Genetic Liability for Internalizing Versus Externalizing Behavior Manifests in The
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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. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Temporal Proteomic Analysis of HIV Infection Reveals Remodelling of The
1 1 Temporal proteomic analysis of HIV infection reveals 2 remodelling of the host phosphoproteome 3 by lentiviral Vif variants 4 5 Edward JD Greenwood 1,2,*, Nicholas J Matheson1,2,*, Kim Wals1, Dick JH van den Boomen1, 6 Robin Antrobus1, James C Williamson1, Paul J Lehner1,* 7 1. Cambridge Institute for Medical Research, Department of Medicine, University of 8 Cambridge, Cambridge, CB2 0XY, UK. 9 2. These authors contributed equally to this work. 10 *Correspondence: [email protected]; [email protected]; [email protected] 11 12 Abstract 13 Viruses manipulate host factors to enhance their replication and evade cellular restriction. 14 We used multiplex tandem mass tag (TMT)-based whole cell proteomics to perform a 15 comprehensive time course analysis of >6,500 viral and cellular proteins during HIV 16 infection. To enable specific functional predictions, we categorized cellular proteins regulated 17 by HIV according to their patterns of temporal expression. We focussed on proteins depleted 18 with similar kinetics to APOBEC3C, and found the viral accessory protein Vif to be 19 necessary and sufficient for CUL5-dependent proteasomal degradation of all members of the 20 B56 family of regulatory subunits of the key cellular phosphatase PP2A (PPP2R5A-E). 21 Quantitative phosphoproteomic analysis of HIV-infected cells confirmed Vif-dependent 22 hyperphosphorylation of >200 cellular proteins, particularly substrates of the aurora kinases. 23 The ability of Vif to target PPP2R5 subunits is found in primate and non-primate lentiviral 2 24 lineages, and remodeling of the cellular phosphoproteome is therefore a second ancient and 25 conserved Vif function. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question -
Structure and Expression Analyses of SVA Elements in Relation to Functional Genes
pISSN 1598-866X eISSN 2234-0742 Genomics Inform 2013;11(3):142-148 G&I Genomics & Informatics http://dx.doi.org/10.5808/GI.2013.11.3.142 ORIGINAL ARTICLE Structure and Expression Analyses of SVA Elements in Relation to Functional Genes Yun-Jeong Kwon, Yuri Choi, Jungwoo Eo, Yu-Na Noh, Jeong-An Gim, Yi-Deun Jung, Ja-Rang Lee, Heui-Soo Kim* Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 609-735, Korea SINE-VNTR-Alu (SVA) elements are present in hominoid primates and are divided into 6 subfamilies (SVA-A to SVA-F) and active in the human population. Using a bioinformatic tool, 22 SVA element-associated genes are identified in the human genome. In an analysis of genomic structure, SVA elements are detected in the 5′ untranslated region (UTR) of HGSNAT (SVA-B), MRGPRX3 (SVA-D), HYAL1 (SVA-F), TCHH (SVA-F), and ATXN2L (SVA-F) genes, while some elements are observed in the 3′UTR of SPICE1 (SVA-B), TDRKH (SVA-C), GOSR1 (SVA-D), BBS5 (SVA-D), NEK5 (SVA-D), ABHD2 (SVA-F), C1QTNF7 (SVA-F), ORC6L (SVA-F), TMEM69 (SVA-F), and CCDC137 (SVA-F) genes. They could contribute to exon extension or supplying poly A signals. LEPR (SVA-C), ALOX5 (SVA-D), PDS5B (SVA-D), and ABCA10 (SVA-F) genes also showed alternative transcripts by SVA exonization events. Dominant expression of HYAL1_SVA appeared in lung tissues, while HYAL1_noSVA showed ubiquitous expression in various human tissues. Expression of both transcripts (TDRKH_SVA and TDRKH_noSVA) of the TDRKH gene appeared to be ubiquitous. -
Chapter 2 Gene Regulation and Speciation in House Mice
UC Berkeley UC Berkeley Electronic Theses and Dissertations Title Gene regulation and the genomic basis of speciation and adaptation in house mice (Mus musculus) Permalink https://escholarship.org/uc/item/8ck133qd Author Mack, Katya L Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California Gene regulation and the genomic basis of speciation and adaptation in house mice (Mus musculus) By Katya L. Mack A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Integrative Biology in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Michael W. Nachman, Chair Professor Rasmus Nielsen Professor Craig T. Miller Fall 2018 Abstract Gene regulation and the genomic basis of speciation and adaptation in house mice (Mus musculus) by Katya Mack Doctor of Philosophy in Integrative Biology University of California, Berkeley Professor Michael W. Nachman, Chair Gene expression is a molecular phenotype that is essential to organismal form and fitness. However, how gene regulation evolves over evolutionary time and contributes to phenotypic differences within and between species is still not well understood. In my dissertation, I examined the role of gene regulation in adaptation and speciation in house mice (Mus musculus). In chapter 1, I reviewed theoretical models and empirical data on the role of gene regulation in the origin of new species. I discuss how regulatory divergence between species can result in hybrid dysfunction and point to areas that could benefit from future research. In chapter 2, I characterized regulatory divergence between M. -
Gene Regulation Underlies Environmental Adaptation in House Mice
Downloaded from genome.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Research Gene regulation underlies environmental adaptation in house mice Katya L. Mack,1 Mallory A. Ballinger,1 Megan Phifer-Rixey,2 and Michael W. Nachman1 1Department of Integrative Biology and Museum of Vertebrate Zoology, University of California, Berkeley, California 94720, USA; 2Department of Biology, Monmouth University, West Long Branch, New Jersey 07764, USA Changes in cis-regulatory regions are thought to play a major role in the genetic basis of adaptation. However, few studies have linked cis-regulatory variation with adaptation in natural populations. Here, using a combination of exome and RNA- seq data, we performed expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses to study the genetic architecture of regulatory variation in wild house mice (Mus musculus domesticus) using individuals from five pop- ulations collected along a latitudinal cline in eastern North America. Mice in this transect showed clinal patterns of variation in several traits, including body mass. Mice were larger in more northern latitudes, in accordance with Bergmann’s rule. We identified 17 genes where cis-eQTLs were clinal outliers and for which expression level was correlated with latitude. Among these clinal outliers, we identified two genes (Adam17 and Bcat2) with cis-eQTLs that were associated with adaptive body mass variation and for which expression is correlated with body mass both within and between populations. Finally, we per- formed a weighted gene co-expression network analysis (WGCNA) to identify expression modules associated with measures of body size variation in these mice. -
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 -
Gene Regulation and the Genomic Basis of Speciation and Adaptation in House Mice (Mus Musculus)
Gene regulation and the genomic basis of speciation and adaptation in house mice (Mus musculus) By Katya L. Mack A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Integrative Biology in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Michael W. Nachman, Chair Professor Rasmus Nielsen Professor Craig T. Miller Fall 2018 Abstract Gene regulation and the genomic basis of speciation and adaptation in house mice (Mus musculus) by Katya Mack Doctor of Philosophy in Integrative Biology University of California, Berkeley Professor Michael W. Nachman, Chair Gene expression is a molecular phenotype that is essential to organismal form and fitness. However, how gene regulation evolves over evolutionary time and contributes to phenotypic differences within and between species is still not well understood. In my dissertation, I examined the role of gene regulation in adaptation and speciation in house mice (Mus musculus). In chapter 1, I reviewed theoretical models and empirical data on the role of gene regulation in the origin of new species. I discuss how regulatory divergence between species can result in hybrid dysfunction and point to areas that could benefit from future research. In chapter 2, I characterized regulatory divergence between M. m. domesticus and M. m. musculus associated with male hybrid sterility. The major model for the evolution of post-zygotic isolation proposes that hybrid sterility or inviability will evolve as a product of deleterious interactions (i.e., negative epistasis) between alleles at different loci when joined together in hybrids. As the regulation of gene expression is inherently based on interactions between loci, disruption of gene regulation in hybrids may be a common mechanism for post-zygotic isolation. -
(B6;129.Cg-Gt(ROSA)26Sor Tm20(CAG-Ctgf-GFP)Jsd) Were Crossed with Female Foxd1cre/+ Heterozygote Mice 1, and Experimental Mice Were Selected As Foxd1cre/+; Rs26cig/+
Supplemental Information SI Methods Animal studies Heterozygote mice (B6;129.Cg-Gt(ROSA)26Sor tm20(CAG-Ctgf-GFP)Jsd) were crossed with female Foxd1Cre/+ heterozygote mice 1, and experimental mice were selected as Foxd1Cre/+; Rs26CIG/+. In some studies Coll-GFPTg or TCF/Lef:H2B-GFPTg mice or Foxd1Cre/+; Rs26tdTomatoR/+ mice were used as described 2; 3. Left kidneys were subjected to ureteral obstruction using a posterior surgical approach as described 2. In some experiments recombinant mouse DKK1 (0.5mg/kg) or an equal volume of vehicle was administered by daily IP injection. In the in vivo ASO experiment, either specific Lrp6 (TACCTCAATGCGATTT) or scrambled negative control ASO (AACACGTCTATACGC) (30mg/kg) (Exiqon, LNA gapmers) was administered by IP injection on d-1, d1, d4, and d7. In other experiments anti-CTGF domain-IV antibodies (5mg/kg) or control IgG were administered d-1, d1 and d6. All animal experiments were performed under approved IACUC protocols held at the University of Washington and Biogen. Recombinant protein and antibody generation and characterization Human CTGF domain I (sequence Met1 CPDEPAPRCPAGVSLVLDGCGCCRVCAKQLGELCTERDPCDPHKGLFC), domain I+II (sequence Met1CPDEPAPRCPAGVSLVLDGCGCCRVCAKQLGELCTERDPCDPHKGLFCCIFGGT VYRSGESFQSSCKYQCTCLDGAVGCMPLCSMDVRLPSPDCPFPRRVKLPGKCCEE) were cloned and expressed in 293 cells, and purified by Chelating SFF(Ni) Column, tested for single band by SEC and PAGE, and tested for absence of contamination. Domain-IV (sequence GKKCIRTPKISKPIKFELSGCTSMKTYRAKFCGVCTDGRCCTPHRTTTLPVEFKCPDGE VMKKNMMFIKTCACHYNCPGDNDIFESLYYRKMY) was purchased from Peprotech. Mouse or human DKK1 was generated from the coding sequence with some modifications and a tag. Secreted protein was harvested from 293 cells, and purified by nickel column, and tested for activity in a supertopflash (STF) assay 4. DKK1 showed EC50 of 0.69nM for WNT3a-induced WNT signaling in STF cells. -
Supplementary Material
Table S1 . Genes up-regulated in the CL of stimulated in relation to control animals ( 1.5 fold, P ≤ 0.05). UniGene ID Gene Title Gene Symbol fold change P value Bt.16350.2.A1_s_at guanylate binding protein 5 GBP5 4.42 0.002 Bt.2498.2.A1_a_at fibrinogen gamma chain FGG 3.81 0.002 Bt.440.1.S1_at neurotensin NTS 3.74 0.036 major histocompatibility complex, class I, A /// major Bt.27760.1.S1_at histocompatibility complex, class I, A BoLA /// HLA-A 3.56 0.022 Bt.146.1.S1_at defensin, beta 4A DEFB4A 3.12 0.002 Bt.7165.1.S1_at chemokine (C-X-C motif) ligand 5 CXCL5 3.06 0.031 Bt.15731.1.A1_at V-set and immunoglobulin domain containing 4 VSIG4 3.03 0.047 Bt.22869.1.S2_at fatty acid binding protein 5 (psoriasis-associated) FABP5 3.02 0.006 Bt.4604.1.S1_a_at acyl-CoA synthetase medium-chain family member 1 ACSM1 2.93 0.001 Bt.6406.1.S3_at CCAAT/enhancer binding protein (C/EBP), delta CEBPD 2.92 0.011 Bt.19845.2.A1_at coagulation factor XIII, A1 polypeptide F13A1 2.83 0.005 Bt.209.3.S1_at lysozyme (renal amyloidosis) LYZ 2.77 0.0003 Bt.15908.1.S1_at methyltransferase like 7A METTL7A 2.59 0.007 Bt.28383.1.S1_at granulysin GNLY 2.58 0.034 Bt.20455.1.S1_at Microtubule-associated protein tau MAPT 2.56 0.047 Bt.6556.1.S1_at regakine 1 LOC504773 2.55 0.011 Bt.11259.1.S1_at putative ISG12(a) protein ISG12(A) 2.55 0.037 Bt.28243.1.S1_a_at vanin 1 VNN1 2.54 0.008 Bt.405.1.S1_at follistatin FST 2.52 0.002 Bt.9510.2.A1_a_at T-cell immunoglobulin and mucin domain containing 4 TIMD4 2.47 0.024 Bt.499.1.S1_a_at prolactin receptor PRLR 2.44 0.010 serpin peptidase -
Gene Regulation Underlies Environmental Adaptation in House Mice 2 3 Short Title: Gene Regulation and Adaptation 4 5 6 Katya L
Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press 1 Title: Gene regulation underlies environmental adaptation in house mice 2 3 Short title: Gene regulation and adaptation 4 5 6 Katya L. Mack1, Mallory A. Ballinger1, Megan Phifer-Rixey2, Michael W. Nachman1 7 8 1Department oF Integrative Biology and Museum oF Vertebrate Zoology, University oF 9 CaliFornia, Berkeley, CA 94720, USA 10 2Department oF Biology, Monmouth University, West Long Branch, NJ 07764, USA 11 12 13 Corresponding Author: 14 Michael Nachman 15 Department oF Integrative Biology and Museum oF Vertebrate Zoology 16 3101 Valley LiFe Sciences Building 17 University of California, Berkeley 94707 18 Phone: 510 642-1792 19 Email: [email protected] 20 21 22 Keywords: evolution, adaptation, gene regulation 1 Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press 23 Abstract 24 Changes in cis- regulatory regions are thought to play a major role in the genetic basis oF 25 adaptation. However, few studies have linked cis- regulatory variation with adaptation in 26 natural populations. Here, using a combination oF exome and RNA-seq data, we performed 27 expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses 28 to study the genetic architecture oF regulatory variation in wild house mice (Mus musculus 29 domesticus) using individuals From 5 populations collected along a latitudinal cline in 30 eastern North America. Mice in this transect showed clinal patterns of variation in several 31 traits, including body mass. Mice were larger in more northern latitudes, in accordance 32 with Bergmann’s rule.