DOCSLIB.ORG

Sup Fig.Pptx

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Sup Fig.Pptx Supplementary Figure S1 A C Complete medium Complete medium 1.61,6 24 h 48 h 72 h Cells treated with siPFDN2 siControl 120 1.41,4 siPFDN2 siC siPFDN2 siC siPFDN2 siC siPFDN2 100 1.21,2 ** ** ** / siControl 11 PFDN2 15 kDa 80 0.80,8 / siControl levels 1 0.97 1 0.54 1 0.33 60 0.60,6 cells ± 0.35 ± 0,32 ± 0.06 40 0.40,4 GAPDH 37 kDa 0.20,2 % living 20 mRNA PFDN2 00 1 1 1 1 1 1 0 24 h 48 h 72 h 24 h 48 h 72 h Time after transfection Time after transfection 1.61,6 Cells treated with siPFDN5 siControl 24 h 48 h 72 h 140 1.41,4 ** siPFDN5 1.21,2 siC siPFDN5 siC siPFDN5 siC siPFDN5 120 ** * * / siControl 11 100 PFDN5 15 kDa / siControl 0.80,8 80 levels 0.60,6 1 0.51 1 0.77 1 0.45 cells 60 ± 0.17 ± 0.12 ± 0.10 0.40,4 40 0.20,2 GAPDH 37 kDa % living 20 mRNA PFDN5 00 24 h 48 h 72 h 1 1 1 1 1 1 0 Time after transfection 24 h 48 h 72 h Time after transfection B 48 h of serum starvation D 48 h of serum starvation 1,6 1.6 72 h 1,4 1.4 siControl Cells treated with siPFDN2 siC siPFDN2 120 1,2 1.2 siPFDN2 PFDN2 15 kDa 11 100 0.8 1 0.377 0,8 80 ± 0.109 0,6 0.6 37 kDa 60 0,4 0.4 GAPDH 0,2 0.2 40 mRNA PFDN2 levels / siControl 1 1 00 % living cell / siControl 20 72 h Time after transfection 0 72 h Time after transfection 1.2 1,2 siControl Cells treated with siPFDN5 72h 120 1 1 siPFDN5 siC siPFDN5 100 0.8 0,8 PFDN5 15 kDa 80 0.6 0,6 siControl 1 0.25 / ± 0.16 60 0.4 0,4 cell GAPDH 37 kDa 40 0.2 0,2 1 1 % living mRNA PFDN5 levels / siControl 20 0 0 72h 0 Time after transfection 72 h Time after transfection Supplementary Figure S2 A siPFDN2 siPFDN5 22 38 755 999 619 3056 Before serum After serum Before serum After serum stimulation stimulation stimulation stimulation B C GOs whose expression level changes in deficient cells in PFDN2 and PFDN5 after serum stimulation GO p siPFDN2 p siPFDN5 cell adhesion 2.78E-14 6.30E-09 nervous system development 7.14E-12 0 22 38 1580 animal organ morphogenesis 3.17E-10 1.09E-07 regulation of cell differentiation 1.26E-08 8.76E-07 vasculature development 2.33E-08 6.24E-07 negative regulation of developmental 4.56E-06 1.89E-05 process siPFDN2 siPFDN5 synapse organization 2.30E-05 2.87E-05 cytoskeleton organization 2.78E-05 2.32E-07 heart development 4.70E-05 1.94E-06 n = 10322 p = 7.24e-17 D 2 2 1.5 1,5 1 0.5 1 siPFDN2 0,5 0 siPFDN5 -0.5 0 FC 2 log -0,5 -1 -1.5 -1 -1,5 -2 -2 Genes Supplementary Figure S3 A FC) 2 (Log 1 . Before serum induction expression 0 0 . siControl 5 0 Differential .0 -0 siPFDN2 / .5 -1 B . 0 1 [0.206-11] .0 After serum induction (11-24] 0 .5 FC) 2 (24-45.9] 0 .0 1 Before serum induction .0 (45.9-93.5] (Log -0 expression .5 0 (93.5-1900] .5 -1 * .0 siControl0 Lenght .0 * Differential -0 [0.206-11] C .5 (kb) siPFDN2 / (11-24] -1 . 0 (24-45.9] 1 0-4 .0 After serum induction( 45.9-93.5] 5-7 0 (93.5-1900] .5 8-11 0 1 .0 FC) 12-17 -0 2 . * 18-362 5 Number -1 * .0 * of 0-4 introns 0.5 5-7 8-11 12-17 18-362 0 Induction after serum addition (Log -1 0 Log 10 (gene siControl siPFDN2 1 Number length Lower Middle of Upper introns , kb) 2 tercil tercil tercil : 3 Supplementary Figure S4 Expression level (CPM) Supplementary Figure S5 A PFDN5 E1 E2 E3 E4 E5 E6 B E2 E3 E4 WT PFDN5 GTACAGACCAAGTATGTGGAAGCCAAGGACTGTCTGAACGTGCTGAACAAGAGCAACGAGGGGAAAGAATTACTCGTCCCACTGACGAGTTCTATGTATGTCCCTGGGAAGCTGCATGAT V Q T K Y V E A K D C L N V L N K S N E G K E L L V P L T S S M Y V P G K L H D 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 PFDN5 KO GTACAGACCGAGTTATGTGGAAGCCAAGGACTGTCTGAACGTGCTGAACAAGAGCAACGAGGGGAAAGAATTACTCGTCCCACTGACGAGTTCTATGTATGTCCCTGGGAAGCTGCATGA V Q T E L C G S Q G L S E R A E Q E Q R G E R I T R P T D E F Y V C P W E A A STOP 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 C PFDN5 15 kDa GAPDH 37 kDa Supplementary Figure S6 A 14 SE MX A5 A3 12 RI AF AL 10 8 6 % affected events % affected 4 2 0 Events that occur less frequently in EventsNew events that appear in siPFDN5 cells that occur more frequently in PFDN5-deficient cells. PFDN5-deficient cells. B FASN Ratio short isoform / long isoform 33 2.52,5 22 1.51,5 11 0.50,5 00 WT PFDN5 KO PFDN5 KO + PFDN5 Supplementary Figure S7 OPA1 A 104668 bp Ex18 Ex19 Ex19 In19 11 0.8 0,8 0.60,6 siControl 0.40,4 siPFDN5 0.20,2 Relative levels of pre-mRNA Relative levels of pre-mRNA 0 0 0 10 20 30 40 50 60 70 Time post-DRB wash (min) B Intron 18 removed Ex18 Ex19 In19 0.80,8 0.60,6 0.40,4 siControl siPFDN5 0.20,2 Relative levels of pre-mRNA Relative levelsof pre-mRNA 00 0 10 20 30 40 50 60 70 Time post-DRB wash (min) Supplementary Figure S8 A Flag-PFDN5 20 kDa PFDN5 15 kDa GAPDH 37 kDa B ChIP after RNAse treatment PFDN5 in CTNNBL1 PFDN5 in CD44 18 10 **** 16 **** 9 8 14 **** 7 12 **** **** 6 10 5 8 **** 4 6 3 4 Flag/ negative control 2 Flag / negativeFlag / control 2 1 0 0 Ex1 Ex5 Ex16 Ex1 Ex6 Ex19 FLAG FLAG-PFDN5 Supplementary Figure S9 6.0 ) M P C ( (CPM) (CPM) n o i s s 5.5 e r expression p x e n RR == 0.06780.0678 a e Pp == 0.50430.5043 M Mean 5.0 -1.0 -0.5 0.0 0.50.5 1.01.0 1.5 2.02.0 PFDN5 PFDN5 (ChIP-seq (ChIP-seq signal signal)) Supplementary Figure S10 A Non-snRNP snRNP PRP19C prp46- syf1- lsm8- smx3- hsh49- cef1-13 clf1-1 prp2-1 lsm6∆ 5001 5001 5003 5001 5002 pfdn1∆ X X X pfdn2∆ X X X pfdn3∆ X pfdn4∆ X X X X X pfdn5∆ X pfdn6∆ X X X X Table. Pearson correlation coefficient ≥ 0.13 Source: https://thecellmap.org/ B Supplementary Figure S11 A B C PRPF19 PRLG1 U2AF65 50 kDa 50 kDa 50 kDa 1 0.80 1 1.34 1 1.05 ± 0.10 ± 0.28 ± 0.65 GAPDH GAPDH GAPDH 37 kDa 37 kDa 37 kDa 1 1 1 1 1 1 Supplementary Figure S12 A PRP19 in CTNNBL1 PRP19 in CD44 12 10 II 10 II * pol pol 8 8 siControl 6 ** 6 siPFDN2 4 4 2 2 PRP19 / Total RNA RNA Total PRP19 / PRP19 / Total RNA RNA Total PRP19 / 0 0 Ex1 Ex5 Ex16 Ex1C1 V5Ex9 C19Ex19 B UA2F65 in CTNNBL1 UA2F65 in CD44 30 25 II II 25 ** pol pol 20 * 20 ** 15 siControl 15 10 siPFDN2 10 5 5 UA2F65/ Total RNA RNA Total UA2F65/ UA2F65 / Total RNA RNA Total UA2F65 / 0 0 Ex1 Ex5 Ex16 Ex1C1 Ex9V5 Ex19C19 Supplementary Figure S13 A Total RNA pol II in CTNNBL1 Total RNA pol II in CD44 0,006 0,006 * * 0,004 0,004 siControl siControl 0,002 siPFDN2 0,002 siPFDN2 RNA pol II / Input RNA RNA pol II/ Input RNA 0,000 0 Ex1 Ex5 Ex16 Ex1 Ex9 Ex19 B Total RNA pol II in CTNNBL1 Total RNA pol II in CD44 0,006 0,006 0,004 WT 0,004 WT PFDN5 KO PFDN5 KO 0,002 0,002 RNA pol II / Input RNA RNA pol II / Input RNA 0 0 Ex1 Ex5 Ex16 Ex1 Ex9 Ex19 Supplementary Figure S14 Nascent pre-mRNA P PRP19C P P P U2AF65 P CTD P P P P CDK9 Prefoldin RNA pol II Transcritpion-dependent spliceosome pre-catalytic activation P P P PRP19C P U2AF65 P CTD P P P P CDK9 Prefoldin RNA pol II Co-transcriptional splicing P P P PRP19C P U2AF65 P CTD P P P P CDK9 Prefoldin RNA pol II SupplementaryFigure S15 A PFDN5 (ChIP-seq signal) -0.5 0.0 0.5 1.0 1.5 2.0 PFDN5 in promoters in PFDN5 PFDN5in M y c -d e p M y *** c promoters - in d e p B Supplementary figure S1. Efficiency of the siRNA-mediated depletion of PFDN2 and PFDN5. A) Left panels: PFDN2 and PFDN5 mRNA levels in HCT116 cells, 24, 48 and 72 hours after being transfected with siPFDN2 or siPFDN5, respectively, or with a siRNA control (siControl).
Load more

Recommended publications
  • Novel Human Embryonic Stem Cell Regulators Identified by Conserved and Distinct Cpg Island Methylation State
    RESEARCH ARTICLE Novel Human Embryonic Stem Cell Regulators Identified by Conserved and Distinct CpG Island Methylation State Steve Pells1,2*, Eirini Koutsouraki1, Sofia Morfopoulou1, Sara Valencia-Cadavid1, Simon R. Tomlinson1, Ravi Kalathur3, Matthias E. Futschik3, Paul A. De Sousa1,2* 1 MRC Centre for Regenerative Medicine, School of Clinical Studies, University of Edinburgh, Edinburgh, EH16 4SB, United Kingdom, 2 Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, United Kingdom, 3 Centre for Molecular and Structural Biomedicine, University of Algarve, 8005–139, Faro, Portugal * [email protected] (PDS); [email protected] (SP) Abstract Human embryonic stem cells (hESCs) undergo epigenetic changes in vitro which may com- OPEN ACCESS promise function, so an epigenetic pluripotency “signature” would be invaluable for line vali- Citation: Pells S, Koutsouraki E, Morfopoulou S, dation. We assessed Cytosine-phosphate-Guanine Island (CGI) methylation in hESCs by Valencia-Cadavid S, Tomlinson SR, Kalathur R, et al. genomic DNA hybridisation to a CGI array, and saw substantial variation in CGI methylation (2015) Novel Human Embryonic Stem Cell Regulators Identified by Conserved and Distinct CpG between lines. Comparison of hESC CGI methylation profiles to corresponding somatic Island Methylation State. PLoS ONE 10(7): tissue data and hESC mRNA expression profiles identified a conserved hESC-specific e0131102. doi:10.1371/journal.pone.0131102 methylation pattern associated with expressed genes. Transcriptional repressors and acti- Editor: Jason Glenn Knott, Michigan State University, vators were over-represented amongst genes whose associated CGIs were methylated or UNITED STATES unmethylated specifically in hESCs, respectively. Knockdown of candidate transcriptional Received: March 10, 2015 regulators (HMGA1, GLIS2, PFDN5) induced differentiation in hESCs, whereas ectopic Accepted: May 27, 2015 expression in fibroblasts modulated iPSC colony formation.
    [Show full text]
  • A Molecular and Genetic Analysis of Otosclerosis
    A molecular and genetic analysis of otosclerosis Joanna Lauren Ziff Submitted for the degree of PhD University College London January 2014 1 Declaration I, Joanna Ziff, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Where work has been conducted by other members of our laboratory, this has been indicated by an appropriate reference. 2 Abstract Otosclerosis is a common form of conductive hearing loss. It is characterised by abnormal bone remodelling within the otic capsule, leading to formation of sclerotic lesions of the temporal bone. Encroachment of these lesions on to the footplate of the stapes in the middle ear leads to stapes fixation and subsequent conductive hearing loss. The hereditary nature of otosclerosis has long been recognised due to its recurrence within families, but its genetic aetiology is yet to be characterised. Although many familial linkage studies and candidate gene association studies to investigate the genetic nature of otosclerosis have been performed in recent years, progress in identifying disease causing genes has been slow. This is largely due to the highly heterogeneous nature of this condition. The research presented in this thesis examines the molecular and genetic basis of otosclerosis using two next generation sequencing technologies; RNA-sequencing and Whole Exome Sequencing. RNA–sequencing has provided human stapes transcriptomes for healthy and diseased stapes, and in combination with pathway analysis has helped identify genes and molecular processes dysregulated in otosclerotic tissue. Whole Exome Sequencing has been employed to investigate rare variants that segregate with otosclerosis in affected families, and has been followed by a variant filtering strategy, which has prioritised genes found to be dysregulated during RNA-sequencing.
    [Show full text]
  • Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
    www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.
    [Show full text]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • Human Prefoldin Modulates Co-Transcriptional Pre-Mrna Splicing
    bioRxiv preprint doi: https://doi.org/10.1101/2020.06.14.150466; this version posted July 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. BIOLOGICAL SCIENCES: Biochemistry Human prefoldin modulates co-transcriptional pre-mRNA splicing Payán-Bravo L 1,2, Peñate X 1,2 *, Cases I 3, Pareja-Sánchez Y 1, Fontalva S 1,2, Odriozola Y 1,2, Lara E 1, Jimeno-González S 2,5, Suñé C 4, Reyes JC 5, Chávez S 1,2. 1 Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville, Spain. 2 Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain. 3 Centro Andaluz de Biología del Desarrollo, CSIC-Universidad Pablo de Olavide, Seville, Spain. 4 Department of Molecular Biology, Institute of Parasitology and Biomedicine "López Neyra" IPBLN-CSIC, PTS, Granada, Spain. 5 Andalusian Center of Molecular Biology and Regenerative Medicine-CABIMER, Junta de Andalucia-University of Pablo de Olavide-University of Seville-CSIC, Seville, Spain. Correspondence: Sebastián Chávez, IBiS, campus HUVR, Avda. Manuel Siurot s/n, Sevilla, 41013, Spain. Phone: +34-955923127: e-mail: [email protected]. * Co- corresponding; [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.14.150466; this version posted July 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Prefoldin is a heterohexameric complex conserved from archaea to humans that plays a cochaperone role during the cotranslational folding of actin and tubulin monomers.
    [Show full text]
  • Research Article Sex Difference of Ribosome in Stroke-Induced Peripheral Immunosuppression by Integrated Bioinformatics Analysis
    Hindawi BioMed Research International Volume 2020, Article ID 3650935, 15 pages https://doi.org/10.1155/2020/3650935 Research Article Sex Difference of Ribosome in Stroke-Induced Peripheral Immunosuppression by Integrated Bioinformatics Analysis Jian-Qin Xie ,1,2,3 Ya-Peng Lu ,1,3 Hong-Li Sun ,1,3 Li-Na Gao ,2,3 Pei-Pei Song ,2,3 Zhi-Jun Feng ,3 and Chong-Ge You 2,3 1Department of Anesthesiology, Lanzhou University Second Hospital, Lanzhou, Gansu 730030, China 2Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, Gansu 730030, China 3The Second Clinical Medical College of Lanzhou University, Lanzhou, Gansu 730030, China Correspondence should be addressed to Chong-Ge You; [email protected] Received 13 April 2020; Revised 8 October 2020; Accepted 18 November 2020; Published 3 December 2020 Academic Editor: Rudolf K. Braun Copyright © 2020 Jian-Qin Xie 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. Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex- specific outcome, and revealing potential treatment targets. Gene expression dataset GSE37587, including 68 peripheral whole blood samples which were collected within 24 hours from known onset of symptom and again at 24-48 hours after onset (20 women and 14 men), was downloaded from the Gene Expression Omnibus (GEO) datasets.
    [Show full text]
  • Multipronged Approach to Study Glaucoma-Associated Phenotypes
    University of Tennessee Health Science Center UTHSC Digital Commons Theses and Dissertations (ETD) College of Graduate Health Sciences 8-2016 Multipronged Approach to Study Glaucoma- Associated Phenotypes Sumana Rameshbabu Chintalapudi University of Tennessee Health Science Center Follow this and additional works at: https://dc.uthsc.edu/dissertations Part of the Neurosciences Commons Recommended Citation Chintalapudi, Sumana Rameshbabu (http://orcid.org/0000-0003-1079-0950), "Multipronged Approach to Study Glaucoma- Associated Phenotypes" (2016). Theses and Dissertations (ETD). Paper 404. http://dx.doi.org/10.21007/etd.cghs.2016.0410. This Dissertation is brought to you for free and open access by the College of Graduate Health Sciences at UTHSC Digital Commons. It has been accepted for inclusion in Theses and Dissertations (ETD) by an authorized administrator of UTHSC Digital Commons. For more information, please contact [email protected]. Multipronged Approach to Study Glaucoma-Associated Phenotypes Document Type Dissertation Degree Name Doctor of Philosophy (PhD) Program Integrated Program in Biomedical Sciences Track Neuroscience Research Advisor Monica M. Jablonski, Ph.D. Committee Edward Chaum, M.D., Ph.D. Dianna A. Johnson, Ph.D. Rajendra Raghow, Ph.D. Vanessa Morales-Tirado, Ph.D. Robert W. Williams, Ph.D. ORCID http://orcid.org/0000-0003-1079-0950 DOI 10.21007/etd.cghs.2016.0410 Comments One year embargo expires August 2017. This dissertation is available at UTHSC Digital Commons: https://dc.uthsc.edu/dissertations/404 Multipronged Approach to Study Glaucoma-Associated Phenotypes A Dissertation Presented for The Graduate Studies Council The University of Tennessee Health Science Center In Partial Fulfillment Of the Requirements for the Degree Doctor of Philosophy From The University of Tennessee By Sumana Rameshbabu Chintalapudi August 2016 .
    [Show full text]
  • The Role and Robustness of the Gini Coefficient As an Unbiased Tool For
    www.nature.com/scientificreports OPEN The role and robustness of the Gini coefcient as an unbiased tool for the selection of Gini genes for normalising expression profling data Marina Wright Muelas 1*, Farah Mughal1, Steve O’Hagan2,3, Philip J. Day3,4* & Douglas B. Kell 1,5* We recently introduced the Gini coefcient (GC) for assessing the expression variation of a particular gene in a dataset, as a means of selecting improved reference genes over the cohort (‘housekeeping genes’) typically used for normalisation in expression profling studies. Those genes (transcripts) that we determined to be useable as reference genes difered greatly from previous suggestions based on hypothesis-driven approaches. A limitation of this initial study is that a single (albeit large) dataset was employed for both tissues and cell lines. We here extend this analysis to encompass seven other large datasets. Although their absolute values difer a little, the Gini values and median expression levels of the various genes are well correlated with each other between the various cell line datasets, implying that our original choice of the more ubiquitously expressed low-Gini-coefcient genes was indeed sound. In tissues, the Gini values and median expression levels of genes showed a greater variation, with the GC of genes changing with the number and types of tissues in the data sets. In all data sets, regardless of whether this was derived from tissues or cell lines, we also show that the GC is a robust measure of gene expression stability. Using the GC as a measure of expression stability we illustrate its utility to fnd tissue- and cell line-optimised housekeeping genes without any prior bias, that again include only a small number of previously reported housekeeping genes.
    [Show full text]
  • PFDN5 (NM 145897) Human Tagged ORF Clone Product Data
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG223996 PFDN5 (NM_145897) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: PFDN5 (NM_145897) Human Tagged ORF Clone Tag: TurboGFP Symbol: PFDN5 Synonyms: MM-1; MM1; PFD5 Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RG223996 representing NM_145897 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGGCGCAGTCTATTAACATCACGGAGCTGAATCTGCCGCAGCTAGAAATGCTCAAGAACCAGCTGGACC AGATGTATGTCCCTGGGAAGCTGCATGATGTGGAACACGTGCTCATCGATGTGGGAACTGGGTACTATGT AGAGAAGACAGCTGAGGATGCCAAGGACTTCTTCAAGAGGAAGATAGATTTTCTAACCAAGCAGATGGAG AAAATCCAACCAGCTCTTCAGGAGAAGCACGCCATGAAACAGGCCGTCATGGAAATGATGAGTCAGAAGA TTCAGCAGCTCACAGCCCTGGGGGCAGCTCAGGCTACTGCTAAGGCC ACGCGTACGCGGCCGCTCGAG - GFP Tag - GTTTAA Protein Sequence: >RG223996 representing NM_145897 Red=Cloning site Green=Tags(s) MAQSINITELNLPQLEMLKNQLDQMYVPGKLHDVEHVLIDVGTGYYVEKTAEDAKDFFKRKIDFLTKQME KIQPALQEKHAMKQAVMEMMSQKIQQLTALGAAQATAKA TRTRPLE - GFP Tag - V Restriction Sites: SgfI-MluI This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 3 PFDN5 (NM_145897) Human Tagged ORF Clone – RG223996
    [Show full text]
  • Human Prefoldin Modulates Co-Transcriptional Pre-Mrna Splicing
    bioRxiv preprint doi: https://doi.org/10.1101/2020.06.14.150466; this version posted April 6, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Human prefoldin modulates co-transcriptional pre-mRNA splicing Laura Payán-Bravo1,2, Sara Fontalva1,2, Xenia Peñate1,2*, Ildefonso Cases3, José Antonio Guerrero-Martínez5, Yerma Pareja-Sánchez1, Yosu Odriozola-Gil1, Esther Lara1, Silvia Jimeno-González2,5, Carles Suñé4, Mari Cruz Muñoz-Centeno1,2, José C. Reyes5, Sebastián Chávez1,2* 1 Instituto de Biomedicina de Sevilla, Universidad de Sevilla-CSIC-Hospital Universitario V. del Rocío, Seville, Spain. 2 Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Seville, Spain. 3 Centro Andaluz de Biología del Desarrollo, CSIC-Universidad Pablo de Olavide, Seville, Spain. 4 Department of Molecular Biology, Institute of Parasitology and Biomedicine "López Neyra" IPBLN-CSIC, PTS, Granada, Spain. 5 Andalusian Center of Molecular Biology and Regenerative Medicine-CABIMER, Junta de Andalucia-University of Pablo de Olavide-University of Seville-CSIC, Seville, Spain. * To whom correspondence should be addressed. Tel: +34 955923127; Fax: +34 955923101; Email: [email protected]. Correspondence may also be addressed to Xenia Peñate. Tel: +34 955923129; Fax: +34 955923101; Email: [email protected]. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.14.150466; this version posted April 6, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. ABSTRACT Prefoldin is a heterohexameric complex conserved from archaea to humans that plays a cochaperone role during the co-translational folding of actin and tubulin monomers.
    [Show full text]
  • Chromosome 12Q13.13Q13.13 Microduplication and Microdeletion: a Case Report and Literature Review Jie Hu1,2*, Zhishuo Ou1, Elena Infante3, Sally J
    Hu et al. Molecular Cytogenetics (2017) 10:24 DOI 10.1186/s13039-017-0326-4 CASE REPORT Open Access Chromosome 12q13.13q13.13 microduplication and microdeletion: a case report and literature review Jie Hu1,2*, Zhishuo Ou1, Elena Infante3, Sally J. Kochmar1, Suneeta Madan-Khetarpal3, Lori Hoffner4, Shafagh Parsazad1 and Urvashi Surti1,2,4 Abstract Background: Duplications or deletions in the 12q13.13 region are rare. Only scattered cases with duplications and/ or deletions in this region have been reported in the literature or in online databases. Owing to the limited number of patients with genomic alteration within this region and lack of systematic analysis of these patients, the common clinical manifestation of these patients has remained elusive. Case presentation: Here we report an 802 kb duplication in the 12q13.13q13.13 region in a 14 year-old male who presented with dysmorphic features, developmental delay (DD), mild intellectual disability (ID) and mild deformity of digits. Comparing the phenotype of our patient with those of reported patients, we find that patients with the 12q13. 13 duplication or the deletion share similar phenotypes, including dysmorphic facies, abnormal nails, intellectual disability, and deformity of digits or limbs. However, patients with the deletion appear to have more severe deformity of digits or limbs. Conclusions: Deletion and duplication of the 12q13.13 region may represent novel contiguous gene alteration syndromes. All seven reported 12q13.13 deletions and three of four duplications are de novo and vary in size. Therefore, these genomic alterations are not due to non-allelic homologous recombination. Keywords: 12q13.13 Microdeletion/Microduplication, Array CGH, HOXC, SPT7, SP1 Background variation) databases.
    [Show full text]
  • Multiplex Gene Expression Profiling of 16 Target Genes in Neoplastic And
    International Journal of Molecular Sciences Article Multiplex Gene Expression Profiling of 16 Target Genes in Neoplastic and Non-Neoplastic Canine Mammary Tissues Using Branched-DNA Assay Florenza Lüder Ripoli 1,2, Susanne Conradine Hammer 1,2, Annika Mohr 1,2, Saskia Willenbrock 1, Marion Hewicker-Trautwein 3, Bertram Brenig 4, Hugo Murua Escobar 2 and Ingo Nolte 1,* 1 Small Animal Clinic, University of Veterinary Medicine Hannover, Hannover D-30559, Germany; fl[email protected] (F.L.R.); [email protected] (S.C.H.); [email protected] (A.M.); [email protected] (S.W.) 2 Hematology Oncology and Palliative Medicine, Clinic III, University of Rostock, Rostock D-18057, Germany; [email protected] 3 Department of Pathology, University of Veterinary Medicine Hannover, Hannover D-30559, Germany; [email protected] 4 Institute of Veterinary Medicine, Georg-August-University Göttingen, Göttingen D-37077, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-511-953-6400 Academic Editor: Dario Marchetti Received: 8 August 2016; Accepted: 9 September 2016; Published: 21 September 2016 Abstract: Mammary gland tumors are one of the most common neoplasms in female dogs, and certain breeds are prone to develop the disease. The use of biomarkers in canines is still restricted to research purposes. Therefore, the necessity to analyze gene profiles in different mammary entities in large sample sets is evident in order to evaluate the strength of potential markers serving as future prognostic factors. The aim of the present study was to analyze the gene expression of 16 target genes (BRCA1, BRCA2, FOXO3, GATA4, HER2, HMGA1, HMGA2, HMGB1, MAPK1, MAPK3, MCL1, MYC, PFDN5, PIK3CA, PTEN, and TP53) known to be involved in human and canine mammary neoplasm development.
    [Show full text]