Supplemental Table 1 Enriched Genes in Cortical Astrocytes from Aged

Total Page:16

File Type:pdf, Size:1020Kb

Supplemental Table 1 Enriched Genes in Cortical Astrocytes from Aged Supplemental Table 1 Enriched genes in cortical astrocytes from aged and young-adult mice * Genes were present in the astrocyte module from the WGCNA analysis, and contains astrocyte enriched genes compared to microglia and oligodendrocytes # = Fold change of aged astrocyte expression over the average expression of all analyzed samples (microglia, astrocytes: young, old, with and without myelin contamination) $ ; aged = genes only present in the aged astrocyte top 1000 list (used to compare with lists from Cahoy, Lovatt, Doyle; see Fig. 4B), all = genes present in all astrocyte top 1000 lists Gene Symbol* Aged astr. (log2) Young astr.(log2) FC (aged/ aver.)# Location Ptprz1 15.37 15.02 18.76 Plasma Membrane Slc7a10 14.49 14.44 18.28 Plasma Membrane Gjb6 15.13 14.42 18.18 Plasma Membrane Dclk1 14.63 14.28 17.18 unknown Hes5 15.69 15.55 16.94 Nucleus Fgfr3 15.27 14.46 16.54 Plasma Membrane Entpd2 13.85 13.56 15.92 Cytoplasm Grin2c 14.93 14.87 15.75 Plasma Membrane Slc1a2 15.51 15.39 15.58 Plasma Membrane Fjx1 14.36 13.98 14.52 Extracellular Space Slc6a1 14.20 14.16 14.47 Plasma Membrane Kcnk1 12.93 13.49 14.43 Plasma Membrane Ppap2b 16.16 16.10 14.37 Plasma Membrane Fam20a 14.48 14.72 14.00 Extracellular Space Dbx2 13.68 13.32 13.99 Nucleus Itih3 13.93 13.93 13.94 Extracellular Space Htra1 17.12 16.91 13.92 Extracellular Space Atp1a2 14.59 14.48 13.73 Plasma Membrane Scg3 15.71 15.72 13.68 Extracellular Space F3 15.59 15.08 13.51 Plasma Membrane Mmd2 14.22 14.60 13.50 unknown Nrcam 13.73 13.88 13.47 Plasma Membrane Cldn10a 13.37 13.57 13.46 Ppp1r3g 13.18 12.49 13.45 Cytoplasm Atp1b2 15.28 13.92 13.45 Plasma Membrane Fzd2 13.07 13.48 13.38 Plasma Membrane Dtx1 13.81 13.94 13.37 Nucleus Acsl6 12.75 12.10 13.36 Cytoplasm Slc13a5 13.32 13.22 13.31 Plasma Membrane Nkain4 13.92 14.45 13.29 Extracellular Space Cspg5 15.69 15.96 13.29 Extracellular Space Ntsr2 15.61 15.85 13.15 Plasma Membrane Gja1 12.02 11.50 12.85 Plasma Membrane Scara3 13.19 13.73 12.85 Plasma Membrane Timp3 14.48 14.37 12.78 Extracellular Space Luzp2 12.66 12.77 12.70 unknown Rapgef3 14.90 14.72 12.68 Nucleus Cyp4f15 12.78 12.66 12.66 Cytoplasm C030009O12Rik 11.84 11.49 12.65 unknown Dkk3 13.75 12.89 12.53 Extracellular Space Nrxn1 13.85 13.65 12.46 Plasma Membrane ENSMUST00000000102 13.62 13.70 12.29 Cytoplasm Slc4a4 12.47 12.85 12.27 Plasma Membrane Bcan 16.32 15.28 12.25 Extracellular Space Slc6a11 12.45 13.09 11.99 Plasma Membrane Omg 14.01 14.35 11.97 Plasma Membrane Btbd17 14.09 14.23 11.97 Plasma Membrane Slc25a18 13.48 13.40 11.91 Cytoplasm Fkbp10 12.76 12.43 11.88 Cytoplasm Id4 12.51 12.13 11.74 Nucleus Fam181b 13.89 13.94 11.68 unknown ENSMUST00000066583 12.10 11.52 11.67 Cytoplasm Pdpn 12.60 13.03 11.48 Plasma Membrane Mfsd2a 13.09 12.88 11.47 unknown Mlc1 15.82 16.16 11.47 Plasma Membrane Prnp 15.77 15.75 11.40 Plasma Membrane Foxg1 13.14 12.48 11.38 Nucleus Cxcl14 14.80 15.12 11.38 Extracellular Space Bmpr1b 11.54 11.57 11.34 Plasma Membrane Trim9 14.41 14.67 11.24 Cytoplasm Gpm6a 13.32 13.63 11.17 Plasma Membrane Sdc2 11.44 11.15 11.14 Plasma Membrane Ptn 15.07 15.27 11.13 Extracellular Space Ntrk2 14.87 15.11 11.13 Plasma Membrane Ttyh1 15.43 15.17 11.04 Plasma Membrane Crym 13.77 14.31 10.98 Cytoplasm Cml5 10.87 10.03 10.98 unknown 2810432L12Rik 12.42 12.43 10.95 Aqp4 13.65 14.18 10.93 Plasma Membrane ENSMUST00000114270 12.73 12.95 10.87 Extracellular Space Gabrb1 11.92 12.08 10.84 Plasma Membrane Acsbg1 14.99 15.41 10.82 Cytoplasm Nr2f1 13.83 13.39 10.82 Nucleus Cyp2j9 13.52 12.71 10.72 Cytoplasm Ndp 12.02 12.28 10.72 Extracellular Space Itga7 13.18 12.89 10.71 Plasma Membrane Ngef 14.49 14.57 10.70 Cytoplasm Ephx2 11.56 11.23 10.69 Cytoplasm Fam59b 12.42 12.91 10.67 unknown Acsl3 12.54 11.15 10.60 Cytoplasm Slco1c1 12.72 11.98 10.53 Plasma Membrane Slc38a3 13.20 13.33 10.48 Plasma Membrane Sox9 11.57 11.58 10.42 Nucleus Lhx2 13.51 13.97 10.36 Nucleus Sox2 12.00 11.70 10.25 Nucleus Gli3 11.81 11.71 10.24 Nucleus Cdh2 13.30 13.20 10.21 Plasma Membrane AI464131 12.74 13.14 10.19 Nucleus LOC552874 11.93 12.19 10.05 Myh11 11.55 10.45 10.04 Cytoplasm Serpinh1 11.98 12.12 10.04 Extracellular Space 6030451C04Rik 12.43 12.37 9.94 unknown Gnao1 14.00 14.01 9.93 Plasma Membrane Hey1 12.32 12.00 9.88 Nucleus Nr2e1 11.60 11.41 9.84 Nucleus Sqle 13.63 13.37 9.78 Cytoplasm Cbs 14.72 15.00 9.75 Cytoplasm Gpr37l1 14.31 14.15 9.72 Plasma Membrane Megf10 11.87 11.65 9.72 Plasma Membrane Lrig1 12.28 12.14 9.54 Extracellular Space Gdf1 14.86 14.57 9.43 Extracellular Space Bdh1 11.85 12.13 9.39 Cytoplasm Tnfrsf19 12.78 13.18 9.29 Plasma Membrane Grm3 12.42 12.71 9.27 Plasma Membrane Aldh1l1 14.87 15.13 9.25 Cytoplasm Nat8 12.67 12.73 9.24 Nucleus Fermt2 11.96 11.66 9.17 Cytoplasm 2610017I09Rik 14.50 15.01 9.16 unknown Acta2 15.05 14.85 9.16 Cytoplasm LOC100047843 12.41 12.37 9.15 Gm11627 11.07 11.26 9.10 unknown Gabrg1 11.80 11.76 9.10 Plasma Membrane Gm266 10.69 10.30 9.07 unknown Ppp1r3c 12.30 12.22 9.05 Cytoplasm Frmpd1 12.18 12.30 9.04 Cytoplasm Gm6145 11.87 11.57 9.02 unknown Sod3 12.26 12.05 9.00 Extracellular Space Dio2 13.00 13.37 9.00 Cytoplasm Pou3f3 11.26 11.06 8.97 Nucleus Cntfr 11.29 12.23 8.96 Plasma Membrane Kcnn2 11.35 11.86 8.86 Plasma Membrane ENSMUST00000104895 8.96 7.96 8.84 Atp1b1 13.07 13.36 8.83 Plasma Membrane Tmem35 10.40 10.12 8.74 unknown Daam2 13.60 13.89 8.72 unknown Scrg1 13.12 14.12 8.71 Extracellular Space Astn1 11.90 12.23 8.70 unknown Slc25a34 11.70 11.74 8.69 Cytoplasm Mboat2 11.50 10.59 8.58 Cytoplasm Ntm 11.01 10.19 8.58 Plasma Membrane Clmn 12.32 12.22 8.55 Cytoplasm LOC100046032 10.57 10.06 8.52 Nfib 13.12 13.20 8.51 Nucleus Clu 16.95 16.48 8.44 Extracellular Space Efemp1 10.48 9.29 8.38 Extracellular Space 2900062L11Rik 11.69 12.17 8.37 Gucy1a3 11.14 10.47 8.34 Cytoplasm Hepacam 12.61 12.97 8.34 Plasma Membrane Sncg 11.51 10.30 8.32 Cytoplasm Tlcd1 11.44 11.56 8.32 unknown Elovl2 11.39 11.61 8.28 Cytoplasm Ak3l1 11.75 12.03 8.17 Epdr1 12.41 12.88 8.17 Nucleus Notch3 12.18 11.99 8.16 Plasma Membrane Ltbp1 10.06 9.75 8.16 Extracellular Space 6720482D04 9.89 9.52 8.16 unknown Wnk2 12.80 12.96 8.12 Cytoplasm Lrrc4b 14.53 14.97 8.11 unknown Rbpms2 11.52 11.27 8.09 unknown 2610034M16Rik 10.84 11.25 8.03 unknown Fabp7 12.50 13.17 8.02 Cytoplasm Nxn 12.83 12.77 8.00 Nucleus Alpl 10.58 9.39 7.98 Plasma Membrane Celsr1 11.07 11.12 7.97 Plasma Membrane 1190002H23Rik 13.86 14.61 7.97 Kctd15 11.61 11.52 7.94 unknown Cnn3 13.85 14.02 7.94 Cytoplasm Bmp7 10.95 10.89 7.94 Extracellular Space Baalc 13.15 14.16 7.92 Cytoplasm Fam171b 12.45 12.08 7.91 unknown Acot11 13.02 13.15 7.87 Cytoplasm Klf9 12.62 12.18 7.81 Nucleus Ndrg2 15.47 15.28 7.78 Cytoplasm Ptrf 15.06 14.94 7.78 Nucleus Adora2b 11.34 11.50 7.78 Plasma Membrane Rpe65 10.18 9.27 7.73 Cytoplasm Tagln3 12.06 12.24 7.65 Extracellular Space Syne1 11.08 10.42 7.63 Nucleus Gldc 12.83 13.59 7.60 Cytoplasm Dner 10.86 11.27 7.59 Plasma Membrane B3galt1 9.65 10.14 7.56 Cytoplasm Timp4 12.16 12.39 7.54 Extracellular Space Agxt2l1 11.85 11.52 7.54 unknown Efr3b 13.49 13.41 7.52 unknown Slc2a4 10.62 10.23 7.45 Plasma Membrane Angptl4 12.52 12.69 7.41 Extracellular Space Plcb1 10.87 10.32 7.41 Cytoplasm Lingo4 10.62 10.29 7.39 unknown Pamr1 11.97 12.05 7.36 Extracellular Space 2610301F02Rik 10.07 9.73 7.36 Cyp2j8 10.73 10.09 7.34 unknown Raver2 11.31 11.21 7.29 Nucleus Nhsl1 10.74 10.84 7.27 unknown Tst 13.02 13.45 7.25 Cytoplasm Dhcr24 13.27 13.80 7.24 Cytoplasm Fam163a 10.77 11.27 7.23 unknown Cyp4f14 10.92 11.60 7.23 Cytoplasm Fam59a 9.75 9.56 7.23 unknown 9430011C21Rik 9.28 8.54 7.21 unknown Mt2 16.46 16.45 7.20 unknown S1pr1 15.72 15.80 7.19 Plasma Membrane Limch1 12.97 12.84 7.18 unknown Abcb9 14.36 14.10 7.18 Cytoplasm Unc13c 8.84 8.27 7.16 Cytoplasm 1700084C01Rik 9.74 10.46 7.14 unknown 1200009O22Rik 10.41 10.62 7.13 Mfge8 17.58 17.45 7.13 Extracellular Space Caskin2 10.88 10.73 7.11 Cytoplasm Cmtm5 14.18 14.86 7.11 Extracellular Space Ednra 10.90 10.69 7.08 Plasma Membrane Chchd10 15.56 15.31 7.06 Cytoplasm Pcdh17 10.89 10.99 7.06 unknown Kank1 11.49 11.69 7.05 Nucleus Maob 11.46 12.23 7.03 Cytoplasm Lgi1 10.07 9.54 6.97 Plasma Membrane Tpm2 12.29 11.53 6.96 Cytoplasm Adcyap1r1 11.23 11.56 6.96 Plasma Membrane Ppp2r2b 11.25 11.73 6.95 Cytoplasm Pdk4 10.37 10.60 6.94 Cytoplasm Cpe 16.93 17.38 6.93 Plasma Membrane Tgfb2 11.13 10.99 6.87 Extracellular Space Tagln 14.93 15.29 6.86 Cytoplasm Gstm5 15.02 15.09 6.84 Cytoplasm Hapln1 10.52 11.05 6.81 Extracellular Space Iglon5 11.37 11.90 6.81 unknown Rnf182 10.57 10.74 6.80 Cytoplasm Nat8b 13.40 13.58 6.79 Lysmd2 11.45 11.40 6.78 unknown Aifm3 13.04 13.93 6.78 Cytoplasm Me1 11.45 11.99 6.77 Cytoplasm Prkcdbp 11.91 11.64 6.76 Cytoplasm Pik3ip1 13.03 12.62 6.75 unknown Bai1 13.14 13.63 6.75 Plasma Membrane Kcnj16 11.68 11.77 6.75 Plasma Membrane Fstl1 11.05 10.98 6.73 Extracellular Space Pdgfrb 11.25 11.60 6.73 Plasma Membrane Igdcc4 11.82 12.28 6.72 Plasma Membrane Gm715 9.89 9.86 6.71 unknown Kbtbd11 13.34 13.34 6.71 unknown LOC100047857 10.35 10.54 6.70 Gdpd2 11.46 12.26 6.67 Plasma Membrane Inhbb 10.51 10.64 6.67 Extracellular Space 6330418B08Rik 9.90 9.64 6.66 unknown Paqr6 12.23 12.55 6.65 unknown Ogn 9.02 7.19 6.65 Extracellular Space Sfxn5 13.72 13.87 6.65 Cytoplasm Igfbp2 11.22 11.61 6.63 Extracellular Space Ezr 13.27 13.18 6.62 Plasma Membrane Fzd1 10.57 10.41 6.62 Plasma Membrane Igsf1 11.12 11.34 6.61 Plasma Membrane ENSMUST00000110346 9.64 9.50 6.60 Plasma Membrane Fezf2 9.70 9.45 6.59 unknown Rab30 8.99 9.03 6.58 Cytoplasm Adk 13.99 13.93 6.54 Nucleus Paqr8 9.98 9.65 6.53 Plasma Membrane Me3 9.90 9.22 6.52 Cytoplasm XM_001474456
Recommended publications
  • Association Analyses of Known Genetic Variants with Gene
    ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac.
    [Show full text]
  • From Inverse Agonism to 'Paradoxical Pharmacology' Richard A
    International Congress Series 1249 (2003) 27-37 From inverse agonism to 'Paradoxical Pharmacology' Richard A. Bond*, Kenda L.J. Evans, Zsirzsanna Callaerts-Vegh Department of Pharmacological and Pharmaceutical Sciences, University of Houston, 521 Science and Research Bldg 2, 4800 Caltioun, Houston, TX 77204-5037, USA Received 16 April 2003; accepted 16 April 2003 Abstract The constitutive or spontaneous activity of G protein-coupled receptors (GPCRs) and compounds acting as inverse agonists is a recent but well-established phenomenon. Dozens of receptor subtypes for numerous neurotransmitters and hormones have been shown to posses this property. However, do to the apparently low percentage of receptors in the spontaneously active state, the physiologic relevance of these findings remains questionable. The possibility that the reciprocal nature of the effects of agonists and inverse agonists may extend to cellular signaling is discussed, and that this may account for the beneficial effects of certain p-adrenoceptor inverse agonists in the treatment of heart failure. © 2003 Elsevier Science B.V. All rights reserved. Keywords. Inverse agonism; GPCR; Paradoxical pharmacology 1. Brief history of inverse agonism at G protein-coupled receptors For approximately three-quarters of a century, ligands that interacted with G protein- coupled receptors (GPCRs) were classified either as agonists or antagonists. Receptors were thought to exist in a single quiescent state that could only induce cellular signaling upon agonist binding to the receptor to produce an activated state of the receptor. In this model, antagonists had no cellular signaling ability on their own, but did bind to the receptor and prevented agonists from being able to bind and activate the receptor.
    [Show full text]
  • Table 2. Significant
    Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S.
    [Show full text]
  • New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology
    Cancer Research and Treatment 2003;35(4):304-313 New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology Yong-Wan Kim, Ph.D.1, Min-Je Suh, M.S.1, Jin-Sik Bae, M.S.1, Su Mi Bae, M.S.1, Joo Hee Yoon, M.D.2, Soo Young Hur, M.D.2, Jae Hoon Kim, M.D.2, Duck Young Ro, M.D.2, Joon Mo Lee, M.D.2, Sung Eun Namkoong, M.D.2, Chong Kook Kim, Ph.D.3 and Woong Shick Ahn, M.D.2 1Catholic Research Institutes of Medical Science, 2Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul; 3College of Pharmacy, Seoul National University, Seoul, Korea Purpose: This study utilized both mRNA differential significant genes of unknown function affected by the display and the Gene Ontology (GO) analysis to char- HPV-16-derived pathway. The GO analysis suggested that acterize the multiple interactions of a number of genes the cervical cancer cells underwent repression of the with gene expression profiles involved in the HPV-16- cancer-specific cell adhesive properties. Also, genes induced cervical carcinogenesis. belonging to DNA metabolism, such as DNA repair and Materials and Methods: mRNA differential displays, replication, were strongly down-regulated, whereas sig- with HPV-16 positive cervical cancer cell line (SiHa), and nificant increases were shown in the protein degradation normal human keratinocyte cell line (HaCaT) as a con- and synthesis. trol, were used. Each human gene has several biological Conclusion: The GO analysis can overcome the com- functions in the Gene Ontology; therefore, several func- plexity of the gene expression profile of the HPV-16- tions of each gene were chosen to establish a powerful associated pathway, identify several cancer-specific cel- cervical carcinogenesis pathway.
    [Show full text]
  • Nuclear Organization and the Epigenetic Landscape of the Mus Musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected]
    University of Connecticut OpenCommons@UConn Doctoral Dissertations University of Connecticut Graduate School 8-9-2019 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected] Follow this and additional works at: https://opencommons.uconn.edu/dissertations Recommended Citation Liu, Alicia, "Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome" (2019). Doctoral Dissertations. 2273. https://opencommons.uconn.edu/dissertations/2273 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia J. Liu, Ph.D. University of Connecticut, 2019 ABSTRACT X-linked imprinted genes have been hypothesized to contribute parent-of-origin influences on social cognition. A cluster of imprinted genes Xlr3b, Xlr4b, and Xlr4c, implicated in cognitive defects, are maternally expressed and paternally silent in the murine brain. These genes defy classic mechanisms of autosomal imprinting, suggesting a novel method of imprinted gene regulation. Using Xlr3b and Xlr4c as bait, this study uses 4C-Seq on neonatal whole brain of a 39,XO mouse model, to provide the first in-depth analysis of chromatin dynamics surrounding an imprinted locus on the X-chromosome. Significant differences in long-range contacts exist be- tween XM and XP monosomic samples. In addition, XM interaction profiles contact a greater number of genes linked to cognitive impairment, abnormality of the nervous system, and abnormality of higher mental function. This is not a pattern that is unique to the imprinted Xlr3/4 locus. Additional Alicia J. Liu - University of Connecticut - 2019 4C-Seq experiments show that other genes on the X-chromosome, implicated in intellectual disability and/or ASD, also produce more maternal contacts to other X-linked genes linked to cognitive impairment.
    [Show full text]
  • Genetic Basis of Simple and Complex Traits with Relevance to Avian Evolution
    Genetic basis of simple and complex traits with relevance to avian evolution Małgorzata Anna Gazda Doctoral Program in Biodiversity, Genetics and Evolution D Faculdade de Ciências da Universidade do Porto 2019 Supervisor Miguel Jorge Pinto Carneiro, Auxiliary Researcher, CIBIO/InBIO, Laboratório Associado, Universidade do Porto Co-supervisor Ricardo Lopes, CIBIO/InBIO Leif Andersson, Uppsala University FCUP Genetic basis of avian traits Nota Previa Na elaboração desta tese, e nos termos do número 2 do Artigo 4º do Regulamento Geral dos Terceiros Ciclos de Estudos da Universidade do Porto e do Artigo 31º do D.L.74/2006, de 24 de Março, com a nova redação introduzida pelo D.L. 230/2009, de 14 de Setembro, foi efetuado o aproveitamento total de um conjunto coerente de trabalhos de investigação já publicados ou submetidos para publicação em revistas internacionais indexadas e com arbitragem científica, os quais integram alguns dos capítulos da presente tese. Tendo em conta que os referidos trabalhos foram realizados com a colaboração de outros autores, o candidato esclarece que, em todos eles, participou ativamente na sua conceção, na obtenção, análise e discussão de resultados, bem como na elaboração da sua forma publicada. Este trabalho foi apoiado pela Fundação para a Ciência e Tecnologia (FCT) através da atribuição de uma bolsa de doutoramento (PD/BD/114042/2015) no âmbito do programa doutoral em Biodiversidade, Genética e Evolução (BIODIV). 2 FCUP Genetic basis of avian traits Acknowledgements Firstly, I would like to thank to my all supervisors Miguel Carneiro, Ricardo Lopes and Leif Andersson, for the demanding task of supervising myself last four years.
    [Show full text]
  • Environmental Influences on Endothelial Gene Expression
    ENDOTHELIAL CELL GENE EXPRESSION John Matthew Jeff Herbert Supervisors: Prof. Roy Bicknell and Dr. Victoria Heath PhD thesis University of Birmingham August 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Tumour angiogenesis is a vital process in the pathology of tumour development and metastasis. Targeting markers of tumour endothelium provide a means of targeted destruction of a tumours oxygen and nutrient supply via destruction of tumour vasculature, which in turn ultimately leads to beneficial consequences to patients. Although current anti -angiogenic and vascular targeting strategies help patients, more potently in combination with chemo therapy, there is still a need for more tumour endothelial marker discoveries as current treatments have cardiovascular and other side effects. For the first time, the analyses of in-vivo biotinylation of an embryonic system is performed to obtain putative vascular targets. Also for the first time, deep sequencing is applied to freshly isolated tumour and normal endothelial cells from lung, colon and bladder tissues for the identification of pan-vascular-targets. Integration of the proteomic, deep sequencing, public cDNA libraries and microarrays, delivers 5,892 putative vascular targets to the science community.
    [Show full text]
  • 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.
    [Show full text]
  • Nuclear Factor I/B Is an Oncogene in Small Cell Lung Cancer
    Nuclear Factor I/B is an Oncogene in Small Cell Lung Cancer The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Dooley, A. L. et al. “Nuclear factor I/B is an oncogene in small cell lung cancer.” Genes & Development 25 (2011): 1470-1475. As Published http://dx.doi.org/10.1101/gad.2046711 Publisher Cold Spring Harbor Laboratory Press in association with The Genetics Society Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/66512 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike 3.0 Detailed Terms http://creativecommons.org/licenses/by-nc-sa/3.0/ Dooley 1 Nuclear Factor I/B is an Oncogene in Small Cell Lung Cancer Alison L. Dooley1, Monte M. Winslow1, Derek Y. Chiang2,3,4, Shantanu Banerji2,3, Nicolas Stransky2, Talya L. Dayton1, Eric L. Snyder1, Stephanie Senna1, Charles A. Whittaker1, Roderick T. Bronson5, Denise Crowley1, Jordi Barretina2,3, Levi Garraway2,3, Matthew Meyerson2,3, Tyler Jacks1,6 1David H. Koch Institute for Integrative Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 2The Broad Institute, Cancer Program, Cambridge, Massachusetts, USA 3Dana-Farber Cancer Institute, Department of Medical Oncology and Center for Cancer Genome Discovery, Boston, Massachusetts, USA 4Current address: Lineberger Comprehensive Cancer Center, 450 West Drive, CB #7295, Chapel Hill, North Carolina, USA 5Department of Pathology, Tufts University School of Medicine and Veterinary Medicine, North Grafton, Massachusetts, USA 6Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA Key Words: Small Cell Lung Cancer, Mouse model, Nuclear Factor I/B Dooley 2 Abstract Small cell lung cancer (SCLC) is an aggressive cancer often diagnosed after it has metastasized.
    [Show full text]
  • Guthrie Cdna Resource Center
    cDNA Resource Center cDNA Resource Center Catalog cDNA Resource Center Missouri University of Science and Technology 400 W 11th Rolla, MO 65409 TEL: (573) 341-7610 FAX: (573) 341-7609 EMAIL: [email protected] www.cdna.org September, 2008 1 cDNA Resource Center Visit our web site for product updates 2 cDNA Resource Center The cDNA Resource Center The cDNA Resource Center is a service provided by the faculty of the Department of Biological Sciences of Missouri University of Science and Technology. The purpose of the cDNA Resource Center is to further scientific investigation by providing cDNA clones of human proteins involved in signal transduction processes. This is achieved by providing high quality clones for important signaling proteins in a timely manner. By high quality, we mean that the clones are • Sequence verified • Propagated in a versatile vector useful in bacterial and mammalian systems • Free of extraneous 3' and 5' untranslated regions • Expression verified (in most cases) by coupled in vitro transcription/translation assays • Available in wild-type, epitope-tagged and common mutant forms (e.g., constitutively- active or dominant negative) By timely, we mean that the clones are • Usually shipped within a day from when you place your order. Clones can be ordered from our web pages, by FAX or by phone. Within the United States, clones are shipped by overnight courier (FedEx); international orders are shipped International Priority (FedEx). The clones are supplied for research purposes only. Details on use of the material are included on the Material Transfer Agreement (page 3). Clones are distributed by agreement in Invitrogen's pcDNA3.1+ vector.
    [Show full text]
  • Differential Gene Expression in Oligodendrocyte Progenitor Cells, Oligodendrocytes and Type II Astrocytes
    Tohoku J. Exp. Med., 2011,Differential 223, 161-176 Gene Expression in OPCs, Oligodendrocytes and Type II Astrocytes 161 Differential Gene Expression in Oligodendrocyte Progenitor Cells, Oligodendrocytes and Type II Astrocytes Jian-Guo Hu,1,2,* Yan-Xia Wang,3,* Jian-Sheng Zhou,2 Chang-Jie Chen,4 Feng-Chao Wang,1 Xing-Wu Li1 and He-Zuo Lü1,2 1Department of Clinical Laboratory Science, The First Affiliated Hospital of Bengbu Medical College, Bengbu, P.R. China 2Anhui Key Laboratory of Tissue Transplantation, Bengbu Medical College, Bengbu, P.R. China 3Department of Neurobiology, Shanghai Jiaotong University School of Medicine, Shanghai, P.R. China 4Department of Laboratory Medicine, Bengbu Medical College, Bengbu, P.R. China Oligodendrocyte precursor cells (OPCs) are bipotential progenitor cells that can differentiate into myelin-forming oligodendrocytes or functionally undetermined type II astrocytes. Transplantation of OPCs is an attractive therapy for demyelinating diseases. However, due to their bipotential differentiation potential, the majority of OPCs differentiate into astrocytes at transplanted sites. It is therefore important to understand the molecular mechanisms that regulate the transition from OPCs to oligodendrocytes or astrocytes. In this study, we isolated OPCs from the spinal cords of rat embryos (16 days old) and induced them to differentiate into oligodendrocytes or type II astrocytes in the absence or presence of 10% fetal bovine serum, respectively. RNAs were extracted from each cell population and hybridized to GeneChip with 28,700 rat genes. Using the criterion of fold change > 4 in the expression level, we identified 83 genes that were up-regulated and 89 genes that were down-regulated in oligodendrocytes, and 92 genes that were up-regulated and 86 that were down-regulated in type II astrocytes compared with OPCs.
    [Show full text]
  • 140503 IPF Signatures Supplement Withfigs Thorax
    Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network.
    [Show full text]