and nascent transcription datasets, we narrowed the 50,000+ ATAC-seq peaks to 2164 TP53 targets and subsequently selected 6 high-probability TP53 binding sites for testing. ChIP-qPCR revealed that for 5 of the 6 targets, TP53 binding correlates with the local accessibility determined by ATAC-seq. These results demonstrate that changes in labile zinc directly alter chromatin accessibility and transcription factor binding to DNA.
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Affiliation(s)
- Leah J. Damon
- Department of Biochemistry, University of Colorado, Boulder, CO 80303
| | - Daniel Ocampo
- Department of Biochemistry, University of Colorado, Boulder, CO 80303
| | - Lynn Sanford
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, 80309
| | - Taylor Jones
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, 80309
| | - Mary A. Allen
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, 80309
- BioFrontiers Institute, University of Colorado, Boulder, CO 80303
| | - Robin D. Dowell
- Department of Molecular, Cellular, Developmental Biology, University of Colorado, Boulder, 80309
- BioFrontiers Institute, University of Colorado, Boulder, CO 80303
| | - Amy E. Palmer
- Department of Biochemistry, University of Colorado, Boulder, CO 80303
- BioFrontiers Institute, University of Colorado, Boulder, CO 80303
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Nair S, Ameen M, Sundaram L, Pampari A, Schreiber J, Balsubramani A, Wang YX, Burns D, Blau HM, Karakikes I, Wang KC, Kundaje A. Transcription factor stoichiometry, motif affinity and syntax regulate single-cell chromatin dynamics during fibroblast reprogramming to pluripotency. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.04.560808. [PMID: 37873116 PMCID: PMC10592962 DOI: 10.1101/2023.10.04.560808] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Ectopic expression of OCT4, SOX2, KLF4 and MYC (OSKM) transforms differentiated cells into induced pluripotent stem cells. To refine our mechanistic understanding of reprogramming, especially during the early stages, we profiled chromatin accessibility and gene expression at single-cell resolution across a densely sampled time course of human fibroblast reprogramming. Using neural networks that map DNA sequence to ATAC-seq profiles at base-resolution, we annotated cell-state-specific predictive transcription factor (TF) motif syntax in regulatory elements, inferred affinity- and concentration-dependent dynamics of Tn5-bias corrected TF footprints, linked peaks to putative target genes, and elucidated rewiring of TF-to-gene cis-regulatory networks. Our models reveal that early in reprogramming, OSK, at supraphysiological concentrations, rapidly open transient regulatory elements by occupying non-canonical low-affinity binding sites. As OSK concentration falls, the accessibility of these transient elements decays as a function of motif affinity. We find that these OSK-dependent transient elements sequester the somatic TF AP-1. This redistribution is strongly associated with the silencing of fibroblast-specific genes within individual nuclei. Together, our integrated single-cell resource and models reveal insights into the cis-regulatory code of reprogramming at unprecedented resolution, connect TF stoichiometry and motif syntax to diversification of cell fate trajectories, and provide new perspectives on the dynamics and role of transient regulatory elements in somatic silencing.
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Affiliation(s)
- Surag Nair
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Mohamed Ameen
- Department of Cancer Biology, Stanford University, Stanford, CA, USA
- Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | | | - Anusri Pampari
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jacob Schreiber
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Yu Xin Wang
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
| | - David Burns
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
| | - Helen M Blau
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Ioannis Karakikes
- Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
| | - Kevin C Wang
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Anshul Kundaje
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
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9
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Trouillon J, Doubleday PF, Sauer U. Genomic footprinting uncovers global transcription factor responses to amino acids in Escherichia coli. Cell Syst 2023; 14:860-871.e4. [PMID: 37820729 DOI: 10.1016/j.cels.2023.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/01/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023]
Abstract
Our knowledge of transcriptional responses to changes in nutrient availability comes primarily from few well-studied transcription factors (TFs), often lacking an unbiased genome-wide perspective. Leveraging recent advances allowing bacterial genomic footprinting, we comprehensively mapped the genome-wide regulatory responses of Escherichia coli to exogenous leucine, methionine, alanine, and lysine. The global TF Lrp was found to individually sense three amino acids and mount three different target gene responses. Overall, 531 genes had altered RNA polymerase occupancy, and 32 TFs responded directly or indirectly to the presence of amino acids, including regulators of membrane and osmotic pressure homeostasis. About 70% of the detected TF-DNA interactions had not been reported before. We thus identified 682 previously unknown TF-binding locations, for a subset of which the involved TFs were identified by affinity purification. This comprehensive map of amino acid regulation illustrates the incompleteness of the known transcriptional regulation network, even in E. coli.
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Affiliation(s)
- Julian Trouillon
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Peter F Doubleday
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland.
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10
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Wang L, Trasanidis N, Wu T, Dong G, Hu M, Bauer DE, Pinello L. Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics. Nat Methods 2023; 20:1368-1378. [PMID: 37537351 DOI: 10.1038/s41592-023-01971-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 07/05/2023] [Indexed: 08/05/2023]
Abstract
Gene regulatory networks (GRNs) are key determinants of cell function and identity and are dynamically rewired during development and disease. Despite decades of advancement, challenges remain in GRN inference, including dynamic rewiring, causal inference, feedback loop modeling and context specificity. To address these challenges, we develop Dictys, a dynamic GRN inference and analysis method that leverages multiomic single-cell assays of chromatin accessibility and gene expression, context-specific transcription factor footprinting, stochastic process network and efficient probabilistic modeling of single-cell RNA-sequencing read counts. Dictys improves GRN reconstruction accuracy and reproducibility and enables the inference and comparative analysis of context-specific and dynamic GRNs across developmental contexts. Dictys' network analyses recover unique insights in human blood and mouse skin development with cell-type-specific and dynamic GRNs. Its dynamic network visualizations enable time-resolved discovery and investigation of developmental driver transcription factors and their regulated targets. Dictys is available as a free, open-source and user-friendly Python package.
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Affiliation(s)
- Lingfei Wang
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Department of Pathology, Harvard Medical School, Boston, MA, USA
- Gene Regulation Observatory, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nikolaos Trasanidis
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Department of Pathology, Harvard Medical School, Boston, MA, USA
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Ting Wu
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Guanlan Dong
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Department of Pathology, Harvard Medical School, Boston, MA, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Bioinformatics and Integrative Genomics PhD Program, Harvard Medical School, Boston, MA, USA
| | - Michael Hu
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Department of Pathology, Harvard Medical School, Boston, MA, USA
| | - Daniel E Bauer
- Gene Regulation Observatory, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Luca Pinello
- Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital Research Institute, Department of Pathology, Harvard Medical School, Boston, MA, USA.
- Gene Regulation Observatory, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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11
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van der Sande M, Frölich S, van Heeringen SJ. Computational approaches to understand transcription regulation in development. Biochem Soc Trans 2023; 51:1-12. [PMID: 36695505 PMCID: PMC9988001 DOI: 10.1042/bst20210145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/07/2023] [Accepted: 01/13/2023] [Indexed: 01/26/2023]
Abstract
Gene regulatory networks (GRNs) serve as useful abstractions to understand transcriptional dynamics in developmental systems. Computational prediction of GRNs has been successfully applied to genome-wide gene expression measurements with the advent of microarrays and RNA-sequencing. However, these inferred networks are inaccurate and mostly based on correlative rather than causative interactions. In this review, we highlight three approaches that significantly impact GRN inference: (1) moving from one genome-wide functional modality, gene expression, to multi-omics, (2) single cell sequencing, to measure cell type-specific signals and predict context-specific GRNs, and (3) neural networks as flexible models. Together, these experimental and computational developments have the potential to significantly impact the quality of inferred GRNs. Ultimately, accurately modeling the regulatory interactions between transcription factors and their target genes will be essential to understand the role of transcription factors in driving developmental gene expression programs and to derive testable hypotheses for validation.
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Affiliation(s)
| | | | - Simon J. van Heeringen
- Radboud University, Department of Molecular Developmental Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, 6525GA Nijmegen, The Netherlands
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12
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Hajirnis N, Pandey S, Mishra RK. CRISPR/Cas9 and FLP-FRT mediated regulatory dissection of the BX-C of Drosophila melanogaster. CHROMOSOME RESEARCH : AN INTERNATIONAL JOURNAL ON THE MOLECULAR, SUPRAMOLECULAR AND EVOLUTIONARY ASPECTS OF CHROMOSOME BIOLOGY 2023; 31:7. [PMID: 36719476 DOI: 10.1007/s10577-023-09716-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/23/2022] [Accepted: 11/28/2022] [Indexed: 02/01/2023]
Abstract
The homeotic genes or Hox define the anterior-posterior (AP) body axis formation in bilaterians and are often present on the chromosome in an order collinear to their function across the AP axis. However, there are many cases wherein the Hox are not collinear, but their expression pattern is conserved across the AP axis. The expression pattern of Hox is attributed to the cis-regulatory modules (CRMs) consisting of enhancers, initiators, or repressor elements that regulate the genes in a segment-specific manner. In the Drosophila melanogaster Hox complex, the bithorax complex (BX-C) and even the CRMs are organized in an order that is collinear to their function in the thoracic and abdominal segments. In the present study, the regulatorily inert regions were targeted using CRISPR/Cas9 to generate a series of transgenic lines with the insertion of FRT sequences. These FRT lines are repurposed to shuffle the CRMs associated with Abd-B to generate modular deletion, duplication, or inversion of multiple CRMs. The rearrangements yielded entirely novel phenotypes in the fly suggesting the requirement of such complex manipulations to address the significance of higher order arrangement of the CRMs. The functional map and the transgenic flies generated in this study are important resources to decipher the collective ability of multiple regulatory elements in the eukaryotic genome to function as complex modules.
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Affiliation(s)
- Nikhil Hajirnis
- CSIR - Centre for Cellular and Molecular Biology, Hyderabad, India.,Department of Anatomy and Neurobiology, University of Maryland, Baltimore, USA
| | | | - Rakesh K Mishra
- CSIR - Centre for Cellular and Molecular Biology, Hyderabad, India. .,AcSIR - Academy of Scientific and Innovative Research, Ghaziabad, India. .,Tata Institute for Genetics and Society (TIGS), Bangalore, India.
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13
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Portuguez AS, Grbesa I, Tal M, Deitch R, Raz D, Kliker L, Weismann R, Schwartz M, Loza O, Cohen L, Marchenkov-Flam L, Sung MH, Kaplan T, Hakim O. Ep300 sequestration to functionally distinct glucocorticoid receptor binding loci underlie rapid gene activation and repression. Nucleic Acids Res 2022; 50:6702-6714. [PMID: 35713523 PMCID: PMC9262608 DOI: 10.1093/nar/gkac488] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 05/18/2022] [Accepted: 05/26/2022] [Indexed: 12/24/2022] Open
Abstract
The rapid transcriptional response to the transcription factor, glucocorticoid receptor (GR), including gene activation or repression, is mediated by the spatial association of genes with multiple GR binding sites (GBSs) over large genomic distances. However, only a minority of the GBSs have independent GR-mediated activating capacity, and GBSs with independent repressive activity were rarely reported. To understand the positive and negative effects of GR we mapped the regulatory environment of its gene targets. We show that the chromatin interaction networks of GR-activated and repressed genes are spatially separated and vary in the features and configuration of their GBS and other non-GBS regulatory elements. The convergence of the KLF4 pathway in GR-activated domains and the STAT6 pathway in GR-repressed domains, impose opposite transcriptional effects to GR, independent of hormone application. Moreover, the ROR and Rev-erb transcription factors serve as positive and negative regulators, respectively, of GR-mediated gene activation. We found that the spatial crosstalk between GBSs and non-GBSs provides a physical platform for sequestering the Ep300 co-activator from non-GR regulatory loci in both GR-activated and -repressed gene compartments. While this allows rapid gene repression, Ep300 recruitment to GBSs is productive specifically in the activated compartments, thus providing the basis for gene induction.
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Affiliation(s)
| | | | - Moran Tal
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Rachel Deitch
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Dana Raz
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Limor Kliker
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Ran Weismann
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Michal Schwartz
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Olga Loza
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Leslie Cohen
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Libi Marchenkov-Flam
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 206, Ramat-Gan 5290002, Israel
| | - Myong-Hee Sung
- Laboratory of Molecular Biology and Immunology, NIA, National Institutes of Health, Baltimore, MD 21224, USA
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 91904, Israel,Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91121, Israel
| | - Ofir Hakim
- To whom correspondence should be addressed. Tel: +972 3 738 4295; Fax: +972 3 738 4296;
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14
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Grandi FC, Modi H, Kampman L, Corces MR. Chromatin accessibility profiling by ATAC-seq. Nat Protoc 2022; 17:1518-1552. [PMID: 35478247 PMCID: PMC9189070 DOI: 10.1038/s41596-022-00692-9] [Citation(s) in RCA: 132] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 02/22/2022] [Indexed: 12/13/2022]
Abstract
The assay for transposase-accessible chromatin using sequencing (ATAC-seq) provides a simple and scalable way to detect the unique chromatin landscape associated with a cell type and how it may be altered by perturbation or disease. ATAC-seq requires a relatively small number of input cells and does not require a priori knowledge of the epigenetic marks or transcription factors governing the dynamics of the system. Here we describe an updated and optimized protocol for ATAC-seq, called Omni-ATAC, that is applicable across a broad range of cell and tissue types. The ATAC-seq workflow has five main steps: sample preparation, transposition, library preparation, sequencing and data analysis. This protocol details the steps to generate and sequence ATAC-seq libraries, with recommendations for sample preparation and downstream bioinformatic analysis. ATAC-seq libraries for roughly 12 samples can be generated in 10 h by someone familiar with basic molecular biology, and downstream sequencing analysis can be implemented using benchmarked pipelines by someone with basic bioinformatics skills and with access to a high-performance computing environment.
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Affiliation(s)
- Fiorella C Grandi
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Hailey Modi
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Lucas Kampman
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - M Ryan Corces
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA.
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
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15
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Sun F, Ou J, Shoffner AR, Luan Y, Yang H, Song L, Safi A, Cao J, Yue F, Crawford GE, Poss KD. Enhancer selection dictates gene expression responses in remote organs during tissue regeneration. Nat Cell Biol 2022; 24:685-696. [PMID: 35513710 DOI: 10.1038/s41556-022-00906-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 03/23/2022] [Indexed: 12/14/2022]
Abstract
Acute trauma stimulates local repair mechanisms but can also impact structures distant from the injury, for example through the activity of circulating factors. To study the responses of remote tissues during tissue regeneration, we profiled transcriptomes of zebrafish brains after experimental cardiac damage. We found that the transcription factor gene cebpd was upregulated remotely in brain ependymal cells as well as kidney tubular cells, in addition to its local induction in epicardial cells. cebpd mutations altered both local and distant cardiac injury responses, altering the cycling of epicardial cells as well as exchange between distant fluid compartments. Genome-wide profiling and transgenesis identified a hormone-responsive enhancer near cebpd that exists in a permissive state, enabling rapid gene expression in heart, brain and kidney after cardiac injury. Deletion of this sequence selectively abolished cebpd induction in remote tissues and disrupted fluid regulation after injury, without affecting its local cardiac expression response. Our findings suggest a model to broaden gene function during regeneration in which enhancer regulatory elements define short- and long-range expression responses to injury.
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Affiliation(s)
- Fei Sun
- Duke Regeneration Center, Duke University, Durham, NC, USA.,Department of Cell Biology, Duke University Medical Center, Durham, NC, USA
| | - Jianhong Ou
- Duke Regeneration Center, Duke University, Durham, NC, USA
| | - Adam R Shoffner
- Duke Regeneration Center, Duke University, Durham, NC, USA.,Department of Cell Biology, Duke University Medical Center, Durham, NC, USA
| | - Yu Luan
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Hongbo Yang
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China
| | - Lingyun Song
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.,Division of Medical Genetics, Department of Pediatrics, Duke University, Durham, NC, USA
| | - Alexias Safi
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.,Division of Medical Genetics, Department of Pediatrics, Duke University, Durham, NC, USA
| | - Jingli Cao
- Cardiovascular Research Institute, Weill Cornell Medical College, New York, NY, USA.,Department of Cell and Developmental Biology, Weill Cornell Medical College, New York, NY, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Gregory E Crawford
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.,Division of Medical Genetics, Department of Pediatrics, Duke University, Durham, NC, USA
| | - Kenneth D Poss
- Duke Regeneration Center, Duke University, Durham, NC, USA. .,Department of Cell Biology, Duke University Medical Center, Durham, NC, USA.
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16
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Coda DM, Patel H, Gori I, Gaarenstroom TE, Song OR, Howell M, Hill CS. A network of transcription factors governs the dynamics of NODAL/Activin transcriptional responses. J Cell Sci 2022; 135:jcs259972. [PMID: 35302162 PMCID: PMC9080556 DOI: 10.1242/jcs.259972] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 03/08/2022] [Indexed: 11/20/2022] Open
Abstract
SMAD2, an effector of the NODAL/Activin signalling pathway, regulates developmental processes by sensing distinct chromatin states and interacting with different transcriptional partners. However, the network of factors that controls SMAD2 chromatin binding and shapes its transcriptional programme over time is poorly characterised. Here, we combine ATAC-seq with computational footprinting to identify temporal changes in chromatin accessibility and transcription factor activity upon NODAL/Activin signalling. We show that SMAD2 binding induces chromatin opening genome wide. We discover footprints for FOXI3, FOXO3 and ZIC3 at the SMAD2-bound enhancers of the early response genes, Pmepa1 and Wnt3, respectively, and demonstrate their functionality. Finally, we determine a mechanism by which NODAL/Activin signalling induces delayed gene expression, by uncovering a self-enabling transcriptional cascade whereby activated SMADs, together with ZIC3, induce the expression of Wnt3. The resultant activated WNT pathway then acts together with the NODAL/Activin pathway to regulate expression of delayed target genes in prolonged NODAL/Activin signalling conditions. This article has an associated First Person interview with the first author of the paper.
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Affiliation(s)
- Davide M. Coda
- Developmental Signalling Laboratory, The Francis Crick Institute, London, NW1 1AT, UK
| | - Harshil Patel
- Bioinformatics and Biostatistics Facility, The Francis Crick Institute, London, NW1 1AT, UK
| | - Ilaria Gori
- Developmental Signalling Laboratory, The Francis Crick Institute, London, NW1 1AT, UK
| | - Tessa E. Gaarenstroom
- Developmental Signalling Laboratory, The Francis Crick Institute, London, NW1 1AT, UK
| | - Ok-Ryul Song
- High Throughput Screening Facility, The Francis Crick Institute, London, NW1 1AT, UK
| | - Michael Howell
- High Throughput Screening Facility, The Francis Crick Institute, London, NW1 1AT, UK
| | - Caroline S. Hill
- Developmental Signalling Laboratory, The Francis Crick Institute, London, NW1 1AT, UK
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17
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Zhang Z, Lin L, Chen H, Ye W, Dong S, Zheng X, Wang Y. ATAC-Seq Reveals the Landscape of Open Chromatin and cis-Regulatory Elements in the Phytophthora sojae Genome. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2022; 35:301-310. [PMID: 35037783 DOI: 10.1094/mpmi-11-21-0291-ta] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Nucleosome-free open chromatin often harbors transcription factor (TF)-binding sites that are associated with active cis-regulatory elements. However, analysis of open chromatin regions has rarely been applied to oomycete or fungal plant pathogens. In this study, we performed the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) to identify open chromatin and cis-regulatory elements in Phytophthora sojae at the mycelial stage. We identified 10,389 peaks representing nucleosome-free regions (NFRs). The peaks were enriched in gene-promoter regions and associated with 40% of P. sojae genes; transcription levels were higher for genes with multiple peaks than genes with a single peak and were higher for genes with a single peak than genes without peak. Chromatin accessibility was positively correlated with gene transcription level. Through motif discovery based on NFR peaks in core promoter regions, 25 candidate cis-regulatory motifs with evidence of TF-binding footprints were identified. These motifs exhibited various preferences for location in the promoter region and associations with the transcription level of their target genes, which included some putative pathogenicity-related genes. As the first study revealing the landscape of open chromatin and the correlation between chromatin accessibility and gene transcription level in oomycetes, the results provide a technical reference and data resources for future studies on the regulatory mechanisms of gene transcription.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Zhichao Zhang
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Long Lin
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Han Chen
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Wenwu Ye
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Suomeng Dong
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Xiaobo Zheng
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
| | - Yuanchao Wang
- Department of Plant Pathology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), Nanjing, Jiangsu 210095, China
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18
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Abstract
Assays for transposase-accessible chromatin sequencing (ATAC-seq) provides an innovative approach to study chromatin status in multiple cell types. Moreover, it is also possible to efficiently extract differentially accessible chromatin (DACs) regions by using state-of-the-art algorithms (e.g. DESeq2) to predict gene activity in specific samples. Furthermore, it has recently been shown that small dips in sequencing peaks can be attributed to the binding of transcription factors. These dips, also known as footprints, can be used to identify trans-regulating interactions leading to gene expression. Current protocols used to identify footprints (e.g. pyDNAse and HINT-ATAC) have shown limitations resulting in the discovery of many false positive footprints. We generated a novel approach to identify genuine footprints within any given ATAC-seq dataset. Herein, we developed a new pipeline embedding DACs together with bona fide footprints resulting in the generation of a Predictive gene regulatory Network (PreNet) simply from ATAC-seq data. We further demonstrated that PreNet can be used to unveil meaningful molecular regulatory pathways in a given cell type.
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Affiliation(s)
- Nazmus Salehin
- Embryology Unit, Children's Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia.,School of Medical Sciences, Sydney Medical School, University of Sydney, NSW 2006, Australia
| | - Patrick P L Tam
- Embryology Unit, Children's Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia.,School of Medical Sciences, Sydney Medical School, University of Sydney, NSW 2006, Australia
| | - Pierre Osteil
- Embryology Unit, Children's Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia.,School of Medical Sciences, Sydney Medical School, University of Sydney, NSW 2006, Australia
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19
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Lemma RB, Ledsaak M, Fuglerud BM, Sandve GK, Eskeland R, Gabrielsen OS. Chromatin occupancy and target genes of the haematopoietic master transcription factor MYB. Sci Rep 2021; 11:9008. [PMID: 33903675 PMCID: PMC8076236 DOI: 10.1038/s41598-021-88516-w] [Citation(s) in RCA: 9] [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: 11/14/2020] [Accepted: 04/13/2021] [Indexed: 02/02/2023] Open
Abstract
The transcription factor MYB is a master regulator in haematopoietic progenitor cells and a pioneer factor affecting differentiation and proliferation of these cells. Leukaemic transformation may be promoted by high MYB levels. Despite much accumulated molecular knowledge of MYB, we still lack a comprehensive understanding of its target genes and its chromatin action. In the present work, we performed a ChIP-seq analysis of MYB in K562 cells accompanied by detailed bioinformatics analyses. We found that MYB occupies both promoters and enhancers. Five clusters (C1-C5) were found when we classified MYB peaks according to epigenetic profiles. C1 was enriched for promoters and C2 dominated by enhancers. C2-linked genes were connected to hematopoietic specific functions and had GATA factor motifs as second in frequency. C1 had in addition to MYB-motifs a significant frequency of ETS-related motifs. Combining ChIP-seq data with RNA-seq data allowed us to identify direct MYB target genes. We also compared ChIP-seq data with digital genomic footprinting. MYB is occupying nearly a third of the super-enhancers in K562. Finally, we concluded that MYB cooperates with a subset of the other highly expressed TFs in this cell line, as expected for a master regulator.
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Affiliation(s)
- Roza B Lemma
- Department of Biosciences, University of Oslo, Blindern, PO Box 1066, 0316, Oslo, Norway
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318, Oslo, Norway
| | - Marit Ledsaak
- Department of Biosciences, University of Oslo, Blindern, PO Box 1066, 0316, Oslo, Norway
- Institute of Basic Medical Sciences, Department of Molecular Medicine, University of Oslo, Blindern, PO Box 1112, 0317, Oslo, Norway
| | - Bettina M Fuglerud
- Department of Biosciences, University of Oslo, Blindern, PO Box 1066, 0316, Oslo, Norway
- Terry Fox Laboratory, BC Cancer, Vancouver, BC, V5Z 1L3, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Geir Kjetil Sandve
- Department of Informatics, University of Oslo, Blindern, PO Box 1080, 0371, Oslo, Norway
| | - Ragnhild Eskeland
- Department of Biosciences, University of Oslo, Blindern, PO Box 1066, 0316, Oslo, Norway
- Institute of Basic Medical Sciences, Department of Molecular Medicine, University of Oslo, Blindern, PO Box 1112, 0317, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Odd S Gabrielsen
- Department of Biosciences, University of Oslo, Blindern, PO Box 1066, 0316, Oslo, Norway.
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20
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Dual DNA and protein tagging of open chromatin unveils dynamics of epigenomic landscapes in leukemia. Nat Methods 2021; 18:293-302. [PMID: 33649590 PMCID: PMC8272231 DOI: 10.1038/s41592-021-01077-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 01/20/2021] [Indexed: 02/08/2023]
Abstract
The architecture of chromatin regulates eukaryotic cell states by controlling transcription factor access to sites of gene regulation. Here we describe a dual transposase-peroxidase approach, integrative DNA and protein tagging (iDAPT), which detects both DNA (iDAPT-seq) and protein (iDAPT-MS) associated with accessible regions of chromatin. In addition to direct identification of bound transcription factors, iDAPT enables the inference of their gene regulatory networks, protein interactors and regulation of chromatin accessibility. We applied iDAPT to profile the epigenomic consequences of granulocytic differentiation of acute promyelocytic leukemia, yielding previously undescribed mechanistic insights. Our findings demonstrate the power of iDAPT as a platform for studying the dynamic epigenomic landscapes and their transcription factor components associated with biological phenomena and disease.
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21
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Minnoye L, Marinov GK, Krausgruber T, Pan L, Marand AP, Secchia S, Greenleaf WJ, Furlong EEM, Zhao K, Schmitz RJ, Bock C, Aerts S. Chromatin accessibility profiling methods. NATURE REVIEWS. METHODS PRIMERS 2021; 1:10. [PMID: 38410680 PMCID: PMC10895463 DOI: 10.1038/s43586-020-00008-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/01/2020] [Indexed: 02/06/2023]
Abstract
Chromatin accessibility, or the physical access to chromatinized DNA, is a widely studied characteristic of the eukaryotic genome. As active regulatory DNA elements are generally 'accessible', the genome-wide profiling of chromatin accessibility can be used to identify candidate regulatory genomic regions in a tissue or cell type. Multiple biochemical methods have been developed to profile chromatin accessibility, both in bulk and at the single-cell level. Depending on the method, enzymatic cleavage, transposition or DNA methyltransferases are used, followed by high-throughput sequencing, providing a view of genome-wide chromatin accessibility. In this Primer, we discuss these biochemical methods, as well as bioinformatics tools for analysing and interpreting the generated data, and insights into the key regulators underlying developmental, evolutionary and disease processes. We outline standards for data quality, reproducibility and deposition used by the genomics community. Although chromatin accessibility profiling is invaluable to study gene regulation, alone it provides only a partial view of this complex process. Orthogonal assays facilitate the interpretation of accessible regions with respect to enhancer-promoter proximity, functional transcription factor binding and regulatory function. We envision that technological improvements including single-molecule, multi-omics and spatial methods will bring further insight into the secrets of genome regulation.
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Affiliation(s)
- Liesbeth Minnoye
- Center for Brain & Disease Research, VIB-KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | | | - Thomas Krausgruber
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Lixia Pan
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, NIH, Bethesda, MD, USA
| | | | - Stefano Secchia
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | | | - Eileen E M Furlong
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Keji Zhao
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, NIH, Bethesda, MD, USA
| | | | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Institute of Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Stein Aerts
- Center for Brain & Disease Research, VIB-KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
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22
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Abstract
The ATAC-seq assay has emerged as the most useful, versatile, and widely adaptable method for profiling accessible chromatin regions and tracking the activity of cis-regulatory elements (cREs) in eukaryotes. Thanks to its great utility, it is now being applied to map active chromatin in the context of a very wide diversity of biological systems and questions. In the course of these studies, considerable experience working with ATAC-seq data has accumulated and a standard set of computational tasks that need to be carried for most ATAC-seq analyses has emerged. Here, we review and provide examples of common such analytical procedures (including data processing, quality control, peak calling, identifying differentially accessible open chromatin regions, and variable transcription factor (TF) motif accessibility) and discuss recommended optimal practices.
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23
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ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation. Nat Commun 2020; 11:4267. [PMID: 32848148 PMCID: PMC7449963 DOI: 10.1038/s41467-020-18035-1] [Citation(s) in RCA: 283] [Impact Index Per Article: 70.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 07/23/2020] [Indexed: 12/22/2022] Open
Abstract
While footprinting analysis of ATAC-seq data can theoretically enable investigation of transcription factor (TF) binding, the lack of a computational tool able to conduct different levels of footprinting analysis has so-far hindered the widespread application of this method. Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework enabling genome-wide investigation of TF binding dynamics for hundreds of TFs simultaneously. We validate TOBIAS using paired ATAC-seq and ChIP-seq data, and find that TOBIAS outperforms existing methods for bias correction and footprinting. As a proof-of-concept, we illustrate how TOBIAS can unveil complex TF dynamics during zygotic genome activation in both humans and mice, and propose how zygotic Dux activates cascades of TFs, binds to repeat elements and induces expression of novel genetic elements.
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24
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Xu S, Feng W, Lu Z, Yu CY, Shao W, Nakshatri H, Reiter JL, Gao H, Chu X, Wang Y, Liu Y. regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data. Front Bioeng Biotechnol 2020; 8:886. [PMID: 32850739 PMCID: PMC7405637 DOI: 10.3389/fbioe.2020.00886] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/09/2020] [Indexed: 12/21/2022] Open
Abstract
Expression quantitative trait loci (eQTL) analysis is useful for identifying genetic variants correlated with gene expression, however, it cannot distinguish between causal and nearby non-functional variants. Because the majority of disease-associated SNPs are located in regulatory regions, they can impact allele-specific binding (ASB) of transcription factors and result in differential expression of the target gene alleles. In this study, our aim was to identify functional single-nucleotide polymorphisms (SNPs) that alter transcriptional regulation and thus, potentially impact cellular function. Here, we present regSNPs-ASB, a generalized linear model-based approach to identify regulatory SNPs that are located in transcription factor binding sites. The input for this model includes ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) raw read counts from heterozygous loci, where differential transposase-cleavage patterns between two alleles indicate preferential transcription factor binding to one of the alleles. Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression. By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also in eQTL regions. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In summary, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
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Affiliation(s)
- Siwen Xu
- Institute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, China.,Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Weixing Feng
- Institute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, China
| | - Zixiao Lu
- Regenstrief Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Christina Y Yu
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.,Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
| | - Wei Shao
- Regenstrief Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Harikrishna Nakshatri
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Jill L Reiter
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Hongyu Gao
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Xiaona Chu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yue Wang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yunlong Liu
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
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25
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Liu Y, Fu L, Kaufmann K, Chen D, Chen M. A practical guide for DNase-seq data analysis: from data management to common applications. Brief Bioinform 2020; 20:1865-1877. [PMID: 30010713 DOI: 10.1093/bib/bby057] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 06/06/2018] [Accepted: 06/10/2018] [Indexed: 01/01/2023] Open
Abstract
Deoxyribonuclease I (DNase I)-hypersensitive site sequencing (DNase-seq) has been widely used to determine chromatin accessibility and its underlying regulatory lexicon. However, exploring DNase-seq data requires sophisticated downstream bioinformatics analyses. In this study, we first review computational methods for all of the major steps in DNase-seq data analysis, including experimental design, quality control, read alignment, peak calling, annotation of cis-regulatory elements, genomic footprinting and visualization. The challenges associated with each step are highlighted. Next, we provide a practical guideline and a computational pipeline for DNase-seq data analysis by integrating some of these tools. We also discuss the competing techniques and the potential applications of this pipeline for the analysis of analogous experimental data. Finally, we discuss the integration of DNase-seq with other functional genomics techniques.
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Affiliation(s)
- Yongjing Liu
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China
| | - Liangyu Fu
- Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität zu Berlin, Berlin 10115, Germany
| | - Kerstin Kaufmann
- Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität zu Berlin, Berlin 10115, Germany
| | - Dijun Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ming Chen
- Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität zu Berlin, Berlin 10115, Germany
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26
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Cao B, Wu X, Zhou J, Wu H, Liu L, Zhang Q, DeMott MS, Gu C, Wang L, You D, Dedon PC. Nick-seq for single-nucleotide resolution genomic maps of DNA modifications and damage. Nucleic Acids Res 2020; 48:6715-6725. [PMID: 32484547 PMCID: PMC7337925 DOI: 10.1093/nar/gkaa473] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 05/16/2020] [Accepted: 05/22/2020] [Indexed: 12/12/2022] Open
Abstract
DNA damage and epigenetic marks are well established to have profound influences on genome stability and cell phenotype, yet there are few technologies to obtain high-resolution genomic maps of the many types of chemical modifications of DNA. Here we present Nick-seq for quantitative, sensitive, and accurate mapping of DNA modifications at single-nucleotide resolution across genomes. Pre-existing breaks are first blocked and DNA modifications are then converted enzymatically or chemically to strand-breaks for both 3'-extension by nick-translation to produce nuclease-resistant oligonucleotides and 3'-terminal transferase tailing. Following library preparation and next generation sequencing, the complementary datasets are mined with a custom workflow to increase sensitivity, specificity and accuracy of the map. The utility of Nick-seq is demonstrated with genomic maps of site-specific endonuclease strand-breaks in purified DNA from Eschericia coli, phosphorothioate epigenetics in Salmonella enterica Cerro 87, and oxidation-induced abasic sites in DNA from E. coli treated with a sublethal dose of hydrogen peroxide. Nick-seq applicability is demonstrated with strategies for >25 types of DNA modification and damage.
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Affiliation(s)
- Bo Cao
- College of Life Sciences, Qufu Normal University, Qufu, Shandong 273165, China
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Drug Resistance Interdisciplinary Research Group, Singapore 138602, Singapore
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, and School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Xiaolin Wu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Drug Resistance Interdisciplinary Research Group, Singapore 138602, Singapore
- Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and School of Pharmaceutical Sciences, Wuhan University, Wuhan, Hubei 430071, China
| | - Jieliang Zhou
- KK Research Center, KK Women's and Children's Hospital, 229899, Singapore
| | - Hang Wu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- School of Life Sciences, Anhui University, Hefei, Anhui 230601, China
| | - Lili Liu
- College of Life Sciences, Qufu Normal University, Qufu, Shandong 273165, China
| | - Qinghua Zhang
- College of Life Sciences, Qufu Normal University, Qufu, Shandong 273165, China
| | - Michael S DeMott
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Center for Environmental Health Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Chen Gu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Lianrong Wang
- Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and School of Pharmaceutical Sciences, Wuhan University, Wuhan, Hubei 430071, China
| | - Delin You
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, and School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Peter C Dedon
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Drug Resistance Interdisciplinary Research Group, Singapore 138602, Singapore
- Center for Environmental Health Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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27
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Smith JP, Sheffield NC. Analytical Approaches for ATAC-seq Data Analysis. CURRENT PROTOCOLS IN HUMAN GENETICS 2020; 106:e101. [PMID: 32543102 PMCID: PMC8191135 DOI: 10.1002/cphg.101] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
ATAC-seq, the assay for transposase-accessible chromatin using sequencing, is a quick and efficient approach to investigating the chromatin accessibility landscape. Investigating chromatin accessibility has broad utility for answering many biological questions, such as mapping nucleosomes, identifying transcription factor binding sites, and measuring differential activity of DNA regulatory elements. Because the ATAC-seq protocol is both simple and relatively inexpensive, there has been a rapid increase in the availability of chromatin accessibility data. Furthermore, advances in ATAC-seq protocols are rapidly extending its breadth to additional experimental conditions, cell types, and species. Accompanying the increase in data, there has also been an explosion of new tools and analytical approaches for analyzing it. Here, we explain the fundamentals of ATAC-seq data processing, summarize common analysis approaches, and review computational tools to provide recommendations for different research questions. This primer provides a starting point and a reference for analysis of ATAC-seq data. © 2020 Wiley Periodicals LLC.
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Affiliation(s)
- Jason P. Smith
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia
| | - Nathan C. Sheffield
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
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28
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Srivastava D, Mahony S. Sequence and chromatin determinants of transcription factor binding and the establishment of cell type-specific binding patterns. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2020; 1863:194443. [PMID: 31639474 PMCID: PMC7166147 DOI: 10.1016/j.bbagrm.2019.194443] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 09/21/2019] [Accepted: 10/06/2019] [Indexed: 12/14/2022]
Abstract
Transcription factors (TFs) selectively bind distinct sets of sites in different cell types. Such cell type-specific binding specificity is expected to result from interplay between the TF's intrinsic sequence preferences, cooperative interactions with other regulatory proteins, and cell type-specific chromatin landscapes. Cell type-specific TF binding events are highly correlated with patterns of chromatin accessibility and active histone modifications in the same cell type. However, since concurrent chromatin may itself be a consequence of TF binding, chromatin landscapes measured prior to TF activation provide more useful insights into how cell type-specific TF binding events became established in the first place. Here, we review the various sequence and chromatin determinants of cell type-specific TF binding specificity. We identify the current challenges and opportunities associated with computational approaches to characterizing, imputing, and predicting cell type-specific TF binding patterns. We further focus on studies that characterize TF binding in dynamic regulatory settings, and we discuss how these studies are leading to a more complex and nuanced understanding of dynamic protein-DNA binding activities. We propose that TF binding activities at individual sites can be viewed along a two-dimensional continuum of local sequence and chromatin context. Under this view, cell type-specific TF binding activities may result from either strongly favorable sequence features or strongly favorable chromatin context.
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Affiliation(s)
- Divyanshi Srivastava
- Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA, United States of America
| | - Shaun Mahony
- Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA, United States of America.
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29
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Branco GP, Valieris R, Povoa LV, Araújo LFD, Fernandes GR, Souza JESD, Amorim MGD, Ferreira ENE, Silva ITD, Nunes DN, Dias-Neto E. A comparison between SOLiD 5500XLand Ion Torrent PGM-derived miRNA expression profiles in two breast cell lines. Genet Mol Biol 2020; 43:e20180351. [PMID: 32352476 PMCID: PMC7201575 DOI: 10.1590/1678-4685-gmb-2018-0351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 06/06/2019] [Indexed: 11/22/2022] Open
Abstract
Next-generation sequencing (NGS) platforms allow the analysis of hundreds of
millions of molecules in a single sequencing run, revolutionizing many research
areas. NGS-based microRNA studies enable expression quantification in
unprecedented scale without the limitations of closed-platforms. Yet, whereas a
massive amount of data produced by these platforms is available, comparisons of
quantification/discovery capabilities between platforms are still lacking. Here
we compare two NGS-platforms: SOLiD and PGM, by evaluating their microRNA
identification/quantification capabilities using two breast-derived cell-lines.
A high expression correlation (R2 > 0.9) was achieved, encompassing 97% of
the miRNAs, and the few discrepancies in miRNA counts were attributable to
molecules that have very low expression. Quantification divergences indicative
of artefactual representation were seen for 14 miRNAs (higher in SOLiD-reads)
and another 10 miRNAs more abundant in PGM-data. An inspection of these revealed
an increased and statistically significant count of uracyls and uracyl-stretches
for PGM-enriched miRNAs, compared to SOLiD and to the miRBase. In parallel,
adenines and adenine-stretches were enriched for SOLiDderived miRNA reads. We
conclude that, whereas both platforms are overall consistent and can be used
interchangeably for microRNA expression studies, particular sequence features
appear to be indicative of specific platform bias, and their presence in
microRNAs should be considered for database-analyses.
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Affiliation(s)
| | - Renan Valieris
- A.C.Camargo Cancer Center, Laboratório de Biologia Computacional, São Paulo, SP, Brazil
| | - Lucas Venezian Povoa
- A.C.Camargo Cancer Center, Laboratório de Biologia Computacional, São Paulo, SP, Brazil.,Instituto Tecnológico de Aeronáutica, Divisão de Ciências Computacionais, Grupo de Inteligência Artificial e Robótica, São José dos Campos, SP, Brazil.,Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, Caraguatatuba, SP, Brazil
| | | | | | | | - Maria Galli de Amorim
- A.C.Camargo Cancer Center, Laboratório de Genômica Médica, CIPE, São Paulo, SP, Brazil
| | - Elisa Napolitano E Ferreira
- A.C.Camargo Cancer Center, Laboratório de Genômica e Biologia, CIPE, São Paulo, SP, Brazil.,Grupo Fleury Pesquisa e Desenvolvimento, São Paulo, SP, Brazil
| | - Israel Tojal da Silva
- A.C.Camargo Cancer Center, Laboratório de Biologia Computacional, São Paulo, SP, Brazil
| | - Diana Noronha Nunes
- A.C.Camargo Cancer Center, Laboratório de Genômica Médica, CIPE, São Paulo, SP, Brazil
| | - Emmanuel Dias-Neto
- A.C.Camargo Cancer Center, Laboratório de Genômica Médica, CIPE, São Paulo, SP, Brazil.,Universidade de São Paulo, Faculdade de Medicina, Departamento & Instituto de Psiquiatria, Laboratório de Neurociências Alzira Denise Hertzog Silva (LIM-27), São Paulo, SP, Brazil
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30
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Bubb KL, Deal RB. Considerations in the analysis of plant chromatin accessibility data. CURRENT OPINION IN PLANT BIOLOGY 2020; 54:69-78. [PMID: 32113082 PMCID: PMC8959678 DOI: 10.1016/j.pbi.2020.01.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 01/16/2020] [Accepted: 01/21/2020] [Indexed: 05/04/2023]
Abstract
Transcriptional control is exerted primarily through the binding of transcription factor proteins to regulatory elements in DNA. By virtue of eukaryotic DNA being complexed with histones, transcription factor binding to DNA alters or eliminates histone-DNA contacts, leading to increased accessibility of the DNA region to nuclease enzymes. This hypersensitivity to nuclease digestion has been used to define DNA binding events and regulatory elements across genomes, and to compare these attributes between cell types or conditions. These approaches make it possible to define the regulatory elements in a genome as well as to predict the regulatory networks of transcription factors and their target genes in a given cell state. As these chromatin accessibility assays are increasingly used, it is important to consider how to analyze the resulting data to avoid artifactual results or misinterpretation. In this review, we focus on some of the key technical and computational caveats associated with plant chromatin accessibility data, including strategies for sample preparation, sequencing, read mapping, and downstream analyses.
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Affiliation(s)
- Kerry L Bubb
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington, USA.
| | - Roger B Deal
- Emory University, Department of Biology, Atlanta, GA, USA
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31
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Yan F, Powell DR, Curtis DJ, Wong NC. From reads to insight: a hitchhiker's guide to ATAC-seq data analysis. Genome Biol 2020; 21:22. [PMID: 32014034 PMCID: PMC6996192 DOI: 10.1186/s13059-020-1929-3] [Citation(s) in RCA: 216] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 01/08/2020] [Indexed: 12/16/2022] Open
Abstract
Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.
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Affiliation(s)
- Feng Yan
- Australian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - David R Powell
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - David J Curtis
- Australian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.,Department of Clinical Haematology, Alfred Health, Melbourne, VIC, Australia
| | - Nicholas C Wong
- Australian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia. .,Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia.
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32
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Youn A, Marquez EJ, Lawlor N, Stitzel ML, Ucar D. BiFET: sequencing Bias-free transcription factor Footprint Enrichment Test. Nucleic Acids Res 2019; 47:e11. [PMID: 30428075 PMCID: PMC6344870 DOI: 10.1093/nar/gky1117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 10/23/2018] [Indexed: 01/15/2023] Open
Abstract
Transcription factor (TF) footprinting uncovers putative protein–DNA binding via combined analyses of chromatin accessibility patterns and their underlying TF sequence motifs. TF footprints are frequently used to identify TFs that regulate activities of cell/condition-specific genomic regions (target loci) in comparison to control regions (background loci) using standard enrichment tests. However, there is a strong association between the chromatin accessibility level and the GC content of a locus and the number and types of TF footprints that can be detected at this site. Traditional enrichment tests (e.g. hypergeometric) do not account for this bias and inflate false positive associations. Therefore, we developed a novel post-processing method, Bias-free Footprint Enrichment Test (BiFET), that corrects for the biases arising from the differences in chromatin accessibility levels and GC contents between target and background loci in footprint enrichment analyses. We applied BiFET on TF footprint calls obtained from EndoC-βH1 ATAC-seq samples using three different algorithms (CENTIPEDE, HINT-BC and PIQ) and showed BiFET’s ability to increase power and reduce false positive rate when compared to hypergeometric test. Furthermore, we used BiFET to study TF footprints from human PBMC and pancreatic islet ATAC-seq samples to show its utility to identify putative TFs associated with cell-type-specific loci.
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Affiliation(s)
- Ahrim Youn
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Eladio J Marquez
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Nathan Lawlor
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Michael L Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.,Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT 06030, USA.,Department of Genetics & Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030, USA
| | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.,Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT 06030, USA.,Department of Genetics & Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030, USA
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33
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Abstract
Physical access to DNA is a highly dynamic property of chromatin that plays an essential role in establishing and maintaining cellular identity. The organization of accessible chromatin across the genome reflects a network of permissible physical interactions through which enhancers, promoters, insulators and chromatin-binding factors cooperatively regulate gene expression. This landscape of accessibility changes dynamically in response to both external stimuli and developmental cues, and emerging evidence suggests that homeostatic maintenance of accessibility is itself dynamically regulated through a competitive interplay between chromatin-binding factors and nucleosomes. In this Review, we examine how the accessible genome is measured and explore the role of transcription factors in initiating accessibility remodelling; our goal is to illustrate how chromatin accessibility defines regulatory elements within the genome and how these epigenetic features are dynamically established to control gene expression.
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Affiliation(s)
- Sandy L Klemm
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Zohar Shipony
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA. .,Department of Applied Physics, Stanford University, Stanford, CA, USA. .,Chan Zuckerberg BioHub, San Francisco, CA, USA.
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34
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Oh KS, Ha J, Baek S, Sung MH. XL-DNase-seq: improved footprinting of dynamic transcription factors. Epigenetics Chromatin 2019; 12:30. [PMID: 31164146 PMCID: PMC6547507 DOI: 10.1186/s13072-019-0277-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/17/2019] [Indexed: 02/08/2023] Open
Abstract
Background As the cost of high-throughput sequencing technologies decreases, genome-wide chromatin accessibility profiling methods such as the assay of transposase-accessible chromatin using sequencing (ATAC-seq) are employed widely, with data accumulating at an unprecedented rate. However, accurate inference of protein occupancy requires higher-resolution footprinting analysis where major hurdles exist, including the sequence bias of nucleases and the short-lived chromatin binding of many transcription factors (TFs) with consequent lack of footprints. Results Here we introduce an assay termed cross-link (XL)-DNase-seq, designed to capture chromatin interactions of dynamic TFs. Mild cross-linking improved the detection of DNase-based footprints of dynamic TFs but interfered with ATAC-based footprinting of the same TFs. Conclusions XL-DNase-seq may help extract novel gene regulatory circuits involving previously undetectable TFs. The DNase-seq and ATAC-seq data generated in our systematic comparison of various cross-linking conditions also represent an unprecedented-scale resource derived from activated mouse macrophage-like cells which share many features of inflammatory macrophages. Electronic supplementary material The online version of this article (10.1186/s13072-019-0277-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Kyu-Seon Oh
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD, 21224, USA
| | - Jisu Ha
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD, 21224, USA
| | - Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, 41 Library Drive, Bethesda, MD, 20892, USA
| | - Myong-Hee Sung
- Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD, 21224, USA.
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35
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Karabacak Calviello A, Hirsekorn A, Wurmus R, Yusuf D, Ohler U. Reproducible inference of transcription factor footprints in ATAC-seq and DNase-seq datasets using protocol-specific bias modeling. Genome Biol 2019; 20:42. [PMID: 30791920 PMCID: PMC6385462 DOI: 10.1186/s13059-019-1654-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 02/13/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND DNase-seq and ATAC-seq are broadly used methods to assay open chromatin regions genome-wide. The single nucleotide resolution of DNase-seq has been further exploited to infer transcription factor binding sites (TFBSs) in regulatory regions through footprinting. Recent studies have demonstrated the sequence bias of DNase I and its adverse effects on footprinting efficiency. However, footprinting and the impact of sequence bias have not been extensively studied for ATAC-seq. RESULTS Here, we undertake a systematic comparison of the two methods and show that a modification to the ATAC-seq protocol increases its yield and its agreement with DNase-seq data from the same cell line. We demonstrate that the two methods have distinct sequence biases and correct for these protocol-specific biases when performing footprinting. Despite the differences in footprint shapes, the locations of the inferred footprints in ATAC-seq and DNase-seq are largely concordant. However, the protocol-specific sequence biases in conjunction with the sequence content of TFBSs impact the discrimination of footprint from the background, which leads to one method outperforming the other for some TFs. Finally, we address the depth required for reproducible identification of open chromatin regions and TF footprints. CONCLUSIONS We demonstrate that the impact of bias correction on footprinting performance is greater for DNase-seq than for ATAC-seq and that DNase-seq footprinting leads to better performance. It is possible to infer concordant footprints by using replicates, highlighting the importance of reproducibility assessment. The results presented here provide an overview of the advantages and limitations of footprinting analyses using ATAC-seq and DNase-seq.
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Affiliation(s)
- Aslıhan Karabacak Calviello
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany
- Department of Biology, Humboldt University, Berlin, Germany
| | - Antje Hirsekorn
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Ricardo Wurmus
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Dilmurat Yusuf
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Uwe Ohler
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany.
- Department of Biology, Humboldt University, Berlin, Germany.
- Department of Computer Science, Humboldt University, Berlin, Germany.
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36
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Abstract
Programs of gene transcription are controlled by cis-acting DNA elements, including enhancers, silencers, and promoters. Local accessibility of chromatin has proven to be a highly informative structural feature for identifying such regulatory elements, which tend to be relatively open due to their interactions with proteins. Recently, ATAC-seq (assay for transposase-accessible chromatin using sequencing) has emerged as one of the most powerful approaches for genome-wide chromatin accessibility profiling. This method assesses DNA accessibility using hyperactive Tn5 transposase, which simultaneously cuts DNA and inserts sequencing adaptors, preferentially in regions of open chromatin. ATAC-seq is a relatively simple procedure which can be applied to only a few thousand cells. It is well-suited to developing embryos of sea urchins and other echinoderms, which are a prominent experimental model for understanding the genomic control of animal development. In this chapter, we present a protocol for applying ATAC-seq to embryonic cells of sea urchins.
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Affiliation(s)
- Tanvi Shashikant
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Charles A Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, United States.
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KLF6 and STAT3 co-occupy regulatory DNA and functionally synergize to promote axon growth in CNS neurons. Sci Rep 2018; 8:12565. [PMID: 30135567 PMCID: PMC6105645 DOI: 10.1038/s41598-018-31101-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 08/10/2018] [Indexed: 11/26/2022] Open
Abstract
The failure of axon regeneration in the CNS limits recovery from damage and disease. Members of the KLF family of transcription factors can exert both positive and negative effects on axon regeneration, but the underlying mechanisms are unclear. Here we show that forced expression of KLF6 promotes axon regeneration by corticospinal tract neurons in the injured spinal cord. RNA sequencing identified 454 genes whose expression changed upon forced KLF6 expression in vitro, including sub-networks that were highly enriched for functions relevant to axon extension including cytoskeleton remodeling, lipid synthesis, and bioenergetics. In addition, promoter analysis predicted a functional interaction between KLF6 and a second transcription factor, STAT3, and genome-wide footprinting using ATAC-Seq data confirmed frequent co-occupancy. Co-expression of the two factors yielded a synergistic elevation of neurite growth in vitro. These data clarify the transcriptional control of axon growth and point the way toward novel interventions to promote CNS regeneration.
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38
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Swinstead EE, Paakinaho V, Hager GL. Chromatin reprogramming in breast cancer. Endocr Relat Cancer 2018; 25:R385-R404. [PMID: 29692347 PMCID: PMC6029727 DOI: 10.1530/erc-18-0033] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 04/24/2018] [Indexed: 02/06/2023]
Abstract
Reprogramming of the chromatin landscape is a critical component to the transcriptional response in breast cancer. Effects of sex hormones such as estrogens and progesterone have been well described to have a critical impact on breast cancer proliferation. However, the complex network of the chromatin landscape, enhancer regions and mode of function of steroid receptors (SRs) and other transcription factors (TFs), is an intricate web of signaling and functional processes that is still largely misunderstood at the mechanistic level. In this review, we describe what is currently known about the dynamic interplay between TFs with chromatin and the reprogramming of enhancer elements. Emphasis has been placed on characterizing the different modes of action of TFs in regulating enhancer activity, specifically, how different SRs target enhancer regions to reprogram chromatin in breast cancer cells. In addition, we discuss current techniques employed to study enhancer function at a genome-wide level. Further, we have noted recent advances in live cell imaging technology. These single-cell approaches enable the coupling of population-based assays with real-time studies to address many unsolved questions about SRs and chromatin dynamics in breast cancer.
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Affiliation(s)
- Erin E Swinstead
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Ville Paakinaho
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
- Institute of BiomedicineUniversity of Eastern Finland, Kuopio, Finland
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene ExpressionNational Cancer Institute, NIH, Bethesda, Maryland, USA
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39
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Umeyama T, Ito T. DMS-Seq for In Vivo Genome-wide Mapping of Protein-DNA Interactions and Nucleosome Centers. Cell Rep 2018; 21:289-300. [PMID: 28978481 DOI: 10.1016/j.celrep.2017.09.035] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 07/31/2017] [Accepted: 09/08/2017] [Indexed: 01/05/2023] Open
Abstract
Protein-DNA interactions provide the basis for chromatin structure and gene regulation. Comprehensive identification of protein-occupied sites is thus vital to an in-depth understanding of genome function. Dimethyl sulfate (DMS) is a chemical probe that has long been used to detect footprints of DNA-bound proteins in vitro and in vivo. Here, we describe a genomic footprinting method, dimethyl sulfate sequencing (DMS-seq), which exploits the cell-permeable nature of DMS to obviate the need for nuclear isolation. This feature makes DMS-seq simple in practice and removes the potential risk of protein re-localization during nuclear isolation. DMS-seq successfully detects transcription factors bound to cis-regulatory elements and non-canonical chromatin particles in nucleosome-free regions. Furthermore, an unexpected preference of DMS confers on DMS-seq a unique potential to directly detect nucleosome centers without using genetic manipulation. We expect that DMS-seq will serve as a characteristic method for genome-wide interrogation of in vivo protein-DNA interactions.
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Affiliation(s)
- Taichi Umeyama
- Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan; Core Research for Evolutional Science and Technology (CREST), Japan Agency for Medical Research and Development (AMED), Tokyo 100-0004, Japan; Laboratory for Microbiome Sciences, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Takashi Ito
- Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan; Core Research for Evolutional Science and Technology (CREST), Japan Agency for Medical Research and Development (AMED), Tokyo 100-0004, Japan.
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40
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Baek S, Goldstein I, Hager GL. Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity. Cell Rep 2018; 19:1710-1722. [PMID: 28538187 DOI: 10.1016/j.celrep.2017.05.003] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 04/04/2017] [Accepted: 04/26/2017] [Indexed: 02/06/2023] Open
Abstract
In response to activating signals, transcription factors (TFs) bind DNA and regulate gene expression. TF binding can be measured by protection of the bound sequence from DNase digestion (i.e., footprint). Here, we report that 80% of TF binding motifs do not show a measurable footprint, partly because of a variable cleavage pattern within the motif sequence. To more faithfully portray the effect of TFs on chromatin, we developed an algorithm that captures two TF-dependent effects on chromatin accessibility: footprinting and motif-flanking accessibility. The algorithm, termed bivariate genomic footprinting (BaGFoot), efficiently detects TF activity. BaGFoot is robust to different accessibility assays (DNase-seq, ATAC-seq), all examined peak-calling programs, and a variety of cut bias correction approaches. BaGFoot reliably predicts TF binding and provides valuable information regarding the TFs affecting chromatin accessibility in various biological systems and following various biological events, including in cases where an absolute footprint cannot be determined.
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Affiliation(s)
- Songjoon Baek
- Lab of Receptor Biology and Gene Expression, The National Cancer Institute, NIH, Bethesda, MD 20892, USA
| | - Ido Goldstein
- Lab of Receptor Biology and Gene Expression, The National Cancer Institute, NIH, Bethesda, MD 20892, USA.
| | - Gordon L Hager
- Lab of Receptor Biology and Gene Expression, The National Cancer Institute, NIH, Bethesda, MD 20892, USA.
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41
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Assenov Y, Brocks D, Gerhäuser C. Intratumor heterogeneity in epigenetic patterns. Semin Cancer Biol 2018; 51:12-21. [PMID: 29366906 DOI: 10.1016/j.semcancer.2018.01.010] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 11/24/2017] [Accepted: 01/17/2018] [Indexed: 02/08/2023]
Abstract
Analogous to life on earth, tumor cells evolve through space and time and adapt to different micro-environmental conditions. As a result, tumors are composed of millions of genetically diversified cells at the time of diagnosis. Profiling these variants contributes to understanding tumors' clonal origins and might help to better understand response to therapy. However, even genetically homogenous cell populations show remarkable diversity in their response to different environmental stimuli, suggesting that genetic heterogeneity does not explain the full spectrum of tumor plasticity. Understanding epigenetic diversity across cancer cells provides important additional information about the functional state of subclones and therefore allows better understanding of tumor evolution and resistance to current therapies.
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Affiliation(s)
- Yassen Assenov
- Epigenomics and Cancer Risk Factors, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - David Brocks
- Epigenomics and Cancer Risk Factors, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Clarissa Gerhäuser
- Epigenomics and Cancer Risk Factors, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
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42
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Maher KA, Bajic M, Kajala K, Reynoso M, Pauluzzi G, West DA, Zumstein K, Woodhouse M, Bubb K, Dorrity MW, Queitsch C, Bailey-Serres J, Sinha N, Brady SM, Deal RB. Profiling of Accessible Chromatin Regions across Multiple Plant Species and Cell Types Reveals Common Gene Regulatory Principles and New Control Modules. THE PLANT CELL 2018. [PMID: 29229750 DOI: 10.1101/167932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The transcriptional regulatory structure of plant genomes remains poorly defined relative to animals. It is unclear how many cis-regulatory elements exist, where these elements lie relative to promoters, and how these features are conserved across plant species. We employed the assay for transposase-accessible chromatin (ATAC-seq) in four plant species (Arabidopsis thaliana, Medicago truncatula, Solanum lycopersicum, and Oryza sativa) to delineate open chromatin regions and transcription factor (TF) binding sites across each genome. Despite 10-fold variation in intergenic space among species, the majority of open chromatin regions lie within 3 kb upstream of a transcription start site in all species. We find a common set of four TFs that appear to regulate conserved gene sets in the root tips of all four species, suggesting that TF-gene networks are generally conserved. Comparative ATAC-seq profiling of Arabidopsis root hair and non-hair cell types revealed extensive similarity as well as many cell-type-specific differences. Analyzing TF binding sites in differentially accessible regions identified a MYB-driven regulatory module unique to the hair cell, which appears to control both cell fate regulators and abiotic stress responses. Our analyses revealed common regulatory principles among species and shed light on the mechanisms producing cell-type-specific transcriptomes during development.
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Affiliation(s)
- Kelsey A Maher
- Department of Biology, Emory University, Atlanta, Georgia 30322
- Graduate Program in Biochemistry, Cell, and Developmental Biology, Emory University, Atlanta, Georgia 30322
| | - Marko Bajic
- Department of Biology, Emory University, Atlanta, Georgia 30322
- Graduate Program in Genetics and Molecular Biology, Emory University, Atlanta, Georgia 30322
| | - Kaisa Kajala
- Department of Plant Biology and Genome Center, University of California, Davis, California 95616
| | - Mauricio Reynoso
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Germain Pauluzzi
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Donnelly A West
- Department of Plant Biology, University of California, Davis, California 95616
| | - Kristina Zumstein
- Department of Plant Biology, University of California, Davis, California 95616
| | - Margaret Woodhouse
- Department of Plant Biology, University of California, Davis, California 95616
| | - Kerry Bubb
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Michael W Dorrity
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Christine Queitsch
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Julia Bailey-Serres
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Neelima Sinha
- Department of Plant Biology, University of California, Davis, California 95616
| | - Siobhan M Brady
- Department of Plant Biology and Genome Center, University of California, Davis, California 95616
| | - Roger B Deal
- Department of Biology, Emory University, Atlanta, Georgia 30322
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43
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Maher KA, Bajic M, Kajala K, Reynoso M, Pauluzzi G, West DA, Zumstein K, Woodhouse M, Bubb K, Dorrity MW, Queitsch C, Bailey-Serres J, Sinha N, Brady SM, Deal RB. Profiling of Accessible Chromatin Regions across Multiple Plant Species and Cell Types Reveals Common Gene Regulatory Principles and New Control Modules. THE PLANT CELL 2018; 30:15-36. [PMID: 29229750 PMCID: PMC5810565 DOI: 10.1105/tpc.17.00581] [Citation(s) in RCA: 175] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 10/30/2017] [Accepted: 12/06/2017] [Indexed: 05/19/2023]
Abstract
The transcriptional regulatory structure of plant genomes remains poorly defined relative to animals. It is unclear how many cis-regulatory elements exist, where these elements lie relative to promoters, and how these features are conserved across plant species. We employed the assay for transposase-accessible chromatin (ATAC-seq) in four plant species (Arabidopsis thaliana, Medicago truncatula, Solanum lycopersicum, and Oryza sativa) to delineate open chromatin regions and transcription factor (TF) binding sites across each genome. Despite 10-fold variation in intergenic space among species, the majority of open chromatin regions lie within 3 kb upstream of a transcription start site in all species. We find a common set of four TFs that appear to regulate conserved gene sets in the root tips of all four species, suggesting that TF-gene networks are generally conserved. Comparative ATAC-seq profiling of Arabidopsis root hair and non-hair cell types revealed extensive similarity as well as many cell-type-specific differences. Analyzing TF binding sites in differentially accessible regions identified a MYB-driven regulatory module unique to the hair cell, which appears to control both cell fate regulators and abiotic stress responses. Our analyses revealed common regulatory principles among species and shed light on the mechanisms producing cell-type-specific transcriptomes during development.
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Affiliation(s)
- Kelsey A Maher
- Department of Biology, Emory University, Atlanta, Georgia 30322
- Graduate Program in Biochemistry, Cell, and Developmental Biology, Emory University, Atlanta, Georgia 30322
| | - Marko Bajic
- Department of Biology, Emory University, Atlanta, Georgia 30322
- Graduate Program in Genetics and Molecular Biology, Emory University, Atlanta, Georgia 30322
| | - Kaisa Kajala
- Department of Plant Biology and Genome Center, University of California, Davis, California 95616
| | - Mauricio Reynoso
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Germain Pauluzzi
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Donnelly A West
- Department of Plant Biology, University of California, Davis, California 95616
| | - Kristina Zumstein
- Department of Plant Biology, University of California, Davis, California 95616
| | - Margaret Woodhouse
- Department of Plant Biology, University of California, Davis, California 95616
| | - Kerry Bubb
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Michael W Dorrity
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Christine Queitsch
- University of Washington, School of Medicine, Department of Genome Sciences, Seattle, Washington 98195
| | - Julia Bailey-Serres
- Center for Plant Cell Biology, Botany and Plant Sciences Department, University of California, Riverside, California 92521
| | - Neelima Sinha
- Department of Plant Biology, University of California, Davis, California 95616
| | - Siobhan M Brady
- Department of Plant Biology and Genome Center, University of California, Davis, California 95616
| | - Roger B Deal
- Department of Biology, Emory University, Atlanta, Georgia 30322
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44
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Goldstein I, Hager GL. Dynamic enhancer function in the chromatin context. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2018; 10:10.1002/wsbm.1390. [PMID: 28544514 PMCID: PMC6638546 DOI: 10.1002/wsbm.1390] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 03/21/2017] [Accepted: 03/23/2017] [Indexed: 12/28/2022]
Abstract
Enhancers serve as critical regulatory elements in higher eukaryotic cells. The characterization of enhancer function has evolved primarily from genome-wide methodologies, including chromatin immunoprecipitation (ChIP-seq), DNase-I hypersensitivity (DNase-seq), digital genomic footprinting (DGF), and the chromosome conformation capture techniques (3C, 4C, and Hi-C). These population-based assays average signals across millions of cells and lead to enhancer models characterized by static and sequential binding. More recently, fluorescent microscopy techniques, including fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, and single molecule tracking (SMT), reveal a highly dynamic binding behavior for these factors in live cells. Furthermore, a refined analysis of genomic footprinting suggests that many transcription factors leave minimal or no footprints in chromatin, even when present and active in a given cell type. In this study, we review the implications of these new approaches for an accurate understanding of enhancer function in real time. In vivo SMT, in particular, has recently evolved as a promising methodology to probe enhancer function in live cells. Integration of findings from the many approaches now employed in the study of enhancer function suggest a highly dynamic view for the action of enhancer activating factors, viewed on a time scale of milliseconds to seconds, rather than minutes to hours. WIREs Syst Biol Med 2018, 10:e1390. doi: 10.1002/wsbm.1390 This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > Imaging.
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Affiliation(s)
- Ido Goldstein
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Gordon L. Hager
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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45
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Festuccia N, Gonzalez I, Owens N, Navarro P. Mitotic bookmarking in development and stem cells. Development 2017; 144:3633-3645. [DOI: 10.1242/dev.146522] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The changes imposed on the nucleus, chromatin and its regulators during mitosis lead to the dismantlement of most gene regulatory processes. However, an increasing number of transcriptional regulators are being identified as capable of binding their genomic targets during mitosis. These so-called ‘mitotic bookmarking factors’ encompass transcription factors and chromatin modifiers that are believed to convey gene regulatory information from mother to daughter cells. In this Primer, we review mitotic bookmarking processes in development and stem cells and discuss the interest and potential importance of this concept with regard to epigenetic regulation and cell fate transitions involving cellular proliferation.
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Affiliation(s)
- Nicola Festuccia
- Epigenetics of Stem Cells, Department of Developmental and Stem Cell Biology, Institut Pasteur, CNRS UMR3738, 25 rue du Docteur Roux, 75015 Paris, France
| | - Inma Gonzalez
- Epigenetics of Stem Cells, Department of Developmental and Stem Cell Biology, Institut Pasteur, CNRS UMR3738, 25 rue du Docteur Roux, 75015 Paris, France
| | - Nick Owens
- Epigenetics of Stem Cells, Department of Developmental and Stem Cell Biology, Institut Pasteur, CNRS UMR3738, 25 rue du Docteur Roux, 75015 Paris, France
| | - Pablo Navarro
- Epigenetics of Stem Cells, Department of Developmental and Stem Cell Biology, Institut Pasteur, CNRS UMR3738, 25 rue du Docteur Roux, 75015 Paris, France
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46
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Schwessinger R, Suciu MC, McGowan SJ, Telenius J, Taylor S, Higgs DR, Hughes JR. Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints. Genome Res 2017; 27:1730-1742. [PMID: 28904015 PMCID: PMC5630036 DOI: 10.1101/gr.220202.117] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 08/07/2017] [Indexed: 12/22/2022]
Abstract
In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome.
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Affiliation(s)
- Ron Schwessinger
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Maria C Suciu
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Simon J McGowan
- Computational Biology Research Group, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Jelena Telenius
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Stephen Taylor
- Computational Biology Research Group, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Doug R Higgs
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
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47
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Birkenbihl RP, Liu S, Somssich IE. Transcriptional events defining plant immune responses. CURRENT OPINION IN PLANT BIOLOGY 2017; 38:1-9. [PMID: 28458046 DOI: 10.1016/j.pbi.2017.04.004] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Revised: 04/06/2017] [Accepted: 04/10/2017] [Indexed: 05/20/2023]
Abstract
Rapid and massive transcriptional reprogramming upon pathogen recognition is the decisive step in plant-phytopathogen interactions. Plant transcription factors (TFs) are key players in this process but they require a suite of other context-specific co-regulators to establish sensory transcription regulatory networks to bring about host immunity. Molecular, genetic and biochemical studies, particularly in the model plants Arabidopsis and rice, are continuously uncovering new components of the transcriptional machinery that can selectively impact host resistance toward a diverse range of pathogens. Moreover, detailed studies on key immune regulators, such as WRKY TFs and NPR1, are beginning to reveal the underlying mechanisms by which defense hormones influence the function of these factors. Here we provide a short update on such recent developments.
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Affiliation(s)
- Rainer P Birkenbihl
- Department of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Carl-von-Linné Weg 10, 50829 Koeln, Germany.
| | - Shouan Liu
- College of Plant Sciences, Jilin University, 130062 Changchun, China.
| | - Imre E Somssich
- Department of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Carl-von-Linné Weg 10, 50829 Koeln, Germany.
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48
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Inukai S, Kock KH, Bulyk ML. Transcription factor-DNA binding: beyond binding site motifs. Curr Opin Genet Dev 2017; 43:110-119. [PMID: 28359978 PMCID: PMC5447501 DOI: 10.1016/j.gde.2017.02.007] [Citation(s) in RCA: 200] [Impact Index Per Article: 28.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Revised: 02/02/2017] [Accepted: 02/07/2017] [Indexed: 12/12/2022]
Abstract
Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA. While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding. In this review, we discuss technological developments for identifying TF binding preferences and highlight recent discoveries that elaborate how TF interactions, local DNA structure, and genomic features influence TF-DNA binding. We highlight novel approaches for characterizing functional binding site motifs that promise to inform our understanding of how TF binding controls gene expression and ultimately contributes to phenotype.
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Affiliation(s)
- Sachi Inukai
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Kian Hong Kock
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Program in Biological and Biomedical Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Martha L Bulyk
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Program in Biological and Biomedical Sciences, Harvard University, Cambridge, MA 02138, USA; Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
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49
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Ramirez RN, El-Ali NC, Mager MA, Wyman D, Conesa A, Mortazavi A. Dynamic Gene Regulatory Networks of Human Myeloid Differentiation. Cell Syst 2017; 4:416-429.e3. [PMID: 28365152 DOI: 10.1016/j.cels.2017.03.005] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 10/31/2016] [Accepted: 03/03/2017] [Indexed: 12/15/2022]
Abstract
The reconstruction of gene regulatory networks underlying cell differentiation from high-throughput gene expression and chromatin data remains a challenge. Here, we derive dynamic gene regulatory networks for human myeloid differentiation using a 5-day time series of RNA-seq and ATAC-seq data. We profile HL-60 promyelocytes differentiating into macrophages, neutrophils, monocytes, and monocyte-derived macrophages. We find a rapid response in the expression of key transcription factors and lineage markers that only regulate a subset of their targets at a given time, which is followed by chromatin accessibility changes that occur later along with further gene expression changes. We observe differences between promyelocyte- and monocyte-derived macrophages at both the transcriptional and chromatin landscape level, despite using the same differentiation stimulus, which suggest that the path taken by cells in the differentiation landscape defines their end cell state. More generally, our approach of combining neighboring time points and replicates to achieve greater sequencing depth can efficiently infer footprint-based regulatory networks from long series data.
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Affiliation(s)
- Ricardo N Ramirez
- Developmental and Cell Biology, University of California Irvine, Irvine, CA 92697-2300, USA; Center for Complex Biological Systems, University of California Irvine, Irvine, CA 92697-2300, USA
| | - Nicole C El-Ali
- Developmental and Cell Biology, University of California Irvine, Irvine, CA 92697-2300, USA; Center for Complex Biological Systems, University of California Irvine, Irvine, CA 92697-2300, USA
| | - Mikayla Anne Mager
- Developmental and Cell Biology, University of California Irvine, Irvine, CA 92697-2300, USA; Center for Complex Biological Systems, University of California Irvine, Irvine, CA 92697-2300, USA
| | - Dana Wyman
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA 92697-2300, USA
| | - Ana Conesa
- Centro de Investigacion Principe Felipe, 46012 Valencia, Spain; Microbiology and Cell Science, University of Florida, Gainesville, FL 32603, USA
| | - Ali Mortazavi
- Developmental and Cell Biology, University of California Irvine, Irvine, CA 92697-2300, USA; Center for Complex Biological Systems, University of California Irvine, Irvine, CA 92697-2300, USA.
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50
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Goldstein I, Baek S, Presman DM, Paakinaho V, Swinstead EE, Hager GL. Transcription factor assisted loading and enhancer dynamics dictate the hepatic fasting response. Genome Res 2016; 27:427-439. [PMID: 28031249 PMCID: PMC5340970 DOI: 10.1101/gr.212175.116] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 12/21/2016] [Indexed: 02/03/2023]
Abstract
Fasting elicits transcriptional programs in hepatocytes leading to glucose and ketone production. This transcriptional program is regulated by many transcription factors (TFs). To understand how this complex network regulates the metabolic response to fasting, we aimed at isolating the enhancers and TFs dictating it. Measuring chromatin accessibility revealed that fasting massively reorganizes liver chromatin, exposing numerous fasting-induced enhancers. By utilizing computational methods in combination with dissecting enhancer features and TF cistromes, we implicated four key TFs regulating the fasting response: glucocorticoid receptor (GR), cAMP responsive element binding protein 1 (CREB1), peroxisome proliferator activated receptor alpha (PPARA), and CCAAT/enhancer binding protein beta (CEBPB). These TFs regulate fuel production by two distinctly operating modules, each controlling a separate metabolic pathway. The gluconeogenic module operates through assisted loading, whereby GR doubles the number of sites occupied by CREB1 as well as enhances CREB1 binding intensity and increases accessibility of CREB1 binding sites. Importantly, this GR-assisted CREB1 binding was enhancer-selective and did not affect all CREB1-bound enhancers. Single-molecule tracking revealed that GR increases the number and DNA residence time of a portion of chromatin-bound CREB1 molecules. These events collectively result in rapid synergistic gene expression and higher hepatic glucose production. Conversely, the ketogenic module operates via a GR-induced TF cascade, whereby PPARA levels are increased following GR activation, facilitating gradual enhancer maturation next to PPARA target genes and delayed ketogenic gene expression. Our findings reveal a complex network of enhancers and TFs that dynamically cooperate to restore homeostasis upon fasting.
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Affiliation(s)
- Ido Goldstein
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Diego M Presman
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Ville Paakinaho
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Erin E Swinstead
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene Expression, The National Cancer Institute, The National Institutes of Health, Bethesda, Maryland 20892, USA
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