RGMA and IL21R Show Association with Experimental Inflammation and Multiple Sclerosis

Total Page:16

File Type:pdf, Size:1020Kb

RGMA and IL21R Show Association with Experimental Inflammation and Multiple Sclerosis Genes and Immunity (2010) 11, 279–293 & 2010 Macmillan Publishers Limited All rights reserved 1466-4879/10 $32.00 www.nature.com/gene ORIGINAL ARTICLE RGMA and IL21R show association with experimental inflammation and multiple sclerosis R Nohra1, AD Beyeen1, JP Guo2, M Khademi1, E Sundqvist1, MT Hedreul1, F Sellebjerg3, C Smestad4, AB Oturai3, HF Harbo4,5, E Wallstro¨m1, J Hillert6, L Alfredsson7, I Kockum1, M Jagodic1, J Lorentzen2 and T Olsson1 1Department of Clinical Neuroscience, Neuroimmunology Unit, Karolinska Institutet, Stockholm, Sweden; 2Department of Biochemistry and Biophysics, Medical Inflammation Research, Karolinska Institutet, Stockholm, Sweden; 3Danish Multiple Sclerosis Center Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark; 4Department of Neurology, Oslo University Hospital, Ulleva˚l, Oslo, Norway; 5Department of Neurology, Faculty Division Ulleva˚l, Oslo University Hospital, University of Oslo, Oslo, Norway; 6Department of Clinical Neuroscience, Division of Neurology, Karolinska Institutet, Stockholm, Sweden and 7Department of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden Rat chromosome 1 harbors overlapping quantitative trait loci (QTL) for cytokine production and experimental models of inflammatory diseases. We fine-dissected this region that regulated cytokine production, myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE), anti-MOG antibodies and pristane-induced arthritis (PIA) in advanced intercross lines (AILs). Analysis in the tenth and twelfth generation of AILs resolved the region in two narrow QTL, Eae30 and Eae31. Eae30 showed linkage to MOG-EAE, anti-MOG antibodies and levels of interleukin-6 (IL-6). Eae31 showed linkage to EAE, PIA, anti-MOG antibodies and levels of tumor necrosis factor (TNF) and IL-6. Confidence intervals defined a limited set of potential candidate genes, with the most interesting being RGMA, IL21R and IL4R. We tested the association with multiple sclerosis (MS) in a Nordic case–control material. A single nucleotide polymorphism in RGMA associated with MS in males (odds ratio (OR) ¼ 1.33). Polymorphisms of RGMA also correlated with changes in the expression of interferon-g (IFN-g) and TNF in cerebrospinal fluid of MS patients. In IL21R, there was one positively associated (OR ¼ 1.14) and two protective (OR ¼ 0.87 and 0.68) haplotypes. One of the protective haplotypes correlated to lower IFN-g expression in peripheral blood mononuclear cells of MS patients. We conclude that RGMA and IL21R and their pathways are crucial in MS pathogenesis and warrant further studies as potential biomarkers and therapeutic targets. Genes and Immunity (2010) 11, 279–293; doi:10.1038/gene.2009.111; published online 14 January 2010 Keywords: multiple sclerosis; experimental autoimmune encephalomyelitis; autoimmunity; RGMA; IL21R Introduction demonstrated for type 1 diabetes and MS genes.12 Therefore, cross-disciplinary genetics may be rewarding. Common inflammatory autoimmune disorders, such as Discovery of additional genes contributing to MS and multiple sclerosis (MS), type 1 diabetes and rheumatoid their disease regulatory mechanisms may allow the arthritis (RA) are complex chronic diseases with poorly development of more selective therapies and biomarkers understood etiologies. We are particularly interested in in MS. MS that is a chronic inflammatory disease of the central There are many obstacles in studying genetic regula- nervous system. Both environmental and genetic factors tion of autoimmune disorders in human cohorts, includ- contribute to its etiology.1 The human leukocyte antigen ing limited possibility of functional studies and an complex is a major genetic regulator of MS,2–4 whereas uncontrolled contribution of environmental factors. non-human leukocyte antigen genes are numerous and Positioning of disease regulating loci can also be have low odds ratios (ORs).5,6 Only recently, with achieved using animal models in rodents mimicking analysis of very large cohorts, non-human leukocyte the human diseases in which both genetic and environ- antigen MS genes are starting to be unambiguously mental factors can be controlled. Numerous quantitative identified.7–14 Another important concept is the sharing trait loci (QTL) have previously been mapped using of risk genes between inflammatory diseases,15 as now crosses between inbred rodent strains with diverse susceptibilities to autoimmune inflammatory diseases.16 Recent progress suggests that this strategy is productive Correspondence: Dr R Nohra, Department of Clinical Neuroscience, in revealing susceptibility genes and functional path- Neuroimmunology Unit, Neuroimmunology Unit, CMM, L8:04, ways shared between experimental models and complex Karolinska University Hospital, Stockholm SE-171 76, Sweden. 17 E-mail: [email protected] human disorders. Received 9 June 2009; revised 27 November 2009; accepted 30 Experimental autoimmune encephalomyelitis (EAE), November 2009; published online 14 January 2010 a model for MS, has defined pathogenic mechanisms RGMA and IL21R R Nohra et al 280 underlying neuroinflammation, and has allowed MOG-induced EAE (MOG-EAE)29 and in 465 (DA  18 development of treatments for MS. Experimental PVG.1AV1) rats of AIL-G12 subjected to PIA. autoimmune encephalomyelitis induced with myelin Linkage analysis in EAE confirmed two separate QTL oligodendrocyte glycopreotein (MOG) in rats closely overlapping with the loci controlling TNF and IL-6 mimics clinical and pathological features of human MS.19 production (Figure 1b). The first QTL, hereafter named Furthermore, the cytokine orchestration in MS and EAE Eae30, spans 6 Mb between the markers D1Rat217 and correlate well.20–22 Similarly, various animal models for D1Rat270, and showed significant linkage to all clinical RA have been used, with pristane-induced arthritis (PIA) phenotypes in addition to a linkage to the production of being the model of choice for studies on erosive RA and anti-MOG IgG2b (Supplementary Table S1; Figures 1b acute-phase responses in arthritis.23 It best fulfills the and c). Disease susceptibility and increased anti-MOG criteria for diagnosis of RA24 and is characterized IgG2b levels were conferred by the EAE-susceptible DA by pronounced bone and cartilage erosions, presence alleles. The second QTL, Eae31, covering a region of of serum rheumatoid factors and T-cell infiltrations B10 Mb between D1Rat193 and D1Rat68, was linked to in joints.25 all clinical phenotypes and to anti-MOG IgG1, IgG2b and In this study, we investigate a quantitative trait locus total IgG titers (Supplementary Table S1; Figures 1b and on rat chromosome 1, originally identified in a c). The PVG allele drove more severe disease and higher (LEW.1AV1  PVG.1AV1) F2 cross (Lewis  Piebald-Viral- levels of anti-MOG IgGs. For both QTL, there were Glaxo), which carries variants of gene(s) regulating levels effects of sex as an interactive covariate for all linked of tumor necrosis factor (TNF), interleukin (IL)-6 and IL- disease and immune sub-phenotypes in a complex 1b.26 Interestingly, the QTL overlaps loci that regulate EAE manner. On analysis of female and male rats separately and PIA.27,28 Defining genes behind this region might in Eae30, female rats displayed significant linkage to all therefore unravel genetically controlled pathways that clinical phenotypes, but not to anti-MOG IgGs, whereas regulate inflammation in general. Here we aimed first to male rats displayed significant linkage to incidence, day fine-map candidate genes responsible for the regulation of of onset and anti-MOG IgGs. For the Eae31 locus, female EAE and PIA in vivo,aswellasforin vitro cytokine rats also displayed significant linkage to all clinical production after stimulation with lipopolysaccharide phenotypes, but not to the IgG response. In males, there (LPS), and secondly to determine whether any of the was no linkage to clinical phenotypes, but instead to the human homologous genes associate with MS or ex vivo anti-MOG IgGs (Supplementary Table S1). cytokine production. We have refined this large80-Mb In an analogous linkage study on PIA, we identified QTL into two narrow loci: Eae30 and Eae31/Pia32 using the Pia32, spanning B2.1 Mb from D1Rat193 to D1Got334 tenth (G10) and twelfth (G12) generation of advanced and overlapping with Eae31 and the QTL of IL-6 and intercross line (AIL) subjected to EAE and PIA, respec- TNF. Pia32 linked to disease incidence, onset and disease tively. Subsequent investigation of candidate genes from severity (Supplementary Table S2; Figure 1d). Collec- Eae30 and Eae31 in a Nordic MS case–control cohort tively, the Eae31/Pia32 defines a narrow locus controlling demonstrated association of RGMA and IL21R with MS. two different organ-specific inflammatory diseases. Confirmation of linkage data in a congenic strain On the basis of data from the F2 cross, we developed a Results congenic rat strain, PVG.LEW-D1Rat270-D1Rat68 (here- A locus on rat chromosome 1 resolves into two independent after called PVG.LEW) by selectively breeding a frag- QTL that regulate expression of TNF and IL-6 ment from the EAE-susceptible LEW.1AV1 into a genetic A region on rat chromosome 1 was previously linked background of the major histocompatibility complex- to LPS-induced TNF responses in an F2 cross between identical, but EAE-resistant, PVG.1AV1. We used AIL to the EAE-resistant PVG.1AV1 and EAE-susceptible LE- predict how the congenic strain should behave.
Recommended publications
  • WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).
    [Show full text]
  • 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
    [Show full text]
  • Genome-Wide DNA Methylation Analysis Reveals Molecular Subtypes of Pancreatic Cancer
    www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 17), pp: 28990-29012 Research Paper Genome-wide DNA methylation analysis reveals molecular subtypes of pancreatic cancer Nitish Kumar Mishra1 and Chittibabu Guda1,2,3,4 1Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, 68198, USA 2Bioinformatics and Systems Biology Core, University of Nebraska Medical Center, Omaha, NE, 68198, USA 3Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA 4Fred and Pamela Buffet Cancer Center, University of Nebraska Medical Center, Omaha, NE, 68198, USA Correspondence to: Chittibabu Guda, email: [email protected] Keywords: TCGA, pancreatic cancer, differential methylation, integrative analysis, molecular subtypes Received: October 20, 2016 Accepted: February 12, 2017 Published: March 07, 2017 Copyright: Mishra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients.
    [Show full text]
  • Human Induced Pluripotent Stem Cell–Derived Podocytes Mature Into Vascularized Glomeruli Upon Experimental Transplantation
    BASIC RESEARCH www.jasn.org Human Induced Pluripotent Stem Cell–Derived Podocytes Mature into Vascularized Glomeruli upon Experimental Transplantation † Sazia Sharmin,* Atsuhiro Taguchi,* Yusuke Kaku,* Yasuhiro Yoshimura,* Tomoko Ohmori,* ‡ † ‡ Tetsushi Sakuma, Masashi Mukoyama, Takashi Yamamoto, Hidetake Kurihara,§ and | Ryuichi Nishinakamura* *Department of Kidney Development, Institute of Molecular Embryology and Genetics, and †Department of Nephrology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan; ‡Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Hiroshima, Japan; §Division of Anatomy, Juntendo University School of Medicine, Tokyo, Japan; and |Japan Science and Technology Agency, CREST, Kumamoto, Japan ABSTRACT Glomerular podocytes express proteins, such as nephrin, that constitute the slit diaphragm, thereby contributing to the filtration process in the kidney. Glomerular development has been analyzed mainly in mice, whereas analysis of human kidney development has been minimal because of limited access to embryonic kidneys. We previously reported the induction of three-dimensional primordial glomeruli from human induced pluripotent stem (iPS) cells. Here, using transcription activator–like effector nuclease-mediated homologous recombination, we generated human iPS cell lines that express green fluorescent protein (GFP) in the NPHS1 locus, which encodes nephrin, and we show that GFP expression facilitated accurate visualization of nephrin-positive podocyte formation in
    [Show full text]
  • Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm
    Hindawi Complexity Volume 2017, Article ID 9194801, 8 pages https://doi.org/10.1155/2017/9194801 Research Article Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm Jincai Yang,1 Huichao Gu,1 Xingpeng Jiang,1 Qingyang Huang,2 Xiaohua Hu,1 and Xianjun Shen1 1 School of Computer Science, Central China Normal University, Wuhan 430079, China 2School of Life Science, Central China Normal University, Wuhan 430079, China Correspondence should be addressed to Jincai Yang; [email protected] Received 31 March 2017; Revised 26 May 2017; Accepted 8 June 2017; Published 7 August 2017 Academic Editor: Fang-Xiang Wu Copyright © 2017 Jincai Yang 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 the past 20 years, much progress has been made on the genetic analysis of osteoporosis. A number of genes and SNPs associated with osteoporosis have been found through GWAS method. In this paper, we intend to identify the suspected risky SNPs of osteoporosis with computational methods based on the known osteoporosis GWAS-associated SNPs. The process includes two steps. Firstly, we decided whether the genes associated with the suspected risky SNPs are associated with osteoporosis by using random walk algorithm on the PPI network of osteoporosis GWAS-associated genes and the genes associated with the suspected risky SNPs. In order to solve the overfitting problem in ID3 decision tree algorithm, we then classified the SNPs with positive results based on their features of position and function through a simplified classification decision tree which was constructed by ID3 decision tree algorithm with PEP (Pessimistic-Error Pruning).
    [Show full text]
  • Like Dendritic Cells With
    Existence of CD8α-Like Dendritic Cells with a Conserved Functional Specialization and a Common Molecular Signature in Distant Mammalian Species This information is current as of October 6, 2021. Vanessa Contreras, Céline Urien, Rachel Guiton, Yannick Alexandre, Thien-Phong Vu Manh, Thibault Andrieu, Karine Crozat, Luc Jouneau, Nicolas Bertho, Mathieu Epardaud, Jayne Hope, Ariel Savina, Sebastian Amigorena, Michel Bonneau, Marc Dalod and Isabelle Schwartz-Cornil Downloaded from J Immunol 2010; 185:3313-3325; Prepublished online 11 August 2010; doi: 10.4049/jimmunol.1000824 http://www.jimmunol.org/content/185/6/3313 http://www.jimmunol.org/ Supplementary http://www.jimmunol.org/content/suppl/2010/08/11/jimmunol.100082 Material 4.DC1 References This article cites 64 articles, 33 of which you can access for free at: http://www.jimmunol.org/content/185/6/3313.full#ref-list-1 by guest on October 6, 2021 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2010 by The American Association of Immunologists, Inc. All rights reserved.
    [Show full text]
  • Transforming Growth Factor ß1-Mediated Functional Inhibition Of
    Myelodysplastic Syndromes SUPPLEMENTARY APPENDIX Transforming growth factor 1- mediated functional inhibition of mesenchymal stromal celβls in myelodysplastic syndromes and acute myeloid leukemia Stefanie Geyh, 1* Manuel Rodríguez-Paredes, 1,2 * Paul Jäger, 1 Annemarie Koch, 1 Felix Bormann, 2 Julian Gutekunst, 2 Christoph Zilkens, 3 Ulrich Germing, 1 Guido Kobbe, 1 Frank Lyko, 2 Rainer Haas 1 and Thomas Schroeder 1 1Department of Hematology, Oncology and Clinical Immunology, University of Duesseldorf, Medical Faculty; 2Division of Epigenetics, DKFZ- ZMBH Alliance, German Cancer Research Center, Heidelberg and 3Department of Orthopedic Surgery, University of Duesseldorf, Medical Faculty, Germany *SG and MR-P contributed equally to this work. ©2018 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2017.186734 Received: December 19, 2017. Accepted: May 14, 2018. Pre-published: May 17, 2018. Correspondence: [email protected] Figure S1 Downregulated genes Downregulated genes Upregulated Figure S1. Heatmaps showing the 50 most upregulated and downregulated genes between the 3 healthy MSC controls and the 9 RCMD-, RAEB- and AML-derived MSC samples. Color scale depicts the rlog-transformed FPKM values for each gene and every sample. Figure S2 Downregulated genes Downregulated genes Upregulated Figure S2. Heatmaps showing the 50 most upregulated and downregulated genes between the 3 healthy MSC controls and the 3 RCMD, RAEB and AML MSC samples, respectively. Color scales depict the rlog-transformed FPKM values for each gene and every sample. Figure S3 A. B. 0.0015 *** ** <-3 -2 0.0010 RCMD RAEB AML -1 0 1 0.0005 Log2FC LTF 2 CCL26/GAPDH INHBB >3 0.0000 TGFB2 y S h D ML M A ealt ll LTF H a EGF 0.003 *** ** INHBB TGFB2 0.002 INHBB IGFBP7 0.001 GDF11 LIF/GAPDH BMP1 0.000 y L th M TNFSF12 l A FGF13 ea ll MDS H a FGF13 0.0015 * TNFSF10 TNFSF10 0.0010 0.0005 SPP1/GAPDH 0.0000 y th l AML ea H all MDS Figure S3.
    [Show full text]
  • A Study of the Differential Expression Profiles of Keshan Disease Lncrna/Mrna Genes Based on RNA-Seq
    421 Original Article A study of the differential expression profiles of Keshan disease lncRNA/mRNA genes based on RNA-seq Guangyong Huang1, Jingwen Liu2, Yuehai Wang1, Youzhang Xiang3 1Department of Cardiology, Liaocheng People’s Hospital of Shandong University, Liaocheng, China; 2School of Nursing, Liaocheng Vocational & Technical College, Liaocheng, China; 3Shandong Institute for Endemic Disease Control, Jinan, China Contributions: (I) Conception and design: G Huang, Y Xiang; (II) Administrative support: G Huang, Y Wang; (III) Provision of study materials or patients: G Huang, J Liu, Y Xiang; (IV) Collection and assembly of data: G Huang, J Liu; (V) Data analysis and interpretation: J Liu, Y Wang; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. Correspondence to: Guangyong Huang, MD, PhD. Department of Cardiology, Liaocheng People’s Hospital of Shandong University, No. 67 of Dongchang Street, Liaocheng 252000, China. Email: [email protected]. Background: This study aims to analyze the differential expression profiles of lncRNA in Keshan disease (KSD) and to explore the molecular mechanism of the disease occurrence and development. Methods: RNA-seq technology was used to construct the lncRNA/mRNA expression library of a KSD group (n=10) and a control group (n=10), and then Cuffdiff software was used to obtain the gene lncRNA/ mRNA FPKM value as the expression profile of lncRNA/mRNA. The fold changes between the two sets of samples were calculated to obtain differential lncRNA/mRNA expression profiles, and a bioinformatics analysis of differentially expressed genes was performed. Results: A total of 89,905 lncRNAs and 20,315 mRNAs were detected.
    [Show full text]
  • Figure S1. 17-Mer Distribution in the Yangtze Finless Porpoise Genome
    Figure S1. 17-mer distribution in the Yangtze finless porpoise genome. The x-axis is 17-mer depth (X); the y-axis is the number of sequencing reads at that depth. Figure S2. Sequence depth distribution of the assembly data. The x-axis shows the sequencing depth (X) and the y-axis shows the number of bases at a given depth. The results demonstrate that 99% of bases sequencing depth is more than 20. Figure S3. Comparison of gene structure characteristics of Yangtze finless porpoise and other cetaceans. The x-axis represents the length of corresponding genetic element of exon number and the y-axis represents gene density. Figure S4. Phylogeny relationships between the Yangtze finless porpoise and other mammals reconstructed by RAxML with the GTR+G+I model. Table S1. Summary of sequenced reads Raw Reads Qualified Reads1 Total Read Sequence Physical Total Read Sequence Physical Library SRA Data Length Coverage2 Coverage2 Data Length Coverage2 Coverage2 Insert Size (bp) Number (Gb) (bp) (×) (×) (Gb) (bp) (×) (×) 289 58.94 150.00 23.67 22.80 57.84 149.75 23.23 22.41 SRR6923836 462 71.33 150.00 28.65 44.12 70.12 149.74 28.16 43.44 SRR6923837 624 67.47 150.00 27.10 56.36 63.90 149.67 25.66 53.50 SRR6923834 791 57.58 150.00 23.12 60.97 55.39 149.67 22.24 58.78 SRR6923835 4,000 108.73 150.00 43.67 582.22 70.74 150.00 28.41 378.80 SRR6923832 7,000 115.4 150.00 46.35 1,081.39 84.76 150.00 34.04 794.27 SRR6923833 11,000 107.37 150.00 43.12 1,581.08 79.78 150.00 32.04 1,174.81 SRR6923830 18,000 127.46 150.00 51.19 3,071.33 97.75 150.00 39.26 2,355.42 SRR6923831 Total 714.28 - 286.87 6,500.27 580.28 - 233.04 4,881.43 - 1Raw reads in mate-paired libraries were filtered to remove duplicates and reads with low quality and/or adapter contamination, raw reads in paired-end libraries were filtered in the same manner then subjected to k-mer-based correction.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2009/0269772 A1 Califano Et Al
    US 20090269772A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2009/0269772 A1 Califano et al. (43) Pub. Date: Oct. 29, 2009 (54) SYSTEMS AND METHODS FOR Publication Classification IDENTIFYING COMBINATIONS OF (51) Int. Cl. COMPOUNDS OF THERAPEUTIC INTEREST CI2O I/68 (2006.01) CI2O 1/02 (2006.01) (76) Inventors: Andrea Califano, New York, NY G06N 5/02 (2006.01) (US); Riccardo Dalla-Favera, New (52) U.S. Cl. ........... 435/6: 435/29: 706/54; 707/E17.014 York, NY (US); Owen A. (57) ABSTRACT O'Connor, New York, NY (US) Systems, methods, and apparatus for searching for a combi nation of compounds of therapeutic interest are provided. Correspondence Address: Cell-based assays are performed, each cell-based assay JONES DAY exposing a different sample of cells to a different compound 222 EAST 41ST ST in a plurality of compounds. From the cell-based assays, a NEW YORK, NY 10017 (US) Subset of the tested compounds is selected. For each respec tive compound in the Subset, a molecular abundance profile from cells exposed to the respective compound is measured. (21) Appl. No.: 12/432,579 Targets of transcription factors and post-translational modu lators of transcription factor activity are inferred from the (22) Filed: Apr. 29, 2009 molecular abundance profile data using information theoretic measures. This data is used to construct an interaction net Related U.S. Application Data work. Variances in edges in the interaction network are used to determine the drug activity profile of compounds in the (60) Provisional application No. 61/048.875, filed on Apr.
    [Show full text]
  • The Biological Age of a Bloodstain Donor Author(S): Jack Ballantyne, Ph.D
    The author(s) shown below used Federal funding provided by the U.S. Department of Justice to prepare the following resource: Document Title: The Biological Age of a Bloodstain Donor Author(s): Jack Ballantyne, Ph.D. Document Number: 251894 Date Received: July 2018 Award Number: 2009-DN-BX-K179 This resource has not been published by the U.S. Department of Justice. This resource is being made publically available through the Office of Justice Programs’ National Criminal Justice Reference Service. Opinions or points of view expressed are those of the author(s) and do not necessarily reflect the official position or policies of the U.S. Department of Justice. National Center for Forensic Science University of Central Florida P.O. Box 162367 · Orlando, FL 32826 Phone: 407.823.4041 Fax: 407.823.4042 Web site: http://www.ncfs.org/ Biological Evidence _________________________________________________________________________________________________________ The Biological Age of a Bloodstain Donor FINAL REPORT May 27, 2014 Department of Justice, National Institute of justice Award Number: 2009-DN-BX-K179 (1 October 2009 – 31 May 2014) _________________________________________________________________________________________________________ Principal Investigator: Jack Ballantyne, PhD Professor Department of Chemistry Associate Director for Research National Center for Forensic Science P.O. Box 162367 Orlando, FL 32816-2366 Phone: (407) 823 4440 Fax: (407) 823 4042 e-mail: [email protected] 1 This resource was prepared by the author(s) using Federal funds provided by the U.S. Department of Justice. Opinions or points of view expressed are those of the author(s) and do not necessarily reflect the official position or policies of the U.S.
    [Show full text]
  • Supplementary Tables 1
    Supplementary Table S1. Treatment schema for mice using radiotherapy and AZD8055 General treatment schema. Mice received daily AZD8055 administration (via gavage) for 3 weeks and/or 1-2 weeks of 2-Gy daily fractions (Monday-Friday). Doses of each modality varied for the dose escalation phase. For the standard treatment arms, AZD8055 10 mg/Kg and 20 Gy in 10 fractions of radiotherapy were given . Experimental Treatment Groups Week 1 Week 2 Week 3 Treatment totals Untreated Control AZD8055 n/a n/a n/a n/a 10-20 mice XRT n/a n/a n/a AZD8055 Alone AZD8055 ||||||| ||||||| ||||||| 5-20 mg/Kg x 21 days 10-20 mice XRT n/a n/a n/a XRT Alone AZD8055 n/a n/a n/a n/a 10-20 mice XRT ||||| ||||| 20 Gy/ 10 fractions Combined AZD8055 ||||||| ||||||| ||||||| 5-20 mg/Kg x 21 days 10-20 mice XRT ||||| |||||12 Week Obeservation Period 20 Gy / 10 fractions Supplementary Table S2. Treatment Mean XRT Enhancement Cell line Group Dose Densityb Failuresc/Total Failure Rate Ratiod a XRT Alone 60 Gy/cm³ 14/18 78% Rh30 XRT + 7.33 AZD8055 27 Gy/cm³ 4/15 27% XRT Alone 59 Gy/cm³ 3/12 25% Rh18 XRT + 0.83 AZD8055 44 Gy/cm³ 8/15 53% a. Radiotherapy b. Given dose, Gy / volume of tumor at initiation of treatment, cc c. Incomplete/no response or recurrence of xenograft after complete response XRT A Mean Dose/XRT A Fraction Failure Free . XRTAZD Mean Dose/XRTAZD Fraction Failure Free where Fraction Failure Free = 1 – (Failures/Total) / / For Rh30: / 7.33 / / / For Rh18: / 0.83 / Supplementary Table S3.
    [Show full text]