1
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Angelis N, Baulies A, Hubl F, Kucharska A, Kelly G, Llorian M, Boeing S, Li VSW. Loss of ARID3A perturbs intestinal epithelial proliferation-differentiation ratio and regeneration. J Exp Med 2024; 221:e20232279. [PMID: 39150450 DOI: 10.1084/jem.20232279] [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: 12/11/2023] [Revised: 06/08/2024] [Accepted: 07/19/2024] [Indexed: 08/17/2024] Open
Abstract
Intestinal stem cells at the crypt divide and give rise to progenitor cells that proliferate and differentiate into various mature cell types in the transit-amplifying (TA) zone. Here, we showed that the transcription factor ARID3A regulates intestinal epithelial cell proliferation and differentiation at the TA progenitors. ARID3A forms an expression gradient from the villus tip to the upper crypt mediated by TGF-β and WNT. Intestinal-specific deletion of Arid3a reduces crypt proliferation, predominantly in TA cells. Bulk and single-cell transcriptomic analysis shows increased enterocyte and reduced secretory differentiation in the Arid3a cKO intestine, accompanied by enriched upper-villus gene signatures of both cell lineages. We find that the enhanced epithelial differentiation in the Arid3a-deficient intestine is caused by increased binding and transcription of HNF1 and HNF4. Finally, we show that loss of Arid3a impairs irradiation-induced regeneration with sustained cell death and reprogramming. Our findings imply that Arid3a functions to fine-tune the proliferation-differentiation dynamics at the TA progenitors, which are essential for injury-induced regeneration.
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Affiliation(s)
- Nikolaos Angelis
- Stem Cell and Cancer Biology Laboratory, The Francis Crick Institute , London, UK
| | - Anna Baulies
- Stem Cell and Cancer Biology Laboratory, The Francis Crick Institute , London, UK
| | - Florian Hubl
- Stem Cell and Cancer Biology Laboratory, The Francis Crick Institute , London, UK
| | - Anna Kucharska
- Stem Cell and Cancer Biology Laboratory, The Francis Crick Institute , London, UK
| | - Gavin Kelly
- Bioinformatics and Biostatistics Science Technology Platform, The Francis Crick Institute , London, UK
| | - Miriam Llorian
- Bioinformatics and Biostatistics Science Technology Platform, The Francis Crick Institute , London, UK
| | - Stefan Boeing
- Bioinformatics and Biostatistics Science Technology Platform, The Francis Crick Institute , London, UK
| | - Vivian S W Li
- Stem Cell and Cancer Biology Laboratory, The Francis Crick Institute , London, UK
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2
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Jovanovic VM, Narisu N, Bonnycastle LL, Tharakan R, Mesch KT, Glover HJ, Yan T, Sinha N, Sen C, Castellano D, Yang S, Blivis D, Ryu S, Bennett DF, Rosales-Soto G, Inman J, Ormanoglu P, LeClair CA, Xia M, Schneider M, Hernandez-Ochoa EO, Erdos MR, Simeonov A, Chen S, Singeç I, Collins FS, Doege CA, Tristan CA. Scalable Hypothalamic Arcuate Neuron Differentiation from Human Pluripotent Stem Cells Suitable for Modeling Metabolic and Reproductive Disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.601062. [PMID: 39005353 PMCID: PMC11244856 DOI: 10.1101/2024.06.27.601062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
The hypothalamus, composed of several nuclei, is essential for maintaining our body's homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.
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3
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Chen ACY, Jaiswal S, Martinez D, Yerinde C, Ji K, Miranda V, Fung ME, Weiss SA, Zschummel M, Taguchi K, Garris CS, Mempel TR, Hacohen N, Sen DR. The aged tumor microenvironment limits T cell control of cancer. Nat Immunol 2024; 25:1033-1045. [PMID: 38745085 DOI: 10.1038/s41590-024-01828-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/27/2024] [Indexed: 05/16/2024]
Abstract
The etiology and effect of age-related immune dysfunction in cancer is not completely understood. Here we show that limited priming of CD8+ T cells in the aged tumor microenvironment (TME) outweighs cell-intrinsic defects in limiting tumor control. Increased tumor growth in aging is associated with reduced CD8+ T cell infiltration and function. Transfer of T cells from young mice does not restore tumor control in aged mice owing to rapid induction of T cell dysfunction. Cell-extrinsic signals in the aged TME drive a tumor-infiltrating age-associated dysfunctional (TTAD) cell state that is functionally, transcriptionally and epigenetically distinct from canonical T cell exhaustion. Altered natural killer cell-dendritic cell-CD8+ T cell cross-talk in aged tumors impairs T cell priming by conventional type 1 dendritic cells and promotes TTAD cell formation. Aged mice are thereby unable to benefit from therapeutic tumor vaccination. Critically, myeloid-targeted therapy to reinvigorate conventional type 1 dendritic cells can improve tumor control and restore CD8+ T cell immunity in aging.
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Affiliation(s)
- Alex C Y Chen
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Sneha Jaiswal
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniela Martinez
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Cansu Yerinde
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Keely Ji
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Velita Miranda
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Megan E Fung
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Sarah A Weiss
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Maria Zschummel
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Kazuhiro Taguchi
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Christopher S Garris
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
| | - Thorsten R Mempel
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Nir Hacohen
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Debattama R Sen
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA.
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4
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Barisic D, Chin CR, Meydan C, Teater M, Tsialta I, Mlynarczyk C, Chadburn A, Wang X, Sarkozy M, Xia M, Carson SE, Raggiri S, Debek S, Pelzer B, Durmaz C, Deng Q, Lakra P, Rivas M, Steidl C, Scott DW, Weng AP, Mason CE, Green MR, Melnick A. ARID1A orchestrates SWI/SNF-mediated sequential binding of transcription factors with ARID1A loss driving pre-memory B cell fate and lymphomagenesis. Cancer Cell 2024; 42:583-604.e11. [PMID: 38458187 DOI: 10.1016/j.ccell.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 11/20/2023] [Accepted: 02/14/2024] [Indexed: 03/10/2024]
Abstract
ARID1A, a subunit of the canonical BAF nucleosome remodeling complex, is commonly mutated in lymphomas. We show that ARID1A orchestrates B cell fate during the germinal center (GC) response, facilitating cooperative and sequential binding of PU.1 and NF-kB at crucial genes for cytokine and CD40 signaling. The absence of ARID1A tilts GC cell fate toward immature IgM+CD80-PD-L2- memory B cells, known for their potential to re-enter new GCs. When combined with BCL2 oncogene, ARID1A haploinsufficiency hastens the progression of aggressive follicular lymphomas (FLs) in mice. Patients with FL with ARID1A-inactivating mutations preferentially display an immature memory B cell-like state with increased transformation risk to aggressive disease. These observations offer mechanistic understanding into the emergence of both indolent and aggressive ARID1A-mutant lymphomas through the formation of immature memory-like clonal precursors. Lastly, we demonstrate that ARID1A mutation induces synthetic lethality to SMARCA2/4 inhibition, paving the way for potential precision therapy for high-risk patients.
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Affiliation(s)
- Darko Barisic
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Christopher R Chin
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Matt Teater
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Ioanna Tsialta
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Coraline Mlynarczyk
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Amy Chadburn
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Xuehai Wang
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Margot Sarkozy
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Min Xia
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Sandra E Carson
- Department of Biochemistry, Cell and Molecular Biology, Weill Cornell Medicine, New York, NY, USA
| | - Santo Raggiri
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Sonia Debek
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA; Department of Experimental Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Benedikt Pelzer
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Ceyda Durmaz
- Graduate Program of Physiology, Biophysics and Systems Biology, Weill Cornell Medicine, New York, NY, USA
| | - Qing Deng
- Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Priya Lakra
- Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Martin Rivas
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA; Sylvester Comprehensive Cancer Center, University of Miami, FL, USA
| | - Christian Steidl
- Centre for Lymphoid Cancer, BC Cancer and University of British Columbia, British Columbia, Vancouver, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - David W Scott
- Centre for Lymphoid Cancer, BC Cancer and University of British Columbia, British Columbia, Vancouver, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrew P Weng
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Michael R Green
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ari Melnick
- Division of Hematology and Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA.
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5
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Roussos P, Ma Y, Girdhar K, Hoffman G, Fullard J, Bendl J. Sex differences in brain cell-type specific chromatin accessibility in schizophrenia. RESEARCH SQUARE 2024:rs.3.rs-4158509. [PMID: 38645177 PMCID: PMC11030506 DOI: 10.21203/rs.3.rs-4158509/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Our understanding of the sex-specific role of the non-coding genome in serious mental illness remains largely incomplete. To address this gap, we explored sex differences in 1,393 chromatin accessibility profiles, derived from neuronal and non-neuronal nuclei of two distinct cortical regions from 234 cases with serious mental illness and 235 controls. We identified sex-specific enhancer-promoter interactions and showed that they regulate genes involved in X-chromosome inactivation (XCI). Examining chromosomal conformation allowed us to identify sex-specific cis- and trans-regulatory domains (CRDs and TRDs). Co-localization of sex-specific TRDs with schizophrenia common risk variants pinpointed male-specific regulatory regions controlling a number of metabolic pathways. Additionally, enhancers from female-specific TRDs were found to regulate two genes known to escape XCI, (XIST and JPX), underlying the importance of TRDs in deciphering sex differences in schizophrenia. Overall, these findings provide extensive characterization of sex differences in the brain epigenome and disease-associated regulomes.
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Affiliation(s)
| | - Yixuan Ma
- Icahn School of Medicine at Mount Sinai
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6
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Karwacki-Neisius V, Jang A, Cukuroglu E, Tai A, Jiao A, Predes D, Yoon J, Brookes E, Chen J, Iberg A, Halbritter F, Õunap K, Gecz J, Schlaeger TM, Ho Sui S, Göke J, He X, Lehtinen MK, Pomeroy SL, Shi Y. WNT signalling control by KDM5C during development affects cognition. Nature 2024; 627:594-603. [PMID: 38383780 PMCID: PMC10954547 DOI: 10.1038/s41586-024-07067-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 01/12/2024] [Indexed: 02/23/2024]
Abstract
Although KDM5C is one of the most frequently mutated genes in X-linked intellectual disability1, the exact mechanisms that lead to cognitive impairment remain unknown. Here we use human patient-derived induced pluripotent stem cells and Kdm5c knockout mice to conduct cellular, transcriptomic, chromatin and behavioural studies. KDM5C is identified as a safeguard to ensure that neurodevelopment occurs at an appropriate timescale, the disruption of which leads to intellectual disability. Specifically, there is a developmental window during which KDM5C directly controls WNT output to regulate the timely transition of primary to intermediate progenitor cells and consequently neurogenesis. Treatment with WNT signalling modulators at specific times reveal that only a transient alteration of the canonical WNT signalling pathway is sufficient to rescue the transcriptomic and chromatin landscapes in patient-derived cells and to induce these changes in wild-type cells. Notably, WNT inhibition during this developmental period also rescues behavioural changes of Kdm5c knockout mice. Conversely, a single injection of WNT3A into the brains of wild-type embryonic mice cause anxiety and memory alterations. Our work identifies KDM5C as a crucial sentinel for neurodevelopment and sheds new light on KDM5C mutation-associated intellectual disability. The results also increase our general understanding of memory and anxiety formation, with the identification of WNT functioning in a transient nature to affect long-lasting cognitive function.
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Affiliation(s)
- Violetta Karwacki-Neisius
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Ahram Jang
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Engin Cukuroglu
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Albert Tai
- Department of Immunology, Tufts University School of Medicine, Boston, MA, USA
- Data Intensive Studies Center, Tufts University, Medford, MA, USA
| | - Alan Jiao
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Ludwig Institute for Cancer Research, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Danilo Predes
- Department of Neurology, F. M Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joon Yoon
- Department of Biostatistics, The Harvard Chan School of Public Health, Bioinformatics Core, Cambridge, MA, USA
| | - Emily Brookes
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- School of Biological Sciences, University of Southampton, Southampton, UK
| | - Jiekai Chen
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- CAS Key Laboratory of Regenerative Biology and Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Aimee Iberg
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Florian Halbritter
- Children's Cancer Research Institute, St Anna Kinderkrebsforschung, Vienna, Austria
| | - Katrin Õunap
- Department of Clinical Genetics, Genetic and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Jozef Gecz
- Adelaide Medical School and Robinson Research Institute, University of Adelaide, Adelaide, South Australia, Australia
| | - Thorsten M Schlaeger
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA, USA
| | - Shannan Ho Sui
- Department of Biostatistics, The Harvard Chan School of Public Health, Bioinformatics Core, Cambridge, MA, USA
| | - Jonathan Göke
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Xi He
- Department of Neurology, F. M Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria K Lehtinen
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Scott L Pomeroy
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yang Shi
- Division of Newborn Medicine and Epigenetics Program, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Ludwig Institute for Cancer Research, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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7
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Walker JT, Saunders DC, Rai V, Chen HH, Orchard P, Dai C, Pettway YD, Hopkirk AL, Reihsmann CV, Tao Y, Fan S, Shrestha S, Varshney A, Petty LE, Wright JJ, Ventresca C, Agarwala S, Aramandla R, Poffenberger G, Jenkins R, Mei S, Hart NJ, Phillips S, Kang H, Greiner DL, Shultz LD, Bottino R, Liu J, Below JE, Parker SCJ, Powers AC, Brissova M. Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature 2023; 624:621-629. [PMID: 38049589 DOI: 10.1038/s41586-023-06693-2] [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: 12/02/2021] [Accepted: 09/28/2023] [Indexed: 12/06/2023]
Abstract
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.
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Affiliation(s)
- John T Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chunhua Dai
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yasminye D Pettway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexander L Hopkirk
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Conrad V Reihsmann
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yicheng Tao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Simin Fan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Shristi Shrestha
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan J Wright
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christa Ventresca
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Samir Agarwala
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Radhika Aramandla
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Greg Poffenberger
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Regina Jenkins
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shaojun Mei
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nathaniel J Hart
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sharon Phillips
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dale L Greiner
- Department of Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA, USA
| | | | - Rita Bottino
- Imagine Pharma, Devon, PA, USA
- Institute of Cellular Therapeutics, Allegheny-Singer Research Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Jie Liu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Alvin C Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA.
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- VA Tennessee Valley Healthcare System, Nashville, TN, USA.
| | - Marcela Brissova
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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8
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van Lopik J, Alizada A, Trapotsi MA, Hannon GJ, Bornelöv S, Czech Nicholson B. Unistrand piRNA clusters are an evolutionarily conserved mechanism to suppress endogenous retroviruses across the Drosophila genus. Nat Commun 2023; 14:7337. [PMID: 37957172 PMCID: PMC10643416 DOI: 10.1038/s41467-023-42787-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 10/18/2023] [Indexed: 11/15/2023] Open
Abstract
The PIWI-interacting RNA (piRNA) pathway prevents endogenous genomic parasites, i.e. transposable elements, from damaging the genetic material of animal gonadal cells. Specific regions in the genome, called piRNA clusters, are thought to define each species' piRNA repertoire and therefore its capacity to recognize and silence specific transposon families. The unistrand cluster flamenco (flam) is essential in the somatic compartment of the Drosophila ovary to restrict Gypsy-family transposons from infecting the neighbouring germ cells. Disruption of flam results in transposon de-repression and sterility, yet it remains unknown whether this silencing mechanism is present more widely. Here, we systematically characterise 119 Drosophila species and identify five additional flam-like clusters separated by up to 45 million years of evolution. Small RNA-sequencing validated these as bona-fide unistrand piRNA clusters expressed in somatic cells of the ovary, where they selectively target transposons of the Gypsy family. Together, our study provides compelling evidence of a widely conserved transposon silencing mechanism that co-evolved with virus-like Gypsy-family transposons.
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Affiliation(s)
- Jasper van Lopik
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Azad Alizada
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Maria-Anna Trapotsi
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Gregory J Hannon
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Susanne Bornelöv
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK.
| | - Benjamin Czech Nicholson
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK.
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9
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Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. RESEARCH SQUARE 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
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Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
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10
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Girdhar K, Bendl J, Baumgartner A, Therrien K, Venkatesh S, Mathur D, Dong P, Rahman S, Kleopoulos SP, Misir R, Reach SM, Auluck PK, Marenco S, Lewis DA, Haroutunian V, Funk C, Voloudakis G, Hoffman GE, Fullard JF, Roussos P. The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.02.23296067. [PMID: 37873320 PMCID: PMC10593028 DOI: 10.1101/2023.10.02.23296067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Non-coding variants increase risk of neuropsychiatric disease. However, our understanding of the cell-type specific role of the non-coding genome in disease is incomplete. We performed population scale (N=1,393) chromatin accessibility profiling of neurons and non-neurons from two neocortical brain regions: the anterior cingulate cortex and dorsolateral prefrontal cortex. Across both regions, we observed notable differences in neuronal chromatin accessibility between schizophrenia cases and controls. A per-sample disease pseudotime was positively associated with genetic liability for schizophrenia. Organizing chromatin into cis- and trans-regulatory domains, identified a prominent neuronal trans-regulatory domain (TRD1) active in immature glutamatergic neurons during fetal development. Polygenic risk score analysis using genetic variants within chromatin accessibility of TRD1 successfully predicted susceptibility to schizophrenia in the Million Veteran Program cohort. Overall, we present the most extensive resource to date of chromatin accessibility in the human cortex, yielding insights into the cell-type specific etiology of schizophrenia.
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Affiliation(s)
- Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Karen Therrien
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Deepika Mathur
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah M Reach
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pavan K Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Cory Funk
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, 10468, USA
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11
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Takeuchi F, Liang YQ, Shimizu-Furusawa H, Isono M, Ang MY, Mori K, Mori T, Kakazu E, Yoshio S, Kato N. Gene-regulation modules in nonalcoholic fatty liver disease revealed by single-nucleus ATAC-seq. Life Sci Alliance 2023; 6:e202301988. [PMID: 37491046 PMCID: PMC10368228 DOI: 10.26508/lsa.202301988] [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: 02/13/2023] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 07/27/2023] Open
Abstract
We investigated the progression of nonalcoholic fatty liver disease from fatty liver to steatohepatitis using single-nucleus and bulk ATAC-seq on the livers of rats fed a high-fat diet (HFD). Rats fed HFD for 4 wk developed fatty liver, and those fed HFD for 8 wk further progressed to steatohepatitis. We observed an increase in the proportion of inflammatory macrophages, consistent with the pathological progression. Utilizing machine learning, we divided global gene regulation into modules, wherein transcription factors within a module could regulate genes within the same module, reaffirming known regulatory relationships between transcription factors and biological processes. We identified core genes-central to co-expression and protein-protein interaction-for the biological processes discovered. Notably, a large part of the core genes overlapped with genes previously implicated in nonalcoholic fatty liver disease. Single-nucleus ATAC-seq, combined with data-driven statistical analysis, offers insight into in vivo global gene regulation as a combination of modules and assists in identifying core genes of relevant biological processes.
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Affiliation(s)
- Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Systems Genomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Yi-Qiang Liang
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hana Shimizu-Furusawa
- Department of Hygiene and Public Health, School of Medicine, Teikyo University, Tokyo, Japan
| | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Mia Yang Ang
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Department of Clinical Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kotaro Mori
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Taizo Mori
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Eiji Kakazu
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Sachiyo Yoshio
- Department of Liver Diseases, The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, Japan
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Department of Clinical Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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12
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Freeman TF, Zhao Q, Surya A, Rothe R, Cenik ES. Ribosome biogenesis disruption mediated chromatin structure changes revealed by SRAtac, a customizable end to end analysis pipeline for ATAC-seq. BMC Genomics 2023; 24:512. [PMID: 37658321 PMCID: PMC10472662 DOI: 10.1186/s12864-023-09576-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 08/11/2023] [Indexed: 09/03/2023] Open
Abstract
The nucleolus is a large nuclear body that serves as the primary site for ribosome biogenesis. Recent studies have suggested that it also plays an important role in organizing chromatin architecture. However, to establish a causal relationship between nucleolar ribosome assembly and chromatin architecture, genetic tools are required to disrupt nucleolar ribosome biogenesis. In this study, we used ATAC-seq to investigate changes in chromatin accessibility upon specific depletion of two ribosome biogenesis components, RPOA-2 and GRWD-1, in the model organism Caenorhabditis elegans. To facilitate the analysis of ATAC-seq data, we introduced two tools: SRAlign, an extensible NGS data processing workflow, and SRAtac, a customizable end-to-end ATAC-seq analysis pipeline. Our results revealed highly comparable changes in chromatin accessibility following both RPOA-2 and GRWD-1 perturbations. However, we observed a weak correlation between changes in chromatin accessibility and gene expression. While our findings corroborate the idea of a feedback mechanism between ribosomal RNA synthesis, nucleolar ribosome large subunit biogenesis, and chromatin structure during the L1 stage of C. elegans development, they also prompt questions regarding the functional impact of these alterations on gene expression.
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Affiliation(s)
- Trevor F Freeman
- Department of Molecular Biosciences, University of Texas, Austin, TX, 78712, USA
| | - Qiuxia Zhao
- Department of Molecular Biosciences, University of Texas, Austin, TX, 78712, USA
| | - Agustian Surya
- Department of Molecular Biosciences, University of Texas, Austin, TX, 78712, USA
| | - Reed Rothe
- Department of Molecular Biosciences, University of Texas, Austin, TX, 78712, USA
| | - Elif Sarinay Cenik
- Department of Molecular Biosciences, University of Texas, Austin, TX, 78712, USA.
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13
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Pruvost M, Patzig J, Yattah C, Selcen I, Hernandez M, Park HJ, Moyon S, Liu S, Morioka MS, Shopland L, Al-Dalahmah O, Bendl J, Fullard JF, Roussos P, Goldman J, He Y, Dupree JL, Casaccia P. The stability of the myelinating oligodendrocyte transcriptome is regulated by the nuclear lamina. Cell Rep 2023; 42:112848. [PMID: 37515770 PMCID: PMC10600948 DOI: 10.1016/j.celrep.2023.112848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/26/2023] [Accepted: 07/07/2023] [Indexed: 07/31/2023] Open
Abstract
Oligodendrocytes are specialized cells that insulate and support axons with their myelin membrane, allowing proper brain function. Here, we identify lamin A/C (LMNA/C) as essential for transcriptional and functional stability of myelinating oligodendrocytes. We show that LMNA/C levels increase with differentiation of progenitors and that loss of Lmna in differentiated oligodendrocytes profoundly alters their chromatin accessibility and transcriptional signature. Lmna deletion in myelinating glia is compatible with normal developmental myelination. However, altered chromatin accessibility is detected in fully differentiated oligodendrocytes together with increased expression of progenitor genes and decreased levels of lipid-related transcription factors and inner mitochondrial membrane transcripts. These changes are accompanied by altered brain metabolism, lower levels of myelin-related lipids, and altered mitochondrial structure in oligodendrocytes, thereby resulting in myelin thinning and the development of a progressively worsening motor phenotype. Overall, our data identify LMNA/C as essential for maintaining the transcriptional and functional stability of myelinating oligodendrocytes.
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Affiliation(s)
- Mathilde Pruvost
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA
| | - Julia Patzig
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA
| | - Camila Yattah
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Graduate Program in Biochemistry, The Graduate Center of The City University of New York, 365 5(th) Avenue, New York, NY 10016, USA
| | - Ipek Selcen
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Graduate Program in Biochemistry, The Graduate Center of The City University of New York, 365 5(th) Avenue, New York, NY 10016, USA
| | - Marylens Hernandez
- Graduate School of Biological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hye-Jin Park
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA
| | - Sarah Moyon
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA
| | - Shibo Liu
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Structural Biology Initiative, Advanced Science Research Center at the Graduate Center, City University of New York, New York, NY 10031, USA
| | - Malia S Morioka
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Macaulay Honors College, City College of New York, New York, NY 10031, USA
| | - Lindsay Shopland
- Jackson Laboratory, 1650 Santa Ana Ave, Sacramento, CA 95835, USA
| | - Osama Al-Dalahmah
- Department of Pathology and Cell Biology, Division of Neuropathology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, and the New York Presbyterian Hospital, New York, NY 10032, USA
| | - Jaroslav Bendl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY 10468, USA; Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - James Goldman
- Department of Pathology and Cell Biology, Division of Neuropathology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, and the New York Presbyterian Hospital, New York, NY 10032, USA
| | - Ye He
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Macaulay Honors College, City College of New York, New York, NY 10031, USA
| | - Jeffrey L Dupree
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Patrizia Casaccia
- Neuroscience Initiative at the Advanced Science Research Center of the Graduate Center of the City University of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA; Graduate Program in Biochemistry, The Graduate Center of The City University of New York, 365 5(th) Avenue, New York, NY 10016, USA; Graduate School of Biological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Graduate Program in Biology, The Graduate Center of The City University of New York, 365 5th Avenue, New York, NY 10016, USA.
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14
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Wang E, Wang M, Guo L, Fullard JF, Micallef C, Bendl J, Song WM, Ming C, Huang Y, Li Y, Yu K, Peng J, Bennett DA, De Jager PL, Roussos P, Haroutunian V, Zhang B. Genome-wide methylomic regulation of multiscale gene networks in Alzheimer's disease. Alzheimers Dement 2023; 19:3472-3495. [PMID: 36811307 PMCID: PMC10440222 DOI: 10.1002/alz.12969] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/19/2022] [Indexed: 02/24/2023]
Abstract
INTRODUCTION Recent studies revealed the association of abnormal methylomic changes with Alzheimer's disease (AD) but there is a lack of systematic study of the impact of methylomic alterations over the molecular networks underlying AD. METHODS We profiled genome-wide methylomic variations in the parahippocampal gyrus from 201 post mortem control, mild cognitive impaired, and AD brains. RESULTS We identified 270 distinct differentially methylated regions (DMRs) associated with AD. We quantified the impact of these DMRs on each gene and each protein as well as gene and protein co-expression networks. DNA methylation had a profound impact on both AD-associated gene/protein modules and their key regulators. We further integrated the matched multi-omics data to show the impact of DNA methylation on chromatin accessibility, which further modulates gene and protein expression. DISCUSSION The quantified impact of DNA methylation on gene and protein networks underlying AD identified potential upstream epigenetic regulators of AD. HIGHLIGHTS A cohort of DNA methylation data in the parahippocampal gyrus was developed from 201 post mortem control, mild cognitive impaired, and Alzheimer's disease (AD) brains. Two hundred seventy distinct differentially methylated regions (DMRs) were found to be associated with AD compared to normal control. A metric was developed to quantify methylation impact on each gene and each protein. DNA methylation was found to have a profound impact on not only the AD-associated gene modules but also key regulators of the gene and protein networks. Key findings were validated in an independent multi-omics cohort in AD. The impact of DNA methylation on chromatin accessibility was also investigated by integrating the matched methylomic, epigenomic, transcriptomic, and proteomic data.
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Affiliation(s)
- Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Lei Guo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - John F Fullard
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Courtney Micallef
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Jaroslav Bendl
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute of Genomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Won-min Song
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Chen Ming
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Yong Huang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Yuxin Li
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Kaiwen Yu
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Philip L. De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology and the Taub Institute, Columbia University Medical Center, New York, New York, USA
| | - Panos Roussos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute of Genomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, 130 West Kingsbridge Road, Bronx, NY 10468, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, 130 West Kingsbridge Road, Bronx, NY 10468, USA
- The Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, One Gustave L Levy Place, New York, NY 10029, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute of Genomics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
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15
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Vu HTH, Zhang Y, Tuteja G, Dorman KS. Unsupervised contrastive peak caller for ATAC-seq. Genome Res 2023; 33:1133-1144. [PMID: 37217250 PMCID: PMC10538491 DOI: 10.1101/gr.277677.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 04/27/2023] [Indexed: 05/24/2023]
Abstract
The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a common assay to identify chromatin accessible regions by using a Tn5 transposase that can access, cut, and ligate adapters to DNA fragments for subsequent amplification and sequencing. These sequenced regions are quantified and tested for enrichment in a process referred to as "peak calling." Most unsupervised peak calling methods are based on simple statistical models and suffer from elevated false positive rates. Newly developed supervised deep learning methods can be successful, but they rely on high quality labeled data for training, which can be difficult to obtain. Moreover, though biological replicates are recognized to be important, there are no established approaches for using replicates in the deep learning tools, and the approaches available for traditional methods either cannot be applied to ATAC-seq, where control samples may be unavailable, or are post hoc and do not capitalize on potentially complex, but reproducible signal in the read enrichment data. Here, we propose a novel peak caller that uses unsupervised contrastive learning to extract shared signals from multiple replicates. Raw coverage data are encoded to obtain low-dimensional embeddings and optimized to minimize a contrastive loss over biological replicates. These embeddings are passed to another contrastive loss for learning and predicting peaks and decoded to denoised data under an autoencoder loss. We compared our replicative contrastive learner (RCL) method with other existing methods on ATAC-seq data, using annotations from ChromHMM genomic labels and transcription factor ChIP-seq as noisy truth. RCL consistently achieved the best performance.
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Affiliation(s)
- Ha T H Vu
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa 50011, USA
- Department of Genetics, Development and Cell Biology, Ames, Iowa 50011, USA
| | - Yudi Zhang
- Department of Statistics, Iowa State University, Ames, Iowa 50011, USA
| | - Geetu Tuteja
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa 50011, USA
- Department of Genetics, Development and Cell Biology, Ames, Iowa 50011, USA
| | - Karin S Dorman
- Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa 50011, USA;
- Department of Genetics, Development and Cell Biology, Ames, Iowa 50011, USA
- Department of Statistics, Iowa State University, Ames, Iowa 50011, USA
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16
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Huynh K, Smith BR, Macdonald SJ, Long AD. Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster. PLoS Genet 2023; 19:e1010439. [PMID: 37146087 PMCID: PMC10191298 DOI: 10.1371/journal.pgen.1010439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 05/17/2023] [Accepted: 04/20/2023] [Indexed: 05/07/2023] Open
Abstract
We use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks.
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Affiliation(s)
- Khoi Huynh
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
| | - Brittny R. Smith
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
| | - Stuart J. Macdonald
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
- Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America
| | - Anthony D. Long
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
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17
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Kühlwein JK, Ruf WP, Kandler K, Witzel S, Lang C, Mulaw MA, Ekici AB, Weishaupt JH, Ludolph AC, Grozdanov V, Danzer KM. ALS is imprinted in the chromatin accessibility of blood cells. Cell Mol Life Sci 2023; 80:131. [PMID: 37095391 PMCID: PMC10126052 DOI: 10.1007/s00018-023-04769-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/20/2023] [Accepted: 03/27/2023] [Indexed: 04/26/2023]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a complex and incurable neurodegenerative disorder in which genetic and epigenetic factors contribute to the pathogenesis of all forms of ALS. The interplay of genetic predisposition and environmental footprints generates epigenetic signatures in the cells of affected tissues, which then alter transcriptional programs. Epigenetic modifications that arise from genetic predisposition and systemic environmental footprints should in theory be detectable not only in affected CNS tissue but also in the periphery. Here, we identify an ALS-associated epigenetic signature ('epiChromALS') by chromatin accessibility analysis of blood cells of ALS patients. In contrast to the blood transcriptome signature, epiChromALS includes also genes that are not expressed in blood cells; it is enriched in CNS neuronal pathways and it is present in the ALS motor cortex. By combining simultaneous ATAC-seq and RNA-seq with single-cell sequencing in PBMCs and motor cortex from ALS patients, we demonstrate that epigenetic changes associated with the neurodegenerative disease can be found in the periphery, thus strongly suggesting a mechanistic link between the epigenetic regulation and disease pathogenesis.
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Affiliation(s)
- Julia K Kühlwein
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Wolfgang P Ruf
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Katharina Kandler
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Simon Witzel
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Christina Lang
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Medhanie A Mulaw
- Medical Faculty, University of Ulm, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Arif B Ekici
- Institute of Human Genetics, University Clinic Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, 91054, Erlangen, Bayern, Germany
| | - Jochen H Weishaupt
- Division for Neurodegenerative Diseases, Neurology Department, University Medicine Mannheim, Heidelberg University, 68167, Mannheim, Baden-Wuerttemberg, Germany
| | - Albert C Ludolph
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
- German Center for Neurodegenerative Diseases (DZNE), 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Veselin Grozdanov
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany
| | - Karin M Danzer
- Department of Neurology, University Clinic, University of Ulm, Albert-Einstein-Allee 11, 89081, Ulm, Baden-Wuerttemberg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), 89081, Ulm, Baden-Wuerttemberg, Germany.
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18
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Mohammed Ismail W, Mazzone A, Ghiraldini FG, Kaur J, Bains M, Munankarmy A, Bagwell MS, Safgren SL, Moore-Weiss J, Buciuc M, Shimp L, Leach KA, Duarte LF, Nagi CS, Carcamo S, Chung CY, Hasson D, Dadgar N, Zhong J, Lee JH, Couch FJ, Revzin A, Ordog T, Bernstein E, Gaspar-Maia A. MacroH2A histone variants modulate enhancer activity to repress oncogenic programs and cellular reprogramming. Commun Biol 2023; 6:215. [PMID: 36823213 PMCID: PMC9950461 DOI: 10.1038/s42003-023-04571-1] [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: 10/03/2022] [Accepted: 02/09/2023] [Indexed: 02/25/2023] Open
Abstract
Considerable efforts have been made to characterize active enhancer elements, which can be annotated by accessible chromatin and H3 lysine 27 acetylation (H3K27ac). However, apart from poised enhancers that are observed in early stages of development and putative silencers, the functional significance of cis-regulatory elements lacking H3K27ac is poorly understood. Here we show that macroH2A histone variants mark a subset of enhancers in normal and cancer cells, which we coined 'macro-Bound Enhancers', that modulate enhancer activity. We find macroH2A variants localized at enhancer elements that are devoid of H3K27ac in a cell type-specific manner, indicating a role for macroH2A at inactive enhancers to maintain cell identity. In following, reactivation of macro-bound enhancers is associated with oncogenic programs in breast cancer and their repressive role is correlated with the activity of macroH2A2 as a negative regulator of BRD4 chromatin occupancy. Finally, through single cell epigenomic profiling of normal mammary stem cells derived from mice, we show that macroH2A deficiency facilitates increased activity of transcription factors associated with stem cell activity.
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Affiliation(s)
- Wazim Mohammed Ismail
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Amelia Mazzone
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Flavia G Ghiraldini
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jagneet Kaur
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Manvir Bains
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Amik Munankarmy
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Monique S Bagwell
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Stephanie L Safgren
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - John Moore-Weiss
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Marina Buciuc
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Lynzie Shimp
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Kelsey A Leach
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Luis F Duarte
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chandandeep S Nagi
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
| | - Saul Carcamo
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute Bioinformatics for Next Generation Sequencing (BiNGS) Shared Resource Facility, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Chi-Yeh Chung
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dan Hasson
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute Bioinformatics for Next Generation Sequencing (BiNGS) Shared Resource Facility, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Neda Dadgar
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Jian Zhong
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Jeong-Heon Lee
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Fergus J Couch
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Alexander Revzin
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Tamas Ordog
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA
| | - Emily Bernstein
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexandre Gaspar-Maia
- Division of Experimental Pathology, Department of Lab Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
- Center for Individualized Medicine, Epigenomics program, Mayo Clinic, Rochester, MN, USA.
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19
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Criscione SW, Martin MJ, Oien DB, Gorthi A, Miragaia RJ, Zhang J, Chen H, Karl DL, Mendler K, Markovets A, Gagrica S, Delpuech O, Dry JR, Grondine M, Hattersley MM, Urosevic J, Floc’h N, Drew L, Yao Y, Smith PD. The landscape of therapeutic vulnerabilities in EGFR inhibitor osimertinib drug tolerant persister cells. NPJ Precis Oncol 2022; 6:95. [PMID: 36575215 PMCID: PMC9794691 DOI: 10.1038/s41698-022-00337-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 12/12/2022] [Indexed: 12/28/2022] Open
Abstract
Third-generation EGFR tyrosine kinase inhibitors (EGFR-TKIs), including osimertinib, an irreversible EGFR-TKI, are important treatments for non-small cell lung cancer with EGFR-TKI sensitizing or EGFR T790M resistance mutations. While patients treated with osimertinib show clinical benefit, disease progression and drug resistance are common. Emergence of de novo acquired resistance from a drug tolerant persister (DTP) cell population is one mechanism proposed to explain progression on osimertinib and other targeted cancer therapies. Here we profiled osimertinib DTPs using RNA-seq and ATAC-seq to characterize the features of these cells and performed drug screens to identify therapeutic vulnerabilities. We identified several vulnerabilities in osimertinib DTPs that were common across models, including sensitivity to MEK, AURKB, BRD4, and TEAD inhibition. We linked several of these vulnerabilities to gene regulatory changes, for example, TEAD vulnerability was consistent with evidence of Hippo pathway turning off in osimertinib DTPs. Last, we used genetic approaches using siRNA knockdown or CRISPR knockout to validate AURKB, BRD4, and TEAD as the direct targets responsible for the vulnerabilities observed in the drug screen.
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Affiliation(s)
- Steven W. Criscione
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Matthew J. Martin
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Derek B. Oien
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Aparna Gorthi
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA ,grid.267309.90000 0001 0629 5880Department of Cell Systems & Anatomy, Greehey Children’s Cancer Research Institute, University of Texas at Health San Antonio, San Antonio, TX USA
| | - Ricardo J. Miragaia
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Jingwen Zhang
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Huawei Chen
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Daniel L. Karl
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Kerrin Mendler
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Aleksandra Markovets
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Sladjana Gagrica
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Oona Delpuech
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Jonathan R. Dry
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Michael Grondine
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Maureen M. Hattersley
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Jelena Urosevic
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Nicolas Floc’h
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Lisa Drew
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Yi Yao
- grid.418152.b0000 0004 0543 9493Research and Early Development, Oncology R&D, AstraZeneca, Boston, MA USA
| | - Paul D. Smith
- grid.417815.e0000 0004 5929 4381Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
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20
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Li S, Zong X, Zhang L, Li L, Wu J. A chromatin accessibility landscape during early adipogenesis of human adipose-derived stem cells. Adipocyte 2022; 11:239-249. [PMID: 35435105 PMCID: PMC9037556 DOI: 10.1080/21623945.2022.2063015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Obesity has become a serious global public health problem; a deeper understanding of systemic change of chromatin accessibility during human adipogenesis contributes to conquering obesity and its related diseases. Here, we applied the ATAC-seq method to depict a high-quality genome‐wide time-resolved accessible chromatin atlas during adipogenesis of human adipose-derived stem cells (hASCs). Our data indicated that the chromatin accessibility drastic dynamically reformed during the adipogenesis of hASCs and 8 h may be the critical transition node of adipogenesis chromatin states from commitment phase to determination phase. Moreover, upon adipogenesis, we also found that the chromatin accessibility of regions related to anti-apoptotic, angiogenic and immunoregulatory gradually increased, which is beneficial to maintaining the health of adipose tissue (AT). Finally, the chromatin accessibility changed significantly in intronic regions of peroxisome proliferator‐activated receptor γ during adipogenesis, and these regions were rich in transcription factors binding motifs that were exposed for further regulation. Overall, we systematically analysed the complex change of chromatin accessibility occurring in the early stage of adipogenesis and deepened our understanding of human adipogenesis. Furthermore, we also provided a good reference data resource of genome‐wide chromatin accessibility for future studies on human adipogenesis.
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Affiliation(s)
- Sen Li
- Department of Biochemistry & Immunology, Capital Institute of Pediatrics, Beijing, China
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, China
| | - Xiaolin Zong
- Division of achievements transformation, Development Center for Medical Science & Technology National Health Commission of the People’s Republic of China, Beijing, China
| | - Liheng Zhang
- Shanghai Jiayin Biotechnology Co., Ltd, Shanghai, China
| | - Luya Li
- Department of Biochemistry & Immunology, Capital Institute of Pediatrics, Beijing, China
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, China
| | - Jianxin Wu
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, China
- Beijing TongRen Hospital, Capital Medical University, Beijing, China
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21
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Tu X, Marand AP, Schmitz RJ, Zhong S. A combinatorial indexing strategy for low-cost epigenomic profiling of plant single cells. PLANT COMMUNICATIONS 2022; 3:100308. [PMID: 35605196 PMCID: PMC9284282 DOI: 10.1016/j.xplc.2022.100308] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 06/15/2023]
Abstract
Understanding how cis-regulatory elements facilitate gene expression is a key question in biology. Recent advances in single-cell genomics have led to the discovery of cell-specific chromatin landscapes that underlie transcription programs in animal models. However, the high equipment and reagent costs of commercial systems limit their applications for many laboratories. In this study, we developed a combinatorial index and dual PCR barcode strategy to profile the Arabidopsis thaliana root single-cell epigenome without any specialized equipment. We generated chromatin accessibility profiles for 13 576 root nuclei with an average of 12 784 unique Tn5 integrations per cell. Integration of the single-cell assay for transposase-accessible chromatin sequencing and RNA sequencing data sets enabled the identification of 24 cell clusters with unique transcription, chromatin, and cis-regulatory signatures. Comparison with single-cell data generated using the commercial microfluidic platform from 10X Genomics revealed that this low-cost combinatorial index method is capable of unbiased identification of cell-type-specific chromatin accessibility. We anticipate that, by removing cost, instrumentation, and other technical obstacles, this method will be a valuable tool for routine investigation of single-cell epigenomes and provide new insights into plant growth and development and plant interactions with the environment.
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Affiliation(s)
- Xiaoyu Tu
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
| | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, GA 30602, USA.
| | - Silin Zhong
- State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, China.
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22
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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: 112] [Impact Index Per Article: 56.0] [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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23
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Niu YN, Roberts EG, Denisko D, Hoffman MM. Assessing and assuring interoperability of a genomics file format. Bioinformatics 2022; 38:3327-3336. [PMID: 35575355 PMCID: PMC9237710 DOI: 10.1093/bioinformatics/btac327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 03/30/2022] [Accepted: 05/11/2022] [Indexed: 12/01/2022] Open
Abstract
Motivation Bioinformatics software tools operate largely through the use of specialized genomics file formats. Often these formats lack formal specification, making it difficult or impossible for the creators of these tools to robustly test them for correct handling of input and output. This causes problems in interoperability between different tools that, at best, wastes time and frustrates users. At worst, interoperability issues could lead to undetected errors in scientific results. Results We developed a new verification system, Acidbio, which tests for correct behavior in bioinformatics software packages. We crafted tests to unify correct behavior when tools encounter various edge cases—potentially unexpected inputs that exemplify the limits of the format. To analyze the performance of existing software, we tested the input validation of 80 Bioconda packages that parsed the Browser Extensible Data (BED) format. We also used a fuzzing approach to automatically perform additional testing. Of 80 software packages examined, 75 achieved less than 70% correctness on our test suite. We categorized multiple root causes for the poor performance of different types of software. Fuzzing detected other errors that the manually designed test suite could not. We also created a badge system that developers can use to indicate more precisely which BED variants their software accepts and to advertise the software’s performance on the test suite. Availability and implementation Acidbio is available at https://github.com/hoffmangroup/acidbio. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yi Nian Niu
- Princess Margaret Cancer Centre University Health Network, Toronto, ON, M5G 2C1, Canada
| | - Eric G Roberts
- Princess Margaret Cancer Centre University Health Network, Toronto, ON, M5G 2C1, Canada
| | - Danielle Denisko
- Princess Margaret Cancer Centre University Health Network, Toronto, ON, M5G 2C1, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada
| | - Michael M Hoffman
- Princess Margaret Cancer Centre University Health Network, Toronto, ON, M5G 2C1, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.,Department of Computer Science, University of Toronto, Toronto, ON, M5S 2E4, Canada.,Vector Institute, Toronto, ON, M5G 1M1, Canada
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24
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Shah K, Maradana MR, Joaquina Delàs M, Metidji A, Graelmann F, Llorian M, Chakravarty P, Li Y, Tolaini M, Shapiro M, Kelly G, Cheshire C, Bhurta D, Bharate SB, Stockinger B. Cell-intrinsic Aryl Hydrocarbon Receptor signalling is required for the resolution of injury-induced colonic stem cells. Nat Commun 2022; 13:1827. [PMID: 35383166 PMCID: PMC8983642 DOI: 10.1038/s41467-022-29098-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 02/23/2022] [Indexed: 12/17/2022] Open
Abstract
The aryl hydrocarbon receptor (AHR) is an environmental sensor that integrates microbial and dietary cues to influence physiological processes within the intestinal microenvironment, protecting against colitis and colitis-associated colorectal cancer development. Rapid tissue regeneration upon injury is important for the reinstatement of barrier integrity and its dysregulation promotes malignant transformation. Here we show that AHR is important for the termination of the regenerative response and the reacquisition of mature epithelial cell identity post injury in vivo and in organoid cultures in vitro. Using an integrative multi-omics approach in colon organoids, we show that AHR is required for timely termination of the regenerative response through direct regulation of transcription factors involved in epithelial cell differentiation as well as restriction of chromatin accessibility to regeneration-associated Yap/Tead transcriptional targets. Safeguarding a regulated regenerative response places AHR at a pivotal position in the delicate balance between controlled regeneration and malignant transformation. Rapid intestinal regeneration after injury is critical to maintain barrier integrity and homeostasis, but must be tightly controlled to prevent tumorigenesis. Here they show that the aryl hydrocarbon receptor is required to terminate the regenerative response after wound healing.
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Affiliation(s)
| | | | | | - Amina Metidji
- Department of Oncology, St Jude Children's Hospital, Memphis, TN, USA
| | - Frederike Graelmann
- Immunology and Environment, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | | | | | - Ying Li
- The Francis Crick Institute, London, UK
| | | | | | | | | | - Deendyal Bhurta
- Natural Products & Medicinal Chemistry Division, CSIR - Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India
| | - Sandip B Bharate
- Natural Products & Medicinal Chemistry Division, CSIR - Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India
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25
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Sumida TS, Dulberg S, Schupp JC, Lincoln MR, Stillwell HA, Axisa PP, Comi M, Unterman A, Kaminski N, Madi A, Kuchroo VK, Hafler DA. Type I interferon transcriptional network regulates expression of coinhibitory receptors in human T cells. Nat Immunol 2022; 23:632-642. [PMID: 35301508 PMCID: PMC8989655 DOI: 10.1038/s41590-022-01152-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/03/2022] [Indexed: 12/15/2022]
Abstract
Although inhibition of T cell coinhibitory receptors has revolutionized cancer therapy, the mechanisms governing their expression on human T cells have not been elucidated. In the present study, we show that type 1 interferon (IFN-I) regulates coinhibitory receptor expression on human T cells, inducing PD-1/TIM-3/LAG-3 while inhibiting TIGIT expression. High-temporal-resolution mRNA profiling of IFN-I responses established the dynamic regulatory networks uncovering three temporal transcriptional waves. Perturbation of key transcription factors (TFs) and TF footprint analysis revealed two regulator modules with different temporal kinetics that control expression of coinhibitory receptors and IFN-I response genes, with SP140 highlighted as one of the key regulators that differentiates LAG-3 and TIGIT expression. Finally, we found that the dynamic IFN-I response in vitro closely mirrored T cell features in acute SARS-CoV-2 infection. The identification of unique TFs controlling coinhibitory receptor expression under IFN-I response may provide targets for enhancement of immunotherapy in cancer, infectious diseases and autoimmunity.
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Affiliation(s)
- Tomokazu S Sumida
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA.
| | - Shai Dulberg
- Department of Pathology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Jonas C Schupp
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Respiratory Medicine, Hannover Medical School and Biomedical Research in End-stage and Obstructive Lung Disease Hannover, German Lung Research Center, Hannover, Germany
| | - Matthew R Lincoln
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Helen A Stillwell
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Pierre-Paul Axisa
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Michela Comi
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Avraham Unterman
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Pulmonary Institute, Tel Aviv Sourasky Medical Center, Tel Aviv University, Tel Aviv, Israel
| | - Naftali Kaminski
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Asaf Madi
- Department of Pathology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA.
| | - Vijay K Kuchroo
- Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - David A Hafler
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
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26
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Luo L, Gribskov M, Wang S. Bibliometric review of ATAC-Seq and its application in gene expression. Brief Bioinform 2022; 23:6543486. [PMID: 35255493 PMCID: PMC9116206 DOI: 10.1093/bib/bbac061] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/06/2022] [Accepted: 02/09/2022] [Indexed: 11/30/2022] Open
Abstract
With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.
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Affiliation(s)
- Liheng Luo
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
| | - Michael Gribskov
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Sufang Wang
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
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27
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Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res 2021; 31:2258-2275. [PMID: 34815310 PMCID: PMC8647829 DOI: 10.1101/gr.268482.120] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/16/2021] [Indexed: 12/12/2022]
Abstract
Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.
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Affiliation(s)
- Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Christa Ventresca
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Swarooparani Vadlamudi
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Jeremy Kaplan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Claudia Lalancette
- Epigenomics Core, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Katherine Gallagher
- Department of Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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28
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Dong C, Simonett SP, Shin S, Stapleton DS, Schueler KL, Churchill GA, Lu L, Liu X, Jin F, Li Y, Attie AD, Keller MP, Keleş S. INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants. Genome Biol 2021; 22:241. [PMID: 34425882 PMCID: PMC8381555 DOI: 10.1186/s13059-021-02450-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 08/02/2021] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies reveal many non-coding variants associated with complex traits. However, model organism studies largely remain as an untapped resource for unveiling the effector genes of non-coding variants. We develop INFIMA, Integrative Fine-Mapping, to pinpoint causal SNPs for diversity outbred (DO) mice eQTL by integrating founder mice multi-omics data including ATAC-seq, RNA-seq, footprinting, and in silico mutation analysis. We demonstrate INFIMA's superior performance compared to alternatives with human and mouse chromatin conformation capture datasets. We apply INFIMA to identify novel effector genes for GWAS variants associated with diabetes. The results of the application are available at http://www.statlab.wisc.edu/shiny/INFIMA/ .
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Affiliation(s)
- Chenyang Dong
- Department of Statistics, University of Wisconsin-Madison, Madison, WI USA
| | - Shane P. Simonett
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Sunyoung Shin
- Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX USA
| | - Donnie S. Stapleton
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Kathryn L. Schueler
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | | | - Leina Lu
- Case Western University, Cleveland, OH USA
| | | | - Fulai Jin
- Case Western University, Cleveland, OH USA
| | - Yan Li
- Case Western University, Cleveland, OH USA
| | - Alan D. Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Mark P. Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Sündüz Keleş
- Department of Statistics, University of Wisconsin-Madison, Madison, WI USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI USA
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29
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Rui J, Deng S, Perdigoto AL, Ponath G, Kursawe R, Lawlor N, Sumida T, Levine-Ritterman M, Stitzel ML, Pitt D, Lu J, Herold KC. Tet2 Controls the Responses of β cells to Inflammation in Autoimmune Diabetes. Nat Commun 2021; 12:5074. [PMID: 34417463 PMCID: PMC8379260 DOI: 10.1038/s41467-021-25367-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 08/06/2021] [Indexed: 01/02/2023] Open
Abstract
β cells may participate and contribute to their own demise during Type 1 diabetes (T1D). Here we report a role of their expression of Tet2 in regulating immune killing. Tet2 is induced in murine and human β cells with inflammation but its expression is reduced in surviving β cells. Tet2-KO mice that receive WT bone marrow transplants develop insulitis but not diabetes and islet infiltrates do not eliminate β cells even though immune cells from the mice can transfer diabetes to NOD/scid recipients. Tet2-KO recipients are protected from transfer of disease by diabetogenic immune cells.Tet2-KO β cells show reduced expression of IFNγ-induced inflammatory genes that are needed to activate diabetogenic T cells. Here we show that Tet2 regulates pathologic interactions between β cells and immune cells and controls damaging inflammatory pathways. Our data suggests that eliminating TET2 in β cells may reduce activating pathologic immune cells and killing of β cells.
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Affiliation(s)
- Jinxiu Rui
- Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT, USA
| | - Songyan Deng
- Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT, USA
| | - Ana Luisa Perdigoto
- Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT, USA
| | - Gerald Ponath
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Romy Kursawe
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Nathan Lawlor
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomokazu Sumida
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | | | - Michael L Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences and Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA
| | - David Pitt
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Jun Lu
- Department of Genetics, Yale University, New Haven, CT, USA
| | - Kevan C Herold
- Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT, USA.
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30
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Deficient H2A.Z deposition is associated with genesis of uterine leiomyoma. Nature 2021; 596:398-403. [PMID: 34349258 DOI: 10.1038/s41586-021-03747-1] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 06/18/2021] [Indexed: 02/07/2023]
Abstract
One in four women suffers from uterine leiomyomas (ULs)-benign tumours of the uterine wall, also known as uterine fibroids-at some point in premenopausal life. ULs can cause excessive bleeding, pain and infertility1, and are a common cause of hysterectomy2. They emerge through at least three distinct genetic drivers: mutations in MED12 or FH, or genomic rearrangement of HMGA23. Here we created genome-wide datasets, using DNA, RNA, assay for transposase-accessible chromatin (ATAC), chromatin immunoprecipitation (ChIP) and HiC chromatin immunoprecipitation (HiChIP) sequencing of primary tissues to profoundly understand the genesis of UL. We identified somatic mutations in genes encoding six members of the SRCAP histone-loading complex4, and found that germline mutations in the SRCAP members YEATS4 and ZNHIT1 predispose women to UL. Tumours bearing these mutations showed defective deposition of the histone variant H2A.Z. In ULs, H2A.Z occupancy correlated positively with chromatin accessibility and gene expression, and negatively with DNA methylation, but these correlations were weak in tumours bearing SRCAP complex mutations. In these tumours, open chromatin emerged at transcription start sites where H2A.Z was lost, which was associated with upregulation of genes. Furthermore, YEATS4 defects were associated with abnormal upregulation of bivalent embryonic stem cell genes, as previously shown in mice5. Our work describes a potential mechanism of tumorigenesis-epigenetic instability caused by deficient H2A.Z deposition-and suggests that ULs arise through an aberrant differentiation program driven by deranged chromatin, emanating from a small number of mutually exclusive driver mutations.
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Welch N, Singh SS, Kumar A, Dhruba SR, Mishra S, Sekar J, Bellar A, Attaway AH, Chelluboyina A, Willard BB, Li L, Huo Z, Karnik SS, Esser K, Longworth MS, Shah YM, Davuluri G, Pal R, Dasarathy S. Integrated multiomics analysis identifies molecular landscape perturbations during hyperammonemia in skeletal muscle and myotubes. J Biol Chem 2021; 297:101023. [PMID: 34343564 PMCID: PMC8424232 DOI: 10.1016/j.jbc.2021.101023] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 07/16/2021] [Accepted: 07/28/2021] [Indexed: 12/27/2022] Open
Abstract
Ammonia is a cytotoxic molecule generated during normal cellular functions. Dysregulated ammonia metabolism, which is evident in many chronic diseases such as liver cirrhosis, heart failure, and chronic obstructive pulmonary disease, initiates a hyperammonemic stress response in tissues including skeletal muscle and in myotubes. Perturbations in levels of specific regulatory molecules have been reported, but the global responses to hyperammonemia are unclear. In this study, we used a multiomics approach to vertically integrate unbiased data generated using an assay for transposase-accessible chromatin with high-throughput sequencing, RNA-Seq, and proteomics. We then horizontally integrated these data across different models of hyperammonemia, including myotubes and mouse and human muscle tissues. Changes in chromatin accessibility and/or expression of genes resulted in distinct clusters of temporal molecular changes including transient, persistent, and delayed responses during hyperammonemia in myotubes. Known responses to hyperammonemia, including mitochondrial and oxidative dysfunction, protein homeostasis disruption, and oxidative stress pathway activation, were enriched in our datasets. During hyperammonemia, pathways that impact skeletal muscle structure and function that were consistently enriched were those that contribute to mitochondrial dysfunction, oxidative stress, and senescence. We made several novel observations, including an enrichment in antiapoptotic B-cell leukemia/lymphoma 2 family protein expression, increased calcium flux, and increased protein glycosylation in myotubes and muscle tissue upon hyperammonemia. Critical molecules in these pathways were validated experimentally. Human skeletal muscle from patients with cirrhosis displayed similar responses, establishing translational relevance. These data demonstrate complex molecular interactions during adaptive and maladaptive responses during the cellular stress response to hyperammonemia.
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Affiliation(s)
- Nicole Welch
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA; Department of Gastroenterology and Hepatology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Shashi Shekhar Singh
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Avinash Kumar
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Saugato Rahman Dhruba
- Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA
| | - Saurabh Mishra
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jinendiran Sekar
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Annette Bellar
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Amy H Attaway
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA; Department of Pulmonary Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Aruna Chelluboyina
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Belinda B Willard
- Proteomics Research Core Services, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ling Li
- Proteomics Research Core Services, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Zhiguang Huo
- Department of Biostatistics, College of Public Health and Health Profession, University of Florida, Gainesville, Florida, USA
| | - Sadashiva S Karnik
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Karyn Esser
- Department of Physiology and Functional Genomics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Michelle S Longworth
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Yatrik M Shah
- Department of Molecular & Integrative Physiology and Department of Gastroenterology, University of Michigan, Ann Arbor, Michigan, USA
| | - Gangarao Davuluri
- Integrated Physiology and Molecular Metabolism, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Ranadip Pal
- Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
| | - Srinivasan Dasarathy
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA; Department of Gastroenterology and Hepatology, Cleveland Clinic, Cleveland, Ohio, USA.
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32
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Mehrmohamadi M, Sepehri MH, Nazer N, Norouzi MR. A Comparative Overview of Epigenomic Profiling Methods. Front Cell Dev Biol 2021; 9:714687. [PMID: 34368164 PMCID: PMC8340004 DOI: 10.3389/fcell.2021.714687] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
In the past decade, assays that profile different aspects of the epigenome have grown exponentially in number and variation. However, standard guidelines for researchers to choose between available tools depending on their needs are lacking. Here, we introduce a comprehensive collection of the most commonly used bulk and single-cell epigenomic assays and compare and contrast their strengths and weaknesses. We summarize some of the most important technical and experimental parameters that should be considered for making an appropriate decision when designing epigenomic experiments.
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Affiliation(s)
- Mahya Mehrmohamadi
- Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran
| | | | - Naghme Nazer
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
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33
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Liang D, Elwell AL, Aygün N, Krupa O, Wolter JM, Kyere FA, Lafferty MJ, Cheek KE, Courtney KP, Yusupova M, Garrett ME, Ashley-Koch A, Crawford GE, Love MI, de la Torre-Ubieta L, Geschwind DH, Stein JL. Cell-type-specific effects of genetic variation on chromatin accessibility during human neuronal differentiation. Nat Neurosci 2021; 24:941-953. [PMID: 34017130 PMCID: PMC8254789 DOI: 10.1038/s41593-021-00858-w] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/15/2021] [Indexed: 02/03/2023]
Abstract
Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood as to how these variants influence gene regulation. To model the functional impact of common genetic variation on the noncoding genome during human cortical development, we performed the assay for transposase accessible chromatin using sequencing (ATAC-seq) and analyzed chromatin accessibility quantitative trait loci (QTL) in cultured human neural progenitor cells and their differentiated neuronal progeny from 87 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (roughly 30%) of chromatin accessibility-QTL were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type-specific chromatin accessibility-QTL and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying noncoding neuropsychiatric disorder risk loci.
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Affiliation(s)
- Dan Liang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Angela L Elwell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Oleh Krupa
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Justin M Wolter
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Felix A Kyere
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael J Lafferty
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kerry E Cheek
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kenan P Courtney
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marianna Yusupova
- Neurogenetics Program, Department of Neurology, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Melanie E Garrett
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Allison Ashley-Koch
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Gregory E Crawford
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Luis de la Torre-Ubieta
- Neurogenetics Program, Department of Neurology, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H Geschwind
- Neurogenetics Program, Department of Neurology, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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34
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Currin KW, Erdos MR, Narisu N, Rai V, Vadlamudi S, Perrin HJ, Idol JR, Yan T, Albanus RD, Broadaway KA, Etheridge AS, Bonnycastle LL, Orchard P, Didion JP, Chaudhry AS, Innocenti F, Schuetz EG, Scott LJ, Parker SCJ, Collins FS, Mohlke KL. Genetic effects on liver chromatin accessibility identify disease regulatory variants. Am J Hum Genet 2021; 108:1169-1189. [PMID: 34038741 PMCID: PMC8323023 DOI: 10.1016/j.ajhg.2021.05.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 05/04/2021] [Indexed: 02/02/2023] Open
Abstract
Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
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Affiliation(s)
- Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Vivek Rai
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Hannah J Perrin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jacqueline R Idol
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tingfen Yan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lori L Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amarjit S Chaudhry
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Erin G Schuetz
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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35
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Asma H, Halfon MS. Annotating the Insect Regulatory Genome. INSECTS 2021; 12:591. [PMID: 34209769 PMCID: PMC8305585 DOI: 10.3390/insects12070591] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/23/2021] [Accepted: 06/25/2021] [Indexed: 11/17/2022]
Abstract
An ever-growing number of insect genomes is being sequenced across the evolutionary spectrum. Comprehensive annotation of not only genes but also regulatory regions is critical for reaping the full benefits of this sequencing. Driven by developments in sequencing technologies and in both empirical and computational discovery strategies, the past few decades have witnessed dramatic progress in our ability to identify cis-regulatory modules (CRMs), sequences such as enhancers that play a major role in regulating transcription. Nevertheless, providing a timely and comprehensive regulatory annotation of newly sequenced insect genomes is an ongoing challenge. We review here the methods being used to identify CRMs in both model and non-model insect species, and focus on two tools that we have developed, REDfly and SCRMshaw. These resources can be paired together in a powerful combination to facilitate insect regulatory annotation over a broad range of species, with an accuracy equal to or better than that of other state-of-the-art methods.
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Affiliation(s)
- Hasiba Asma
- Program in Genetics, Genomics, and Bioinformatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA;
| | - Marc S. Halfon
- Program in Genetics, Genomics, and Bioinformatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA;
- Department of Biochemistry, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biomedical Informatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biological Sciences, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- NY State Center of Excellence in Bioinformatics & Life Sciences, Buffalo, NY 14203, USA
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36
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Wang S, Lee MP, Jones S, Liu J, Waldhaus J. Mapping the regulatory landscape of auditory hair cells from single-cell multi-omics data. Genome Res 2021; 31:1885-1899. [PMID: 33837132 DOI: 10.1101/gr.271080.120] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 03/23/2021] [Indexed: 11/25/2022]
Abstract
Auditory hair cells transduce sound to the brain and in mammals these cells reside together with supporting cells in the sensory epithelium of the cochlea, called the organ of Corti. To establish the organ's delicate function during development and differentiation, spatiotemporal gene expression is strictly controlled by chromatin accessibility and cell type-specific transcription factors, jointly representing the regulatory landscape. Bulk-sequencing technology and cellular heterogeneity obscured investigations on the interplay between transcription factors and chromatin accessibility in inner ear development. To study the formation of the regulatory landscape in hair cells, we collected single-cell chromatin accessibility profiles accompanied by single-cell RNA data from genetically labeled murine hair cells and supporting cells after birth. Using an integrative approach, we predicted cell type-specific activating and repressing functions of developmental transcription factors. Furthermore, by integrating gene expression and chromatin accessibility datasets, we reconstructed gene regulatory networks. Then, using a comparative approach, 20 hair cell-specific activators and repressors, including putative downstream target genes, were identified. Clustering of target genes resolved groups of related transcription factors and was utilized to infer their developmental functions. Finally, the heterogeneity in the single-cell data allowed us to spatially reconstruct transcriptional as well as chromatin accessibility trajectories, indicating that gradual changes in the chromatin accessibility landscape were lagging behind the transcriptional identity of hair cells along the organ's longitudinal axis. Overall, this study provides a strategy to spatially reconstruct the formation of a lineage specific regulatory landscape using a single-cell multi-omics approach.
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Affiliation(s)
- Shuze Wang
- University of Michigan, Kresge Hearing Research Institute
| | - Mary P Lee
- University of Michigan, Kresge Hearing Research Institute
| | - Scott Jones
- University of Michigan, Kresge Hearing Research Institute
| | | | - Joerg Waldhaus
- University of Michigan, Kresge Hearing Research Institute;
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37
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Kissane S, Dhandapani V, Orsini L. Protocol for assay of transposase accessible chromatin sequencing in non-model species. STAR Protoc 2021; 2:100341. [PMID: 33659905 PMCID: PMC7896190 DOI: 10.1016/j.xpro.2021.100341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The assay for transposase accessible chromatin (ATAC-seq) is a method for mapping genome-wide chromatin accessibility. Coupled with high-throughput sequencing, it enables integrative epigenomics analyses. ATAC-seq requires direct access to cell nuclei, a major challenge in non-model species such as small invertebrates, whose soft tissue is surrounded by a protective exoskeleton. Here, we present modifications of the ATAC-seq protocol for applications in small crustaceans, extending applications to non-model species. For complete information on the use and execution of this protocol, please refer to Buenrostro et al. (2013). ATAC-seq modified protocol for applications in non-model species Transposase titration identifies thresholds for optimal transposition at lower costs Minimal number of cells/tissue is identified for low input reactions Proof of concept ATAC-seq analysis for the waterflea Daphnia magna
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Affiliation(s)
- Stephen Kissane
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK
| | | | - Luisa Orsini
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK
- Corresponding author
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38
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Singh NP, De Kumar B, Paulson A, Parrish ME, Zhang Y, Florens L, Conaway JW, Si K, Krumlauf R. A six-amino-acid motif is a major determinant in functional evolution of HOX1 proteins. Genes Dev 2020; 34:1680-1696. [PMID: 33184220 PMCID: PMC7706710 DOI: 10.1101/gad.342329.120] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 10/09/2020] [Indexed: 01/19/2023]
Abstract
Gene duplication and divergence is a major driver in the emergence of evolutionary novelties. How variations in amino acid sequences lead to loss of ancestral activity and functional diversification of proteins is poorly understood. We used cross-species functional analysis of Drosophila Labial and its mouse HOX1 orthologs (HOXA1, HOXB1, and HOXD1) as a paradigm to address this issue. Mouse HOX1 proteins display low (30%) sequence similarity with Drosophila Labial. However, substituting endogenous Labial with the mouse proteins revealed that HOXA1 has retained essential ancestral functions of Labial, while HOXB1 and HOXD1 have diverged. Genome-wide analysis demonstrated similar DNA-binding patterns of HOXA1 and Labial in mouse cells, while HOXB1 binds to distinct targets. Compared with HOXB1, HOXA1 shows an enrichment in co-occupancy with PBX proteins on target sites and exists in the same complex with PBX on chromatin. Functional analysis of HOXA1-HOXB1 chimeric proteins uncovered a novel six-amino-acid C-terminal motif (CTM) flanking the homeodomain that serves as a major determinant of ancestral activity. In vitro DNA-binding experiments and structural prediction show that CTM provides an important domain for interaction of HOXA1 proteins with PBX. Our findings show that small changes outside of highly conserved DNA-binding regions can lead to profound changes in protein function.
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Affiliation(s)
| | - Bony De Kumar
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA
| | - Ariel Paulson
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA
| | - Mark E Parrish
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA
| | - Ying Zhang
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA
| | - Laurence Florens
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA
| | - Joan W Conaway
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA.,Department of Biochemistry and Molecular Biology, Kansas University Medical Center, Kansas City, Kansas 66160, USA
| | - Kausik Si
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA.,Department of Molecular and Integrative Physiology, Kansas University Medical Center, Kansas City, Kansas 66160, USA
| | - Robb Krumlauf
- Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA.,Department of Anatomy and Cell Biology, Kansas University Medical Center, Kansas City, Kansas 66160, USA
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39
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Hauberg ME, Creus-Muncunill J, Bendl J, Kozlenkov A, Zeng B, Corwin C, Chowdhury S, Kranz H, Hurd YL, Wegner M, Børglum AD, Dracheva S, Ehrlich ME, Fullard JF, Roussos P. Common schizophrenia risk variants are enriched in open chromatin regions of human glutamatergic neurons. Nat Commun 2020; 11:5581. [PMID: 33149216 PMCID: PMC7643171 DOI: 10.1038/s41467-020-19319-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 10/08/2020] [Indexed: 01/04/2023] Open
Abstract
The chromatin landscape of human brain cells encompasses key information to understanding brain function. Here we use ATAC-seq to profile the chromatin structure in four distinct populations of cells (glutamatergic neurons, GABAergic neurons, oligodendrocytes, and microglia/astrocytes) from three different brain regions (anterior cingulate cortex, dorsolateral prefrontal cortex, and primary visual cortex) in human postmortem brain samples. We find that chromatin accessibility varies greatly by cell type and, more moderately, by brain region, with glutamatergic neurons showing the largest regional variability. Transcription factor footprinting implicates cell-specific transcriptional regulators and infers cell-specific regulation of protein-coding genes, long intergenic noncoding RNAs and microRNAs. In vivo transgenic mouse experiments validate the cell type specificity of several of these human-derived regulatory sequences. We find that open chromatin regions in glutamatergic neurons are enriched for neuropsychiatric risk variants, particularly those associated with schizophrenia. Integration of cell-specific chromatin data with a bulk tissue study of schizophrenia brains increases statistical power and confirms that glutamatergic neurons are most affected. These findings illustrate the utility of studying the cell-type-specific epigenome in complex tissues like the human brain, and the potential of such approaches to better understand the genetic basis of human brain function.
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Affiliation(s)
- Mads E Hauberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Jordi Creus-Muncunill
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jaroslav Bendl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Alexey Kozlenkov
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Biao Zeng
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Chuhyon Corwin
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sarah Chowdhury
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Harald Kranz
- Gene Bridges, Im Neuenheimer Feld 584, 69120, Heidelberg, Germany
| | - Yasmin L Hurd
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Wegner
- Institut für Biochemie, Emil-Fischer-Zentrum, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Stella Dracheva
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Michelle E Ehrlich
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA.
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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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