What Is the Extent of the Role Played by Genetic Factors in Periodontitis?

Total Page:16

File Type:pdf, Size:1020Kb

What Is the Extent of the Role Played by Genetic Factors in Periodontitis? Perio Insight 4 Summer 2017 www.efp.org/perioinsight DEBATE EXPERT VIEW FOCUS RESEARCH Editor: Joanna Kamma What is the extent of the role played by genetic factors in periodontitis? Discover latest JCP research hile genetic factors are known to play a role in In a comprehensive overview of current knowledge, The Journal of Clinical Periodontology Wperiodontitis, a lot of research still needs to be they outline what is known today and discuss the (JCP) is the official scientific publication done to understand the mechanisms that are involved. most promising lines for future inquiry. of the European Federation of Indeed, the limited extent to which the genetic They note that the phenotypes of aggressive Periodontology (EFP). It publishes factors associated with periodontitis have been periodontitis (AgP) and chronic periodontitis (CP) may research relating to periodontal and peri- identified is “somewhat disappointing”, say Bruno not be as distinct as previously assumed because they implant diseases and their treatment. G. Loos and Deon P.M. Chin, from the Academic share genetic and other risk factors. The six JCP articles summarised in this Centre for Dentistry in Amsterdam. More on pages 2-5 edition of Perio Insight cover: (1) how periodontitis changes renal structures by oxidative stress and lipid peroxidation; (2) gingivitis and lifestyle influences on high-sensitivity C-reactive protein and interleukin 6 in adolescents; (3) the long-term efficacy of periodontal Researchers call regenerative therapies; (4) tooth loss in generalised aggressive periodontitis; (5) the association between diabetes for global action mellitus/hyperglycaemia and peri- implant diseases; (6) the efficacy of on periodontal collagen matrix seal and collagen sponge on ridge preservation in disease combination with bone allograft. Edited by Maurizio Tonetti, the JCP is call for global action to reduce the published monthly and has an impact A impact of periodontal diseases on factor of 3.477. health and well-being has been issued More on page 7-8 in a health-policy paper published in the Journal of Clinical Periodontology (JCP), CONTENTS the EFP’s scientific journal. The paper has been endorsed or Role of genetic factors in supported the EFP and 50 other periodontitis Page 2-5 international and national societies of periodontology. Experts call for global action Page 6 More on page 6 Latest JCP research Pages 7-8 Partners Issue 4 - Summer 2017 2 EXPERT VIEW What is the extent of the role played by genetic factors in the aetiology of periodontitis? By Bruno G. Loos and Deon P.M. Chin. While genetic factors are known to play a role in periodontitis, a lot of research still needs to be done to understand the precise mechanisms involved. Indeed, the limited extent to which the genetic factors associated with periodontitis have been identified is somewhat disappointing, although there are some promising lines of inquiry. eriodontitis is a complex chronic Fig. 1. Genetic multi-causality model for periodontitis Pinflammatory disease, in which there are multiple causal components1 that play their aetiological roles simultaneously and interact with each other. At least five domains of causal risk factors can be distinguished for periodontitis (see Fig. 1): 1. Environmental factors (a dysbiotic subgingival bacterial biofilm); 2. Genetic risk factors; 3. Lifestyle factors such as smoking, poor diet, and stress; 4. Systemic diseases, such as diabetes; 5. Other factors, as yet unknown but most likely also including tooth-related, occlusal, and iatrogenic factors. Within the domain of genetic risk factors for periodontitis, not only do certain genetic variations play a role, epigenetic changes in DNA are also involved. For the last 20 years, the periodontal community has followed the classification of two distinct phenotypes of periodontitis: aggressive Note: The multicausality model for periodontitis. Causal factors are ordered in five domains and periodontitis (AgP) and chronic periodontitis (CP). they play a role simultaneously, as well as interact with each other. Importantly, the relative AgP occurs most often at a younger age (up contribution of each causal factor varies among patients, therefore the size of each “piece” of to 35 years old) and these cases involve more the pie chart should be estimated per individual patient. genetic risk factors than CP cases (see Fig.2). See: Loos, B. G., Papantonopoulos, G., Jepsen, S. & Laine, M.L. (2015). What is the contribution of genetics to However, the phenotypes AgP and CP may not periodontal risk? Dental Clinics of North America, 59, 761-780. be as distinct as previously assumed and thus may not really be separate entities, because they do share genetic and other risk factors. It has been long recognised that cases of AgP can As in other complex chronic diseases, it is important The most common genetic variation between occur also in people aged over 35 and that cases to realise that a multitude of genetic variations individuals is called a single nucleotide of CP can occur in those below this age. (probably more than a hundred) are involved, so polymorphism (SNP). The frequency of a SNP is periodontal disease is called polygenic. on average one per 300 nucleotides. Nonetheless, almost all current studies on genetics use the defined disease entities: Taking this into account, it is somewhat Therefore, it is estimated that there are over 10 either AgP or CP. This has helped researchers to disappointing that, in the case of periodontitis, million SNPs in the human genome. These are focus on well-described case-control studies, the genetic factors associated with or annotated in the haplotype map (HapMap). something that is much needed in the search for contributing to the pathogenesis have been There are different types of SNPs: noncoding, identified only to a very limited extent and have genetic risk factors.2 coding, and regulatory polymorphisms. In been poorly validated. addition, there are other genetic variations such Genetic basis of periodontitis It is also possible that genetic variants as variable number tandem repeats (VNTR), On the basis of epidemiological studies of twins associated with periodontitis in, for example, nucleotide insertions and nucleotide deletions. and families with a higher rate of AgP, it can Caucasians may not be associated with other Variants in 38 genes have been associated with be concluded that in the younger patients the ethnic populations such as Asians, Brazilians, periodontitis, identified by using either the genetic contribution may account for as much and Africans. While a considerable overlap of candidate-gene approach or by genome-wide as 50% of causal factors, while in the older genetic variants between different ethnicities is association studies (GWAS) (see Table 1). patients a genetic contribution of at most 25% expected, it is important to realise that there will has been estimated.3 also be population-specific variants of risk genes. Issue 4 - Summer 2017 3 EXPERT VIEW Fig. 2. Genetic contribution to the aetiology of periodontitis to the discovery of novel candidate genes that have not been known or previously hypothesised – which yields not only new genetic risk factors but also the genetic variants found in GWAS can point to hitherto unknown genes and proteins. This enables the investigation of possible roles in biological pathways, especially in diseases such as periodontitis in which the pathophysiology is not well understood. The results of an initial GWAS need to be replicated (validated) in an independent case-control cohort with the candidate-gene approach. Until now five GWAS related to periodontitis have been performed. Genetic variants A total of 38 genes have been identified, in which one or several genetic variants have been associated with periodontitis, based on either the candidate-gene approach or GWAS (see Table 1). Only original genetic studies in which at least 100 cases and at least 100 controls were enrolled were considered in this brief review; however, Note: The genetic contribution to the aetiology of periodontitis in relatively younger individuals this low cut-off level may still yield false positive 3 with aggressive periodontitis has been considered higher than in older individuals with chronic results (type I error). periodontitis. In older individuals, environmental factors (a dysbiotic subgingival bacterial The table presents a global compilation, biofilm), lifestyle factors, systemic disease, age (immune senescence) contribute more to summarising the results from studies that have periodontitis development, whereas genetic factors play a smaller role. included different ethnicities. The genes which See: Loos, B. G., Papantonopoulos, G., Jepsen, S. & Laine, M.L. (2015). What is the contribution of have variant alleles (minor alleles) associated genetics to periodontal risk? Dental Clinics of North America, 59, 761-780. with both AgP and CP, with AgP only, with CP only, or just with periodontitis (PD) are listed in the table in sequence of the number of independent studies available. A given gene Candidate-gene approach be excluded.3Findings of negative associations with an SNP association with the disease in at for one selected SNP cannot rule out a potential Most often, the genetic loci, and the genetic least two independent studies provides greater disease association of the gene in question. polymorphisms that are positioned within these certainty about the validity. loci, have been chosen for candidate-gene studies Therefore,
Recommended publications
  • The Porcine Major Histocompatibility Complex and Related Paralogous Regions: a Review Patrick Chardon, Christine Renard, Claire Gaillard, Marcel Vaiman
    The porcine Major Histocompatibility Complex and related paralogous regions: a review Patrick Chardon, Christine Renard, Claire Gaillard, Marcel Vaiman To cite this version: Patrick Chardon, Christine Renard, Claire Gaillard, Marcel Vaiman. The porcine Major Histocom- patibility Complex and related paralogous regions: a review. Genetics Selection Evolution, BioMed Central, 2000, 32 (2), pp.109-128. 10.1051/gse:2000101. hal-00894302 HAL Id: hal-00894302 https://hal.archives-ouvertes.fr/hal-00894302 Submitted on 1 Jan 2000 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Genet. Sel. Evol. 32 (2000) 109–128 109 c INRA, EDP Sciences Review The porcine Major Histocompatibility Complex and related paralogous regions: a review Patrick CHARDON, Christine RENARD, Claire ROGEL GAILLARD, Marcel VAIMAN Laboratoire de radiobiologie et d’etude du genome, Departement de genetique animale, Institut national de la recherche agronomique, Commissariat al’energie atomique, 78352, Jouy-en-Josas Cedex, France (Received 18 November 1999; accepted 17 January 2000) Abstract – The physical alignment of the entire region of the pig major histocompat- ibility complex (MHC) has been almost completed. In swine, the MHC is called the SLA (swine leukocyte antigen) and most of its class I region has been sequenced.
    [Show full text]
  • Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by PubMed Central Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes Regine Bergholdt1*, Caroline Brorsson1, Kasper Lage2,3,4, Jens Høiriis Nielsen5, Søren Brunak2, Flemming Pociot1,6,7 1 Hagedorn Research Institute and Steno Diabetes Center, Gentofte, Denmark, 2 Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark, 3 Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 4 Broad Institute of MIT and Harvard, Seven Cambridge Center, Cambridge, Massachusetts, United States of America, 5 Department of Medical Biochemistry and Genetics, University of Copenhagen, Copenhagen, Denmark, 6 University of Lund/Clinical Research Centre (CRC), Malmø, Sweden, 7 Department of Biomedical Science, University of Copenhagen, Copenhagen, Denmark Abstract Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have previously identified sets of genes, likely to represent distinct cellular pathways involved in T1D risk. Here we evaluate the candidate genes involved in these putative interaction networks not only at the single gene level, but also in the context of the networks of which they form an integral part. mRNA expression levels for each gene were evaluated and profiling was performed by measuring and comparing constitutive expression in human islets versus cytokine-stimulated expression levels, and for lymphocytes by comparing expression levels among controls and T1D individuals.
    [Show full text]
  • Molecular and Epigenetic Features of Melanomas and Tumor Immune
    Seremet et al. J Transl Med (2016) 14:232 DOI 10.1186/s12967-016-0990-x Journal of Translational Medicine RESEARCH Open Access Molecular and epigenetic features of melanomas and tumor immune microenvironment linked to durable remission to ipilimumab‑based immunotherapy in metastatic patients Teofila Seremet1,3*† , Alexander Koch2†, Yanina Jansen1, Max Schreuer1, Sofie Wilgenhof1, Véronique Del Marmol3, Danielle Liènard3, Kris Thielemans4, Kelly Schats5, Mark Kockx5, Wim Van Criekinge2, Pierre G. Coulie6, Tim De Meyer2, Nicolas van Baren6,7 and Bart Neyns1 Abstract Background: Ipilimumab (Ipi) improves the survival of advanced melanoma patients with an incremental long-term benefit in 10–15 % of patients. A tumor signature that correlates with this survival benefit could help optimizing indi- vidualized treatment strategies. Methods: Freshly frozen melanoma metastases were collected from patients treated with either Ipi alone (n: 7) or Ipi combined with a dendritic cell vaccine (TriMixDC-MEL) (n: 11). Samples were profiled by immunohistochemistry (IHC), whole transcriptome (RNA-seq) and methyl-DNA sequencing (MBD-seq). Results: Patients were divided in two groups according to clinical evolution: durable benefit (DB; 5 patients) and no clinical benefit (NB; 13 patients). 20 metastases were profiled by IHC and 12 were profiled by RNA- and MBD-seq. 325 genes were identified as differentially expressed between DB and NB. Many of these genes reflected a humoral and cellular immune response. MBD-seq revealed differences between DB and NB patients in the methylation of genes linked to nervous system development and neuron differentiation. DB tumors were more infiltrated by CD8+ and PD-L1+ cells than NB tumors.
    [Show full text]
  • NFKBIL1 Antibody (Center) Blocking Peptide Synthetic Peptide Catalog # Bp10682c
    10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 NFKBIL1 Antibody (Center) Blocking peptide Synthetic peptide Catalog # BP10682c Specification NFKBIL1 Antibody (Center) Blocking NFKBIL1 Antibody (Center) Blocking peptide - peptide - Background Product Information This gene encodes a divergent member of the Primary Accession Q9UBC1 I-kappa-Bfamily of proteins. Its function has not been determined. The genelies within the major histocompatibility complex (MHC) class NFKBIL1 Antibody (Center) Blocking peptide - Additional Information Iregion on chromosome 6. Multiple transcript variants encodingdifferent isoforms have been found for this gene. [provided byRefSeq]. Gene ID 4795 NFKBIL1 Antibody (Center) Blocking Other Names peptide - References NF-kappa-B inhibitor-like protein 1, Inhibitor of kappa B-like protein, I-kappa-B-like Clancy, R.M., et al. Arthritis Rheum. protein, IkappaBL, Nuclear factor of kappa 62(11):3415-3424(2010)Bailey, S.D., et al. light polypeptide gene enhancer in B-cells Diabetes Care inhibitor-like 1, NFKBIL1, IKBL 33(10):2250-2253(2010)Ucisik-Akkaya, E., et Format al. Mol. Hum. Reprod. Peptides are lyophilized in a solid powder 16(10):770-777(2010)Rose, J.E., et al. Mol. format. Peptides can be reconstituted in Med. 16 (7-8), 247-253 (2010) :Owecki, M.K., solution using the appropriate buffer as et al. Pol. Merkur. Lekarski needed. 28(167):366-370(2010) Storage Maintain refrigerated at 2-8°C for up to 6 months. For long term storage store at -20°C. Precautions This product is for research use only. Not for use in diagnostic or therapeutic procedures.
    [Show full text]
  • NFKBIL1 Antibody Cat
    NFKBIL1 Antibody Cat. No.: 56-654 NFKBIL1 Antibody Confocal immunofluorescent analysis of NFKBIL1 NFKBIL1 Antibody immunohistochemistry analysis in Antibody with MDA-MB435 cell followed by Alexa Fluor formalin fixed and paraffin embedded human brain tissue 488-conjugated goat anti-rabbit lgG (green).Actin filaments followed by peroxidase conjugation of the secondary have been labeled with Alexa Fluor 555 phalloidin antibody and DAB staining. (red).DAPI was used to stain the cell nuclear (blue). Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human HOMOLOGY: Predicted species reactivity based on immunogen sequence: Mouse, Pig This NFKBIL1 antibody is generated from rabbits immunized with a KLH conjugated IMMUNOGEN: synthetic peptide between 327-356 amino acids from the C-terminal region of human NFKBIL1. TESTED APPLICATIONS: IF, IHC-P, WB September 24, 2021 1 https://www.prosci-inc.com/nfkbil1-antibody-56-654.html For WB starting dilution is: 1:1000 APPLICATIONS: For IHC-P starting dilution is: 1:10~50 For IF starting dilution is: 1:10~50 PREDICTED MOLECULAR 43 kDa WEIGHT: Properties This antibody is purified through a protein A column, followed by peptide affinity PURIFICATION: purification. CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: NFKBIL1 NF-kappa-B inhibitor-like protein 1, Inhibitor of kappa B-like protein, I-kappa-B-like ALTERNATE NAMES: protein, IkappaBL, Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-like 1, NFKBIL1, IKBL ACCESSION NO.: Q9UBC1 PROTEIN GI NO.: 44888077 GENE ID: 4795 USER NOTE: Optimal dilutions for each application to be determined by the researcher.
    [Show full text]
  • Proteomics Analysis of Cellular Proteins Co-Immunoprecipitated with Nucleoprotein of Influenza a Virus (H7N9)
    Article Proteomics Analysis of Cellular Proteins Co-Immunoprecipitated with Nucleoprotein of Influenza A Virus (H7N9) Ningning Sun 1,:, Wanchun Sun 2,:, Shuiming Li 3, Jingbo Yang 1, Longfei Yang 1, Guihua Quan 1, Xiang Gao 1, Zijian Wang 1, Xin Cheng 1, Zehui Li 1, Qisheng Peng 2,* and Ning Liu 1,* Received: 26 August 2015 ; Accepted: 22 October 2015 ; Published: 30 October 2015 Academic Editor: David Sheehan 1 Central Laboratory, Jilin University Second Hospital, Changchun 130041, China; [email protected] (N.S.); [email protected] (J.Y.); [email protected] (L.Y.); [email protected] (G.Q.); [email protected] (X.G.); [email protected] (Z.W.); [email protected] (X.C.); [email protected] (Z.L.) 2 Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, Jilin University, Changchun 130062, China; [email protected] 3 College of Life Sciences, Shenzhen University, Shenzhen 518057, China; [email protected] * Correspondence: [email protected] (Q.P.); [email protected] (N.L.); Tel./Fax: +86-431-8879-6510 (Q.P. & N.L.) : These authors contributed equally to this work. Abstract: Avian influenza A viruses are serious veterinary pathogens that normally circulate among avian populations, causing substantial economic impacts. Some strains of avian influenza A viruses, such as H5N1, H9N2, and recently reported H7N9, have been occasionally found to adapt to humans from other species. In order to replicate efficiently in the new host, influenza viruses have to interact with a variety of host factors. In the present study, H7N9 nucleoprotein was transfected into human HEK293T cells, followed by immunoprecipitated and analyzed by proteomics approaches.
    [Show full text]
  • The Role and Assembly Mechanism of Nucleoprotein in Influenza a Virus
    ARTICLE Received 28 Sep 2012 | Accepted 8 Feb 2013 | Published 12 Mar 2013 DOI: 10.1038/ncomms2589 The role and assembly mechanism of nucleoprotein in influenza A virus ribonucleoprotein complexes Lauren Turrell1, Jon W. Lyall2, Laurence S. Tiley2, Ervin Fodor1 & Frank T. Vreede1 The nucleoprotein of negative-strand RNA viruses forms a major component of the ribonucleoprotein complex that is responsible for viral transcription and replication. However, the precise role of nucleoprotein in viral RNA transcription and replication is not clear. Here we show that nucleoprotein of influenza A virus is entirely dispensable for replication and transcription of short viral RNA-like templates in vivo, suggesting that nucleoprotein repre- sents an elongation factor for the viral RNA polymerase. We also find that the recruitment of nucleoprotein to nascent ribonucleoprotein complexes during replication of full-length viral genes is mediated through nucleoprotein–nucleoprotein homo-oligomerization in a ‘tail loop- first’ orientation and is independent of RNA binding. This work demonstrates that nucleo- protein does not regulate the initiation and termination of transcription and replication by the viral polymerase in vivo, and provides new mechanistic insights into the assembly and regulation of viral ribonucleoprotein complexes. 1 Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK. 2 Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK. Correspondence and requests for materials should be addressed to F.T.V. (email: [email protected]). NATURE COMMUNICATIONS | 4:1591 | DOI: 10.1038/ncomms2589 | www.nature.com/naturecommunications 1 & 2013 Macmillan Publishers Limited.
    [Show full text]
  • Pleiotropy in Complex Traits
    Pleiotropy in complex traits Sophie Hackinger Wellcome Sanger Institute University of Cambridge Jesus College This dissertation is submitted for the degree of Doctor of Philosophy September 2018 ii Abstract Thesis title: Pleiotropy in complex traits Name: Sophie Hackinger Genome-wide association studies (GWAS) have uncovered thousands of complex trait loci, many of which are associated with multiple phenotypes. The dedicated study of these pleiotropic effects is becoming increasingly common due to the availability of sample collections with high-dimensional phenotype data, such as the UK Biobank, and can yield important insights into the aetiology underlying complex disorders. In my PhD, I performed multi-trait analyses of medically relevant complex phenotypes to identify shared genetic factors. My first project involved a genome-wide overlap analysis of osteoarthritis (OA) and bone- mineral density (BMD), using summary statistics from two large-scale GWAS. OA and BMD are known to be inversely correlated, yet the genetics underlying this link remain poorly understood. I found robust evidence for association with OA at the SMAD3 locus, which is known to play a role in bone remodeling and cartilage maintenance. My second project aimed to elucidate the increased prevalence of type 2 diabetes (T2D) in schizophrenia (SCZ) patients. I used GWAS summary statistics of SCZ and T2D from the PGC and DIAGRAM consortia, respectively, to perform polygenic risk score analyses in three patient groups (SCZ only, T2D only, comorbid SCZ and T2D) and population-based controls. I find that the comorbid patient group have a higher genetic risk for both T2D and SCZ compared to controls, supporting the hypothesis that the epidemiologic link between these disorders is at least in part due to genetic factors.
    [Show full text]
  • Genes Between the Complement Cluster and HLA-B THOMAS SPIES*, MAUREEN BRESNAHAN, and JACK L
    Proc. Nati. Acad. Sci. USA Vol. 86, pp. 8955-8958, November 1989 Immunology Human major histocompatibility complex contains a minimum of 19 genes between the complement cluster and HLA-B THOMAS SPIES*, MAUREEN BRESNAHAN, AND JACK L. STROMINGER Department of Biochemistry and Molecular Biology, Harvard University, Cambridge, MA 02138 Contributed by Jack L. Strominger, August 15, 1989 ABSTRACT A 600-kilobase (kb) DNA segment from the meric side, the gene for 21-OHB is 350 kb distant from the human major histocompatibility complex (MHC) class HI nearest class II locus, DR. Presently, no genes have been region was isolated by extension of a previous 435-kb chromo- localized within this region. On the telomeric side, the gene some walk. The contiguous series of cloned overlapping for C2 is separated by 600 kb from the proximal class I locus, cosmids contains the entire 555-kb interval between C2 in the HLA-B. This interval includes the genes for the tumor complement gene cluster and HLA-B. This region is known to necrosis factors (TNFs) a and 83 and the major heat shock encode the tumor necrosis factors (TNFs) a and (, B144, and protein HSP70 (7, 8, 11). the major heat shock protein HSP70. Moreover, a cluster of To identify genes within the MHC class III region, a 435-kb genes, BAT1-BAT5 (HLA-B-associated transcripts) has been genomic segment centromeric to HLA-B has recently been localized in the vicinity of the genes for TNFa and TNF3. An isolated by chromosome walking with overlapping cosmids additional four genes were identified by isolation of corre- (12).
    [Show full text]
  • Protein Moonlighting Revealed by Non-Catalytic Phenotypes of Yeast Enzymes
    Genetics: Early Online, published on November 10, 2017 as 10.1534/genetics.117.300377 Protein Moonlighting Revealed by Non-Catalytic Phenotypes of Yeast Enzymes Adriana Espinosa-Cantú1, Diana Ascencio1, Selene Herrera-Basurto1, Jiewei Xu2, Assen Roguev2, Nevan J. Krogan2 & Alexander DeLuna1,* 1 Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del IPN, 36821 Irapuato, Guanajuato, Mexico. 2 Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, 94158, USA. *Corresponding author: [email protected] Running title: Genetic Screen for Moonlighting Enzymes Keywords: Protein moonlighting; Systems genetics; Pleiotropy; Phenotype; Metabolism; Amino acid biosynthesis; Saccharomyces cerevisiae 1 Copyright 2017. 1 ABSTRACT 2 A single gene can partake in several biological processes, and therefore gene 3 deletions can lead to different—sometimes unexpected—phenotypes. However, it 4 is not always clear whether such pleiotropy reflects the loss of a unique molecular 5 activity involved in different processes or the loss of a multifunctional protein. Here, 6 using Saccharomyces cerevisiae metabolism as a model, we systematically test 7 the null hypothesis that enzyme phenotypes depend on a single annotated 8 molecular function, namely their catalysis. We screened a set of carefully selected 9 genes by quantifying the contribution of catalysis to gene-deletion phenotypes 10 under different environmental conditions. While most phenotypes were explained 11 by loss of catalysis, slow growth was readily rescued by a catalytically-inactive 12 protein in about one third of the enzymes tested. Such non-catalytic phenotypes 13 were frequent in the Alt1 and Bat2 transaminases and in the isoleucine/valine- 14 biosynthetic enzymes Ilv1 and Ilv2, suggesting novel "moonlighting" activities in 15 these proteins.
    [Show full text]
  • Uq00522f8 OA.Pdf
    1 2 DR THAISE MELO (Orcid ID : 0000-0003-0983-4602) 3 DR MARINA R. S. FORTES (Orcid ID : 0000-0002-7254-1960) 4 5 6 Article type : Original Article 7 8 9 Short Running Title: Across-breed QTL validation for sexual precocity in tropical cattle 10 Title: ACROSS-BREED VALIDATION STUDY CONFIRMS AND IDENTIFIES 11 NEW LOCI ASSOCIATED WITH SEXUAL PRECOCITY IN BRAHMAN AND 12 NELLORE CATTLE1 13 Thaise Pinto de Melo*, Marina Rufino Salinas Fortes†‡, Ben Hayes‡, Lucia Galvão de 14 Albuquerque*§, Roberto Carvalheiro*§ 15 16 *Department of Animal Science, School of Agricultural and Veterinarian Sciences, 17 FCAV/ UNESP - Sao Paulo State University, Jaboticabal, Sao Paulo, 14884-900, 18 Brazil. 19 †The University of Queensland, School of Chemistry and Molecular Biosciences, St 20 Lucia, Queensland 4072, Australia. 21 ‡The University of Queensland, Queensland Alliance for Agriculture and Food 22 Innovation, St Lucia, Queensland 4072, Australia. 23 §National Council for Scientific and Technological Development (CNPq), Brasília, 24 Distrito Federal, Brazil. 25 Corresponding author: Roberto Carvalheiro, School of Agricultural and Veterinarian 26 Sciences, FCAV/ UNESP - Sao Paulo State University, Jaboticabal, Brazil. Email: 27 [email protected] Manuscript 28 This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/JBG.12429 This article is protected by copyright. All rights reserved 29 ABSTRACT: The aim of this study was to identify candidate regions associated with 30 sexual precocity in Bos indicus.
    [Show full text]
  • A Prioritization Analysis of Disease Association by Data-Mining of Functional Annotation of Human Genes
    Genomics 99 (2012) 1–9 Contents lists available at SciVerse ScienceDirect Genomics journal homepage: www.elsevier.com/locate/ygeno A prioritization analysis of disease association by data-mining of functional annotation of human genes Takayuki Taniya a,b, Susumu Tanaka c, Yumi Yamaguchi-Kabata b,1, Hideki Hanaoka d, Chisato Yamasaki a,b, Harutoshi Maekawa a,e, Roberto A. Barrero f, Boris Lenhard g, Milton W. Datta h, Mary Shimoyama i, Roger Bumgarner j, Ranajit Chakraborty k,l, Ian Hopkinson m, Libin Jia n, Winston Hide o, Charles Auffray p, Shinsei Minoshima q, Tadashi Imanishi b,⁎, Takashi Gojobori b,r,⁎⁎ a Japan Biological Information Research Center, Japan Biological Informatics Consortium, AIST Bio-IT Research Building 7F, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan b Biological Information Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan c Tokyo Metropolitan Institute of Medical Science, 2-1-6 Kamikitazawa, Setagaya-ku, Tokyo 156-8506, Japan d University of Tokyo, Laboratory of Plant Biotechnology, Biotechnology Research Center, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan e C's Lab Co., Ltd., Yamate Bldg. 2F, 7-5-1 Hamamatsu-cho, Minato-ku, Tokyo 101-0041, Japan f Centre for Comparative Genomics, Murdoch University, South Street, WA 6150, Australia g Center for Genomics and Bioinformatics, Karolinska Institute, Berzelius väg 35, SE-171 77 Stockholm, Sweden h Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, United
    [Show full text]