Synergistic Genetic Interactions Between Pkhd1 and Pkd1 Result in an ARPKD-Like Phenotype in Murine Models
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Educational Paper Ciliopathies
Eur J Pediatr (2012) 171:1285–1300 DOI 10.1007/s00431-011-1553-z REVIEW Educational paper Ciliopathies Carsten Bergmann Received: 11 June 2011 /Accepted: 3 August 2011 /Published online: 7 September 2011 # The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Cilia are antenna-like organelles found on the (NPHP) . Ivemark syndrome . Meckel syndrome (MKS) . surface of most cells. They transduce molecular signals Joubert syndrome (JBTS) . Bardet–Biedl syndrome (BBS) . and facilitate interactions between cells and their Alstrom syndrome . Short-rib polydactyly syndromes . environment. Ciliary dysfunction has been shown to Jeune syndrome (ATD) . Ellis-van Crefeld syndrome (EVC) . underlie a broad range of overlapping, clinically and Sensenbrenner syndrome . Primary ciliary dyskinesia genetically heterogeneous phenotypes, collectively (Kartagener syndrome) . von Hippel-Lindau (VHL) . termed ciliopathies. Literally, all organs can be affected. Tuberous sclerosis (TSC) . Oligogenic inheritance . Modifier. Frequent cilia-related manifestations are (poly)cystic Mutational load kidney disease, retinal degeneration, situs inversus, cardiac defects, polydactyly, other skeletal abnormalities, and defects of the central and peripheral nervous Introduction system, occurring either isolated or as part of syn- dromes. Characterization of ciliopathies and the decisive Defective cellular organelles such as mitochondria, perox- role of primary cilia in signal transduction and cell isomes, and lysosomes are well-known -
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ANALYTICAL SCIENCES NOVEMBER 2020, VOL. 36 1 2020 © The Japan Society for Analytical Chemistry Supporting Information Fig. S1 Detailed MS/MS data of myoglobin. 17 2 ANALYTICAL SCIENCES NOVEMBER 2020, VOL. 36 Table S1 : The protein names (antigens) identified by pH 2.0 solution in the eluted-fraction. These proteins were identified one or more out of six analyses. Accession Description P08908 5-hydroxytryptamine receptor 1A OS=Homo sapiens GN=HTR1A PE=1 SV=3 - [5HT1A_HUMAN] Q9NRR6 72 kDa inositol polyphosphate 5-phosphatase OS=Homo sapiens GN=INPP5E PE=1 SV=2 - [INP5E_HUMAN] P82987 ADAMTS-like protein 3 OS=Homo sapiens GN=ADAMTSL3 PE=2 SV=4 - [ATL3_HUMAN] Q9Y6K8 Adenylate kinase isoenzyme 5 OS=Homo sapiens GN=AK5 PE=1 SV=2 - [KAD5_HUMAN] P02763 Alpha-1-acid glycoprotein 1 OS=Homo sapiens GN=ORM1 PE=1 SV=1 - [A1AG1_HUMAN] P19652 Alpha-1-acid glycoprotein 2 OS=Homo sapiens GN=ORM2 PE=1 SV=2 - [A1AG2_HUMAN] P01011 Alpha-1-antichymotrypsin OS=Homo sapiens GN=SERPINA3 PE=1 SV=2 - [AACT_HUMAN] P01009 Alpha-1-antitrypsin OS=Homo sapiens GN=SERPINA1 PE=1 SV=3 - [A1AT_HUMAN] P04217 Alpha-1B-glycoprotein OS=Homo sapiens GN=A1BG PE=1 SV=4 - [A1BG_HUMAN] P08697 Alpha-2-antiplasmin OS=Homo sapiens GN=SERPINF2 PE=1 SV=3 - [A2AP_HUMAN] P02765 Alpha-2-HS-glycoprotein OS=Homo sapiens GN=AHSG PE=1 SV=1 - [FETUA_HUMAN] P01023 Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 - [A2MG_HUMAN] P01019 Angiotensinogen OS=Homo sapiens GN=AGT PE=1 SV=1 - [ANGT_HUMAN] Q9NQ90 Anoctamin-2 OS=Homo sapiens GN=ANO2 PE=1 SV=2 - [ANO2_HUMAN] P01008 Antithrombin-III -
Title a New Centrosomal Protein Regulates Neurogenesis By
Title A new centrosomal protein regulates neurogenesis by microtubule organization Authors: Germán Camargo Ortega1-3†, Sven Falk1,2†, Pia A. Johansson1,2†, Elise Peyre4, Sanjeeb Kumar Sahu5, Loïc Broic4, Camino De Juan Romero6, Kalina Draganova1,2, Stanislav Vinopal7, Kaviya Chinnappa1‡, Anna Gavranovic1, Tugay Karakaya1, Juliane Merl-Pham8, Arie Geerlof9, Regina Feederle10,11, Wei Shao12,13, Song-Hai Shi12,13, Stefanie M. Hauck8, Frank Bradke7, Victor Borrell6, Vijay K. Tiwari§, Wieland B. Huttner14, Michaela Wilsch- Bräuninger14, Laurent Nguyen4 and Magdalena Götz1,2,11* Affiliations: 1. Institute of Stem Cell Research, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 2. Physiological Genomics, Biomedical Center, Ludwig-Maximilian University Munich, Germany. 3. Graduate School of Systemic Neurosciences, Biocenter, Ludwig-Maximilian University Munich, Germany. 4. GIGA-Neurosciences, Molecular regulation of neurogenesis, University of Liège, Belgium 5. Institute of Molecular Biology (IMB), Mainz, Germany. 6. Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d’Alacant, Spain. 7. Laboratory for Axon Growth and Regeneration, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 8. Research Unit Protein Science, Helmholtz Centre Munich, German Research Center for Environmental Health, Munich, Germany. 9. Protein Expression and Purification Facility, Institute of Structural Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 10. Institute for Diabetes and Obesity, Monoclonal Antibody Core Facility, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 11. SYNERGY, Excellence Cluster of Systems Neurology, Biomedical Center, Ludwig- Maximilian University Munich, Germany. 12. Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, USA 13. -
PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41
American Society of Human Genetics 62nd Annual Meeting November 6–10, 2012 San Francisco, California PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41. Genes Underlying Neurological Disease Room 134 #196–#204 2. 4:30–6:30pm: Plenary Abstract 42. Cancer Genetics III: Common Presentations Hall D #1–#6 Variants Ballroom 104 #205–#213 43. Genetics of Craniofacial and Wednesday, November 7 Musculoskeletal Disorders Room 124 #214–#222 10:30am–12:45 pm: Concurrent Platform Session A (11–19): 44. Tools for Phenotype Analysis Room 132 #223–#231 11. Genetics of Autism Spectrum 45. Therapy of Genetic Disorders Room 130 #232–#240 Disorders Hall D #7–#15 46. Pharmacogenetics: From Discovery 12. New Methods for Big Data Ballroom 103 #16–#24 to Implementation Room 123 #241–#249 13. Cancer Genetics I: Rare Variants Room 135 #25–#33 14. Quantitation and Measurement of Friday, November 9 Regulatory Oversight by the Cell Room 134 #34–#42 8:00am–10:15am: Concurrent Platform Session D (47–55): 15. New Loci for Obesity, Diabetes, and 47. Structural and Regulatory Genomic Related Traits Ballroom 104 #43–#51 Variation Hall D #250–#258 16. Neuromuscular Disease and 48. Neuropsychiatric Disorders Ballroom 103 #259–#267 Deafness Room 124 #52–#60 49. Common Variants, Rare Variants, 17. Chromosomes and Disease Room 132 #61–#69 and Everything in-Between Room 135 #268–#276 18. Prenatal and Perinatal Genetics Room 130 #70–#78 50. Population Genetics Genome-Wide Room 134 #277–#285 19. Vascular and Congenital Heart 51. Endless Forms Most Beautiful: Disease Room 123 #79–#87 Variant Discovery in Genomic Data Ballroom 104 #286–#294 52. -
University of Oklahoma
UNIVERSITY OF OKLAHOMA GRADUATE COLLEGE MACRONUTRIENTS SHAPE MICROBIAL COMMUNITIES, GENE EXPRESSION AND PROTEIN EVOLUTION A DISSERTATION SUBMITTED TO THE GRADUATE FACULTY in partial fulfillment of the requirements for the Degree of DOCTOR OF PHILOSOPHY By JOSHUA THOMAS COOPER Norman, Oklahoma 2017 MACRONUTRIENTS SHAPE MICROBIAL COMMUNITIES, GENE EXPRESSION AND PROTEIN EVOLUTION A DISSERTATION APPROVED FOR THE DEPARTMENT OF MICROBIOLOGY AND PLANT BIOLOGY BY ______________________________ Dr. Boris Wawrik, Chair ______________________________ Dr. J. Phil Gibson ______________________________ Dr. Anne K. Dunn ______________________________ Dr. John Paul Masly ______________________________ Dr. K. David Hambright ii © Copyright by JOSHUA THOMAS COOPER 2017 All Rights Reserved. iii Acknowledgments I would like to thank my two advisors Dr. Boris Wawrik and Dr. J. Phil Gibson for helping me become a better scientist and better educator. I would also like to thank my committee members Dr. Anne K. Dunn, Dr. K. David Hambright, and Dr. J.P. Masly for providing valuable inputs that lead me to carefully consider my research questions. I would also like to thank Dr. J.P. Masly for the opportunity to coauthor a book chapter on the speciation of diatoms. It is still such a privilege that you believed in me and my crazy diatom ideas to form a concise chapter in addition to learn your style of writing has been a benefit to my professional development. I’m also thankful for my first undergraduate research mentor, Dr. Miriam Steinitz-Kannan, now retired from Northern Kentucky University, who was the first to show the amazing wonders of pond scum. Who knew that studying diatoms and algae as an undergraduate would lead me all the way to a Ph.D. -
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. -
Dramatic Nucleolar Dispersion in the Salivary Gland of Schwenkfeldina Sp
www.nature.com/scientificreports OPEN Dramatic nucleolar dispersion in the salivary gland of Schwenkfeldina sp. (Diptera: Sciaridae) José Mariano Amabis & Eduardo Gorab * Micronucleoli are among the structures composing the peculiar scenario of the nucleolus in salivary gland nuclei of dipterans representative of Sciaridae. Micronucleolar bodies contain ribosomal DNA and RNA, are transcriptionally active and may appear free in the nucleoplasm or associated with specifc chromosome regions in salivary gland nuclei. This report deals with an extreme case of nucleolar fragmentation/dispersion detected in the salivary gland of Schwenkfeldina sp. Such a phenomenon in this species was found to be restricted to cell types undergoing polyteny and seems to be diferentially controlled according to the cell type. Furthermore, transcriptional activity was detected in virtually all the micronucleolar bodies generated in the salivary gland. The relative proportion of the rDNA in polytene and diploid tissues showed that rDNA under-replication did not occur in polytene nuclei suggesting that the nucleolar and concomitant rDNA dispersion in Schwenkfeldina sp. may refect a previously hypothesised process in order to counterbalance the rDNA loss due to the under-replication. The chromosomal distribution of epigenetic markers for the heterochromatin agreed with early cytological observations in this species suggesting that heterochromatin is spread throughout the chromosome length of Schwenkfeldina sp. A comparison made with results from another sciarid species argues for a role played by the heterochromatin in the establishment of the rDNA topology in polytene nuclei of Sciaridae. Transcriptional activity of ribosomal RNA (rRNA) genes in specifc chromosome regions is the primary event for the local assembly of the nucleolus, the starting site of ribosome biogenesis. -
Supplementary Table S1. Prioritization of Candidate FPC Susceptibility Genes by Private Heterozygous Ptvs
Supplementary Table S1. Prioritization of candidate FPC susceptibility genes by private heterozygous PTVs Number of private Number of private Number FPC patient heterozygous PTVs in heterozygous PTVs in tumors with somatic FPC susceptibility Hereditary cancer Hereditary Gene FPC kindred BCCS samples mutation DNA repair gene Cancer driver gene gene gene pancreatitis gene ATM 19 1 - Yes Yes Yes Yes - SSPO 12 8 1 - - - - - DNAH14 10 3 - - - - - - CD36 9 3 - - - - - - TET2 9 1 - - Yes - - - MUC16 8 14 - - - - - - DNHD1 7 4 1 - - - - - DNMT3A 7 1 - - Yes - - - PKHD1L1 7 9 - - - - - - DNAH3 6 5 - - - - - - MYH7B 6 1 - - - - - - PKD1L2 6 6 - - - - - - POLN 6 2 - Yes - - - - POLQ 6 7 - Yes - - - - RP1L1 6 6 - - - - - - TTN 6 5 4 - - - - - WDR87 6 7 - - - - - - ABCA13 5 3 1 - - - - - ASXL1 5 1 - - Yes - - - BBS10 5 0 - - - - - - BRCA2 5 6 1 Yes Yes Yes Yes - CENPJ 5 1 - - - - - - CEP290 5 5 - - - - - - CYP3A5 5 2 - - - - - - DNAH12 5 6 - - - - - - DNAH6 5 1 1 - - - - - EPPK1 5 4 - - - - - - ESYT3 5 1 - - - - - - FRAS1 5 4 - - - - - - HGC6.3 5 0 - - - - - - IGFN1 5 5 - - - - - - KCP 5 4 - - - - - - LRRC43 5 0 - - - - - - MCTP2 5 1 - - - - - - MPO 5 1 - - - - - - MUC4 5 5 - - - - - - OBSCN 5 8 2 - - - - - PALB2 5 0 - Yes - Yes Yes - SLCO1B3 5 2 - - - - - - SYT15 5 3 - - - - - - XIRP2 5 3 1 - - - - - ZNF266 5 2 - - - - - - ZNF530 5 1 - - - - - - ACACB 4 1 1 - - - - - ALS2CL 4 2 - - - - - - AMER3 4 0 2 - - - - - ANKRD35 4 4 - - - - - - ATP10B 4 1 - - - - - - ATP8B3 4 6 - - - - - - C10orf95 4 0 - - - - - - C2orf88 4 0 - - - - - - C5orf42 4 2 - - - - -
Ciliopathies Gene Panel
Ciliopathies Gene Panel Contact details Introduction Regional Genetics Service The ciliopathies are a heterogeneous group of conditions with considerable phenotypic overlap. Levels 4-6, Barclay House These inherited diseases are caused by defects in cilia; hair-like projections present on most 37 Queen Square cells, with roles in key human developmental processes via their motility and signalling functions. Ciliopathies are often lethal and multiple organ systems are affected. Ciliopathies are London, WC1N 3BH united in being genetically heterogeneous conditions and the different subtypes can share T +44 (0) 20 7762 6888 many clinical features, predominantly cystic kidney disease, but also retinal, respiratory, F +44 (0) 20 7813 8578 skeletal, hepatic and neurological defects in addition to metabolic defects, laterality defects and polydactyly. Their clinical variability can make ciliopathies hard to recognise, reflecting the ubiquity of cilia. Gene panels currently offer the best solution to tackling analysis of genetically Samples required heterogeneous conditions such as the ciliopathies. Ciliopathies affect approximately 1:2,000 5ml venous blood in plastic EDTA births. bottles (>1ml from neonates) Ciliopathies are generally inherited in an autosomal recessive manner, with some autosomal Prenatal testing must be arranged dominant and X-linked exceptions. in advance, through a Clinical Genetics department if possible. Referrals Amniotic fluid or CV samples Patients presenting with a ciliopathy; due to the phenotypic variability this could be a diverse set should be sent to Cytogenetics for of features. For guidance contact the laboratory or Dr Hannah Mitchison dissecting and culturing, with ([email protected]) / Prof Phil Beales ([email protected]) instructions to forward the sample to the Regional Molecular Genetics Referrals will be accepted from clinical geneticists and consultants in nephrology, metabolic, laboratory for analysis respiratory and retinal diseases. -
Evaluation of Variability in Human Kidney Organoids
ARTICLES https://doi.org/10.1038/s41592-018-0253-2 Evaluation of variability in human kidney organoids Belinda Phipson 1, Pei X. Er1, Alexander N. Combes1,2, Thomas A. Forbes1,3,4, Sara E. Howden1,2, Luke Zappia1,5, Hsan-Jan Yen1, Kynan T. Lawlor1, Lorna J. Hale1,4, Jane Sun6, Ernst Wolvetang6, Minoru Takasato1,7, Alicia Oshlack1,5 and Melissa H. Little 1,2,4* The utility of human pluripotent stem cell–derived kidney organoids relies implicitly on the robustness and transferability of the protocol. Here we analyze the sources of transcriptional variation in a specific kidney organoid protocol. Although individ- ual organoids within a differentiation batch showed strong transcriptional correlation, we noted significant variation between experimental batches, particularly in genes associated with temporal maturation. Single-cell profiling revealed shifts in neph- ron patterning and proportions of component cells. Distinct induced pluripotent stem cell clones showed congruent transcrip- tional programs, with interexperimental and interclonal variation also strongly associated with nephron patterning. Epithelial cells isolated from organoids aligned with total organoids at the same day of differentiation, again implicating relative matura- tion as a confounder. This understanding of experimental variation facilitated an optimized analysis of organoid-based disease modeling, thereby increasing the utility of kidney organoids for personalized medicine and functional genomics. he ability to derive induced pluripotent stem cells (iPSCs) In this study, we provide a comprehensive transcriptional from the somatic cells of patients1, together with directed dif- and morphological evaluation of our kidney organoid protocol. Tferentiation protocols, provides a capacity to model the cell Applying RNA sequencing (RNA-seq) to 57 whole organoids and types affected by disease. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
De Novo, Systemic, Deleterious Amino Acid Substitutions Are Common in Large Cytoskeleton‑Related Protein Coding Regions
BIOMEDICAL REPORTS 6: 211-216, 2017 De novo, systemic, deleterious amino acid substitutions are common in large cytoskeleton‑related protein coding regions REBECCA J. STOLL1, GRACE R. THOMPSON1, MOHAMMAD D. SAMY1 and GEORGE BLANCK1,2 1Department of Molecular Medicine, Morsani College of Medicine, University of South Florida; 2Immunology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA Received June 13, 2016; Accepted October 31, 2016 DOI: 10.3892/br.2016.826 Abstract. Human mutagenesis is largely random, thus large Introduction coding regions, simply on the basis of probability, represent relatively large mutagenesis targets. Thus, we considered Genetic damage is largely random and therefore tends to the possibility that large cytoskeletal-protein related coding affect the larger, functional regions of the human genome regions (CPCRs), including extra-cellular matrix (ECM) more frequently than the smaller regions (1). For example, coding regions, would have systemic nucleotide variants that a systematic study has revealed that cancer fusion genes, on are not present in common SNP databases. Presumably, such average, are statistically, significantly larger than other human variants arose recently in development or in recent, preceding genes (2,3). The large introns of potential cancer fusion genes generations. Using matched breast cancer and blood-derived presumably allow for many different productive recombina- normal datasets from the cancer genome atlas, CPCR single tion opportunities, i.e., many recombinations that would allow nucleotide variants (SNVs) not present in the All SNPs(142) for exon juxtaposition and the generation of hybrid proteins. or 1000 Genomes databases were identified. Using the Protein Smaller cancer fusion genes tend to be associated with the rare Variation Effect Analyzer internet-based tool, it was discov- types of cancer, for example EWS RNA binding protein 1 in ered that apparent, systemic mutations (not shared among Ewing's sarcoma.