DOCSLIB.ORG

Supplementary Figure S1. Generation of Floxed Nphs2 Exon 2 Allele and Confirmation

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

CONDITIONAL PODOCIN INACTIVATION SUPPLEMENTARY DATA SUPPLEMENTARY FIGURES AND TABLES: Supplementary Figure S1. Generation of floxed Nphs2 exon 2 allele and confirmation of gene targeting. A. A 7.7-kb targeting vector consisting of a loxP site in intron 1-2 and a loxP-Frt-Neo-Frt cassette in intron 2-3 was generated by PCR and inserted into an MCI proprietary vector. The linearized vector was electroporated into ES cells. B. Screening of 400 ES cell clones by Southern blot hybridization, using a Neo probe and a 3' probe, revealed two correctly targeted clones 121 and 130. A Target vector 1 2 NEO 5’ end 3’ end 3’ probe Wild-type allele 1 2 3 9.2 kb Xmn I Xmn I 5’ end neo probe Floxed allele 1 2 NEO 3 5 kb Xmn I Xmn I 7.8 kb Nde I Nde I B Neo probe, NdeI 3’ probe, XmnI WT 121 130 121 130 MW MW - 1 - Supplementary Figure S2. Generation of Nphs2lox2/-,Cre+ mice and excision of exon 2 upon Cre recombinase induction. A. Triallelic Nphs2lox2/-,Cre+ mice were obtained by mating phenotypically normal Nphs2lox2/lox2 mice with Nphs2+/-,Cre+ mice. Mendelian inheritance of these alleles was observed. B. Genotypes were verified by multiplex PCR of tail genomic DNA. C. Cre recombinase activity was induced upon tamoxifen administration, leading to excision of the floxed exon 2 of the Nphs2 gene. D. Cre recombinase activity in the kidney was verified by PCR using a set of forward and reverse primers designed around exon 2 and demonstrating a 692-bp product (before Cre) and a 316-bp product (after Cre) using genomic DNA extracted from the renal cortex. - 2 - A B C D F R FR - 3 - Supplementary Figure S3. Significant correlation (r = 0.827, p<0.0001) between the fold-change in expression levels obtained from the microarray experiment and quantitative real-time PCR of 15 genes at weeks 1, 2, and 4 (n = 45). 10 8 6 4 2 -10 -8 -6 -4 -2 -2 2 4 6 8 10 -4 -6 qRT-PCR fold-change -8 -10 Microarray fold-change - 4 - Supplementary Table S1. Primers and probe sets used for the verification of microarray data using quantitative real-time PCR. Applied Biosystems Gene Gene product Reference 18S 18S ribosomal RNA Hs99999901_s1 Adm Adrenomedullin Mm00437438_g1 Dock1 Dedicator of cytokinesis 1 Mm01269874_m1 Frk Fyn-related kinase Mm00456656_m1 Gas2l3 Growth arrest-specific 2 like 3 Mm02600495_m1 Mitogen-activated protein kinase-activated protein Mapkapk3 Mm00628676_m1 kinase 3 Nphs1 Nephrin Mm00497828_m1 Nphs2 Podocin Mm00499928_m1 Pbk PDZ binding kinase Mm00517793_m1 Ptpro Protein tyrosine phosphatase, receptor type, O Mm00478480_m1 Smad3 SMAD homolog 3 Mm00489641_m1 Smurf1 SMAD specific E3 ubiquitin protein ligase 1 Mm00547102_m1 Tgfb1 Transforming growth factor-beta 1 Mm03024053_m1 Tgfb3 Transforming growth factor-beta 3 Mm01307959_m1 Tgfbr1 Transforming growth factor-beta receptor, type 1 Mm03024015_m1 Tgfbr2 Transforming growth factor-beta receptor, type 2 Mm03024091_m1 - 5 - Supplementary Table S2. Global gene expression profiling, using microarrays, at 1, 2 and 4 weeks after podocin inactivation, in isolated glomeruli of Nphs2lox2/-,Cre+ mice, as compared to control mice. Using thresholds of a t-test p value < 0.001 and at least ± 1.5 fold-change in expression, we found significant perturbations in 42, 62 and 738 annotated and non-annotated genes at weeks 1, 2 and 4, respectively. - 6 - WEEK 1 Probesets Symbol Title Fold-change p 1421244_at Esr1 estrogen receptor 1 (alpha) 93,81 1,97E-05 1452242_at Cep55 centrosomal protein 55 7,17 1,08E-04 1426817_at Mki67 antigen identified by monoclonal antibody Ki 67 6,35 4,77E-04 1454694_a_at Top2a topoisomerase (DNA) II alpha 6,11 6,40E-04 1434815_a_at Mapkapk3 mitogen-activated protein kinase-activated protein kinase 3 5,75 4,49E-06 1448226_at Rrm2 ribonucleotide reductase M2 5,15 1,94E-04 1450920_at Ccnb2 cyclin B2 4,87 3,06E-04 1448627_s_at Pbk PDZ binding kinase 4,85 2,34E-04 1428852_at Dock3 dedicator of cyto-kinesis 3 4,76 8,54E-04 1424278_a_at Birc5 baculoviral IAP repeat-containing 5 4,59 5,49E-04 1416802_a_at Cdca5 cell division cycle associated 5 4,40 7,20E-05 1423775_s_at Prc1 protein regulator of cytokinesis 1 4,08 1,86E-04 1437716_x_at Kif22 kinesin family member 22 3,85 6,94E-04 1436847_s_at Cdca8 cell division cycle associated 8 3,80 7,45E-04 1439377_x_at Cdc20 cell division cycle 20 homolog 3,26 6,12E-04 1453416_at Gas2l3 growth arrest-specific 2 like 3 3,08 3,05E-04 1419153_at 2810417H13Rik RIKEN cDNA 2810417H13 gene 2,63 6,15E-04 1455990_at Kif23 kinesin family member 23 2,40 1,71E-05 1449171_at Ttk Ttk protein kinase 2,37 5,67E-04 1437370_at Sgol2 shugoshin-like 2 2,35 7,32E-04 1422430_at Fignl1 fidgetin-like 1 2,30 4,31E-04 1436707_x_at Ncaph non-SMC condensin I complex, subunit H 2,27 8,90E-04 1418281_at Rad51 RAD51 homolog 2,25 7,52E-04 1422944_a_at Diap3 diaphanous homolog 3 2,13 5,34E-04 1452040_a_at Cdca3 cell division cycle associated 3 2,05 1,32E-04 1426858_at Inhbb inhibin beta-B 2,00 2,27E-04 1416698_a_at Cks1b CDC28 protein kinase 1b 2,00 7,31E-04 1417445_at Kntc2 kinetochore associated 2 1,94 4,61E-04 1429295_s_at Trip13 thyroid hormone receptor interactor 13 1,88 1,23E-04 1431087_at Spbc24 spindle pole body component 24 homolog 1,86 7,90E-04 1438434_at Arhgap11a Rho GTPase activating protein 11A 1,85 8,77E-04 1437580_s_at Nek2 NIMA (never in mitosis gene a)-related expressed kinase 2 1,78 5,34E-04 1416431_at Tubb6 tubulin, beta 6 1,76 3,83E-04 1452305_s_at Cenpn-201 centromere protein N Gene 1,75 5,13E-04 1432417_a_at Tspan2 tetraspanin 2 1,70 1,32E-04 1435773_at 4930547N16Rik RIKEN cDNA 4930547N16 gene 1,55 6,34E-04 1424766_at Ercc6l excision repair cross-complementing rodent repair deficiency, complementation group 6-like 1,55 8,57E-04 1458560_at Aspm asp (abnormal spindle)-like, microcephaly associated 1,53 3,20E-04 1418369_at Prim1 DNA primase, p49 subunit 1,52 3,14E-04 1448878_at Mxd3 Max dimerization protein 3 1,52 7,49E-04 1419838_s_at Plk4 polo-like kinase 4 1,51 2,79E-04 - 7 - WEEK 2 Probesets Symbol Title Fold-change p UPREGULATED 1421244_at Esr1 estrogen receptor 1 (alpha) 90,40 1,46E-06 1438009_at Hist1h2ao histone cluster 1, H2ao gene 7,93 8,16E-04 1416077_at Adm adrenomedullin 3,69 4,99E-04 1434815_a_at Mapkapk3 mitogen-activated protein kinase-activated protein kinase 3 3,50 1,04E-04 1429637_at 2210419I08Rik RIKEN cDNA 2210419I08 gene 2,63 4,62E-04 1416805_at 1110032E23Rik RIKEN cDNA 1110032E23 gene 2,45 3,42E-04 1422128_at Rpl14 ribosomal protein L14 2,44 4,78E-05 1428852_at Dock3 dedicator of cyto-kinesis 3 2,42 1,05E-04 1460601_at Myrip myosin VIIA and Rab interacting protein 2,37 2,82E-04 1448698_at Ccnd1 cyclin D1 1,98 1,03E-04 1418780_at Cyp39a1 cytochrome P450, family 39, subfamily a, polypeptide 1 1,96 6,95E-04 1459860_x_at Trim2 tripartite motif protein 2 1,93 8,49E-06 1454613_at Dpysl3 dihydropyrimidinase-like 3 1,84 9,93E-04 1433509_s_at Reep1 receptor accessory protein 1 1,80 1,89E-05 1431777_a_at Hmgn3 high mobility group nucleosomal binding domain 3 1,78 9,24E-04 1428713_s_at Gins2 GINS complex subunit 2 1,73 1,01E-03 1416205_at Glb1 galactosidase, beta 1 1,69 6,16E-04 1450455_s_at Akr1c12 aldo-keto reductase family 1, member C12 1,65 4,40E-04 1447787_x_at Gja7 gap junction membrane channel protein alpha 7 1,63 5,03E-04 1417719_at Sap30 sin3 associated polypeptide 1,58 1,99E-04 1439887_at Rnf152 ring finger protein 152 1,56 4,98E-04 1426569_a_at Frk fyn-related kinase 1,56 9,10E-04 1426652_at Mcm3 minichromosome maintenance deficient 3 1,55 5,76E-04 1449577_x_at Tpm2 tropomyosin 2, beta 1,54 5,30E-04 1439514_at Cks1b CDC28 protein kinase 1b 1,52 4,13E-04 1423488_at Mmd monocyte to macrophage differentiation-associated 1,52 4,54E-04 1436448_a_at Ptgs1 prostaglandin-endoperoxide synthase 1 1,51 1,62E-04 DOWNREGULATED 1440854_at 2810403A07Rik -1,50 2,71E-04 1436871_at Sfrs7 splicing factor, arginine/serine-rich 7 -1,51 3,30E-04 1455092_at Zfp207 zinc finger protein 207 -1,52 9,75E-04 1456659_at Sytl3 synaptotagmin-like 3 -1,52 8,05E-04 1419499_at Gpam glycerol-3-phosphate acyltransferase, mitochondrial -1,54 9,19E-04 1430152_at Eps15 epidermal growth factor receptor pathway substrate 15 -1,55 3,04E-04 1457771_at Ptpro Protein tyrosine phosphatase, receptor type, O -1,56 3,69E-04 1457302_at Slc20a2 Solute carrier family 20, member 2 -1,58 8,06E-04 1443088_at Sdccag10 serologically defined colon cancer antigen 10 -1,60 4,44E-04 1437181_at Peli2 pellino 2 -1,62 7,98E-04 1456956_at Ikzf2 IKAROS family zinc finger 2 -1,62 2,11E-04 1459381_at Dach1 Dachshund 1 -1,64 5,73E-04 1439769_at Zfp644 Zinc finger protein 644 -1,65 9,85E-04 1415822_at Scd2 stearoyl-Coenzyme A desaturase 2 -1,65 3,36E-04 1440621_at Kitl Kit ligand -1,68 3,70E-04 1452815_at P2ry10 purinergic receptor P2Y, G-protein coupled 10 -1,69 8,50E-04 1438838_at B230206F22Rik RIKEN cDNA B230206F22 gene -1,82 3,29E-04 1443184_at Cdc14a CDC14 cell division cycle 14 homolog A -1,94 6,38E-04 1451702_at Cmtm7 CKLF-like MARVEL transmembrane domain containing 7 -2,01 1,13E-04 1437605_at Nphs2 nephrosis 2 homolog, podocin -2,09 8,76E-04 1429144_at Prei4 preimplantation protein 4 -2,13 2,98E-05 1432352_at Colec12 collectin sub-family member 12 -2,26 7,41E-04 - 8 - 1438295_at Glcci1 Glucocorticoid induced transcript 1 -2,28 9,93E-04 1429951_at Ssbp2 single-stranded DNA binding protein 2 -3,63 2,17E-04 - 9 - WEEK 4 Probesets Symbol Title Fold-change p UPREGULATED 1421244_at Esr1 estrogen receptor 1 (alpha) 58,98 5,87E-06 1426547_at Gc group specific component 12,06 2,46E-04 1431379_a_at Slc13a1 solute carrier family 13 (sodium/sulphate symporters), member 1 9,41 1,49E-04 1448541_at Kns2 kinesin 2 8,29 1,59E-04
Recommended publications
  • Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

    Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis.
  • Rhoa Promotes Epidermal Stem Cell Proliferation Via PKN1-Cyclin D1 Signaling

    Rhoa Promotes Epidermal Stem Cell Proliferation Via PKN1-Cyclin D1 Signaling

    RESEARCH ARTICLE RhoA promotes epidermal stem cell proliferation via PKN1-cyclin D1 signaling Fan Wang1, Rixing Zhan2, Liang Chen1, Xia Dai1, Wenping Wang1, Rui Guo1, Xiaoge Li1, Zhe Li1, Liang Wang1, Shupeng Huang1, Jie Shen1, Shirong Li1☯*, Chuan Cao1☯* 1 Department of Plastic and Reconstructive Surgery, Southwestern Hospital, Third Military Medical University, Chongqing, China, 2 School of Nursing, Third Military Medical University, Chongqing, China ☯ These authors contributed equally to this work. * [email protected] (LS); [email protected] (CC) a1111111111 Abstract a1111111111 a1111111111 a1111111111 a1111111111 Objective Epidermal stem cells (ESCs) play a critical role in wound healing, but the mechanism under- lying ESC proliferation is not well defined. Here, we explore the effects of RhoA on ESC pro- liferation and the possible underlying mechanism. OPEN ACCESS Citation: Wang F, Zhan R, Chen L, Dai X, Wang W, Methods Guo R, et al. (2017) RhoA promotes epidermal (+/+) (-/- stem cell proliferation via PKN1-cyclin D1 Human ESCs were enriched by rapid adhesion to collagen IV. RhoA (G14V), RhoA ) signaling. PLoS ONE 12(2): e0172613. (T19N) and pGFP control plasmids were transfected into human ESCs. The effect of RhoA doi:10.1371/journal.pone.0172613 on cell proliferation was detected by cell proliferation and DNA synthesis assays. Induction Editor: Austin John Cooney, University of Texas at of PKN1 activity by RhoA was determined by immunoblot analysis, and the effects of PKN1 Austin Dell Medical School, UNITED STATES on RhoA in terms of inducing cell proliferation and cyclin D1 expression were detected using Received: August 10, 2016 specific siRNA targeting PKN1. The effects of U-46619 (a RhoA agonist) and C3 transferase Accepted: February 6, 2017 (a RhoA antagonist) on ESC proliferation were observed in vivo.
  • Angio-Associated Migratory Cell Protein Interacts with Epidermal

    Angio-Associated Migratory Cell Protein Interacts with Epidermal

    Cellular Signalling 61 (2019) 10–19 Contents lists available at ScienceDirect Cellular Signalling journal homepage: www.elsevier.com/locate/cellsig Angio-associated migratory cell protein interacts with epidermal growth factor receptor and enhances proliferation and drug resistance in human T non-small cell lung cancer cells Shun Yaoa, Feifei Shia, Yingying Wanga,b, Xiaoyang Suna, Wenbo Suna, Yifeng Zhanga, ⁎ ⁎ Xianfang Liuc, Xiangguo Liua,b, , Ling Sua,b, a Shandong Provincial Key Laboratory of Animal Cell and Developmental Biology, School of Life Sciences, Shandong University, Qingdao, China b Shandong Provincial Collaborative Innovation Center of Cell Biology, School of Life Sciences, Shandong Normal University, Jinan, China c The Department of Otolaryngology Head and Neck Surgery, Shandong Provincial Hospital, Affiliated to Shandong University, Jinan, China ARTICLE INFO ABSTRACT Keywords: Angio-associated migratory cell protein (AAMP) is expressed in some human cancer cells. Previous studies have AAMP shown AAMP high expression predicted poor prognosis. But its biological role in non-small cell lung cancer Proliferation (NSCLC) cells is still unknown. In our present study, we attempted to explore the functions of AAMP in NSCLC Tumorigenesis cells. According to our findings, AAMP knockdown inhibited lung cancer cell proliferation and inhibited lung EGFR cancer cell tumorigenesis in the mouse xenograft model. Epidermal growth factor receptor (EGFR) is a primary Icotinib receptor tyrosine kinase (RTK) that promotes proliferation and plays an important role in cancer pathology. We Doxorubicin found AAMP interacted with EGFR and enhanced its dimerization and phosphorylation at tyrosine 1173 which activated ERK1/2 in NSCLC cells. In addition, we showed AAMP conferred the lung cancer cells resistance to chemotherapeutic agents such as icotinib and doxorubicin.
  • 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.
  • Expression Gene Network Analyses Reveal Molecular Mechanisms And

    Expression Gene Network Analyses Reveal Molecular Mechanisms And

    www.nature.com/scientificreports OPEN Diferential expression and co- expression gene network analyses reveal molecular mechanisms and candidate biomarkers involved in breast muscle myopathies in chicken Eva Pampouille1,2, Christelle Hennequet-Antier1, Christophe Praud1, Amélie Juanchich1, Aurélien Brionne1, Estelle Godet1, Thierry Bordeau1, Fréderic Fagnoul2, Elisabeth Le Bihan-Duval1 & Cécile Berri1* The broiler industry is facing an increasing prevalence of breast myopathies, such as white striping (WS) and wooden breast (WB), and the precise aetiology of these occurrences remains poorly understood. To progress our understanding of the structural changes and molecular pathways involved in these myopathies, a transcriptomic analysis was performed using an 8 × 60 K Agilent chicken microarray and histological study. The study used pectoralis major muscles from three groups: slow-growing animals (n = 8), fast-growing animals visually free from defects (n = 8), or severely afected by both WS and WB (n = 8). In addition, a weighted correlation network analysis was performed to investigate the relationship between modules of co-expressed genes and histological traits. Functional analysis suggested that selection for fast growing and breast meat yield has progressively led to conditions favouring metabolic shifts towards alternative catabolic pathways to produce energy, leading to an adaptive response to oxidative stress and the frst signs of infammatory, regeneration and fbrosis processes. All these processes are intensifed in muscles afected by severe myopathies, in which new mechanisms related to cellular defences and remodelling seem also activated. Furthermore, our study opens new perspectives for myopathy diagnosis by highlighting fne histological phenotypes and genes whose expression was strongly correlated with defects. Te poultry industry relies on the production of fast-growing chickens, which are slaughtered at high weights and intended for cutting and processing.
  • An Animal Model with a Cardiomyocyte-Specific Deletion of Estrogen Receptor Alpha: Functional, Metabolic, and Differential Netwo

    An Animal Model with a Cardiomyocyte-Specific Deletion of Estrogen Receptor Alpha: Functional, Metabolic, and Differential Netwo

    Washington University School of Medicine Digital Commons@Becker Open Access Publications 2014 An animal model with a cardiomyocyte-specific deletion of estrogen receptor alpha: Functional, metabolic, and differential network analysis Sriram Devanathan Washington University School of Medicine in St. Louis Timothy Whitehead Washington University School of Medicine in St. Louis George G. Schweitzer Washington University School of Medicine in St. Louis Nicole Fettig Washington University School of Medicine in St. Louis Attila Kovacs Washington University School of Medicine in St. Louis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Devanathan, Sriram; Whitehead, Timothy; Schweitzer, George G.; Fettig, Nicole; Kovacs, Attila; Korach, Kenneth S.; Finck, Brian N.; and Shoghi, Kooresh I., ,"An animal model with a cardiomyocyte-specific deletion of estrogen receptor alpha: Functional, metabolic, and differential network analysis." PLoS One.9,7. e101900. (2014). https://digitalcommons.wustl.edu/open_access_pubs/3326 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors Sriram Devanathan, Timothy Whitehead, George G. Schweitzer, Nicole Fettig, Attila Kovacs, Kenneth S. Korach, Brian N. Finck, and Kooresh I. Shoghi This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/3326 An Animal Model with a Cardiomyocyte-Specific Deletion of Estrogen Receptor Alpha: Functional, Metabolic, and Differential Network Analysis Sriram Devanathan1, Timothy Whitehead1, George G. Schweitzer2, Nicole Fettig1, Attila Kovacs3, Kenneth S.
  • Product Data Sheet

    Product Data Sheet

    Product Data Sheet ExProfileTM Human AMPK Signaling Related Gene qPCR Array For focused group profiling of human AMPK signaling genes expression Cat. No. QG004-A (4 x 96-well plate, Format A) Cat. No. QG004-B (4 x 96-well plate, Format B) Cat. No. QG004-C (4 x 96-well plate, Format C) Cat. No. QG004-D (4 x 96-well plate, Format D) Cat. No. QG004-E (4 x 96-well plate, Format E) Plates available individually or as a set of 6. Each set contains 336 unique gene primer pairs deposited in one 96-well plate. Introduction The ExProfile human AMPK signaling related gene qPCR array profiles the expression of 336 human genes related to AMPK-mediated signal transduction. These genes are carefully chosen for their close pathway correlation based on a thorough literature search of peer-reviewed publications, mainly including genes that encode AMP-activated protein kinase complex，its regulators and targets involved in many important biological processes, such as glucose uptake, β-oxidation of fatty acids and modulation of insulin secretion. This array allows researchers to study the pathway-related genes to gain understanding of their roles in the different biological processes. QG004 plate 01: 84 unique gene PCR primer pairs QG004 plate 02: 84 unique gene PCR primer pairs QG004 plate 03: 84 unique gene PCR primer pairs QG004 plate 04: 84 unique gene PCR primer pairs Shipping and storage condition Shipped at room temperate Stable for at least 6 months when stored at -20°C Array format GeneCopoeia provides five qPCR array formats (A, B, C, D, and E) suitable for use with the following real- time cyclers.
  • 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.
  • Evidence for Differential Alternative Splicing in Blood of Young Boys With

    Evidence for Differential Alternative Splicing in Blood of Young Boys With

    Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling.
  • Difference in Allelic Expression of the CLCN1 Gene and the Possible Influence on the Myotonia Congenita Phenotype

    Difference in Allelic Expression of the CLCN1 Gene and the Possible Influence on the Myotonia Congenita Phenotype

    European Journal of Human Genetics (2004) 12, 738–743 & 2004 Nature Publishing Group All rights reserved 1018-4813/04 $30.00 www.nature.com/ejhg ARTICLE Difference in allelic expression of the CLCN1 gene and the possible influence on the myotonia congenita phenotype Morten Dun1*, Eskild Colding-Jrgensen2, Morten Grunnet3,5, Thomas Jespersen3, John Vissing4 and Marianne Schwartz1 1Department of Clinical Genetics, 4062, University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark; 2Department of Clinical Neurophysiology 3063,University Hospital, Rigshospitalet, Blegdamsvej 9, DK- 2100 Copenhagen, Denmark; 3Department of Medical Physiology, The Panum Institute, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark; 4Department of Neurology and The Copenhagen Muscle Research Center, University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark Mutations in the CLCN1 gene, encoding a muscle-specific chloride channel, can cause either recessive or dominant myotonia congenita (MC). The recessive form, Becker’s myotonia, is believed to be caused by two loss-of-function mutations, whereas the dominant form, Thomsen’s myotonia, is assumed to be a consequence of a dominant-negative effect. However, a subset of CLCN1 mutations can cause both recessive and dominant MC. We have identified two recessive and two dominant MC families segregating the common R894X mutation. Real-time quantitative RT-PCR did not reveal any obvious association between the total CLCN1 mRNA level in muscle and the mode of inheritance, but the dominant family with the most severe phenotype expressed twice the expected amount of the R894X mRNA allele. Variation in allelic expression has not previously been described for CLCN1, and our finding suggests that allelic variation may be an important modifier of disease progression in myotonia congenita.
  • Ubiquitylome Profiling of Parkin-Null Brain Reveals Dysregulation Of

    Ubiquitylome Profiling of Parkin-Null Brain Reveals Dysregulation Of

    Neurobiology of Disease 127 (2019) 114–130 Contents lists available at ScienceDirect Neurobiology of Disease journal homepage: www.elsevier.com/locate/ynbdi Ubiquitylome profiling of Parkin-null brain reveals dysregulation of calcium T homeostasis factors ATP1A2, Hippocalcin and GNA11, reflected by altered firing of noradrenergic neurons Key J.a,1, Mueller A.K.b,1, Gispert S.a, Matschke L.b, Wittig I.c, Corti O.d,e,f,g, Münch C.h, ⁎ ⁎ Decher N.b, , Auburger G.a, a Exp. Neurology, Goethe University Medical School, 60590 Frankfurt am Main, Germany b Institute for Physiology and Pathophysiology, Vegetative Physiology and Marburg Center for Mind, Brain and Behavior - MCMBB; Clinic for Neurology, Philipps-University Marburg, 35037 Marburg, Germany c Functional Proteomics, SFB 815 Core Unit, Goethe University Medical School, 60590 Frankfurt am Main, Germany d Institut du Cerveau et de la Moelle épinière, ICM, Paris, F-75013, France e Inserm, U1127, Paris, F-75013, France f CNRS, UMR 7225, Paris, F-75013, France g Sorbonne Universités, Paris, F-75013, France h Institute of Biochemistry II, Goethe University Medical School, 60590 Frankfurt am Main, Germany ARTICLE INFO ABSTRACT Keywords: Parkinson's disease (PD) is the second most frequent neurodegenerative disorder in the old population. Among Parkinson's disease its monogenic variants, a frequent cause is a mutation in the Parkin gene (Prkn). Deficient function of Parkin Mitochondria triggers ubiquitous mitochondrial dysfunction and inflammation in the brain, but it remains unclear howse- Parkin lective neural circuits become vulnerable and finally undergo atrophy. Ubiquitin We attempted to go beyond previous work, mostly done in peripheral tumor cells, which identified protein Calcium targets of Parkin activity, an ubiquitin E3 ligase.
  • A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

    A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

    A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing Supplementary Information Supplementary Discussion All SARS-CoV-2 protein and gene functions described in the subnetwork appendices, including the text below and the text found in the individual bait subnetworks, are based on the functions of homologous genes from other coronavirus species. These are mainly from SARS-CoV and MERS-CoV, but when available and applicable other related viruses were used to provide insight into function. The SARS-CoV-2 proteins and genes listed here were designed and researched based on the gene alignments provided by Chan et. al. 1 2020 .​ Though we are reasonably sure the genes here are well annotated, we want to note that not every ​ protein has been verified to be expressed or functional during SARS-CoV-2 infections, either in vitro or in vivo. ​ ​ In an effort to be as comprehensive and transparent as possible, we are reporting the sub-networks of these functionally unverified proteins along with the other SARS-CoV-2 proteins. In such cases, we have made notes within the text below, and on the corresponding subnetwork figures, and would advise that more caution be taken when examining these proteins and their molecular interactions. Due to practical limits in our sample preparation and data collection process, we were unable to generate data for proteins corresponding to Nsp3, Orf7b, and Nsp16. Therefore these three genes have been left out of the following literature review of the SARS-CoV-2 proteins and the protein-protein interactions (PPIs) identified in this study.