GAPVD1 and ANKFY1 Mutations Implicate RAB5 Regulation in Nephrotic Syndrome
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
Supplementary Information Integrative Analyses of Splicing in the Aging Brain: Role in Susceptibility to Alzheimer’S Disease
Supplementary Information Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease Contents 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project 1.2. Mount Sinai Brain Bank Alzheimer’s Disease 1.3. CommonMind Consortium 1.4. Data Availability 2. Supplementary Tables 3. Supplementary Figures Note: Supplementary Tables are provided as separate Excel files. 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project Gene expression data1. Gene expression data were generated using RNA- sequencing from Dorsolateral Prefrontal Cortex (DLPFC) of 540 individuals, at an average sequence depth of 90M reads. Detailed description of data generation and processing was previously described2 (Mostafavi, Gaiteri et al., under review). Samples were submitted to the Broad Institute’s Genomics Platform for transcriptome analysis following the dUTP protocol with Poly(A) selection developed by Levin and colleagues3. All samples were chosen to pass two initial quality filters: RNA integrity (RIN) score >5 and quantity threshold of 5 ug (and were selected from a larger set of 724 samples). Sequencing was performed on the Illumina HiSeq with 101bp paired-end reads and achieved coverage of 150M reads of the first 12 samples. These 12 samples will serve as a deep coverage reference and included 2 males and 2 females of nonimpaired, mild cognitive impaired, and Alzheimer's cases. The remaining samples were sequenced with target coverage of 50M reads; the mean coverage for the samples passing QC is 95 million reads (median 90 million reads). The libraries were constructed and pooled according to the RIN scores such that similar RIN scores would be pooled together. -
Microgenomics of Ameloblastoma
RESEARCH REPORTS Biological P. DeVilliers1, C. Suggs2, D. Simmons2, V. Murrah3, and J.T. Wright2* Microgenomics of 1Department of Pathology, University of Alabama at Ameloblastoma Birmingham; 2Department of Pediatric Dentistry, CB #7450, and 3Department of Oral Pathology, University of North Carolina at Chapel Hill, NC 27599, USA; *corresponding author, [email protected] J Dent Res 90(4):463-469, 2011 ABSTRACT INTRODUCTION Gene expression profiles of human ameloblastoma microdissected cells were characterized with the meloblastoma is an aggressive tumor of odontogenic epithelial origin, purpose of identifying genes and their protein Awith devastating morbidity if left untreated, due to its unlimited growth products that could be targeted as diagnostic and potential. It is characterized by a high rate of recurrence (up to 70%, depend- prognostic markers as well as for potential thera- ing on the treatment modality) and potential to undergo malignant transfor- peutic interventions. Five formalin-fixed, decalci- mation and to metastasize (up to 2% of cases). Malignant ameloblastoma is fied, paraffin-embedded samples of ameloblastoma defined as a histologically benign-appearing ameloblastoma with metastasis were subjected to laser capture microdissection, (Goldenberg et al., 2004; Cardoso et al., 2009). Surgical resection is the treat- linear mRNA amplification, and hybridization to ment of choice, which can cause further morbidity to the craniofacial com- oligonucleotide human 41,000 RNA arrays and plex, with loss of function and esthetics (Olasoji and Enwere, 2003). compared with universal human reference RNA, Gene expression profiling of tumor cell populations has advanced our to determine the gene expression signature. understanding of the pathogenesis of human tumors (Naderi et al., 2004). -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Chemical Genetic Screen Identifies Gapex-5/GAPVD1 and STBD1 As Novel AMPK Substrates
Chemical genetic screen identifies Gapex-5/GAPVD1 and STBD1 as novel AMPK substrates Ducommun, Serge; Deak, Maria; Zeigerer, Anja; Göransson, Olga; Seitz, Susanne; Collodet, Caterina; Madsen, Agnete Bjerregaard; Jensen, Thomas Elbenhardt; Viollet, Benoit; Foretz, Marc; Gut, Philipp; Sumpton, David; Sakamoto, Kei Published in: Cellular Signalling DOI: 10.1016/j.cellsig.2019.02.001 Publication date: 2019 Document version Publisher's PDF, also known as Version of record Document license: CC BY-NC-ND Citation for published version (APA): Ducommun, S., Deak, M., Zeigerer, A., Göransson, O., Seitz, S., Collodet, C., Madsen, A. B., Jensen, T. E., Viollet, B., Foretz, M., Gut, P., Sumpton, D., & Sakamoto, K. (2019). Chemical genetic screen identifies Gapex- 5/GAPVD1 and STBD1 as novel AMPK substrates. Cellular Signalling, 57, 45-57. https://doi.org/10.1016/j.cellsig.2019.02.001 Download date: 24. Sep. 2021 Cellular Signalling 57 (2019) 45–57 Contents lists available at ScienceDirect Cellular Signalling journal homepage: www.elsevier.com/locate/cellsig Chemical genetic screen identifies Gapex-5/GAPVD1 and STBD1 as novel AMPK substrates T Serge Ducommuna,b,1, Maria Deaka, Anja Zeigererc,d,e, Olga Göranssonf, Susanne Seitzc,d,e, Caterina Collodeta,b, Agnete B. Madseng, Thomas E. Jenseng, Benoit Violleth,i,j, Marc Foretzh,i,j, ⁎ Philipp Guta, David Sumptonk, Kei Sakamotoa,b, a Nestlé Research, École Polytechnique Fédérale de Lausanne (EPFL) Innovation Park, bâtiment G, 1015 Lausanne, Switzerland b School of Life Sciences, EPFL, 1015 Lausanne, Switzerland -
(12) Patent Application Publication (10) Pub. No.: US 2006/0088532 A1 Alitalo Et Al
US 20060O88532A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2006/0088532 A1 Alitalo et al. (43) Pub. Date: Apr. 27, 2006 (54) LYMPHATIC AND BLOOD ENDOTHELIAL Related U.S. Application Data CELL GENES (60) Provisional application No. 60/363,019, filed on Mar. (76) Inventors: Kari Alitalo, Helsinki (FI); Taija 7, 2002. Makinen, Helsinki (FI); Tatiana Petrova, Helsinki (FI); Pipsa Publication Classification Saharinen, Helsinki (FI); Juha Saharinen, Helsinki (FI) (51) Int. Cl. A6IR 48/00 (2006.01) Correspondence Address: A 6LX 39/395 (2006.01) MARSHALL, GERSTEIN & BORUN LLP A6II 38/18 (2006.01) 233 S. WACKER DRIVE, SUITE 6300 (52) U.S. Cl. .............................. 424/145.1: 514/2: 514/44 SEARS TOWER (57) ABSTRACT CHICAGO, IL 60606 (US) The invention provides polynucleotides and genes that are (21) Appl. No.: 10/505,928 differentially expressed in lymphatic versus blood vascular endothelial cells. These genes are useful for treating diseases (22) PCT Filed: Mar. 7, 2003 involving lymphatic vessels, such as lymphedema, various inflammatory diseases, and cancer metastasis via the lym (86). PCT No.: PCT/USO3FO6900 phatic system. Patent Application Publication Apr. 27, 2006 Sheet 1 of 2 US 2006/0088532 A1 integrin O9 integrin O1 KIAAO711 KAAO644 ApoD Fig. 1 Patent Application Publication Apr. 27, 2006 Sheet 2 of 2 US 2006/0088532 A1 CN g uueleo-gº US 2006/0O88532 A1 Apr. 27, 2006 LYMPHATIC AND BLOOD ENDOTHELLAL CELL lymphatic vessels, such as lymphangiomas or lymphang GENES iectasis. Witte, et al., Regulation of Angiogenesis (eds. Goldber, I. D. & Rosen, E. M.) 65-112 (Birkauser, Basel, BACKGROUND OF THE INVENTION Switzerland, 1997). -
Supplementary Table S2
1-high in cerebrotropic Gene P-value patients Definition BCHE 2.00E-04 1 Butyrylcholinesterase PLCB2 2.00E-04 -1 Phospholipase C, beta 2 SF3B1 2.00E-04 -1 Splicing factor 3b, subunit 1 BCHE 0.00022 1 Butyrylcholinesterase ZNF721 0.00028 -1 Zinc finger protein 721 GNAI1 0.00044 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 GNAI1 0.00049 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 PDE1B 0.00069 -1 Phosphodiesterase 1B, calmodulin-dependent MCOLN2 0.00085 -1 Mucolipin 2 PGCP 0.00116 1 Plasma glutamate carboxypeptidase TMX4 0.00116 1 Thioredoxin-related transmembrane protein 4 C10orf11 0.00142 1 Chromosome 10 open reading frame 11 TRIM14 0.00156 -1 Tripartite motif-containing 14 APOBEC3D 0.00173 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3D ANXA6 0.00185 -1 Annexin A6 NOS3 0.00209 -1 Nitric oxide synthase 3 SELI 0.00209 -1 Selenoprotein I NYNRIN 0.0023 -1 NYN domain and retroviral integrase containing ANKFY1 0.00253 -1 Ankyrin repeat and FYVE domain containing 1 APOBEC3F 0.00278 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F EBI2 0.00278 -1 Epstein-Barr virus induced gene 2 ETHE1 0.00278 1 Ethylmalonic encephalopathy 1 PDE7A 0.00278 -1 Phosphodiesterase 7A HLA-DOA 0.00305 -1 Major histocompatibility complex, class II, DO alpha SOX13 0.00305 1 SRY (sex determining region Y)-box 13 ABHD2 3.34E-03 1 Abhydrolase domain containing 2 MOCS2 0.00334 1 Molybdenum cofactor synthesis 2 TTLL6 0.00365 -1 Tubulin tyrosine ligase-like family, member 6 SHANK3 0.00394 -1 SH3 and multiple ankyrin repeat domains 3 ADCY4 0.004 -1 Adenylate cyclase 4 CD3D 0.004 -1 CD3d molecule, delta (CD3-TCR complex) (CD3D), transcript variant 1, mRNA. -
Identification of Novel Kirrel3 Gene Splice Variants in Adult Human
Durcan et al. BMC Physiology 2014, 14:11 http://www.biomedcentral.com/1472-6793/14/11 RESEARCH ARTICLE Open Access Identification of novel Kirrel3 gene splice variants in adult human skeletal muscle Peter Joseph Durcan1, Johannes D Conradie1, Mari Van deVyver2 and Kathryn Helen Myburgh1* Abstract Background: Multiple cell types including trophoblasts, osteoclasts and myoblasts require somatic cell fusion events as part of their physiological functions. In Drosophila Melanogaster the paralogus type 1 transmembrane receptors and members of the immunoglobulin superfamily Kin of Irre (Kirre) and roughest (Rst) regulate myoblast fusion during embryonic development. Present within the human genome are three homologs to Kirre termed Kin of Irre like (Kirrel) 1, 2 and 3. Currently it is unknown if Kirrel3 is expressed in adult human skeletal muscle. Results: We investigated (using PCR and Western blot) Kirrel3 in adult human skeletal muscle samples taken at rest and after mild exercise induced muscle damage. Kirrel3 mRNA expression was verified by sequencing and protein presence via blotting with 2 different anti-Kirrel3 protein antibodies. Evidence for three alternatively spliced Kirrel3 mRNA transcripts in adult human skeletal muscle was obtained. Kirrel3 mRNA in adult human skeletal muscle was detected at low or moderate levels, or not at all. This sporadic expression suggests that Kirrel3 is expressed in a pulsatile manner. Several anti Kirrel3 immunoreactive proteins were detected in all adult human skeletal muscle samples analysed and results suggest the presence of different isoforms or posttranslational modification, or both. Conclusion: The results presented here demonstrate for the first time that there are at least 3 splice variants of Kirrel3 expressed in adult human skeletal muscle, two of which have never previously been identified in human muscle. -
KIRREL Is Differentially Expressed in Adipose Tissue From
KIRREL is differentially expressed in adipose tissue from “fertil+” and “fertil-” cows: in vitro role in ovary? Stéphanie Coyral-Castel, Christelle Ramé, Juliette Cognie, Jerôme Lecardonnel, Sylvain Marthey, Diane Esquerré, Christelle Hennequet-Antier, Sébastien Elis, Sébastien Fritz, Mekki Boussaha, et al. To cite this version: Stéphanie Coyral-Castel, Christelle Ramé, Juliette Cognie, Jerôme Lecardonnel, Sylvain Marthey, et al.. KIRREL is differentially expressed in adipose tissue from “fertil+” and “fertil-” cows: invitro role in ovary?. Reproduction -Cambridge- Supplement-, Society for Reproduction and Fertility, 2018, 155 (2), pp.181-196. 10.1530/REP-17-0649. hal-02625059 HAL Id: hal-02625059 https://hal.inrae.fr/hal-02625059 Submitted on 26 May 2020 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. Copyright Page 1 of 49Reproduction Advance Publication first posted on 23 November 2017 as Manuscript REP-17-0649 1 KIRREL is differentially expressed in adipose tissue from “fertil+” and “fertil-” cows: 2 in vitro role in ovary? 3 4 S Coyral-Castel1,2,3,4,5, -
The Use of Phosphoproteomic Data to Identify Altered Kinases and Signaling Pathways in Cancer
The use of phosphoproteomic data to identify altered kinases and signaling pathways in cancer By Sara Renee Savage Thesis Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Biomedical Informatics August 10, 2018 Nashville, Tennessee Approved: Bing Zhang, Ph.D. Carlos Lopez, Ph.D. Qi Liu, Ph.D. ACKNOWLEDGEMENTS The work presented in this thesis would not have been possible without the funding provided by the NLM training grant (T15-LM007450) and the support of the Biomedical Informatics department at Vanderbilt. I am particularly indebted to Rischelle Jenkins, who helped me solve all administrative issues. Furthermore, this work is the result of a collaboration between all members of the Zhang lab and the larger CPTAC consortium. I would like to thank the other CPTAC centers for processing the data, and Chen Huang and Suhas Vasaikar in the Zhang lab for analyzing the colon cancer copy number and proteomic data, respectively. All members of the Zhang lab have been extremely helpful in answering any questions I had and offering suggestions on my work. Finally, I would like to acknowledge my mentor, Bing Zhang. I am extremely grateful for his guidance and for giving me the opportunity to work on these projects. ii TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ................................................................................................ ii LIST OF TABLES............................................................................................................ -
Research Article Clinic-Genomic Association Mining for Colorectal Cancer Using Publicly Available Datasets
Hindawi Publishing Corporation BioMed Research International Volume 2014, Article ID 170289, 10 pages http://dx.doi.org/10.1155/2014/170289 Research Article Clinic-Genomic Association Mining for Colorectal Cancer Using Publicly Available Datasets Fang Liu,1 Yaning Feng,1 Zhenye Li,2 Chao Pan,1 Yuncong Su,1 Rui Yang,1 Liying Song,1 Huilong Duan,1 and Ning Deng1 1 Department of Biomedical Engineering, Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China 2 General Hospital of Ningxia Medical University, Yinchuan 750004, China Correspondence should be addressed to Ning Deng; [email protected] Received 30 March 2014; Accepted 12 May 2014; Published 2 June 2014 Academic Editor: Degui Zhi Copyright © 2014 Fang Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In recent years, a growing number of researchers began to focus on how to establish associations between clinical and genomic data. However, up to now, there is lack of research mining clinic-genomic associations by comprehensively analysing available gene expression data for a single disease. Colorectal cancer is one of the malignant tumours. A number of genetic syndromes have been proven to be associated with colorectal cancer. This paper presents our research on mining clinic-genomic associations for colorectal cancer under biomedical big data environment. The proposed method is engineered with multiple technologies, including extracting clinical concepts using the unified medical language system (UMLS), extracting genes through the literature mining, and mining clinic-genomic associations through statistical analysis. -
Family of Neural Wiring Receptors in Bilaterians Defined by Phylogenetic, Biochemical, and Structural Evidence
Family of neural wiring receptors in bilaterians defined by phylogenetic, biochemical, and structural evidence Shouqiang Chenga,1, Yeonwoo Parkb,1, Justyna D. Kurletoa,c,1, Mili Jeond, Kai Zinnd, Joseph W. Thorntonb,e,f, and Engin Özkana,2 aDepartment of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL 60637; bCommittee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637; cFaculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, 30-387 Krakow, Poland; dDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125; eDepartment of Human Genetics, The University of Chicago, Chicago, IL 60637; and fDepartment of Ecology and Evolution, The University of Chicago, Chicago, IL 60637 Edited by Rachelle Gaudet, Harvard University, Cambridge, MA, and accepted by Editorial Board Member Jeremy Nathans April 8, 2019 (received for review November 5, 2018) The evolution of complex nervous systems was accompanied by the Most of the Dprs and DIPs that have been studied thus far are expansion of numerous protein families, including cell-adhesion expressed exclusively in the nervous system. In the pupal optic molecules, surface receptors, and their ligands. These proteins lobe, the larval ventral nerve cord, olfactory receptor neurons, and mediate axonal guidance, synapse targeting, and other neuronal the neuromuscular system, each Dpr and DIP is expressed in a wiring-related functions. Recently, 32 interacting cell surface pro- unique subset of neurons (5, 7–9). One Dpr is also expressed in teins belonging to two newly defined families of the Ig superfamily postsynaptic muscle cells (10). In the optic lobe, Dprs and DIPs (IgSF) in fruit flies were discovered to label different subsets of are expressed in distinctive combinations in different neuronal neurons in the brain and ventral nerve cord.