Table S1: Gene Symbol Full Gene Name Entrez Gene ID Refseq A2M
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Analyses of Allele-Specific Gene Expression in Highly Divergent
ARTICLES Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance James J Crowley1,10, Vasyl Zhabotynsky1,10, Wei Sun1,2,10, Shunping Huang3, Isa Kemal Pakatci3, Yunjung Kim1, Jeremy R Wang3, Andrew P Morgan1,4,5, John D Calaway1,4,5, David L Aylor1,9, Zaining Yun1, Timothy A Bell1,4,5, Ryan J Buus1,4,5, Mark E Calaway1,4,5, John P Didion1,4,5, Terry J Gooch1,4,5, Stephanie D Hansen1,4,5, Nashiya N Robinson1,4,5, Ginger D Shaw1,4,5, Jason S Spence1, Corey R Quackenbush1, Cordelia J Barrick1, Randal J Nonneman1, Kyungsu Kim2, James Xenakis2, Yuying Xie1, William Valdar1,4, Alan B Lenarcic1, Wei Wang3,9, Catherine E Welsh3, Chen-Ping Fu3, Zhaojun Zhang3, James Holt3, Zhishan Guo3, David W Threadgill6, Lisa M Tarantino7, Darla R Miller1,4,5, Fei Zou2,11, Leonard McMillan3,11, Patrick F Sullivan1,5,7,8,11 & Fernando Pardo-Manuel de Villena1,4,5,11 Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Because regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in further characterizing these mechanisms. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. Effects from these variants influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Download on 20
bioRxiv preprint doi: https://doi.org/10.1101/850776; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Intramembrane protease RHBDL4 cleaves oligosaccharyltransferase subunits to target them for ER-associated degradation Julia D. Knopf1, Nina Landscheidt1, Cassandra L. Pegg2, Benjamin L. Schulz2, Nathalie Kühnle1, Chao-Wei Chao1, Simon Huck1 and Marius K. Lemberg1, # 1Centre for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany. 2School of Chemistry and Molecular Biosciences, ARC Training Centre for Biopharmaceutical Innovation, The University of Queensland, St Lucia QLD 4072, Australia. #Corresponding author: [email protected] Running title: RHBDL4 triggers ERAD of OST subunits Key words: Rhomboid serine protease, Rhbdd1, ubiquitin-dependent proteolysis, post- translational protein abundance control, N-linked glycosylation. Abbreviations ERAD, ER-associated degradation; OST, oligosacharyltransferase; TM, transmembrane; UIM, ubiquitin-interacting motif. Abstract The Endoplasmic Reticulum (ER)-resident intramembrane rhomboid protease RHBDL4 generates metastable protein fragments and together with the ER-associated degradation (ERAD) machinery provides a clearance mechanism for aberrant and surplus proteins. However, the endogenous substrate spectrum and with that the role of RHBDL4 in physiological ERAD is mainly unknown. Here, we use a substrate trapping approach in combination with quantitative proteomics to identify physiological RHBDL4 substrates. This revealed oligosacharyltransferase (OST) complex subunits such as the catalytic active subunit STT3A as substrates for the RHBDL4-dependent ERAD pathway. RHBDL4-catalyzed cleavage inactivates OST subunits by triggering dislocation into the cytoplasm and subsequent proteasomal degradation. -
The Atypical Guanine-Nucleotide Exchange Factor, Dock7, Negatively Regulates Schwann Cell Differentiation and Myelination
The Journal of Neuroscience, August 31, 2011 • 31(35):12579–12592 • 12579 Cellular/Molecular The Atypical Guanine-Nucleotide Exchange Factor, Dock7, Negatively Regulates Schwann Cell Differentiation and Myelination Junji Yamauchi,1,3,5 Yuki Miyamoto,1 Hajime Hamasaki,1,3 Atsushi Sanbe,1 Shinji Kusakawa,1 Akane Nakamura,2 Hideki Tsumura,2 Masahiro Maeda,4 Noriko Nemoto,6 Katsumasa Kawahara,5 Tomohiro Torii,1 and Akito Tanoue1 1Department of Pharmacology and 2Laboratory Animal Resource Facility, National Research Institute for Child Health and Development, Setagaya, Tokyo 157-8535, Japan, 3Department of Biological Sciences, Tokyo Institute of Technology, Midori, Yokohama 226-8501, Japan, 4IBL, Ltd., Fujioka, Gumma 375-0005, Japan, and 5Department of Physiology and 6Bioimaging Research Center, Kitasato University School of Medicine, Sagamihara, Kanagawa 252-0374, Japan In development of the peripheral nervous system, Schwann cells proliferate, migrate, and ultimately differentiate to form myelin sheath. In all of the myelination stages, Schwann cells continuously undergo morphological changes; however, little is known about their underlying molecular mechanisms. We previously cloned the dock7 gene encoding the atypical Rho family guanine-nucleotide exchange factor (GEF) and reported the positive role of Dock7, the target Rho GTPases Rac/Cdc42, and the downstream c-Jun N-terminal kinase in Schwann cell migration (Yamauchi et al., 2008). We investigated the role of Dock7 in Schwann cell differentiation and myelination. Knockdown of Dock7 by the specific small interfering (si)RNA in primary Schwann cells promotes dibutyryl cAMP-induced morpholog- ical differentiation, indicating the negative role of Dock7 in Schwann cell differentiation. It also results in a shorter duration of activation of Rac/Cdc42 and JNK, which is the negative regulator of myelination, and the earlier activation of Rho and Rho-kinase, which is the positive regulator of myelination. -
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. -
Arg206cys Substitution in DNASE1L3 Causes a Defect in DNASE1L3 Protein Secretion That Confers Risk of Systemic Lupus Erythematos
Ann Rheum Dis: first published as 10.1136/annrheumdis-2020-218810 on 17 January 2021. Downloaded from Systemic lupus erythematosus TRANSLATIONAL SCIENCE Arg206Cys substitution in DNASE1L3 causes a defect in DNASE1L3 protein secretion that confers risk of systemic lupus erythematosus Latanya N Coke ,1 Hongxiu Wen ,1 Mary Comeau ,2 Mustafa H Ghanem ,1,3 Andrew Shih ,1 Christine N Metz ,1,3 Wentian Li ,1 Carl D Langefeld ,2 Peter K Gregersen ,1,3 Kim R Simpfendorfer 1,3 Handling editor Josef S ABSTRACT Key messages Smolen Objectives To determine if the polymorphism encoding the Arg206Cys substitution in DNASE1L3 explains the ► Additional material is What is already known about this subject? published online only. To view, association of the DNASE1L3/PXK gene locus with systemic ► The coding polymorphism rs35677470 is the please visit the journal online lupus erythematosus (SLE) and to examine the effect of the causal variant for rheumatoid arthritis (RA) and (http:// dx. doi. org/ 10. 1136/ Arg206Cys sequence change on DNASE1L3 protein function. scleroderma/systemic sclerosis (SSc) association annrheumdis- 2020- 218810). Methods Conditional analysis for rs35677470 was in the DNASE1L3/PXK locus and is reported to 1 performed on cases and controls with European ancestry The Institute of Molecular eliminate DNASE1L3 enzyme function. Medicine, Northwell Health from the SLE Immunochip study, and genotype and haplotype Feinstein Institutes for Medical frequencies were compared. DNASE1L3 protein levels were What does this study add? Research, Manhasset, New measured in cells and supernatants of HEK293 cells and York, USA ► The coding polymorphism rs35677470 is 2 monocyte-derived dendritic cells expressing recombinant and Department of Biostatistics the causal variant for the systemic lupus endogenous 206Arg and 206Cys protein variants. -
743914V1.Full.Pdf
bioRxiv preprint doi: https://doi.org/10.1101/743914; this version posted August 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Cross-talks of glycosylphosphatidylinositol biosynthesis with glycosphingolipid biosynthesis 2 and ER-associated degradation 3 4 Yicheng Wang1,2, Yusuke Maeda1, Yishi Liu3, Yoko Takada2, Akinori Ninomiya1, Tetsuya 5 Hirata1,2,4, Morihisa Fujita3, Yoshiko Murakami1,2, Taroh Kinoshita1,2,* 6 7 1Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan 8 2WPI Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, 9 Japan 10 3Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, 11 School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China 12 4Current address: Center for Highly Advanced Integration of Nano and Life Sciences (G- 13 CHAIN), Gifu University, 1-1 Yanagido, Gifu-City, Gifu 501-1193, Japan 14 15 *Correspondence and requests for materials should be addressed to T.K. (email: 16 [email protected]) 17 18 19 Glycosylphosphatidylinositol (GPI)-anchored proteins and glycosphingolipids interact with 20 each other in the mammalian plasma membranes, forming dynamic microdomains. How their 21 interaction starts in the cells has been unclear. Here, based on a genome-wide CRISPR-Cas9 22 genetic screen for genes required for GPI side-chain modification by galactose in the Golgi 23 apparatus, we report that b1,3-galactosyltransferase 4 (B3GALT4), also called GM1 24 ganglioside synthase, additionally functions in transferring galactose to the N- 25 acetylgalactosamine side-chain of GPI. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
De Novo Characterization of Cell-Free DNA Fragmentation Hotspots Boosts
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.16.201350; this version posted July 16, 2020. 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 4.0 International license. 1 De novo characterization of cell-free DNA fragmentation hotspots 2 boosts the power for early detection and localization of multi- 3 cancer 4 Xionghui Zhou1, Yaping Liu1-4 * 5 1 Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 6 45229 7 2 Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, 8 Cincinnati, OH 45229 9 3 Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 10 45229 11 4 Department of Electrical Engineering and Computing Sciences, University of Cincinnati 12 College of Engineering and Applied Science, Cincinnati, OH 45229 13 * Email: [email protected] 14 15 16 17 18 19 20 21 22 23 24 25 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.16.201350; this version posted July 16, 2020. 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 4.0 International license. 26 Abstract 27 The global variation of cell-free DNA fragmentation patterns is a promising biomarker for 28 cancer diagnosis. However, the characterization of its hotspots and aberrations in early- 29 stage cancer at the fine-scale is still poorly understood. -
Recombinant Human FLRT2 Protein Catalog Number: ATGP3291
Recombinant human FLRT2 protein Catalog Number: ATGP3291 PRODUCT INPORMATION Expression system Baculovirus Domain 36-541aa UniProt No. O43155 NCBI Accession No. NP_037363 Alternative Names FLRT2 PRODUCT SPECIFICATION Molecular Weight 57.5 kDa (514aa) Concentration 0.25mg/ml (determined by absorbance at 280nm) Formulation Liquid in. Phosphate-Buffered Saline (pH 7.4) containing 10% glycerol Purity > 90% by SDS-PAGE Endotoxin level < 1 EU per 1ug of protein (determined by LAL method) Tag His-Tag Application SDS-PAGE Storage Condition Can be stored at +2C to +8C for 1 week. For long term storage, aliquot and store at -20C to -80C. Avoid repeated freezing and thawing cycles. BACKGROUND Description FLRT2, also known as leucine-rich repeat transmembrane protein FLRT2, is one of three FLRT (fibronectin, leucine rich repeat, transmembrane) glycoproteins expressed in distinct areas of the developing brain and other tissues. Human FLRT1 and FLRT3 ECDs (extracellular domain) share approximately 47% aa identity with FLRT2. The fibronectin domain of all three FLRTs can bind to FGF receptors. Recombinant human FLRT2, fused to His-tag 1 Recombinant human FLRT2 protein Catalog Number: ATGP3291 at C-terminus, was expressed in insect cell and purified by using conventional chromatography techniques. Amino acid Sequence CPSVCRCDRN FVYCNERSLT SVPLGIPEGV TVLYLHNNQI NNAGFPAELH NVQSVHTVYL YGNQLDEFPM NLPKNVRVLH LQENNIQTIS RAALAQLLKL EELHLDDNSI STVGVEDGAF REAISLKLLF LSKNHLSSVP VGLPVDLQEL RVDENRIAVI SDMAFQNLTS LERLIVDGNL LTNKGIAEGT FSHLTKLKEF SIVRNSLSHP PPDLPGTHLI RLYLQDNQIN HIPLTAFSNL RKLERLDISN NQLRMLTQGV FDNLSNLKQL TARNNPWFCD CSIKWVTEWL KYIPSSLNVR GFMCQGPEQV RGMAVRELNM NLLSCPTTTP GLPLFTPAPS TASPTTQPPT LSIPNPSRSY TPPTPTTSKL PTIPDWDGRE RVTPPISERI QLSIHFVNDT SIQVSWLSLF TVMAYKLTWV KMGHSLVGGI VQERIVSGEK QHLSLVNLEP RSTYRICLVP LDAFNYRAVE DTICSEATTH ASYLNNGSNT ASSHEQTTSH SMGSPFLEHH HHHH General References Haines B.P., et al. (2006) Dev. -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened.