Rare Non-Coding Variation Identified by Large Scale Whole Genome Sequencing Reveals
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Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. -
Human Lectins, Their Carbohydrate Affinities and Where to Find Them
biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body. -
Identification of Potential Pathogenic Genes Associated with Osteoporosis
610.BJBJR0010.1302/2046-3758.612.BJR-2017-0102 research-article2017 Freely available online OPEN ACCESS BJR RESEARCH Identification of potential pathogenic genes associated with osteoporosis Objectives B. Xia, Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteo- Y. Li, porosis. J. Zhou, Methods B. Tian, Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples L. Feng and 62 control blood samples, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in osteoporosis using Limma pack- Jining No. 1 People’s age (3.2.1) and Meta-MA packages. Gene Ontology and Kyoto Encyclopedia of Genes and Hospital, Jining, Genomes enrichment analyses were performed to identify biological functions. Further- Shandong Province, more, the transcriptional regulatory network was established between the top 20 DEGs and China transcriptional factors using the UCSC ENCODE Genome Browser. Receiver operating char- acteristic (ROC) analysis was applied to investigate the diagnostic value of several DEGs. Results A total of 1320 DEGs were obtained, of which 855 were up-regulated and 465 were down- regulated. These differentially expressed genes were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, mainly associated with gene expres- sion and osteoclast differentiation. In the transcriptional regulatory network, there were 6038 interactions pairs involving 88 transcriptional factors. In addition, the quantitative reverse transcriptase-polymerase chain reaction result validated the expression of several genes (VPS35, FCGR2A, TBCA, HIRA, TYROBP, and JUND). Finally, ROC analyses showed that VPS35, HIRA, PHF20 and NFKB2 had a significant diagnostic value for osteoporosis. -
Tissue-Specific Alteration of Metabolic Pathways Influences Glycemic Regulation
bioRxiv preprint doi: https://doi.org/10.1101/790618; this version posted October 3, 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 4.0 International license. Tissue-Specific Alteration of Metabolic Pathways Influences Glycemic Regulation 1,2 3 4 5,6,7 Natasha H. J. Ng *, Sara M. Willems *, Juan Fernandez , Rebecca S. Fine , Eleanor Wheeler8,3, Jennifer Wessel9,10, Hidetoshi Kitajima4, Gaelle Marenne8, Jana K. Rundle1, Xueling Sim11,12, Hanieh Yeghootkar13, Nicola L. Beer1, Anne Raimondo1, Andrei I. Tarasov1, Soren K. Thomsen1,14, Martijn van de Bunt4,1, Shuai Wang15, Sai Chen12, Yuning Chen15, Yii-Der Ida Chen16, Hugoline G. de Haan17, Niels Grarup18, Ruifang Li-Gao17, Tibor V. Varga19, Jennifer L Asimit8,20, Shuang Feng21, Rona J. Strawbridge22,23, Erica L. Kleinbrink24, Tarunveer S. Ahluwalia25,26, Ping An27, Emil V. Appel18, Dan E Arking28, Juha Auvinen29,30, Lawrence F. Bielak31, Nathan A. Bihlmeyer28, Jette Bork-Jensen18, Jennifer A. Brody32,33, Archie Campbell34, Audrey Y Chu35, Gail Davies36,37, Ayse Demirkan38, James S. Floyd32,33, Franco Giulianini35, Xiuqing Guo16, Stefan Gustafsson39, Benoit Hastoy1, Anne U. Jackson12, Johanna Jakobsdottir40, Marjo-Riitta Jarvelin41,29,42, Richard A. Jensen32,33, Stavroula Kanoni43, Sirkka Keinanen- Kiukaanniemi44,45, Jin Li46, Man Li47,48, Kurt Lohman49, Yingchang Lu50,51, Jian'an Luan3, Alisa K. Manning52,53, Jonathan Marten54, Carola Marzi55,56, Karina Meidtner57,56, Dennis O. Mook- Kanamori17,58, Taulant Muka59,38, Giorgio Pistis60,61, Bram Prins8, Kenneth M. -
Tumor Suppressive Microrna-375 Regulates Oncogene AEG-1&Sol;MTDH in Head and Neck Squamous Cell Carcinoma (HNSCC)
Journal of Human Genetics (2011) 56, 595–601 & 2011 The Japan Society of Human Genetics All rights reserved 1434-5161/11 $32.00 www.nature.com/jhg ORIGINAL ARTICLE Tumor suppressive microRNA-375 regulates oncogene AEG-1/MTDH in head and neck squamous cell carcinoma (HNSCC) Nijiro Nohata1,2, Toyoyuki Hanazawa2, Naoko Kikkawa1,2, Muradil Mutallip1,2, Daiju Sakurai2, Lisa Fujimura3, Kazumori Kawakami4, Takeshi Chiyomaru4, Hirofumi Yoshino4, Hideki Enokida4, Masayuki Nakagawa4, Yoshitaka Okamoto2 and Naohiko Seki1 Our microRNA (miRNA) expression signatures of hypopharyngeal squamous cell carcinoma, maxillary sinus squamous cell carcinoma and esophageal squamous cell carcinoma revealed that miR-375 was significantly reduced in cancer tissues compared with normal epithelium. In this study, we focused on the functional significance of miR-375 in cancer cells and identification of miR-375-regulated novel cancer networks in head and neck squamous cell carcinoma (HNSCC). Restoration of miR-375 showed significant inhibition of cell proliferation and induction of cell apoptosis in SAS and FaDu cell lines, suggesting that miR-375 functions as a tumor suppressor. We adopted genome-wide gene expression analysis to search for miR-375-regulated molecular targets. Gene expression data and luciferase reporter assays revealed that AEG-1/MTDH was directly regulated by miR-375. Cancer cell proliferation was significantly inhibited in HNSCC cells transfected with si-AEG-1/MTDH. In addition, expression levels of AEG-1/MTDH were significantly upregulated in cancer tissues. Therefore, AEG-1/MTDH may function as an oncogene in HNSCC. The identification of novel tumor suppressive miRNA and its regulated cancer pathways could provide new insights into potential molecular mechanisms of HNSCC oncogenesis. -
ORM-Like Protein (ORMDL) – Annäherung an Die Funktion Über Die Interaktion
ORM-like protein (ORMDL) - Annäherung an die Funktion über die Interaktion Julian Klingbeil München 2019 Aus der Kinderklinik und Kinderpoliklinik im Dr. von Haunerschen Kinderspital der Ludwig–Maximilians–Universität München Direktor: Prof. Dr. med. Dr. sci. nat. C. Klein ORM-like protein (ORMDL) – Annäherung an die Funktion über die Interaktion Dissertation zum Erwerb des Doktorgrades der Medizin an der Medizinischen Fakultät der Ludwig–Maximilians–Universität zu München vorgelegt von Julian Malte Klingbeil aus Berlin 2019 Mit Genehmigung der Medizinischen Fakultät der Universität München Berichterstatterin: Prof. Dr. Ania Muntau Mitberichterstatter: Prof. Dr. Katja Radon PD Dr. Anne Hilgendorff Prof. Dr. Jürgen Behr Prof. Dr. Ortrud Steinlein Mitbetreuung durch den promovierten Mitarbeiter: Prof. Dr. Søren Gersting Dekan: Prof. Dr. med. dent. Reinhard Hickel Tag der mündlichen Prüfung: 10.10.2019 Inhaltsverzeichnis Zusammenfassung xiii 1 Einleitung 1 1.1 Asthma bronchiale . .1 1.1.1 Epidemiologie, Pathogenese und Klassifikation . .2 1.1.2 Therapie . .4 1.1.3 Gen-Umwelt-Interaktionen und Genomweite Assoziationsstudien5 1.2 Das neue Asthma-Risikogen ORMDL . .8 1.3 Der β2-Adrenorezeptor . 11 1.4 Protein-Protein-Interaktionen . 13 1.4.1 Biolumineszenz-Resonanz-Energie-Transfer . 15 1.5 Zielsetzung der Arbeit . 18 2 Material und Methoden 19 2.1 Material . 19 2.1.1 Laborgeräte . 19 2.1.2 Allgemeine Verbrauchsmaterialien, Chemikalien und Reagenzien . 21 2.1.3 Lösungen, Reagenzien-Kits und Puffer . 26 2.1.4 Medium . 28 2.1.5 Zelllinien und Bakterienstämme . 28 2.1.6 Antikörper . 29 2.1.7 β-Sympathomimetika . 29 2.1.8 Restriktionsenzyme . 30 2.1.9 Vektoren und DNA . -
A SARS-Cov-2 Protein Interaction Map Reveals Targets for Drug Repurposing
Article A SARS-CoV-2 protein interaction map reveals targets for drug repurposing https://doi.org/10.1038/s41586-020-2286-9 A list of authors and affiliations appears at the end of the paper Received: 23 March 2020 Accepted: 22 April 2020 A newly described coronavirus named severe acute respiratory syndrome Published online: 30 April 2020 coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than Check for updates 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efcacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and eforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identifed the human proteins that physically associated with each of the SARS-CoV-2 proteins using afnity-purifcation mass spectrometry, identifying 332 high-confdence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. -
Chromatin Conformation Links Distal Target Genes to CKD Loci
BASIC RESEARCH www.jasn.org Chromatin Conformation Links Distal Target Genes to CKD Loci Maarten M. Brandt,1 Claartje A. Meddens,2,3 Laura Louzao-Martinez,4 Noortje A.M. van den Dungen,5,6 Nico R. Lansu,2,3,6 Edward E.S. Nieuwenhuis,2 Dirk J. Duncker,1 Marianne C. Verhaar,4 Jaap A. Joles,4 Michal Mokry,2,3,6 and Caroline Cheng1,4 1Experimental Cardiology, Department of Cardiology, Thoraxcenter Erasmus University Medical Center, Rotterdam, The Netherlands; and 2Department of Pediatrics, Wilhelmina Children’s Hospital, 3Regenerative Medicine Center Utrecht, Department of Pediatrics, 4Department of Nephrology and Hypertension, Division of Internal Medicine and Dermatology, 5Department of Cardiology, Division Heart and Lungs, and 6Epigenomics Facility, Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands ABSTRACT Genome-wide association studies (GWASs) have identified many genetic risk factors for CKD. However, linking common variants to genes that are causal for CKD etiology remains challenging. By adapting self-transcribing active regulatory region sequencing, we evaluated the effect of genetic variation on DNA regulatory elements (DREs). Variants in linkage with the CKD-associated single-nucleotide polymorphism rs11959928 were shown to affect DRE function, illustrating that genes regulated by DREs colocalizing with CKD-associated variation can be dysregulated and therefore, considered as CKD candidate genes. To identify target genes of these DREs, we used circular chro- mosome conformation capture (4C) sequencing on glomerular endothelial cells and renal tubular epithelial cells. Our 4C analyses revealed interactions of CKD-associated susceptibility regions with the transcriptional start sites of 304 target genes. Overlap with multiple databases confirmed that many of these target genes are involved in kidney homeostasis. -
White Matter DNA Methylation Profiling Reveals Deregulation Of
Acta Neuropathologica (2020) 139:135–156 https://doi.org/10.1007/s00401-019-02074-0 ORIGINAL PAPER White matter DNA methylation profling reveals deregulation of HIP1, LMAN2, MOBP, and other loci in multiple system atrophy Conceição Bettencourt1,2 · Sandrine C. Foti1,3 · Yasuo Miki1,4 · Juan Botia5 · Aparajita Chatterjee1 · Thomas T. Warner1,2,6 · Tamas Revesz1,3 · Tammaryn Lashley1,3 · Robert Balazs1,3 · Emmanuelle Viré7 · Janice L. Holton1,2 Received: 2 July 2019 / Revised: 29 August 2019 / Accepted: 9 September 2019 / Published online: 18 September 2019 © The Author(s) 2019 Abstract Multiple system atrophy (MSA) is a fatal late-onset neurodegenerative disease. Although presenting with distinct pathological hallmarks, which in MSA consist of glial cytoplasmic inclusions (GCIs) containing fbrillar α-synuclein in oligodendro- cytes, both MSA and Parkinson’s disease are α-synucleinopathies. Pathologically, MSA can be categorized into striatonigral degeneration (SND), olivopontocerebellar atrophy (OPCA) or mixed subtypes. Despite extensive research, the regional vulnerability of the brain to MSA pathology remains poorly understood. Genetic, epigenetic and environmental factors have been proposed to explain which brain regions are afected by MSA, and to what extent. Here, we explored for the frst time epigenetic changes in post-mortem brain tissue from MSA cases. We conducted a case–control study, and profled DNA methylation in white mater from three brain regions characterized by severe-to-mild GCIs burden in the MSA mixed subtype (cerebellum, frontal lobe and occipital lobe). Our genome-wide approach using Illumina MethylationEPIC arrays and a powerful cross-region analysis identifed 157 CpG sites and 79 genomic regions where DNA methylation was signifcantly altered in the MSA mixed-subtype cases. -
Development of a Novel Protein Identification Approach to Define Mitochondrial Proteomic Signatures in Glioblastoma Oncogenesis
bioRxiv preprint doi: https://doi.org/10.1101/270942; this version posted February 26, 2018. 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 4.0 International license. Manuscript 1 Title: Development of a novel protein identification approach to define mitochondrial 2 proteomic signatures in glioblastoma oncogenesis: T98G vs U87MG cell lines model. 3 4 Authors: Leopoldo Gómez-Caudilloa, Ángel G. Martínez-Batallara, Ariadna J. Ortega- 5 Lozanoa, Diana L. Fernández-Cotob, Haydee Rosas-Vargasc, Fernando Minauro- 6 Sanmiguelc*, Sergio Encarnación-Guevaraa*. 7 8 Author addresses: 9 a Centro de Ciencias Genómicas, UNAM. Av. Universidad s/n, Col. Chamilpa, CP 62210, 10 Cuernavaca, Morelos, México. 11 b Instituto Nacional de Salud Pública. Av. Universidad 655, Col. Santa María Ahuacatitlán, 12 CP 62100, Cuernavaca, Morelos, México. 13 c Unidad de Investigación Médica en Genética Humana, Hospital de Pediatría, Centro 14 Médico Nacional Siglo XXI, IMSS. Av. Cuauhtémoc 330, Col. Doctores, CP 06720, 15 CdMx, México. 16 17 Corresponding authors: 18 * Sergio Encarnación-Guevara email: [email protected] 19 Tel: +52 777 3291899. 20 * Fernando Minauro-Sanmiguel email: [email protected] 21 Tel: +52 55 56276900 ext. 21941. 22 Keywords: Glioblastoma, Mitochondria, 2DE, Random Sampling, Principal Components 23 Analysis, Proteomic Signature, Metabolic change. 1 24bioRxiv preprint doi: https://doi.org/10.1101/270942; this version posted February 26, 2018. 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. -
Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards
Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein -
Variations in the G6PC2/ABCB11 Genomic Region Are Associated with Fasting Glucose Levels Wei-Min Chen,1,2 Michael R
Research article Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels Wei-Min Chen,1,2 Michael R. Erdos,3 Anne U. Jackson,4 Richa Saxena,5 Serena Sanna,4,6 Kristi D. Silver,7 Nicholas J. Timpson,8 Torben Hansen,9 Marco Orrù,6 Maria Grazia Piras,6 Lori L. Bonnycastle,3 Cristen J. Willer,4 Valeriya Lyssenko,10 Haiqing Shen,7 Johanna Kuusisto,11 Shah Ebrahim,12 Natascia Sestu,13 William L. Duren,4 Maria Cristina Spada,6 Heather M. Stringham,4 Laura J. Scott,4 Nazario Olla,6 Amy J. Swift,3 Samer Najjar,13 Braxton D. Mitchell,7 Debbie A. Lawlor,8 George Davey Smith,8 Yoav Ben-Shlomo,14 Gitte Andersen,9 Knut Borch-Johnsen,9,15,16 Torben Jørgensen,15 Jouko Saramies,17 Timo T. Valle,18 Thomas A. Buchanan,19,20 Alan R. Shuldiner,7 Edward Lakatta,13 Richard N. Bergman,20 Manuela Uda,6 Jaakko Tuomilehto,18,21 Oluf Pedersen,9,16 Antonio Cao,6 Leif Groop,10 Karen L. Mohlke,22 Markku Laakso,11 David Schlessinger,13 Francis S. Collins,3 David Altshuler,5 Gonçalo R. Abecasis,4 Michael Boehnke,4 Angelo Scuteri,23,24 and Richard M. Watanabe20,25 1Department of Public Health Sciences and 2Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA. 3Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA. 4Center for Statistical Genetics and Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA. 5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.