Evolutionarily Conserved Regulation of Embryonic Fast-Twitch Skeletal Muscle
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Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives
Journal of Heredity 2007:98(2):115–122 ª The American Genetic Association. 2007. All rights reserved. doi:10.1093/jhered/esl064 For permissions, please email: [email protected]. Advance Access publication January 5, 2007 Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives BRET A. PAYSEUR AND MICHAEL PLACE From the Laboratory of Genetics, University of Wisconsin, Madison, WI 53706. Address correspondence to the author at the address above, or e-mail: [email protected]. Abstract Identification of the genes that underlie reproductive isolation provides important insights into the process of speciation. According to the Dobzhansky–Muller model, these genes suffer disrupted interactions in hybrids due to independent di- vergence in separate populations. In hybrid populations, natural selection acts to remove the deleterious heterospecific com- binations that cause these functional disruptions. When selection is strong, this process can maintain multilocus associations, primarily between conspecific alleles, providing a signature that can be used to locate incompatibilities. We applied this logic to populations of house mice that were formed by hybridization involving two species that show partial reproductive isolation, Mus domesticus and Mus musculus. Using molecular markers likely to be informative about species ancestry, we scanned the genomes of 1) classical inbred strains and 2) recombinant inbred lines for pairs of loci that showed extreme linkage disequi- libria. By using the same set of markers, we identified a list of locus pairs that displayed similar patterns in both scans. These genomic regions may contain genes that contribute to reproductive isolation between M. domesticus and M. -
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. -
Genome Analysis and Knowledge
Dahary et al. BMC Medical Genomics (2019) 12:200 https://doi.org/10.1186/s12920-019-0647-8 SOFTWARE Open Access Genome analysis and knowledge-driven variant interpretation with TGex Dvir Dahary1*, Yaron Golan1, Yaron Mazor1, Ofer Zelig1, Ruth Barshir2, Michal Twik2, Tsippi Iny Stein2, Guy Rosner3,4, Revital Kariv3,4, Fei Chen5, Qiang Zhang5, Yiping Shen5,6,7, Marilyn Safran2, Doron Lancet2* and Simon Fishilevich2* Abstract Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient’s phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex’s main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex’s broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards’ recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. -
Sarcomeric Deficits Underlie MYBPC1-Associated Myopathy with Myogenic Tremor
Sarcomeric deficits underlie MYBPC1-associated myopathy with myogenic tremor Janelle Geist Hauserman, … , Christopher Ward, Aikaterini Kontrogianni- Konstantopoulos JCI Insight. 2021. https://doi.org/10.1172/jci.insight.147612. Research In-Press Preview Cell biology Muscle biology Myosin Binding Protein-C slow (sMyBP-C) comprises a subfamily of cytoskeletal proteins encoded byM YBPC1 that is expressed in skeletal muscles where it contributes to myosin thick filament stabilization and actomyosin cross-bridge regulation. Recently, our group described the causal association of dominant missense pathogenic variants in MYBPC1 with an early-onset myopathy characterized by generalized muscle weakness, hypotonia, dysmorphia, skeletal deformities, and myogenic tremor occurring in the absence of neuropathy. To mechanistically interrogate the etiologies of this MYBPC1-associated myopathy in vivo, we generated a knock-in mouse model carrying the E248K pathogenic variant. Using a battery of phenotypic, behavioral, and physiological measurements spanning neonatal to young adult life, we find that heterozygous E248K mice faithfully recapitulate the onset and progression of generalized myopathy, tremor occurrence, and skeletal deformities seen in human carriers. Moreover, using a combination of biochemical, ultrastructural, and contractile assessments at the level of the tissue, cell, and myofilaments, we show that the loss-of- function phenotype observed in mutant muscles is primarily driven by disordered and misaligned sarcomeres containing fragmented -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
Variation in Protein Coding Genes Identifies Information
bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number. -
Research Article Microarray-Based Comparisons of Ion Channel Expression Patterns: Human Keratinocytes to Reprogrammed Hipscs To
Hindawi Publishing Corporation Stem Cells International Volume 2013, Article ID 784629, 25 pages http://dx.doi.org/10.1155/2013/784629 Research Article Microarray-Based Comparisons of Ion Channel Expression Patterns: Human Keratinocytes to Reprogrammed hiPSCs to Differentiated Neuronal and Cardiac Progeny Leonhard Linta,1 Marianne Stockmann,1 Qiong Lin,2 André Lechel,3 Christian Proepper,1 Tobias M. Boeckers,1 Alexander Kleger,3 and Stefan Liebau1 1 InstituteforAnatomyCellBiology,UlmUniversity,Albert-EinsteinAllee11,89081Ulm,Germany 2 Institute for Biomedical Engineering, Department of Cell Biology, RWTH Aachen, Pauwelstrasse 30, 52074 Aachen, Germany 3 Department of Internal Medicine I, Ulm University, Albert-Einstein Allee 11, 89081 Ulm, Germany Correspondence should be addressed to Alexander Kleger; [email protected] and Stefan Liebau; [email protected] Received 31 January 2013; Accepted 6 March 2013 Academic Editor: Michael Levin Copyright © 2013 Leonhard Linta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Ion channels are involved in a large variety of cellular processes including stem cell differentiation. Numerous families of ion channels are present in the organism which can be distinguished by means of, for example, ion selectivity, gating mechanism, composition, or cell biological function. To characterize the distinct expression of this group of ion channels we have compared the mRNA expression levels of ion channel genes between human keratinocyte-derived induced pluripotent stem cells (hiPSCs) and their somatic cell source, keratinocytes from plucked human hair. This comparison revealed that 26% of the analyzed probes showed an upregulation of ion channels in hiPSCs while just 6% were downregulated. -
Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals
animals Review Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals Mohammadreza Mohammadabadi 1 , Farhad Bordbar 1,* , Just Jensen 2 , Min Du 3 and Wei Guo 4 1 Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman 77951, Iran; [email protected] 2 Center for Quantitative Genetics and Genomics, Aarhus University, 8210 Aarhus, Denmark; [email protected] 3 Washington Center for Muscle Biology, Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; [email protected] 4 Muscle Biology and Animal Biologics, Animal and Dairy Science, University of Wisconsin-Madison, Madison, WI 53558, USA; [email protected] * Correspondence: [email protected] Simple Summary: Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of in- creasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale. Citation: Mohammadabadi, M.; Abstract: Farm-animal species play crucial roles in satisfying demands for meat on a global scale, Bordbar, F.; Jensen, J.; Du, M.; Guo, W. -
Transcriptomic Profiling of Ca Transport Systems During
cells Article Transcriptomic Profiling of Ca2+ Transport Systems during the Formation of the Cerebral Cortex in Mice Alexandre Bouron Genetics and Chemogenomics Lab, Université Grenoble Alpes, CNRS, CEA, INSERM, Bâtiment C3, 17 rue des Martyrs, 38054 Grenoble, France; [email protected] Received: 29 June 2020; Accepted: 24 July 2020; Published: 29 July 2020 Abstract: Cytosolic calcium (Ca2+) transients control key neural processes, including neurogenesis, migration, the polarization and growth of neurons, and the establishment and maintenance of synaptic connections. They are thus involved in the development and formation of the neural system. In this study, a publicly available whole transcriptome sequencing (RNA-Seq) dataset was used to examine the expression of genes coding for putative plasma membrane and organellar Ca2+-transporting proteins (channels, pumps, exchangers, and transporters) during the formation of the cerebral cortex in mice. Four ages were considered: embryonic days 11 (E11), 13 (E13), and 17 (E17), and post-natal day 1 (PN1). This transcriptomic profiling was also combined with live-cell Ca2+ imaging recordings to assess the presence of functional Ca2+ transport systems in E13 neurons. The most important Ca2+ routes of the cortical wall at the onset of corticogenesis (E11–E13) were TACAN, GluK5, nAChR β2, Cav3.1, Orai3, transient receptor potential cation channel subfamily M member 7 (TRPM7) non-mitochondrial Na+/Ca2+ exchanger 2 (NCX2), and the connexins CX43/CX45/CX37. Hence, transient receptor potential cation channel mucolipin subfamily member 1 (TRPML1), transmembrane protein 165 (TMEM165), and Ca2+ “leak” channels are prominent intracellular Ca2+ pathways. The Ca2+ pumps sarco/endoplasmic reticulum Ca2+ ATPase 2 (SERCA2) and plasma membrane Ca2+ ATPase 1 (PMCA1) control the resting basal Ca2+ levels. -
Gene Expression During Normal and FSHD Myogenesis Tsumagari Et Al
Gene expression during normal and FSHD myogenesis Tsumagari et al. Tsumagari et al. BMC Medical Genomics 2011, 4:67 http://www.biomedcentral.com/1755-8794/4/67 (27 September 2011) Tsumagari et al. BMC Medical Genomics 2011, 4:67 http://www.biomedcentral.com/1755-8794/4/67 RESEARCHARTICLE Open Access Gene expression during normal and FSHD myogenesis Koji Tsumagari1, Shao-Chi Chang1, Michelle Lacey2,3, Carl Baribault2,3, Sridar V Chittur4, Janet Sowden5, Rabi Tawil5, Gregory E Crawford6 and Melanie Ehrlich1,3* Abstract Background: Facioscapulohumeral muscular dystrophy (FSHD) is a dominant disease linked to contraction of an array of tandem 3.3-kb repeats (D4Z4) at 4q35. Within each repeat unit is a gene, DUX4, that can encode a protein containing two homeodomains. A DUX4 transcript derived from the last repeat unit in a contracted array is associated with pathogenesis but it is unclear how. Methods: Using exon-based microarrays, the expression profiles of myogenic precursor cells were determined. Both undifferentiated myoblasts and myoblasts differentiated to myotubes derived from FSHD patients and controls were studied after immunocytochemical verification of the quality of the cultures. To further our understanding of FSHD and normal myogenesis, the expression profiles obtained were compared to those of 19 non-muscle cell types analyzed by identical methods. Results: Many of the ~17,000 examined genes were differentially expressed (> 2-fold, p < 0.01) in control myoblasts or myotubes vs. non-muscle cells (2185 and 3006, respectively) or in FSHD vs. control myoblasts or myotubes (295 and 797, respectively). Surprisingly, despite the morphologically normal differentiation of FSHD myoblasts to myotubes, most of the disease-related dysregulation was seen as dampening of normal myogenesis- specific expression changes, including in genes for muscle structure, mitochondrial function, stress responses, and signal transduction. -
Stem Cells and Ion Channels
Stem Cells International Stem Cells and Ion Channels Guest Editors: Stefan Liebau, Alexander Kleger, Michael Levin, and Shan Ping Yu Stem Cells and Ion Channels Stem Cells International Stem Cells and Ion Channels Guest Editors: Stefan Liebau, Alexander Kleger, Michael Levin, and Shan Ping Yu Copyright © 2013 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “Stem Cells International.” All articles are open access articles distributed under the Creative Com- mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editorial Board Nadire N. Ali, UK Joseph Itskovitz-Eldor, Israel Pranela Rameshwar, USA Anthony Atala, USA Pavla Jendelova, Czech Republic Hannele T. Ruohola-Baker, USA Nissim Benvenisty, Israel Arne Jensen, Germany D. S. Sakaguchi, USA Kenneth Boheler, USA Sue Kimber, UK Paul R. Sanberg, USA Dominique Bonnet, UK Mark D. Kirk, USA Paul T. Sharpe, UK B. Bunnell, USA Gary E. Lyons, USA Ashok Shetty, USA Kevin D. Bunting, USA Athanasios Mantalaris, UK Igor Slukvin, USA Richard K. Burt, USA Pilar Martin-Duque, Spain Ann Steele, USA Gerald A. Colvin, USA EvaMezey,USA Alexander Storch, Germany Stephen Dalton, USA Karim Nayernia, UK Marc Turner, UK Leonard M. Eisenberg, USA K. Sue O’Shea, USA Su-Chun Zhang, USA Marina Emborg, USA J. Parent, USA Weian Zhao, USA Josef Fulka, Czech Republic Bruno Peault, USA Joel C. Glover, Norway Stefan Przyborski, UK Contents Stem Cells and Ion Channels, Stefan Liebau,