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Tsai CY, Hsu JSJ, Chen PL, Wu CC. Implementing next-generation sequencing for diagnosis and management of hereditary hearing impairment: a comprehensive review. Expert Rev Mol Diagn 2024:1-13. [PMID: 39194060 DOI: 10.1080/14737159.2024.2396866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 08/22/2024] [Indexed: 08/29/2024]
Abstract
INTRODUCTION Sensorineural hearing impairment (SNHI), a common childhood disorder with heterogeneous genetic causes, can lead to delayed language development and psychosocial problems. Next-generation sequencing (NGS) offers high-throughput screening and high-sensitivity detection of genetic etiologies of SNHI, enabling clinicians to make informed medical decisions, provide tailored treatments, and improve prognostic outcomes. AREAS COVERED This review covers the diverse etiologies of HHI and the utility of different NGS modalities (targeted sequencing and whole exome/genome sequencing), and includes HHI-related studies on newborn screening, genetic counseling, prognostic prediction, and personalized treatment. Challenges such as the trade-off between cost and diagnostic yield, detection of structural variants, and exploration of the non-coding genome are also highlighted. EXPERT OPINION In the current landscape of NGS-based diagnostics for HHI, there are both challenges (e.g. detection of structural variants and non-coding genome variants) and opportunities (e.g. the emergence of medical artificial intelligence tools). The authors advocate the use of technological advances such as long-read sequencing for structural variant detection, multi-omics analysis for non-coding variant exploration, and medical artificial intelligence for pathogenicity assessment and outcome prediction. By integrating these innovations into clinical practice, precision medicine in the diagnosis and management of HHI can be further improved.
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Affiliation(s)
- Cheng-Yu Tsai
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan
| | - Jacob Shu-Jui Hsu
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pei-Lung Chen
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Institute of Molecular Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Chi Wu
- Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Medical Research, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan
- Department of Otolaryngology, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan
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2
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Dayal Aggarwal D, Mishra P, Yadav G, Mitra S, Patel Y, Singh M, Sahu RK, Sharma V. Decoding the connection between lncRNA and obesity: Perspective from humans and Drosophila. Heliyon 2024; 10:e35327. [PMID: 39166041 PMCID: PMC11334870 DOI: 10.1016/j.heliyon.2024.e35327] [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: 11/28/2023] [Revised: 07/20/2024] [Accepted: 07/26/2024] [Indexed: 08/22/2024] Open
Abstract
Background Obesity is a burgeoning global health problem with an escalating prevalence and severe implications for public health. New evidence indicates that long non-coding RNAs (lncRNAs) may play a pivotal role in regulating adipose tissue function and energy homeostasis across various species. However, the molecular mechanisms underlying obesity remain elusive. Scope of review This review discusses obesity and fat metabolism in general, highlighting the emerging importance of lncRNAs in modulating adipogenesis. It describes the regulatory networks, latest tools, techniques, and approaches to enhance our understanding of obesity and its lncRNA-mediated epigenetic regulation in humans and Drosophila. Major conclusions This review analyses large datasets of human and Drosophila lncRNAs from published databases and literature with experimental evidence supporting lncRNAs role in fat metabolism. It concludes that lncRNAs play a crucial role in obesity-related metabolism. Cross-species comparisons highlight the relevance of Drosophila findings to human obesity, emphasizing their potential role in adipose tissue biology. Furthermore, it discusses how recent technological advancements and multi-omics data integration enhance our capacity to characterize lncRNAs and their function. Additionally, this review briefly touches upon innovative methodologies like experimental evolution and advanced sequencing technologies for identifying novel genes and lncRNA regulators in Drosophila, which can potentially contribute to obesity research.
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Affiliation(s)
- Dau Dayal Aggarwal
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - Prachi Mishra
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - Gaurav Yadav
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - Shrishti Mitra
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - Yashvant Patel
- Department of Zoology, Banaras Hindu University, Varanasi, India
| | - Manvender Singh
- Department of Biotechnology, UIET, MD University, Rohtak, India
| | - Ranjan Kumar Sahu
- Department of Neurology, Houston Methodist Research Insititute, Houston, Tx, USA
| | - Vijendra Sharma
- Department of Biomedical Sciences, University of Windsor, Ontario, Canada
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3
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Sheikhnia F, Fazilat A, Rashidi V, Azizzadeh B, Mohammadi M, Maghsoudi H, Majidinia M. Exploring the therapeutic potential of quercetin in cancer treatment: Targeting long non-coding RNAs. Pathol Res Pract 2024; 260:155374. [PMID: 38889494 DOI: 10.1016/j.prp.2024.155374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 05/11/2024] [Accepted: 05/28/2024] [Indexed: 06/20/2024]
Abstract
The escalating global incidence of cancer, which results in millions of fatalities annually, underscores the pressing need for effective pharmacological interventions across diverse cancer types. Long noncoding RNAs (lncRNAs), a class of RNA molecules that lack protein-coding capacity but profoundly impact gene expression regulation, have emerged as pivotal players in key cellular processes, including proliferation, apoptosis, metastasis, cellular metabolism, and drug resistance. Among natural compounds, quercetin, a phenolic compound abundantly present in fruits and vegetables has garnered attention due to its significant anticancer properties. Quercetin demonstrates the ability to inhibit cancer cell growth and induce apoptosis-a process often impaired in malignant cells. In this comprehensive review, we delve into the therapeutic potential of quercetin in cancer treatment, with a specific focus on its intricate interactions with lncRNAs. We explore how quercetin modulates lncRNA expression and function to exert its anticancer effects. Notably, quercetin suppresses oncogenic lncRNAs that drive cancer development and progression while enhancing tumor-suppressive lncRNAs that impede cancer growth and dissemination. Additionally, we discuss quercetin's role as a chemopreventive agent, which plays a crucial role in mitigating cancer risk. We address research challenges and future directions, emphasizing the necessity for in-depth mechanistic studies and strategies to enhance quercetin's bioavailability and target specificity. By synthesizing existing knowledge, this review underscores quercetin's promising potential as a novel therapeutic strategy in the ongoing battle against cancer, offering fresh insights and avenues for further investigation in this critical field.
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Affiliation(s)
- Farhad Sheikhnia
- Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran; Department of Clinical Biochemistry, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran
| | - Ahmad Fazilat
- Motamed Cancer Institute, Breast Cancer Research Center, ACECR, Tehran, Iran
| | - Vahid Rashidi
- Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran
| | - Bita Azizzadeh
- Department of Biochemistry, School of Medicine, Ilam University of Medical sciences, Ilam, Iran
| | - Mahya Mohammadi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hossein Maghsoudi
- Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran; Department of Clinical Biochemistry, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran
| | - Maryam Majidinia
- Solid Tumor Research Center, Cellular and Molecular Medicine Institute, Urmia University of Medical Sciences, Urmia, Iran.
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4
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Ma Y, Harris J, Li P, Jiang C, Sun H, Cao H. An Integrative Transcriptome Subtraction Strategy to Identify Human lncRNAs That Specifically Play a Role in Activation of Human Hepatic Stellate Cells. Noncoding RNA 2024; 10:34. [PMID: 38921831 PMCID: PMC11206700 DOI: 10.3390/ncrna10030034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/31/2024] [Accepted: 06/04/2024] [Indexed: 06/27/2024] Open
Abstract
Fibrotic liver features excessive deposition of extracellular matrix (ECM), primarily produced from "activated" hepatic stellate cells (HSCs). While targeting human HSCs (hHSCs) in fibrosis therapeutics shows promise, the overall understanding of hHSC activation remains limited, in part because it is very challenging to define the role of human long non-coding RNAs (lncRNAs) in hHSC activation. To address this challenge, we identified another cell type that acts via a diverse gene network to promote fibrogenesis. Then, we identified the lncRNAs that were differentially regulated in activated hHSCs and the other profibrotic cell. Next, we conducted concurrent analysis to identify those lncRNAs that were specifically involved in fibrogenesis. We tested and confirmed that transdifferentiation of vascular smooth muscle cells (VSMCs) represents such a process. By overlapping TGFβ-regulated lncRNAs in multiple sets of hHSCs and VSMCs, we identified a highly selected list of lncRNA candidates that could specifically play a role in hHSC activation. We experimentally characterized one human lncRNA, named CARMN, which was significantly regulated by TGFβ in all conditions above. CARMN knockdown significantly reduced the expression levels of a panel of marker genes for hHSC activation, as well as the levels of ECM deposition and hHSC migration. Conversely, gain of function of CARMN using CRISPR activation (CRISPR-a) yielded the completely opposite effects. Taken together, our work addresses a bottleneck in identifying human lncRNAs that specifically play a role in hHSC activation and provides a framework to effectively select human lncRNAs with significant pathophysiological role.
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Affiliation(s)
| | | | | | | | | | - Haiming Cao
- Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
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5
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Illarregi U, Lopez-Lopez E. LncRNA expression and regulatory networks across pediatric cancers. Transl Pediatr 2024; 13:383-386. [PMID: 38455753 PMCID: PMC10915441 DOI: 10.21037/tp-23-531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 01/11/2024] [Indexed: 03/09/2024] Open
Affiliation(s)
- Unai Illarregi
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Elixabet Lopez-Lopez
- Department of Biochemistry and Molecular Biology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
- Pediatric Oncology Group, Biobizkaia Health Research Institute, Barakaldo, Spain
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6
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Greenlaw AC, Alavattam KG, Tsukiyama T. Post-transcriptional regulation shapes the transcriptome of quiescent budding yeast. Nucleic Acids Res 2024; 52:1043-1063. [PMID: 38048329 PMCID: PMC10853787 DOI: 10.1093/nar/gkad1147] [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: 08/09/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 12/06/2023] Open
Abstract
To facilitate long-term survival, cells must exit the cell cycle and enter quiescence, a reversible non-replicative state. Budding yeast cells reprogram their gene expression during quiescence entry to silence transcription, but how the nascent transcriptome changes in quiescence is unknown. By investigating the nascent transcriptome, we identified over a thousand noncoding RNAs in quiescent and G1 yeast cells, and found noncoding transcription represented a larger portion of the quiescent transcriptome than in G1. Additionally, both mRNA and ncRNA are subject to increased post-transcriptional regulation in quiescence compared to G1. We found that, in quiescence, the nuclear exosome-NNS pathway suppresses over one thousand mRNAs, in addition to canonical noncoding RNAs. RNA sequencing through quiescent entry revealed two distinct time points at which the nuclear exosome controls the abundance of mRNAs involved in protein production, cellular organization, and metabolism, thereby facilitating efficient quiescence entry. Our work identified a previously unknown key biological role for the nuclear exosome-NNS pathway in mRNA regulation and uncovered a novel layer of gene-expression control in quiescence.
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Affiliation(s)
- Alison C Greenlaw
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Molecular and Cellular Biology Program, Fred Hutchinson Cancer Center and University of Washington, Seattle, WA 98195, USA
| | - Kris G Alavattam
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Toshio Tsukiyama
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
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Liao H, Barra C, Zhou Z, Peng X, Woodhouse I, Tailor A, Parker R, Carré A, Borrow P, Hogan MJ, Paes W, Eisenlohr LC, Mallone R, Nielsen M, Ternette N. MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer. Nat Commun 2024; 15:661. [PMID: 38253617 PMCID: PMC10803737 DOI: 10.1038/s41467-023-44460-z] [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: 07/24/2022] [Accepted: 12/14/2023] [Indexed: 01/24/2024] Open
Abstract
Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.
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Affiliation(s)
- Hanqing Liao
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | | | - Zhicheng Zhou
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
| | - Xu Peng
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
| | - Isaac Woodhouse
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Arun Tailor
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Robert Parker
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Alexia Carré
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
| | - Persephone Borrow
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Michael J Hogan
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Wayne Paes
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Laurence C Eisenlohr
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, 75014, Paris, France
| | | | - Nicola Ternette
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK.
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK.
- University of Utrecht, Department of Pharmaceutical Sciences, 3584 CH, Utrecht, The Netherlands.
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8
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Kotlyarov S. Identification of Important Genes Associated with the Development of Atherosclerosis. Curr Gene Ther 2024; 24:29-45. [PMID: 36999180 DOI: 10.2174/1566523223666230330091241] [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: 09/17/2022] [Revised: 12/06/2022] [Accepted: 01/26/2023] [Indexed: 04/01/2023]
Abstract
Atherosclerosis is one of the most important medical problems due to its prevalence and significant contribution to the structure of temporary and permanent disability and mortality. Atherosclerosis is a complex chain of events occurring in the vascular wall over many years. Disorders of lipid metabolism, inflammation, and impaired hemodynamics are important mechanisms of atherogenesis. A growing body of evidence strengthens the understanding of the role of genetic and epigenetic factors in individual predisposition and development of atherosclerosis and its clinical outcomes. In addition, hemodynamic changes, lipid metabolism abnormalities, and inflammation are closely related and have many overlapping links in regulation. A better study of these mechanisms may improve the quality of diagnosis and management of such patients.
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Affiliation(s)
- Stanislav Kotlyarov
- Department of Nursing, Ryazan State Medical University Named After Academician I.P. Pavlov, Russian Federation
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Poller W, Sahoo S, Hajjar R, Landmesser U, Krichevsky AM. Exploration of the Noncoding Genome for Human-Specific Therapeutic Targets-Recent Insights at Molecular and Cellular Level. Cells 2023; 12:2660. [PMID: 37998395 PMCID: PMC10670380 DOI: 10.3390/cells12222660] [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: 10/06/2023] [Revised: 11/13/2023] [Accepted: 11/14/2023] [Indexed: 11/25/2023] Open
Abstract
While it is well known that 98-99% of the human genome does not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs [ncRNAs] with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two topics of high current interest: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel therapeutic targets in human diseases? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the profound interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with remarkable recent progress regarding delivery, efficacy, and safety of nucleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.
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Affiliation(s)
- Wolfgang Poller
- Department for Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum Charité (DHZC), Charité-Universitätsmedizin Berlin, 12200 Berlin, Germany;
- Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 13353 Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Site Berlin, 10785 Berlin, Germany
| | - Susmita Sahoo
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1030, New York, NY 10029, USA;
| | - Roger Hajjar
- Gene & Cell Therapy Institute, Mass General Brigham, 65 Landsdowne St, Suite 143, Cambridge, MA 02139, USA;
| | - Ulf Landmesser
- Department for Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum Charité (DHZC), Charité-Universitätsmedizin Berlin, 12200 Berlin, Germany;
- German Center for Cardiovascular Research (DZHK), Site Berlin, 10785 Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Anna M. Krichevsky
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
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Calanca N, Francisco ALN, Bizinelli D, Kuasne H, Barros Filho MC, Flores BCT, Pinto CAL, Rainho CA, Soares MBP, Marchi FA, Kowalski LP, Rogatto SR. DNA methylation-based depiction of the immune microenvironment and immune-associated long non-coding RNAs in oral cavity squamous cell carcinomas. Biomed Pharmacother 2023; 167:115559. [PMID: 37742611 DOI: 10.1016/j.biopha.2023.115559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/18/2023] [Accepted: 09/19/2023] [Indexed: 09/26/2023] Open
Abstract
Oral cavity squamous cell carcinoma (OSCC) is a complex and dynamic disease characterized by clinicopathological and molecular heterogeneity. Spatial and temporal heterogeneity of cell subpopulations has been associated with cancer progression and implicated in the prognosis and therapy response. Emerging evidence indicates that aberrant epigenetic profiles in OSCC may foster an immunosuppressive tumor microenvironment by modulating the expression of immune-related long non-coding RNAs (lncRNAs). DNA methylation analysis was performed in 46 matched OSCC and normal adjacent tissue samples using a genome-wide platform (Infinium HumanMethylation450 BeadChip). Reference-based computational deconvolution (MethylCIBERSORT) was applied to infer the immune cell composition of the bulk samples. The expression levels of genes encoding immune markers and differentially methylated lncRNAs were investigated using The Cancer Genome Atlas dataset. OSCC specimens presented distinct immune cell composition, including the enrichment of monocyte lineage cells, natural killer cells, cytotoxic T-lymphocytes, regulatory T-lymphocytes, and neutrophils. In contrast, B-lymphocytes, effector T-lymphocytes, and fibroblasts were diminished in tumor samples. The hypomethylation of three immune-associated lncRNAs (MEG3, MIR155HG, and WFDC21P) at individual CpG sites was confirmed by bisulfite-pyrosequencing. Also, the upregulation of a set of immune markers (FOXP3, GZMB, IL10, IL2RA, TGFB, IFNG, TDO2, IDO1, and HIF1A) was detected. The immune cell composition, immune markers alteration, and dysregulation of immune-associated lncRNAs reinforce the impact of the immune microenvironment in OSCC. These concurrent factors contribute to tumor heterogeneity, suggesting that epi-immunotherapy could be an efficient alternative to treat OSCC.
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Affiliation(s)
- Naiade Calanca
- Department of Clinical Genetics, University Hospital of Southern Denmark-Vejle, Institute of Regional Health Research, University of Southern Denmark, Odense 5000, Denmark; Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu 18618-689, SP, Brazil
| | - Ana Lucia Noronha Francisco
- Department of Head and Neck Surgery and Otorhinolaryngology, A.C.Camargo Cancer Center, São Paulo 01509-001, SP, Brazil
| | - Daniela Bizinelli
- International Research Center (CIPE), A.C.Camargo Cancer Center, São Paulo 01508-010, SP, Brazil
| | - Hellen Kuasne
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal H3A1A3, QC, Canada
| | | | - Bianca Campos Troncarelli Flores
- Department of Clinical Genetics, University Hospital of Southern Denmark-Vejle, Institute of Regional Health Research, University of Southern Denmark, Odense 5000, Denmark
| | | | - Claudia Aparecida Rainho
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu 18618-689, SP, Brazil
| | - Milena Botelho Pereira Soares
- Health Technology Institute, SENAI CIMATEC, Salvador 41650-010, BA, Brazil; Gonçalo Moniz Institute, FIOCRUZ, Salvador 40296-710, BA, Brazil
| | - Fabio Albuquerque Marchi
- Department of Head and Neck Surgery, University of São Paulo Medical School, São Paulo 05402-000, SP, Brazil
| | - Luiz Paulo Kowalski
- Department of Head and Neck Surgery and Otorhinolaryngology, A.C.Camargo Cancer Center, São Paulo 01509-001, SP, Brazil; Department of Head and Neck Surgery, University of São Paulo Medical School, São Paulo 05402-000, SP, Brazil
| | - Silvia Regina Rogatto
- Department of Clinical Genetics, University Hospital of Southern Denmark-Vejle, Institute of Regional Health Research, University of Southern Denmark, Odense 5000, Denmark.
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Varabyou A, Sommer MJ, Erdogdu B, Shinder I, Minkin I, Chao KH, Park S, Heinz J, Pockrandt C, Shumate A, Rincon N, Puiu D, Steinegger M, Salzberg SL, Pertea M. CHESS 3: an improved, comprehensive catalog of human genes and transcripts based on large-scale expression data, phylogenetic analysis, and protein structure. Genome Biol 2023; 24:249. [PMID: 37904256 PMCID: PMC10614308 DOI: 10.1186/s13059-023-03088-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 10/16/2023] [Indexed: 11/01/2023] Open
Abstract
CHESS 3 represents an improved human gene catalog based on nearly 10,000 RNA-seq experiments across 54 body sites. It significantly improves current genome annotation by integrating the latest reference data and algorithms, machine learning techniques for noise filtering, and new protein structure prediction methods. CHESS 3 contains 41,356 genes, including 19,839 protein-coding genes and 158,377 transcripts, with 14,863 protein-coding transcripts not in other catalogs. It includes all MANE transcripts and at least one transcript for most RefSeq and GENCODE genes. On the CHM13 human genome, the CHESS 3 catalog contains an additional 129 protein-coding genes. CHESS 3 is available at http://ccb.jhu.edu/chess .
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Affiliation(s)
- Ales Varabyou
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA.
| | - Markus J Sommer
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Beril Erdogdu
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Ida Shinder
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Cross Disciplinary Graduate Program in Biomedical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Ilia Minkin
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Kuan-Hao Chao
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Sukhwan Park
- School of Biological Sciences, Seoul National University, Seoul, South Korea
- Artificial Intelligence Institute, Seoul National University, Seoul, South Korea
| | - Jakob Heinz
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Christopher Pockrandt
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Alaina Shumate
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Natalia Rincon
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Daniela Puiu
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA
| | - Martin Steinegger
- School of Biological Sciences, Seoul National University, Seoul, South Korea
- Artificial Intelligence Institute, Seoul National University, Seoul, South Korea
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, South Korea
| | - Steven L Salzberg
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
| | - Mihaela Pertea
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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12
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SL, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O'Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. Am J Hum Genet 2023; 110:1704-1717. [PMID: 37802043 PMCID: PMC10577076 DOI: 10.1016/j.ajhg.2023.09.003] [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: 06/22/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 10/08/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jacob A Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon Lr Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Tulane University Translational Science Institute, New Orleans, LA, USA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA; Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Take Naseri
- Naseri & Associates Public Health Consultancy Firm and Family Health Clinic, Apia, Samoa; International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Wayne H-H Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (NHRI), Miaoli County, Taiwan
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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13
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Eun JW, Cheong JY, Jeong JY, Kim HS. A New Understanding of Long Non-Coding RNA in Hepatocellular Carcinoma-From m 6A Modification to Blood Biomarkers. Cells 2023; 12:2272. [PMID: 37759495 PMCID: PMC10528438 DOI: 10.3390/cells12182272] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
With recent advancements in biological research, long non-coding RNAs (lncRNAs) with lengths exceeding 200 nucleotides have emerged as pivotal regulators of gene expression and cellular phenotypic modulation. Despite initial skepticism due to their low sequence conservation and expression levels, their significance in various biological processes has become increasingly apparent. We provided an overview of lncRNAs and discussed their defining features and modes of operation. We then explored their crucial function in the hepatocarcinogenesis process, elucidating their complex involvement in hepatocellular carcinoma (HCC). The influential role of lncRNAs within the HCC tumor microenvironment is emphasized, illustrating their potential as key modulators of disease dynamics. We also investigated the significant influence of N6-methyladenosine (m6A) modification on lncRNA function in HCC, enhancing our understanding of both their roles and their upstream regulators. Additionally, the potential of lncRNAs as promising biomarkers was discussed in liver cancer diagnosis, suggesting a novel avenue for future research and clinical application. Finally, our work underscored the dual potential of lncRNAs as both contributors to HCC pathogenesis and innovative tools for its diagnosis. Existing challenges and prospective trajectories in lncRNA research are also discussed, emphasizing their potential in advancing liver cancer research.
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Affiliation(s)
- Jung Woo Eun
- Department of Gastroenterology, Ajou University School of Medicine, 164 World cup-ro, Yeongtong-gu, Suwon 16499, Republic of Korea; (J.W.E.); (J.Y.C.)
| | - Jae Youn Cheong
- Department of Gastroenterology, Ajou University School of Medicine, 164 World cup-ro, Yeongtong-gu, Suwon 16499, Republic of Korea; (J.W.E.); (J.Y.C.)
| | - Jee-Yeong Jeong
- Department of Biochemistry, College of Medicine, Kosin University, Seo-gu, Busan 49267, Republic of Korea;
- Institute for Medical Science, College of Medicine, Kosin University, Seo-gu, Busan 49267, Republic of Korea
| | - Hyung Seok Kim
- Department of Biochemistry, College of Medicine, Kosin University, Seo-gu, Busan 49267, Republic of Korea;
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14
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Thatai AKS, Ammankallu S, Devasahayam Arokia Balaya R, Soman SP, Nisar M, Babu S, John L, George A, Anto CK, Sanjeev D, Kandiyil MK, Raj SS, Awasthi K, Vinodchandra SS, Prasad TSK, Raju R. VirhostlncR: A comprehensive database to explore lncRNAs and their targets in viral infections. Comput Biol Med 2023; 164:107279. [PMID: 37572440 DOI: 10.1016/j.compbiomed.2023.107279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 07/11/2023] [Accepted: 07/16/2023] [Indexed: 08/14/2023]
Abstract
Long non-coding-RNAs (lncRNAs) are an expanding set of cis-/trans-regulatory RNA genes that outnumber the protein-coding genes. Although being increasingly discovered, the functional role of the majority of lncRNAs in diverse biological conditions is undefined. Increasing evidence supports the critical role of lncRNAs in the emergence, regulation, and progression of various viral infections including influenza, hepatitis, coronavirus, and human immunodeficiency virus. Hence, the identification of signature lncRNAs would facilitate focused analysis of their functional roles accounting for their targets and regulatory mechanisms associated with infections. Towards this, we compiled 2803 lncRNAs identified to be modulated by 33 viral strains in various mammalian cell types and are provided through the resource named VirhostlncR (http://ciods.in/VirhostlncR/). The information on each of the viral strains, their multiplicity of infection, duration of infection, host cell name and cell types, fold change of lncRNA expression, and their specific identification methods are integrated into VirhostlncR. Based on the current datasets, we report 150 lncRNAs including differentiation antagonizing non-protein coding RNA (DANCR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed gene 3 (MEG3), nuclear paraspeckle assembly transcript 1 (NEAT1), and plasmacytoma variant translocation 1 (PVT1) to be perturbed by two or more viruses. Analysis of viral protein interactions with human transcription factors (TFs) or TF-containing protein complexes identified that distinct viruses can transcriptionally regulate many of these lncRNAs through multiple protein complexes. Together, we believe that the current dataset will enable priority selection of lncRNAs for identification of their targets and serve as an effective platform for the analysis of noncoding RNA-mediated regulations in viral infections.
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Affiliation(s)
- Arun Kumar Sumaithangi Thatai
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - Shruthi Ammankallu
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - Rex Devasahayam Arokia Balaya
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Sreelakshmi Pathappillil Soman
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India; Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Mahammad Nisar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Sreeranjini Babu
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India; Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Levin John
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Anju George
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - Christy Kallely Anto
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Diya Sanjeev
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India.
| | - Mrudula Kinarulla Kandiyil
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - Sini S Raj
- Department of Computer Science, University of Kerala, Thiruvananthapuram, 695 581, Kerala, India.
| | - Kriti Awasthi
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - S S Vinodchandra
- Department of Computer Science, University of Kerala, Thiruvananthapuram, 695 581, Kerala, India.
| | - Thottethodi Subrahmanya Keshava Prasad
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India; Omics Analytics Pvt. Ltd., Yenepoya Incubator, Deralakatte, Mangalore, 575 018, Karnataka, India.
| | - Rajesh Raju
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, 575 018, Karnataka, India; Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Manjanade, Mangalore, 575 018, Karnataka, India; Omics Analytics Pvt. Ltd., Yenepoya Incubator, Deralakatte, Mangalore, 575 018, Karnataka, India.
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15
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Ma Y, Cao H. 'Lnc-ing' T reg cells to the aging liver. NATURE AGING 2023; 3:760-761. [PMID: 37291220 DOI: 10.1038/s43587-023-00439-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Affiliation(s)
- Yonghe Ma
- Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Haiming Cao
- Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
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16
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SLR, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJF, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O’Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291966. [PMID: 37425772 PMCID: PMC10327287 DOI: 10.1101/2023.06.28.23291966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, 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
- Center for Computational Biology & Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jacob A. Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K. Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA
- Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E. Cade
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C. Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K. Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A. Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon LR. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N. Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G. Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth JF. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C. Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W. Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics and Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E. Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | | | - Jeffrey R. O’Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | | | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | | | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
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17
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Mattick JS, Amaral PP, Carninci P, Carpenter S, Chang HY, Chen LL, Chen R, Dean C, Dinger ME, Fitzgerald KA, Gingeras TR, Guttman M, Hirose T, Huarte M, Johnson R, Kanduri C, Kapranov P, Lawrence JB, Lee JT, Mendell JT, Mercer TR, Moore KJ, Nakagawa S, Rinn JL, Spector DL, Ulitsky I, Wan Y, Wilusz JE, Wu M. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat Rev Mol Cell Biol 2023; 24:430-447. [PMID: 36596869 PMCID: PMC10213152 DOI: 10.1038/s41580-022-00566-8] [Citation(s) in RCA: 426] [Impact Index Per Article: 426.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/16/2022] [Indexed: 01/05/2023]
Abstract
Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term 'lncRNAs' encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.
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Affiliation(s)
- John S Mattick
- School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW, Australia.
- UNSW RNA Institute, UNSW, Sydney, NSW, Australia.
| | - Paulo P Amaral
- INSPER Institute of Education and Research, São Paulo, Brazil
| | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Human Technopole, Milan, Italy
| | - Susan Carpenter
- Department of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamics Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Department of Dermatology, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Ling-Ling Chen
- CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Runsheng Chen
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Caroline Dean
- John Innes Centre, Norwich Research Park, Norwich, UK
| | - Marcel E Dinger
- School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW, Australia
- UNSW RNA Institute, UNSW, Sydney, NSW, Australia
| | - Katherine A Fitzgerald
- Division of Innate Immunity, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Mitchell Guttman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Tetsuro Hirose
- Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
| | - Maite Huarte
- Department of Gene Therapy and Regulation of Gene Expression, Center for Applied Medical Research, University of Navarra, Pamplona, Spain
- Institute of Health Research of Navarra, Pamplona, Spain
| | - Rory Johnson
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - Chandrasekhar Kanduri
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Philipp Kapranov
- Institute of Genomics, School of Medicine, Huaqiao University, Xiamen, China
| | - Jeanne B Lawrence
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Jeannie T Lee
- Department of Molecular Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Joshua T Mendell
- Howard Hughes Medical Institute, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Timothy R Mercer
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
| | - Kathryn J Moore
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Shinichi Nakagawa
- RNA Biology Laboratory, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan
| | - John L Rinn
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO, USA
- BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, USA
- Howard Hughes Medical Institute, University of Colorado Boulder, Boulder, CO, USA
| | - David L Spector
- Cold Spring Harbour Laboratory, Cold Spring Harbour, NY, USA
| | - Igor Ulitsky
- Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel
| | - Yue Wan
- Laboratory of RNA Genomics and Structure, Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Department of Biochemistry, National University of Singapore, Singapore, Singapore
| | - Jeremy E Wilusz
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Therapeutic Innovation Center, Baylor College of Medicine, Houston, TX, USA
| | - Mian Wu
- Translational Research Institute, Henan Provincial People's Hospital, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
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18
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Mattick JS. RNA out of the mist. Trends Genet 2023; 39:187-207. [PMID: 36528415 DOI: 10.1016/j.tig.2022.11.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 11/08/2022] [Accepted: 11/27/2022] [Indexed: 12/23/2022]
Abstract
RNA has long been regarded primarily as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences interrupted by large tracts of transcribed but untranslated sequences, and that multicellular organisms also express many long 'intergenic' and antisense noncoding RNAs (lncRNAs). The identification of small RNAs that regulate mRNA translation and half-life did not disturb the prevailing view that animals and plant genomes are full of evolutionary debris and that their development is mainly supervised by transcription factors. Gathering evidence to the contrary involved addressing the low conservation, expression, and genetic visibility of lncRNAs, demonstrating their cell-specific roles in cell and developmental biology, and their association with chromatin-modifying complexes and phase-separated domains. The emerging picture is that most lncRNAs are the products of genetic loci termed 'enhancers', which marshal generic effector proteins to their sites of action to control cell fate decisions during development.
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Affiliation(s)
- John S Mattick
- School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW 2052, Australia; UNSW RNA Institute, UNSW, Sydney, NSW 2052, Australia.
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19
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Corral A, Alcala M, Carmen Duran-Ruiz M, Arroba AI, Ponce-Gonzalez JG, Todorčević M, Serra D, Calderon-Dominguez M, Herrero L. Role of long non-coding RNAs in adipose tissue metabolism and associated pathologies. Biochem Pharmacol 2022; 206:115305. [DOI: 10.1016/j.bcp.2022.115305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 11/17/2022]
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20
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Duffy EE, Finander B, Choi G, Carter AC, Pritisanac I, Alam A, Luria V, Karger A, Phu W, Sherman MA, Assad EG, Pajarillo N, Khitun A, Crouch EE, Ganesh S, Chen J, Berger B, Sestan N, O'Donnell-Luria A, Huang EJ, Griffith EC, Forman-Kay JD, Moses AM, Kalish BT, Greenberg ME. Developmental dynamics of RNA translation in the human brain. Nat Neurosci 2022; 25:1353-1365. [PMID: 36171426 PMCID: PMC10198132 DOI: 10.1038/s41593-022-01164-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 08/12/2022] [Indexed: 01/27/2023]
Abstract
The precise regulation of gene expression is fundamental to neurodevelopment, plasticity and cognitive function. Although several studies have profiled transcription in the developing human brain, there is a gap in understanding of accompanying translational regulation. In this study, we performed ribosome profiling on 73 human prenatal and adult cortex samples. We characterized the translational regulation of annotated open reading frames (ORFs) and identified thousands of previously unknown translation events, including small ORFs that give rise to human-specific and/or brain-specific microproteins, many of which we independently verified using proteomics. Ribosome profiling in stem-cell-derived human neuronal cultures corroborated these findings and revealed that several neuronal activity-induced non-coding RNAs encode previously undescribed microproteins. Physicochemical analysis of brain microproteins identified a class of proteins that contain arginine-glycine-glycine (RGG) repeats and, thus, may be regulators of RNA metabolism. This resource expands the known translational landscape of the human brain and illuminates previously unknown brain-specific protein products.
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Affiliation(s)
- Erin E Duffy
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
| | | | - GiHun Choi
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Ava C Carter
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Iva Pritisanac
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON, Canada
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Aqsa Alam
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA, USA
| | - William Phu
- Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Maxwell A Sherman
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elena G Assad
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Naomi Pajarillo
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Alexandra Khitun
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Elizabeth E Crouch
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Sanika Ganesh
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jin Chen
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| | - Bonnie Berger
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Anne O'Donnell-Luria
- Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Eric J Huang
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Pathology Service 113B, San Francisco Veterans Affairs Healthcare System, San Francisco, CA, USA
| | - Eric C Griffith
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Julie D Forman-Kay
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON, Canada
| | - Alan M Moses
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
| | - Brian T Kalish
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
- Department of Paediatrics, Division of Neonatology, Hospital for Sick Children, Toronto, ON, Canada.
- Program in Neuroscience and Mental Health, SickKids Research Institute, Toronto, ON, Canada.
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21
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Palos K, Nelson Dittrich AC, Yu L, Brock JR, Railey CE, Wu HYL, Sokolowska E, Skirycz A, Hsu PY, Gregory BD, Lyons E, Beilstein MA, Nelson ADL. Identification and functional annotation of long intergenic non-coding RNAs in Brassicaceae. THE PLANT CELL 2022; 34:3233-3260. [PMID: 35666179 PMCID: PMC9421480 DOI: 10.1093/plcell/koac166] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 05/05/2022] [Indexed: 06/01/2023]
Abstract
Long intergenic noncoding RNAs (lincRNAs) are a large yet enigmatic class of eukaryotic transcripts that can have critical biological functions. The wealth of RNA-sequencing (RNA-seq) data available for plants provides the opportunity to implement a harmonized identification and annotation effort for lincRNAs that enables cross-species functional and genomic comparisons as well as prioritization of functional candidates. In this study, we processed >24 Tera base pairs of RNA-seq data from >16,000 experiments to identify ∼130,000 lincRNAs in four Brassicaceae: Arabidopsis thaliana, Camelina sativa, Brassica rapa, and Eutrema salsugineum. We used nanopore RNA-seq, transcriptome-wide structural information, peptide data, and epigenomic data to characterize these lincRNAs and identify conserved motifs. We then used comparative genomic and transcriptomic approaches to highlight lincRNAs in our data set with sequence or transcriptional conservation. Finally, we used guilt-by-association analyses to assign putative functions to lincRNAs within our data set. We tested this approach on a subset of lincRNAs associated with germination and seed development, observing germination defects for Arabidopsis lines harboring T-DNA insertions at these loci. LincRNAs with Brassicaceae-conserved putative miRNA binding motifs, small open reading frames, or abiotic-stress modulated expression are a few of the annotations that will guide functional analyses into this cryptic portion of the transcriptome.
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Affiliation(s)
- Kyle Palos
- The Boyce Thompson Institute, Cornell University, Ithaca, New York, USA
| | | | - Li’ang Yu
- The Boyce Thompson Institute, Cornell University, Ithaca, New York, USA
| | - Jordan R Brock
- Department of Horticulture, Michigan State University, East Lansing, Michigan, USA
| | - Caylyn E Railey
- The Boyce Thompson Institute, Cornell University, Ithaca, New York, USA
| | - Hsin-Yen Larry Wu
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA
| | | | | | - Polly Yingshan Hsu
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA
| | - Brian D Gregory
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Eric Lyons
- The School of Plant Sciences, University of Arizona, Tucson, Arizona, USA
| | - Mark A Beilstein
- The School of Plant Sciences, University of Arizona, Tucson, Arizona, USA
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22
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Bukhari I, Khan MR, Hussain MA, Thorne RF, Yu Y, Zhang B, Zheng P, Mi Y. PINTology: A short history of the lncRNA LINC-PINT in different diseases. WILEY INTERDISCIPLINARY REVIEWS. RNA 2022; 13:e1705. [PMID: 35019222 DOI: 10.1002/wrna.1705] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/09/2021] [Accepted: 11/17/2021] [Indexed: 12/24/2022]
Abstract
LINC-PINT is a p53-induced long intergenic noncoding transcript that plays a crucial role in many diseases, especially cancer. This long noncoding RNA (lncRNA) gene produces in total 102 (LNCipedia) alternatively spliced variants (LINC-PINT:1 to LINC-PINT:102). The functions of known variants include RNA transcripts, host transcripts for circular RNA (circRNA) generation and as sources for the translation of short peptides. In most human tumors, LINC-PINT is down-regulated where it serves as a tumor suppressor. However, the diversity of its functions in other maladies signifies its general clinical importance. Current LINC-PINT molecular functions include RNA-protein interactions, miRNA sponging and epigenetic modulation with these mechanisms operating in different cellular contexts to exert effects on biological processes ranging from DNA damage responses, cell cycle and growth arrest, senescence, cell migration and invasion, and apoptosis. Genetic polymorphisms in LINC-PINT have also been functionally associated with cancer and other pathologies including the autoimmune diseases pemphigus foliaceus and arthritis. Hence, LINC-PINT shows great potential as a clinical biomarker, especially for the diagnosis and prognosis of cancer. In this review, we explore the current knowledge highlighting the distinctive molecular functions of LINC-PINT in specific cancers and other disease states. This article is categorized under: RNA in Disease and Development > RNA in Disease.
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Affiliation(s)
- Ihtisham Bukhari
- Henan Key Laboratory of Helicobacter pylori, Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Department of Gastroenterology, Fifth Affiliated hospital of Zhengzhou University, Zhengzhou, China
| | - Muhammad Riaz Khan
- Research Center on Aging, Centre Intégré Universitaire de Santé et Services Sociaux de l'Estrie - Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada.,Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Mohammed Amir Hussain
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.,Département de Médecine, Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Rick Francis Thorne
- Translational Research Institute, Henan Provincial People's Hospital, School of Clinical Medicine, Henan University, Zhengzhou, China.,School of Environmental & Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Yong Yu
- Henan Key Laboratory of Helicobacter pylori, Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Department of Gastroenterology, Fifth Affiliated hospital of Zhengzhou University, Zhengzhou, China
| | - Bingyong Zhang
- Department of Gastroenterology, Henan Provincial People's Hospital, School of Clinical Medicine, Henan University, Zhengzhou, China
| | - Pengyuan Zheng
- Henan Key Laboratory of Helicobacter pylori, Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Department of Gastroenterology, Fifth Affiliated hospital of Zhengzhou University, Zhengzhou, China
| | - Yang Mi
- Henan Key Laboratory of Helicobacter pylori, Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Department of Gastroenterology, Fifth Affiliated hospital of Zhengzhou University, Zhengzhou, China
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23
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Haimbaugh A, Akemann C, Meyer D, Gurdziel K, Baker TR. Insight into 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced disruption of zebrafish spermatogenesis via single cell RNA-seq. PNAS NEXUS 2022; 1:pgac060. [PMID: 35799832 PMCID: PMC9252172 DOI: 10.1093/pnasnexus/pgac060] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 06/17/2022] [Indexed: 02/05/2023]
Abstract
2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a potent and environmentally persistent endocrine disrupting chemical. Our previous work demonstrated the latent reproductive maladies of early-life TCDD exposure in zebrafish. Zebrafish acutely exposed to low, environmentally relevant levels of TCDD (50 pg/mL) during two windows of sexual differentiation in development (1 hour of exposure at 3 and 7 weeks postfertilization) were later infertile, showed a reduction in sperm, and exhibited gene expression consistent with an altered microenvironment, even months after exposure. Due to the highly heterogeneous cell- type and -stage landscape of the testes, we hypothesized various cell types contribute markedly different profiles toward the pathology of TCDD exposure. To investigate the contributions of the diverse cell types in the adult zebrafish testes to TCDD-induced pathology, we utilized single-cell RNA-seq and the 10x Genomics platform. The method successfully captured every stage of testicular germ cell development. Testes of adult fish exposed during sexual differentiation to TCDD contained sharply decreased populations of late spermatocytes, spermatids, and spermatozoa. Spermatogonia and early spermatocyte populations were, in contrast, enriched following exposure. Pathway analysis of differentially expressed genes supported previous findings that TCDD exposure resulted in male infertility, and suggested this outcome is due to apoptosis of spermatids and spermatozoa, even years after exposure cessation. Increased germ cell apoptosis was confirmed histologically. These results provide support for an environmental exposure explanation of idiopathic male infertility.
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Affiliation(s)
- Alex Haimbaugh
- Department of Pharmacology, School of Medicine, Wayne State University, Detroit, MI 48207, USA
| | - Camille Akemann
- Department of Pharmacology, School of Medicine, Wayne State University, Detroit, MI 48207, USA
| | - Danielle Meyer
- Department of Pharmacology, School of Medicine, Wayne State University, Detroit, MI 48207, USA
| | - Katherine Gurdziel
- Applied Genome Technology Center, School of Medicine, Wayne State University, Detroit, MI 48207, USA
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24
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Pulido-Quetglas C, Johnson R. Designing libraries for pooled CRISPR functional screens of long noncoding RNAs. Mamm Genome 2022; 33:312-327. [PMID: 34533605 PMCID: PMC9114037 DOI: 10.1007/s00335-021-09918-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 09/09/2021] [Indexed: 02/01/2023]
Abstract
Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.
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Affiliation(s)
- Carlos Pulido-Quetglas
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, 3012, Bern, Switzerland
| | - Rory Johnson
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland.
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland.
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland.
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25
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Zhang YY, Zhang WY, Xin XH, Du PF. dbEssLnc: A manually curated database of human and mouse essential lncRNA genes. Comput Struct Biotechnol J 2022; 20:2657-2663. [PMID: 35685362 PMCID: PMC9162909 DOI: 10.1016/j.csbj.2022.05.043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/20/2022] [Accepted: 05/21/2022] [Indexed: 02/07/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) play important roles in many biological processes. Knocking out or knocking down some lncRNAs will lead to lethality or infertility. These lncRNAs are called essential lncRNAs. Knowledges of essential lncRNAs are important in establishing minimal genomes of living cells, developing drug therapies and early diagnostic approaches for complex diseases. However, existing databases focus on collecting essential coding genes. Essential non-coding gene records are rare in existing databases. A comprehensive collection of essential non-coding genes, particularly essential lncRNA genes, is demanded. We manually curated 207 essential lncRNAs from literatures for establishing a database on essential lncRNAs, which is named as dbEssLnc (Database of essential lncRNAs). The dbEssLnc database has a web-based user-friendly interface for the users to browse, to search, to visualize and to blast search records in the database. The dbEssLnc database is freely accessible at https://esslnc.pufengdu.org. All data and source codes for mirroring the dbEssLnc database have been deposited in GitHub (https://github.com/yyZhang14/dbEssLnc).
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Affiliation(s)
- Ying-Ying Zhang
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
| | - Wen-Ya Zhang
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
| | - Xiao-Hong Xin
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
| | - Pu-Feng Du
- College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
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26
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Ilieva M, Uchida S. Long Non-Coding RNAs in Induced Pluripotent Stem Cells and Their Differentiation. Am J Physiol Cell Physiol 2022; 322:C769-C774. [PMID: 35235428 DOI: 10.1152/ajpcell.00059.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The breakthrough technology for reprogramming somatic cells into induced pluripotent stem cells (iPSC) has created a new path for science and medicine. The iPSC technology provides a powerful tool for elucidating the mechanisms of cellular differentiation and cell fate decision as well as to study targets and pathways relevant to pathological processes. Since they can be generated from any person, iPSC are a promising resource for regenerative medicine potentiating the possibility to discover new drugs in a high-throughput screening format and treat diseases through personalized cell therapy-based strategies. However, the reprogramming process is complex, and its regulation needs fine tuning. The regulatory mechanisms of cell reprogramming and differentiation are still not elucidated, but significant results show that multiple long non-coding RNAs (lncRNAs) play essential roles. In this mini review, we discuss the latest research on lncRNAs in iPSC stemness, neuronal and cardiac differentiation.
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Affiliation(s)
- Mirolyuba Ilieva
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, Copenhagen SV, Denmark
| | - Shizuka Uchida
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, Copenhagen SV, Denmark
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27
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Sideris N, Dama P, Bayraktar S, Stiff T, Castellano L. LncRNAs in breast cancer: a link to future approaches. Cancer Gene Ther 2022; 29:1866-1877. [PMID: 35788171 PMCID: PMC9750866 DOI: 10.1038/s41417-022-00487-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/06/2022] [Accepted: 05/27/2022] [Indexed: 01/25/2023]
Abstract
Breast cancer affects millions of women each year. Despite recent advances in targeted treatments breast cancer remains a significant threat to women's health. In recent years the development of high-throughput sequencing technologies has advanced the field of transcriptomics shedding light on the role of non-coding RNAs (ncRNAs), including long ncRNAs (lncRNAs), in human cellular function and disease. LncRNAs are classified as transcripts longer than 200nt with no coding potential. These transcripts constitute a diverse group of regulatory molecules essential to the modulation of crucial cellular processes, which dysregulation of leads to disease. LncRNAs exert their regulatory functions through their sequences and by forming complex secondary and tertiary structures that interact with other transcripts, chromatin and/or proteins. Numerous studies have provided evidence of the involvement of LncRNAs in tumor development and disease progression. They possess multiple characteristics that make them novel therapeutic and diagnostic targets. Indeed, the discovery of a novel mechanism by which lncRNAs associated with proteins can induce the formation of phase-separated droplets broadens our understanding of the spatiotemporal control of cellular processes and opens up developing a new treatment. Nevertheless, the role and the molecular mechanisms of many lncRNAs in the regulation of cellular processes and cancer still remain elusive. This is due to the absence of a thorough characterization of the regulatory role of their loci and the functional impact of their aberrations in cancer biology. Here, we present some of the latest advances concerning the role of LncRNAs in breast cancer.
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Affiliation(s)
- Nikolaos Sideris
- grid.12082.390000 0004 1936 7590Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG UK
| | - Paola Dama
- grid.12082.390000 0004 1936 7590Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG UK
| | - Salih Bayraktar
- grid.12082.390000 0004 1936 7590Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG UK
| | - Thomas Stiff
- grid.12082.390000 0004 1936 7590Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG UK
| | - Leandro Castellano
- grid.12082.390000 0004 1936 7590Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG UK ,grid.7445.20000 0001 2113 8111Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ UK
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28
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Abstract
Although long noncoding RNAs (lncRNAs) are generally expressed at low levels, emerging evidence has revealed that many play important roles in gene regulation by a variety of mechanisms as they engage with proteins. Given that the abundance of proteins often greatly exceeds that of their interacting lncRNAs, quantification of the relative abundance, or even the exact stoichiometry in some cases, within lncRNA-protein complexes is helpful for understanding of the mechanism(s) of action of lncRNAs. We discuss methods used to examine lncRNA and protein expression at the single cell, subcellular, and suborganelle levels, the average and local lncRNA concentration in cells, as well as how lncRNAs can modulate the functions of their interacting proteins even at a low stoichiometric concentration.
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Affiliation(s)
- Man Wu
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Liang-Zhong Yang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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29
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The role of long non-coding RNAs in the regulation of pancreatic beta cell identity. Biochem Soc Trans 2021; 49:2153-2161. [PMID: 34581756 PMCID: PMC8589412 DOI: 10.1042/bst20210207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 09/02/2021] [Accepted: 09/08/2021] [Indexed: 12/29/2022]
Abstract
Type 2 diabetes (T2D) is a widespread disease affecting millions in every continental population. Pancreatic β-cells are central to the regulation of circulating glucose, but failure in the maintenance of their mass and/or functional identity leads to T2D. Long non-coding RNAs (lncRNAs) represent a relatively understudied class of transcripts which growing evidence implicates in diabetes pathogenesis. T2D-associated single nucleotide polymorphisms (SNPs) have been identified in lncRNA loci, although these appear to function primarily through regulating β-cell proliferation. In the last decade, over 1100 lncRNAs have been catalogued in islets and the roles of a few have been further investigated, definitively linking them to β-cell function. These studies show that lncRNAs can be developmentally regulated and show highly tissue-specific expression. lncRNAs regulate neighbouring β-cell-specific transcription factor expression, with knockdown or overexpression of lncRNAs impacting a network of other key genes and pathways. Finally, gene expression analysis in studies of diabetic models have uncovered a number of lncRNAs with roles in β-cell function. A deeper understanding of these lncRNA roles in maintaining β-cell identity, and its deterioration, is required to fully appreciate the β-cell molecular network and to advance novel diabetes treatments.
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30
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Micheel J, Safrastyan A, Wollny D. Advances in Non-Coding RNA Sequencing. Noncoding RNA 2021; 7:70. [PMID: 34842804 PMCID: PMC8628893 DOI: 10.3390/ncrna7040070] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/22/2021] [Accepted: 10/26/2021] [Indexed: 12/11/2022] Open
Abstract
Non-coding RNAs (ncRNAs) comprise a set of abundant and functionally diverse RNA molecules. Since the discovery of the first ncRNA in the 1960s, ncRNAs have been shown to be involved in nearly all steps of the central dogma of molecular biology. In recent years, the pace of discovery of novel ncRNAs and their cellular roles has been greatly accelerated by high-throughput sequencing. Advances in sequencing technology, library preparation protocols as well as computational biology helped to greatly expand our knowledge of which ncRNAs exist throughout the kingdoms of life. Moreover, RNA sequencing revealed crucial roles of many ncRNAs in human health and disease. In this review, we discuss the most recent methodological advancements in the rapidly evolving field of high-throughput sequencing and how it has greatly expanded our understanding of ncRNA biology across a large number of different organisms.
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Affiliation(s)
| | | | - Damian Wollny
- RNA Bioinformatics/High Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University, 07743 Jena, Germany; (J.M.); (A.S.)
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31
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Long non-coding RNAs associated with infection and vaccine-induced immunity. Essays Biochem 2021; 65:657-669. [PMID: 34528687 DOI: 10.1042/ebc20200072] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 08/01/2021] [Accepted: 08/10/2021] [Indexed: 12/31/2022]
Abstract
The immune system responds to infection or vaccination through a dynamic and complex process that involves several molecular and cellular factors. Among these factors, long non-coding RNAs (lncRNAs) have emerged as significant players in all areas of biology, particularly in immunology. Most of the mammalian genome is transcribed in a highly regulated manner, generating a diversity of lncRNAs that impact the differentiation and activation of immune cells and affect innate and adaptive immunity. Here, we have reviewed the range of functions and mechanisms of lncRNAs in response to infectious disease, including pathogen recognition, interferon (IFN) response, and inflammation. We describe examples of lncRNAs exploited by pathogenic agents during infection, which indicate that lncRNAs are a fundamental part of the arms race between hosts and pathogens. We also discuss lncRNAs potentially implicated in vaccine-induced immunity and present examples of lncRNAs associated with the antibody response of subjects receiving Influenza or Yellow Fever vaccines. Elucidating the widespread involvement of lncRNAs in the immune system will improve our understanding of the factors affecting immune response to different pathogenic agents, to better prevent and treat disease.
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32
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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: 3] [Impact Index Per Article: 1.0] [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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33
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Ruan X, Li P, Ma Y, Jiang CF, Chen Y, Shi Y, Gupta N, Seifuddin F, Pirooznia M, Ohnishi Y, Yoneda N, Nishiwaki M, Dumbovic G, Rinn JL, Higuchi Y, Kawai K, Suemizu H, Cao H. Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis. J Clin Invest 2021; 131:136336. [PMID: 33048844 DOI: 10.1172/jci136336] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 10/09/2020] [Indexed: 12/11/2022] Open
Abstract
A growing number of long noncoding RNAs (lncRNAs) have emerged as vital metabolic regulators. However, most human lncRNAs are nonconserved and highly tissue specific, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). In this study, we established a pipeline to identify putative hLMRs that are metabolically sensitive, disease relevant, and population applicable. We first progressively processed multilevel human transcriptome data to select liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a nonalcoholic fatty liver disease (NAFLD) population, and respond to dietary intervention in a small NAFLD cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and NAFLD populations, we predicted the specific function for each hLMR. Using gain- and loss-of-function approaches in humanized mice as well as ectopic expression in conventional mice, we validated the regulatory role of one nonconserved hLMR in cholesterol metabolism by coordinating with an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. Our work overcame the heterogeneity intrinsic to human data to enable the efficient identification and functional definition of disease-relevant human lncRNAs in metabolic homeostasis.
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Affiliation(s)
- Xiangbo Ruan
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Ping Li
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Yonghe Ma
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Cheng-Fei Jiang
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Yi Chen
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Yu Shi
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Nikhil Gupta
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Fayaz Seifuddin
- Bioinformatics and Computational Biology, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Mehdi Pirooznia
- Bioinformatics and Computational Biology, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Yasuyuki Ohnishi
- Laboratory Animal Research Department, Biomedical Research Laboratory, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Nao Yoneda
- Laboratory Animal Research Department, Biomedical Research Laboratory, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Megumi Nishiwaki
- Laboratory Animal Research Department, Biomedical Research Laboratory, Central Institute for Experimental Animals, Kawasaki, Japan.,Technical Service Department, CLEA Japan Inc., Shizuoka, Japan
| | - Gabrijela Dumbovic
- Department of Biochemistry and BioFrontiers, University of Colorado Boulder, Boulder, Colorado, USA
| | - John L Rinn
- Department of Biochemistry and BioFrontiers, University of Colorado Boulder, Boulder, Colorado, USA
| | - Yuichiro Higuchi
- Laboratory Animal Research Department, Biomedical Research Laboratory, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Kenji Kawai
- Department Pathology Analysis Center, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Hiroshi Suemizu
- Laboratory Animal Research Department, Biomedical Research Laboratory, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Haiming Cao
- Cardiovascular Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
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34
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Abstract
The world of long non-coding RNAs (lncRNAs) has opened up massive new prospects in understanding the regulation of gene expression. Not only are there seemingly almost infinite numbers of lncRNAs in the mammalian cell, but they have highly diverse mechanisms of action. In the nucleus, some are chromatin-associated, transcribed from transcriptional enhancers (eRNAs) and/or direct changes in the epigenetic landscape with profound effects on gene expression. The pituitary gonadotrope is responsible for activation of reproduction through production and secretion of appropriate levels of the gonadotropic hormones. As such, it exemplifies a cell whose function is defined through changes in developmental and temporal patterns of gene expression, including those that are hormonally induced. Roles for diverse distal regulatory elements and eRNAs in gonadotrope biology have only just begun to emerge. Here, we will present an overview of the different kinds of lncRNAs that alter gene expression, and what is known about their roles in regulating some of the key gonadotrope genes. We will also review various screens that have detected differentially expressed pituitary lncRNAs associated with changes in reproductive state and those whose expression is found to play a role in gonadotrope-derived nonfunctioning pituitary adenomas. We hope to shed light on this exciting new field, emphasize the open questions, and encourage research to illuminate the roles of lncRNAs in various endocrine systems.
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Affiliation(s)
- Tal Refael
- Faculty of Biology, Technion Israel Institute of Technology, Haifa 32000, Israel
| | - Philippa Melamed
- Faculty of Biology, Technion Israel Institute of Technology, Haifa 32000, Israel
- Correspondence: Philippa Melamed, PhD, Faculty of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel.
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35
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Chowdhary A, Satagopam V, Schneider R. Long Non-coding RNAs: Mechanisms, Experimental, and Computational Approaches in Identification, Characterization, and Their Biomarker Potential in Cancer. Front Genet 2021; 12:649619. [PMID: 34276764 PMCID: PMC8281131 DOI: 10.3389/fgene.2021.649619] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/20/2021] [Indexed: 01/09/2023] Open
Abstract
Long non-coding RNAs are diverse class of non-coding RNA molecules >200 base pairs of length having various functions like gene regulation, dosage compensation, epigenetic regulation. Dysregulation and genomic variations of several lncRNAs have been implicated in several diseases. Their tissue and developmental specific expression are contributing factors for them to be viable indicators of physiological states of the cells. Here we present an comprehensive review the molecular mechanisms and functions, state of the art experimental and computational pipelines and challenges involved in the identification and functional annotation of lncRNAs and their prospects as biomarkers. We also illustrate the application of co-expression networks on the TCGA-LIHC dataset for putative functional predictions of lncRNAs having a therapeutic potential in Hepatocellular carcinoma (HCC).
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Affiliation(s)
- Anshika Chowdhary
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Venkata Satagopam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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36
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Abstract
BACKGROUND Long non-coding RNAs (lncRNAs) have evolved as a critical regulatory mechanism for almost all biological processes. By dynamically interacting with their molecular partners, lncRNAs regulate gene activity at multiple levels ranging from transcription, pre-mRNA splicing, RNA transporting, RNA decay, and translation of mRNA. RESULTS AND CONCLUSIONS Dysregulation of lncRNAs has been associated with human diseases, including cancer, neurodegenerative, and cardiometabolic diseases. However, as lncRNAs are usually much less conserved than mRNAs at the sequence level, most human lncRNAs are either primate or human specific. The pathophysiological significance of human lncRNAs is still mostly unclear due to the persistent limitations in studying human-specific genes. This review will focus on recent discoveries showing human lncRNAs' roles in regulating metabolic homeostasis and the potential of targeting this unique group of genes for treatment of cardiometabolic diseases.
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Affiliation(s)
- Xiangbo Ruan
- Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
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37
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Lu H, Zhang J, Chen YE, Garcia-Barrio MT. Integration of Transformative Platforms for the Discovery of Causative Genes in Cardiovascular Diseases. Cardiovasc Drugs Ther 2021; 35:637-654. [PMID: 33856594 DOI: 10.1007/s10557-021-07175-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/18/2021] [Indexed: 12/11/2022]
Abstract
Cardiovascular diseases are the leading cause of morbidity and mortality worldwide. Genome-wide association studies (GWAS) are powerful epidemiological tools to find genes and variants associated with cardiovascular diseases while follow-up biological studies allow to better understand the etiology and mechanisms of disease and assign causality. Improved methodologies and reduced costs have allowed wider use of bulk and single-cell RNA sequencing, human-induced pluripotent stem cells, organoids, metabolomics, epigenomics, and novel animal models in conjunction with GWAS. In this review, we feature recent advancements relevant to cardiovascular diseases arising from the integration of genetic findings with multiple enabling technologies within multidisciplinary teams to highlight the solidifying transformative potential of this approach. Well-designed workflows integrating different platforms are greatly improving and accelerating the unraveling and understanding of complex disease processes while promoting an effective way to find better drug targets, improve drug design and repurposing, and provide insight towards a more personalized clinical practice.
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Affiliation(s)
- Haocheng Lu
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA
| | - Jifeng Zhang
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA.,Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, Ann Arbor, MI, 48109, USA
| | - Y Eugene Chen
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA. .,Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, Ann Arbor, MI, 48109, USA.
| | - Minerva T Garcia-Barrio
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA.
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Johannsen EB, Baughn LB, Sharma N, Zjacic N, Pirooznia M, Elhaik E. The Genetics of Sudden Infant Death Syndrome-Towards a Gene Reference Resource. Genes (Basel) 2021; 12:216. [PMID: 33540853 PMCID: PMC7913088 DOI: 10.3390/genes12020216] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 01/21/2021] [Accepted: 01/29/2021] [Indexed: 12/16/2022] Open
Abstract
Sudden infant death syndrome (SIDS) is the unexpected death of an infant under one year of age that remains unexplained after a thorough investigation. Despite SIDS remaining a diagnosis of exclusion with an unexplained etiology, it is widely accepted that SIDS can be caused by environmental and/or biological factors, with multiple underlying candidate genes. However, the lack of biomarkers raises questions as to why genetic studies on SIDS to date are unable to provide a clearer understanding of the disease etiology. We sought to improve the identification of SIDS-associated genes by reviewing the SIDS genetic literature and objectively categorizing and scoring the reported genes based on the strength of evidence (from C1 (high) to C5 (low)). This was followed by analyses of function, associations between genes, the enrichment of gene ontology (GO) terms, and pathways and gender difference in tissue gene expression. We constructed a curated database for SIDS gene candidates consisting of 109 genes, 14 of which received a category 4 (C4) and 95 genes received the lowest category of C5. That none of the genes was classified into the higher categories indicates the low level of supporting evidence. We found that genes of both scoring categories show distinct networks and are highly diverse in function and involved in many GO terms and pathways, in agreement with the perception of SIDS as a heterogeneous syndrome. Genes of both scoring categories are part of the cardiac system, muscle, and ion channels, whereas immune-related functions showed enrichment for C4 genes. A limited association was found with neural development. Overall, inconsistent reports and missing metadata contribute to the ambiguity of genetic studies. Considering those parameters could help improve the identification of at-risk SIDS genes. However, the field is still far from offering a full-pledged genetic test to identify at-risk infants and is still hampered with methodological challenges and misunderstandings of the vulnerabilities of vital biological mechanisms.
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Affiliation(s)
| | - Linda B. Baughn
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; (L.B.B.); (N.S.)
| | - Neeraj Sharma
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; (L.B.B.); (N.S.)
| | - Nicolina Zjacic
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK;
| | - Mehdi Pirooznia
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Eran Elhaik
- Department of Biology, Lund University, 22362 Lund, Sweden;
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