1
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Chatsirisupachai K, Moene CJI, Kleinendorst R, Kreibich E, Molina N, Krebs A. Mouse promoters are characterised by low occupancy and high turnover of RNA polymerase II. Mol Syst Biol 2025; 21:447-471. [PMID: 40164797 PMCID: PMC12048509 DOI: 10.1038/s44320-025-00094-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 02/28/2025] [Accepted: 03/13/2025] [Indexed: 04/02/2025] Open
Abstract
The general transcription machinery and its occupancy at promoters are highly conserved across metazoans. This contrasts with the kinetics of mRNA production that considerably differ between model species such as Drosophila and mouse. The molecular basis for these kinetic differences is currently unknown. Here, we used Single-Molecule Footprinting to measure RNA Polymerase II (Pol II) occupancy, the fraction of DNA molecules bound, at promoters in mouse and Drosophila cell lines. Single-molecule data reveals that Pol II occupancy is on average 3-5 times more frequent at transcriptionally active Drosophila promoters than active mouse promoters. Kinetic modelling of the occupancy states suggests that these differences in Pol II occupancy are determined by the ratio between the transcription initiation and Pol II turnover rates. We used chemical perturbation of transcription initiation to determine Pol II turnover rate in both species. Integration of these data into the model shows that infrequent Pol II occupancy in mouse is explained by the combination of high Pol II turnover and low transcription initiation rates.
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Affiliation(s)
| | - Christina J I Moene
- Genome Biology Unit, EMBL Meyerhofstaße 1, 69117, Heidelberg, Germany
- Division of Gene Regulation, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | | | - Elisa Kreibich
- Genome Biology Unit, EMBL Meyerhofstaße 1, 69117, Heidelberg, Germany
- ETH Zürich, Department for Biosystems Science and Engineering (D-BSSE), Basel, Switzerland
| | - Nacho Molina
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg; Centre National de la Recherche Scientifique (CNRS) UMR 7104; Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 1258, 1 Rue Laurent Fries, 67404, Illkirch, France.
| | - Arnaud Krebs
- Genome Biology Unit, EMBL Meyerhofstaße 1, 69117, Heidelberg, Germany.
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2
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Betti MJ, Lin P, Aldrich MC, Gamazon ER. Genetically regulated eRNA expression predicts chromatin contact frequency and reveals genetic mechanisms at GWAS loci. Nat Commun 2025; 16:3193. [PMID: 40180945 PMCID: PMC11968980 DOI: 10.1038/s41467-025-58023-x] [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: 06/07/2024] [Accepted: 02/18/2025] [Indexed: 04/05/2025] Open
Abstract
The biological functions of extragenic enhancer RNAs and their impact on disease risk remain relatively underexplored. In this work, we develop in silico models of genetically regulated expression of enhancer RNAs across 49 cell and tissue types, characterizing their degree of genetic control. Leveraging the estimated genetically regulated expression for enhancer RNAs and canonical genes in a large-scale DNA biobank (N > 70,000) and high-resolution Hi-C contact data, we train a deep learning-based model of pairwise three-dimensional chromatin contact frequency for enhancer-enhancer and enhancer-gene pairs in cerebellum and whole blood. Notably, the use of genetically regulated expression of enhancer RNAs provides substantial tissue-specific predictive power, supporting a role for these transcripts in modulating spatial chromatin organization. We identify schizophrenia-associated enhancer RNAs independent of GWAS loci using enhancer RNA-based TWAS and determine the causal effects of these enhancer RNAs using Mendelian randomization. Using enhancer RNA-based TWAS, we generate a comprehensive resource of tissue-specific enhancer associations with complex traits in the UK Biobank. Finally, we show that a substantially greater proportion (63%) of GWAS associations colocalize with causal regulatory variation when enhancer RNAs are included.
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Affiliation(s)
- Michael J Betti
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 700, Nashville, TN, 37203, USA.
| | - Phillip Lin
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 700, Nashville, TN, 37203, USA
| | - Melinda C Aldrich
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 700, Nashville, TN, 37203, USA
| | - Eric R Gamazon
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 700, Nashville, TN, 37203, USA.
- Clare Hall, University of Cambridge, Herschel Rd, Cambridge, CB3 9AL, UK.
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3
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Fan C, Wang Q, Krijger PHL, Cats D, Selle M, Khorosjutina O, Dhanjal S, Schmierer B, Mei H, de Laat W, Ten Dijke P. Identification of a SNAI1 enhancer RNA that drives cancer cell plasticity. Nat Commun 2025; 16:2890. [PMID: 40133308 PMCID: PMC11937597 DOI: 10.1038/s41467-025-58032-w] [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: 09/27/2024] [Accepted: 03/11/2025] [Indexed: 03/27/2025] Open
Abstract
Enhancer RNAs (eRNAs) are a pivotal class of enhancer-derived non-coding RNAs that drive gene expression. Here we identify the SNAI1 enhancer RNA (SNAI1e; SCREEM2) as a key activator of SNAI1 expression and a potent enforcer of transforming growth factor-β (TGF-β)/SMAD signaling in cancer cells. SNAI1e depletion impairs TGF-β-induced epithelial-mesenchymal transition (EMT), migration, in vivo extravasation, stemness, and chemotherapy resistance in breast cancer cells. SNAI1e functions as an eRNA to cis-regulate SNAI1 enhancer activity by binding to and strengthening the enrichment of the transcriptional co-activator bromodomain containing protein 4 (BRD4) at the local enhancer. SNAI1e selectively promotes the expression of SNAI1, which encodes the EMT transcription factor SNAI1. Furthermore, we reveal that SNAI1 interacts with and anchors the inhibitory SMAD7 in the nucleus, and thereby prevents TGF-β type I receptor (TβRI) polyubiquitination and proteasomal degradation. Our findings establish SNAI1e as a critical driver of SNAI1 expression and TGF-β-induced cell plasticity.
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Affiliation(s)
- Chuannan Fan
- Oncode Institute and Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Qian Wang
- Oncode Institute and Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Peter H L Krijger
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Davy Cats
- Department of Biomedical Data Sciences, Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands
| | - Miriam Selle
- Department of Medical Biochemistry and Biophysics, SciLifeLab and Karolinska Institute, Solna, Sweden
| | - Olga Khorosjutina
- Department of Medical Biochemistry and Biophysics, SciLifeLab and Karolinska Institute, Solna, Sweden
| | - Soniya Dhanjal
- Department of Medical Biochemistry and Biophysics, SciLifeLab and Karolinska Institute, Solna, Sweden
| | - Bernhard Schmierer
- Department of Medical Biochemistry and Biophysics, SciLifeLab and Karolinska Institute, Solna, Sweden
| | - Hailiang Mei
- Department of Biomedical Data Sciences, Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands
| | - Wouter de Laat
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Peter Ten Dijke
- Oncode Institute and Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands.
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4
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Mick S, Carroll C, Uriostegui-Arcos M, Fiszbein A. Hybrid exons evolved by coupling transcription initiation and splicing at the nucleotide level. Nucleic Acids Res 2025; 53:gkae1251. [PMID: 39739742 PMCID: PMC11797052 DOI: 10.1093/nar/gkae1251] [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: 10/12/2023] [Revised: 11/27/2024] [Accepted: 12/05/2024] [Indexed: 01/02/2025] Open
Abstract
Exons within transcripts are traditionally classified as first, internal or last exons, each governed by different regulatory mechanisms. We recently described the widespread usage of 'hybrid' exons that serve as terminal or internal exons in different transcripts. Here, we employ an interpretable deep learning pipeline to dissect the sequence features governing the co-regulation of transcription initiation and splicing in hybrid exons. Using ENCODE data from human tissues, we identified 80 000 hybrid first-internal exons. These exons often possess a relaxed chromatin state, allowing transcription initiation within the gene body. Interestingly, transcription start sites of hybrid exons are typically centered at the 3' splice site, suggesting tight coupling between splicing and transcription initiation. We identified two subcategories of hybrid exons: the majority resemble internal exons, maintaining strong 3' splice sites, while a minority show enrichment in promoter elements, resembling first exons. Diving into the evolution of their sequences, we found that human hybrid exons with orthologous first exons in other species usually gained 3' splice sites or whole exons upstream, while those with orthologous internal exons often gained promoter elements. Overall, our findings unveil the intricate regulatory landscape of hybrid exons and reveal stronger connections between transcription initiation and RNA splicing than previously acknowledged.
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Affiliation(s)
- Steven T Mick
- Biology Department, Boston University, 24 Cummington Ave., Boston, 02215, USA
| | - Christine L Carroll
- Biology Department, Boston University, 24 Cummington Ave., Boston, 02215, USA
| | | | - Ana Fiszbein
- Biology Department, Boston University, 24 Cummington Ave., Boston, 02215, USA
- Computing & Data Sciences, Boston University, 665 Commonwealth Ave., Boston, 02215, USA
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5
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Yin JA, Frick L, Scheidmann MC, Liu T, Trevisan C, Dhingra A, Spinelli A, Wu Y, Yao L, Vena DL, Knapp B, Guo J, De Cecco E, Ging K, Armani A, Oakeley EJ, Nigsch F, Jenzer J, Haegele J, Pikusa M, Täger J, Rodriguez-Nieto S, Bouris V, Ribeiro R, Baroni F, Bedi MS, Berry S, Losa M, Hornemann S, Kampmann M, Pelkmans L, Hoepfner D, Heutink P, Aguzzi A. Arrayed CRISPR libraries for the genome-wide activation, deletion and silencing of human protein-coding genes. Nat Biomed Eng 2025; 9:127-148. [PMID: 39633028 PMCID: PMC11754104 DOI: 10.1038/s41551-024-01278-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 10/04/2024] [Indexed: 12/07/2024]
Abstract
Arrayed CRISPR libraries extend the scope of gene-perturbation screens to non-selectable cell phenotypes. However, library generation requires assembling thousands of vectors expressing single-guide RNAs (sgRNAs). Here, by leveraging massively parallel plasmid-cloning methodology, we show that arrayed libraries can be constructed for the genome-wide ablation (19,936 plasmids) of human protein-coding genes and for their activation and epigenetic silencing (22,442 plasmids), with each plasmid encoding an array of four non-overlapping sgRNAs designed to tolerate most human DNA polymorphisms. The quadruple-sgRNA libraries yielded high perturbation efficacies in deletion (75-99%) and silencing (76-92%) experiments and substantial fold changes in activation experiments. Moreover, an arrayed activation screen of 1,634 human transcription factors uncovered 11 novel regulators of the cellular prion protein PrPC, screening with a pooled version of the ablation library led to the identification of 5 novel modifiers of autophagy that otherwise went undetected, and 'post-pooling' individually produced lentiviruses eliminated template-switching artefacts and enhanced the performance of pooled screens for epigenetic silencing. Quadruple-sgRNA arrayed libraries are a powerful and versatile resource for targeted genome-wide perturbations.
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Grants
- A.A. is supported by institutional core funding by the University of Zurich and the University Hospital of Zurich, and is the recipient of grants from the Nomis Foundation, the Swiss National Research Foundation (grant ID 179040 and grant ID 207872, Sinergia grant ID 183563), the Swiss Personal-ized Health Network (SPHN, 2017DRI17), an Advanced Grant of the European Research Council (ERC Prion2020 No. 670958), the HMZ ImmunoTarget grant, the Human Frontiers Science Pro-gram (grant ID RGP0001/2022), the Michael J. Fox Foundation (grant ID MJFF-022156), Swissuni-versities (CRISPR4ALL), and a donation from the estate of Dr. Hans Salvisberg.
- J-A.Y. is the recip-ient of the postdoc grant Forschungskredit from University of Zurich and the Career Development Awards grant of the Synapsis Foundation – Alzheimer Research Switzerland ARS (Grant ID 2021-CDA02).
- China Scholarship Council
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Affiliation(s)
- Jiang-An Yin
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland.
| | - Lukas Frick
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Manuel C Scheidmann
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Tingting Liu
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Chiara Trevisan
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Ashutosh Dhingra
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Anna Spinelli
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Yancheng Wu
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Longping Yao
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Dalila Laura Vena
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Britta Knapp
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Jingjing Guo
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Elena De Cecco
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Kathi Ging
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Andrea Armani
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
- Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Edward J Oakeley
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Florian Nigsch
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Joel Jenzer
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Jasmin Haegele
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Michal Pikusa
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Joachim Täger
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | | | - Vangelis Bouris
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Rafaela Ribeiro
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Federico Baroni
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Manmeet Sakshi Bedi
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Scott Berry
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- EMBL Australia Node in Single Molecule Science, School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Marco Losa
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Simone Hornemann
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Martin Kampmann
- Institute for Neurodegenerative Diseases, Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Lucas Pelkmans
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Dominic Hoepfner
- Novartis Institutes for Biomedical Research, Novartis Campus, Basel, Switzerland
| | - Peter Heutink
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Adriano Aguzzi
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland.
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6
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An H, Hong Y, Goh YT, Koh CWQ, Kanwal S, Zhang Y, Lu Z, Yap PML, Neo SP, Wong CM, Wong AST, Yu Y, Ho JSY, Gunaratne J, Goh WSS. m 6Am sequesters PCF11 to suppress premature termination and drive neuroblastoma differentiation. Mol Cell 2024; 84:4142-4157.e14. [PMID: 39481383 DOI: 10.1016/j.molcel.2024.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 08/08/2024] [Accepted: 10/01/2024] [Indexed: 11/02/2024]
Abstract
N6,2'-O-dimethyladenosine (m6Am) is an abundant mRNA modification that impacts multiple diseases, but its function remains controversial because the m6Am reader is unknown. Using quantitative proteomics, we identified transcriptional terminator premature cleavage factor II (PCF11) as a m6Am-specific reader in human cells. Direct quantification of mature versus nascent RNAs reveals that m6Am does not regulate mRNA stability but promotes nascent transcription. Mechanistically, m6Am functions by sequestering PCF11 away from proximal RNA polymerase II (RNA Pol II). This suppresses PCF11 from dissociating RNA Pol II near transcription start sites, thereby promoting full-length transcription of m6Am-modified RNAs. m6Am's unique relationship with PCF11 means m6Am function is enhanced when PCF11 is reduced, which occurs during all-trans-retinoic-acid (ATRA)-induced neuroblastoma-differentiation therapy. Here, m6Am promotes expression of ATF3, which represses neuroblastoma biomarker MYCN. Depleting m6Am suppresses MYCN repression in ATRA-treated neuroblastoma and maintains their tumor-stem-like properties. Collectively, we characterize m6Am as an anti-terminator RNA modification that suppresses premature termination and modulates neuroblastoma's therapeutic response.
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Affiliation(s)
- Huihui An
- Shenzhen Bay Laboratory, Shenzhen, China; School of Biological Sciences, University of Hong Kong, Hong Kong, China; Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Yifan Hong
- Shenzhen Bay Laboratory, Shenzhen, China
| | | | | | | | - Yi Zhang
- Shenzhen Bay Laboratory, Shenzhen, China
| | - Zhaoqi Lu
- Shenzhen Bay Laboratory, Shenzhen, China
| | | | - Suat Peng Neo
- Institute of Molecular and Cell Biology, Singapore, Singapore
| | - Chun-Ming Wong
- Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Alice S T Wong
- School of Biological Sciences, University of Hong Kong, Hong Kong, China
| | - Yang Yu
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jessica Sook Yuin Ho
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore, Singapore
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7
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Abdul R, Fazio T, Savige J, Mack HG. Syndromic PRD: case report of McArdle retinopathy and review of literature. CANADIAN JOURNAL OF OPHTHALMOLOGY 2024; 59:e415-e419. [PMID: 38431269 DOI: 10.1016/j.jcjo.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 02/14/2024] [Indexed: 03/05/2024]
Affiliation(s)
- Rahman Abdul
- University of Melbourne, Parkville, Victoria, Australia
| | - Timothy Fazio
- University of Melbourne, Parkville, Victoria, Australia; Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Judy Savige
- University of Melbourne, Parkville, Victoria, Australia
| | - Heather G Mack
- University of Melbourne, Parkville, Victoria, Australia.
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8
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Antikainen AA, Haukka JK, Kumar A, Syreeni A, Hägg-Holmberg S, Ylinen A, Kilpeläinen E, Kytölä A, Palotie A, Putaala J, Thorn LM, Harjutsalo V, Groop PH, Sandholm N. Whole-genome sequencing identifies variants in ANK1, LRRN1, HAS1, and other genes and regulatory regions for stroke in type 1 diabetes. Sci Rep 2024; 14:13453. [PMID: 38862513 PMCID: PMC11166668 DOI: 10.1038/s41598-024-61840-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/10/2024] [Indexed: 06/13/2024] Open
Abstract
Individuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-exome or whole-genome sequencing of 1,051 individuals with T1D, we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. We analysed the genome comprehensively with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. In addition, we attempted replication in T1D using a genome-wide association study (N = 3,945) and direct genotyping (N = 3,263), and in the general population from the large-scale population-wide FinnGen project and UK Biobank summary statistics. We identified a rare missense variant on SREBF1 exome-wide significantly associated with stroke (rs114001633, p.Pro227Leu, p-value = 7.30 × 10-8), which replicated for hemorrhagic stroke in T1D. Using gene aggregate analysis, we identified exome-wide significant genes: ANK1 and LRRN1 displayed replication evidence in T1D, and LRRN1, HAS1 and UACA in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window on LINC01500, which replicated in T1D. Finally, we identified a suggestively stroke-associated TRPM2-AS promoter (p-value = 5.78 × 10-6) with borderline significant replication in T1D, which we validated with an in vitro cell-based assay. Due to the rarity of the identified genetic variants, future replication of the genomic regions represented here is required with sequencing of individuals with T1D. Nevertheless, we here report the first genome-wide analysis on stroke in individuals with diabetes.
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Affiliation(s)
- Anni A Antikainen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jani K Haukka
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anmol Kumar
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Stefanie Hägg-Holmberg
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anni Ylinen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Elina Kilpeläinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Anastasia Kytölä
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jukka Putaala
- Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Lena M Thorn
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia.
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
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9
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Inomata Y, Kawatani N, Yamashita H, Hattori F. Lgr6-expressing functional nail stem-like cells differentiated from human-induced pluripotent stem cells. PLoS One 2024; 19:e0303260. [PMID: 38743670 PMCID: PMC11093308 DOI: 10.1371/journal.pone.0303260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
The nail matrix containing stem cell populations produces nails and may contribute to fingertip regeneration. Nails are important tissues that maintain the functions of the hand and foot for handling objects and locomotion. Tumor chemotherapy impairs nail growth and, in many cases, loses them, although not permanently. In this report, we have achieved the successful differentiation of nail stem (NS)-like cells from human-induced pluripotent stem cells (iPSCs) via digit organoids by stepwise stimulation, tracing the molecular processes involved in limb development. Comprehensive mRNA sequencing analysis revealed that the digit organoid global gene expression profile fits human finger development. The NS-like cells expressed Lgr6 mRNA and protein and produced type-I keratin, KRT17, and type-II keratin, KRT81, which are abundant in nails. Furthermore, we succeeded in producing functional Lgr6-reporter human iPSCs. The reporter iPSC-derived Lgr6-positive cells also produced KRT17 and KRT81 proteins in the percutaneously transplanted region. To the best of our knowledge, this is the first report of NS-like cell differentiation from human iPSCs. Our differentiation method and reporter construct enable the discovery of drugs for nail repair and possibly fingertip-regenerative therapy.
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Affiliation(s)
- Yukino Inomata
- Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Hirakata city, Osaka, Japan
- Osaka College of High-Technology, Osaka City, Osaka, Japan
| | - Nano Kawatani
- Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Hirakata city, Osaka, Japan
- Osaka College of High-Technology, Osaka City, Osaka, Japan
| | - Hiromi Yamashita
- Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Hirakata city, Osaka, Japan
| | - Fumiyuki Hattori
- Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Hirakata city, Osaka, Japan
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10
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Abugessaisa I, Manabe RI, Kawashima T, Tagami M, Takahashi C, Okazaki Y, Bandinelli S, Kasukawa T, Ferrucci L. OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults. GeroScience 2024; 46:2063-2081. [PMID: 37817005 PMCID: PMC10828349 DOI: 10.1007/s11357-023-00961-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/24/2023] [Indexed: 10/12/2023] Open
Abstract
While some old adults stay healthy and non-frail up to late in life, others experience multimorbidity and frailty often accompanied by a pro-inflammatory state. The underlying molecular mechanisms for those differences are still obscure. Here, we used gene expression analysis to understand the molecular underpinning between non-frail and frail individuals in old age. Twenty-four adults (50% non-frail and 50% frail) from InCHIANTI study were included. Total RNA extracted from whole blood was analyzed by Cap Analysis of Gene Expression (CAGE). CAGE identified transcription start site (TSS) and active enhancer regions. We identified a set of differentially expressed (DE) TSS and enhancer between non-frail and frail and male and female participants. Several DE TSSs were annotated as lncRNA (XIST and TTTY14) and antisense RNAs (ZFX-AS1 and OVCH1 Antisense RNA 1). The promoter region chr6:366,786,54-366,787,97;+ was DE and overlapping the longevity CDKN1A gene. GWAS-LD enrichment analysis identifies overlapping LD-blocks with the DE regions with reported traits in GWAS catalog (isovolumetric relaxation time and urinary tract infection frequency). Furthermore, we used weighted gene co-expression network analysis (WGCNA) to identify changes of gene expression associated with clinical traits and identify key gene modules. We performed functional enrichment analysis of the gene modules with significant trait/module correlation. One gene module is showing a very distinct pattern in hub genes. Glycogen Phosphorylase L (PYGL) was the top ranked hub gene between non-frail and frail. We predicted transcription factor binding sites (TFBS) and motif activity. TF involved in age-related pathways (e.g., FOXO3 and MYC) shows different expression patterns between non-frail and frail participants. Expanding the study of OVCH1 Antisense RNA 1 and PYGL may help understand the mechanisms leading to loss of homeostasis that ultimately causes frailty.
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Affiliation(s)
- Imad Abugessaisa
- Laboratory for Large-Scale Biomedical Data Technology, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan.
| | - Ri-Ichiroh Manabe
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Tsugumi Kawashima
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Michihira Tagami
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Chitose Takahashi
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Yasushi Okazaki
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Stefania Bandinelli
- Azienda USL Toscana Centro, InCHIANTI, Villa Margherita, Primo piano Viale Michelangelo, 41, 50125, Firenze, Italy
| | - Takeya Kasukawa
- Laboratory for Large-Scale Biomedical Data Technology, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Institute for Protein Research, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD, 21225, USA
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11
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Zoch A, Konieczny G, Auchynnikava T, Stallmeyer B, Rotte N, Heep M, Berrens RV, Schito M, Kabayama Y, Schöpp T, Kliesch S, Houston B, Nagirnaja L, O'Bryan MK, Aston KI, Conrad DF, Rappsilber J, Allshire RC, Cook AG, Tüttelmann F, O'Carroll D. C19ORF84 connects piRNA and DNA methylation machineries to defend the mammalian germ line. Mol Cell 2024; 84:1021-1035.e11. [PMID: 38359823 PMCID: PMC10960678 DOI: 10.1016/j.molcel.2024.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 12/01/2023] [Accepted: 01/17/2024] [Indexed: 02/17/2024]
Abstract
In the male mouse germ line, PIWI-interacting RNAs (piRNAs), bound by the PIWI protein MIWI2 (PIWIL4), guide DNA methylation of young active transposons through SPOCD1. However, the underlying mechanisms of SPOCD1-mediated piRNA-directed transposon methylation and whether this pathway functions to protect the human germ line remain unknown. We identified loss-of-function variants in human SPOCD1 that cause defective transposon silencing and male infertility. Through the analysis of these pathogenic alleles, we discovered that the uncharacterized protein C19ORF84 interacts with SPOCD1. DNMT3C, the DNA methyltransferase responsible for transposon methylation, associates with SPOCD1 and C19ORF84 in fetal gonocytes. Furthermore, C19ORF84 is essential for piRNA-directed DNA methylation and male mouse fertility. Finally, C19ORF84 mediates the in vivo association of SPOCD1 with the de novo methylation machinery. In summary, we have discovered a conserved role for the human piRNA pathway in transposon silencing and C19ORF84, an uncharacterized protein essential for orchestrating piRNA-directed DNA methylation.
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Affiliation(s)
- Ansgar Zoch
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK.
| | - Gabriela Konieczny
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Tania Auchynnikava
- Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Birgit Stallmeyer
- Institute of Reproductive Genetics, University of Münster, Münster, Germany
| | - Nadja Rotte
- Institute of Reproductive Genetics, University of Münster, Münster, Germany
| | - Madeleine Heep
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Rebecca V Berrens
- Institute for Developmental and Regenerative Medicine, University of Oxford, IMS-Tetsuya Nakamura Building, Old Road Campus, Roosevelt Drive, Oxford OX37TY, UK
| | - Martina Schito
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Yuka Kabayama
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Theresa Schöpp
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Sabine Kliesch
- Centre of Reproductive Medicine and Andrology, Department of Clinical and Surgical Andrology, University Hospital Münster, Münster, Germany
| | - Brendan Houston
- School of BioSciences and Bio21 Institute, Faculty of Science, The University of Melbourne, Parkville, VIC, Australia
| | - Liina Nagirnaja
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, USA
| | - Moira K O'Bryan
- School of BioSciences and Bio21 Institute, Faculty of Science, The University of Melbourne, Parkville, VIC, Australia
| | - Kenneth I Aston
- Andrology and In Vitro Fertilization Laboratory, Department of Surgery (Urology), University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Donald F Conrad
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, USA; Center for Embryonic Cell and Gene Therapy, Oregon Health and Science University, Portland, OR, USA
| | - Juri Rappsilber
- Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK; Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Gustav-Meyer-Allee 25, 13355 Berlin, Germany
| | - Robin C Allshire
- Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Atlanta G Cook
- Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Frank Tüttelmann
- Institute of Reproductive Genetics, University of Münster, Münster, Germany
| | - Dónal O'Carroll
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, Institute for Stem Cell Research, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, Edinburgh EH9 3BF, UK.
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12
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Gu X, Wang M, Zhang XO. TE-TSS: an integrated data resource of human and mouse transposable element (TE)-derived transcription start site (TSS). Nucleic Acids Res 2024; 52:D322-D333. [PMID: 37956335 PMCID: PMC10767810 DOI: 10.1093/nar/gkad1048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 10/21/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023] Open
Abstract
Transposable elements (TEs) are abundant in the genome and serve as crucial regulatory elements. Some TEs function as epigenetically regulated promoters, and these TE-derived transcription start sites (TSSs) play a crucial role in regulating genes associated with specific functions, such as cancer and embryogenesis. However, the lack of an accessible database that systematically gathers TE-derived TSS data is a current research gap. To address this, we established TE-TSS, an integrated data resource of human and mouse TE-derived TSSs (http://xozhanglab.com/TETSS). TE-TSS has compiled 2681 RNA sequencing datasets, spanning various tissues, cell lines and developmental stages. From these, we identified 5768 human TE-derived TSSs and 2797 mouse TE-derived TSSs, with 47% and 38% being experimentally validated, respectively. TE-TSS enables comprehensive exploration of TSS usage in diverse samples, providing insights into tissue-specific gene expression patterns and transcriptional regulatory elements. Furthermore, TE-TSS compares TE-derived TSS regions across 15 mammalian species, enhancing our understanding of their evolutionary and functional aspects. The establishment of TE-TSS facilitates further investigations into the roles of TEs in shaping the transcriptomic landscape and offers valuable resources for comprehending their involvement in diverse biological processes.
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Affiliation(s)
- Xiaobing Gu
- Shanghai Key Laboratory of Maternal and Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Mingdong Wang
- Shanghai Key Laboratory of Maternal and Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Xiao-Ou Zhang
- Shanghai Key Laboratory of Maternal and Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
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13
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Türker F, Brennan A, Margolis SS. Neuronal membrane proteasome-derived peptides modulate NMDAR-dependent neuronal signaling to promote changes in gene expression. Mol Biol Cell 2024; 35:ar6. [PMID: 37910253 PMCID: PMC10881162 DOI: 10.1091/mbc.e23-06-0218] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/20/2023] [Accepted: 10/20/2023] [Indexed: 11/03/2023] Open
Abstract
The neuronal membrane proteasome (NMP) degrades intracellular proteins into peptides that are released directly into the extracellular space, whereby they stimulate neurons to promote signaling mechanisms that remain unknown. Here, we demonstrate that neuronal stimulation promotes NMP activity and, subsequently, enhanced production of NMP peptides. We show that these neuronal activity-dependent NMP peptides can rapidly promote N-methyl-D-aspartate receptor (NMDAR)-dependent calcium influx in neurons. This leads to sustained phosphorylation of the well-defined stimulus-induced transcription factor, cyclic AMP response element (CRE)-binding protein (CREB). Downstream of these events, we identified changes to neuronal target genes which included increased expression of immediate early genes (e.g., Fos, Npas4, Egr4) and other genes known to have critical neuroregulatory roles. Further observations led to the discovery that NMP peptide-induced changes in gene expression is dependent on NMDARs and independent of AMPA receptors or voltage-gated sodium channels. These data demonstrate that NMP peptides are endogenous and selective activators of NMDA receptors and act as sufficient and novel stimuli within the context of neuronal activity-dependent signaling. This novel pathway is parallel to classic neuronal activity-dependent programs and points to NMP and its resulting peptides as potential modulators of neuronal function.
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Affiliation(s)
- Fulya Türker
- Department of Biological Chemistry, The Johns Hopkins University, School of Medicine, Baltimore, MD 21205
| | - Anna Brennan
- Department of Biological Chemistry, The Johns Hopkins University, School of Medicine, Baltimore, MD 21205
| | - Seth S. Margolis
- Department of Biological Chemistry, The Johns Hopkins University, School of Medicine, Baltimore, MD 21205
- Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD 21205
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14
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Betti MJ, Aldrich MC, Gamazon ER. Minimum entropy framework identifies a novel class of genomic functional elements and reveals regulatory mechanisms at human disease loci. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.11.544507. [PMID: 37398170 PMCID: PMC10312628 DOI: 10.1101/2023.06.11.544507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
We introduce CoRE-BED, a framework trained using 19 epigenomic features in 33 major cell and tissue types to predict cell-type-specific regulatory function. CoRE-BED identifies nine functional classes de-novo, capturing both known and new regulatory categories. Notably, we describe a previously undercharacterized class that we term Development Associated Elements (DAEs), which are highly enriched in cell types with elevated regenerative potential and distinguished by the dual presence of either H3K4me2 and H3K9ac (an epigenetic signature associated with kinetochore assembly) or H3K79me3 and H4K20me1 (a signature associated with transcriptional pause release). Unlike bivalent promoters, which represent a transitory state between active and silenced promoters, DAEs transition directly to or from a non-functional state during stem cell differentiation and are proximal to highly expressed genes. CoRE-BED's interpretability facilitates causal inference and functional prioritization. Across 70 complex traits, distal insulators account for the largest mean proportion of SNP heritability (~49%) captured by the GWAS. Collectively, our results demonstrate the value of exploring non-conventional ways of regulatory classification that enrich for trait heritability, to complement existing approaches for cis-regulatory prediction.
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Affiliation(s)
| | | | - Eric R Gamazon
- Vanderbilt University Medical Center, Nashville, TN
- Clare Hall, University of Cambridge, Cambridge, England
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15
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Dondi A, Lischetti U, Jacob F, Singer F, Borgsmüller N, Coelho R, Heinzelmann-Schwarz V, Beisel C, Beerenwinkel N. Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer. Nat Commun 2023; 14:7780. [PMID: 38012143 PMCID: PMC10682465 DOI: 10.1038/s41467-023-43387-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023] Open
Abstract
Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.
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Affiliation(s)
- Arthur Dondi
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ulrike Lischetti
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland.
| | - Francis Jacob
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Franziska Singer
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
| | - Nico Borgsmüller
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ricardo Coelho
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Viola Heinzelmann-Schwarz
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
- University Hospital Basel, Gynecological Cancer Center, Spitalstrasse 21, 4031, Basel, Switzerland
| | - Christian Beisel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
| | - Niko Beerenwinkel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland.
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16
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Kerimov N, Tambets R, Hayhurst JD, Rahu I, Kolberg P, Raudvere U, Kuzmin I, Chowdhary A, Vija A, Teras HJ, Kanai M, Ulirsch J, Ryten M, Hardy J, Guelfi S, Trabzuni D, Kim-Hellmuth S, Rayner W, Finucane H, Peterson H, Mosaku A, Parkinson H, Alasoo K. eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs. PLoS Genet 2023; 19:e1010932. [PMID: 37721944 PMCID: PMC10538656 DOI: 10.1371/journal.pgen.1010932] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/28/2023] [Accepted: 08/22/2023] [Indexed: 09/20/2023] Open
Abstract
The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.
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Affiliation(s)
- Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ralf Tambets
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - James D. Hayhurst
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ida Rahu
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Peep Kolberg
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Uku Raudvere
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Ivan Kuzmin
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Anshika Chowdhary
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Andreas Vija
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Hans J. Teras
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jacob Ulirsch
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - John Hardy
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Sebastian Guelfi
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Daniah Trabzuni
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Sarah Kim-Hellmuth
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
- Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital LMU Munich, Munich, Germany
| | - William Rayner
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Hilary Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Abayomi Mosaku
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Helen Parkinson
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
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17
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Engelhard CA, Khani S, Derdak S, Bilban M, Kornfeld JW. Nanopore sequencing unveils the complexity of the cold-activated murine brown adipose tissue transcriptome. iScience 2023; 26:107190. [PMID: 37564700 PMCID: PMC10410515 DOI: 10.1016/j.isci.2023.107190] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 04/28/2023] [Accepted: 06/16/2023] [Indexed: 08/12/2023] Open
Abstract
Alternative transcription increases transcriptome complexity by expression of multiple transcripts per gene. Annotation and quantification of transcripts using short-read sequencing is non-trivial. Long-read sequencing aims at overcoming these problems by sequencing full-length transcripts. Activation of brown adipose tissue (BAT) thermogenesis involves major transcriptomic remodeling and positively affects metabolism via increased energy expenditure. We benchmark Oxford Nanopore Technology (ONT) long-read sequencing protocols to Illumina short-read sequencing assessing alignment characteristics, gene and transcript detection and quantification, differential gene and transcript expression, transcriptome reannotation, and differential transcript usage (DTU). We find ONT sequencing is superior to Illumina for transcriptome reassembly, reducing the risk of false-positive events by unambiguously mapping reads to transcripts. We identified novel isoforms of genes undergoing DTU in cold-activated BAT including Cars2, Adtrp, Acsl5, Scp2, Aldoa, and Pde4d, validated by real-time PCR. The reannotated murine BAT transcriptome established here provides a framework for future investigations into the regulation of BAT.
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Affiliation(s)
- Christoph Andreas Engelhard
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
| | - Sajjad Khani
- Max Planck Institute for Metabolism Research, Gleueler Strasse 50, 50931 Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Sophia Derdak
- Core Facilities, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna, Austria
| | - Martin Bilban
- Department of Laboratory Medicine & Core Facilities, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Jan-Wilhelm Kornfeld
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
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18
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Pagni S, Custodio HM, Frankish A, Mudge JM, Mills JD, Sisodiya SM. SCN1A: bioinformatically informed revised boundaries for promoter and enhancer regions. Hum Mol Genet 2023; 32:1753-1763. [PMID: 36715146 PMCID: PMC10162429 DOI: 10.1093/hmg/ddad015] [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: 10/07/2022] [Revised: 01/06/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
Pathogenic variations in the sodium voltage-gated channel alpha subunit 1 (SCN1A) gene are responsible for multiple epilepsy phenotypes, including Dravet syndrome, febrile seizures (FS) and genetic epilepsy with FS plus. Phenotypic heterogeneity is a hallmark of SCN1A-related epilepsies, the causes of which are yet to be clarified. Genetic variation in the non-coding regulatory regions of SCN1A could be one potential causal factor. However, a comprehensive understanding of the SCN1A regulatory landscape is currently lacking. Here, we summarized the current state of knowledge of SCN1A regulation, providing details on its promoter and enhancer regions. We then integrated currently available data on SCN1A promoters by extracting information related to the SCN1A locus from genome-wide repositories and clearly defined the promoter and enhancer regions of SCN1A. Further, we explored the cellular specificity of differential SCN1A promoter usage. We also reviewed and integrated the available human brain-derived enhancer databases and mouse-derived data to provide a comprehensive computationally developed summary of SCN1A brain-active enhancers. By querying genome-wide data repositories, extracting SCN1A-specific data and integrating the different types of independent evidence, we created a comprehensive catalogue that better defines the regulatory landscape of SCN1A, which could be used to explore the role of SCN1A regulatory regions in disease.
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Affiliation(s)
- Susanna Pagni
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Bucks SL9 0RJ, UK
| | - Helena Martins Custodio
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Bucks SL9 0RJ, UK
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - James D Mills
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Bucks SL9 0RJ, UK
- Amsterdam UMC, Department of (Neuro) Pathology, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, 1105 AZ The Netherlands
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Bucks SL9 0RJ, UK
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19
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Kerimov N, Tambets R, Hayhurst JD, Rahu I, Kolberg P, Raudvere U, Kuzmin I, Chowdhary A, Vija A, Teras HJ, Kanai M, Ulirsch J, Ryten M, Hardy J, Guelfi S, Trabzuni D, Kim-Hellmuth S, Rayner W, Finucane H, Peterson H, Mosaku A, Parkinson H, Alasoo K. Systematic visualisation of molecular QTLs reveals variant mechanisms at GWAS loci. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.06.535816. [PMID: 37066341 PMCID: PMC10104061 DOI: 10.1101/2023.04.06.535816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Splicing quantitative trait loci (QTLs) have been implicated as a common mechanism underlying complex trait associations. However, utilising splicing QTLs in target discovery and prioritisation has been challenging due to extensive data normalisation which often renders the direction of the genetic effect as well as its magnitude difficult to interpret. This is further complicated by the fact that strong expression QTLs often manifest as weak splicing QTLs and vice versa, making it difficult to uniquely identify the underlying molecular mechanism at each locus. We find that these ambiguities can be mitigated by visualising the association between the genotype and average RNA sequencing read coverage in the region. Here, we generate these QTL coverage plots for 1.7 million molecular QTL associations in the eQTL Catalogue identified with five quantification methods. We illustrate the utility of these QTL coverage plots by performing colocalisation between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. We find that while visually confirmed splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases. All our association summary statistics and QTL coverage plots are freely available at https://www.ebi.ac.uk/eqtl/.
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Affiliation(s)
- Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ralf Tambets
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - James D Hayhurst
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ida Rahu
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Peep Kolberg
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Uku Raudvere
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Ivan Kuzmin
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Anshika Chowdhary
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Andreas Vija
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Hans J Teras
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jacob Ulirsch
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London
| | - John Hardy
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London
| | - Sebastian Guelfi
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London
| | - Daniah Trabzuni
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London
| | - Sarah Kim-Hellmuth
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital LMU Munich, Munich, Germany
| | - Will Rayner
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Hilary Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
| | - Abayomi Mosaku
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Helen Parkinson
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia
- Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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20
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Shah NM, Jang HJ, Liang Y, Maeng JH, Tzeng SC, Wu A, Basri NL, Qu X, Fan C, Li A, Katz B, Li D, Xing X, Evans BS, Wang T. Pan-cancer analysis identifies tumor-specific antigens derived from transposable elements. Nat Genet 2023; 55:631-639. [PMID: 36973455 DOI: 10.1038/s41588-023-01349-3] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 02/23/2023] [Indexed: 03/29/2023]
Abstract
Cryptic promoters within transposable elements (TEs) can be transcriptionally reactivated in tumors to create new TE-chimeric transcripts, which can produce immunogenic antigens. We performed a comprehensive screen for these TE exaptation events in 33 TCGA tumor types, 30 GTEx adult tissues and 675 cancer cell lines, and identified 1,068 TE-exapted candidates with the potential to generate shared tumor-specific TE-chimeric antigens (TS-TEAs). Whole-lysate and HLA-pulldown mass spectrometry data confirmed that TS-TEAs are presented on the surface of cancer cells. In addition, we highlight tumor-specific membrane proteins transcribed from TE promoters that constitute aberrant epitopes on the extracellular surface of cancer cells. Altogether, we showcase the high pan-cancer prevalence of TS-TEAs and atypical membrane proteins that could potentially be therapeutically exploited and targeted.
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Affiliation(s)
- Nakul M Shah
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - H Josh Jang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI, USA
| | - Yonghao Liang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ju Heon Maeng
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Angela Wu
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Noah L Basri
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Xuan Qu
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Changxu Fan
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Amy Li
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Benjamin Katz
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Daofeng Li
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Xiaoyun Xing
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA.
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
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21
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Zhou H, Arapoglou T, Li X, Li Z, Zheng X, Moore J, Asok A, Kumar S, Blue E, Buyske S, Cox N, Felsenfeld A, Gerstein M, Kenny E, Li B, Matise T, Philippakis A, Rehm HL, Sofia HJ, Snyder G, NHGRI Genome Sequencing Program Variant Functional Annotation Working Group, Weng Z, Neale B, Sunyaev S, Lin X. FAVOR: functional annotation of variants online resource and annotator for variation across the human genome. Nucleic Acids Res 2023; 51:D1300-D1311. [PMID: 36350676 PMCID: PMC9825437 DOI: 10.1093/nar/gkac966] [Citation(s) in RCA: 74] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/25/2022] [Accepted: 10/14/2022] [Indexed: 11/11/2022] Open
Abstract
Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.
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Affiliation(s)
- Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Theodore Arapoglou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xiuwen Zheng
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Jill Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Sushant Kumar
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Elizabeth E Blue
- Division of Medical Genetics, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Nancy Cox
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Eimear Kenny
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Tara Matise
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Anthony Philippakis
- Data Science Platform, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Heidi J Sofia
- National Human Genome Research Institute, Bethesda, DC, USA
| | - Grace Snyder
- National Human Genome Research Institute, Bethesda, DC, USA
| | | | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Benjamin Neale
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Shamil R Sunyaev
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
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22
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scDrug: From single-cell RNA-seq to drug response prediction. Comput Struct Biotechnol J 2022; 21:150-157. [PMID: 36544472 PMCID: PMC9747355 DOI: 10.1016/j.csbj.2022.11.055] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/27/2022] [Accepted: 11/27/2022] [Indexed: 12/03/2022] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) technology allows massively parallel characterization of thousands of cells at the transcriptome level. scRNA-seq is emerging as an important tool to investigate the cellular components and their interactions in the tumor microenvironment. scRNA-seq is also used to reveal the association between tumor microenvironmental patterns and clinical outcomes and to dissect cell-specific effects of drug treatment in complex tissues. Recent advances in scRNA-seq have driven the discovery of biomarkers in diseases and therapeutic targets. Although methods for prediction of drug response using gene expression of scRNA-seq data have been proposed, an integrated tool from scRNA-seq analysis to drug discovery is required. We present scDrug as a bioinformatics workflow that includes a one-step pipeline to generate cell clustering for scRNA-seq data and two methods to predict drug treatments. The scDrug pipeline consists of three main modules: scRNA-seq analysis for identification of tumor cell subpopulations, functional annotation of cellular subclusters, and prediction of drug responses. scDrug enables the exploration of scRNA-seq data readily and facilitates the drug repurposing process. scDrug is freely available on GitHub at https://github.com/ailabstw/scDrug.
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23
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Chothani SP, Adami E, Widjaja AA, Langley SR, Viswanathan S, Pua CJ, Zhihao NT, Harmston N, D'Agostino G, Whiffin N, Mao W, Ouyang JF, Lim WW, Lim S, Lee CQE, Grubman A, Chen J, Kovalik JP, Tryggvason K, Polo JM, Ho L, Cook SA, Rackham OJL, Schafer S. A high-resolution map of human RNA translation. Mol Cell 2022; 82:2885-2899.e8. [PMID: 35841888 DOI: 10.1016/j.molcel.2022.06.023] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 03/10/2022] [Accepted: 06/15/2022] [Indexed: 10/17/2022]
Abstract
Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome.
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Affiliation(s)
- Sonia P Chothani
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Eleonora Adami
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore; Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
| | - Anissa A Widjaja
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Sarah R Langley
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore
| | - Sivakumar Viswanathan
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Chee Jian Pua
- National Heart Research Institute Singapore (NHRIS), National Heart Centre Singapore, Singapore 169609, Singapore
| | - Nevin Tham Zhihao
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore
| | - Nathan Harmston
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore; Science Division, Yale-NUS College, Singapore 138527, Singapore
| | - Giuseppe D'Agostino
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore
| | - Nicola Whiffin
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Wang Mao
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - John F Ouyang
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Wei Wen Lim
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore; National Heart Research Institute Singapore (NHRIS), National Heart Centre Singapore, Singapore 169609, Singapore
| | - Shiqi Lim
- National Heart Research Institute Singapore (NHRIS), National Heart Centre Singapore, Singapore 169609, Singapore
| | - Cheryl Q E Lee
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Alexandra Grubman
- Department of Anatomy and Developmental Biology, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Wellington Road, Clayton, VIC 3800, Australia; Australian Regenerative Medicine Institute, Monash University, Wellington Road, Clayton, VIC 3800, Australia
| | - Joseph Chen
- Department of Anatomy and Developmental Biology, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Wellington Road, Clayton, VIC 3800, Australia; Australian Regenerative Medicine Institute, Monash University, Wellington Road, Clayton, VIC 3800, Australia
| | - J P Kovalik
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Karl Tryggvason
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Jose M Polo
- Department of Anatomy and Developmental Biology, Monash University, Wellington Road, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Wellington Road, Clayton, VIC 3800, Australia; Australian Regenerative Medicine Institute, Monash University, Wellington Road, Clayton, VIC 3800, Australia
| | - Lena Ho
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Stuart A Cook
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore; National Heart Research Institute Singapore (NHRIS), National Heart Centre Singapore, Singapore 169609, Singapore; London Institute of Medical Sciences, London W12 ONN, UK
| | - Owen J L Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore; School of Biological Sciences, University of Southampton, Southampton, UK.
| | - Sebastian Schafer
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore; National Heart Research Institute Singapore (NHRIS), National Heart Centre Singapore, Singapore 169609, Singapore.
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24
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Tian X, Duan W, Zhang X, Wu X, Zhang C, Wang Z, Cao G, Gu Y, Shao F, Yan T. Metagenomic Next-Generation Sequencing Reveals the Profile of Viral Infections in Kidney Transplant Recipients During the COVID-19 Pandemic. Front Public Health 2022; 10:888064. [PMID: 35899152 PMCID: PMC9309489 DOI: 10.3389/fpubh.2022.888064] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/20/2022] [Indexed: 01/08/2023] Open
Abstract
Background To study the clinical application of metagenomic next-generation sequencing (mNGS) in the detection of viral infections in kidney transplant recipients (KTRs) during the COVID-19 pandemic. Methods Using mNGS technology, 50 human fluid samples of KTRs were detected, including 20 bronchoalveolar lavage fluid (BALF) samples, 21 urine samples and 9 blood samples. The detected nucleic acid sequences were compared and analyzed with the existing viral nucleic acid sequences in the database, and the virus infection spectrum of KTRs was drawn. Results The viral nucleic acids of 15 types of viruses were detected in 96.00% (48/50) of the samples, of which 11 types of viruses were in BALF (95.00%, 19/20), and the dominant viruses were torque teno virus (TTV) (65.00%; 13/20), cytomegalovirus (CMV) (45.00%; 9/20) and human alphaherpesvirus 1 (25.00%; 5/20). 12 viruses (95.24%, 20/21) were detected in the urine, and the dominant viruses were TTV (52.38%; 11/21), JC polyomavirus (52.38%; 11/21), BK polyomavirus (42.86%; 9/21), CMV (33.33%; 7/21) and human betaherpesvirus 6B (28.57%; 6/21). 7 viruses were detected in the blood (100.00%, 9/9), and the dominant virus was TTV (100.00%; 9/9). Four rare viruses were detected in BALF and urine, including WU polyomavirus, primate bocaparvovirus 1, simian virus 12, and volepox virus. Further analysis showed that TTV infection with high reads indicated a higher risk of acute rejection (P < 0.05). Conclusions mNGS detection reveals the rich virus spectrum of infected KTRs, and improves the detection rate of rare viruses. TTV may be a new biomarker for predicting rejection.
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Affiliation(s)
- Xiangyong Tian
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Wenjing Duan
- Department of the Clinical Research Center, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Xiulei Zhang
- Microbiology Laboratory, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Xiaoqiang Wu
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Chan Zhang
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Zhiwei Wang
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Guanghui Cao
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Yue Gu
- Department of Nephrology, Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Fengmin Shao
- Department of Nephrology, Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
| | - Tianzhong Yan
- Department of Urology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China
- *Correspondence: Tianzhong Yan
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25
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The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome. BMC Genomics 2022; 23:487. [PMID: 35787153 PMCID: PMC9251931 DOI: 10.1186/s12864-022-08717-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 06/16/2022] [Indexed: 12/30/2022] Open
Abstract
Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. This heterogeneity in assembled transcript sets might be partially explained by sequencing depth. Here, we used real and simulated short-read sequencing data as well as long-read data to systematically investigate the impact of sequencing depths on the accuracy of assembled transcripts. We assembled and analyzed transcripts from 671 human short-read data sets and four long-read data sets. At the first level, there is a positive correlation between the number of reads and the number of recovered transcripts. However, the effect of the sequencing depth varied based on cell or tissue type, the type of read and the nature and expression levels of the transcripts. The detection of coding transcripts saturated rapidly with both short and long-reads, however, there was no sign of early saturation for noncoding transcripts at any sequencing depth. Increasing long-read sequencing depth specifically benefited transcripts containing transposable elements. Finally, we show how single-cell RNA-seq can be guided by transcripts assembled from bulk long-read samples, and demonstrate that noncoding transcripts are expressed at similar levels to coding transcripts but are expressed in fewer cells. This study highlights the impact of sequencing depth on transcript assembly.
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SCN1A overexpression, associated with a genomic region marked by a risk variant for a common epilepsy, raises seizure susceptibility. Acta Neuropathol 2022; 144:107-127. [PMID: 35551471 PMCID: PMC9217876 DOI: 10.1007/s00401-022-02429-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/29/2022] [Accepted: 04/30/2022] [Indexed: 11/01/2022]
Abstract
Mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures is associated with common variation at rs7587026, located in the promoter region of SCN1A. We sought to explore possible underlying mechanisms. SCN1A expression was analysed in hippocampal biopsy specimens of individuals with mesial temporal lobe epilepsy with hippocampal sclerosis who underwent surgical treatment, and hippocampal neuronal cell loss was quantitatively assessed using immunohistochemistry. In healthy individuals, hippocampal volume was measured using MRI. Analyses were performed stratified by rs7587026 type. To study the functional consequences of increased SCN1A expression, we generated, using transposon-mediated bacterial artificial chromosome transgenesis, a zebrafish line expressing exogenous scn1a, and performed EEG analysis on larval optic tecta at 4 day post-fertilization. Finally, we used an in vitro promoter analysis to study whether the genetic motif containing rs7587026 influences promoter activity. Hippocampal SCN1A expression differed by rs7587026 genotype (Kruskal-Wallis test P = 0.004). Individuals homozygous for the minor allele showed significantly increased expression compared to those homozygous for the major allele (Dunn's test P = 0.003), and to heterozygotes (Dunn's test P = 0.035). No statistically significant differences in hippocampal neuronal cell loss were observed between the three genotypes. Among 597 healthy participants, individuals homozygous for the minor allele at rs7587026 displayed significantly reduced mean hippocampal volume compared to major allele homozygotes (Cohen's D = - 0.28, P = 0.02), and to heterozygotes (Cohen's D = - 0.36, P = 0.009). Compared to wild type, scn1lab-overexpressing zebrafish larvae exhibited more frequent spontaneous seizures [one-way ANOVA F(4,54) = 6.95 (P < 0.001)]. The number of EEG discharges correlated with the level of scn1lab overexpression [one-way ANOVA F(4,15) = 10.75 (P < 0.001]. Finally, we showed that a 50 bp promoter motif containing rs7587026 exerts a strong regulatory role on SCN1A expression, though we could not directly link this to rs7587026 itself. Our results develop the mechanistic link between rs7587026 and mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures. Furthermore, we propose that quantitative precision may be important when increasing SCN1A expression in current strategies aiming to treat seizures in conditions involving SCN1A haploinsufficiency, such as Dravet syndrome.
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A framework to score the effects of structural variants in health and disease. Genome Res 2022; 32:766-777. [PMID: 35197310 PMCID: PMC8997355 DOI: 10.1101/gr.275995.121] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 02/22/2022] [Indexed: 11/25/2022]
Abstract
While technological advances improved the identification of structural variants (SVs) in the human genome, their interpretation remains challenging. Several methods utilize individual mechanistic principles like the deletion of coding sequence or 3D genome architecture disruptions. However, a comprehensive tool using the broad spectrum of available annotations is missing. Here, we describe CADD-SV, a method to retrieve and integrate a wide set of annotations to predict the effects of SVs. Previously, supervised learning approaches were limited due to a small number and biased set of annotated pathogenic or benign SVs. We overcome this problem by using a surrogate training-objective, the Combined Annotation Dependent Depletion (CADD) of functional variants. We use human and chimpanzee derived SVs as proxy-neutral and contrast them with matched simulated variants as proxy-deleterious, an approach that has proven powerful for short sequence variants. Our tool computes summary statistics over diverse variant annotations and uses random forest models to prioritize deleterious structural variants. The resulting CADD-SV scores correlate with known pathogenic and rare population variants. We further show that we can prioritize somatic cancer variants as well as noncoding variants known to affect gene expression. We provide a website and offline-scoring tool for easy application of CADD-SV.
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28
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Preclinical Research in McArdle Disease: A Review of Research Models and Therapeutic Strategies. Genes (Basel) 2021; 13:genes13010074. [PMID: 35052414 PMCID: PMC8774685 DOI: 10.3390/genes13010074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 12/22/2021] [Accepted: 12/23/2021] [Indexed: 02/06/2023] Open
Abstract
McArdle disease is an autosomal recessive disorder of muscle glycogen metabolism caused by pathogenic mutations in the PYGM gene, which encodes the skeletal muscle-specific isoform of glycogen phosphorylase. Clinical symptoms are mainly characterized by transient acute “crises” of early fatigue, myalgia and contractures, which can be accompanied by rhabdomyolysis. Owing to the difficulty of performing mechanistic studies in patients that often rely on invasive techniques, preclinical models have been used for decades, thereby contributing to gain insight into the pathophysiology and pathobiology of human diseases. In the present work, we describe the existing in vitro and in vivo preclinical models for McArdle disease and review the insights these models have provided. In addition, despite presenting some differences with the typical patient’s phenotype, these models allow for a deep study of the different features of the disease while representing a necessary preclinical step to assess the efficacy and safety of possible treatments before they are tested in patients.
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29
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Moore JE, Zhang XO, Elhajjajy SI, Fan K, Pratt HE, Reese F, Mortazavi A, Weng Z. Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types. Genome Res 2021; 32:389-402. [PMID: 34949670 PMCID: PMC8805725 DOI: 10.1101/gr.275723.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 12/19/2021] [Indexed: 12/02/2022]
Abstract
Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type–specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3′ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.
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Affiliation(s)
| | | | | | - Kaili Fan
- University of Massachusetts Chan Medical School
| | | | | | | | - Zhiping Weng
- University of Massachusetts Chan Medical School;
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30
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Buonaiuto G, Desideri F, Taliani V, Ballarino M. Muscle Regeneration and RNA: New Perspectives for Ancient Molecules. Cells 2021; 10:cells10102512. [PMID: 34685492 PMCID: PMC8533951 DOI: 10.3390/cells10102512] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 09/17/2021] [Accepted: 09/18/2021] [Indexed: 12/21/2022] Open
Abstract
The ability of the ribonucleic acid (RNA) to self-replicate, combined with a unique cocktail of chemical properties, suggested the existence of an RNA world at the origin of life. Nowadays, this hypothesis is supported by innovative high-throughput and biochemical approaches, which definitively revealed the essential contribution of RNA-mediated mechanisms to the regulation of fundamental processes of life. With the recent development of SARS-CoV-2 mRNA-based vaccines, the potential of RNA as a therapeutic tool has received public attention. Due to its intrinsic single-stranded nature and the ease with which it is synthesized in vitro, RNA indeed represents the most suitable tool for the development of drugs encompassing every type of human pathology. The maximum effectiveness and biochemical versatility is achieved in the guise of non-coding RNAs (ncRNAs), which are emerging as multifaceted regulators of tissue specification and homeostasis. Here, we report examples of coding and ncRNAs involved in muscle regeneration and discuss their potential as therapeutic tools. Small ncRNAs, such as miRNA and siRNA, have been successfully applied in the treatment of several diseases. The use of longer molecules, such as lncRNA and circRNA, is less advanced. However, based on the peculiar properties discussed below, they represent an innovative pool of RNA biomarkers and possible targets of clinical value.
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MESH Headings
- Animals
- Biomarkers/metabolism
- COVID-19
- Homeostasis
- Humans
- Mice
- MicroRNAs/metabolism
- Muscle, Skeletal/metabolism
- Muscle, Skeletal/pathology
- Muscle, Skeletal/virology
- Myocardium/metabolism
- Origin of Life
- RNA, Circular
- RNA, Long Noncoding/genetics
- RNA, Messenger/metabolism
- RNA, Small Interfering/metabolism
- RNA, Small Untranslated/genetics
- RNA, Untranslated/genetics
- RNA, Viral/metabolism
- Regeneration
- SARS-CoV-2/genetics
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Affiliation(s)
- Giulia Buonaiuto
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy; (G.B.); (F.D.); (V.T.)
| | - Fabio Desideri
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy; (G.B.); (F.D.); (V.T.)
- Center for Life Nano & Neuro-Science of Instituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Valeria Taliani
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy; (G.B.); (F.D.); (V.T.)
| | - Monica Ballarino
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy; (G.B.); (F.D.); (V.T.)
- Correspondence:
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31
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Stefos GC, Szantai E, Konstantopoulos D, Samiotaki M, Fousteri M. aniFOUND: analysing the associated proteome and genomic landscape of the repaired nascent non-replicative chromatin. Nucleic Acids Res 2021; 49:e64. [PMID: 33693861 DOI: 10.1093/nar/gkab144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 02/01/2021] [Accepted: 02/22/2021] [Indexed: 12/13/2022] Open
Abstract
Specific capture of chromatin fractions with distinct and well-defined features has emerged as both challenging and a key strategy towards a comprehensive understanding of genome biology. In this context, we developed aniFOUND (accelerated native isolation of factors on unscheduled nascent DNA), an antibody-free method, which can label, capture, map and characterise nascent chromatin fragments that are synthesized in response to specific cues outside S-phase. We used the 'unscheduled' DNA synthesis (UDS) that takes place during the repair of UV-induced DNA lesions and coupled the captured chromatin to high-throughput analytical technologies. By mass-spectrometry we identified several factors with no previously known role in UVC-DNA damage response (DDR) as well as known DDR proteins. We experimentally validated the repair-dependent recruitment of the chromatin remodeller RSF1 and the cohesin-loader NIPBL at sites of UVC-induced photolesions. Developing aniFOUND-seq, a protocol for mapping UDS activity with high resolution, allowed us to monitor the landscape of UVC repair-synthesis events genome wide. We further resolved repair efficacy of the rather unexplored repeated genome, in particular rDNA and telomeres. In summary, aniFOUND delineates the proteome composition and genomic landscape of chromatin loci with specific features by integrating state-of-the-art 'omics' technologies to promote a comprehensive view of their function.
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Affiliation(s)
- Georgios C Stefos
- Institute for Fundamental Biomedical Research, BSRC 'Alexander Fleming', Vari 16672, Greece
| | - Eszter Szantai
- Institute for Fundamental Biomedical Research, BSRC 'Alexander Fleming', Vari 16672, Greece
| | | | | | - Maria Fousteri
- Institute for Fundamental Biomedical Research, BSRC 'Alexander Fleming', Vari 16672, Greece
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32
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Agostini F, Zagalak J, Attig J, Ule J, Luscombe NM. Intergenic RNA mainly derives from nascent transcripts of known genes. Genome Biol 2021; 22:136. [PMID: 33952325 PMCID: PMC8097831 DOI: 10.1186/s13059-021-02350-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 04/12/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Eukaryotic genomes undergo pervasive transcription, leading to the production of many types of stable and unstable RNAs. Transcription is not restricted to regions with annotated gene features but includes almost any genomic context. Currently, the source and function of most RNAs originating from intergenic regions in the human genome remain unclear. RESULTS We hypothesize that many intergenic RNAs can be ascribed to the presence of as-yet unannotated genes or the "fuzzy" transcription of known genes that extends beyond the annotated boundaries. To elucidate the contributions of these two sources, we assemble a dataset of more than 2.5 billion publicly available RNA-seq reads across 5 human cell lines and multiple cellular compartments to annotate transcriptional units in the human genome. About 80% of transcripts from unannotated intergenic regions can be attributed to the fuzzy transcription of existing genes; the remaining transcripts originate mainly from putative long non-coding RNA loci that are rarely spliced. We validate the transcriptional activity of these intergenic RNAs using independent measurements, including transcriptional start sites, chromatin signatures, and genomic occupancies of RNA polymerase II in various phosphorylation states. We also analyze the nuclear localization and sensitivities of intergenic transcripts to nucleases to illustrate that they tend to be rapidly degraded either on-chromatin by XRN2 or off-chromatin by the exosome. CONCLUSIONS We provide a curated atlas of intergenic RNAs that distinguishes between alternative processing of well-annotated genes from independent transcriptional units based on the combined analysis of chromatin signatures, nuclear RNA localization, and degradation pathways.
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Affiliation(s)
| | - Julian Zagalak
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Jan Attig
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK
| | - Jernej Ule
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Nicholas M Luscombe
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK
- UCL Genetics Institute, Department of Genetics, Environment and Evolution, University College London, Gower Street, London, WC1E 6BT, UK
- Okinawa Institute of Science & Technology Graduate University, 1919-1 Tancha, Onna-son, Kunigami-gun, Okinawa, 904-0495, Japan
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33
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Migocka-Patrzałek M, Elias M. Muscle Glycogen Phosphorylase and Its Functional Partners in Health and Disease. Cells 2021; 10:cells10040883. [PMID: 33924466 PMCID: PMC8070155 DOI: 10.3390/cells10040883] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 04/09/2021] [Accepted: 04/11/2021] [Indexed: 02/07/2023] Open
Abstract
Glycogen phosphorylase (PG) is a key enzyme taking part in the first step of glycogenolysis. Muscle glycogen phosphorylase (PYGM) differs from other PG isoforms in expression pattern and biochemical properties. The main role of PYGM is providing sufficient energy for muscle contraction. However, it is expressed in tissues other than muscle, such as the brain, lymphoid tissues, and blood. PYGM is important not only in glycogen metabolism, but also in such diverse processes as the insulin and glucagon signaling pathway, insulin resistance, necroptosis, immune response, and phototransduction. PYGM is implicated in several pathological states, such as muscle glycogen phosphorylase deficiency (McArdle disease), schizophrenia, and cancer. Here we attempt to analyze the available data regarding the protein partners of PYGM to shed light on its possible interactions and functions. We also underline the potential for zebrafish to become a convenient and applicable model to study PYGM functions, especially because of its unique features that can complement data obtained from other approaches.
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34
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Abugessaisa I, Ramilowski JA, Lizio M, Severin J, Hasegawa A, Harshbarger J, Kondo A, Noguchi S, Yip CW, Ooi J, Tagami M, Hori F, Agrawal S, Hon C, Cardon M, Ikeda S, Ono H, Bono H, Kato M, Hashimoto K, Bonetti A, Kato M, Kobayashi N, Shin J, de Hoon M, Hayashizaki Y, Carninci P, Kawaji H, Kasukawa T. FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs. Nucleic Acids Res 2021; 49:D892-D898. [PMID: 33211864 PMCID: PMC7779024 DOI: 10.1093/nar/gkaa1054] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/16/2020] [Accepted: 10/21/2020] [Indexed: 11/15/2022] Open
Abstract
The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.
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Affiliation(s)
- Imad Abugessaisa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jordan A Ramilowski
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Advanced Medical Research Center, Yokohama City University, Kanagawa, Japan
| | - Marina Lizio
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jesicca Severin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Akira Hasegawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jayson Harshbarger
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Atsushi Kondo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Shuhei Noguchi
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Chi Wai Yip
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | | | - Michihira Tagami
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Fumi Hori
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Saumya Agrawal
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Chung Chau Hon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Melissa Cardon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Shuya Ikeda
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
| | - Hiromasa Ono
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
| | - Hidemasa Bono
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
- Program of Biomedical Science, Graduate School of Integrated Sciences for Life, Hiroshima University
| | - Masaki Kato
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Kosuke Hashimoto
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Alessandro Bonetti
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Karolinska Institutet, Stockholm, Sweden
| | - Masaki Kato
- RIKEN Head Office for Information Systems and Cybersecurity, Wako, Saitama, Japan
| | - Norio Kobayashi
- RIKEN Head Office for Information Systems and Cybersecurity, Wako, Saitama, Japan
| | - Jay Shin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Michiel de Hoon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | | | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Hideya Kawaji
- Correspondence may also be addressed to Hideya Kawaji.
| | - Takeya Kasukawa
- To whom correspondence should be addressed. Tel: +81 45 503 9222; Fax: +81 45 503 9219;
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35
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Cipriano A, Macino M, Buonaiuto G, Santini T, Biferali B, Peruzzi G, Colantoni A, Mozzetta C, Ballarino M. Epigenetic regulation of Wnt7b expression by the cis-acting long noncoding RNA Lnc-Rewind in muscle stem cells. eLife 2021; 10:54782. [PMID: 33432928 PMCID: PMC7837680 DOI: 10.7554/elife.54782] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 01/11/2021] [Indexed: 12/19/2022] Open
Abstract
Skeletal muscle possesses an outstanding capacity to regenerate upon injury due to the adult muscle stem cell (MuSC) activity. This ability requires the proper balance between MuSC expansion and differentiation, which is critical for muscle homeostasis and contributes, if deregulated, to muscle diseases. Here, we functionally characterize a novel chromatin-associated long noncoding RNA (lncRNA), Lnc-Rewind, which is expressed in murine MuSCs and conserved in human. We find that, in mouse, Lnc-Rewind acts as an epigenetic regulator of MuSC proliferation and expansion by influencing the expression of skeletal muscle genes and several components of the WNT (Wingless-INT) signalling pathway. Among them, we identified the nearby Wnt7b gene as a direct Lnc-Rewind target. We show that Lnc-Rewind interacts with the G9a histone lysine methyltransferase and mediates the in cis repression of Wnt7b by H3K9me2 deposition. Overall, these findings provide novel insights into the epigenetic regulation of adult muscle stem cells fate by lncRNAs.
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Affiliation(s)
- Andrea Cipriano
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy
| | - Martina Macino
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy.,Institute of Molecular Biology and Pathology (IBPM), National Research Council (CNR) at Sapienza University of Rome, Rome, Italy
| | - Giulia Buonaiuto
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy
| | - Tiziana Santini
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy.,Center for Life Nano Science at Sapienza, Istituto Italiano di Tecnologia, Rome, Italy
| | - Beatrice Biferali
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy.,Institute of Molecular Biology and Pathology (IBPM), National Research Council (CNR) at Sapienza University of Rome, Rome, Italy
| | - Giovanna Peruzzi
- Center for Life Nano Science at Sapienza, Istituto Italiano di Tecnologia, Rome, Italy
| | - Alessio Colantoni
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy
| | - Chiara Mozzetta
- Institute of Molecular Biology and Pathology (IBPM), National Research Council (CNR) at Sapienza University of Rome, Rome, Italy
| | - Monica Ballarino
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy
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Sharipov RN, Kondrakhin YV, Ryabova AS, Yevshin IS, Kolpakov FA. Assessment of transcriptional importance of cell line-specific features based on GTRD and FANTOM5 data. PLoS One 2020; 15:e0243332. [PMID: 33347457 PMCID: PMC7751965 DOI: 10.1371/journal.pone.0243332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 11/19/2020] [Indexed: 11/18/2022] Open
Abstract
Creating a complete picture of the regulation of transcription seems to be an urgent task of modern biology. Regulation of transcription is a complex process carried out by transcription factors (TFs) and auxiliary proteins. Over the past decade, ChIP-Seq has become the most common experimental technology studying genome-wide interactions between TFs and DNA. We assessed the transcriptional significance of cell line-specific features using regression analysis of ChIP-Seq datasets from the GTRD database and transcriptional start site (TSS) activities from the FANTOM5 expression atlas. For this purpose, we initially generated a large number of features that were defined as the presence or absence of TFs in different promoter regions around TSSs. Using feature selection and regression analysis, we identified sets of the most important TFs that affect expression activity of TSSs in human cell lines such as HepG2, K562 and HEK293. We demonstrated that some TFs can be classified as repressors and activators depending on their location relative to TSS.
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Affiliation(s)
- Ruslan N. Sharipov
- Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation
- Specialized Educational Scientific Center, Novosibirsk State University, Novosibirsk, Russian Federation
- BIOSOFT.RU, Ltd, Novosibirsk, Russian Federation
| | - Yury V. Kondrakhin
- Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation
- BIOSOFT.RU, Ltd, Novosibirsk, Russian Federation
| | - Anna S. Ryabova
- Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation
- BIOSOFT.RU, Ltd, Novosibirsk, Russian Federation
| | - Ivan S. Yevshin
- Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation
- BIOSOFT.RU, Ltd, Novosibirsk, Russian Federation
| | - Fedor A. Kolpakov
- Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation
- BIOSOFT.RU, Ltd, Novosibirsk, Russian Federation
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Kamaraj US, Chen J, Katwadi K, Ouyang JF, Yang Sun YB, Lim YM, Liu X, Handoko L, Polo JM, Petretto E, Rackham OJ. EpiMogrify Models H3K4me3 Data to Identify Signaling Molecules that Improve Cell Fate Control and Maintenance. Cell Syst 2020; 11:509-522.e10. [DOI: 10.1016/j.cels.2020.09.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 04/30/2020] [Accepted: 09/14/2020] [Indexed: 12/14/2022]
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38
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Aguiar JA, Tremblay BJM, Mansfield MJ, Woody O, Lobb B, Banerjee A, Chandiramohan A, Tiessen N, Cao Q, Dvorkin-Gheva A, Revill S, Miller MS, Carlsten C, Organ L, Joseph C, John A, Hanson P, Austin RC, McManus BM, Jenkins G, Mossman K, Ask K, Doxey AC, Hirota JA. Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue. Eur Respir J 2020; 56:2001123. [PMID: 32675206 PMCID: PMC7366180 DOI: 10.1183/13993003.01123-2020] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 07/01/2020] [Indexed: 12/21/2022]
Abstract
In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged, causing the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV, the agent responsible for the 2003 SARS outbreak, utilises angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) host molecules for viral entry. ACE2 and TMPRSS2 have recently been implicated in SARS-CoV-2 viral infection. Additional host molecules including ADAM17, cathepsin L, CD147 and GRP78 may also function as receptors for SARS-CoV-2.To determine the expression and in situ localisation of candidate SARS-CoV-2 receptors in the respiratory mucosa, we analysed gene expression datasets from airway epithelial cells of 515 healthy subjects, gene promoter activity analysis using the FANTOM5 dataset containing 120 distinct sample types, single cell RNA sequencing (scRNAseq) of 10 healthy subjects, proteomic datasets, immunoblots on multiple airway epithelial cell types, and immunohistochemistry on 98 human lung samples.We demonstrate absent to low ACE2 promoter activity in a variety of lung epithelial cell samples and low ACE2 gene expression in both microarray and scRNAseq datasets of epithelial cell populations. Consistent with gene expression, rare ACE2 protein expression was observed in the airway epithelium and alveoli of human lung, confirmed with proteomics. We present confirmatory evidence for the presence of TMPRSS2, CD147 and GRP78 protein in vitro in airway epithelial cells and confirm broad in situ protein expression of CD147 and GRP78 in the respiratory mucosa.Collectively, our data suggest the presence of a mechanism dynamically regulating ACE2 expression in human lung, perhaps in periods of SARS-CoV-2 infection, and also suggest that alternative receptors for SARS-CoV-2 exist to facilitate initial host cell infection.
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Affiliation(s)
| | | | - Michael J Mansfield
- Genomics and Regulatory Systems Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Japan
| | - Owen Woody
- Faculty of Mathematics, University of Waterloo, Waterloo, ON, Canada
| | - Briallen Lobb
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Arinjay Banerjee
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Abiram Chandiramohan
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Nicholas Tiessen
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Quynh Cao
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Anna Dvorkin-Gheva
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Spencer Revill
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Matthew S Miller
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
- Dept of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Christopher Carlsten
- Division of Respiratory Medicine, Dept of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Louise Organ
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Chitra Joseph
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Alison John
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Paul Hanson
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Richard C Austin
- Division of Nephrology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Bruce M McManus
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Gisli Jenkins
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Karen Mossman
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Kjetil Ask
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Andrew C Doxey
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
- A.C. Doxey and J.A. Hirota contributed equally to this article as lead authors and supervised the work
| | - Jeremy A Hirota
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
- A.C. Doxey and J.A. Hirota contributed equally to this article as lead authors and supervised the work
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39
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Aguiar JA, Tremblay BJM, Mansfield MJ, Woody O, Lobb B, Banerjee A, Chandiramohan A, Tiessen N, Cao Q, Dvorkin-Gheva A, Revill S, Miller MS, Carlsten C, Organ L, Joseph C, John A, Hanson P, Austin RC, McManus BM, Jenkins G, Mossman K, Ask K, Doxey AC, Hirota JA. Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue. Eur Respir J 2020; 56. [PMID: 32675206 DOI: 10.1101/2020.04.07.030742] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 07/01/2020] [Indexed: 05/19/2023]
Abstract
In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged, causing the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV, the agent responsible for the 2003 SARS outbreak, utilises angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) host molecules for viral entry. ACE2 and TMPRSS2 have recently been implicated in SARS-CoV-2 viral infection. Additional host molecules including ADAM17, cathepsin L, CD147 and GRP78 may also function as receptors for SARS-CoV-2.To determine the expression and in situ localisation of candidate SARS-CoV-2 receptors in the respiratory mucosa, we analysed gene expression datasets from airway epithelial cells of 515 healthy subjects, gene promoter activity analysis using the FANTOM5 dataset containing 120 distinct sample types, single cell RNA sequencing (scRNAseq) of 10 healthy subjects, proteomic datasets, immunoblots on multiple airway epithelial cell types, and immunohistochemistry on 98 human lung samples.We demonstrate absent to low ACE2 promoter activity in a variety of lung epithelial cell samples and low ACE2 gene expression in both microarray and scRNAseq datasets of epithelial cell populations. Consistent with gene expression, rare ACE2 protein expression was observed in the airway epithelium and alveoli of human lung, confirmed with proteomics. We present confirmatory evidence for the presence of TMPRSS2, CD147 and GRP78 protein in vitro in airway epithelial cells and confirm broad in situ protein expression of CD147 and GRP78 in the respiratory mucosa.Collectively, our data suggest the presence of a mechanism dynamically regulating ACE2 expression in human lung, perhaps in periods of SARS-CoV-2 infection, and also suggest that alternative receptors for SARS-CoV-2 exist to facilitate initial host cell infection.
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Affiliation(s)
| | | | - Michael J Mansfield
- Genomics and Regulatory Systems Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Japan
| | - Owen Woody
- Faculty of Mathematics, University of Waterloo, Waterloo, ON, Canada
| | - Briallen Lobb
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Arinjay Banerjee
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Abiram Chandiramohan
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Nicholas Tiessen
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Quynh Cao
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Anna Dvorkin-Gheva
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Spencer Revill
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Matthew S Miller
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
- Dept of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Christopher Carlsten
- Division of Respiratory Medicine, Dept of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Louise Organ
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Chitra Joseph
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Alison John
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Paul Hanson
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Richard C Austin
- Division of Nephrology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Bruce M McManus
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Gisli Jenkins
- Nottingham NIHR Biomedical Research Centre, Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Karen Mossman
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
| | - Kjetil Ask
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
| | - Andrew C Doxey
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
- A.C. Doxey and J.A. Hirota contributed equally to this article as lead authors and supervised the work
| | - Jeremy A Hirota
- Dept of Biology, University of Waterloo, Waterloo, ON, Canada
- McMaster Immunology Research Centre, McMaster University, Hamilton, ON, Canada
- Firestone Institute for Respiratory Health - Division of Respirology, Dept of Medicine, McMaster University, Hamilton, ON, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
- A.C. Doxey and J.A. Hirota contributed equally to this article as lead authors and supervised the work
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40
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Hu FF, Liu CJ, Liu LL, Zhang Q, Guo AY. Expression profile of immune checkpoint genes and their roles in predicting immunotherapy response. Brief Bioinform 2020; 22:5894466. [PMID: 32814346 DOI: 10.1093/bib/bbaa176] [Citation(s) in RCA: 201] [Impact Index Per Article: 40.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 06/28/2020] [Accepted: 07/12/2020] [Indexed: 01/06/2023] Open
Abstract
Immune checkpoint genes (ICGs) play critical roles in circumventing self-reactivity and represent a novel target to develop treatments for cancers. However, a comprehensive analysis for the expression profile of ICGs at a pan-cancer level and their correlation with patient response to immune checkpoint blockade (ICB) based therapy is still lacking. In this study, we defined three expression patterns of ICGs using a comprehensive survey of RNA-seq data of tumor and immune cells from the functional annotation of the mammalian genome (FANTOM5) project. The correlation between the expression patterns of ICGs and patients survival and response to ICB therapy was investigated. The expression patterns of ICGs were robust across cancers, and upregulation of ICGs was positively correlated with high lymphocyte infiltration and good prognosis. Furthermore, we built a model (ICGe) to predict the response of patients to ICB therapy using five features of ICG expression. A validation scenario of six independent datasets containing data of 261 patients with CTLA-4 and PD-1 blockade immunotherapies demonstrated that ICGe achieved area under the curves of 0.64-0.82 and showed a robust performance and outperformed other mRNA-based predictors. In conclusion, this work revealed expression patterns of ICGs and underlying correlations between ICGs and response to ICB, which helps to understand the mechanisms of ICGs in ICB signal pathways and other anticancer treatments.
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Affiliation(s)
- Fei-Fei Hu
- Wuhan University of Science and Technology
| | | | - Lan-Lan Liu
- Huazhong University of Science and Technology
| | - Qiong Zhang
- Huazhong University of Science and Technology
| | - An-Yuan Guo
- Huazhong University of Science and Technology
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41
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Alam T, Agrawal S, Severin J, Young RS, Andersson R, Arner E, Hasegawa A, Lizio M, Ramilowski JA, Abugessaisa I, Ishizu Y, Noma S, Tarui H, Taylor MS, Lassmann T, Itoh M, Kasukawa T, Kawaji H, Marchionni L, Sheng G, R R Forrest A, Khachigian LM, Hayashizaki Y, Carninci P, de Hoon MJL. Comparative transcriptomics of primary cells in vertebrates. Genome Res 2020; 30:951-961. [PMID: 32718981 PMCID: PMC7397866 DOI: 10.1101/gr.255679.119] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 06/09/2020] [Indexed: 12/18/2022]
Abstract
Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.
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Affiliation(s)
- Tanvir Alam
- College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
| | - Saumya Agrawal
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Jessica Severin
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Robert S Young
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, United Kingdom.,MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Robin Andersson
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Erik Arner
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Akira Hasegawa
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Marina Lizio
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | | | - Imad Abugessaisa
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yuri Ishizu
- RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama 230-0045, Japan
| | - Shohei Noma
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Hiroshi Tarui
- RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama 230-0045, Japan
| | - Martin S Taylor
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Timo Lassmann
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Telethon Kids Institute, University of Western Australia, Perth, WA 6009, Australia
| | - Masayoshi Itoh
- RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan
| | - Takeya Kasukawa
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Hideya Kawaji
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan
| | - Luigi Marchionni
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Guojun Sheng
- International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan
| | - Alistair R R Forrest
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Harry Perkins Institute of Medical Research, and the Centre for Medical Research, University of Western Australia, QEII Medical Centre, Perth, WA 6009, Australia
| | - Levon M Khachigian
- Vascular Biology and Translational Research, School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, NSW 2052 Australia
| | | | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
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Xia X, Wu WKK, Wong SH, Liu D, Kwong TNY, Nakatsu G, Yan PS, Chuang YM, Chan MWY, Coker OO, Chen Z, Yeoh YK, Zhao L, Wang X, Cheng WY, Chan MTV, Chan PKS, Sung JJY, Wang MH, Yu J. Bacteria pathogens drive host colonic epithelial cell promoter hypermethylation of tumor suppressor genes in colorectal cancer. MICROBIOME 2020; 8:108. [PMID: 32678024 PMCID: PMC7367367 DOI: 10.1186/s40168-020-00847-4] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 04/26/2020] [Indexed: 05/09/2023]
Abstract
BACKGROUND Altered microbiome composition and aberrant promoter hypermethylation of tumor suppressor genes (TSGs) are two important hallmarks of colorectal cancer (CRC). Here we performed concurrent 16S rRNA gene sequencing and methyl-CpG binding domain-based capture sequencing in 33 tissue biopsies (5 normal colonic mucosa tissues, 4 pairs of adenoma and adenoma-adjacent tissues, and 10 pairs of CRC and CRC-adjacent tissues) to identify significant associations between TSG promoter hypermethylation and CRC-associated bacteria, followed by functional validation of the methylation-associated bacteria. RESULTS Fusobacterium nucleatum and Hungatella hathewayi were identified as the top two methylation-regulating bacteria. Targeted analysis on bona fide TSGs revealed that H. hathewayi and Streptococcus spp. significantly correlated with CDX2 and MLH1 promoter hypermethylation, respectively. Mechanistic validation with cell-line and animal models revealed that F. nucleatum and H. hathewayi upregulated DNA methyltransferase. H. hathewayi inoculation also promoted colonic epithelial cell proliferation in germ-free and conventional mice. CONCLUSION Our integrative analysis revealed previously unknown epigenetic regulation of TSGs in host cells through inducing DNA methyltransferase by F. nucleatum and H. hathewayi, and established the latter as CRC-promoting bacteria. Video abstract.
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Affiliation(s)
- Xiaoxuan Xia
- Division of Biostatistics, Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - William Ka Kei Wu
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Sunny Hei Wong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Dabin Liu
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Thomas Ngai Yeung Kwong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Geicho Nakatsu
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Pearlly S Yan
- Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - Yu-Ming Chuang
- Department of Biomedical Sciences, National Chung Cheng University, Chia-Yi, Taiwan, Republic of China
| | - Michael Wing-Yan Chan
- Department of Biomedical Sciences, National Chung Cheng University, Chia-Yi, Taiwan, Republic of China
| | - Olabisi Oluwabukola Coker
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Zigui Chen
- Department of Microbiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Yun Kit Yeoh
- Department of Microbiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Liuyang Zhao
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Xiansong Wang
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Wing Yin Cheng
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Matthew Tak Vai Chan
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Paul Kay Sheung Chan
- Department of Microbiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Joseph Jao Yiu Sung
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China
| | - Maggie Haitian Wang
- Division of Biostatistics, Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China.
| | - Jun Yu
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China.
- State Key Laboratory of Digestive Diseases, Institute of Digestive Diseases, CUHK-Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China.
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, Special Administrative Region of China.
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Rodríguez-Martínez M, Boissiére T, Noe Gonzalez M, Litchfield K, Mitter R, Walker J, Kjœr S, Ismail M, Downward J, Swanton C, Svejstrup JQ. Evidence That STK19 Is Not an NRAS-dependent Melanoma Driver. Cell 2020; 181:1395-1405.e11. [PMID: 32531245 PMCID: PMC7298618 DOI: 10.1016/j.cell.2020.04.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 03/18/2020] [Accepted: 04/10/2020] [Indexed: 12/20/2022]
Abstract
STK19 was proposed to be a cancer driver, and recent work by Yin et al. (2019) in Cell suggested that the frequently recurring STK19 D89N substitution represents a gain-of-function change, allowing increased phosphorylation of NRAS to enhance melanocyte transformation. Here we show that the STK19 gene has been incorrectly annotated, and that the expressed protein is 110 amino acids shorter than indicated by current databases. The "cancer driving" STK19 D89N substitution is thus outside the coding region. We also fail to detect evidence of the mutation affecting STK19 expression; instead, it is a UV signature mutation, found in the promoter of other genes as well. Furthermore, STK19 is exclusively nuclear and chromatin-associated, while no evidence for it being a kinase was found. The data in this Matters Arising article raise fundamental questions about the recently proposed role for STK19 in melanoma progression via a function as an NRAS kinase, suggested by Yin et al. (2019) in Cell. See also the response by Yin et al. (2020), published in this issue.
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Affiliation(s)
- Marta Rodríguez-Martínez
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Thierry Boissiére
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Melvin Noe Gonzalez
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Kevin Litchfield
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Richard Mitter
- Bioinformatics and Biostatistics, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Jane Walker
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Svend Kjœr
- Structural Biology Science Technology Platform, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Mohamed Ismail
- Oncogene Biology Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Julian Downward
- Oncogene Biology Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Charles Swanton
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Jesper Q Svejstrup
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
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44
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Steffens S, Fu X, He F, Li Y, Babarinde IA, Hutchins AP. DPre: computational identification of differentiation bias and genes underlying cell type conversions. Bioinformatics 2020; 36:1637-1639. [PMID: 31621827 DOI: 10.1093/bioinformatics/btz789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 10/09/2019] [Accepted: 10/15/2019] [Indexed: 11/12/2022] Open
Abstract
SUMMARY Cells are generally resistant to cell type conversions, but can be converted by the application of growth factors, chemical inhibitors and ectopic expression of genes. However, it remains difficult to accurately identify the destination cell type or differentiation bias when these techniques are used to alter cell type. Consequently, there is demand for computational techniques that can help researchers understand both the cell type and differentiation bias. While advanced tools identifying cell types exist for single cell data and the deconvolution of mixed cell populations, the problem of exploring partially differentiated cells of indeterminate transcriptional identity has not been addressed. To fill this gap, we developed driver-predictor, which relies on scoring per gene transcriptional similarity between RNA-Seq datasets to reveal directional bias of differentiation. By comparing against large cell type transcriptome libraries or a desired target expression profile, the tool enables the user to visualize both the changes in transcriptional identity as well as the genes accounting for the cell type changes. This software will be a powerful tool for researchers to explore in vitro experiments that involve cell type conversions. AVAILABILITY AND IMPLEMENTATION Source code is open source under the MIT license and is freely available on https://github.com/LoaloaF/DPre. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Simon Steffens
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Xiuling Fu
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Fangfang He
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Yuhao Li
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Isaac A Babarinde
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Andrew P Hutchins
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
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45
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Bertuzzi M, Tang D, Calligaris R, Vlachouli C, Finaurini S, Sanges R, Goldwurm S, Catalan M, Antonutti L, Manganotti P, Pizzolato G, Pezzoli G, Persichetti F, Carninci P, Gustincich S. A human minisatellite hosts an alternative transcription start site for NPRL3 driving its expression in a repeat number-dependent manner. Hum Mutat 2020; 41:807-824. [PMID: 31898848 DOI: 10.1002/humu.23974] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 11/16/2019] [Accepted: 12/24/2019] [Indexed: 12/21/2022]
Abstract
Minisatellites, also called variable number of tandem repeats (VNTRs), are a class of repetitive elements that may affect gene expression at multiple levels and have been correlated to disease. Their identification and role as expression quantitative trait loci (eQTL) have been limited by their absence in comparative genomic hybridization and single nucleotide polymorphisms arrays. By taking advantage of cap analysis of gene expression (CAGE), we describe a new example of a minisatellite hosting a transcription start site (TSS) which expression is dependent on the repeat number. It is located in the third intron of the gene nitrogen permease regulator like protein 3 (NPRL3). NPRL3 is a component of the GAP activity toward rags 1 protein complex that inhibits mammalian target of rapamycin complex 1 (mTORC1) activity and it is found mutated in familial focal cortical dysplasia and familial focal epilepsy. CAGE tags represent an alternative TSS identifying TAGNPRL3 messenger RNAs (mRNAs). TAGNPRL3 is expressed in red blood cells both at mRNA and protein levels, it interacts with its protein partner NPRL2 and its overexpression inhibits cell proliferation. This study provides an example of a minisatellite that is both a TSS and an eQTL as well as identifies a new VNTR that may modify mTORC1 activity.
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Affiliation(s)
| | - Dave Tang
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - Raffaella Calligaris
- Area of Neuroscience, SISSA, Trieste, Italy.,Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | | | - Sara Finaurini
- Area of Neuroscience, SISSA, Trieste, Italy.,Department of Health Sciences, Università del Piemonte Orientale and IRCAD, Novara, Italy
| | - Remo Sanges
- Area of Neuroscience, SISSA, Trieste, Italy.,Central RNA Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | | | - Mauro Catalan
- Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | - Lucia Antonutti
- Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | - Paolo Manganotti
- Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | - Gilberto Pizzolato
- Department of Medical Sciences, Neurology Unit, University of Trieste, Trieste, Italy
| | - Gianni Pezzoli
- Parkinson Institute, ASST G. Pini-CTO, ex ICP, Milan, Italy
| | - Francesca Persichetti
- Department of Health Sciences, Università del Piemonte Orientale and IRCAD, Novara, Italy
| | - Piero Carninci
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.,Laboratory for Transcriptome Technology, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
| | - Stefano Gustincich
- Area of Neuroscience, SISSA, Trieste, Italy.,Central RNA Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
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46
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Abstract
Two decades ago a class of ion channels, hitherto unsuspected, was discovered. In mammals these Transient Receptor Potential channels (TRPs) have not only expanded in number (to 26 functional channels) but also expanded the view of our interface with the physical and chemical environment. Some are heat and cold sensors while others monitor endogenous and/or exogenous chemical signals. Some TRP channels monitor osmotic potential, and others measure cell movement, stretching, and fluid flow. Many TRP channels are major players in nociception and integration of pain signals. One member of the vanilloid sub-family of channels is TRPV6. This channel is highly selective for divalent cations, particularly calcium, and plays a part in general whole-body calcium homeostasis, capturing calcium in the gut from the diet. TRPV6 can be greatly elevated in a number of cancers deriving from epithelia and considerable study has been made of its role in the cancer phenotype where calcium control is dysfunctional. This review compiles and updates recent published work on TRPV6 as a promising drug target in a number of cancers including those afflicting breast, ovarian, prostate and pancreatic tissues.
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Affiliation(s)
- John M. Stewart
- Soricimed Biopharma Inc. 18 Botsford Street, Moncton, NB, Canada, E1C 4W7
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47
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Atlas of quantitative single-base-resolution N 6-methyl-adenine methylomes. Nat Commun 2019; 10:5636. [PMID: 31822664 PMCID: PMC6904561 DOI: 10.1038/s41467-019-13561-z] [Citation(s) in RCA: 132] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 11/12/2019] [Indexed: 01/14/2023] Open
Abstract
Various methyltransferases and demethylases catalyse methylation and demethylation of N6-methyladenosine (m6A) and N6,2'-O-dimethyladenosine (m6Am) but precise methylomes uniquely mediated by each methyltransferase/demethylase are still lacking. Here, we develop m6A-Crosslinking-Exonuclease-sequencing (m6ACE-seq) to map transcriptome-wide m6A and m6Am at quantitative single-base-resolution. This allows for the generation of a comprehensive atlas of distinct methylomes uniquely mediated by every individual known methyltransferase or demethylase. Our atlas reveals METTL16 to indirectly impact manifold methylation targets beyond its consensus target motif and highlights the importance of precision in mapping PCIF1-dependent m6Am. Rather than reverse RNA methylation, we find that both ALKBH5 and FTO instead maintain their regulated sites in an unmethylated steady-state. In FTO's absence, anomalous m6Am disrupts snRNA interaction with nuclear export machinery, potentially causing aberrant pre-mRNA splicing events.
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48
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Grozhik AV, Olarerin-George AO, Sindelar M, Li X, Gross SS, Jaffrey SR. Antibody cross-reactivity accounts for widespread appearance of m 1A in 5'UTRs. Nat Commun 2019; 10:5126. [PMID: 31719534 PMCID: PMC6851129 DOI: 10.1038/s41467-019-13146-w] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/10/2019] [Indexed: 11/30/2022] Open
Abstract
N1-methyladenosine (m1A) was proposed to be a highly prevalent modification in mRNA 5'UTRs based on mapping studies using an m1A-binding antibody. We developed a bioinformatic approach to discover m1A and other modifications in mRNA throughout the transcriptome by analyzing preexisting ultra-deep RNA-Seq data for modification-induced misincorporations. Using this approach, we detected appreciable levels of m1A only in one mRNA: the mitochondrial MT-ND5 transcript. As an alternative approach, we also developed an antibody-based m1A-mapping approach to detect m1A at single-nucleotide resolution, and confirmed that the commonly used m1A antibody maps sites to the transcription-start site in mRNA 5'UTRs. However, further analysis revealed that these were false-positives caused by binding of the antibody to the m7G-cap. A different m1A antibody that lacks cap-binding cross-reactivity does not show enriched binding in 5'UTRs. These results demonstrate that high-stoichiometry m1A sites are exceedingly rare in mRNAs and that previous mappings of m1A to 5'UTRs were the result of antibody cross-reactivity to the 5' cap.
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Affiliation(s)
- Anya V Grozhik
- Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA
| | | | - Miriam Sindelar
- Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Xing Li
- Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Steven S Gross
- Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Samie R Jaffrey
- Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA.
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49
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Boulias K, Toczydłowska-Socha D, Hawley BR, Liberman N, Takashima K, Zaccara S, Guez T, Vasseur JJ, Debart F, Aravind L, Jaffrey SR, Greer EL. Identification of the m 6Am Methyltransferase PCIF1 Reveals the Location and Functions of m 6Am in the Transcriptome. Mol Cell 2019; 75:631-643.e8. [PMID: 31279658 DOI: 10.1016/j.molcel.2019.06.006] [Citation(s) in RCA: 196] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 04/08/2019] [Accepted: 06/02/2019] [Indexed: 12/21/2022]
Abstract
mRNAs are regulated by nucleotide modifications that influence their cellular fate. Two of the most abundant modified nucleotides are N6-methyladenosine (m6A), found within mRNAs, and N6,2'-O-dimethyladenosine (m6Am), which is found at the first transcribed nucleotide. Distinguishing these modifications in mapping studies has been difficult. Here, we identify and biochemically characterize PCIF1, the methyltransferase that generates m6Am. We find that PCIF1 binds and is dependent on the m7G cap. By depleting PCIF1, we generated transcriptome-wide maps that distinguish m6Am and m6A. We find that m6A and m6Am misannotations arise from mRNA isoforms with alternative transcription start sites (TSSs). These isoforms contain m6Am that maps to "internal" sites, increasing the likelihood of misannotation. We find that depleting PCIF1 does not substantially affect mRNA translation but is associated with reduced stability of a subset of m6Am-annotated mRNAs. The discovery of PCIF1 and our accurate mapping technique will facilitate future studies to characterize m6Am's function.
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Affiliation(s)
- Konstantinos Boulias
- Division of Newborn Medicine, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Diana Toczydłowska-Socha
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA; Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Ben R Hawley
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
| | - Noa Liberman
- Division of Newborn Medicine, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Ken Takashima
- Division of Newborn Medicine, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Sara Zaccara
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA
| | - Théo Guez
- IBMM, Université de Montpellier, CNRS, ENSCM, Montpellier, France
| | | | - Françoise Debart
- IBMM, Université de Montpellier, CNRS, ENSCM, Montpellier, France
| | - L Aravind
- NCBI, National Library of Medicine, NIH, Bethesda, MD 20894, USA
| | - Samie R Jaffrey
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10065, USA.
| | - Eric Lieberman Greer
- Division of Newborn Medicine, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA.
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50
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Abugessaisa I, Noguchi S, Hasegawa A, Kondo A, Kawaji H, Carninci P, Kasukawa T. refTSS: A Reference Data Set for Human and Mouse Transcription Start Sites. J Mol Biol 2019; 431:2407-2422. [DOI: 10.1016/j.jmb.2019.04.045] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Revised: 04/25/2019] [Accepted: 04/29/2019] [Indexed: 01/22/2023]
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