DOCSLIB.ORG

Refined Mapping of the Renal Failure Rf-3 Quantitative Trait Locus

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Refined Mapping of the Renal Failure Rf-3 Quantitative Trait Locus BASIC RESEARCH www.jasn.org Refined Mapping of the Renal Failure Rf-3 Quantitative Trait Locus Caitlin C. O’Meara,*† Jozef Lazar,*‡ Matthew Hoffman,*† Carol Moreno,*† and Howard J. Jacob*†§ *Human and Molecular Genetics Center, †Department of Physiology, ‡Department of Dermatology, and §Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin ABSTRACT Rf-3, a quantitative trait locus (QTL) on rat chromosome 3, affects the development of CKD in Fawn- Hooded Hypertensive (FHH) rats. This QTL spans 110 Mb and approximately 1400 genes; therefore, narrowing the position of this locus is necessary to elucidate potential candidate genes. Here, we used congenic models and comparative genomics to refine the Rf-3 candidate region. We generated congenic lines carrying smaller intervals (subcongenics) of the Rf-3 region and used these lines to reduce the Rf-3 candidate region by 94% (to 7.1 Mb). We used comparative genomics to identify QTL for both nephropathy and albuminuria in the syntenic region of this interval for both human and mouse. We also used the overlapping homologous regions to reduce the number of likely positional candidate genes to 13 known or predicted genes. By combining congenic models and cross-species studies, we narrowed the list of candidate genes to a level that we could sequence the whole interval to further identify the causative gene in future studies. J Am Soc Nephrol 22: 518–525, 2011. doi: 10.1681/ASN.2010060661 Chronic kidney disease (CKD) is a growing health sive (FHH) rat is a well-established model for hy- risk in the United States and worldwide, with the pertension-associated kidney disease.16–20 This incidence continuing to rise at an alarming rate.1 particular strain spontaneously develops systolic Epidemiologic studies have shown that familial and and glomerular hypertension, and consequently, ethnic components contribute to an individual’s renal complications, as indicated by proteinuria, al- risk of developing renal complications as a result of buminuria, and glomerular sclerosis.16,18–23 Be- hypertension and/or diabetes.1–5 Human associa- cause of its robust phenotype, we crossed this strain tion and linkage studies have identified specific re- with the normotensive, renal failure–resistant Au- gions of the genome that significantly contribute to gust Copenhagen Irish (ACI) rat and performed F2 renal disease susceptibility6–12; however, the degree linkage analyses to identify regions of the rat ge- of genetic heritability accounted for by these genes nome that cause kidney disease susceptibility in the is only a small percentage of the total heritability.13 FHH rat.20,21 These linkage analyses showed the Consequently, there is a need to pursue other strat- presence of five renal failure quantitative trait loci egies for identifying genes and their associated (QTLs) called Renal failure 1 through 5 (Rf-1 pathways that are driving CKD. The rat model of- fers numerous advantages, such as an abundance of Received June 23, 2010. Accepted October 16, 2010. physiologic data on many well-characterized dis- Published online ahead of print. Publication date available at ease models and available consomic and congenic www.jasn.org. strains that can be used to study the genetic basis of Correspondence: Dr. Howard J. Jacob, HRC5200, 8701 Water- kidney disease.14,15 town Plank Road, Milwaukee, WI 53226. Phone: 414-456-4887; As in humans, genes play a role in the develop- Fax: 414-456-6516; E-mail: [email protected] ment of CKD in rats. The Fawn-Hooded Hyperten- Copyright © 2011 by the American Society of Nephrology 518 ISSN : 1046-6673/2203-518 J Am Soc Nephrol 22: 518–525, 2011 www.jasn.org BASIC RESEARCH through Rf-5). Subsequent phenotypic analysis of single and RESULTS double congenic animals has shown a synergistic relationship between the various Rf QTLs. Specifically, an interaction was Assessment of Albumin Excretion and BP in Rf-1 ؉ identified between Rf-1 and Rf-3, and Rf-1 and Rf-4, whereas, 3؉4 Congenic Strains the Rf-3 and Rf-4 loci had little to no apparent effect on renal To physically narrow the candidate region of the Rf-3 QTL, we gen- function alone.24,25 erated and phenotyped a panel of subcongenic lines targeting the Rf-3 To elucidate the specific gene variant(s) causing the ob- QTL for UAV at 9 weeks of age after UNX. We found that congenic served phenotype, it is necessary to narrow the candidate lines containing the FHH genotype between genetic markers region to a manageable number of genes, because the Rf-3 D3Got102 and D3Got121 had higher UAV compared with other sub- region is 110 Mbp in size and contains Ͼ1400 genes. Our congenic lines (data not shown). To further study the contribution group has previously used this strategy to narrow the Rf-2 of this region to renal impairment, we selected two subcongenic QTL region and identify Rab38 as a candidate gene.22 Be- lines—Rf-1 ϩ 3ϩ4_a (ACI.FHH [D1Mit18-D1Rat90]/[D3Rat6- cause gene–gene interactions have been identified between D3Got149]/[D14Mit11-D14Rat33/D14Rat65-D14Rat90]) and the various Rf QTLs and because of the polygenic nature of Rf-1 ϩ 3ϩ4_b (ACI.FHH [D1Mit18-D1Rat90]/[D3Got102- renal disease, we received triple congenic animals from Dr. D3Got149]/[D14Mit11-D14Rat33/D14Rat65-D14Rat90])—for Abraham Provoost (Erasmus MC, Rotterdam, The Nether- phenotypic analysis. These overlapping congenic lines are geneti- lands) that have an ACI disease-resistant background and cally identical to Rf-1 ϩ 4 except for the Rf-3 region, where FHH-sensitive locus introgressed onto Rf-1 (D1Mit18- Rf-1 ϩ 3ϩ4_a is FHH from D3Rat6 to D3Got149 and Rf-1 ϩ D1Rat90), Rf-3 (D3Rat84-D3Rat59), and Rf-4 (D14Mit11- 3ϩ4_b is FHH from D3Got102 to D3Got149 (Figure 1). At 9 D14Rat33/D14Rat65-D14Rat90), called Rf-1 ϩ 3ϩ4, be- weeks of age, Rf-1 ϩ 3ϩ4_b had significantly higher levels of cause the presence of FHH alleles on the Rf-1 locus, and UAV than Rf-1 ϩ 3ϩ4_a (40.06 Ϯ 7.60 versus 15.40 Ϯ 2.40 possibly the Rf-4 locus, is necessary for Rf-3 to have a mea- mg/d, respectively, P ϭ 0.024) and also compared with surable effect on renal disease.24,25 In preliminary studies, Rf-1 ϩ 4 (11.18 Ϯ 3.18 mg/d, P ϭ 0.002; Figure 2), indicat- we observed that, after unilateral nephrectomy (UNX), albumin excretion (UAV) of Rf-1 ϩ 3ϩ4 is almost three times higher than that of the Rf-1 ϩ 4 double congenics (ACI.FHH [D1Mit18-D1Rat90]/[D14Mit11-D14Rat33/ D14Rat65-D14Rat90]), showing the utility of the triple congenic model for mapping disease- causing variant(s) in Rf-3 on a resistant genome background. In this study, we crossed Rf-1 ϩ 3ϩ4 animals to Rf-1 ϩ 4 animals to generate subcongenic lines targeting the Rf-3 QTL. Phenotypic analysis of these sub- congenic lines showed a 7.1-Mb region of rat chromosome 3 that significantly con- tributes to the early development of renal disease. Interestingly, three separate link- age analysis studies in human and mouse have mapped kidney disease loci con- cordant to this 7.1-Mb candidate re- gion,12,26,27 suggesting that the same ge- netic elements may play a role in renal disease susceptibility across species. By comparing the breakpoints of our candi- date region to the boundaries of mouse and human renal function QTLs, we were able to further narrow down the list of candi- Figure 1. Schematic representation of the flanking markers on rat chromosome 3 for Rf-1 ϩ 4, Rf-1 ϩ 3ϩ4_a, and Rf-1 ϩ 3ϩ4_b congenic lines and the homologous regions date genes from 1400 to just 13 known and in human and mouse. The flanking markers for the FHH rat chromosome 3 (RNO3) are predicted genes. In addition to cross-species D3Got102-D3Got149 for Rf-1 ϩ 3ϩ4_b and for Rf-1 ϩ 3ϩ4_a are D3Rat6-D3Got149. analysis, we also sequenced the entire 7.1-Mb The region differentiating lines a and b (Rf-3_b), from D3Got102 to D3Got121,is region to identify variants between ACI and homologous to two regions on human chromosome 20, from the p end of the FHH potentially responsible for the Rf-3 re- chromosome to approximately 1.3 Mb and from 29 to 37 Mb. Rf-3_b is homologous to nal phenotype. mouse chromosome 2 from approximately 151.4 to 158.1 Mb. J Am Soc Nephrol 22: 518–525, 2011 Fine Mapping the Rf-3 QTL 519 BASIC RESEARCH www.jasn.org Figure 3. Mean arterial pressure (MAP) is elevated in Rf- 1ϩ3ϩ4_b animals. Number of animals was 6, 7, and 6 for Rf-1 ϩ ϩ Figure 2. Rf-1 3 4_b animals excrete higher levels of albumin ϩ 4, Rf-1 ϩ 3ϩ4_a, and Rf-1 ϩ 3ϩ4_b, respectively. **P Ͻ 0.01. ϩ ϩ ϩ than Rf-1 4 and Rf-1 3 4_a animals at 9 weeks of age. Number Statistical comparison was done using a one-way ANOVA fol- ϩ ϩ ϩ of animals was 9, 13, and 16 for Rf-1 4, Rf-1 3 4_a, and lowed by a Holm-Sidak post hoc test. Rf-1 ϩ 3ϩ4_b, respectively. *P Ͻ 0.05; **P Ͻ 0.01. Datasets were not normally distributed, so each data point was log ϩ Ϯ Ͻ ϩ ϩ transformed before statistical analysis. Statistical comparison with Rf-1 4 (0.34 0.10, P 0.001) and Rf-1 3 4_a Ϯ ϭ was done using a one-way ANOVA followed by a Holm-Sidak (0.52 0.05, P 0.004) glomeruli (Figure 4C).
Load more

Recommended publications
  • The Rise and Fall of the Bovine Corpus Luteum
    University of Nebraska Medical Center DigitalCommons@UNMC Theses & Dissertations Graduate Studies Spring 5-6-2017 The Rise and Fall of the Bovine Corpus Luteum Heather Talbott University of Nebraska Medical Center Follow this and additional works at: https://digitalcommons.unmc.edu/etd Part of the Biochemistry Commons, Molecular Biology Commons, and the Obstetrics and Gynecology Commons Recommended Citation Talbott, Heather, "The Rise and Fall of the Bovine Corpus Luteum" (2017). Theses & Dissertations. 207. https://digitalcommons.unmc.edu/etd/207 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@UNMC. It has been accepted for inclusion in Theses & Dissertations by an authorized administrator of DigitalCommons@UNMC. For more information, please contact [email protected]. THE RISE AND FALL OF THE BOVINE CORPUS LUTEUM by Heather Talbott A DISSERTATION Presented to the Faculty of the University of Nebraska Graduate College in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Biochemistry and Molecular Biology Graduate Program Under the Supervision of Professor John S. Davis University of Nebraska Medical Center Omaha, Nebraska May, 2017 Supervisory Committee: Carol A. Casey, Ph.D. Andrea S. Cupp, Ph.D. Parmender P. Mehta, Ph.D. Justin L. Mott, Ph.D. i ACKNOWLEDGEMENTS This dissertation was supported by the Agriculture and Food Research Initiative from the USDA National Institute of Food and Agriculture (NIFA) Pre-doctoral award; University of Nebraska Medical Center Graduate Student Assistantship; University of Nebraska Medical Center Exceptional Incoming Graduate Student Award; the VA Nebraska-Western Iowa Health Care System Department of Veterans Affairs; and The Olson Center for Women’s Health, Department of Obstetrics and Gynecology, Nebraska Medical Center.
    [Show full text]
  • Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
    Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing.
    [Show full text]
  • Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis
    Hindawi Disease Markers Volume 2019, Article ID 3521746, 10 pages https://doi.org/10.1155/2019/3521746 Research Article Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis Wei Liu,1 Jishi Ye,2 and Hong Yan 1 1Department of Anesthesiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China 2Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei, China Correspondence should be addressed to Hong Yan; [email protected] Received 2 November 2018; Accepted 31 December 2018; Published 10 February 2019 Academic Editor: Hubertus Himmerich Copyright © 2019 Wei Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. The neurobiological mechanisms underlying the chemotherapy-induced neuropathic pain are only partially understood. Among them, microglia activation was identified as the key component of neuropathic pain. The aim of this study was to identify differentially expressed genes (DEGs) and pathways associated with vincristine-induced neuropathic pain by using bioinformatics analysis and observe the effects of oxycodone on these DEG expressions in a vincristine-induced microglia activation model. Methods. Based on microarray profile GSE53897, we identified DEGs between vincristine-induced neuropathic pain rats and the control group. Using the ToppGene database, the prioritization DEGs were screened and performed by gene ontology (GO) and signaling pathway enrichment. A protein-protein interaction (PPI) network was used to explore the relationship among DEGs.
    [Show full text]
  • Autophagy Patterns and Prognosis in Uveal Melanomas
    Modern Pathology (2011) 24, 1036–1045 1036 & 2011 USCAP, Inc. All rights reserved 0893-3952/11 $32.00 Autophagy patterns and prognosis in uveal melanomas Alexandra N Giatromanolaki1, Georgios St Charitoudis2, Nikolaos E Bechrakis3, Vassilios P Kozobolis4, Michael I Koukourakis5, Michael H Foerster2 and Efthimios L Sivridis1 1Department of Pathology, Democritus University of Thrace Medical School, Alexandroupolis, Greece; 2Department of Ophthalmology, Charite´ Medical University, Campus Benjamin Franklin, Berlin, Germany; 3Department of Ophthalmology, University of Innsbruck Medical School, Innsbruck, Austria; 4Department of Ophthalmology, Democritus University of Thrace Medical School, Alexandroupolis, Greece and 5Department of Radiotherapy/Oncology, Democritus University of Thrace Medical School, Alexandroupolis, Greece Autophagy is a self-degradation mechanism by which cells recycle their own cytoplasmic constituents. It has been claimed that, under certain conditions, such a process may be associated with tumor progression. In this study, the autophagic activity was investigated in a series of 99 uveal melanomas after immunohistochemical staining for the autophagy-associated proteins MAP1LC3A and BECN1, most commonly known as LC3A and Beclin 1, respectively. These were assessed in parallel with the hypoxia-inducible factor 1a (HIF1A) and its downstream protein lactate dehydrogenase 5 (composed by five LDHA subunits). Increased autophagic reactivity, detected by MAP1LC3A or BECN1, was associated with intense pigmentation and tumor hypoxia. Uveal melanomas with extensive overexpression of BECN1 or those with underexpression of this protein were associated with the worst prognosis, but the former manifested metastases much earlier than the latter; only 58% of patients with extensive BECN1 overexpression were alive at 4 years, compared with 80% of patients with underexpressed patterns.
    [Show full text]
  • ` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2
    ` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2, Stefan Knapp3,4,*, Matthieu Schapira1,5,* 1. Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada 2. Princess Margaret Cancer Centre and Department of Medical Biophysics, University of Toronto , Toronto, ON M5G 1L7, Canada 3. Nuffield Department of Clinical Medicine, Target Discovery Institute, and Structural Genomic Consortium, University of Oxford, Headington, Oxford OX3 7DQ, United Kingdom 4. Institute for Pharmaceutical Chemistry, Johann Wolfgang Goethe University, D-60438 Frankfurt am Main, Germany 5. Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada * Correspondence: [email protected], [email protected] Epigenetic chemical probes are having a strong impact on biological discovery and target validation. Systematic coverage of emerging epigenetic target classes with these potent, selective, cell-active chemical tools will profoundly influence our understanding of the human biology and pathology of chromatin-templated mechanisms. ` Chemical probes are research-enablers Advances in genomics and proteomics methodologies in recent years have made it possible to associate thousands of genes and proteins with specific diseases, biological processes, molecular networks and pathways. However, data from these large scale initiatives alone has not translated widely into new studies on these disease-associated proteins, and the biomedical research community still tends to focus on proteins that were already known before the sequencing of the human genome1. The human kinome for instance, a target class of direct relevance to cancer and other disease areas, is a telling example: based on the number of research articles indexed in pubmed in 2011, 75% of the research activity focused on only 10% of the 518 human kinases – largely the same kinases that were the focus of research before sequencing of the human genome - while 60% of the kinome, some 300 enzymes, was virtually ignored by the community2.
    [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]
  • Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis
    Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma, Anna-Karin Ekman, Cecilia Bivik Eding and Charlotta Enerbäck The self-archived postprint version of this journal article is available at Linköping University Institutional Repository (DiVA): http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-147791 N.B.: When citing this work, cite the original publication. Verma, D., Ekman, A., Bivik Eding, C., Enerbäck, C., (2018), Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis, Journal of Investigative Dermatology, 138(5), 1088-1093. https://doi.org/10.1016/j.jid.2017.11.036 Original publication available at: https://doi.org/10.1016/j.jid.2017.11.036 Copyright: Elsevier http://www.elsevier.com/ Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma*a, Anna-Karin Ekman*a, Cecilia Bivik Edinga and Charlotta Enerbäcka *Authors contributed equally aIngrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Division of Dermatology, Linköping University, Linköping, Sweden Corresponding author: Charlotta Enerbäck Ingrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Linköping University SE-581 85 Linköping, Sweden Phone: +46 10 103 7429 E-mail: [email protected] Short title Differential methylation in psoriasis Abbreviations CGI, CpG island; DMS, differentially methylated site; RRBS, reduced representation bisulphite sequencing Keywords (max 6) psoriasis, epidermis, methylation, Wnt, susceptibility, expression 1 ABSTRACT Psoriasis is a chronic inflammatory skin disease with both local and systemic components. Genome-wide approaches have identified more than 60 psoriasis-susceptibility loci, but genes are estimated to explain only one third of the heritability in psoriasis, suggesting additional, yet unidentified, sources of heritability.
    [Show full text]
  • A CRISPR-Cas9–Engineered Mouse Model for GPI-Anchor Deficiency Mirrors Human Phenotypes and Exhibits Hippocampal Synaptic Dysfunctions
    A CRISPR-Cas9–engineered mouse model for GPI-anchor deficiency mirrors human phenotypes and exhibits hippocampal synaptic dysfunctions Miguel Rodríguez de los Santosa,b,c,d, Marion Rivalane,f, Friederike S. Davidd,g, Alexander Stumpfh, Julika Pitschi,j, Despina Tsortouktzidisi, Laura Moreno Velasquezh, Anne Voigth, Karl Schillingk, Daniele Matteil, Melissa Longe,f, Guido Vogta,c, Alexej Knausd, Björn Fischer-Zirnsaka,c, Lars Wittlerm, Bernd Timmermannn, Peter N. Robinsono,p, Denise Horna, Stefan Mundlosa,c, Uwe Kornaka,c,q, Albert J. Beckeri, Dietmar Schmitzh, York Wintere,f, and Peter M. Krawitzd,1 aInstitute for Medical Genetics and Human Genetics, Charité–Universitätsmedizin Berlin, 13353 Berlin, Germany; bBerlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; cResearch Group Development and Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; dInstitute for Genomic Statistics and Bioinformatics, University of Bonn, 53127 Bonn, Germany; eAnimal Outcome Core Facility of the NeuroCure Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; fInstitute of Cognitive Neurobiology, Humboldt University, 10117 Berlin, Germany; gInstitute of Human Genetics, Faculty of Medicine, University Hospital Bonn, 53127 Bonn, Germany; hNeuroscience Research Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; iSection for Translational Epilepsy Research, Department of Neuropathology, University Hospital Bonn, 53127 Bonn, Germany; jDepartment of Epileptology,
    [Show full text]
  • Tepzz¥ 6Z54za T
    (19) TZZ¥ ZZ_T (11) EP 3 260 540 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 27.12.2017 Bulletin 2017/52 C12N 15/113 (2010.01) A61K 9/127 (2006.01) A61K 31/713 (2006.01) C12Q 1/68 (2006.01) (21) Application number: 17000579.7 (22) Date of filing: 12.11.2011 (84) Designated Contracting States: • Sarma, Kavitha AL AT BE BG CH CY CZ DE DK EE ES FI FR GB Philadelphia, PA 19146 (US) GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO • Borowsky, Mark PL PT RO RS SE SI SK SM TR Needham, MA 02494 (US) • Ohsumi, Toshiro Kendrick (30) Priority: 12.11.2010 US 412862 P Cambridge, MA 02141 (US) 20.12.2010 US 201061425174 P 28.07.2011 US 201161512754 P (74) Representative: Clegg, Richard Ian et al Mewburn Ellis LLP (62) Document number(s) of the earlier application(s) in City Tower accordance with Art. 76 EPC: 40 Basinghall Street 11840099.3 / 2 638 163 London EC2V 5DE (GB) (71) Applicant: The General Hospital Corporation Remarks: Boston, MA 02114 (US) •Thecomplete document including Reference Tables and the Sequence Listing can be downloaded from (72) Inventors: the EPO website • Lee, Jeannie T •This application was filed on 05-04-2017 as a Boston, MA 02114 (US) divisional application to the application mentioned • Zhao, Jing under INID code 62. San Diego, CA 92122 (US) •Claims filed after the date of receipt of the divisional application (Rule 68(4) EPC). (54) POLYCOMB-ASSOCIATED NON-CODING RNAS (57) This invention relates to long non-coding RNAs (IncRNAs), libraries of those ncRNAs that bind chromatin modifiers, such as Polycomb Repressive Complex 2, inhibitory nucleic acids and methods and compositions for targeting IncRNAs.
    [Show full text]
  • 4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
    Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).
    [Show full text]
  • Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
    Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database.
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]