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Roca-Umbert A, Garcia-Calleja J, Vogel-González M, Fierro-Villegas A, Ill-Raga G, Herrera-Fernández V, Bosnjak A, Muntané G, Gutiérrez E, Campelo F, Vicente R, Bosch E. Human genetic adaptation related to cellular zinc homeostasis. PLoS Genet 2023; 19:e1010950. [PMID: 37747921 PMCID: PMC10553801 DOI: 10.1371/journal.pgen.1010950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 10/05/2023] [Accepted: 08/31/2023] [Indexed: 09/27/2023] Open
Abstract
SLC30A9 encodes a ubiquitously zinc transporter (ZnT9) and has been consistently suggested as a candidate for positive selection in humans. However, no direct adaptive molecular phenotype has been demonstrated. Our results provide evidence for directional selection operating in two major complementary haplotypes in Africa and East Asia. These haplotypes are associated with differential gene expression but also differ in the Met50Val substitution (rs1047626) in ZnT9, which we show is found in homozygosis in the Denisovan genome and displays accompanying signatures suggestive of archaic introgression. Although we found no significant differences in systemic zinc content between individuals with different rs1047626 genotypes, we demonstrate that the expression of the derived isoform (ZnT9 50Val) in HEK293 cells shows a gain of function when compared with the ancestral (ZnT9 50Met) variant. Notably, the ZnT9 50Val variant was found associated with differences in zinc handling by the mitochondria and endoplasmic reticulum, with an impact on mitochondrial metabolism. Given the essential role of the mitochondria in skeletal muscle and since the derived allele at rs1047626 is known to be associated with greater susceptibility to several neuropsychiatric traits, we propose that adaptation to cold may have driven this selection event, while also impacting predisposition to neuropsychiatric disorders in modern humans.
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Affiliation(s)
- Ana Roca-Umbert
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Jorge Garcia-Calleja
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Marina Vogel-González
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Alejandro Fierro-Villegas
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Ill-Raga
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Víctor Herrera-Fernández
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Anja Bosnjak
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Muntané
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Esteban Gutiérrez
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Felix Campelo
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rubén Vicente
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
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Polimanti R, Walters RK, Johnson EC, McClintick JN, Adkins AE, Adkins DE, Bacanu SA, Bierut LJ, Bigdeli TB, Brown S, Bucholz KK, Copeland WE, Costello EJ, Degenhardt L, Farrer LA, Foroud TM, Fox L, Goate AM, Grucza R, Hack LM, Hancock DB, Hartz SM, Heath AC, Hewitt JK, Hopfer CJ, Johnson EO, Kendler KS, Kranzler HR, Krauter K, Lai D, Madden PAF, Martin NG, Maes HH, Nelson EC, Peterson RE, Porjesz B, Riley BP, Saccone N, Stallings M, Wall TL, Webb BT, Wetherill L, Edenberg HJ, Agrawal A, Gelernter J. Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium. Mol Psychiatry 2020; 25:1673-1687. [PMID: 32099098 PMCID: PMC7392789 DOI: 10.1038/s41380-020-0677-9] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 01/15/2020] [Accepted: 01/30/2020] [Indexed: 01/17/2023]
Abstract
To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10-5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.
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Affiliation(s)
- Renato Polimanti
- Department of Psychiatry, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Raymond K Walters
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jeanette N McClintick
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Amy E Adkins
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel E Adkins
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Silviu-Alin Bacanu
- Virginia Commonwealth University Alcohol Research Center, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - Sandra Brown
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - William E Copeland
- Department of Psychiatry, University of Vermont Medical Center, Burlington, VT, USA
| | - E Jane Costello
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Louisa Degenhardt
- National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Tatiana M Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Louis Fox
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Alison M Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Richard Grucza
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Laura M Hack
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Dana B Hancock
- Center for Omics Discovery and Epidemiology, RTI International, Research Triangle Park, NC, USA
| | - Sarah M Hartz
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - John K Hewitt
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Christian J Hopfer
- Department of Psychiatry, University of Colorado Denver, Aurora, CO, USA
| | - Eric O Johnson
- Center for Omics Discovery and Epidemiology, RTI International, Research Triangle Park, NC, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Henry R Kranzler
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
| | - Kenneth Krauter
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, CO, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Hermine H Maes
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Elliot C Nelson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Roseann E Peterson
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - Brien P Riley
- Virginia Commonwealth University Alcohol Research Center, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Nancy Saccone
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Michael Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Tamara L Wall
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Bradley T Webb
- Virginia Commonwealth University Alcohol Research Center, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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Strillacci MG, Gorla E, Ríos-Utrera A, Vega-Murillo VE, Montaño-Bermudez M, Garcia-Ruiz A, Cerolini S, Román-Ponce SI, Bagnato A. Copy Number Variation Mapping and Genomic Variation of Autochthonous and Commercial Turkey Populations. Front Genet 2019; 10:982. [PMID: 31737031 PMCID: PMC6828962 DOI: 10.3389/fgene.2019.00982] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 09/13/2019] [Indexed: 01/02/2023] Open
Abstract
This study aims at investigating genomic diversity of several turkey populations using Copy Number Variants (CNVs). A total of 115 individuals from six Italian breeds (Colle Euganei, Bronzato Comune Italiano, Parma e Piacenza, Brianzolo, Nero d'Italia, and Ermellinato di Rovigo), seven Narragansett, 38 commercial hybrids, and 30 Mexican turkeys, were genotyped with the Affymetrix 600K single nucleotide polymorphism (SNP) turkey array. The CNV calling was performed with the Hidden Markov Model of PennCNV software and with the Copy Number Analysis Module of SVS 8.4 by Golden Helix®. CNV were summarized into CNV regions (CNVRs) at population level using BEDTools. Variability among populations has been addressed by hierarchical clustering (pvclust R package) and by principal component analysis (PCA). A total of 2,987 CNVs were identified covering 4.65% of the autosomes of the Turkey_5.0/melGal5 assembly. The CNVRs identified in at least two individuals were 362-189 gains, 116 losses, and 57 complexes. Among these regions the 51% contain annotated genes. This study is the first CNV mapping of turkey population using 600K chip. CNVs clustered the individuals according to population and their geographical origin. CNVs are known to be indicators also of adaptation, as some researches in different species are suggesting.
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Affiliation(s)
- Maria G Strillacci
- Department of Veterinary Medicine, Università degli Studi di Milano, Milano, Italy
| | - Erica Gorla
- Department of Veterinary Medicine, Università degli Studi di Milano, Milano, Italy
| | - Angel Ríos-Utrera
- Campo Experimental La Posta, INIFAP, Municipio de Medellín, Veracruz, Mexico
| | | | - Moises Montaño-Bermudez
- Centro Nacional de Investigación en Fisiología y Mejoramiento Animal, INIFAP, Auchitlán, Querétaro, Mexico
| | - Adriana Garcia-Ruiz
- Centro Nacional de Investigación en Fisiología y Mejoramiento Animal, INIFAP, Auchitlán, Querétaro, Mexico
| | - Silvia Cerolini
- Department of Veterinary Medicine, Università degli Studi di Milano, Milano, Italy
| | - Sergio I Román-Ponce
- Centro Nacional de Investigación en Fisiología y Mejoramiento Animal, INIFAP, Auchitlán, Querétaro, Mexico
| | - Alessandro Bagnato
- Department of Veterinary Medicine, Università degli Studi di Milano, Milano, Italy
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