1
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Guo B, Li W, Liu Y, Xu D, Liu Z, Huang C. Aberrant Expressional Profiling of Small RNA by Cold Atmospheric Plasma Treatment in Human Chronic Myeloid Leukemia Cells. Front Genet 2022; 12:809658. [PMID: 35186012 PMCID: PMC8851033 DOI: 10.3389/fgene.2021.809658] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/23/2021] [Indexed: 12/15/2022] Open
Abstract
Small RNAs (sRNAs), particularly microRNAs (miRNAs), are functional molecules that modulate mRNA transcripts and have been implicated in the etiology of various types of cancer. Cold atmospheric plasma (CAP) is a physical technology widely used in the field of cancer treatment after exhibiting extensive lethality on cancer cells. However, few studies have reported the exact role of miRNAs in CAP-induced anti-cancer effects. The aim of the present study was to determine whether miRNAs are involved in CAP-induced cytotoxicity by using high-throughput sequencing. Our research demonstrated that 28 miRNAs were significantly changed (17 upregulated and 11downregulated) following 24 h of treatment with a room-temperature argon plasma jet for 90 s compared with that of the untreated group in human chronic myeloid leukemia K562 cells. GO enrichment analysis revealed that these target genes were related to cell organelles, protein binding, and single-organism processes. Furthermore, KEGG pathway analysis demonstrated that the target genes of differentially expressed miRNAs were primarily involved in the cAMP signaling pathway, AMPK signaling pathway, and phosphatidylinositol signaling system. Taken together, our study demonstrated that CAP treatment could significantly alter the small RNA expression profile of chronic myeloid leukemia cells and provide a novel theoretical insight for elucidating the molecular mechanisms in CAP biomedicine application.
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Affiliation(s)
- Bo Guo
- Department of Cell Biology and Genetics/Key Laboratory of Environment and Genes Related to Diseases, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
- Institute of Genetics and Developmental Biology, Translational Medicine Institute, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Wen Li
- Department of Cell Biology and Genetics/Key Laboratory of Environment and Genes Related to Diseases, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
- Institute of Genetics and Developmental Biology, Translational Medicine Institute, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Yijie Liu
- Department of Cell Biology and Genetics/Key Laboratory of Environment and Genes Related to Diseases, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
- Institute of Genetics and Developmental Biology, Translational Medicine Institute, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Dehui Xu
- State Key Laboratory of Electrical Insulation and Power Equipment, Centre for Plasma Biomedicine, Xi’an Jiaotong University, Xi’an, China
| | - Zhijie Liu
- State Key Laboratory of Electrical Insulation and Power Equipment, Centre for Plasma Biomedicine, Xi’an Jiaotong University, Xi’an, China
| | - Chen Huang
- Department of Cell Biology and Genetics/Key Laboratory of Environment and Genes Related to Diseases, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
- Institute of Genetics and Developmental Biology, Translational Medicine Institute, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, China
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Xi’an, China
- *Correspondence: Chen Huang,
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2
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Rodríguez‐Barrueco R, Latorre J, Devis‐Jáuregui L, Lluch A, Bonifaci N, Llobet FJ, Olivan M, Coll‐Iglesias L, Gassner K, Davis ML, Moreno‐Navarrete JM, Castells‐Nobau A, Plata‐Peña L, Dalmau‐Pastor M, Höring M, Liebisch G, Olkkonen VM, Arnoriaga‐Rodríguez M, Ricart W, Fernández‐Real JM, Silva JM, Ortega FJ, Llobet‐Navas D. A microRNA Cluster Controls Fat Cell Differentiation and Adipose Tissue Expansion By Regulating SNCG. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2104759. [PMID: 34898027 PMCID: PMC8811811 DOI: 10.1002/advs.202104759] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Indexed: 05/08/2023]
Abstract
The H19X-encoded miR-424(322)/503 cluster regulates multiple cellular functions. Here, it is reported for the first time that it is also a critical linchpin of fat mass expansion. Deletion of this miRNA cluster in mice results in obesity, while increasing the pool of early adipocyte progenitors and hypertrophied adipocytes. Complementary loss and gain of function experiments and RNA sequencing demonstrate that miR-424(322)/503 regulates a conserved genetic program involved in the differentiation and commitment of white adipocytes. Mechanistically, it is demonstrated that miR-424(322)/503 targets γ-Synuclein (SNCG), a factor that mediates this program rearrangement by controlling metabolic functions in fat cells, allowing adipocyte differentiation and adipose tissue enlargement. Accordingly, diminished miR-424(322) in mice and obese humans co-segregate with increased SNCG in fat and peripheral blood as mutually exclusive features of obesity, being normalized upon weight loss. The data unveil a previously unknown regulatory mechanism of fat mass expansion tightly controlled by the miR-424(322)/503 through SNCG.
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Affiliation(s)
- Ruth Rodríguez‐Barrueco
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Anatomy UnitDepartment of Pathology and Experimental TherapySchool of MedicineUniversity of Barcelona (UB)L'Hospitalet de Llobregat08907Spain
| | - Jessica Latorre
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Laura Devis‐Jáuregui
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
| | - Aina Lluch
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
| | - Nuria Bonifaci
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC)Instituto de Salud Carlos III, (ISCIII)Madrid28029Spain
| | - Francisco J. Llobet
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
| | - Mireia Olivan
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Anatomy UnitDepartment of Pathology and Experimental TherapySchool of MedicineUniversity of Barcelona (UB)L'Hospitalet de Llobregat08907Spain
| | - Laura Coll‐Iglesias
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
| | - Katja Gassner
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC)Instituto de Salud Carlos III, (ISCIII)Madrid28029Spain
| | - Meredith L. Davis
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Department of PathologyDuke University School of MedicineDurhamNC27710USA
| | - José M. Moreno‐Navarrete
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Anna Castells‐Nobau
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
| | - Laura Plata‐Peña
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
| | - Miki Dalmau‐Pastor
- Anatomy UnitDepartment of Pathology and Experimental TherapySchool of MedicineUniversity of Barcelona (UB)L'Hospitalet de Llobregat08907Spain
- MIFAS by GRECMIP (Minimally Invasive Foot and Ankle Society)Merignac33700France
| | - Marcus Höring
- Institute of Clinical Chemistry and Laboratory MedicineRegensburg University HospitalRegensburg93053Germany
| | - Gerhard Liebisch
- Institute of Clinical Chemistry and Laboratory MedicineRegensburg University HospitalRegensburg93053Germany
| | - Vesa M. Olkkonen
- Minerva Foundation Institute for Medical Research (Biomedicum 2U)and Department of AnatomyFaculty of MedicineUniversity of HelsinkiHelsinki00290Finland
| | - Maria Arnoriaga‐Rodríguez
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - Wifredo Ricart
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - José M. Fernández‐Real
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - José M. Silva
- Department of PathologyIcahn School of Medicine at Mount SinaiNew YorkNY10029USA
| | - Francisco J. Ortega
- Department of DiabetesEndocrinology, and Nutrition (UDEN)Institut d'Investigació Biomèdica de Girona (IDIBGI)Salt17190Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos III (ISCIII)Madrid28029Spain
| | - David Llobet‐Navas
- Molecular Mechanisms and Experimental Therapy in Oncology‐Oncobell ProgramBellvitge Biomedical Research Institute (IDIBELL)L'Hospitalet de Llobregat08908Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC)Instituto de Salud Carlos III, (ISCIII)Madrid28029Spain
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3
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Sonehara K, Sakaue S, Maeda Y, Hirata J, Kishikawa T, Yamamoto K, Matsuoka H, Yoshimura M, Nii T, Ohshima S, Kumanogoh A, Okada Y. Genetic architecture of microRNA expression and its link to complex diseases in the Japanese population. Hum Mol Genet 2021; 31:1806-1820. [PMID: 34919704 PMCID: PMC9169454 DOI: 10.1093/hmg/ddab361] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 10/04/2021] [Accepted: 11/23/2021] [Indexed: 11/13/2022] Open
Abstract
Understanding the genetic effects on non-coding RNA (ncRNA) expression facilitates functional characterization of disease-associated genetic loci. Among several classes of ncRNAs, microRNAs (miRNAs) are key post-transcriptional gene regulators. Despite its biological importance, previous studies on the genetic architecture of miRNA expression focused mostly on the European individuals, underrepresented in other populations. Here, we mapped miRNA expression quantitative trait loci (miRNA-eQTL) for 343 miRNAs in 141 Japanese using small RNA sequencing (sRNA-seq) and whole-genome sequencing (WGS), identifying 1275 cis-miRNA-eQTL variants for 40 miRNAs (false discovery rate < 0.2). Of these, 25 miRNAs having eQTL were unreported in the European studies, including 5 miRNAs with their lead variant monomorphic in the European populations, which demonstrates the value of miRNA-eQTL analysis in diverse ancestral populations. MiRNAs with eQTL effect showed allele-specific expression (ASE) (e.g. miR-146a-3p), and ASE analysis further detected cis-regulatory variants not captured by the conventional miRNA-eQTL mapping (e.g. miR-933). We identified a copy number variation (CNV) associated with miRNA expression (e.g. miR-570-3p, P = 7.2 × 10-6), which contributes to a more comprehensive landscape of miRNA-eQTLs. To elucidate a post-transcriptional modification in miRNAs, we created a catalog of miRNA-editing sites, including ten canonical and six non-canonical sites. Finally, by integrating the miRNA-eQTLs and Japanese genome-wide association studies of 25 complex traits (mean n = 192 833), we conducted a transcriptome-wide association study (TWAS), identifying miR-1908-5p as a potential mediator for adult height, colorectal cancer, and type 2 diabetes (P < 9.1 × 10-5). Our study broadens the population diversity in ncRNA-eQTL studies and contributes to functional annotation of disease-associated loci found in non-European populations.
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Affiliation(s)
- Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, 565-0871, Japan
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Center for Data Sciences, Harvard Medical School, Boston, MA, 02114, USA.,Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA.,Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yuichi Maeda
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, 565-0871, Japan.,Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Jun Hirata
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Pharmaceutical Discovery Research Laboratories, Teijin Pharma Limited, Hino, 191-8512, Japan
| | - Toshihiro Kishikawa
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Department of Otorhinolaryngology - Head and Neck Surgery, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Department of Head and Neck Surgery, Aichi Cancer Center Hospital, Nagoya, 464-8681, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Japan
| | - Hidetoshi Matsuoka
- Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano, 586-8521, Japan
| | - Maiko Yoshimura
- Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano, 586-8521, Japan
| | - Takuro Nii
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Shiro Ohshima
- Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano, 586-8521, Japan
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, 565-0871, Japan.,Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.,Department of Immunopathology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, 565-0871, Japan.,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Japan.,The Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, 565-0871, Japan.,Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
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4
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Nilsson E, Vavakova M, Perfilyev A, Säll J, Jansson PA, Poulsen P, Esguerra JLS, Eliasson L, Vaag A, Göransson O, Ling C. Differential DNA Methylation and Expression of miRNAs in Adipose Tissue From Twin Pairs Discordant for Type 2 Diabetes. Diabetes 2021; 70:2402-2418. [PMID: 34315727 DOI: 10.2337/db20-0324] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 07/21/2021] [Indexed: 11/13/2022]
Abstract
The prevalence of type 2 diabetes (T2D) is increasing worldwide, but current treatments have limitations. miRNAs may play a key role in the development of T2D and can be targets for novel therapies. Here, we examined whether T2D is associated with altered expression and DNA methylation of miRNAs using adipose tissue from 14 monozygotic twin pairs discordant for T2D. Four members each of the miR-30 and let-7-families were downregulated in adipose tissue of subjects with T2D versus control subjects, which was confirmed in an independent T2D case-control cohort. Further, DNA methylation of five CpG sites annotated to gene promoters of differentially expressed miRNAs, including miR-30a and let-7a-3, was increased in T2D versus control subjects. Luciferase experiments showed that increased DNA methylation of the miR-30a promoter reduced its transcription in vitro. Silencing of miR-30 in adipocytes resulted in reduced glucose uptake and TBC1D4 phosphorylation; downregulation of genes involved in demethylation and carbohydrate/lipid/amino acid metabolism; and upregulation of immune system genes. In conclusion, T2D is associated with differential DNA methylation and expression of miRNAs in adipose tissue. Downregulation of the miR-30 family may lead to reduced glucose uptake and altered expression of key genes associated with T2D.
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MESH Headings
- 3T3-L1 Cells
- Adipose Tissue/metabolism
- Adipose Tissue/pathology
- Aged
- Animals
- Arrhythmias, Cardiac/genetics
- Arrhythmias, Cardiac/pathology
- Case-Control Studies
- Cells, Cultured
- Cohort Studies
- DNA Methylation
- Denmark
- Diabetes Mellitus, Type 2/genetics
- Diabetes Mellitus, Type 2/metabolism
- Diabetes Mellitus, Type 2/pathology
- Diseases in Twins/genetics
- Female
- Gene Expression
- Genetic Diseases, X-Linked/genetics
- Genetic Diseases, X-Linked/pathology
- Gigantism/genetics
- Gigantism/pathology
- Heart Defects, Congenital/genetics
- Heart Defects, Congenital/pathology
- Humans
- Intellectual Disability/genetics
- Intellectual Disability/pathology
- Male
- Mice
- MicroRNAs/genetics
- MicroRNAs/metabolism
- Middle Aged
- Sweden
- Twins, Monozygotic/genetics
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Affiliation(s)
- Emma Nilsson
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Magdalena Vavakova
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
- Diabetes, Metabolism and Endocrinology, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Alexander Perfilyev
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Johanna Säll
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Per-Anders Jansson
- Wallenberg Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | | | - Jonathan Lou S Esguerra
- Islet Cell Exocytosis Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Lena Eliasson
- Islet Cell Exocytosis Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Allan Vaag
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Olga Göransson
- Diabetes, Metabolism and Endocrinology, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
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5
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Xu W, Wu Y, Fang X, Zhang Y, Cai N, Wen J, Liao J, Zhang B, Chen X, Chu L. SnoRD126 promotes the proliferation of hepatocellular carcinoma cells through transcriptional regulation of FGFR2 activation in combination with hnRNPK. Aging (Albany NY) 2021; 13:13300-13317. [PMID: 33891563 PMCID: PMC8148486 DOI: 10.18632/aging.203014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 03/14/2021] [Indexed: 02/07/2023]
Abstract
Liver cancer is the sixth most common malignancy and the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) is the primary type of liver cancer. Small nucleolar RNA (snoRNA) dysfunctions have been associated with cancer development. SnoRD126 is an orphan C/D box snoRNA. How snoRD126 activates the PI3K-AKT pathway, and which domain of snoRD126 exerts its oncogenic function was heretofore completely unknown. Here, we demonstrate that snoRD126 binds to hnRNPK protein to regulate FGFR2 expression and activate the PI3K-AKT pathway. Importantly, we identified the critical domain of snoRD126 responsible for its cancer-promoting functions. Our study further confirms the role of snoRD126 in the progression of HCC and suggests that knockdown snoRD126 may be of potential value as a novel therapeutic approach for the treatment of HCC.
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Affiliation(s)
- Weiqi Xu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Yu Wu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Xianlong Fang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Yuxin Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Ning Cai
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Jingyuan Wen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Jingyu Liao
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Bixiang Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Xiaoping Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
| | - Liang Chu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Medical Research Center of Hepatic Surgery in Hubei Province, Wuhan, China
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6
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Rotival M, Siddle KJ, Silvert M, Pothlichet J, Quach H, Quintana-Murci L. Population variation in miRNAs and isomiRs and their impact on human immunity to infection. Genome Biol 2020; 21:187. [PMID: 32731901 PMCID: PMC7391576 DOI: 10.1186/s13059-020-02098-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 07/08/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND MicroRNAs (miRNAs) are key regulators of the immune system, yet their variation and contribution to intra- and inter-population differences in immune responses is poorly characterized. RESULTS We generate 977 miRNA-sequencing profiles from primary monocytes from individuals of African and European ancestry following activation of three TLR pathways (TLR4, TLR1/2, and TLR7/8) or infection with influenza A virus. We find that immune activation leads to important modifications in the miRNA and isomiR repertoire, particularly in response to viral challenges. These changes are much weaker than those observed for protein-coding genes, suggesting stronger selective constraints on the miRNA response to stimulation. This is supported by the limited genetic control of miRNA expression variability (miR-QTLs) and the lower occurrence of gene-environment interactions, in stark contrast with eQTLs that are largely context-dependent. We also detect marked differences in miRNA expression between populations, which are mostly driven by non-genetic factors. On average, miR-QTLs explain approximately 60% of population differences in expression of their cognate miRNAs and, in some cases, evolve adaptively, as shown in Europeans for a miRNA-rich cluster on chromosome 14. Finally, integrating miRNA and mRNA data from the same individuals, we provide evidence that the canonical model of miRNA-driven transcript degradation has a minor impact on miRNA-mRNA correlations, which are, in our setting, mainly driven by co-transcription. CONCLUSION Together, our results shed new light onto the factors driving miRNA and isomiR diversity at the population level and constitute a useful resource for evaluating their role in host differences of immunity to infection.
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Affiliation(s)
- Maxime Rotival
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR 2000, 75015 Paris, France
| | - Katherine J. Siddle
- Broad Institute of MIT and Harvard, Cambridge, MA USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138 USA
| | - Martin Silvert
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR 2000, 75015 Paris, France
- Sorbonne Universités, École Doctorale Complexité du Vivant, 75005 Paris, France
| | - Julien Pothlichet
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR 2000, 75015 Paris, France
- Present Address: DIACCURATE, Institut Pasteur, 75015 Paris, France
| | - Hélène Quach
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR 2000, 75015 Paris, France
- Present Address: UMR7206, Muséum National d’Histoire Naturelle, CNRS, Université Paris Diderot, 75016 Paris, France
| | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR 2000, 75015 Paris, France
- Chair Human Genomics and Evolution, Collège de France, 75005 Paris, France
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7
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Civelek M, Erdmann J. MicroRNAs and regulation of cardiometabolic phenotypes: novel insights into the complexity of genome-wide association studies loci. Cardiovasc Res 2019; 115:1570-1571. [PMID: 31086972 DOI: 10.1093/cvr/cvz120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Mete Civelek
- Department of Biomedical Engineering, Center for Public Health Genomics, The University of Virginia, Charlottesville, VA, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University Heart Center Luebeck, University of Lübeck, Lübeck, Germany.,DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
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8
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Hilton C, Neville MJ, Wittemans LBL, Todorcevic M, Pinnick KE, Pulit SL, Luan J, Kulyté A, Dahlman I, Wareham NJ, Lotta LA, Arner P, Lindgren CM, Langenberg C, Karpe F. MicroRNA-196a links human body fat distribution to adipose tissue extracellular matrix composition. EBioMedicine 2019; 44:467-475. [PMID: 31151930 PMCID: PMC6607082 DOI: 10.1016/j.ebiom.2019.05.047] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 05/21/2019] [Accepted: 05/21/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Abdominal fat mass is associated with metabolic risk whilst gluteal femoral fat is paradoxically protective. MicroRNAs are known to be necessary for adipose tissue formation and function but their role in regulating human fat distribution remains largely unexplored. METHODS An initial microarray screen of abdominal subcutaneous and gluteal adipose tissue, with validatory qPCR, identified microRNA-196a as being strongly differentially expressed between gluteal and abdominal subcutaneous adipose tissue. FINDINGS We found that rs11614913, a SNP within pre-miR-196a-2 at the HOXC locus, is an eQTL for miR-196a expression in abdominal subcutaneous adipose tissue (ASAT). Observations in large cohorts showed that rs11614913 increased waist-to-hip ratio, which was driven specifically by an expansion in ASAT. In further experiments, rs11614913 was associated with adipocyte size. Functional studies and transcriptomic profiling of miR-196a knock-down pre-adipocytes revealed a role for miR-196a in regulating pre-adipocyte proliferation and extracellular matrix pathways. INTERPRETATION These data identify a role for miR-196a in regulating human body fat distribution. FUND: This work was supported by the Medical Research Council and Novo Nordisk UK Research Foundation (G1001959) and Swedish Research Council. We acknowledge the OBB-NIHR Oxford Biomedical Research Centre and the British Heart Foundation (BHF) (RG/17/1/32663). Work performed at the MRC Epidemiology Unit was funded by the United Kingdom's Medical Research Council through grants MC_UU_12015/1, MC_PC_13046, MC_PC_13048 and MR/L00002/1.
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Affiliation(s)
- Catriona Hilton
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, UK
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, UK; NIHR Oxford Biomedical Research Centre, OUH Trust, Oxford OX3 7LE, UK.
| | - Laura B L Wittemans
- Wellcome Trust Centre for Human Genetics, Oxford University, Oxford OX3 7BN, UK; Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Marijana Todorcevic
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, UK
| | - Katherine E Pinnick
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, UK
| | - Sara L Pulit
- Big Data Institute, University of Oxford, Oxford OX3 7FZ, UK; Wellcome Trust Centre for Human Genetics, Oxford University, Oxford OX3 7BN, UK; Department of Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jian'an Luan
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Agné Kulyté
- Department of Medicine (H7), Karolinska Institutet at Karolinska University Hospital - Huddinge, 141 86 Stockholm, Sweden
| | - Ingrid Dahlman
- Department of Medicine (H7), Karolinska Institutet at Karolinska University Hospital - Huddinge, 141 86 Stockholm, Sweden
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Luca A Lotta
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Arner
- Department of Medicine (H7), Karolinska Institutet at Karolinska University Hospital - Huddinge, 141 86 Stockholm, Sweden
| | - Cecilia M Lindgren
- Big Data Institute, University of Oxford, Oxford OX3 7FZ, UK; Wellcome Trust Centre for Human Genetics, Oxford University, Oxford OX3 7BN, UK
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, UK; NIHR Oxford Biomedical Research Centre, OUH Trust, Oxford OX3 7LE, UK.
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9
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MiR-323b-5p acts as a novel diagnostic biomarker for critical limb ischemia in type 2 diabetic patients. Sci Rep 2018; 8:15080. [PMID: 30305681 PMCID: PMC6179988 DOI: 10.1038/s41598-018-33310-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 09/26/2018] [Indexed: 12/12/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a major contributor to peripheral artery disease (PAD), especially in cases that advance to critical limb ischemia (CLI). Accumulating evidence indicates that miRNAs play an important role in the development of PAD and T2DM. Due to the limited value of current diagnostic methods for CLI in T2DM patients, we compared the miRNA expression profiles of Chinese T2DM patients with or without CLI to find out whether distinctive miRNAs could serve as potential diagnostic biomarkers. We statistically identified 7 miRNAs (hsa-miR-200b-3p, hsa-miR-2115-3p, hsa-miR-431-5p, hsa-miR-486-5p, hsa-miR-210-3p, hsa-miR-1264, hsa-miR-323b-5p) which were up-regulated in the CLI group, whereas other 4 miRNAs (hsa-miR-5579-3p, hsa-miR-665, hsa-miR-4285, hsa-miR-500a-3p) were down-regulated. Our validation test suggested a relatively high diagnostic accuracy of serum hsa-miR-323b-5p levels for the detection of CLI in T2DM patients, with a sensitivity of 62.67% and a specificity of 80.65%. The area under the curve (AUC) for miR-323b-5p + confounding risk factors was 0.94 (95% CI: 0.884-0.994, P < 0.001), which was higher than that for miR-323b-5p. Taken together, our results indicate that circulating hsa-miR-323b-5p could be a promising serum biomarker for the diagnosis of critical limb ischemia in type 2 diabetic patients.
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10
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Ponsuksili S, Trakooljul N, Hadlich F, Haack F, Murani E, Wimmers K. Genetic architecture and regulatory impact on hepatic microRNA expression linked to immune and metabolic traits. Open Biol 2018; 7:rsob.170101. [PMID: 29118269 PMCID: PMC5717336 DOI: 10.1098/rsob.170101] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Accepted: 10/02/2017] [Indexed: 02/06/2023] Open
Abstract
Regulation of microRNA (miRNA) expression contributes to a wide range of target gene expression and phenotypes. The miRNA expression in the liver, the central metabolic organ, was examined in 209 pigs, and integrated with haematological and clinical biomarkers of metabolic and overall health, mRNA-target expression levels and single-nucleotide polymorphism (SNP) genotypes. The expression levels of 426 miRNA species correlated with plasma haematological or biochemical traits (r² = |0.19–0.45|, false discovery rate < 5%). Pairs of these miRNAs and their predicted target mRNAs showing expressing levels associated with the identical traits were examined to understand how immune and metabolic traits are affected by miRNA-mediated regulatory networks derived by mapping miRNA abundance as an expression quantitative trait. In total, 221 miRNA-expression-QTL correspond to 164 SNPs and 108 miRNAs, including miR-34a, miR-30e, miR-148-3p, miR-204, miR-181-5p, miR-143-5p and let-7 g that also correlate with the biomarkers. Sixty-one SNPs were simultaneously associated with 29 miRNA and 41 mRNA species. The expression levels of 13 out of 29 miRNA were correlated with one of the biochemical or haematological traits. For example, the expression levels of miR-34a were correlated with serum phosphorus and cholesterin levels; miR-204, miR-15a and miR-16b were correlated with triglyceride. For haematological traits, the expression levels of miR-652 and miR-204 were correlated with the mean corpuscular haemoglobin concentration, and the expression of miR-143 was correlated with plateletcrit. Pleiotropic association analyses revealed genetic links between mRNA and miRNA on SSC6 for miR-34a, SSC9 for miR-708 and SSC14 for miR-652. Our analysis of miRNA and mRNA transcript profiles, their correlation with clinically important plasma parameters of hepatic functions as well as information on their genetic regulation provide novel regulatory networks and potential new biomarkers for immune and metabolic traits.
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Affiliation(s)
- Siriluck Ponsuksili
- Research Unit 'Functional Genome Analysis', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Nares Trakooljul
- Research Unit 'Genomics', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Frieder Hadlich
- Research Unit 'Functional Genome Analysis', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Fiete Haack
- Research Unit 'Functional Genome Analysis', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Eduard Murani
- Research Unit 'Genomics', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Klaus Wimmers
- Research Unit 'Genomics', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany .,Faculty of Agricultural and Environmental Sciences, University Rostock, 18059 Rostock, Germany
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11
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miR-320 mediates diabetes amelioration after duodenal-jejunal bypass via targeting adipoR1. Surg Obes Relat Dis 2018; 14:960-971. [PMID: 29960867 DOI: 10.1016/j.soard.2018.03.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 01/28/2018] [Accepted: 03/06/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND Duodenal-jejunal bypass (DJB) surgery can improve type 2 diabetes (T2D) dramatically. Accumulating evidence implicates deficiency of hepatic adiponectin signaling as a contributor to gluconeogenesis disorders, and some microRNAs (miRNAs) regulate adiponectin receptors (AdipoR1, AdipoR2). We investigated the effects of DJB on hepatic gluconeogenesis, lipid metabolism, and inflammation as well as the effects of miRNA-320 (AdipoR1-targeting miRNA) on DJB-induced T2D amelioration. OBJECTIVES To investigate the essential role of miRNAs in regulation of adiponectin signaling by targeting AdipoR1 in DJB and the underlying mechanisms. SETTING University Hospital, China. METHODS We studied hepatic adiponectin signaling changes and hepatic miRNAs involved in a rat model of DJB. We investigated the effects of miR-320 on AdipoR1 signaling in buffalo rat liver cell lines. Liver tissues and glucose tolerance tests were analyzed in DJB rats injected with lentivirus encoding a miR-320 mimic. RESULTS Transfection with a miR-320 mimic reduced AdipoR1 protein levels and inhibited downstream adiponectin signaling; transfection with a miR-320 inhibitor elicited the opposite effects. A luciferase assay confirmed that miR-320 binds to the 3'-untranslated regions of AdipoR1. Global upregulation of miR-320 expression in DJB rats showed impaired gluconeogenesis, lipid metabolism, and relatively higher expression of inflammation markers. CONCLUSION miR-320 regulates the adipoR1-mediated amelioration of T2D in DJB and should be explored as a potential target for T2D treatment.
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12
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Sharma NK, Varma V, Ma L, Hasstedt SJ, Das SK. Obesity Associated Modulation of miRNA and Co-Regulated Target Transcripts in Human Adipose Tissue of Non-Diabetic Subjects. Microrna 2018; 4:194-204. [PMID: 26527284 PMCID: PMC4740938 DOI: 10.2174/2211536604666151103121817] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2015] [Revised: 10/15/2015] [Accepted: 11/02/2015] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Micro RNAs (miRNAs) are a class of non-coding regulatory RNAs. We performed a transcriptome-wide analysis of subcutaneous adipose tissue and in vitro studies to identify miRNAs and co-regulated target transcripts associated with insulin sensitivity (SI) and obesity in human. METHODS We selected 20 insulin-resistant (IR, SI=2.0±0.7) and 20 insulin-sensitive (IS, SI=7.2±2.3) subjects from a cohort of 117 metabolically characterized non-diabetic Caucasians for comparison. RESULTS After global profiling, 3 miRNAs had marginally different expressions between IR and IS subjects. A total of 14 miRNAs were significantly correlated with %fat mass, body mass index (BMI), or SI. The qRT-PCR validated the correlation of miR-148a-3p with BMI (r=-0.70, P=2.73X10(-6)). MiRNA target filtering analysis identified DNA methyltransferase 1 (DNMT1) as one of the target genes of miR-148a-3p. DNMT1 expression in adipose tissue was positively correlated with BMI (r=0.47, p=8.42X10(-7)) and was inversely correlated with miR-148a-3p (r=-0.34). Differentiation of SGBS preadipocytes showed up-regulation of miR-148a-3p and down-regulation of DNMT1 in differentiated adipocytes. After transfecting miR-148a-3p mimics into HeLa-S3 cells, DNMT1 was down-regulated, while transfection of adipose stem cells with miR-148a-3p inhibitor up-regulated DNMT1. CONCLUSIONS Our results indicate that miR-148a-3pmediated regulation of DNMT1 expression may play a mechanistic role in obesity.
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Affiliation(s)
| | | | | | | | - Swapan K Das
- Section on Endocrinology and Metabolism, Department of Internal Medicine Wake Forest School of Medicine, Medical Center Boulevard, NRC Building#E159 Winston-Salem, North Carolina 27157, USA.
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13
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Le Roy CI, Beaumont M, Jackson MA, Steves CJ, Spector TD, Bell JT. Heritable components of the human fecal microbiome are associated with visceral fat. Gut Microbes 2018; 9:61-67. [PMID: 28767316 PMCID: PMC5914912 DOI: 10.1080/19490976.2017.1356556] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 07/06/2017] [Accepted: 07/10/2017] [Indexed: 02/07/2023] Open
Abstract
Obesity and its associated diseases are one of the major causes of death worldwide. The gut microbiota has been identified to have essential regulatory effects on human metabolism and obesity in particular. In a recent study we provided some insights into the link between the gut microbiota (GM) and adiposity, as well as host genetic modulation of these processes. Our results identify novel evidence of association between 6 adiposity phenotypes and faecal microbial operational taxonomic units (OTUs). Accumulation of visceral fat, a key risk factor for cardio-metabolic disease, has the strongest and most pervasive signature on the gut microbiota of the factors we examined. Furthermore, we observe that the adiposity-associated OTUs were classified as heritable and in some cases were also associated with host genetic variation at obesity-associated human candidate genes FHIT, TDRG1 and ELAVL4. This addendum confirms our previously published results in the TwinsUK cohort using a different approach to OTU clustering and multivariate analysis, and discusses further the importance of considering the GM as a complex ecosystem.
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Affiliation(s)
- Caroline I. Le Roy
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Michelle Beaumont
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Matthew A. Jackson
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Claire J. Steves
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Timothy D. Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jordana T. Bell
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
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14
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Lee PH, Lee C, Li X, Wee B, Dwivedi T, Daly M. Principles and methods of in-silico prioritization of non-coding regulatory variants. Hum Genet 2018; 137:15-30. [PMID: 29288389 PMCID: PMC5892192 DOI: 10.1007/s00439-017-1861-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Accepted: 12/14/2017] [Indexed: 12/13/2022]
Abstract
Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.
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Affiliation(s)
- Phil H Lee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA.
- Quantitative Genomics Program, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Christian Lee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- Department of Life Sciences, Harvard University, Cambridge, MA, USA
| | - Xihao Li
- Quantitative Genomics Program, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brian Wee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
| | - Tushar Dwivedi
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Mark Daly
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
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15
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Giardina S, Hernández-Alonso P, Salas-Salvadó J, Rabassa-Soler A, Bulló M. Modulation of Human Subcutaneous Adipose Tissue MicroRNA Profile Associated with Changes in Adiposity-Related Parameters. Mol Nutr Food Res 2017; 62. [PMID: 29024341 DOI: 10.1002/mnfr.201700594] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 09/22/2017] [Indexed: 12/23/2022]
Abstract
SCOPE To analyze the effect of three calorie-restricted diets with different amount and quality of carbohydrates on subcutaneous adipose tissue (SAT) microRNA (miRNA) profile. METHODS AND RESULTS 6-month parallel, randomized trial conducted on overweight and obese subjects randomized to: 1) low glycemic index diet (LGI), 2) high glycemic index diet (HGI), and 3) low-fat (LF). The genome-wide SAT miRNA profile was assessed in eight randomly selected participants and the most relevant changing miRNAs (n = 13) were validated in 48 subjects. None of the miRNAs showed significant changes between the intervention groups. However, changes in some of them correlated with changes in biochemical and anthropometric variables. Stratifying our population according to tertiles of percentage change in body weight (BW), we observed a significant down-regulation of miR-210 in those subjects in Tertile 1 as compared to Tertile 3. When our population was stratified by tertiles of waist circumference, miR-132, miR-29a, miR-34a, and miR-378 were found to be significantly down-regulated, in T2 compared to T3. Furthermore, when stratified by tertiles of fat mass, we also observed the significant down-regulation of miR-132 in T1. CONCLUSION The macronutrient composition of a calorie-restricted diet does not affect the expression of the miRNAs analyzed, while changes in adiposity play a primary regulatory role.
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Affiliation(s)
- Simona Giardina
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institute of Health Pere Virgili, Universitat Rovira i Virgili, Reus, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Pablo Hernández-Alonso
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institute of Health Pere Virgili, Universitat Rovira i Virgili, Reus, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Jordi Salas-Salvadó
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institute of Health Pere Virgili, Universitat Rovira i Virgili, Reus, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Antoni Rabassa-Soler
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institute of Health Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | - Mònica Bulló
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institute of Health Pere Virgili, Universitat Rovira i Virgili, Reus, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
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16
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Amri EZ, Scheideler M. Small non coding RNAs in adipocyte biology and obesity. Mol Cell Endocrinol 2017; 456:87-94. [PMID: 28412522 DOI: 10.1016/j.mce.2017.04.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Revised: 04/10/2017] [Accepted: 04/10/2017] [Indexed: 12/12/2022]
Abstract
Obesity has reached epidemic proportions world-wide and constitutes a substantial risk factor for hypertension, type 2 diabetes, cardiovascular diseases and certain cancers. So far, regulation of energy intake by dietary and pharmacological treatments has met limited success. The main interest of current research is focused on understanding the role of different pathways involved in adipose tissue function and modulation of its mass. Whole-genome sequencing studies revealed that the majority of the human genome is transcribed, with thousands of non-protein-coding RNAs (ncRNA), which comprise small and long ncRNAs. ncRNAs regulate gene expression at the transcriptional and post-transcriptional level. Numerous studies described the involvement of ncRNAs in the pathogenesis of many diseases including obesity and associated metabolic disorders. ncRNAs represent potential diagnostic biomarkers and promising therapeutic targets. In this review, we focused on small ncRNAs involved in the formation and function of adipocytes and obesity.
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Affiliation(s)
| | - Marcel Scheideler
- Institute for Diabetes and Cancer (IDC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Joint Heidelberg-IDC Translational Diabetes Program, University Hospital Heidelberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany.
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17
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Civelek M. A Smoking-Associated miRNA-mRNA Coexpression Network. ACTA ACUST UNITED AC 2017; 10:CIRCGENETICS.117.001914. [PMID: 29030404 DOI: 10.1161/circgenetics.117.001914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Mete Civelek
- From the Department of Biomedical Engineering, Center for Public Health Genomics, University of Virginia, Charlottesville.
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18
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Kristensen MM, Davidsen PK, Vigelsø A, Hansen CN, Jensen LJ, Jessen N, Bruun JM, Dela F, Helge JW. miRNAs in human subcutaneous adipose tissue: Effects of weight loss induced by hypocaloric diet and exercise. Obesity (Silver Spring) 2017; 25:572-580. [PMID: 28158925 DOI: 10.1002/oby.21765] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 11/29/2016] [Accepted: 12/09/2016] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Obesity is central in the development of insulin resistance. However, the underlying mechanisms still need elucidation. Dysregulated microRNAs (miRNAs; post-transcriptional regulators) in adipose tissue may present an important link. METHODS The miRNA expression in subcutaneous adipose tissue from 19 individuals with severe obesity (10 women and 9 men) before and after a 15-week weight loss intervention was studied using genome-wide microarray analysis. The microarray results were validated with RT-qPCR, and pathway enrichment analysis of in silico predicted targets was performed to elucidate the biological consequences of the miRNA dysregulation. Lastly, the messenger RNA (mRNA) and/or protein expression of multiple predicted targets as well as several proteins involved in lipolysis were investigated. RESULTS The intervention led to upregulation of miR-29a-3p and miR-29a-5p and downregulation of miR-20b-5p. The mRNA and protein expression of predicted targets was not significantly affected by the intervention. However, negative correlations between miR-20b-5p and the protein levels of its predicted target, acyl-CoA synthetase long-chain family member 1, were observed. Several other miRNA-target relationships correlated negatively, indicating possible miRNA regulation, including miR-29a-3p and lipoprotein lipase mRNA levels. Proteins involved in lipolysis were not affected by the intervention. CONCLUSIONS Weight loss influenced several miRNAs, some of which were negatively correlated with predicted targets. These dysregulated miRNAs may affect adipocytokine signaling and forkhead box protein O signaling.
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Affiliation(s)
- Malene M Kristensen
- Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter K Davidsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Andreas Vigelsø
- Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christina N Hansen
- Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lars J Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Jessen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Jens M Bruun
- Randers Regional Hospital, Medical Department M, Randers, Denmark
- Department of Nutrition, Exercise, and Sports (NEXS), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Flemming Dela
- Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Geriatrics, Bispebjerg University Hospital, Copenhagen, Denmark
| | - Jørn W Helge
- Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Principles of microRNA Regulation Revealed Through Modeling microRNA Expression Quantitative Trait Loci. Genetics 2016; 203:1629-40. [PMID: 27260304 PMCID: PMC4981266 DOI: 10.1534/genetics.116.187153] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 05/27/2016] [Indexed: 12/23/2022] Open
Abstract
Extensive work has been dedicated to study mechanisms of microRNA-mediated gene regulation. However, the transcriptional regulation of microRNAs themselves is far less well understood, due to difficulties determining the transcription start sites of transient primary transcripts. This challenge can be addressed using expression quantitative trait loci (eQTLs) whose regulatory effects represent a natural source of perturbation of cis-regulatory elements. Here we used previously published cis-microRNA-eQTL data for the human GM12878 cell line, promoter predictions, and other functional annotations to determine the relationship between functional elements and microRNA regulation. We built a logistic regression model that classifies microRNA/SNP pairs into eQTLs or non-eQTLs with 85% accuracy; shows microRNA-eQTL enrichment for microRNA precursors, promoters, enhancers, and transcription factor binding sites; and depletion for repressed chromatin. Interestingly, although there is a large overlap between microRNA eQTLs and messenger RNA eQTLs of host genes, 74% of these shared eQTLs affect microRNA and host expression independently. Considering microRNA-only eQTLs we find a significant enrichment for intronic promoters, validating the existence of alternative promoters for intragenic microRNAs. Finally, in line with the GM12878 cell line derived from B cells, we find genome-wide association (GWA) variants associated to blood-related traits more likely to be microRNA eQTLs than random GWA and non-GWA variants, aiding the interpretation of GWA results.
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Guo W, Han H, Wang Y, Zhang X, Liu S, Zhang G, Hu S. miR-200a regulates Rheb-mediated amelioration of insulin resistance after duodenal-jejunal bypass. Int J Obes (Lond) 2016; 40:1222-32. [PMID: 27121251 PMCID: PMC4973218 DOI: 10.1038/ijo.2016.60] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 02/06/2016] [Accepted: 03/16/2016] [Indexed: 12/20/2022]
Abstract
Objectives: Duodenal–jejunal bypass (DJB) surgery can induce the rapid and durable remission of diabetes. Recent studies indicate that ameliorated hepatic insulin resistance and improved insulin signaling might contribute to the diabetic control observed after DJB. Ras homolog enriched in brain (Rheb) is reported to have an important role in insulin pathway, and some microRNAs (miRNAs) have been found to regulate Rheb. This study was conducted to investigate the effects of DJB on hepatic insulin resistance and the effects of miRNA-200a, a Rheb-targeting miRNA, on the development of DJB-induced amelioration in hepatic insulin resistance. Subjects: We investigated hepatic insulin signaling change and mapped the hepatic miRNAome involved in a rat model of DJB. We studied the effects of miR-200a on Rheb signaling pathway in buffalo rat liver cell lines. Liver tissues were studied and glucose tolerance tests were conducted in DJB rats injected with lentivirus encoding miR-200a inhibitor and diabetic rats injected with miR-200a mimic. Results: Rheb is a potential target of miR-200a. Transfection with an miR-200a inhibitor increased Rheb protein levels and enhanced the feedback action on insulin receptor substrate-dependent insulin signaling, whereas transfection with an miR-200a mimic produced the opposite effects. A luciferase assay confirmed that miR-200a bind to the 3′UTR (untranslated regions) of Rheb. Global downregulation of miR-200a in DJB rats showed impaired insulin sensitivity whereas upregulation of miR-200a in diabetic rats showed amelioration of diabetes. Conclusions: A novel mechanism was identified, in which miR-200a regulates the Rheb-mediated amelioration of insulin resistance in DJB. The findings suggest miR-200a should be further explored as a potential target for the treatment of diabetes.
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Affiliation(s)
- W Guo
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - H Han
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - Y Wang
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - X Zhang
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - S Liu
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - G Zhang
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
| | - S Hu
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People's Republic of China
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Abstract
To our knowledge, there is no report on microRNA (miRNA) expression and their target analysis in relation to the type of the first feed and its effect on the further growth of fish. Atlantic cod (Gadus morhua) larvae have better growth and development performance when fed natural zooplankton as a start-feed, as compared with those fed typical aquaculture start-feeds. In our experiment, two groups of Atlantic cod larvae were fed reference feed (zooplankton, mostly copepods, filtered from a seawater pond) v. aquaculture feeds: enriched rotifers (Brachionus sp.) and later brine shrimp (Artemia salina). We examined the miRNA expressions of six defined developmental stages as determined and standardised by body length from first feeding for both diet groups. We found eight miRNA (miR-9, miR-19a, miR-130b, miR-146, miR-181a, miR-192, miR-206 and miR-11240) differentially expressed between the two feeding groups in at least one developmental stage. We verified the next-generation sequencing data using real-time RT-PCR. We found 397 putative targets (mRNA) to the differentially expressed miRNA; eighteen of these mRNA showed differential expression in at least one stage. The patterns of differentially expressed miRNA and their putative target mRNA were mostly inverse, but sometimes also concurrent. The predicted miRNA targets were involved in different pathways, including metabolic, phototransduction and signalling pathways. The results of this study provide new nutrigenomic information on the potential role of miRNA in mediating nutritional effects on growth during the start-feeding period in fish larvae.
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Wang J, Yao W, Zhu D, Xie W, Zhang Q. Genetic basis of sRNA quantitative variation analyzed using an experimental population derived from an elite rice hybrid. eLife 2015; 4:e04250. [PMID: 25821986 PMCID: PMC4415135 DOI: 10.7554/elife.03913] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2014] [Accepted: 03/30/2015] [Indexed: 12/16/2022] Open
Abstract
We performed a genetic analysis of sRNA abundance in flag leaf from an immortalized F2 (IMF2) population in rice. We identified 53,613,739 unique sRNAs and 165,797 sRNA expression traits (s-traits). A total of 66,649 s-traits mapped 40,049 local-sQTLs and 30,809 distant-sQTLs. By defining 80,362 sRNA clusters, 22,263 sRNA cluster QTLs (scQTLs) were recovered for 20,249 of all the 50,139 sRNA cluster expression traits (sc-traits). The expression levels for most of s-traits from the same genes or the same sRNA clusters were slightly positively correlated. While genetic co-regulation between sRNAs from the same mother genes and between sRNAs and their mother genes was observed for a portion of the sRNAs, most of the sRNAs and their mother genes showed little co-regulation. Some sRNA biogenesis genes were located in distant-sQTL hotspots and showed correspondence with specific length classes of sRNAs suggesting their important roles in the regulation and biogenesis of the sRNAs. DOI:http://dx.doi.org/10.7554/eLife.03913.001 Genes within the DNA of a plant or animal contain instructions to make molecules called RNAs. Some RNA molecules can be decoded to make proteins, whereas others have different roles. A single gene often contains the instructions to make both protein-coding RNAs and non-coding RNAs. Molecules called small RNAs (or sRNAs) do not code for proteins. Instead, sRNAs can control protein-coding RNA molecules or chemically alter the DNA itself; this allows them to perform many different roles in living organisms. In plants, for example, these molecules affect how the plant grows, the shapes and structures it forms, and how likely it is to survive challenges such as drought and diseases. Often different plants of the same species have different amounts of sRNAs, but the reasons for this remain unclear. Now, Wang, Yao et al. have made use of a technique called ‘expression quantitative locus’ analysis to look at how sRNAs in rice plants are controlled by additional information encoded within DNA. The analysis identified over 53 million sRNA molecules from a population of rice plants. Many of these sRNAs varied in their abundance between different plants within the population. Wang, Yao et al. also found many thousands of individual instructions within the DNA of the rice that can either increase or reduce the abundance of their associated sRNA. Some of the abundant sRNAs were influenced by instructions within their own genes; some were influenced by instructions from other genes; and some were influenced by both. Wang, Yao et al. also found that the control of protein-coding RNAs was not necessarily related to the control of sRNAs encoded by the same gene. Further work is now needed to identify which specific DNA sequences regulate the abundance of sRNA molecules in plants and other organisms. DOI:http://dx.doi.org/10.7554/eLife.03913.002
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Affiliation(s)
- Jia Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Wen Yao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Dan Zhu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
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23
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Albert FW, Kruglyak L. The role of regulatory variation in complex traits and disease. Nat Rev Genet 2015; 16:197-212. [DOI: 10.1038/nrg3891] [Citation(s) in RCA: 684] [Impact Index Per Article: 76.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Dudley JT, Listgarten J, Stegle O, Brenner SE, Parts L. Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2015:342-346. [PMID: 25592594 PMCID: PMC5893135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Advances in molecular profiling and sensor technologies are expanding the scope of personalized medicine beyond genotypes, providing new opportunities for developing richer and more dynamic multi-scale models of individual health. Recent studies demonstrate the value of scoring high-dimensional microbiome, immune, and metabolic traits from individuals to inform personalized medicine. Efforts to integrate multiple dimensions of clinical and molecular data towards predictive multi-scale models of individual health and wellness are already underway. Improved methods for mining and discovery of clinical phenotypes from electronic medical records and technological developments in wearable sensor technologies present new opportunities for mapping and exploring the critical yet poorly characterized "phenome" and "envirome" dimensions of personalized medicine. There are ambitious new projects underway to collect multi-scale molecular, sensor, clinical, behavioral, and environmental data streams from large population cohorts longitudinally to enable more comprehensive and dynamic models of individual biology and personalized health. Personalized medicine stands to benefit from inclusion of rich new sources and dimensions of data. However, realizing these improvements in care relies upon novel informatics methodologies, tools, and systems to make full use of these data to advance both the science and translational applications of personalized medicine.
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Affiliation(s)
- Joel T Dudley
- Icahn School of Medicine at Mount Sinai, 1425 Madison Ave., New York, USA.
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25
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Fairfax BP, Knight JC. Genetics of gene expression in immunity to infection. Curr Opin Immunol 2014; 30:63-71. [PMID: 25078545 PMCID: PMC4426291 DOI: 10.1016/j.coi.2014.07.001] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2014] [Revised: 07/03/2014] [Accepted: 07/06/2014] [Indexed: 01/30/2023]
Abstract
Mapping gene expression as a quantitative trait (eQTL mapping) can reveal local and distant associations with functionally important genetic variation informative for disease. Recent studies are reviewed which have demonstrated that this approach is particularly informative when applied to diverse immune cell populations and situations relevant to infection and immunity. Context-specific eQTL have now been characterised following endotoxin activation, induction with interferons, mycobacteria, and influenza, together with genetic determinants of response to vaccination. The application of genetical genomic approaches offers new opportunities to advance our understanding of gene-environment interactions and fundamental processes in innate and adaptive immunity.
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Affiliation(s)
- Benjamin P Fairfax
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
| | - Julian C Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
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26
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Yeh SD, von Grotthuss M, Gandasetiawan KA, Jayasekera S, Xia XQ, Chan C, Jayaswal V, Ranz JM. Functional divergence of the miRNA transcriptome at the onset of Drosophila metamorphosis. Mol Biol Evol 2014; 31:2557-72. [PMID: 24951729 DOI: 10.1093/molbev/msu195] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
MicroRNAs (miRNAs) are endogenous RNA molecules that regulate gene expression posttranscriptionally. To date, the emergence of miRNAs and their patterns of sequence evolution have been analyzed in great detail. However, the extent to which miRNA expression levels have evolved over time, the role different evolutionary forces play in shaping these changes, and whether this variation in miRNA expression can reveal the interplay between miRNAs and mRNAs remain poorly understood. This is especially true for miRNA expressed during key developmental transitions. Here, we assayed miRNA expression levels immediately before (≥18BPF [18 h before puparium formation]) and after (PF) the increase in the hormone ecdysone responsible for triggering metamorphosis. We did so in four strains of Drosophila melanogaster and two closely related species. In contrast to their sequence conservation, approximately 25% of miRNAs analyzed showed significant within-species variation in male expression levels at ≥18BPF and/or PF. Additionally, approximately 33% showed modifications in their pattern of expression bias between developmental timepoints. A separate analysis of the ≥18BPF and PF stages revealed that changes in miRNA abundance accumulate linearly over evolutionary time at PF but not at ≥18BPF. Importantly, ≥18BPF-enriched miRNAs showed the greatest variation in expression levels both within and between species, so are the less likely to evolve under stabilizing selection. Functional attributes, such as expression ubiquity, appeared more tightly associated with lower levels of miRNA expression polymorphism at PF than at ≥18BPF. Furthermore, ≥18BPF- and PF-enriched miRNAs showed opposite patterns of covariation in expression with mRNAs, which denoted the type of regulatory relationship between miRNAs and mRNAs. Collectively, our results show contrasting patterns of functional divergence associated with miRNA expression levels during Drosophila ontogeny.
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Affiliation(s)
- Shu-Dan Yeh
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Marcin von Grotthuss
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | | | - Suvini Jayasekera
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Xiao-Qin Xia
- Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Carolus Chan
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Vivek Jayaswal
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
| | - José M Ranz
- Department of Ecology and Evolutionary Biology, University of California, Irvine
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27
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Resler AJ, Makar KW, Heath L, Whitton J, Potter JD, Poole EM, Habermann N, Scherer D, Duggan D, Wang H, Lindor NM, Passarelli MN, Baron JA, Newcomb PA, Le Marchand L, Ulrich CM. Genetic variation in prostaglandin synthesis and related pathways, NSAID use and colorectal cancer risk in the Colon Cancer Family Registry. Carcinogenesis 2014; 35:2121-6. [PMID: 24908683 DOI: 10.1093/carcin/bgu119] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Although use of non-steroidal anti-inflammatory drugs (NSAIDs) generally decreases colorectal cancer (CRC) risk, inherited genetic variation in inflammatory pathways may alter their potential as preventive agents. We investigated whether variation in prostaglandin synthesis and related pathways influences CRC risk in the Colon Cancer Family Registry by examining associations between 192 single nucleotide polymorphisms (SNPs) and two variable nucleotide tandem repeats (VNTRs) within 17 candidate genes and CRC risk. We further assessed interactions between these polymorphisms and NSAID use on CRC risk. Using a case-unaffected-sibling-control design, this study included 1621 primary invasive CRC cases and 2592 sibling controls among Caucasian men and women aged 18-90. After adjustment for multiple comparisons, two intronic SNPs were associated with rectal cancer risk: rs11571364 in ALOX12 [OR(het/hzv) = 1.87, 95% confidence interval (CI) = 1.19-2.95, P = 0.03] and rs45525634 in PTGER2 (OR(het/hzv) = 0.49, 95% CI = 0.29-0.82, P = 0.03). Additionally, there was an interaction between NSAID use and the intronic SNP rs2920421 in ALOX12 on risk of CRC (P = 0.03); among those with heterozygous genotypes, risk was reduced for current NSAID users compared with never or former users (OR(het) = 0.60, 95% CI = 0.45-0.80), though not among those with homozygous wild-type or variant genotypes. The results of this study suggest that genetic variation in ALOX12 and PTGER2 may affect the risk of rectal cancer. In addition, this study suggests plausible interactions between NSAID use and variants in ALOX12 on CRC risk. These results may aid in the development of genetically targeted cancer prevention strategies with NSAIDs.
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Affiliation(s)
- Alexa J Resler
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and, Department of Public Health Genetics, University of Washington, Seattle, WA 98195, USA
| | - Karen W Makar
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Laura Heath
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and, Department of Public Health Genetics, University of Washington, Seattle, WA 98195, USA
| | - John Whitton
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - John D Potter
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and, Centre for Public Health Research, Massey University, Wellington 6140, New Zealand
| | - Elizabeth M Poole
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA 02115, USA
| | - Nina Habermann
- Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg 69120, Germany
| | - Dominique Scherer
- Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg 69120, Germany
| | - David Duggan
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Hansong Wang
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Noralane M Lindor
- Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ 85259, USA
| | - Michael N Passarelli
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and, Department of Public Health Genetics, University of Washington, Seattle, WA 98195, USA
| | - John A Baron
- Department of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA and
| | - Polly A Newcomb
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and
| | - Loic Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Cornelia M Ulrich
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Epidemiology and, Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg 69120, Germany, German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
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28
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Parts L, Liu YC, Tekkedil MM, Steinmetz LM, Caudy AA, Fraser AG, Boone C, Andrews BJ, Rosebrock AP. Heritability and genetic basis of protein level variation in an outbred population. Genome Res 2014; 24:1363-70. [PMID: 24823668 PMCID: PMC4120089 DOI: 10.1101/gr.170506.113] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population’s average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance.
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Affiliation(s)
- Leopold Parts
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, M5S3E1, Canada
| | - Yi-Chun Liu
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada
| | - Manu M Tekkedil
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Lars M Steinmetz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Amy A Caudy
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, M5S3E1, Canada
| | - Andrew G Fraser
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, M5S3E1, Canada
| | - Charles Boone
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, M5S3E1, Canada
| | - Brenda J Andrews
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, M5S3E1, Canada
| | - Adam P Rosebrock
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, M5S3E1, Canada;
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29
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Siddle KJ, Deschamps M, Tailleux L, Nédélec Y, Pothlichet J, Lugo-Villarino G, Libri V, Gicquel B, Neyrolles O, Laval G, Patin E, Barreiro LB, Quintana-Murci L. A genomic portrait of the genetic architecture and regulatory impact of microRNA expression in response to infection. Genome Res 2014; 24:850-9. [PMID: 24482540 PMCID: PMC4009614 DOI: 10.1101/gr.161471.113] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
MicroRNAs (miRNAs) are critical regulators of gene expression, and their role in a wide variety of biological processes, including host antimicrobial defense, is increasingly well described. Consistent with their diverse functional effects, miRNA expression is highly context dependent and shows marked changes upon cellular activation. However, the genetic control of miRNA expression in response to external stimuli and the impact of such perturbations on miRNA-mediated regulatory networks at the population level remain to be determined. Here we assessed changes in miRNA expression upon Mycobacterium tuberculosis infection and mapped expression quantitative trait loci (eQTL) in dendritic cells from a panel of healthy individuals. Genome-wide expression profiling revealed that ∼40% of miRNAs are differentially expressed upon infection. We find that the expression of 3% of miRNAs is controlled by proximate genetic factors, which are enriched in a promoter-specific histone modification associated with active transcription. Notably, we identify two infection-specific response eQTLs, for miR-326 and miR-1260, providing an initial assessment of the impact of genotype-environment interactions on miRNA molecular phenotypes. Furthermore, we show that infection coincides with a marked remodeling of the genome-wide relationships between miRNA and mRNA expression levels. This observation, supplemented by experimental data using the model of miR-29a, sheds light on the role of a set of miRNAs in cellular responses to infection. Collectively, this study increases our understanding of the genetic architecture of miRNA expression in response to infection, and highlights the wide-reaching impact of altering miRNA expression on the transcriptional landscape of a cell.
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Affiliation(s)
- Katherine J Siddle
- Institut Pasteur, Unit of Human Evolutionary Genetics, 75015 Paris, France
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30
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Listgarten J, Stegle O, Morris Q, Brenner SE, Parts L. Personalized medicine: from genotypes and molecular phenotypes towards therapy- session introduction. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2014; 19:224-228. [PMID: 24297549 PMCID: PMC5215523 DOI: 10.1142/9789814583220_0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
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31
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Abstract
Transcriptome studies have revealed a surprisingly high level of variation among individuals in expression of key genes in the CNS under both normal and experimental conditions. Ten-fold variation is common, yet the specific causes and consequences of this variation are largely unknown. By combining classic gene mapping methods-family linkage studies and genomewide association-with high-throughput genomics, it is now possible to define quantitative trait loci (QTLs), single-gene variants, and even single SNPs and indels that control gene expression in different brain regions and cells. This review considers some of the major technical and conceptual challenges in analyzing variation in expression in the CNS with a focus on mRNAs, rather than noncoding RNAs or proteins. At one level of analysis, this work has been highly successful, and we finally have techniques that can be used to track down small numbers of loci that control expression in the CNS. But at a higher level of analysis, we still do not understand the genetic architecture of gene expression in brain, the consequences of expression QTLs on protein levels or on cell function, or the combined impact of expression differences on behavior and disease risk. These important gaps are likely to be bridged over the next several decades using (1) much larger sample sizes, (2) more powerful RNA sequencing and proteomic methods, and (3) novel statistical and computational models to predict genome-to-phenome relations.
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Affiliation(s)
- Ashutosh K Pandey
- Department of Genetics, Genomics and Informatics, Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
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32
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Hill AF, Pegtel DM, Lambertz U, Leonardi T, O'Driscoll L, Pluchino S, Ter-Ovanesyan D, Nolte-'t Hoen ENM. ISEV position paper: extracellular vesicle RNA analysis and bioinformatics. J Extracell Vesicles 2013; 2:22859. [PMID: 24376909 PMCID: PMC3873759 DOI: 10.3402/jev.v2i0.22859] [Citation(s) in RCA: 104] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Revised: 12/02/2013] [Accepted: 12/02/2013] [Indexed: 12/19/2022] Open
Abstract
Extracellular vesicles (EVs) are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA) has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV) held a workshop on “evRNA analysis and bioinformatics.” Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.
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Affiliation(s)
- Andrew F Hill
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
| | - D Michiel Pegtel
- Department of Pathology, VU University Medical Centre, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Ulrike Lambertz
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Tommaso Leonardi
- Department of Clinical Neurosciences, John van Geest Cambridge Centre for Brain Repair and Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK ; EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Lorraine O'Driscoll
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Stefano Pluchino
- Department of Clinical Neurosciences, John van Geest Cambridge Centre for Brain Repair and Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Dmitry Ter-Ovanesyan
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Esther N M Nolte-'t Hoen
- Faculty of Veterinary Medicine, Department of Biochemistry and Cell Biology, Utrecht University, Utrecht, The Netherlands
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't Hoen PAC, Friedländer MR, Almlöf J, Sammeth M, Pulyakhina I, Anvar SY, Laros JFJ, Buermans HPJ, Karlberg O, Brännvall M, den Dunnen JT, van Ommen GJB, Gut IG, Guigó R, Estivill X, Syvänen AC, Dermitzakis ET, Lappalainen T. Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories. Nat Biotechnol 2013; 31:1015-22. [DOI: 10.1038/nbt.2702] [Citation(s) in RCA: 193] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2013] [Accepted: 08/21/2013] [Indexed: 02/07/2023]
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Horswell SD, Fryer LGD, Hutchison CE, Zindrou D, Speedy HE, Town MM, Duncan EJ, Sivapackianathan R, Patel HN, Jones EL, Braithwaite A, Salm MPA, Neuwirth CKY, Potter E, Anderson JR, Taylor KM, Seed M, Betteridge DJ, Crook MA, Wierzbicki AS, Scott J, Naoumova RP, Shoulders CC. CDKN2B expression in adipose tissue of familial combined hyperlipidemia patients. J Lipid Res 2013; 54:3491-505. [PMID: 24103848 DOI: 10.1194/jlr.m041814] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The purpose of this study was to determine the core biological processes perturbed in the subcutaneous adipose tissue of familial combined hyperlipidemia (FCHL) patients. Annotation of FCHL and control microarray datasets revealed a distinctive FCHL transcriptome, characterized by gene expression changes regulating five overlapping systems: the cytoskeleton, cell adhesion and extracellular matrix; vesicular trafficking; lipid homeostasis; and cell cycle and apoptosis. Expression values for the cell-cycle inhibitor CDKN2B were increased, replicating data from an independent FCHL cohort. In 3T3-L1 cells, CDKN2B knockdown induced C/EBPα expression and lipid accumulation. The minor allele at SNP site rs1063192 (C) was predicted to create a perfect seed for the human miRNA-323b-5p. A miR-323b-5p mimic significantly reduced endogenous CDKN2B protein levels and the activity of a CDKN2B 3'UTR luciferase reporter carrying the rs1063192 C allele. Although the allele displayed suggestive evidence of association with reduced CDKN2B mRNA in the MuTHER adipose tissue dataset, family studies suggest the association between increased CDKN2B expression and FCHL-lipid abnormalities is driven by factors external to this gene locus. In conclusion, from a comparative annotation analysis of two separate FCHL adipose tissue transcriptomes and a subsequent focus on CDKN2B, we propose that dysfunctional adipogenesis forms an integral part of FCHL pathogenesis.
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Affiliation(s)
- Stuart D Horswell
- Medical Research Council, Clinical Sciences Centre, Hammersmith Hospital, London, United Kingdom
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35
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Lappalainen T, Sammeth M, Friedländer MR, ‘t Hoen PAC, Monlong J, Rivas MA, Gonzàlez-Porta M, Kurbatova N, Griebel T, Ferreira PG, Barann M, Wieland T, Greger L, van Iterson M, Almlöf J, Ribeca P, Pulyakhina I, Esser D, Giger T, Tikhonov A, Sultan M, Bertier G, MacArthur DG, Lek M, Lizano E, Buermans HPJ, Padioleau I, Schwarzmayr T, Karlberg O, Ongen H, Kilpinen H, Beltran S, Gut M, Kahlem K, Amstislavskiy V, Stegle O, Pirinen M, Montgomery SB, Donnelly P, McCarthy MI, Flicek P, Strom TM, Lehrach H, Schreiber S, Sudbrak R, Carracedo Á, Antonarakis SE, Häsler R, Syvänen AC, van Ommen GJ, Brazma A, Meitinger T, Rosenstiel P, Guigó R, Gut IG, Estivill X, Dermitzakis ET. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 2013; 501:506-11. [PMID: 24037378 PMCID: PMC3918453 DOI: 10.1038/nature12531] [Citation(s) in RCA: 1354] [Impact Index Per Article: 123.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2013] [Accepted: 08/05/2013] [Indexed: 02/06/2023]
Abstract
Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project--the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.
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Affiliation(s)
- Tuuli Lappalainen
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
- Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Michael Sammeth
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
| | - Marc R Friedländer
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Peter AC ‘t Hoen
- Department for Human and Clinical Genetics, Leiden University Medical Center, 2300 RC Leiden, the Netherlands
| | - Jean Monlong
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
| | - Manuel A Rivas
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom
| | | | - Natalja Kurbatova
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Thasso Griebel
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | - Pedro G Ferreira
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Matthias Barann
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, D-24105 Kiel, Germany
| | - Thomas Wieland
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
| | - Liliana Greger
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Maarten van Iterson
- Department for Human and Clinical Genetics, Leiden University Medical Center, 2300 RC Leiden, the Netherlands
| | - Jonas Almlöf
- Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden
| | - Paolo Ribeca
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | - Irina Pulyakhina
- Department for Human and Clinical Genetics, Leiden University Medical Center, 2300 RC Leiden, the Netherlands
| | - Daniela Esser
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, D-24105 Kiel, Germany
| | - Thomas Giger
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
| | - Andrew Tikhonov
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Marc Sultan
- Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Gabrielle Bertier
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Daniel G MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge MA 02142, USA
| | - Monkol Lek
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge MA 02142, USA
| | - Esther Lizano
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Henk PJ Buermans
- Department for Human and Clinical Genetics, Leiden University Medical Center, 2300 RC Leiden, the Netherlands
- Leiden Genome Technology Center, 2300 RC Leiden, the Netherlands
| | - Ismael Padioleau
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
- Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Thomas Schwarzmayr
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Olof Karlberg
- Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden
| | - Halit Ongen
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
- Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Helena Kilpinen
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
- Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Sergi Beltran
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | - Marta Gut
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | - Katja Kahlem
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | | | - Oliver Stegle
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Matti Pirinen
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Stephen B Montgomery
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
| | - Peter Donnelly
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Paul Flicek
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Tim M Strom
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, 81675 Munich, Germany
| | | | - Hans Lehrach
- Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
- Dahlem Centre for Genome Research and Medical Systems Biology, 14195 Berlin, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, D-24105 Kiel, Germany
| | - Ralf Sudbrak
- Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
- Dahlem Centre for Genome Research and Medical Systems Biology, 14195 Berlin, Germany
| | - Ángel Carracedo
- Fundacion Publica Galega de Medicina Xenomica SERGAS, Genomic Medicine Group CIBERER, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Stylianos E Antonarakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
| | - Robert Häsler
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, D-24105 Kiel, Germany
| | - Ann-Christine Syvänen
- Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden
| | - Gert-Jan van Ommen
- Department for Human and Clinical Genetics, Leiden University Medical Center, 2300 RC Leiden, the Netherlands
| | - Alvis Brazma
- European Bioinformatics Institute, EMBL-EBI, Hinxton, United Kingdom
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, 81675 Munich, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, D-24105 Kiel, Germany
| | - Roderic Guigó
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Ivo G Gut
- Centro Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain
| | - Xavier Estivill
- Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland
- Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
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36
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Genetic and nongenetic variation revealed for the principal components of human gene expression. Genetics 2013; 195:1117-28. [PMID: 24026092 DOI: 10.1534/genetics.113.153221] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Principal components analysis has been employed in gene expression studies to correct for population substructure and batch and environmental effects. This method typically involves the removal of variation contained in as many as 50 principal components (PCs), which can constitute a large proportion of total variation present in the data. Each PC, however, can detect many sources of variation, including gene expression networks and genetic variation influencing transcript levels. We demonstrate that PCs generated from gene expression data can simultaneously contain both genetic and nongenetic factors. From heritability estimates we show that all PCs contain a considerable portion of genetic variation while nongenetic artifacts such as batch effects were associated to varying degrees with the first 60 PCs. These PCs demonstrate an enrichment of biological pathways, including core immune function and metabolic pathways. The use of PC correction in two independent data sets resulted in a reduction in the number of cis- and trans-expression QTL detected. Comparisons of PC and linear model correction revealed that PC correction was not as efficient at removing known batch effects and had a higher penalty on genetic variation. Therefore, this study highlights the danger of eliminating biologically relevant data when employing PC correction in gene expression data.
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Abstract
Identification and functional interpretation of gene regulatory variants is a major focus of modern genomics. The application of genetic mapping to molecular and cellular traits has enabled the detection of regulatory variation on genome-wide scales and revealed an enormous diversity of regulatory architecture in humans and other species. In this review I summarise the insights gained and questions raised by a decade of genetic mapping of gene expression variation. I discuss recent extensions of this approach using alternative molecular phenotypes that have revealed some of the biological mechanisms that drive gene expression variation between individuals. Finally, I highlight outstanding problems and future directions for development.
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38
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Gemma C, Ramagopalan SV, Down TA, Beyan H, Hawa MI, Holland ML, Hurd PJ, Giovannoni G, Leslie RD, Ebers GC, Rakyan VK. Inactive or moderately active human promoters are enriched for inter-individual epialleles. Genome Biol 2013; 14:R43. [PMID: 23706135 PMCID: PMC4053860 DOI: 10.1186/gb-2013-14-5-r43] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2012] [Accepted: 05/25/2013] [Indexed: 11/13/2022] Open
Abstract
Background Inter-individual epigenetic variation, due to genetic, environmental or random influences, is observed in many eukaryotic species. In mammals, however, the molecular nature of epiallelic variation has been poorly defined, partly due to the restricted focus on DNA methylation. Here we report the first genome-scale investigation of mammalian epialleles that integrates genomic, methylomic, transcriptomic and histone state information. Results First, in a small sample set, we demonstrate that non-genetically determined inter-individual differentially methylated regions (iiDMRs) can be temporally stable over at least 2 years. Then, we show that iiDMRs are associated with changes in chromatin state as measured by inter-individual differences in histone variant H2A.Z levels. However, the correlation of promoter iiDMRs with gene expression is negligible and not improved by integrating H2A.Z information. We find that most promoter epialleles, whether genetically or non-genetically determined, are associated with low levels of transcriptional activity, depleted for housekeeping genes, and either depleted for H3K4me3/enriched for H3K27me3 or lacking both these marks in human embryonic stem cells. The preferential enrichment of iiDMRs at regions of relative transcriptional inactivity validates in a larger independent cohort, and is reminiscent of observations previously made for promoters that undergo hypermethylation in various cancers, in vitro cell culture and ageing. Conclusions Our work identifies potential key features of epiallelic variation in humans, including temporal stability of non-genetically determined epialleles, and concomitant perturbations of chromatin state. Furthermore, our work suggests a novel mechanistic link among inter-individual epialleles observed in the context of normal variation, cancer and ageing.
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Civelek M, Hagopian R, Pan C, Che N, Yang WP, Kayne PS, Saleem NK, Cederberg H, Kuusisto J, Gargalovic PS, Kirchgessner TG, Laakso M, Lusis AJ. Genetic regulation of human adipose microRNA expression and its consequences for metabolic traits. Hum Mol Genet 2013; 22:3023-37. [PMID: 23562819 DOI: 10.1093/hmg/ddt159] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The genetics of messenger RNA (mRNA) expression has been extensively studied in humans and other organisms, but little is known about genetic factors contributing to microRNA (miRNA) expression. We examined natural variation of miRNA expression in adipose tissue in a population of 200 men who have been carefully characterized for metabolic syndrome (MetSyn) phenotypes as part of the Metabolic Syndrome in Men (METSIM) study. We genotyped the subjects using high-density single-nucleotide polymorphism microarrays and quantified the mRNA abundance using genome-wide expression arrays and miRNA abundance using next-generation sequencing. We reliably quantified 356 miRNA species that were expressed in human adipose tissue, a limited number of which made up most of the expressed miRNAs. We mapped the miRNA abundance as an expression quantitative trait and determined cis regulation of expression for nine of the miRNAs and of the processing of one miRNA (miR-28). The degree of genetic variation of miRNA expression was substantially less than that of mRNAs. For the majority of the miRNAs, genetic regulation of expression was independent of the expression of mRNA from which the miRNA is transcribed. We also showed that for 108 miRNAs, mapped reads displayed widespread variation from the canonical sequence. We found a total of 24 miRNAs to be significantly associated with MetSyn traits. We suggest a regulatory role for miR-204-5p which was predicted to inhibit acetyl coenzyme A carboxylase β, a key fatty acid oxidation enzyme that has been shown to play a role in regulating body fat and insulin resistance in adipose tissue.
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Affiliation(s)
- Mete Civelek
- Department of Medicine, University of California, Los Angeles, CA 90095, USA
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40
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van de Bunt M, Gaulton KJ, Parts L, Moran I, Johnson PR, Lindgren CM, Ferrer J, Gloyn AL, McCarthy MI. The miRNA profile of human pancreatic islets and beta-cells and relationship to type 2 diabetes pathogenesis. PLoS One 2013; 8:e55272. [PMID: 23372846 PMCID: PMC3555946 DOI: 10.1371/journal.pone.0055272] [Citation(s) in RCA: 153] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2012] [Accepted: 12/22/2012] [Indexed: 12/21/2022] Open
Abstract
Recent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis. We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility. We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescence-activated cell sorting. In total, 366 miRNAs were found to be expressed (i.e. >100 cumulative reads) in islets and 346 in beta-cells; of the total of 384 unique miRNAs, 328 were shared. A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e. >50% of all reads seen across the tissues) in islets. Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g. miR-27b-3p, miR-192-5p) have not previously been described in the context of islet biology. As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites. We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values <0.01, q-values <0.1). At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants. In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis.
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Affiliation(s)
- Martijn van de Bunt
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kyle J. Gaulton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Leopold Parts
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Donnelly Centre for Cellular and Biomolecular Research, Toronto, Canada
| | - Ignasi Moran
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Paul R. Johnson
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Surgery, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Jorge Ferrer
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Anna L. Gloyn
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
- * E-mail:
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41
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Kilpinen H, Barrett JC. How next-generation sequencing is transforming complex disease genetics. Trends Genet 2013; 29:23-30. [DOI: 10.1016/j.tig.2012.10.001] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2012] [Revised: 09/25/2012] [Accepted: 10/01/2012] [Indexed: 02/02/2023]
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Cheng WC, Chung IF, Huang TS, Chang ST, Sun HJ, Tsai CF, Liang ML, Wong TT, Wang HW. YM500: a small RNA sequencing (smRNA-seq) database for microRNA research. Nucleic Acids Res 2012. [PMID: 23203880 PMCID: PMC3531161 DOI: 10.1093/nar/gks1238] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
MicroRNAs (miRNAs) are small RNAs ∼22 nt in length that are involved in the regulation of a variety of physiological and pathological processes. Advances in high-throughput small RNA sequencing (smRNA-seq), one of the next-generation sequencing applications, have reshaped the miRNA research landscape. In this study, we established an integrative database, the YM500 (http://ngs.ym.edu.tw/ym500/), containing analysis pipelines and analysis results for 609 human and mice smRNA-seq results, including public data from the Gene Expression Omnibus (GEO) and some private sources. YM500 collects analysis results for miRNA quantification, for isomiR identification (incl. RNA editing), for arm switching discovery, and, more importantly, for novel miRNA predictions. Wetlab validation on >100 miRNAs confirmed high correlation between miRNA profiling and RT-qPCR results (R = 0.84). This database allows researchers to search these four different types of analysis results via our interactive web interface. YM500 allows researchers to define the criteria of isomiRs, and also integrates the information of dbSNP to help researchers distinguish isomiRs from SNPs. A user-friendly interface is provided to integrate miRNA-related information and existing evidence from hundreds of sequencing datasets. The identified novel miRNAs and isomiRs hold the potential for both basic research and biotech applications.
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Affiliation(s)
- Wei-Chung Cheng
- Division of Pediatric Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
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