Kohdennettu Uuden Sukupolven DNA-Sekvensointi

Total Page:16

File Type:pdf, Size:1020Kb

Kohdennettu Uuden Sukupolven DNA-Sekvensointi HELSINGIN YLIOPISTO BIOTIETEIDEN LAITOS PERINNÖLLISYYSTIEDE Kohdennettu uuden suku- polven DNA-sekvensointi aksonirappeumataudeissa: uudet KIF1A- ja HSPB1-mutaatiot ja fenotyypit Nella Junna 2015 Sisällysluettelo Lyhenteet ............................................................................................................................................. v 1. Johdanto ....................................................................................................................................... 1 2. Kirjallisuuskatsaus....................................................................................................................... 2 2.1 Hermosto ja neurologiset sairaudet ................................................................................... 2 2.2 Charcot-Marie-Toothin tauti 2 (CMT2) ........................................................................... 3 2.2.1 Oireet, hoidot ja ennuste .................................................................................................... 3 2.2.2 Sairauden aiheuttava mekanismi ....................................................................................... 4 2.2.3 CMT2:n jaottelu ja diagnosointi ........................................................................................ 4 2.3 CMT2:n genetiikka ............................................................................................................. 7 2.3.1 Molekyylimoottorit ja aksonaalinen kuljetus .................................................................... 7 2.3.2 Mitokondriodynamiikka .................................................................................................... 8 2.3.3 Sytoskeletonin toiminta ................................................................................................... 10 2.3.4 Muita funktioita ............................................................................................................... 11 2.4 Hereditäärinen spastinen paraplegia (HSP) ................................................................... 14 2.4.1 Oireet, hoidot ja ennuste .................................................................................................. 14 2.4.2 Sairauden aiheuttava mekanismi ..................................................................................... 15 2.4.3 HSP:n jaottelu ja diagnostiikka ....................................................................................... 15 2.5 HSP:n genetiikka ............................................................................................................... 16 2.5.1 Mitokondriodynamiikka .................................................................................................. 18 2.5.2 Aksonaalisen kuljetuksen häiriöt ..................................................................................... 18 2.5.3 ER-verkoston toiminta ..................................................................................................... 19 2.5.4 BMP-signalointi ............................................................................................................... 21 2.5.5 Endosomien Membraaniliikenne ..................................................................................... 23 2.5.6 Primaarinen myeliinihäiriö .............................................................................................. 23 2.5.7 Kortikospinaaliradan kehityshäiriöt................................................................................. 24 2.5.8 Lipidien synteesi ja metabolia ......................................................................................... 24 2.6 Kohdennettu uuden sukupolven sekvensointimenetelmä .............................................. 25 2.6.1 Uuden sukupolven sekvensointimenetelmät .................................................................... 25 2.6.2 Kohdennettu uuden sukupolven sekvensointimenetelmä ................................................ 26 ii 2.6.3 Sekvensointitulosten analysoiminen ................................................................................ 27 2.6.4 Kohdennetun NGS:n haasteet ja virhelähteet .................................................................. 28 2.6.5 Kohdennettu NGS diagnostiikan apuvälineenä ............................................................... 28 3. Tavoitteet .................................................................................................................................... 30 4. Materiaalit ja menetelmät .......................................................................................................... 31 4.1 Potilaat ................................................................................................................................ 31 4.1.1 CMT-potilaat ................................................................................................................... 31 4.1.2 HSP-potilaat ..................................................................................................................... 33 4.2 Kohdennettu uuden sukupolven sekvensointimenetelmä .............................................. 34 4.2.1 Sekvensointi ..................................................................................................................... 34 4.2.2 Geenipaneeli .................................................................................................................... 35 4.2.3 Ohjelmat ja tietokannat .................................................................................................... 36 4.2.4 Varianttien analysointi ..................................................................................................... 37 4.2.5 Pistemutaatiot .................................................................................................................. 38 4.2.6 Pienet insertiot ja deleetiot ............................................................................................... 39 4.3 Varianttien Sanger-sekvensointi ...................................................................................... 39 4.3.1 PCR-alukkeiden suunnittelu ............................................................................................ 39 4.3.2 PCR-ohjelmat .................................................................................................................. 40 4.3.3 Sekvensointi ..................................................................................................................... 43 4.4 Proteiinieristys fibroblasteista ja HSPB1 Western blot ................................................. 44 4.4.1 Fibroblastien kasvatus ja proteiinien eristys .................................................................... 44 4.4.2 Western blot ..................................................................................................................... 44 5. Tulokset ...................................................................................................................................... 46 5.1 Kohdennetun sekvensoinnin onnistuminen .................................................................... 46 5.2 Varianttien analysoinnin tulokset .................................................................................... 48 5.2.1 Varianttien analysointi ..................................................................................................... 48 5.2.2 Lopputulokset .................................................................................................................. 51 5.2.3 CMT-potilaiden lopputulokset ......................................................................................... 53 5.2.4 HSP-potilaiden lopputulokset .......................................................................................... 55 5.3 Western blot ....................................................................................................................... 56 iii 6. Tulosten tarkastelu .................................................................................................................... 57 6.1 Kohdennetun uuden sukupolven sekvensointimenetelmän onnistuminen .................. 57 6.1.1 Sekvensointi ..................................................................................................................... 57 6.1.2 Varianttien analysointi ..................................................................................................... 57 6.2 HSP- ja CMT-potilaiden molekulaarisen diagnoosin selvittäminen ............................ 59 6.2.1 Mutaatioiden patogeenisuuden arviointi .......................................................................... 59 6.2.1.1 Varmasti ja todennäköisesti patogeeniset mutaatiot ................................................ 60 6.2.1.2 Mahdolliset tautimutaatiot ........................................................................................ 63 6.2.1.3 Potilaat, joille ei löytynyt sairauden aiheuttanutta mutaatiota ................................. 64 6.2.2 Patogeenisten mutaatioiden tunnistamisen ongelmat ...................................................... 66 6.2.3 Kohdennetun NGS:n soveltuvuus diagnostiikassa .......................................................... 66 6.3 Jatkotutkimukset ............................................................................................................... 68 6.3.1 KIF1A-geenin de novo missense-mutaatiot moottoridomeenissa aiheuttavat vakavan taudinkuvan ................................................................................................................................
Recommended publications
  • Supplementary Data
    Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2).
    [Show full text]
  • 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.
    [Show full text]
  • Broad Poster Vivek
    A novel computational method for finding regions with copy number abnormalities in cancer cells Vivek, Manuel Garber, and Mike Zody Broad Institute of MIT and Harvard, Cambridge, MA, USA Introduction Results Cancer can result from the over expression of oncogenes, genes which control and regulate cell growth. Sometimes oncogenes increase in 1 2 3 activity due to a specific genetic mutation called a translocation (Fig 1). SMAD4 – a gene known to be deleted in pancreatic COX10 – a gene deleted in cytochrome c oxidase AK001392 – a hereditary prostate cancer protein This translocation allows the oncogene to remain as active as its paired carcinoma deficiency, known to be related to cell proliferation gene. Amplification of this mutation can occur, thereby creating the proper conditions for uncontrolled cell growth; consequently, each Results from Analysis Program Results from Analysis Program Results from Analysis Program component of the translocation will amplify in similar quantities. In this mutation, the chromosomal region containing the oncogene displaces to Region 1 Region 2 R2 Region 1 Region 2 R2 Region 1 Region 2 R2 a region on another chromosome containing a gene that is expressed Chr18:47044749-47311978 Chr17:13930739-14654741 0.499070821478475 Chr17:13930739-14654741 Chr18:26861790-27072166 0.47355172850856 Chr17:12542326-13930738 Chr8:1789292-1801984 0.406208680312004 frequently. Actual region containing gene Actual region containing gene Actual region containing gene chr18: 45,842,214 - 48,514,513 chr17: 13,966,862 - 14,068,461 chr17: 12,542,326 - 13,930,738 Fig 1. Two chromosomal regions (abcdef and ghijk) are translocating to create two new regions (abckl and ghijedf).
    [Show full text]
  • Long, Noncoding RNA Dysregulation in Glioblastoma
    cancers Review Long, Noncoding RNA Dysregulation in Glioblastoma Patrick A. DeSouza 1,2 , Xuan Qu 1, Hao Chen 1,3, Bhuvic Patel 1 , Christopher A. Maher 2,4,5,6 and Albert H. Kim 1,6,* 1 Department of Neurological Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; [email protected] (P.A.D.); [email protected] (X.Q.); [email protected] (H.C.); [email protected] (B.P.) 2 Department of Internal Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; [email protected] 3 Department of Neuroscience, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA 4 Department of Biomedical Engineering, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA 5 McDonnell Genome Institute, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA 6 Siteman Cancer Center, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA * Correspondence: [email protected] Simple Summary: Developing effective therapies for glioblastoma (GBM), the most common primary brain cancer, remains challenging due to the heterogeneity within tumors and therapeutic resistance that drives recurrence. Noncoding RNAs are transcribed from a large proportion of the genome and remain largely unexplored in their contribution to the evolution of GBM tumors. Here, we will review the general mechanisms of long, noncoding RNAs and the current knowledge of how these impact heterogeneity and therapeutic resistance in GBM. A better understanding of the molecular drivers required for these aggressive tumors is necessary to improve the management and outcomes Citation: DeSouza, P.A.; Qu, X.; of this challenging disease.
    [Show full text]
  • Why Cells and Viruses Cannot Survive Without an ESCRT
    cells Review Why Cells and Viruses Cannot Survive without an ESCRT Arianna Calistri * , Alberto Reale, Giorgio Palù and Cristina Parolin Department of Molecular Medicine, University of Padua, 35121 Padua, Italy; [email protected] (A.R.); [email protected] (G.P.); [email protected] (C.P.) * Correspondence: [email protected] Abstract: Intracellular organelles enwrapped in membranes along with a complex network of vesicles trafficking in, out and inside the cellular environment are one of the main features of eukaryotic cells. Given their central role in cell life, compartmentalization and mechanisms allowing their maintenance despite continuous crosstalk among different organelles have been deeply investigated over the past years. Here, we review the multiple functions exerted by the endosomal sorting complex required for transport (ESCRT) machinery in driving membrane remodeling and fission, as well as in repairing physiological and pathological membrane damages. In this way, ESCRT machinery enables different fundamental cellular processes, such as cell cytokinesis, biogenesis of organelles and vesicles, maintenance of nuclear–cytoplasmic compartmentalization, endolysosomal activity. Furthermore, we discuss some examples of how viruses, as obligate intracellular parasites, have evolved to hijack the ESCRT machinery or part of it to execute/optimize their replication cycle/infection. A special emphasis is given to the herpes simplex virus type 1 (HSV-1) interaction with the ESCRT proteins, considering the peculiarities of this interplay and the need for HSV-1 to cross both the nuclear-cytoplasmic and the cytoplasmic-extracellular environment compartmentalization to egress from infected cells. Citation: Calistri, A.; Reale, A.; Palù, Keywords: ESCRT; viruses; cellular membranes; extracellular vesicles; HSV-1 G.; Parolin, C.
    [Show full text]
  • Oncorequisite Role of an Aldehyde Dehydrogenase in the Pathogenesis of T-Cell Acute Lymphoblastic Leukemia
    Acute Lymphoblastic Leukemia SUPPLEMENTARY APPENDIX Oncorequisite role of an aldehyde dehydrogenase in the pathogenesis of T-cell acute lymphoblastic leukemia Chujing Zhang, 1 Stella Amanda, 1 Cheng Wang, 2 Tze King Tan, 1 Muhammad Zulfaqar Ali, 1 Wei Zhong Leong, 1 Ley Moy Ng, 1 Shojiro Kitajima, 3 Zhenhua Li, 4 Allen Eng Juh Yeoh, 1,4 Shi Hao Tan 1 and Takaomi Sanda 1,5 1Cancer Science Institute of Singapore, National University of Singapore, Singapore; 2Department of Anatomy, National University of Singapore, Singapore; 3Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan; 4VIVA-NUS CenTRAL, Department of Pedi - atrics, National University of Singapore, Singapore and 5Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. ©2021 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2019.245639 Received: December 18, 2019. Accepted: May 14, 2020. Pre-published: May 15, 2020. Correspondence: TAKAOMI SANDA - [email protected] Zhang et al Roles of ALDH in T-ALL Supplementary Information Supplementary Materials and Methods Cell culture and reagents All human leukemia cell lines were cultured in RPMI-1640 medium (BioWest) supplemented with 10% FBS (BioWest). 293T cells were maintained in DMEM medium (BioWest) supplemented with 10% FBS and penicillin/streptomycin (Life Technologies). All-trans retinaldehyde was purchased from Sigma-Aldrich. Glucose free and Glutamine free RPMI- 1640 media were purchased from ThermoFisher. Patient derived xenograft (PDX) sample T-ALL patient-derived PDX sample (DFCI15) was kindly provided by Alejandro Gutierrez (Boston Children’s Hospital, Boston). Mouse studies were conducted according to the recommendations from the Institutional Animal Care and Use Committee (IACUC) and all protocols were approved by the Committee at the National University of Singapore (NUS).
    [Show full text]
  • Impairment of Social Behaviors in Arhgef10 Knockout Mice
    Lu et al. Molecular Autism (2018) 9:11 https://doi.org/10.1186/s13229-018-0197-5 RESEARCH Open Access Impairment of social behaviors in Arhgef10 knockout mice Dai-Hua Lu1, Hsiao-Mei Liao2, Chia-Hsiang Chen3,4, Huang-Ju Tu1, Houng-Chi Liou1, Susan Shur-Fen Gau2* and Wen-Mei Fu1* Abstract Background: Impaired social interaction is one of the essential features of autism spectrum disorder (ASD). Our previous copy number variation (CNV) study discovered a novel deleted region associated with ASD. One of the genes included in the deleted region is ARHGEF10. A missense mutation of ARHGEF10 has been reported to be one of the contributing factors in several diseases of the central nervous system. However, the relationship between the loss of ARHGEF10 and the clinical symptoms of ASD is unclear. Methods: We generated Arhgef10 knockout mice as a model of ASD and characterized the social behavior and the biochemical changes in the brains of the knockout mice. Results: Compared with their wild-type littermates, the Arhgef10-depleted mice showed social interaction impairment, hyperactivity, and decreased depression-like and anxiety-like behavior. Behavioral measures of learning in the Morris water maze were not affected by Arhgef10 deficiency. Moreover, neurotransmitters including serotonin, norepinephrine, and dopamine were significantly increased in different brain regions of the Arhgef10 knockout mice. In addition, monoamine oxidase A (MAO-A) decreased in several brain regions. Conclusions: These results suggest that ARHGEF10 is a candidate risk gene for ASD and that the Arhgef10 knockout model could be a tool for studying the mechanisms of neurotransmission in ASD.
    [Show full text]
  • Analysis of the Indacaterol-Regulated Transcriptome in Human Airway
    Supplemental material to this article can be found at: http://jpet.aspetjournals.org/content/suppl/2018/04/13/jpet.118.249292.DC1 1521-0103/366/1/220–236$35.00 https://doi.org/10.1124/jpet.118.249292 THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS J Pharmacol Exp Ther 366:220–236, July 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Analysis of the Indacaterol-Regulated Transcriptome in Human Airway Epithelial Cells Implicates Gene Expression Changes in the s Adverse and Therapeutic Effects of b2-Adrenoceptor Agonists Dong Yan, Omar Hamed, Taruna Joshi,1 Mahmoud M. Mostafa, Kyla C. Jamieson, Radhika Joshi, Robert Newton, and Mark A. Giembycz Departments of Physiology and Pharmacology (D.Y., O.H., T.J., K.C.J., R.J., M.A.G.) and Cell Biology and Anatomy (M.M.M., R.N.), Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Received March 22, 2018; accepted April 11, 2018 Downloaded from ABSTRACT The contribution of gene expression changes to the adverse and activity, and positive regulation of neutrophil chemotaxis. The therapeutic effects of b2-adrenoceptor agonists in asthma was general enriched GO term extracellular space was also associ- investigated using human airway epithelial cells as a therapeu- ated with indacaterol-induced genes, and many of those, in- tically relevant target. Operational model-fitting established that cluding CRISPLD2, DMBT1, GAS1, and SOCS3, have putative jpet.aspetjournals.org the long-acting b2-adrenoceptor agonists (LABA) indacaterol, anti-inflammatory, antibacterial, and/or antiviral activity. Numer- salmeterol, formoterol, and picumeterol were full agonists on ous indacaterol-regulated genes were also induced or repressed BEAS-2B cells transfected with a cAMP-response element in BEAS-2B cells and human primary bronchial epithelial cells by reporter but differed in efficacy (indacaterol $ formoterol .
    [Show full text]
  • Supplementary Table 3: Genes Only Influenced By
    Supplementary Table 3: Genes only influenced by X10 Illumina ID Gene ID Entrez Gene Name Fold change compared to vehicle 1810058M03RIK -1.104 2210008F06RIK 1.090 2310005E10RIK -1.175 2610016F04RIK 1.081 2610029K11RIK 1.130 381484 Gm5150 predicted gene 5150 -1.230 4833425P12RIK -1.127 4933412E12RIK -1.333 6030458P06RIK -1.131 6430550H21RIK 1.073 6530401D06RIK 1.229 9030607L17RIK -1.122 A330043C08RIK 1.113 A330043L12 1.054 A530092L01RIK -1.069 A630054D14 1.072 A630097D09RIK -1.102 AA409316 FAM83H family with sequence similarity 83, member H 1.142 AAAS AAAS achalasia, adrenocortical insufficiency, alacrimia 1.144 ACADL ACADL acyl-CoA dehydrogenase, long chain -1.135 ACOT1 ACOT1 acyl-CoA thioesterase 1 -1.191 ADAMTSL5 ADAMTSL5 ADAMTS-like 5 1.210 AFG3L2 AFG3L2 AFG3 ATPase family gene 3-like 2 (S. cerevisiae) 1.212 AI256775 RFESD Rieske (Fe-S) domain containing 1.134 Lipo1 (includes AI747699 others) lipase, member O2 -1.083 AKAP8L AKAP8L A kinase (PRKA) anchor protein 8-like -1.263 AKR7A5 -1.225 AMBP AMBP alpha-1-microglobulin/bikunin precursor 1.074 ANAPC2 ANAPC2 anaphase promoting complex subunit 2 -1.134 ANKRD1 ANKRD1 ankyrin repeat domain 1 (cardiac muscle) 1.314 APOA1 APOA1 apolipoprotein A-I -1.086 ARHGAP26 ARHGAP26 Rho GTPase activating protein 26 -1.083 ARL5A ARL5A ADP-ribosylation factor-like 5A -1.212 ARMC3 ARMC3 armadillo repeat containing 3 -1.077 ARPC5 ARPC5 actin related protein 2/3 complex, subunit 5, 16kDa -1.190 activating transcription factor 4 (tax-responsive enhancer element ATF4 ATF4 B67) 1.481 AU014645 NCBP1 nuclear cap
    [Show full text]
  • Gene Ontology Functional Annotations and Pleiotropy
    Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question
    [Show full text]
  • An ARHGEF10 Deletion Is Highly Associated with a Juvenile-Onset Inherited Polyneuropathy in Leonberger and Saint Bernard Dogs
    An ARHGEF10 Deletion Is Highly Associated with a Juvenile-Onset Inherited Polyneuropathy in Leonberger and Saint Bernard Dogs Kari J. Ekenstedt1.*, Doreen Becker2., Katie M. Minor1, G. Diane Shelton3, Edward E. Patterson4, Tim Bley5, Anna Oevermann6, Thomas Bilzer7, Tosso Leeb2, Cord Dro¨ gemu¨ ller2", James R. Mickelson1" 1 Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, United States of America, 2 Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland, 3 Comparative Neuromuscular Laboratory, Department of Pathology, University of California San Diego, La Jolla, California, United States of America, 4 Department of Veterinary Clinical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, United States of America, 5 Small Animal Clinic, Neruology, Vetsuisse Faculty, University of Bern, Bern, Switzerland, 6 Neurocenter, Department of Clinical Research and Veterinary Public Health, Vetsuisse Faculty, University of Bern, Bern, Switzerland, 7 Institute of Neuropathology, Heinrich-Heine-University Du¨sseldorf, Du¨sseldorf, Germany Abstract An inherited polyneuropathy (PN) observed in Leonberger dogs has clinical similarities to a genetically heterogeneous group of peripheral neuropathies termed Charcot-Marie-Tooth (CMT) disease in humans. The Leonberger disorder is a severe, juvenile- onset, chronic, progressive, and mixed PN, characterized by exercise intolerance, gait abnormalities and muscle atrophy of the pelvic limbs, as well as inspiratory stridor and dyspnea. We mapped a PN locus in Leonbergers to a 250 kb region on canine 210 chromosome 16 (Praw =1.16610 ,Pgenome, corrected = 0.006) utilizing a high-density SNP array. Within this interval is the ARHGEF10 gene, a member of the rho family of GTPases known to be involved in neuronal growth and axonal migration, and implicated in human hypomyelination.
    [Show full text]
  • Hereditary Spastic Paraplegia: from Genes, Cells and Networks to Novel Pathways for Drug Discovery
    brain sciences Review Hereditary Spastic Paraplegia: From Genes, Cells and Networks to Novel Pathways for Drug Discovery Alan Mackay-Sim Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD 4111, Australia; a.mackay-sim@griffith.edu.au Abstract: Hereditary spastic paraplegia (HSP) is a diverse group of Mendelian genetic disorders affect- ing the upper motor neurons, specifically degeneration of their distal axons in the corticospinal tract. Currently, there are 80 genes or genomic loci (genomic regions for which the causative gene has not been identified) associated with HSP diagnosis. HSP is therefore genetically very heterogeneous. Finding treatments for the HSPs is a daunting task: a rare disease made rarer by so many causative genes and many potential mutations in those genes in individual patients. Personalized medicine through genetic correction may be possible, but impractical as a generalized treatment strategy. The ideal treatments would be small molecules that are effective for people with different causative mutations. This requires identification of disease-associated cell dysfunctions shared across geno- types despite the large number of HSP genes that suggest a wide diversity of molecular and cellular mechanisms. This review highlights the shared dysfunctional phenotypes in patient-derived cells from patients with different causative mutations and uses bioinformatic analyses of the HSP genes to identify novel cell functions as potential targets for future drug treatments for multiple genotypes. Keywords: neurodegeneration; motor neuron disease; spastic paraplegia; endoplasmic reticulum; Citation: Mackay-Sim, A. Hereditary protein-protein interaction network Spastic Paraplegia: From Genes, Cells and Networks to Novel Pathways for Drug Discovery. Brain Sci. 2021, 11, 403.
    [Show full text]