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Saboktakin Rizi S, Stamenkovic A, Ravandi A. Integrative Omics Approaches in Cardiovascular Disease Research: Current Trends and Future Directions. Can J Cardiol 2025:S0828-282X(25)00126-6. [PMID: 39952467 DOI: 10.1016/j.cjca.2025.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2024] [Revised: 01/29/2025] [Accepted: 02/04/2025] [Indexed: 02/17/2025] Open
Affiliation(s)
- Shekoofeh Saboktakin Rizi
- Precision Cardiovascular Medicine Group, St Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada; Section of Cardiology, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Aleksandra Stamenkovic
- Precision Cardiovascular Medicine Group, St Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada; Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Amir Ravandi
- Precision Cardiovascular Medicine Group, St Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada; Section of Cardiology, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada; Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
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2
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Monistrol-Mula A, Diaz-Torres S, Felez-Nobrega M, Haro JM, Medland SE, Mitchell BL. Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19. Mol Psychiatry 2025; 30:29-36. [PMID: 38956374 DOI: 10.1038/s41380-024-02643-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 07/04/2024]
Abstract
Current literature suggests that people with psychiatric disorders have a higher risk of COVID-19 infection and a worse prognosis of the disease. We aimed to study the genetic contribution to these associations across seven psychiatric disorders as well as a general psychopathology factor (P-factor) and determine whether these are unique or shared across psychiatric disorders using statistical genetic techniques. Using the largest available genome-wide association studies (GWAS), we found a significant genetic overlap between depression, ADHD, PTSD, and the P-factor with both COVID-19 infection and hospitalization, and between anxiety and COVID-19 hospitalization. We used pairwise GWAS to examine this overlap on a fine-grained scale and identified specific regions of the genome shared between several psychiatric disorders, the P-factor, and COVID-19. Gene-based analysis in these genomic regions suggested possible links with immune-related pathways such as thyroid homeostasis, inflammation, and stress response. Finally, we show preliminary evidence for causal associations between depression, ADHD, PTSD, and the P-factor, and higher COVID-19 infection and hospitalization using Mendelian Randomization and Latent Causal Variable methods. Our results support the hypothesis that the relationship between psychiatric disorders and COVID-19 risk is likely due to shared alterations in immune-related pathways and is not a result of environmental factors alone, shedding light on potentially viable therapeutic targets.
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Affiliation(s)
- Anna Monistrol-Mula
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- Department of Medicine, University of Barcelona, Barcelona, Spain.
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
| | - Santiago Diaz-Torres
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mireia Felez-Nobrega
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Josep Maria Haro
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Sarah E Medland
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, University of Queensland, Brisbane, QLD, Australia
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3
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Abdelmalek CM, Singh S, Fasil B, Horvath AR, Mulkey SB, Curé C, Campos M, Cavalcanti DP, Tong VT, Mercado M, Daza M, Marcela Benavides M, Acosta J, Gilboa S, Valencia D, Sancken CL, Newton S, Scalabrin DMF, Mussi-Pinhata MM, Vasconcelos Z, Chakhtoura N, Moye J, Leslie EJ, Bulas D, Vezina G, Marques FJP, Leyser M, Del Campo M, Vilain E, DeBiasi RL, Wang T, Nath A, Haydar T, Muenke M, Mansour TA, du Plessis AJ, Murray JC, Cordero JF, Kousa YA. Building a growing genomic data repository for maternal and fetal health through the PING Consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.24.24307899. [PMID: 38826415 PMCID: PMC11142296 DOI: 10.1101/2024.05.24.24307899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background Prenatally transmitted viruses can cause severe damage to the developing brain. There is unexplained variability in prenatal brain injury and postnatal neurodevelopmental outcomes, suggesting disease modifiers. Discordant outcomes among dizygotic twins could be explained by genetic susceptibly or protection. Among several well-recognized threats to the developing brain, Zika is a mosquito-borne, positive-stranded RNA virus that was originally isolated in Uganda and spread to cause epidemics in Africa, Asia, and the Americas. In the Americas, the virus caused congenital Zika syndrome and a multitude of neurodevelopmental disorders. As of now, there is no preventative treatment or cure for the adverse outcomes caused by prenatal Zika infection. The Prenatal Infection and Neurodevelopmental Genetics (PING) Consortium was initiated in 2016 to identify factors modulating prenatal brain injury and postnatal neurodevelopmental outcomes for Zika and other prenatal viral infections. Methods The Consortium has pooled information from eight multi-site studies conducted at 23 research centers in six countries to build a growing clinical and genomic data repository. This repository is being mined to search for modifiers of virally induced brain injury and developmental outcomes. Multilateral partnerships include commitments with Children's National Hospital (USA), Instituto Nacional de Salud (Colombia), the Natural History of Zika Virus Infection in Gestation program (Brazil), and Zika Instituto Fernandes Figueira (Brazil), in addition to the Centers for Disease Control and Prevention and the National Institutes of Health. Discussion Our goal in bringing together these sets of patient data was to test the hypothesis that personal and populational genetic differences affect the severity of brain injury after a prenatal viral infection and modify neurodevelopmental outcomes. We have enrolled 4,102 mothers and 3,877 infants with 3,063 biological samples and clinical data covering over 80 phenotypic fields and 5,000 variables. There were several notable challenges in bringing together cohorts enrolled in different studies, including variability in the timepoints evaluated and the collected clinical data and biospecimens. Thus far, we have performed whole exome sequencing on 1,226 participants. Here, we present the Consortium's formation and the overarching study design. We began our investigation with prenatal Zika infection with the goal of applying this knowledge to other prenatal infections and exposures that can affect brain development.
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4
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Jeng XJ, Hu Y, Venkat V, Lu TP, Tzeng JY. Transfer learning with false negative control improves polygenic risk prediction. PLoS Genet 2023; 19:e1010597. [PMID: 38011285 PMCID: PMC10723713 DOI: 10.1371/journal.pgen.1010597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 12/15/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
Polygenic risk score (PRS) is a quantity that aggregates the effects of variants across the genome and estimates an individual's genetic predisposition for a given trait. PRS analysis typically contains two input data sets: base data for effect size estimation and target data for individual-level prediction. Given the availability of large-scale base data, it becomes more common that the ancestral background of base and target data do not perfectly match. In this paper, we treat the GWAS summary information obtained in the base data as knowledge learned from a pre-trained model, and adopt a transfer learning framework to effectively leverage the knowledge learned from the base data that may or may not have similar ancestral background as the target samples to build prediction models for target individuals. Our proposed transfer learning framework consists of two main steps: (1) conducting false negative control (FNC) marginal screening to extract useful knowledge from the base data; and (2) performing joint model training to integrate the knowledge extracted from base data with the target training data for accurate trans-data prediction. This new approach can significantly enhance the computational and statistical efficiency of joint-model training, alleviate over-fitting, and facilitate more accurate trans-data prediction when heterogeneity level between target and base data sets is small or high.
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Affiliation(s)
- Xinge Jessie Jeng
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Yifei Hu
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Vaishnavi Venkat
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Tzu-Pin Lu
- Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan
- Department of Public Health, National Taiwan University, Taipei, Taiwan
| | - Jung-Ying Tzeng
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, United States of America
- Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan
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5
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Snaebjarnarson AS, Helgadottir A, Arnadottir GA, Ivarsdottir EV, Thorleifsson G, Ferkingstad E, Einarsson G, Sveinbjornsson G, Thorgeirsson TE, Ulfarsson MO, Halldorsson BV, Olafsson I, Erikstrup C, Pedersen OB, Nyegaard M, Bruun MT, Ullum H, Brunak S, Iversen KK, Christensen AH, Olesen MS, Ghouse J, Banasik K, Knowlton KU, Arnar DO, Thorgeirsson G, Nadauld L, Ostrowski SR, Bundgaard H, Holm H, Sulem P, Stefansson K, Gudbjartsson DF. Complex effects of sequence variants on lipid levels and coronary artery disease. Cell 2023; 186:4085-4099.e15. [PMID: 37714134 DOI: 10.1016/j.cell.2023.08.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/06/2023] [Accepted: 08/10/2023] [Indexed: 09/17/2023]
Abstract
Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Magnus O Ulfarsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik 102, Iceland
| | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus 8200, Denmark; Department of Clinical Medicine, Health, Aarhus University, Aarhus 8200, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge 4600, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg 9220, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense 5000, Denmark
| | - Henrik Ullum
- Statens Serum Institut, Copenhagen 2300, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kasper Karmark Iversen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Emergency Medicine, Copenhagen University Hospital Herlev and Gentofte, Herlev 2900, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Alex Hoerby Christensen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Morten S Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Jonas Ghouse
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT 84143, USA
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Lincoln Nadauld
- Precision Genomics, Intermountain Healthcare, Saint George, UT 84790, USA
| | - Sisse Rye Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland.
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; School of Engineering and Natural Sciences, University of Iceland, Reykjavik 102, Iceland.
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6
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Kulminski AM, Jain‐Washburn E, Philipp I, He L, Loika Y, Loiko E, Bagley O, Ukraintseva S, Yashin A, Arbeev K, Stallard E, Feitosa MF, Schupf N, Christensen K, Culminskaya I. APOE ɛ4 allele and TOMM40-APOC1 variants jointly contribute to survival to older ages. Aging Cell 2022; 21:e13730. [PMID: 36330582 PMCID: PMC9741507 DOI: 10.1111/acel.13730] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 09/23/2022] [Accepted: 03/10/2022] [Indexed: 11/06/2022] Open
Abstract
Age-related diseases characteristic of post-reproductive life, aging, and life span are the examples of polygenic non-Mendelian traits with intricate genetic architectures. Polygenicity of these traits implies that multiple variants can impact their risks independently or jointly as combinations of specific variants. Here, we examined chances to live to older ages, 85 years and older, for carriers of compound genotypes comprised of combinations of genotypes of rs429358 (APOE ɛ4 encoding polymorphism), rs2075650 (TOMM40), and rs12721046 (APOC1) polymorphisms using data from four human studies. The choice of these polymorphisms was motivated by our prior results showing that the ɛ4 carriers having minor alleles of the other two polymorphisms were at exceptionally high risk of Alzheimer's disease (AD), compared with non-carriers of the minor alleles. Consistent with our prior findings for AD, we show here that the adverse effect of the ɛ4 allele on survival to older ages is significantly higher in carriers of minor alleles of rs2075650 and/or rs12721046 polymorphisms compared with their non-carriers. The exclusion of AD cases made this effect stronger. Our results provide compelling evidence that AD does not mediate the associations of the same compound genotypes with chances to survive until older ages, indicating the existence of genetically heterogeneous mechanisms. The survival chances can be mainly associated with lipid- and immunity-related mechanisms, whereas the AD risk, can be driven by the AD-biomarker-related mechanism, among others. Targeting heterogeneous polygenic profiles of individuals at high risks of complex traits is promising for the translation of genetic discoveries to health care.
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Affiliation(s)
- Alexander M. Kulminski
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Ethan Jain‐Washburn
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Ian Philipp
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Liang He
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Elena Loiko
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Olivia Bagley
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Svetlana Ukraintseva
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Anatoliy Yashin
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Konstantin Arbeev
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Eric Stallard
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of GeneticsWashington University School of MedicineSt LouisMissouriUSA
| | - Nicole Schupf
- Gertrude H. Sergievsky CenterColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Kaare Christensen
- Unit of Epidemiology, Biostatistics and Biodemography, Department of Public HealthSouthern Denmark UniversityOdenseDenmark
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamNorth CarolinaUSA
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7
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Jung J, Khan MM, Landry J, Halavatyi A, Machado P, Reiss M, Pepperkok R. Regulation of the COPII secretory machinery via focal adhesions and extracellular matrix signaling. J Cell Biol 2022; 221:213351. [PMID: 35829701 PMCID: PMC9284426 DOI: 10.1083/jcb.202110081] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 05/10/2022] [Accepted: 06/24/2022] [Indexed: 12/19/2022] Open
Abstract
Proteins that enter the secretory pathway are transported from their place of synthesis in the endoplasmic reticulum to the Golgi complex by COPII-coated carriers. The networks of proteins that regulate these components in response to extracellular cues have remained largely elusive. Using high-throughput microscopy, we comprehensively screened 378 cytoskeleton-associated and related proteins for their functional interaction with the coat protein complex II (COPII) components SEC23A and SEC23B. Among these, we identified a group of proteins associated with focal adhesions (FERMT2, MACF1, MAPK8IP2, NGEF, PIK3CA, and ROCK1) that led to the downregulation of SEC23A when depleted by siRNA. Changes in focal adhesions induced by plating cells on ECM also led to the downregulation of SEC23A and decreases in VSVG transport from ER to Golgi. Both the expression of SEC23A and the transport defect could be rescued by treatment with a focal adhesion kinase inhibitor. Altogether, our results identify a network of cytoskeleton-associated proteins connecting focal adhesions and ECM-related signaling with the gene expression of the COPII secretory machinery and trafficking.
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Affiliation(s)
- Juan Jung
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Muzamil Majid Khan
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, German Center for Lung Research, Heidelberg, Germany
| | - Jonathan Landry
- Core Facilities Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Aliaksandr Halavatyi
- Core Facilities Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Pedro Machado
- Core Facilities Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Miriam Reiss
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Rainer Pepperkok
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Core Facilities Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, German Center for Lung Research, Heidelberg, Germany
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8
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Xu B, Zhu Y, Cao C, Chen H, Jin Q, Li G, Ma J, Yang SL, Zhao J, Zhu J, Ding Y, Fang X, Jin Y, Kwok CK, Ren A, Wan Y, Wang Z, Xue Y, Zhang H, Zhang QC, Zhou Y. Recent advances in RNA structurome. SCIENCE CHINA. LIFE SCIENCES 2022; 65:1285-1324. [PMID: 35717434 PMCID: PMC9206424 DOI: 10.1007/s11427-021-2116-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/01/2022] [Indexed: 12/27/2022]
Abstract
RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.
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Affiliation(s)
- Bingbing Xu
- MOE Laboratory of Biosystems Homeostasis & Protection, Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yanda Zhu
- MOE Laboratory of Biosystems Homeostasis & Protection, Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Changchang Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Hao Chen
- Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China
| | - Qiongli Jin
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Guangnan Li
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, 430072, China
| | - Junfeng Ma
- Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Siwy Ling Yang
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, A*STAR, Singapore, Singapore
| | - Jieyu Zhao
- Department of Chemistry, and State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China
| | - Jianghui Zhu
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology and Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing, 100084, China
| | - Yiliang Ding
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, United Kingdom.
| | - Xianyang Fang
- Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
| | - Yongfeng Jin
- MOE Laboratory of Biosystems Homeostasis & Protection, Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
| | - Chun Kit Kwok
- Department of Chemistry, and State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China.
- Shenzhen Research Institute of City University of Hong Kong, Shenzhen, 518057, China.
| | - Aiming Ren
- Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
| | - Yue Wan
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, A*STAR, Singapore, Singapore.
| | - Zhiye Wang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
| | - Yuanchao Xue
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100101, China.
| | - Huakun Zhang
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, 130024, China.
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology and Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
- Tsinghua-Peking Center for Life Sciences, Beijing, 100084, China.
| | - Yu Zhou
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, 430072, China.
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