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The Chemical Defensome of Fish: Conservation and Divergence of Genes Involved in Sensing and Responding to Pollutants Among Five Model Teleosts
The Chemical Defensome of Fish: Conservation and Divergence of Genes Involved in Sensing and Responding to Pollutants Among Five Model Teleosts Marta Eide University of Bergen Xiaokang Zhang Oslo University Hospital Odd André Karlsen University of Bergen Jared V. Goldstone Woods Hole Oceanographic Institution John Stegeman Woods Hole Oceanographic Institution Inge Jonassen University of Bergen Anders Goksøyr ( [email protected] ) University of Bergen Research Article Keywords: Chemical defensome, environmental contaminants, detoxication, nuclear receptors, biotransformation, antioxidant proteins, heat shock proteins, model species, toxicology Posted Date: February 9th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-175531/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 The chemical defensome of fish: conservation and divergence of genes 2 involved in sensing and responding to pollutants among five model 3 teleosts. 4 5 Marta Eide1*, Xiaokang Zhang2,3*, Odd André Karlsen1, Jared V. Goldstone4, John Stegeman4, 6 Inge Jonassen2, Anders Goksøyr1§ 7 8 1. Department of Biological Sciences, University of Bergen, Norway 9 2. Computational Biology Unit, Department of Informatics, University of Bergen, Norway 10 3. Department of Molecular Oncology, Institute for Cancer Research, Oslo University 11 Hospital-Radiumhospitalet, Norway 12 4. Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA 13 14 * The authors contributed equally to the study 15 § Corresponding author: [email protected] 16 17 18 Abstract 19 20 How an organism copes with chemicals is largely determined by the genes and proteins that 21 collectively function to defend against, detoxify and eliminate chemical stressors. This 22 integrative network includes receptors and transcription factors, biotransformation enzymes, 23 transporters, antioxidants, and metal- and heat-responsive genes, and is collectively known 24 as the chemical defensome. -
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UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Asha Marie Miles December 2019 © 2019 Asha Marie Miles UNDERSTANDING THE GENETICS UNDERLYING MASTITIS USING A MULTI-PRONGED APPROACH Asha Marie Miles, Ph. D. Cornell University 2019 This dissertation addresses deficiencies in the existing genetic characterization of mastitis due to granddaughter study designs and selection strategies based primarily on lactation average somatic cell score (SCS). Composite milk samples were collected across 6 sampling periods representing key lactation stages: 0-1 day in milk (DIM), 3- 5 DIM, 10-14 DIM, 50-60 DIM, 90-110 DIM, and 210-230 DIM. Cows were scored for front and rear teat length, width, end shape, and placement, fore udder attachment, udder cleft, udder depth, rear udder height, and rear udder width. Independent multivariable logistic regression models were used to generate odds ratios for elevated SCC (≥ 200,000 cells/ml) and farm-diagnosed clinical mastitis. Within our study cohort, loose fore udder attachment, flat teat ends, low rear udder height, and wide rear teats were associated with increased odds of mastitis. Principal component analysis was performed on these traits to create a single new phenotype describing mastitis susceptibility based on these high-risk phenotypes. Cows (N = 471) were genotyped on the Illumina BovineHD 777K SNP chip and considering all 14 traits of interest, a total of 56 genome-wide associations (GWA) were performed and 28 significantly associated quantitative trait loci (QTL) were identified. -
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. -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells. -
Kif9 Is an Active Kinesin Motor Required for Ciliary Beating and Proximodistal Patterning of Motile Axonemes
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.26.457815; this version posted August 27, 2021. 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 Kif9 is an active kinesin motor required for ciliary beating and proximodistal patterning of motile axonemes Mia J. Konjikusic1,2,3, Chanjae Lee1, Yang Yue4, Bikram D. Shrestha5, Ange M. Nguimtsop1, Amjad Horani6, Steven Brody7,8, Vivek N. Prakash5,9, Ryan S. Gray2,3, Kristen J. Verhey4, John B. Wallingford1* 1 Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA. 2 Department of Pediatrics, Dell Pediatric Research Institute, 1400 Barbara Jordan Blvd, The University of Texas at Austin, Dell Medical School, Austin, TX, USA. 3 Department of Nutritional Sciences, 200 W 24th Street, The University of Texas at Austin, Austin, TX 78712, USA. 4 Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. 5 Department of Physics, University of Miami, Coral Gables, FL, USA. 6 Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA. 7 Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA. 8 Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, 63110 USA 9 Department of Biology and Department of Marine Biology and Ecology, University of Miami, Coral Gables, FL, USA. *Corresponding Author [email protected] Patterson Labs 2401 Speedway Austin, Tx 78712 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.26.457815; this version posted August 27, 2021. -
HHS Public Access Author Manuscript
HHS Public Access Author manuscript Author Manuscript Author ManuscriptFEBS J. Author Manuscript Author manuscript; Author Manuscript available in PMC 2016 September 01. Published in final edited form as: FEBS J. 2015 September ; 282(18): 3556–3578. doi:10.1111/febs.13358. The sequenced rat brain transcriptome, its use in identifying networks predisposing alcohol consumption Laura M. Saba1, Stephen C. Flink1, Lauren A. Vanderlinden1, Yedy Israel2, Lutske Tampier2, Giancarlo Colombo3, Kalervo Kiianmaa4, Richard L. Bell5, Morton P. Printz6, Pamela Flodman7, George Koob8,11, Heather N. Richardson8,12, Joseph Lombardo10, Paula L. Hoffman1,9, and Boris Tabakoff1,9 1Department of Pharmaceutical Sciences, University of Colorado Denver, Aurora, CO, USA 2Laboratory of Pharmacogenetics of Alcoholism, Molecular & Clinical Pharmacology Program, Institute of Biomedical Sciences, Faculty of Medicine, University of Chile, Santiago, Chile 3Neuroscience Institute, National Research Council of Italy, Section of Cagliari, Monserrato, Italy 4Department of Alcohol, Drugs and Addiction, National Institute for Health and Welfare, Helsinki, Finland 5Department of Psychiatry, Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, IN, USA 6Department of Pharmacology, University of California San Diego, La Jolla, CA 7Department of Pediatrics, University of California, Irvine, Irvine, CA, USA 8Committee on the Neurobiology of Addiction Disorders, The Scripps Research Institute, La Jolla, CA, USA 9Department of Pharmacology, University of Colorado Denver, Aurora, CO, USA 10National Supercomputing Center for Energy and Environment, University of Nevada, Las Vegas, Nevada, USA Corresponding Author: Boris Tabakoff, PhD, Department of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences University of Colorado Anschutz Medical Campus, 12850 E. Montview Blvd., Aurora, CO 80045, (303)724-3668, FAX: (303)724-6148. -
Vote Summary Report
Vote Summary Report Reporting Period: 07/01/2020 to 06/30/2021 Location(s): State Street Global Advisors Institution Account(s): SPDR Russell 1000 Low Volatility Focus ETF Healthcare Trust of America, Inc. Meeting Date: 07/07/2020 Country: USA Primary Security ID: 42225P501 Record Date: 04/15/2020 Meeting Type: Annual Ticker: HTA Primary CUSIP: 42225P501 Primary ISIN: US42225P5017 Primary SEDOL: BT9QF28 Proposal Vote Number Proposal Text Proponent Mgmt Rec Instruction 1a Elect Director Scott D. Peters Mgmt For For 1b Elect Director W. Bradley Blair, II Mgmt For For 1c Elect Director Vicki U. Booth Mgmt For For 1d Elect Director H. Lee Cooper Mgmt For For 1e Elect Director Warren D. Fix Mgmt For For 1f Elect Director Peter N. Foss Mgmt For For 1g Elect Director Jay P. Leupp Mgmt For For 1h Elect Director Gary T. Wescombe Mgmt For For 2 Advisory Vote to Ratify Named Executive Mgmt For For Officers' Compensation 3 Ratify Deloitte & Touche LLP as Auditors Mgmt For For EQT Corporation Meeting Date: 07/23/2020 Country: USA Primary Security ID: 26884L109 Record Date: 06/29/2020 Meeting Type: Special Ticker: EQT Primary CUSIP: 26884L109 Primary ISIN: US26884L1098 Primary SEDOL: 2319414 Proposal Vote Number Proposal Text Proponent Mgmt Rec Instruction 1 Increase Authorized Common Stock Mgmt For For 2 Adjourn Meeting Mgmt For Against Vote Summary Report Reporting Period: 07/01/2020 to 06/30/2021 Location(s): State Street Global Advisors Institution Account(s): SPDR Russell 1000 Low Volatility Focus ETF Spectrum Brands Holdings, Inc. Meeting Date: 07/28/2020 Country: USA Primary Security ID: 84790A105 Record Date: 06/03/2020 Meeting Type: Annual Ticker: SPB Primary CUSIP: 84790A105 Primary ISIN: US84790A1051 Primary SEDOL: BDRYFB1 Proposal Vote Number Proposal Text Proponent Mgmt Rec Instruction 1a Elect Director Kenneth C. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
TCTE1 Is a Conserved Component of the Dynein Regulatory Complex and Is Required for Motility and Metabolism in Mouse Spermatozoa
TCTE1 is a conserved component of the dynein PNAS PLUS regulatory complex and is required for motility and metabolism in mouse spermatozoa Julio M. Castanedaa,b,1, Rong Huac,d,1, Haruhiko Miyatab, Asami Ojib,e, Yueshuai Guoc,d, Yiwei Chengc,d, Tao Zhouc,d, Xuejiang Guoc,d, Yiqiang Cuic,d, Bin Shenc, Zibin Wangc, Zhibin Huc,f, Zuomin Zhouc,d, Jiahao Shac,d, Renata Prunskaite-Hyyrylainena,g,h, Zhifeng Yua,i, Ramiro Ramirez-Solisj, Masahito Ikawab,e,k,2, Martin M. Matzuka,g,i,l,m,n,2, and Mingxi Liuc,d,2 aDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030; bResearch Institute for Microbial Diseases, Osaka University, Suita, Osaka 5650871, Japan; cState Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 210029, People’s Republic of China; dDepartment of Histology and Embryology, Nanjing Medical University, Nanjing 210029, People’s Republic of China; eGraduate School of Pharmaceutical Sciences, Osaka University, Suita, Osaka 5650871, Japan; fAnimal Core Facility of Nanjing Medical University, Nanjing 210029, People’s Republic of China; gCenter for Reproductive Medicine, Baylor College of Medicine, Houston, TX 77030; hFaculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu FI-90014, Finland; iCenter for Drug Discovery, Baylor College of Medicine, Houston, TX 77030; jWellcome Trust Sanger Institute, Hinxton CB10 1SA, United Kingdom; kThe Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo 1088639, Japan; lDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; mDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030; and nDepartment of Pharmacology, Baylor College of Medicine, Houston, TX 77030 Contributed by Martin M. -
Supplementary Figures and Tables Figure S1. (A) Heat Map Displaying
Supplementary Figures and Tables Figure S1. (A) Heat map displaying 526 DEGs derived from GSE14827 between metastasis and non-metastasis patients. (B) Heat map displaying 1057 DEGs derived from GSE39055 between recurrence and non-recurrence patients. Rows represent genes and columns represent patients. Red rectangles represent patients with metastasis or recurrence and blue rectangles represent patients without metastasis or recurrence. Figure S2. (A) Dot plots of PQBP1and PCK2 expression in 3 datasets. the red dots represented patients who died during the follow-up and the blue dots represented patients were alive during follow-up. (B) Density plots of PQBP1and PCK2 expression in 3 datasets, the red lines represented expression distributions in patients who died during the follow-up, and the blue lines in patients were alive during follow-up, and the black lines in all patients. (C) Kaplan-Meier curves of PQBP1, PCK2 expression status and combination status of them on overall survival in GSE21257. Table S3. The intersected DEGs identified in 2 discovery datasets. Table S4. Associations of PCK2 and PQBP1 expression status with clinicopathological features of OS patients in GSE14827, GSE39055 and GSE21257. Table S5. Univariate and multivariate Cox regression analyses for overall survival of OS patients in GSE21257. Figure S1 Figure S2 Table S3. The intersected DEGs identified in 2 discovery datasets. GSE14827 GSE39055 Gene Symbol p value Fold Change p value Fold Change Up-regulated ASGR1 0.001184122 2.344428863 0.039400673 1.621460858 ZNF418 -
Looking for Missing Proteins in the Proteome Of
Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update Yves Vandenbrouck, Lydie Lane, Christine Carapito, Paula Duek, Karine Rondel, Christophe Bruley, Charlotte Macron, Anne Gonzalez de Peredo, Yohann Coute, Karima Chaoui, et al. To cite this version: Yves Vandenbrouck, Lydie Lane, Christine Carapito, Paula Duek, Karine Rondel, et al.. Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update. Journal of Proteome Research, American Chemical Society, 2016, 15 (11), pp.3998-4019. 10.1021/acs.jproteome.6b00400. hal-02191502 HAL Id: hal-02191502 https://hal.archives-ouvertes.fr/hal-02191502 Submitted on 19 Mar 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Journal of Proteome Research 1 2 3 Looking for missing proteins in the proteome of human spermatozoa: an 4 update 5 6 Yves Vandenbrouck1,2,3,#,§, Lydie Lane4,5,#, Christine Carapito6, Paula Duek5, Karine Rondel7, 7 Christophe Bruley1,2,3, Charlotte Macron6, Anne Gonzalez de Peredo8, Yohann Couté1,2,3, 8 Karima Chaoui8, Emmanuelle Com7, Alain Gateau5, AnneMarie Hesse1,2,3, Marlene 9 Marcellin8, Loren Méar7, Emmanuelle MoutonBarbosa8, Thibault Robin9, Odile Burlet- 10 Schiltz8, Sarah Cianferani6, Myriam Ferro1,2,3, Thomas Fréour10,11, Cecilia Lindskog12,Jérôme 11 1,2,3 7,§ 12 Garin , Charles Pineau . -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
biomolecules Article Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways Aayushi Srivastava 1,2,3,4 , Abhishek Kumar 1,5,6 , Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany; [email protected] (A.S.); [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120 Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120 Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120 Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics, 40138 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family.