DOCSLIB.ORG

Interplay Between Genetic Predisposition and Diet in Advancing Obesity and Type 2 Diabetes in the Tallyho Mouse Jacaline Parkman [email protected]

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Interplay Between Genetic Predisposition and Diet in Advancing Obesity and Type 2 Diabetes in the Tallyho Mouse Jacaline Parkman Jparkman07@Yahoo.Com Marshall University Marshall Digital Scholar Theses, Dissertations and Capstones 2019 Interplay between genetic predisposition and diet in advancing obesity and type 2 Diabetes in the Tallyho mouse Jacaline Parkman [email protected] Follow this and additional works at: https://mds.marshall.edu/etd Part of the Biochemical Phenomena, Metabolism, and Nutrition Commons, Medical Genetics Commons, and the Medical Nutrition Commons Recommended Citation Parkman, Jacaline, "Interplay between genetic predisposition and diet in advancing obesity and type 2 Diabetes in the Tallyho mouse" (2019). Theses, Dissertations and Capstones. 1211. https://mds.marshall.edu/etd/1211 This Dissertation is brought to you for free and open access by Marshall Digital Scholar. It has been accepted for inclusion in Theses, Dissertations and Capstones by an authorized administrator of Marshall Digital Scholar. For more information, please contact [email protected], [email protected]. INTERPLAY BETWEEN GENETIC PREDISPOSITION AND DIET IN ADVANCING OBESITY AND TYPE 2 DIABETES IN THE TALLYHO MOUSE A dissertation submitted to the Graduate College of Marshall University In partial fulfillment of the requirements for the degree of Doctor of Philosophy In Biomedical Research by Jacaline Parkman Approved by Dr. Jung Han Kim, Committee Chairperson Dr. Eric Blough Dr. Elsa Mangiarua Dr. Travis Salisbury Dr. Nalini Santanam Marshall University May 2019 APPROVAL OF THESIS ii DEDICATION I would like to dedicate this dissertation to my parents Rob and Hye Kyong and my brothers Chris and Clay. Without you guys I would not have made it this far. I love you all. iii ACKNOWLEDGMENTS I first must thank my mentor Dr. Kim. She is an incredible, patient, and hardworking scientist who was always available to me when I had a question or needed any kind of help. She was very understanding with both professional and personal related matters and it was because of her I decided to pursue a PhD at Marshall University. I would also like to acknowledge the members of my committee along with Dr. Kim: Dr. Blough, Dr. Mangiarua, Dr. Salisbury, and Dr. Santanam. As a committee you have created a supportive and intellectually challenging environment that has shaped me into the scientist I am today. I would also like to give an extra thank you to Dr. Mangiarua for being my faculty mentor and helping with the adjustment from undergraduate to graduate school. Thank you to my entire committee for all your help and support. I would like to thank my friends for all their support as well. Be it advice, borrowed equipment, study groups, study breaks involving wine, or reviewing and editing work, thank you Molly Butts, Laura Kutz, Rachel Murphy, and Shreya Mukherji. I couldn’t have done this without you. iv TABLE OF CONTENTS APPROVAL OF THESIS ............................................................................................................... ii DEDICATION ............................................................................................................................... iii ACKNOWLEDGMENTS ............................................................................................................. iv List of Tables .................................................................................................................................. x List of Figures ................................................................................................................................ xi Abstract ......................................................................................................................................... xii Chapter 1 ......................................................................................................................................... 1 Introduction ......................................................................................................................... 1 Abstract ................................................................................................................... 1 The Scope of the Problem ....................................................................................... 1 Adipose Tissue ........................................................................................................ 2 Brown Adipose Tissue (BAT) ................................................................................ 3 White Adipose Tissue (WAT): ............................................................................... 4 Adipocyte Development ......................................................................................... 6 Causes of Obesity ................................................................................................... 7 Genetics................................................................................................................... 7 Environment ............................................................................................................ 9 Gene-Diet Interaction............................................................................................ 13 Pathogenesis of obesity ......................................................................................... 15 Adipose Tissue Dysfunction and Obesity ............................................................. 17 Inflammation ......................................................................................................... 18 Inflammation in Healthy Adipose ......................................................................... 18 v Inflammation in Obesity ....................................................................................... 18 Mitochondria ......................................................................................................... 20 Mitochondria in Healthy Adipose Tissue ............................................................. 20 Mitochondrial Dysfunction in Obesity ................................................................. 21 Insulin Resistance ................................................................................................. 22 Treatment of obesity ............................................................................................. 23 Type 2 Diabetes .................................................................................................... 25 Causes of Type 2 Diabetes .................................................................................... 25 Genetics................................................................................................................. 25 Environment .......................................................................................................... 26 Pathophysiology of T2D ....................................................................................... 27 Beta-cell dysfunction ............................................................................................ 27 Insulin resistance ................................................................................................... 28 Treatment of Type 2 Diabetes ............................................................................... 28 Animal Models for Obesity Research ................................................................... 29 Objectives of the study.......................................................................................... 31 Chapter 2 ....................................................................................................................................... 33 Genotype-dependent metabolic responses to semi-purified high-sucrose high-fat diets in the TALLYHO/Jng vs. C57BL/6 mouse during the development of obesity and type 2 diabetes ............................................................................................................................. 33 Abstract ................................................................................................................. 34 Introduction ........................................................................................................... 34 Materials and Methods .......................................................................................... 36 vi Animals and diets .................................................................................................. 36 Body composition ................................................................................................. 36 Intraperitoneal glucose tolerance test.................................................................... 36 Non-fasting glucose, triglyceride, total cholesterol, and insulin levels in the circulation ............................................................................................................. 37 Indirect calorimetry, locomotor activity, and food intake .................................... 37 Real-time quantitative RT-PCR ............................................................................ 37 Statistical analysis ................................................................................................. 38 Results ................................................................................................................... 38 Body weight and body fat changes ....................................................................... 39 Intraperitoneal glucose tolerance test.................................................................... 42 Indirect calorimetry, locomotor activity, and food intake .................................... 43 Circulating glucose,
Load more

Recommended publications
  • Maternal Overnutrition Programs Hedonic and Metabolic Phenotypes Across Generations Through Sperm Tsrnas
    Maternal overnutrition programs hedonic and metabolic phenotypes across generations through sperm tsRNAs Gitalee Sarkera, Wenfei Suna, David Rosenkranzb, Pawel Pelczarc, Lennart Opitzd, Vissarion Efthymioua, Christian Wolfruma, and Daria Peleg-Raibsteina,1 aLaboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, 8603 Schwerzenbach, Switzerland; bInstitute of Anthropology, Johannes Gutenberg University Mainz, 55099 Mainz, Germany; cCenter for Transgenic Models, University of Basel, 3350 Basel, Switzerland; and dFunctional Genomics Center Zurich, ETH Zurich, 8057 Zurich, Switzerland Edited by Nathaniel Heintz, The Rockefeller University, New York, NY, and approved April 11, 2019 (received for review December 10, 2018) There is a growing body of evidence linking maternal overnutri- altered hedonic and obesogenic phenotypes (12, 13). Similar to tion to obesity and psychopathology that can be conserved across other early nutritional animal models, we have observed only multiple generations. Recently, we demonstrated in a maternal moderate changes in CpG methylation in F1 (first-generation) high-fat diet (HFD; MHFD) mouse model that MHFD induced and F2 (second-generation) sperm between the offspring groups enhanced hedonic behaviors and obesogenic phenotypes that (13–15). This suggests that sperm methylome might not constitute were conserved across three generations via the paternal lineage, the principal mode of transmission of these phenotypes. which was independent of sperm methylome changes. Here, we Although changes in DNA methylation pattern and histone show that sperm tRNA-derived small RNAs (tsRNAs) partly contrib- modifications have been reported following a range of early-life ute to the transmission of such phenotypes. We observe increased environmental exposures (14, 16–19), a causal link between the expression of sperm tsRNAs in the F1 male offspring born to HFD- germ cell epigenetic marks and the observed phenotypes in the exposed dams.
    [Show full text]
  • Analysis of Gene Expression Data for Gene Ontology
    ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins.
    [Show full text]
  • Datasheet: VMA00439 Product Details
    Datasheet: VMA00439 Description: MOUSE ANTI ACBD3 Specificity: ACBD3 Format: Purified Product Type: PrecisionAb™ Monoclonal Clone: 5F9 Isotype: IgG1 Quantity: 100 µl Product Details Applications This product has been reported to work in the following applications. This information is derived from testing within our laboratories, peer-reviewed publications or personal communications from the originators. Please refer to references indicated for further information. For general protocol recommendations, please visit www.bio-rad-antibodies.com/protocols. Yes No Not Determined Suggested Dilution Western Blotting 1/1000 PrecisionAb antibodies have been extensively validated for the western blot application. The antibody has been validated at the suggested dilution. Where this product has not been tested for use in a particular technique this does not necessarily exclude its use in such procedures. Further optimization may be required dependant on sample type. Target Species Human Species Cross Reacts with: Rat Reactivity N.B. Antibody reactivity and working conditions may vary between species. Product Form Purified IgG - liquid Preparation Mouse monoclonal antibody purified by affinity chromatography from ascites Buffer Solution Phosphate buffered saline Preservative 0.09% Sodium Azide (NaN3) Stabilisers 1% Bovine Serum Albumin 50% Glycerol Immunogen Full length recombinant human ACBD3 (NP_073572) produced in HEK293T cells External Database Links UniProt: Q9H3P7 Related reagents Entrez Gene: 64746 ACBD3 Related reagents Page 1 of 2 Synonyms GCP60, GOCAP1, GOLPH1 Specificity Mouse anti Human ACBD3 antibody recognizes ACBD3, also known as PBR- and PKA-associated protein 7, PKA (RIalpha)-associated protein, acyl-Coenzyme A binding domain containing 3, golgi complex associated protein 1 60kDa, golgi phosphoprotein 1 and peripheral benzodiazepine receptor-associated protein PAP7.
    [Show full text]
  • Overnutrition, Ectopic Lipid and the Metabolic Syndrome Scott M Grundy
    Review Overnutrition, ectopic lipid and the metabolic syndrome Scott M Grundy Correspondence to ABSTRACT metabolic processes and predisposes to meta- Dr Scott M Grundy, Internal The metabolic syndrome is a constellation of bolic risk factors.6 Excess lipid in adipose tissue Medicine, UT Southwestsern Medical Center, Dallas, TX metabolic risk factors including atherogenic is called obesity; in other tissues, it is called 75390-9052, USA; scott. dyslipidemia (elevated serum triglycerides, reduced ectopic lipid. In this document, overnutrition [email protected] high-density lipoprotein (HDL) cholesterol), elevated will be defined as the any excess of nutrient blood pressure, dysglycemia (insulin resistance and energy that causes ectopic lipid accumulation Accepted 29 April 2016 elevated serum glucose), a pro-inflammatory state, outside adipose tissue. The essential pathways Published Online First 18 May 2016 and a prothrombotic state. Most persons with whereby overnutrition drives development of metabolic syndrome are obese, and usually have ectopic lipid are shown in figure 1. Excess Copyright © 2016 American fl Federation for Medical abdominal obesity. Generally, obesity is a re ection nutrients come from either dietary triglyceride Research of overnutrition. A current view is that when adipose or carbohydrate. Dietary triglyceride enters the tissue fails to store all excess nutrients as circulation with chylomicrons. Triglycerides are triglyceride, lipid begins to accumulate in various hydrolyzed to fatty acids by lipoprotein lipase tissues (eg, muscle, liver, pancreas, and heart). (LPL); and most of released fatty acids enter This accumulation is called ectopic lipid. Various adipose tissue, where they are re-esterified to mechanisms have been proposed whereby ectopic triglyceride. A portion of fatty acids released by lipid is detrimental in different tissues; these LPL bypasses adipose tissue and enters a variety derangements induce metabolic risk factors.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Genetic Testing for Familial Alzheimer's Disease
    Corporate Medical Policy Genetic Testing for Familial Alzheimer’s Disease AHS – M2038 File Name: genetic_testing_for_familial_alzheimers_disease Origination: 1/2019 Last CAP Review: 10/2020 Next CAP Review: 10/2021 Last Review: 10/2020 Description of Procedure or Service Alzheimer disease (AD) is a neurodegenerative disease defined by a gradual decline in memory, cognitive functions, gross atrophy of the brain, and an accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles (Karch, Cruchaga, & Goate, 2014). Familial Alzheimer disease (FAD) is a rare, inherited form of AD. FAD has a much earlier onset than other forms of Alzheimer disease with symptoms developing in individuals in their thirties or forties. Related Policies General Genetic Testing, Germline Disorders AHS – M2145 General Genetic Testing, Somatic Disorders AHS – M2146 ***Note: This Medical Policy is complex and technical. For questions concerning the technical language and/or specific clinical indications for its use, please consult your physician. Policy BCBSNC will provide coverage for genetic testing for familial Alzheimer disease when it is determined the medical criteria or reimbursement guidelines below are met. Benefits Application This medical policy relates only to the services or supplies described herein. Please refer to the Member's Benefit Booklet for availability of benefits. Member's benefits may vary according to benefit design; therefore member benefit language should be reviewed before applying the terms of this medical policy.
    [Show full text]
  • Knock-Out of ACBD3 Leads to Dispersed Golgi Structure, but Unaffected Mitochondrial Functions in HEK293 and Hela Cells
    International Journal of Molecular Sciences Article Knock-Out of ACBD3 Leads to Dispersed Golgi Structure, but Unaffected Mitochondrial Functions in HEK293 and HeLa Cells Tereza Da ˇnhelovská 1 , Lucie Zdražilová 1 , Hana Štufková 1, Marie Vanišová 1, Nikol Volfová 1, Jana Kˇrížová 1 , OndˇrejKuda 2 , Jana Sládková 1 and Markéta Tesaˇrová 1,* 1 Department of Paediatrics and Inherited Metabolic Disorders, Charles University, First Faculty of Medicine and General University Hospital in Prague, 128 01 Prague, Czech Republic; [email protected] (T.D.); [email protected] (L.Z.); [email protected] (H.Š.); [email protected] (M.V.); [email protected] (N.V.); [email protected] (J.K.); [email protected] (J.S.) 2 Institute of Physiology, Academy of Sciences of the Czech Republic, 142 00 Prague, Czech Republic; [email protected] * Correspondence: [email protected] Abstract: The Acyl-CoA-binding domain-containing protein (ACBD3) plays multiple roles across the cell. Although generally associated with the Golgi apparatus, it operates also in mitochondria. In steroidogenic cells, ACBD3 is an important part of a multiprotein complex transporting cholesterol into mitochondria. Balance in mitochondrial cholesterol is essential for proper mitochondrial protein biosynthesis, among others. We generated ACBD3 knock-out (ACBD3-KO) HEK293 and HeLa cells and characterized the impact of protein absence on mitochondria, Golgi, and lipid profile. In ACBD3- Citation: Daˇnhelovská,T.; KO cells, cholesterol level and mitochondrial structure and functions are not altered, demonstrating Zdražilová, L.; Štufková, H.; that an alternative pathway of cholesterol transport into mitochondria exists. However, ACBD3- Vanišová, M.; Volfová, N.; Kˇrížová,J.; Kuda, O.; Sládková, J.; Tesaˇrová,M.
    [Show full text]
  • Nutritional Strategy for Adolescents Undergoing Bariatric Surgery: Report of a Working Group of the Nutrition Committee of NASPGHAN/NACHRI
    CLINICAL GUIDELINE Nutritional Strategy for Adolescents Undergoing Bariatric Surgery: Report of a Working Group of the Nutrition Committee of NASPGHAN/NACHRI ÃMichell A. Fullmer, yStephanie H. Abrams, zKathleen Hrovat, §Lori Mooney, jjAnn O. Scheimann, zJennifer B. Hillman, and ôDavid L. Suskind ABSTRACT besity seen during adolescence is a multifactorial process Surgical options for the treatment of adolescent obesity have been gaining with several contributing factors, including metabolic dys- popularity. Adolescent patients present a particular challenge to clinicians, O secondary to age-related issues, revolving around both mental and physical regulation, genes, environmental/socioeconomic stressors, and growth. These age-related issues require a unique approach to nutritional energy imbalance (1). Patients with obesity carry an increased intervention for adolescents undergoing bariatric surgery as opposed to morbidity and are at risk for obstructive sleep apnea, metabolic standardized approaches for adults. Despite the increasing numbers of syndrome, orthopedic issues, hypertension, type 2 diabetes, and adolescents undergoing obesity surgery, evidence-based nutritional guide- nonalcoholic steatohepatitis (1,2). These comorbid conditions lines have yet to be published. The goal of this document is to provide the affect an adolescent’s quality of life and daily functioning (3). clinician with recommendations on how to assess, educate, nourish, and The obesity rates of children ages 2 to 19 are now 17.6%, with monitor the adolescent who has undergone obesity surgery. A multidisci- plinary panel composed of 3 pediatric gastroenterologists, 1 psychologist, obesity being classified as a body mass index (BMI) above the 95th and 3 registered dietitians from the Nutrition Committee for the North percentile (4).
    [Show full text]
  • Chuanxiong Rhizoma Compound on HIF-VEGF Pathway and Cerebral Ischemia-Reperfusion Injury’S Biological Network Based on Systematic Pharmacology
    ORIGINAL RESEARCH published: 25 June 2021 doi: 10.3389/fphar.2021.601846 Exploring the Regulatory Mechanism of Hedysarum Multijugum Maxim.-Chuanxiong Rhizoma Compound on HIF-VEGF Pathway and Cerebral Ischemia-Reperfusion Injury’s Biological Network Based on Systematic Pharmacology Kailin Yang 1†, Liuting Zeng 1†, Anqi Ge 2†, Yi Chen 1†, Shanshan Wang 1†, Xiaofei Zhu 1,3† and Jinwen Ge 1,4* Edited by: 1 Takashi Sato, Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of 2 Tokyo University of Pharmacy and Life Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China, Galactophore Department, The First 3 Sciences, Japan Hospital of Hunan University of Chinese Medicine, Changsha, China, School of Graduate, Central South University, Changsha, China, 4Shaoyang University, Shaoyang, China Reviewed by: Hui Zhao, Capital Medical University, China Background: Clinical research found that Hedysarum Multijugum Maxim.-Chuanxiong Maria Luisa Del Moral, fi University of Jaén, Spain Rhizoma Compound (HCC) has de nite curative effect on cerebral ischemic diseases, *Correspondence: such as ischemic stroke and cerebral ischemia-reperfusion injury (CIR). However, its Jinwen Ge mechanism for treating cerebral ischemia is still not fully explained. [email protected] †These authors share first authorship Methods: The traditional Chinese medicine related database were utilized to obtain the components of HCC. The Pharmmapper were used to predict HCC’s potential targets. Specialty section: The CIR genes were obtained from Genecards and OMIM and the protein-protein This article was submitted to interaction (PPI) data of HCC’s targets and IS genes were obtained from String Ethnopharmacology, a section of the journal database.
    [Show full text]
  • Enzyme DHRS7
    Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d.
    [Show full text]
  • Supplemental Information
    Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.
    [Show full text]
  • About the Existence of Common Determinants of Gene Expression In
    González-Prendes et al. BMC Genomics (2019) 20:518 https://doi.org/10.1186/s12864-019-5889-5 RESEARCH ARTICLE Open Access About the existence of common determinants of gene expression in the porcine liver and skeletal muscle Rayner González-Prendes1,6†, Emilio Mármol-Sánchez1†, Raquel Quintanilla2, Anna Castelló1,3, Ali Zidi1, Yuliaxis Ramayo-Caldas1, Tainã Figueiredo Cardoso1,4, Arianna Manunza1,ÁngelaCánovas1,5 and Marcel Amills 1,3* Abstract Background: The comparison of expression QTL (eQTL) maps obtained in different tissues is an essential step to understand how gene expression is genetically regulated in a context-dependent manner. In the current work, we have compared the transcriptomic and eQTL profiles of two porcine tissues (skeletal muscle and liver) which typically show highly divergent expression profiles, in 103 Duroc pigs genotyped with the Porcine SNP60 BeadChip (Illumina) and with available microarray-based measurements of hepatic and muscle mRNA levels. Since structural variation could have effects on gene expression, we have also investigated the co-localization of cis-eQTLs with copy number variant regions (CNVR) segregating in this Duroc population. Results: The analysis of differential expresssion revealed the existence of 1204 and 1490 probes that were overexpressed and underexpressed in the gluteus medius muscle when compared to liver, respectively (|fold- change| > 1.5, q-value < 0.05). By performing genome scans in 103 Duroc pigs with available expression and genotypic data, we identified 76 and 28 genome-wide significant cis-eQTLs regulating gene expression in the gluteus medius muscle and liver, respectively. Twelve of these cis-eQTLs were shared by both tissues (i.e.
    [Show full text]