DOCSLIB.ORG

Bipolar Disorder Related Functional Variants in the Calcium Channel Gene Family

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Bipolar Disorder Related Functional Variants in the Calcium Channel Gene Family. Niamh Louise O’Brien Division of Psychiatry University College London, Thesis submitted for the degree of Doctor of Philosophy UCL 1 I, Niamh O’Brien confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Abstract Bipolar disorder (BD) is a common highly heritable disorder. The calcium channel gene family has been widely implicated in BD aetiology and these genes include CACNA1C, and CACNG4. The association signal for CACNA1C with BD is located in the middle of the third intron of the gene. CACNG4 encodes a transmembrane AMPA receptor regulator that is involved in trafficking AMPA receptors to the neuronal post-synaptic density. High-resolution melting curve (HRM) analysis and whole genome sequencing (WGS) methods were used to identify functional variants in calcium channels genes in the UCL BD cohort. Variants that were predicted to impact gene regulation, transcription or to be damaging to protein structure were genotyped in the larger UCL BD and control cohort. HRM analysis identified 26 calcium channel gene variants. These included two non-synonymous CACNG4 variants that were associated with mental illness (rs371128228, p=1.05x10-4, OR=4.39 and 17:65026851 (C/T), p=5x10-4, OR=9.52). Fluorescent activated cell sorting analysis was used to determine the effect of rs371128228 on trafficking of GluR1 and GluR2 to the cell surface. This analysis demonstrated that the risk allele of rs371128228 significantly decreased cell surface trafficking of GluR1 (p=0.026) but no effect was observed on GluR2 trafficking. WGS analysis of CACNA1C intron 3 identified two BD associated (p=0.015, OR=1.15) variants 105bp apart that were in complete LD. Both variants are predicted to create YY1 transcription factor binding sites. Luciferase reporter assays show a significant decrease in gene expression in the presence of both variants (p=0.004). Protein-DNA complex assays of the CACNA1C variants demonstrate increased nuclear proteins binding affinity for the variant alleles. If these calcium channel variants are confirmed to be important risk factors for BD they could be used as markers for personalised treatment or in the identification of genetic subtypes of BD or other psychiatric illness. 3 Acknowledgements As the end of my time working on this thesis draws to a close I am very aware of the amount of support and direction I have received over the course of my PhD. First and foremost I would like to thank my supervisor Dr.Andrew McQuillin for giving me the wonderful opportunity to carry out this work and PhD and for all of his advice and support throughout the years, no matter how silly the questions I may have asked were. I would like to thank Dr. Hugh Gurling for his introduction to the Molecular Psychiatry laboratory and support and advice during the first years of my PhD. I would like to extend my sincerest gratitude to Dr. Nicholas Bass, who after Dr. Gurling sadly passed away took over the mantle as my secondary supervisor and continued to support me through my PhD. Dr.Bass’s advice and feedback during my write up and constant source of encouragement to keep going was invaluable. My sincerest thanks go to The Bipolar Foundation: Equilibrium and the Fairclough family for providing the funding which has given me the opportunity to work in a field of great interest to me over the course of my PhD. Without this I would not have been able to work in the field of psychiatric genetics. The next in line are my parents and family who have given me tremendous support throughout the course of my work. I can never thank them enough for the encouragement and motivation following my move to London and during the last number of years. They have always pushed me to strive for the best and have listened to me talk about my work non-stop, even when they may not have understood anything I was saying. A very special thanks needs to go to both Alessia and Sally. Without their help I would not be the researcher I am today. They were always on hand no matter how small or large the questions I had about science were. I am greatly indebted to them for their support, advice and friendship during this time. I would like to thank all of my current and ex-colleagues of the Molecular Psychiatry lab, Michael, Yi, Jon, Alex, Kate, Giorgia and Mariam for their support. 4 I would like to thank everyone, especially Kleoniki, Chris, Jaspal and Niamh, who has listened to me complain about failed experiments and thesis writing. There have been many times when your friendship, support and ability to make me laugh have been the exact remedy I needed and you have never shown exasperation whether you felt it or not. A special thanks to Chris as well for helping me with the enormous task of proof-reading this thesis. Last but not least I am sincerely grateful to my partner Gavriil for his constant and never ending support during my PhD. I would like to thank him for his cool calm attitude, his constant emotional support and motivation, the late night food runs and for never doubting my abilities. Lastly, I would like to thank everyone again who has made this possible and made the journey extremely memorable and enjoyable. 5 Table of Contents ABSTRACT 3 ACKNOWLEDGEMENTS 4 TABLE OF CONTENTS 6 LIST OF FIGURES 10 LIST OF TABLES 13 LIST OF ABBREVIATIONS 16 CHAPTER 1 INTRODUCTION 21 1.1 BIPOLAR DISORDER 21 1.1.1 OVERVIEW 21 1.1.2 HISTORY AND CLASSIFICATION 24 1.1.3 DIAGNOSTIC CRITERIA 26 1.1.4 BIPOLAR DISORDER SUBTYPES 30 1.1.5 BIOCHEMICAL PATHWAYS IMPLICATED IN BIPOLAR DISORDER 36 1.1.6 TREATMENT OF BIPOLAR DISORDER 40 1.2 GENETICS OF BIPOLAR DISORDER 46 1.2.1 HERITABILITY OF BIPOLAR DISORDER 46 1.2.2 MOLECULAR GENETIC STUDIES OF BIPOLAR DISORDER 50 1.3 CALCIUM CHANNEL GENES 81 1.3.1 INTRODUCTION 81 1.3.2 GENETIC VARIATION IN CALCIUM CHANNEL GENES 95 1.4 INTRONIC GENETIC VARIATION 99 1.4.1 INTRODUCTION 99 1.4.2 ENCODE DATA 100 1.4.3 UTILISING DATA SETS SUCH AS ENCODE TO INVESTIGATE NGS 103 CHAPTER 2 AIMS OF THESIS 104 CHAPTER 3 MATERIAL AND METHODS 105 3.1 GENERAL METHODS 105 3.1.1 UCL RESEARCH SUBJECTS 105 3.1.2 GENOMIC DNA EXTRACTIONS 107 3.1.3 DNA QUANTIFICATIONS 110 6 3.1.4 POLYMERASE CHAIN REACTION 111 3.1.5 AGAROSE GEL ELECTROPHORESIS 114 3.1.6 MAMMALIAN CELL CULTURE 116 3.2 METHODS FOR RESULTS CHAPTER 4 AND 5: HIGH-RESOLUTION MELTING CURVE ANALYSIS IN CALCIUM CHANNEL GENES 120 3.2.1 RESEARCH SAMPLES 120 3.2.2 HIGH-RESOLUTION MELTING 120 3.2.3 PURIFICATION OF SAMPLES 121 3.2.4 SANGER SEQUENCING 123 3.2.5 VARIANT SELECTION FOR KASPAR GENOTYPING 126 3.2.6 SNV GENOTYPING WITH KASPAR 127 3.2.7 PLASMID CONSTRUCTION 133 3.2.8 CELLULAR TRANSFECTIONS 147 3.2.9 FLOW CYTOMETRY 147 3.3 METHODS FOR RESULTS CHAPTER 5: INVESTIGATION OF VARIANTS USING NEXT GENERATION SEQUENCING ANALYSIS 149 3.3.1 RESEARCH SAMPLES FOR NEXT GENERATION SEQUENCING 149 3.3.2 NEXT GENERATION SEQUENCING AND ANALYSIS 149 3.3.3 VARIANT SELECTION 151 3.3.4 KASPAR GENOTYPING 152 3.3.5 STATISTICAL ANALYSIS 152 3.3.6 PLASMID CONSTRUCTION 153 3.3.7 LUCIFERASE ASSAY 158 3.3.8 ELECTROMOBILITY SHIFT ASSAY 160 3.3.9 EMSA SUPERSHIFT ASSAY 164 CHAPTER 4 HIGH-RESOLUTION MELTING CURVE ANALYSIS OF REGULATORY REGIONS IN CALCIUM CHANNEL GENES 165 4.1 INTRODUCTION 165 4.2 HYPOTHESIS 169 4.3 AIMS 169 4.4 HRM METHODS FOR SCREENING CACNA1C, CACNA1D, AND CACNB3 170 4.5 RESULTS 171 4.5.1 HRM SCREENING OF GENES 171 4.5.2 INVESTIGATION OF THE EFFECTS OF VARIANTS 172 4.5.3 GENOTYPING OF VARIANTS FROM HRM 175 4.6 DISCUSSION 176 7 CHAPTER 5 HIGH RESOLUTION MELTING CURVE ANALYSIS OF CACNG4 179 5.1 INTRODUCTION 179 5.2 HYPOTHESIS 181 5.3 AIMS 183 5.4 HRM SCREENING OF CACNG4 183 5.5 RESULTS 185 5.5.1 HRM SCREENING OF GENES 185 5.5.2 INVESTIGATION OF VARIANT EFFECTS 185 5.5.3 GENOTYPING OF VARIANTS DETECTED BY HRM 187 5.5.4 EFFECT OF RS371128228 ON AMPA-R TRAFFICKING 193 5.6 DISCUSSION 198 CHAPTER 6 INVESTIGATION OF VARIANTS IN CALCIUM CHANNEL GENES USING NEXT GENERATION SEQUENCING DATA 205 6.1 EXONIC REGIONS 205 6.1.1 INTRODUCTION 205 6.1.2 HYPOTHESIS 206 6.1.3 AIM 206 6.1.4 RESULTS 206 6.1.5 DISCUSSION 213 6.2 INTRONIC VARIANTS 215 6.2.1 INTRODUCTION 215 6.2.2 AIMS 217 6.2.3 HYPOTHESIS 217 6.2.4 RESULTS 218 6.2.5 DISCUSSION 237 CHAPTER 7 GENERAL DISCUSSION 241 7.1 STUDY LIMITATIONS AND POTENTIAL CONFOUNDS 245 7.2 FUTURE DIRECTIONS 246 REFERENCES 248 APPENDIX I 274 APPENDIX II 281 II.I DNA EXTRACTION FROM BLOOD SAMPLES 281 II.II AGROSE GELS 281 II.III CELL CULTURE 282 8 II.IV TRANSIENT TRANSFECTION 282 II.V PURIFICATION OF PCR PRODUCTS 282 II.VI MINI AND MIDI PREP 283 II.VII EMSA 283 APPENDIX III 285 APPENDIX IV 288 PUBLICATIONS 290 9 List of Figures Figure 1. Common symptoms of Bipolar Disorder. .............................................................. 23 Figure 2. Weighted mean for discharge diagnoses in 6 psychiatric treatment centres in the United States between 1972-1988................................................................
Recommended publications
  • Responses of Bats to White-Nose Syndrome and Implications for Conservation

    Responses of Bats to White-Nose Syndrome and Implications for Conservation

    University of New Hampshire University of New Hampshire Scholars' Repository Doctoral Dissertations Student Scholarship Spring 2020 Responses of Bats to White-Nose Syndrome and Implications for Conservation Meghan Stark University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/dissertation Recommended Citation Stark, Meghan, "Responses of Bats to White-Nose Syndrome and Implications for Conservation" (2020). Doctoral Dissertations. 2518. https://scholars.unh.edu/dissertation/2518 This Dissertation is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. RESPONSES OF BATS TO WHITE-NOSE SYNDROME AND IMPLICATIONS FOR CONSERVATION BY MEGHAN A. STARK B.S., University of Alabama at Birmingham, 2013 DISSERTATION Submitted to the University of New Hampshire in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy In Genetics May 2020 i This dissertation was examined and approved in partial fulfillment of the requirements for the degree of Ph.D. in Genetics by: Dissertation Director, Matthew MacManes, Assoc. Prof. UNH MCBS Jeffrey T. Foster, Associate Professor, NAU PMI W. Kelley Thomas, Professor, UNH MCBS Rebecca Rowe, Associate Professor, UNH NREN Thomas Lee, Associate Professor Emeritus, UNH NREN On April 6, 2020 Approval signatures are on file with the University of New Hampshire Graduate School. ii DEDICATION I dedicate this work to all of the strong women in my life: Myra Michele Ange Heather Michelle Coons Kaitlyn Danielle Cagle Brindlee Michelle Coons Patricia Gail Miller Sarah Jean Lane “Here’s to strong women.
  • Age-Dependent Myocardial Transcriptomic Changes in the Rat

    Age-Dependent Myocardial Transcriptomic Changes in the Rat

    Revista Română de Medicină de Laborator Vol. 22, Nr. 1, Martie, 2014 9 Research article DOI: 10.2478/rrlm-2014-0001 Age-dependent myocardial transcriptomic changes in the rat. Novel insights into atrial and ventricular arrhythmias pathogenesis Modificări transcriptomice dependente de vârstă în miocardul de șobolan. Noi aspecte referitoare la patogeneza aritmiilor atriale și ventriculare Alina Scridon1,2, Emmanuelle Fouilloux-Meugnier3, Emmanuelle Loizon3, Marcel Perian1, Sophie Rome3, Claude Julien2, Christian Barrès2, Philippe Chevalier2,4 1.Physiology Department, University of Medicine and Pharmacy of Tîrgu Mureș, 540139, Tîrgu Mureș, Romania 2. Unité de Neurocardiologie, EA4612, Université Lyon 1, F-69008, Lyon, France 3. Unité 1060 INSERM CarMen, Université Lyon 1, F-69008, Lyon, France 4. Hospices Civils de Lyon, Hôpital Louis Pradel, Service de Rythmologie, 69500, Bron, France Abstract Background: Aging is associated with significantly increased prevalence of cardiac arrhythmias, but tran- scriptional events that underlie this process remain to be established. To gain deeper insight into molecular mech- anisms of aging-related cardiac arrhythmias, we performed mRNA expression analysis comparing atrial and ven- tricular myocardium from Wistar-Kyoto (WKY) rats of different ages. Methods: Atrial and ventricular sampling was performed in 3 groups (n=4 each) of young (14-week-old), adult (25-week-old), and aging (47-week-old) WKY rats. mRNA expressions of 89 genes involved in cardiac arrhythmogenicity were investigated using TaqMan Low Density Array analysis. Results: Of the 89 studied genes, 40 and 64 genes presented steady atrial and ventricu- lar expressions, respectively. All genes differentially expressed within the atria of WKY rats were up-regulated with advancing age, mainly the genes encoding for various K+, Ca2+, Na+ channels, and type 6 collagen.
  • The Mineralocorticoid Receptor Leads to Increased Expression of EGFR

    The Mineralocorticoid Receptor Leads to Increased Expression of EGFR

    www.nature.com/scientificreports OPEN The mineralocorticoid receptor leads to increased expression of EGFR and T‑type calcium channels that support HL‑1 cell hypertrophy Katharina Stroedecke1,2, Sandra Meinel1,2, Fritz Markwardt1, Udo Kloeckner1, Nicole Straetz1, Katja Quarch1, Barbara Schreier1, Michael Kopf1, Michael Gekle1 & Claudia Grossmann1* The EGF receptor (EGFR) has been extensively studied in tumor biology and recently a role in cardiovascular pathophysiology was suggested. The mineralocorticoid receptor (MR) is an important efector of the renin–angiotensin–aldosterone‑system and elicits pathophysiological efects in the cardiovascular system; however, the underlying molecular mechanisms are unclear. Our aim was to investigate the importance of EGFR for MR‑mediated cardiovascular pathophysiology because MR is known to induce EGFR expression. We identifed a SNP within the EGFR promoter that modulates MR‑induced EGFR expression. In RNA‑sequencing and qPCR experiments in heart tissue of EGFR KO and WT mice, changes in EGFR abundance led to diferential expression of cardiac ion channels, especially of the T‑type calcium channel CACNA1H. Accordingly, CACNA1H expression was increased in WT mice after in vivo MR activation by aldosterone but not in respective EGFR KO mice. Aldosterone‑ and EGF‑responsiveness of CACNA1H expression was confrmed in HL‑1 cells by Western blot and by measuring peak current density of T‑type calcium channels. Aldosterone‑induced CACNA1H protein expression could be abrogated by the EGFR inhibitor AG1478. Furthermore, inhibition of T‑type calcium channels with mibefradil or ML218 reduced diameter, volume and BNP levels in HL‑1 cells. In conclusion the MR regulates EGFR and CACNA1H expression, which has an efect on HL‑1 cell diameter, and the extent of this regulation seems to depend on the SNP‑216 (G/T) genotype.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short

    Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short

    bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 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-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 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.
  • Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C

    Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C

    Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation
  • Cdk15 Igfals Lingo4 Gjb3 Tpbg Lrrc38 Serpinf1 Apod Trp73 Lama4 Chrnd Col9a1col11a1col5a2 Fgl2 Pitx2 Col2a1 Col3a1 Lamb3 Col24a1

    Cdk15 Igfals Lingo4 Gjb3 Tpbg Lrrc38 Serpinf1 Apod Trp73 Lama4 Chrnd Col9a1col11a1col5a2 Fgl2 Pitx2 Col2a1 Col3a1 Lamb3 Col24a1

    Bnc2 Wdr72 Ptchd1 Abtb2 Spag5 Zfp385a Trim17 Ier2 Il1rapl1 Tpd52l1 Fam20a Car8 Syt5 Plxnc1 Sema3e Ndrg4 Snph St6galnac5 Mcpt2 B3galt2 Sphkap Arhgap24 Prss34 Lhfpl2 Ermap Rnf165 Shroom1 Grm4 Mobp Dock2 Tmem9b Slc35d3 Otud7b Serpinb3a Sh3d19 Syt6 Zan Trim67 Clec18a Mcoln1 Tob1 Slc45a2 Pcdhb9 Pcdh17 Plscr1 Gpr143 Cela1 Frem1 Sema3f Lgi2 Igsf9 Fjx1 Cpne4 Adgb Depdc7 Gzmm C1qtnf5 Capn11 Sema3c H2-T22 Unc5c Sytl4 Galnt5 Sytl2 Arhgap11a Pcdha1 Cdh20 Slc35f2 Trim29 B3gnt5 Dock5 Trim9 Padi4 Pcdh19 Abi2 Cldn11 Slitrk1 Fam13a Nrgn Cpa4 Clmp Il1rap Trpm1 Fat4 Nexn Pmel Mmp15 Fat3 H2-M5 Prss38 Wdr41 Prtg Mlana Mettl22 Tnrc6b Cdh6 Sema3b Ptgfrn Cldn1 Cntn4 Bcl2a1b Capn6 Capn5 Pcdhb19 Tcf15 Bmf Rgs8 Tecrl Tyrp1 Rhot1 Rnf123 Cldn6 Adam9 Hlx Rilpl1 Disp1 Atcay Vwc2 Fat2 Srpx2 Cldn3 Unc13c Creb3l1 Rab39b Robo3 Gpnmb Bves Orai2 Slc22a2 Prss8 Cdh10 Scg3 Adam33 Nyx Dchs1 Chmp4c Syt9 Ap1m2 Megf10 Cthrc1 Penk Igsf9b Akap2 Ltbp3 Dnmbp Tff2 Pnoc Vldlr Cpa3 Snx18 Capn3 Btla Htr1b Gm17231 Pcdh9Rab27a Grm8 Cnih2 Scube2 Id2 Reep1 Cpeb3 Mmp16 Slc18b1 Snx33 Clcn5 Cckbr Pkp2 Drp2 Mapk8ip1 Lrrc3b Cxcl14 Zfhx3 Esrp1 Prx Dock3 Sec14l1 Prokr1 Pstpip2 Usp2 Cpvl Syn2 Ntn1 Ptger1 Rxfp3 Tyr Snap91 Htr1d Mtnr1a Gadd45g Mlph Drd4 Foxc2 Cldn4 Birc7 Cdh17 Twist2 Scnn1b Abcc4 Pkp1 Dlk2 Rab3b Amph Mreg Il33 Slit2 Hpse Micu1 Creb3l2 Dsp Lifr S1pr5 Krt15 Svep1 Ahnak Kcnh1 Sphk1 Vwce Clcf1 Ptch2 Pmp22 Sfrp1 Sema6a Lfng Hs3st5 Efcab1 Tlr5 Muc5acKalrn Vwa2 Fzd8 Lpar6 Bmp5 Slc16a9 Cacng4 Arvcf Igfbp2 Mrvi1 Dusp15 Krt5 Atp13a5 Dsg1a Kcnj14 Edn3Memo1 Ngef Prickle2 Cma1 Alx4 Bmp3 Blnk GastAgtr2
  • Spatial Distribution of Leading Pacemaker Sites in the Normal, Intact Rat Sinoa

    Spatial Distribution of Leading Pacemaker Sites in the Normal, Intact Rat Sinoa

    Supplementary Material Supplementary Figure 1: Spatial distribution of leading pacemaker sites in the normal, intact rat sinoatrial 5 nodes (SAN) plotted along a normalized y-axis between the superior vena cava (SVC) and inferior vena 6 cava (IVC) and a scaled x-axis in millimeters (n = 8). Colors correspond to treatment condition (black: 7 baseline, blue: 100 µM Acetylcholine (ACh), red: 500 nM Isoproterenol (ISO)). 1 Supplementary Figure 2: Spatial distribution of leading pacemaker sites before and after surgical 3 separation of the rat SAN (n = 5). Top: Intact SAN preparations with leading pacemaker sites plotted during 4 baseline conditions. Bottom: Surgically cut SAN preparations with leading pacemaker sites plotted during 5 baseline conditions (black) and exposure to pharmacological stimulation (blue: 100 µM ACh, red: 500 nM 6 ISO). 2 a &DUGLDFIoQChDQQHOV .FQM FOXVWHU &DFQDG &DFQDK *MD &DFQJ .FQLS .FQG .FQK .FQM &DFQDF &DFQE .FQM í $WSD .FQD .FQM í .FQN &DVT 5\U .FQM &DFQJ &DFQDG ,WSU 6FQD &DFQDG .FQQ &DFQDJ &DFQDG .FQD .FQT 6FQD 3OQ 6FQD +FQ *MD ,WSU 6FQE +FQ *MG .FQN .FQQ .FQN .FQD .FQE .FQQ +FQ &DFQDD &DFQE &DOP .FQM .FQD .FQN .FQG .FQN &DOP 6FQD .FQD 6FQE 6FQD 6FQD ,WSU +FQ 6FQD 5\U 6FQD 6FQE 6FQD .FQQ .FQH 6FQD &DFQE 6FQE .FQM FOXVWHU V6$1 L6$1 5$ /$ 3 b &DUGLDFReFHSWRUV $GUDF FOXVWHU $GUDD &DY &KUQE &KUP &KJD 0\O 3GHG &KUQD $GUE $GUDG &KUQE 5JV í 9LS $GUDE 7SP í 5JV 7QQF 3GHE 0\K $GUE *QDL $QN $GUDD $QN $QN &KUP $GUDE $NDS $WSE 5DPS &KUP 0\O &KUQD 6UF &KUQH $GUE &KUQD FOXVWHU V6$1 L6$1 5$ /$ 4 c 1HXURQDOPURWHLQV
  • Role and Regulation of Snon/Skil and PLSCR1 Located at 3Q26.2

    Role and Regulation of Snon/Skil and PLSCR1 Located at 3Q26.2

    University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 9-18-2014 Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology Madhav Karthik Kodigepalli University of South Florida, [email protected] Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the Cell Biology Commons, Microbiology Commons, and the Molecular Biology Commons Scholar Commons Citation Kodigepalli, Madhav Karthik, "Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology" (2014). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/5426 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology by Madhav Karthik Kodigepalli A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Cell and Molecular Biology Department of Cell Biology, Microbiology and Molecular Biology College of Arts and Sciences University of South Florida Major Professor: Meera Nanjundan, Ph.D. Richard Pollenz, Ph.D. Patrick Bradshaw, Ph.D. Sandy Westerheide, Ph.D. Date of Approval: September 18, 2014 Keywords: Chemotherapeutics, phospholipid scramblase, toll-like receptor, interferon, dsDNA Copyright © 2014, Madhav Karthik Kodigepalli Dedication I dedicate this research at the lotus feet of Bhagwan Sri Sathya Sai Baba and all the Masters for I am what I am due to their divine grace.
  • Arnau Soler2019.Pdf

    Arnau Soler2019.Pdf

    This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: This work is protected by copyright and other intellectual property rights, which are retained by the thesis author, unless otherwise stated. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author. The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author. When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given. Genetic responses to environmental stress underlying major depressive disorder Aleix Arnau Soler Doctor of Philosophy The University of Edinburgh 2019 Declaration I hereby declare that this thesis has been composed by myself and that the work presented within has not been submitted for any other degree or professional qualification. I confirm that the work submitted is my own, except where work which has formed part of jointly-authored publications has been included. My contribution and those of the other authors to this work are indicated below. I confirm that appropriate credit has been given within this thesis where reference has been made to the work of others. I composed this thesis under guidance of Dr. Pippa Thomson. Chapter 2 has been published in PLOS ONE and is attached in the Appendix A, chapter 4 and chapter 5 are published in Translational Psychiatry and are attached in the Appendix C and D, and I expect to submit chapter 6 as a manuscript for publication.
  • Pflugers Final

    Pflugers Final

    CORE Metadata, citation and similar papers at core.ac.uk Provided by Serveur académique lausannois A comprehensive analysis of gene expression profiles in distal parts of the mouse renal tubule. Sylvain Pradervand2, Annie Mercier Zuber1, Gabriel Centeno1, Olivier Bonny1,3,4 and Dmitri Firsov1,4 1 - Department of Pharmacology and Toxicology, University of Lausanne, 1005 Lausanne, Switzerland 2 - DNA Array Facility, University of Lausanne, 1015 Lausanne, Switzerland 3 - Service of Nephrology, Lausanne University Hospital, 1005 Lausanne, Switzerland 4 – these two authors have equally contributed to the study to whom correspondence should be addressed: Dmitri FIRSOV Department of Pharmacology and Toxicology, University of Lausanne, 27 rue du Bugnon, 1005 Lausanne, Switzerland Phone: ++ 41-216925406 Fax: ++ 41-216925355 e-mail: [email protected] and Olivier BONNY Department of Pharmacology and Toxicology, University of Lausanne, 27 rue du Bugnon, 1005 Lausanne, Switzerland Phone: ++ 41-216925417 Fax: ++ 41-216925355 e-mail: [email protected] 1 Abstract The distal parts of the renal tubule play a critical role in maintaining homeostasis of extracellular fluids. In this review, we present an in-depth analysis of microarray-based gene expression profiles available for microdissected mouse distal nephron segments, i.e., the distal convoluted tubule (DCT) and the connecting tubule (CNT), and for the cortical portion of the collecting duct (CCD) (Zuber et al., 2009). Classification of expressed transcripts in 14 major functional gene categories demonstrated that all principal proteins involved in maintaining of salt and water balance are represented by highly abundant transcripts. However, a significant number of transcripts belonging, for instance, to categories of G protein-coupled receptors (GPCR) or serine-threonine kinases exhibit high expression levels but remain unassigned to a specific renal function.
  • Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024

    Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024

    Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo