1
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Li Q, Faux P, Wentworth Winchester E, Yang G, Chen Y, Ramírez LM, Fuentes-Guajardo M, Poloni L, Steimetz E, Gonzalez-José R, Acuña V, Bortolini MC, Poletti G, Gallo C, Rothhammer F, Rojas W, Zheng Y, Cox JC, Patel V, Hoffman MP, Ding L, Peng C, Cotney J, Navarro N, Cox TC, Delgado M, Adhikari K, Ruiz-Linares A. PITX2 expression and Neanderthal introgression in HS3ST3A1 contribute to variation in tooth dimensions in modern humans. Curr Biol 2024:S0960-9822(24)01568-9. [PMID: 39672157 DOI: 10.1016/j.cub.2024.11.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 09/29/2024] [Accepted: 11/15/2024] [Indexed: 12/15/2024]
Abstract
Dental morphology varies greatly throughout evolution, including in the human lineage, but little is known about the biology of this variation. Here, we use multiomics analyses to examine the genetics of variation in tooth crown dimensions. In a human cohort with mixed continental ancestry, we detected genome-wide significant associations at 18 genome regions. One region includes EDAR, a gene known to impact dental features in East Asians. Furthermore, we find that EDAR variants increase the mesiodistal diameter of all teeth, following an anterior-posterior gradient of decreasing strength. Among the 17 novel-associated regions, we replicate 7/13 in an independent human cohort and find that 4/12 orthologous regions affect molar size in mice. Two association signals point to compelling candidate genes. One is ∼61 kb from PITX2, a major determinant of tooth development. Another overlaps HS3ST3A1, a paralogous neighbor of HS3ST3B1, a tooth enamel knot factor. We document the expression of Pitx2 and Hs3st3a1 in enamel knot and dental epithelial cells of developing mouse incisors. Furthermore, associated SNPs in PITX2 and HS3ST3A1 overlap enhancers active in these cells, suggesting a role for these SNPs in gene regulation during dental development. In addition, we document that Pitx2 and Hs3st3a1/Hs3st3b1 knockout mice show alterations in dental morphology. Finally, we find that associated SNPs in HS3ST3A1 are in a DNA tract introgressed from Neanderthals, consistent with an involvement of HS3ST3A1 in tooth size variation during human evolution.
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Affiliation(s)
- Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China; State Key Laboratory of Complex Severe and Rare Diseases, Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College, and Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing 100730, China
| | - Pierre Faux
- Aix-Marseille Université, CNRS, EFS, ADES, 27 Boulevard Jean Moulin, Marseille 13005, France; GenPhySE Université de Toulouse, INRAE, ENVT, 24 Chemin de Borde Rouge, 31326 Castanet Tolosan, France
| | - Emma Wentworth Winchester
- Department of Genetics and Genome Sciences, University of Connecticut Health, 400 Farmington Avenue, Farmington, CT 06030, USA
| | - Guangrui Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China; Exchange, Development & Service Center for Science & Technology Talents, Sanlihe Road, Beijing 100045, P.R. China
| | - Yingjie Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China
| | - Luis Miguel Ramírez
- Facultad de Odontología, Universidad de Antioquia, Calle 64 N.º 52-59 Of. 107. Apartado Postal 1226, Medellín, Colombia
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Avenida 18 de Septiembre 2222, Arica 1000000, Chile
| | - Lauriane Poloni
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon 21000, France; EPHE, PSL University, Paris 75014, France
| | - Emilie Steimetz
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon 21000, France
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, U9129ACD Puerto Madryn, Argentina
| | - Victor Acuña
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, México City 4510, México
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060 Porto Alegre, Brasil
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31 Lima, Perú
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31 Lima, Perú
| | | | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000 Medellín, Colombia
| | - Youyi Zheng
- State Key Lab of CAD&CG, Zhejiang University, Yuhangtang Road, Hangzhou 310058, China
| | - James C Cox
- Department of Oral and Craniofacial Sciences, School of Dentistry, University of Missouri, Kansas City, MO 64108, USA
| | - Vaishali Patel
- Matrix and Morphogenesis Section, NIDCR, NIH, DHHS, Bethesda, MD 20892, USA
| | - Matthew P Hoffman
- Matrix and Morphogenesis Section, NIDCR, NIH, DHHS, Bethesda, MD 20892, USA
| | - Li Ding
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China
| | - Chenchen Peng
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China
| | - Justin Cotney
- Department of Genetics and Genome Sciences, University of Connecticut Health, 400 Farmington Avenue, Farmington, CT 06030, USA
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon 21000, France; EPHE, PSL University, Paris 75014, France
| | - Timothy C Cox
- Department of Oral and Craniofacial Sciences, School of Dentistry, University of Missouri, Kansas City, MO 64108, USA; Department of Pediatrics, School of Medicine, University of Missouri, 400 N Keene St., Kansas City, MO 64108, USA
| | - Miguel Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China; División Antropología, Facultad de Ciencias Naturales y Museo, Paseo del Bosque s/n, Universidad Nacional de La Plata, La Plata 1900, República Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Godoy Cruz, 2290 Buenos Aires, República Argentina.
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong District, Shanghai 200433, China; Aix-Marseille Université, CNRS, EFS, ADES, 27 Boulevard Jean Moulin, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK.
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2
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Yuan M, Goovaerts S, Vanneste M, Matthews H, Hoskens H, Richmond S, Klein OD, Spritz RA, Hallgrimsson B, Walsh S, Shriver MD, Shaffer JR, Weinberg SM, Peeters H, Claes P. Mapping genes for human face shape: Exploration of univariate phenotyping strategies. PLoS Comput Biol 2024; 20:e1012617. [PMID: 39621772 DOI: 10.1371/journal.pcbi.1012617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 12/20/2024] [Accepted: 11/05/2024] [Indexed: 12/11/2024] Open
Abstract
Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits.
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Affiliation(s)
- Meng Yuan
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Michiel Vanneste
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Hanne Hoskens
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Cell Biology & Anatomy, Cumming School of Medicine, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Stephen Richmond
- Applied Clinical Research and Public Health, School of Dentistry, Cardiff University, Cardiff, United Kingdom
| | - Ophir D Klein
- Departments of Orofacial Sciences and Pediatrics, and Institute for Human Genetics, University of California, San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, Cedars-Sinai Guerin Children's, Los Angeles, California, United States of America
| | - Richard A Spritz
- Human Medical Genetics and Genomics Program, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Benedikt Hallgrimsson
- Department of Cell Biology & Anatomy, Cumming School of Medicine, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, Indiana, United States of America
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Hilde Peeters
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Peter Claes
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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3
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Tagore D, Akey JM. Archaic hominin admixture and its consequences for modern humans. Curr Opin Genet Dev 2024; 90:102280. [PMID: 39577372 DOI: 10.1016/j.gde.2024.102280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 10/18/2024] [Accepted: 10/22/2024] [Indexed: 11/24/2024]
Abstract
As anatomically modern humans dispersed out of Africa, they encountered and mated with now extinct hominins, including Neanderthals and Denisovans. It is now well established that all non-African individuals derive approximately 2% of their genome from Neanderthal ancestors and individuals of Melanesian and Australian aboriginal ancestry inherited an additional 2%-5% of their genomes from Denisovan ancestors. Attention has started to shift from documenting amounts of archaic admixture and identifying introgressed segments to understanding their molecular, phenotypic, and evolutionary consequences and refining models of human history. Here, we review recent insights into admixture between modern and archaic humans, emphasizing methodological innovations and the functional and phenotypic effects Neanderthal and Denisovan sequences have in contemporary individuals.
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Affiliation(s)
- Debashree Tagore
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton 08540, USA. https://twitter.com/@TagoreDebashree
| | - Joshua M Akey
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton 08540, USA.
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4
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Borda V, Loesch DP, Guo B, Laboulaye R, Veliz-Otani D, French JN, Leal TP, Gogarten SM, Ikpe S, Gouveia MH, Mendes M, Abecasis GR, Alvim I, Arboleda-Bustos CE, Arboleda G, Arboleda H, Barreto ML, Barwick L, Bezzera MA, Blangero J, Borges V, Caceres O, Cai J, Chana-Cuevas P, Chen Z, Custer B, Dean M, Dinardo C, Domingos I, Duggirala R, Dieguez E, Fernandez W, Ferraz HB, Gilliland F, Guio H, Horta B, Curran JE, Johnsen JM, Kaplan RC, Kelly S, Kenny EE, Konkle BA, Kooperberg C, Lescano A, Lima-Costa MF, Loos RJF, Manichaikul A, Meyers DA, Naslavsky MS, Nickerson DA, North KE, Padilla C, Preuss M, Raggio V, Reiner AP, Rich SS, Rieder CR, Rienstra M, Rotter JI, Rundek T, Sacco RL, Sanchez C, Sankaran VG, Santos-Lobato BL, Schumacher-Schuh AF, Scliar MO, Silverman EK, Sofer T, Lasky-Su J, Tumas V, Weiss ST, Mata IF, Hernandez RD, Tarazona-Santos E, O'Connor TD. Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas. CELL GENOMICS 2024; 4:100692. [PMID: 39486408 PMCID: PMC11605695 DOI: 10.1016/j.xgen.2024.100692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 08/14/2024] [Accepted: 10/09/2024] [Indexed: 11/04/2024]
Abstract
Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.
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Affiliation(s)
- Victor Borda
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; University of Maryland Institute for Health Computing, University of Maryland School of Medicine, North Bethesda, MD 20852, USA.
| | - Douglas P Loesch
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Bing Guo
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Roland Laboulaye
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Diego Veliz-Otani
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Jennifer N French
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Thiago Peixoto Leal
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, OH, USA
| | | | - Sunday Ikpe
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Marla Mendes
- Department of Genetics, Ecology, and Evolution, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Gonçalo R Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Isabela Alvim
- Department of Genetics, Ecology, and Evolution, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Carlos E Arboleda-Bustos
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogota, Colombia
| | - Gonzalo Arboleda
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogota, Colombia
| | - Humberto Arboleda
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogota, Colombia
| | - Mauricio L Barreto
- Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, BA 40110-040, Brazil
| | - Lucas Barwick
- LTRC Data Coordinating Center, The Emmes Company, Rockville, MD, USA
| | - Marcos A Bezzera
- Department of Genetics, Federal University of Pernambuco, Av. Prof. Moraes Rego, 1235, Recife, PE 50670-901, Brazil
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Vanderci Borges
- Movement Disorders Unit, Department of Neurology and Neurosurgery, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Omar Caceres
- Instituto Nacional de Salud, Lima, Peru; Facultad de Ciencias de la Salud, Universidad Científica del Sur, Lima, Peru
| | - Jianwen Cai
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Pedro Chana-Cuevas
- CETRAM, Facultad de Ciencias Médicas, Universidad de Santiago de Chile, Santiago, Chile
| | - Zhanghua Chen
- Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, CA, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, CA, USA
| | - Michael Dean
- Laboratory of Genomic Diversity, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, MD, USA
| | - Carla Dinardo
- Instituto de Medicina Tropical, University of São Paulo, São Paulo, Brazil
| | - Igor Domingos
- Department of Genetics, Federal University of Pernambuco, Av. Prof. Moraes Rego, 1235, Recife, PE 50670-901, Brazil
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Elena Dieguez
- Neurology Institute, Universidad de la República, Montevideo, Uruguay
| | - Willian Fernandez
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogota, Colombia
| | - Henrique B Ferraz
- Movement Disorders Unit, Department of Neurology and Neurosurgery, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Frank Gilliland
- Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, CA, USA
| | - Heinner Guio
- Instituto Nacional de Salud, Lima, Peru; INBIOMEDIC Research Center, Lima, Peru; Universidad de Huánuco, Huánuco, Peru
| | - Bernardo Horta
- Faculdade de Medicina, Departamento de Medicina Social, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Jill M Johnsen
- Bloodworks Northwest Research Institute, Seattle, WA, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Shannon Kelly
- Vitalant Research Institute, San Francisco, CA, USA; UCSF Benioff Children's Hospital, University of California, San Francisco, Oakland, CA, USA
| | - Eimear E Kenny
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara A Konkle
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Andres Lescano
- Neurology Institute, Universidad de la República, Montevideo, Uruguay
| | - M Fernanda Lima-Costa
- Instituto de Pesquisas René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, MG, Brazil
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Deborah A Meyers
- Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, AZ, USA
| | - Michel S Naslavsky
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, SP, Brazil
| | | | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Michael Preuss
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Victor Raggio
- Genetics Department, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Carlos R Rieder
- Departamento de Neurologia, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Tatjana Rundek
- Department of Neurology, Miller School of Medicine, and The Evelyn F. McKnight Brain Institute, University of Miami, Miami, FL, USA
| | - Ralph L Sacco
- Department of Neurology, Miller School of Medicine, and The Evelyn F. McKnight Brain Institute, University of Miami, Miami, FL, USA
| | | | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Artur Francisco Schumacher-Schuh
- Departamento de Farmacologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Serviço de Neurologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Marilia O Scliar
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, SP, Brazil
| | - Edwin K Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Vitor Tumas
- Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Scott T Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ignacio F Mata
- University of Maryland Institute for Health Computing, University of Maryland School of Medicine, North Bethesda, MD 20852, USA
| | - Ryan D Hernandez
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Eduardo Tarazona-Santos
- Department of Genetics, Ecology, and Evolution, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Facultad de Salud Pública y Administración. Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Timothy D O'Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Program in Health Equity and Population Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Program in Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
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5
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Lee D, Ban HJ, Hong KW, Lee JY, Cha S. High heritability of human facial traits reveals associations with CNTLN, BRCA1, and TMPRSS6 loci in Korean families. Heliyon 2024; 10:e39173. [PMID: 39640822 PMCID: PMC11620094 DOI: 10.1016/j.heliyon.2024.e39173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 10/08/2024] [Accepted: 10/08/2024] [Indexed: 12/07/2024] Open
Abstract
Facial features are determined by interactions between genetic and environmental factors. However, genes underlying facial similarities in individuals from the same family remain less explored. To identify genetic variants associated with heritable facial features, we investigated familial (parent-offspring) associations and estimated familial correlation and heritability using 39 facial measurements in 408 individuals from 117 Korean families. Facial trait heritability ranged from 0.124 to 0.669. Longitudinal facial growth-related traits were highly heritable, including distances from the nasion to right alare (h 2 = 0.668898), pogonion to midendocanthion (h 2 = 0.661557), subnasale to midendocanthion (h 2 = 0.656882), and morphological facial height (h 2 = 0. 654376). We identified the top three significant genome-wide associated variants in the eye, nose, and lip-jaw regions. CNTLN (rs10511632: beta = -0.02696, p = 1.146 × 10-9) and BRCA1 (rs397509305: beta = 0.02741, p = 7.17 × 10-9) loci were associated with distance from the nasion to the right alare. The TMPRSS6 (rs228913: beta = 0.05101, p = 3.68 × 10-9) locus was associated with the distance from the labiale superius to the pogonion and lower facial height. These associations were maintained in an independent unrelated population. In conclusion, we identified new gene variants associated with longitudinal facial morphology that may affect individual facial differences, which has important implications for clinical and forensic applications.
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Affiliation(s)
- Donghyun Lee
- Oneomics Co., Ltd., Bucheon-si, Gyeonggi-do, 14585, South Korea
| | - Hyo-Jeong Ban
- KM Data Division, Korea Institute of Oriental Medicine, Daejeon, 34054, South Korea
| | - Kyung-Won Hong
- Theragen Bio Co., Ltd., Seongnam-si, Gyeonggi-do, 13493, South Korea
| | - Jong Young Lee
- Oneomics Co., Ltd., Bucheon-si, Gyeonggi-do, 14585, South Korea
| | - Seongwon Cha
- KM Data Division, Korea Institute of Oriental Medicine, Daejeon, 34054, South Korea
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6
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Vicuña L. Genetic associations with disease in populations with Indigenous American ancestries. Genet Mol Biol 2024; 47Suppl 1:e20230024. [PMID: 39254840 PMCID: PMC11384980 DOI: 10.1590/1678-4685-gmb-2023-0024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 07/13/2024] [Indexed: 09/11/2024] Open
Abstract
The genetic architecture of complex diseases affecting populations with Indigenous American ancestries is poorly understood due to their underrepresentation in genomics studies. While most of the genetic diversity associated with disease trait variation is shared among worldwide populations, a fraction of this component is expected to be unique to each continental group, including Indigenous Americans. Here, I describe the current state of knowledge from genome-wide association studies on Indigenous populations, as well as non-Indigenous populations with partial Indigenous ancestries from the American continent, focusing on disease susceptibility and anthropometric traits. While some studies identified risk alleles unique to Indigenous populations, their effects on trait variation are mostly small. I suggest that the associations rendered by many inter-population studies are probably inflated due to the absence of socio-cultural-economic covariates in the association models. I encourage the inclusion of admixed individuals in future GWAS studies to control for inter-ancestry differences in environmental factors. I suggest that some complex diseases might have arisen as trade-off costs of adaptations to past evolutionary selective pressures. Finally, I discuss how expanding panels with Indigenous ancestries in GWAS studies is key to accurately assess genetic risk in populations from the American continent, thus decreasing global health disparities.
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Affiliation(s)
- Lucas Vicuña
- University of Chicago, Department of Medicine, Section of Genetic Medicine, Chicago, USA
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7
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Ishida Y, Matsushita M, Yoneshiro T, Saito M, Nakayama K. Association between thermogenic brown fat and genes under positive natural selection in circumpolar populations. J Physiol Anthropol 2024; 43:19. [PMID: 39160621 PMCID: PMC11331686 DOI: 10.1186/s40101-024-00368-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 08/11/2024] [Indexed: 08/21/2024] Open
Abstract
BACKGROUND Adaptation to cold was essential for human migration across Eurasia. Non-shivering thermogenesis through brown adipose tissue (BAT) participates in cold adaptation because some genes involved in the differentiation and function of BAT exhibit signatures of positive natural selection in populations at high latitudes. Whether these genes are associated with the inter-individual variability in BAT thermogenesis remains unclear. In this study, we evaluated the potential associations between BAT activity and single nucleotide polymorphisms (SNPs) in candidate gene regions in East Asian populations. METHODS BAT activity induced by mild cold exposure was measured in 399 healthy Japanese men and women using fluorodeoxyglucose-positron emission tomography and computed tomography (FDG-PET/CT). The capacity for cold-induced thermogenesis and fat oxidation was measured in 56 men. Association analyses with physiological traits were performed for 11 SNPs at six loci (LEPR, ANGPTL8, PLA2G2A, PLIN1, TBX15-WARS2, and FADS1) reported to be under positive natural selection. Associations found in the FDG-PET/CT population were further validated in 84 healthy East Asian men and women, in whom BAT activity was measured using infrared thermography. Associations between the SNP genotypes and BAT activity or other related traits were tested using multiple logistic and linear regression models. RESULTS Of the 11 putative adaptive alleles of the six genes, two intronic SNPs in LEPR (rs1022981 and rs12405556) tended to be associated with higher BAT activity. However, these did not survive multiple test comparisons. Associations with lower body fat percentage, plasma triglyceride, insulin, and HOMA-IR levels were observed in the FDG-PET/CT population (P < 0.05). Other loci, including TBX15-WARS2, which is speculated to mediate cold adaptation in Greenland Inuits, did not show significant differences in BAT thermogenesis. CONCLUSIONS Our results suggest a marginal but significant association between LEPR SNPs. However, robust supporting evidence was not established for the involvement of other loci under positive natural selection in cold adaptation through BAT thermogenesis in East Asian adults. Given the pleiotropic function of these genes, factors other than cold adaptation through BAT thermogenesis, such as diet adaptation, may contribute to positive natural selection at these loci.
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Affiliation(s)
- Yuka Ishida
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan
| | - Mami Matsushita
- Department of Nutrition, School of Nursing and Nutrition, Tenshi College, Sapporo, Hokkaido, 065-0013, Japan
| | - Takeshi Yoneshiro
- Division of Molecular Physiology and Metabolism, Tohoku University Graduate School of Medicine, Sendai, Miyagi, 980-8575, Japan
| | - Masayuki Saito
- Department of Nutrition, School of Nursing and Nutrition, Tenshi College, Sapporo, Hokkaido, 065-0013, Japan
- Laboratory of Biochemistry, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Hokkaido, 060-0818, Japan
| | - Kazuhiro Nakayama
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan.
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Alvarado K, Tang WJ, Watson CJ, Ahmed AR, Gomez AE, Donaka R, Amemiya C, Karasik D, Hsu YH, Kwon RY. Loss of cped1 does not affect bone and lean tissue in zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.10.601974. [PMID: 39026892 PMCID: PMC11257572 DOI: 10.1101/2024.07.10.601974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Human genetic studies have nominated Cadherin-like and PC-esterase Domain-containing 1 (CPED1) as a candidate target gene mediating bone mineral density (BMD) and fracture risk heritability. Recent efforts to define the role of CPED1 in bone in mouse and human models have revealed complex alternative splicing and inconsistent results arising from gene targeting, making its function in bone difficult to interpret. To better understand the role of CPED1 in adult bone mass and morphology, we conducted a comprehensive genetic and phenotypic analysis of cped1 in zebrafish, an emerging model for bone and mineral research. We analyzed two different cped1 mutant lines and performed deep phenotyping to characterize more than 200 measures of adult vertebral, craniofacial, and lean tissue morphology. We also examined alternative splicing of zebrafish cped1 and gene expression in various cell/tissue types. Our studies fail to support an essential role of cped1 in adult zebrafish bone. Specifically, homozygous mutants for both cped1 mutant alleles, which are expected to result in loss-of-function and impact all cped1 isoforms, exhibited no significant differences in the measures examined when compared to their respective wildtype controls, suggesting that cped1 does not significantly contribute to these traits. We identified sequence differences in critical residues of the catalytic triad between the zebrafish and mouse orthologs of CPED1, suggesting that differences in key residues, as well as distinct alternative splicing, could underlie different functions of CPED1 orthologs in the two species. Our studies fail to support a requirement of cped1 in zebrafish bone and lean tissue, adding to evidence that variants at 7q31.31 can act independently of CPED1 to influence BMD and fracture risk.
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Affiliation(s)
- Kurtis Alvarado
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - W. Joyce Tang
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Claire J. Watson
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Ali R. Ahmed
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Arianna Ericka Gomez
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | | | - Chris Amemiya
- Department of Molecular and Cell Biology and Quantitative and Systems Biology Program, University of California, Merced, CA, USA
| | - David Karasik
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
- Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Yi-Hsiang Hsu
- Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Ronald Young Kwon
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
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9
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Romero-Hidalgo S, Sagaceta-Mejía J, Villalobos-Comparán M, Tejero ME, Domínguez-Pérez M, Jacobo-Albavera L, Posadas-Sánchez R, Vargas-Alarcón G, Posadas-Romero C, Macías-Kauffer L, Vadillo-Ortega F, Contreras-Sieck MA, Acuña-Alonzo V, Barquera R, Macín G, Binia A, Guevara-Chávez JG, Sebastián-Medina L, Menjívar M, Canizales-Quinteros S, Carnevale A, Villarreal-Molina T. Selection scan in Native Americans of Mexico identifies FADS2 rs174616: Evidence of gene-diet interactions affecting lipid levels and Delta-6-desaturase activity. Heliyon 2024; 10:e35477. [PMID: 39166092 PMCID: PMC11334880 DOI: 10.1016/j.heliyon.2024.e35477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Accepted: 07/29/2024] [Indexed: 08/22/2024] Open
Abstract
Searching for positive selection signals across genomes has identified functional genetic variants responding to environmental change. In Native Americans of Mexico, we used the fixation index (Fst) and population branch statistic (PBS) to identify SNPs suggesting positive selection. The 103 most differentiated SNPs were tested for associations with metabolic traits, the most significant association was FADS2/rs174616 with body mass index (BMI). This variant lies within a linkage disequilibrium (LD) block independent of previously reported FADS selection signals and has not been clearly associated with metabolic phenotypes. We tested this variant in two independent cohorts with cardiometabolic data. In the Genetics of Atherosclerotic Disease (GEA) cohort, the derived allele (T) was associated with increased BMI, lower LDL-C levels and a decreased risk of subclinical atherosclerosis in women. Significant gene-diet interactions affected lipid, apolipoprotein and adiponectin levels with differences according to sex, involving mainly total and complex dietary carbohydrate%. In the Genotype-related Effects of PUFA trial, the derived allele was associated with lower Δ-6 desaturase activity and erythrocyte membrane dihomo-gamma-linolenic acid (DGLA) levels, and with increased Δ-5 desaturase activity and eicosapentaenoic acid levels. This variant interacted with dietary carbohydrate% affecting Δ-6 desaturase activity. Notably, the relationship of DGLA and other erythrocyte membrane LC-PUFA indices with HOMA-IR differed according to rs174616 genotype, which has implications regarding how these indices should be interpreted. In conclusion, this observational study identified rs174616 as a signal suggesting selection in an independent linkage disequilibrium block, was associated with cardiometabolic and erythrocyte measurements of LC-PUFA in two independent Mexican cohorts and showed significant gene-diet interactions.
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Affiliation(s)
- Sandra Romero-Hidalgo
- Departamento de Genómica Computacional, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Janine Sagaceta-Mejía
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | | | - María Elizabeth Tejero
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Mayra Domínguez-Pérez
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Leonor Jacobo-Albavera
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Rosalinda Posadas-Sánchez
- Departamento de Endocrinología, Instituto Nacional de Cardiología “Ignacio Chávez”, Mexico City, Mexico
| | - Gilberto Vargas-Alarcón
- Departmento de Biología Molecular y Dirección de Investigación, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City, Mexico
| | - Carlos Posadas-Romero
- Departamento de Endocrinología, Instituto Nacional de Cardiología “Ignacio Chávez”, Mexico City, Mexico
| | - Luis Macías-Kauffer
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química UNAM e Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Felipe Vadillo-Ortega
- Unidad de Vinculación de la Facultad de Medicina UNAM en el Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | | | - Víctor Acuña-Alonzo
- Laboratorio de Genética Molecular, Escuela Nacional de Antropología e Historia, Mexico City, Mexico
| | - Rodrigo Barquera
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology (MPI-EVA), Leipzig, Germany
- Anthropology (MPI-EVA), Leipzig, Germany
| | - Gastón Macín
- Escuela Nacional de Antropología e Historia, Mexico City, Mexico
| | - Aristea Binia
- Nestlé Institute of Health Sciences, Innovation Park, EPFL, Lausanne, Switzerland
| | - Jose Guadalupe Guevara-Chávez
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Leticia Sebastián-Medina
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Martha Menjívar
- Departamento de Biología, Facultad de Química UNAM, Mexico City and Unidad Académica de Ciencias y Tecnología, UNAM-Yucatán, Mérida, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química UNAM e Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Alessandra Carnevale
- Laboratorio de Enfermedades Mendelianas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Teresa Villarreal-Molina
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
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10
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Laugwitz L, Cheng F, Collins SC, Hustinx A, Navarro N, Welsch S, Cox H, Hsieh TC, Vijayananth A, Buchert R, Bender B, Efthymiou S, Murphy D, Zafar F, Rana N, Grasshoff U, Falb RJ, Grimmel M, Seibt A, Zheng W, Ghaedi H, Thirion M, Couette S, Azizimalamiri R, Sadeghian S, Galehdari H, Zamani M, Zeighami J, Sedaghat A, Ramshe SM, Zare A, Alipoor B, Klee D, Sturm M, Ossowski S, Houlden H, Riess O, Wieczorek D, Gavin R, Maroofian R, Krawitz P, Yalcin B, Distelmaier F, Haack TB. ZSCAN10 deficiency causes a neurodevelopmental disorder with characteristic oto-facial malformations. Brain 2024; 147:2471-2482. [PMID: 38386308 PMCID: PMC11224597 DOI: 10.1093/brain/awae058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 12/21/2023] [Accepted: 01/21/2024] [Indexed: 02/23/2024] Open
Abstract
Neurodevelopmental disorders are major indications for genetic referral and have been linked to more than 1500 loci including genes encoding transcriptional regulators. The dysfunction of transcription factors often results in characteristic syndromic presentations; however, at least half of these patients lack a genetic diagnosis. The implementation of machine learning approaches has the potential to aid in the identification of new disease genes and delineate associated phenotypes. Next generation sequencing was performed in seven affected individuals with neurodevelopmental delay and dysmorphic features. Clinical characterization included reanalysis of available neuroimaging datasets and 2D portrait image analysis with GestaltMatcher. The functional consequences of ZSCAN10 loss were modelled in mouse embryonic stem cells (mESCs), including a knockout and a representative ZSCAN10 protein truncating variant. These models were characterized by gene expression and western blot analyses, chromatin immunoprecipitation and quantitative PCR (ChIP-qPCR) and immunofluorescence staining. Zscan10 knockout mouse embryos were generated and phenotyped. We prioritized bi-allelic ZSCAN10 loss-of-function variants in seven affected individuals from five unrelated families as the underlying molecular cause. RNA-sequencing analyses in Zscan10-/- mESCs indicated dysregulation of genes related to stem cell pluripotency. In addition, we established in mESCs the loss-of-function mechanism for a representative human ZSCAN10 protein truncating variant by showing alteration of its expression levels and subcellular localization, interfering with its binding to DNA enhancer targets. Deep phenotyping revealed global developmental delay, facial asymmetry and malformations of the outer ear as consistent clinical features. Cerebral MRI showed dysplasia of the semicircular canals as an anatomical correlate of sensorineural hearing loss. Facial asymmetry was confirmed as a clinical feature by GestaltMatcher and was recapitulated in the Zscan10 mouse model along with inner and outer ear malformations. Our findings provide evidence of a novel syndromic neurodevelopmental disorder caused by bi-allelic loss-of-function variants in ZSCAN10.
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Affiliation(s)
- Lucia Laugwitz
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- Department of Neuropediatrics, Developmental Neurology and Social Pediatrics, University of Tübingen, Tübingen 72076, Germany
| | - Fubo Cheng
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
| | | | - Alexander Hustinx
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53127, Germany
| | - Nicolas Navarro
- Biogeosciences, UMR 6282 CNRS, EPHE, Université de Bourgogne, Dijon 2100, France
- EPHE, PSL University, Paris 75014, France
| | - Simon Welsch
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich-Heine-University, Düsseldorf 40225, Germany
| | - Helen Cox
- West Midlands Regional Clinical Genetics Service and Birmingham Health Partners, Birmingham Women’s and Children’s Hospitals NHS Foundation Trust, Birmingham B15 2TG, UK
| | - Tzung-Chien Hsieh
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53127, Germany
| | - Aswinkumar Vijayananth
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53127, Germany
| | - Rebecca Buchert
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
| | - Benjamin Bender
- Diagnostic and Interventional Neuroradiology, Radiologic Clinics, University of Tübingen, Tübingen 72076, Germany
| | - Stephanie Efthymiou
- Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - David Murphy
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Faisal Zafar
- Pediatric Neurology, Children’s Hospital, Multan 60000, Pakistan
| | - Nuzhat Rana
- Pediatric Neurology, Children’s Hospital, Multan 60000, Pakistan
| | - Ute Grasshoff
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- Center for Rare Disease, University of Tübingen, Tübingen 72072, Germany
| | - Ruth J Falb
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
| | - Mona Grimmel
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
| | - Annette Seibt
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich-Heine-University, Düsseldorf 40225, Germany
| | - Wenxu Zheng
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
| | - Hamid Ghaedi
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717443, Iran
| | - Marie Thirion
- Inserm UMR1231, Université de Bourgogne, Dijon Cedex 21070, France
| | - Sébastien Couette
- Biogeosciences, UMR 6282 CNRS, EPHE, Université de Bourgogne, Dijon 2100, France
- EPHE, PSL University, Paris 75014, France
| | - Reza Azizimalamiri
- Department of Pediatric Neurology, Golestan Medical, Educational, and Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
| | - Saeid Sadeghian
- Department of Pediatric Neurology, Golestan Medical, Educational, and Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
| | - Hamid Galehdari
- Department of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz 6135783151, Iran
| | - Mina Zamani
- Department of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz 6135783151, Iran
- Narges Medical Genetics and Prenatal Diagnosis Laboratory, Kianpars, Ahvaz 6155689467, Iran
| | - Jawaher Zeighami
- Narges Medical Genetics and Prenatal Diagnosis Laboratory, Kianpars, Ahvaz 6155689467, Iran
| | - Alireza Sedaghat
- Narges Medical Genetics and Prenatal Diagnosis Laboratory, Kianpars, Ahvaz 6155689467, Iran
- Diabetes Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
| | - Samira Molaei Ramshe
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717443, Iran
| | - Ali Zare
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717443, Iran
| | - Behnam Alipoor
- Department of Laboratory Sciences, Faculty of Paramedicine, Yasuj University of Medical Sciences, Yasuj 7591741417, Iran
| | - Dirk Klee
- Department of Pediatric Radiology, Medical Faculty, Institute of Radiology, Heinrich-Heine-University, Düsseldorf 40225, Germany
| | - Marc Sturm
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- Genomics England, Queen Mary University of London, London EC1M 6BQ, UK
| | - Stephan Ossowski
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen 72076, Germany
| | - Henry Houlden
- Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Olaf Riess
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- Center for Rare Disease, University of Tübingen, Tübingen 72072, Germany
| | - Dagmar Wieczorek
- Medical Faculty and University Hospital Düsseldorf, Institute of Human Genetics, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Ryan Gavin
- West Midlands Regional Genetics Laboratory, Central and South Genomic Laboratory Hub, Birmingham B15 2TG, UK
| | - Reza Maroofian
- Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Peter Krawitz
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53127, Germany
| | - Binnaz Yalcin
- Inserm UMR1231, Université de Bourgogne, Dijon Cedex 21070, France
| | - Felix Distelmaier
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, Heinrich-Heine-University, Düsseldorf 40225, Germany
| | - Tobias B Haack
- Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tübingen, 72076, Germany
- Center for Rare Disease, University of Tübingen, Tübingen 72072, Germany
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11
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Vacca F, Yalcin B, Ansar M. Exploring the pathological mechanisms underlying Cohen syndrome. Front Neurosci 2024; 18:1431400. [PMID: 39010945 PMCID: PMC11247020 DOI: 10.3389/fnins.2024.1431400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Accepted: 06/18/2024] [Indexed: 07/17/2024] Open
Abstract
Cohen Syndrome (CS) is a rare autosomal recessive disorder caused by biallelic mutations in the VPS13B gene. It is characterized by multiple clinical features, including acquired microcephaly, developmental delay, intellectual disability, neutropenia, and retinal degeneration. VPS13B is part of the bridge-like lipid transport (BLTP) protein family, which in mammals also includes VPS13A, -C, and -D. The proteins of this family are peripheral membrane proteins with different sub-cellular localization, but all share similar structural features and have been proposed to act as lipid transport proteins at organellar membrane contact sites. VPS13B is localized at the Golgi apparatus and is essential for the maintenance of organelle architecture. Here we present a review of the experimental data on the function of the protein at the cellular level, discussing the potential link with disease phenotype and review the studies on animal models recapitulating features of the human disease.
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Affiliation(s)
- Fabrizio Vacca
- Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile Des Aveugles, Lausanne, Switzerland
| | - Binnaz Yalcin
- Inserm UMR1231, Université de Bourgogne, Dijon, France
| | - Muhammad Ansar
- Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile Des Aveugles, Lausanne, Switzerland
- Advanced Molecular Genetics and Genomics Disease Research and Treatment Centre, Dow University of Health Sciences, Karachi, Pakistan
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12
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Yuan M, Goovaerts S, Vanneste M, Matthews H, Hoskens H, Richmond S, Klein OD, Spritz RA, Hallgrimsson B, Walsh S, Shriver MD, Shaffer JR, Weinberg SM, Peeters H, Claes P. Mapping genes for human face shape: exploration of univariate phenotyping strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597731. [PMID: 38895298 PMCID: PMC11185724 DOI: 10.1101/2024.06.06.597731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.
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13
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Wisetchat S, Stevens KA, Frost SR. Facial modeling and measurement based upon homologous topographical features. PLoS One 2024; 19:e0304561. [PMID: 38820264 PMCID: PMC11142440 DOI: 10.1371/journal.pone.0304561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 05/13/2024] [Indexed: 06/02/2024] Open
Abstract
Measurement of human faces is fundamental to many applications from recognition to genetic phenotyping. While anthropometric landmarks provide a conventional set of homologous measurement points, digital scans are increasingly used for facial measurement, despite the difficulties in establishing their homology. We introduce an alternative basis for facial measurement, which 1) provides a richer information density than discrete point measurements, 2) derives its homology from shared facial topography (ridges, folds, etc.), and 3) quantifies local morphological variation following the conventions and practices of anatomical description. A parametric model that permits matching a broad range of facial variation by the adjustment of 71 parameters is demonstrated by modeling a sample of 80 adult human faces. The surface of the parametric model can be adjusted to match each photogrammetric surface mesh generally to within 1 mm, demonstrating a novel and efficient means for facial shape encoding. We examine how well this scheme quantifies facial shape and variation with respect to geographic ancestry and sex. We compare this analysis with a more conventional, landmark-based geometric morphometric (GMM) study with 43 landmarks placed on the same set of scans. Our multivariate statistical analysis using the 71 attribute values separates geographic ancestry groups and sexes with a high degree of reliability, and these results are broadly similar to those from GMM, but with some key differences that we discuss. This approach is compared with conventional, non-parametric methods for the quantification of facial shape, including generality, information density, and the separation of size and shape. Potential uses for phenotypic and dysmorphology studies are also discussed.
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Affiliation(s)
- Sawitree Wisetchat
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
| | - Kent A. Stevens
- Department of Computer and Information Science, University of Oregon, Eugene, Oregon, United States of America
| | - Stephen R. Frost
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
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14
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Zeberg H, Jakobsson M, Pääbo S. The genetic changes that shaped Neandertals, Denisovans, and modern humans. Cell 2024; 187:1047-1058. [PMID: 38367615 DOI: 10.1016/j.cell.2023.12.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/20/2023] [Accepted: 12/20/2023] [Indexed: 02/19/2024]
Abstract
Modern human ancestors diverged from the ancestors of Neandertals and Denisovans about 600,000 years ago. Until about 40,000 years ago, these three groups existed in parallel, occasionally met, and exchanged genes. A critical question is why modern humans, and not the other two groups, survived, became numerous, and developed complex cultures. Here, we discuss genetic differences among the groups and some of their functional consequences. As more present-day genome sequences become available from diverse groups, we predict that very few, if any, differences will distinguish all modern humans from all Neandertals and Denisovans. We propose that the genetic basis of what constitutes a modern human is best thought of as a combination of genetic features, where perhaps none of them is present in each and every present-day individual.
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Affiliation(s)
- Hugo Zeberg
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany; Department of Physiology and Pharmacology, Karolinska Institutet, 17165 Stockholm, Sweden.
| | - Mattias Jakobsson
- Department of Organismal Biology, Uppsala University, 75236 Uppsala, Sweden
| | - Svante Pääbo
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany; Okinawa Institute of Science and Technology, Onnason 904-0495, Okinawa, Japan.
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15
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Peyrégne S, Slon V, Kelso J. More than a decade of genetic research on the Denisovans. Nat Rev Genet 2024; 25:83-103. [PMID: 37723347 DOI: 10.1038/s41576-023-00643-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 09/20/2023]
Abstract
Denisovans, a group of now extinct humans who lived in Eastern Eurasia in the Middle and Late Pleistocene, were first identified from DNA sequences just over a decade ago. Only ten fragmentary remains from two sites have been attributed to Denisovans based entirely on molecular information. Nevertheless, there has been great interest in using genetic data to understand Denisovans and their place in human history. From the reconstruction of a single high-quality genome, it has been possible to infer their population history, including events of admixture with other human groups. Additionally, the identification of Denisovan DNA in the genomes of present-day individuals has provided insights into the timing and routes of dispersal of ancient modern humans into Asia and Oceania, as well as the contributions of archaic DNA to the physiology of present-day people. In this Review, we synthesize more than a decade of research on Denisovans, reconcile controversies and summarize insights into their population history and phenotype. We also highlight how our growing knowledge about Denisovans has provided insights into our own evolutionary history.
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Affiliation(s)
- Stéphane Peyrégne
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany.
| | - Viviane Slon
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Anatomy and Anthropology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Dan David Center for Human Evolution and Biohistory Research, Tel Aviv University, Tel Aviv, Israel
| | - Janet Kelso
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany.
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16
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Wilderman A, D'haene E, Baetens M, Yankee TN, Winchester EW, Glidden N, Roets E, Van Dorpe J, Janssens S, Miller DE, Galey M, Brown KM, Stottmann RW, Vergult S, Weaver KN, Brugmann SA, Cox TC, Cotney J. A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development. Nat Commun 2024; 15:136. [PMID: 38167838 PMCID: PMC10762089 DOI: 10.1038/s41467-023-44506-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
Craniofacial abnormalities account for approximately one third of birth defects. The regulatory programs that build the face require precisely controlled spatiotemporal gene expression, achieved through tissue-specific enhancers. Clusters of coactivated enhancers and their target genes, known as superenhancers, are important in determining cell identity but have been largely unexplored in development. In this study we identified superenhancer regions unique to human embryonic craniofacial tissue. To demonstrate the importance of such regions in craniofacial development and disease, we focused on an ~600 kb noncoding region located between NPVF and NFE2L3. We identified long range interactions with this region in both human and mouse embryonic craniofacial tissue with the anterior portion of the HOXA gene cluster. Mice lacking this superenhancer exhibit perinatal lethality, and present with highly penetrant skull defects and orofacial clefts phenocopying Hoxa2-/- mice. Moreover, we identified two cases of de novo copy number changes of the superenhancer in humans both with severe craniofacial abnormalities. This evidence suggests we have identified a critical noncoding locus control region that specifically regulates anterior HOXA genes and copy number changes are pathogenic in human patients.
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Affiliation(s)
| | - Eva D'haene
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Machteld Baetens
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | | | - Emma Wentworth Winchester
- Graduate Program UConn Health, Farmington, CT, USA
- University of Connecticut School of Dental Medicine, Farmington, CT, USA
| | - Nicole Glidden
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Ellen Roets
- Department of Obstetrics, Women's Clinic, Ghent University Hospital, Ghent, Belgium
| | - Jo Van Dorpe
- Department of Pathology, Ghent University, Ghent University Hospital, Ghent, Belgium
| | - Sandra Janssens
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Danny E Miller
- Department of Pediatrics, Division of Genetic Medicine, University of Washington, Washington, WA, USA
- Seattle Children's Hospital, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
- Brotman Baty Institute of Precision Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Miranda Galey
- Department of Pediatrics, Division of Genetic Medicine, University of Washington, Washington, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Kari M Brown
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Rolf W Stottmann
- Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
- The Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University School of Medicine, Columbus, OH, USA
| | - Sarah Vergult
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - K Nicole Weaver
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Samantha A Brugmann
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Timothy C Cox
- Department of Oral & Craniofacial Sciences, University of Missouri Kansas City, Kansas City, MO, USA
- Department of Pediatrics, University of Missouri Kansas City, Kansas City, MO, USA
| | - Justin Cotney
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA.
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17
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Cho HW, Ban HJ, Jin HS, Cha S, Eom YB. A genome-wide association scan reveals novel loci for facial traits of Koreans. Genomics 2023; 115:110710. [PMID: 37734486 DOI: 10.1016/j.ygeno.2023.110710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/07/2023] [Accepted: 09/18/2023] [Indexed: 09/23/2023]
Abstract
DNA-based prediction of externally visible characteristics (EVC) with SNPs is one of the research areas of interest in the forensic field. Based on a previous study performing GWAS on facial traits in a Korean population, herein, we present results stemming from GWA analysis with KoreanChip and novel genetic loci satisfying genome-wide significant level. We discovered a total of 20 signals and 12 loci were found to have novel associations with facial traits, including six loci located in intergenic regions and six loci located at UBE2O, HECTD2, CCDC108, TPK1, FCN2, and FRMPD1. Additionally, we performed a polygenic score analysis for 33 distance-related traits in facial phenotyping and determined genetic relationships between facial traits and SNPs using the GCTA program. The results of the current study offer an understanding of how facial morphology is influenced by complex genetic structures and provide insights into forensic investigation and population genetics.
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Affiliation(s)
- Hye-Won Cho
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea
| | - Hyo-Jeong Ban
- Korea Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea
| | - Hyun-Seok Jin
- Department of Biomedical Laboratory Science, College of Life and Health Sciences, Hoseo University, Asan, Chungnam 31499, Republic of Korea
| | - Seongwon Cha
- Korea Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea.
| | - Yong-Bin Eom
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea; Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea.
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18
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Faux P, Ding L, Ramirez-Aristeguieta LM, Chacón-Duque JC, Comini M, Mendoza-Revilla J, Fuentes-Guajardo M, Jaramillo C, Arias W, Hurtado M, Villegas V, Granja V, Barquera R, Everardo-Martínez P, Quinto-Sánchez M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Poletti G, Gallo C, Rothhammer F, Rojas W, Schmid AB, Adhikari K, Bennett DL, Ruiz-Linares A. Neanderthal introgression in SCN9A impacts mechanical pain sensitivity. Commun Biol 2023; 6:958. [PMID: 37816865 PMCID: PMC10564861 DOI: 10.1038/s42003-023-05286-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 08/25/2023] [Indexed: 10/12/2023] Open
Abstract
The Nav1.7 voltage-gated sodium channel plays a key role in nociception. Three functional variants in the SCN9A gene (encoding M932L, V991L, and D1908G in Nav1.7), have recently been identified as stemming from Neanderthal introgression and to associate with pain symptomatology in UK BioBank data. In 1000 genomes data, these variants are absent in Europeans but common in Latin Americans. Analysing high-density genotype data from 7594 Latin Americans, we characterized Neanderthal introgression in SCN9A. We find that tracts of introgression occur on a Native American genomic background, have an average length of ~123 kb and overlap the M932L, V991L, and D1908G coding positions. Furthermore, we measured experimentally six pain thresholds in 1623 healthy Colombians. We found that Neanderthal ancestry in SCN9A is significantly associated with a lower mechanical pain threshold after sensitization with mustard oil and evidence of additivity of effects across Nav1.7 variants. Our findings support the reported association of Neanderthal Nav1.7 variants with clinical pain, define a specific sensory modality affected by archaic introgression in SCN9A and are consistent with independent effects of the Neanderthal variants on Nav1.7 function.
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Affiliation(s)
- Pierre Faux
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China
- UMR ADES, Aix-Marseille Université, CNRS, EFS, 13005, Marseille, France
- UMR GenPhySE, INRAE, INP, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France
| | - Li Ding
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China
| | | | - J Camilo Chacón-Duque
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, SE-10691, Stockholm, Sweden
- Department of Archaeology and Classical Studies, Stockholm University, SE-1069, Stockholm, Sweden
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Maddalena Comini
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015, Paris, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, 1000000, Arica, Chile
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), 07745, Jena, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Mirsha Quinto-Sánchez
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), 06320, Mexico City, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, 4510, Mexico City, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, 05508-090, São Paulo, SP, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, U9129ACD, Puerto Madryn, Argentina
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, U9129ACD, Puerto Madryn, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, 4510, Mexico City, Mexico
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Arica, Chile
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - Annina B Schmid
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK
| | - Kaustubh Adhikari
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, UK.
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
| | - David L Bennett
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China.
- UMR ADES, Aix-Marseille Université, CNRS, EFS, 13005, Marseille, France.
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
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19
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Montillot C, Skutunova E, Ayushma, Dubied M, Lahmar A, Nguyen S, Peerally B, Prin F, Duffourd Y, Thauvin-Robinet C, Duplomb L, Wang H, Ansar M, Faivre L, Navarro N, Minocha S, Collins SC, Yalcin B. Characterization of Vps13b-mutant mice reveals neuroanatomical and behavioral phenotypes with females less affected. Neurobiol Dis 2023; 185:106259. [PMID: 37573958 DOI: 10.1016/j.nbd.2023.106259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/26/2023] [Accepted: 08/11/2023] [Indexed: 08/15/2023] Open
Abstract
The vacuolar protein sorting-associated protein 13B (VPS13B) is a large and highly conserved protein. Disruption of VPS13B causes the autosomal recessive Cohen syndrome, a rare disorder characterized by microcephaly and intellectual disability among other features, including developmental delay, hypotonia, and friendly-personality. However, the underlying mechanisms by which VPS13B disruption leads to brain dysfunction still remain unexplained. To gain insights into the neuropathogenesis of Cohen syndrome, we systematically characterized brain changes in Vps13b-mutant mice and compared murine findings to 235 previously published and 17 new patients diagnosed with VPS13B-related Cohen syndrome. We showed that Vps13b is differentially expressed across brain regions with the highest expression in the cerebellum, the hippocampus and the cortex with postnatal peak. Half of the Vps13b-/- mice die during the first week of life. The remaining mice have a normal lifespan and display the core phenotypes of the human disease, including microcephaly, growth delay, hypotonia, altered memory, and enhanced sociability. Systematic 2D and 3D brain histo-morphological analyses reveal specific structural changes in the brain starting after birth. The dentate gyrus is the brain region with the most prominent reduction in size, while the motor cortex is specifically thinner in layer VI. The fornix, the fasciculus retroflexus, and the cingulate cortex remain unaffected. Interestingly, these neuroanatomical changes implicate an increase of neuronal death during infantile stages with no progression in adulthood suggesting that VPS13B promotes neuronal survival early in life. Importantly, whilst both sexes were affected, some neuroanatomical and behavioral phenotypes were less pronounced or even absent in females. We evaluate sex differences in Cohen patients and conclude that females are less affected both in mice and patients. Our findings provide new insights about the neurobiology of VPS13B and highlight previously unreported brain phenotypes while defining Cohen syndrome as a likely new entity of non-progressive infantile neurodegeneration.
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Affiliation(s)
- Charlotte Montillot
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Emilia Skutunova
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Ayushma
- Kusuma School of Biological Sciences, Indian Institute of Technology Delhi (IITD), Hauz Khas, New Delhi 110016, India
| | - Morgane Dubied
- Biogéosciences, UMR 6282 CNRS, EPHE, Université de Bourgogne, 21000 Dijon, France
| | - Adam Lahmar
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Sylvie Nguyen
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Benazir Peerally
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Fabrice Prin
- Crick Advanced Light Microscopy Facility, The Francis Crick Institute, London NW1 1AT, UK
| | - Yannis Duffourd
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France; Unité Fonctionnelle Innovation en Diagnostic génomique des maladies rares, FHU-TRANSLAD, Dijon University Hospital, 21000 Dijon, France
| | - Christel Thauvin-Robinet
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France; Unité Fonctionnelle Innovation en Diagnostic génomique des maladies rares, FHU-TRANSLAD, Dijon University Hospital, 21000 Dijon, France; Reference Center for Rare Diseases "Déficiences intellectuelles de causes rares", Dijon University Hospital, 21000 Dijon, France
| | - Laurence Duplomb
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Heng Wang
- DDC Clinic for Special Needs Children, Middlefield, OH 44062, USA
| | - Muhammad Ansar
- Jules Gonin Eye Hospital, University of Lausanne, CH-1015 Lausanne, Switzerland; Advanced Molecular Genetics and Genomics Disease Research and Treatment Centre, Dow University of Health Sciences, Karachi, Pakistan
| | - Laurence Faivre
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France; Reference Center for Rare Diseases "Anomalies du Développement et syndromes malformatifs", Dijon University Hospital, 21000 Dijon, France
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, EPHE, Université de Bourgogne, 21000 Dijon, France; EPHE, PSL University, Paris 75014, France
| | - Shilpi Minocha
- Kusuma School of Biological Sciences, Indian Institute of Technology Delhi (IITD), Hauz Khas, New Delhi 110016, India
| | - Stephan C Collins
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France
| | - Binnaz Yalcin
- Université de Bourgogne, 21000 Dijon, France; Inserm Unit 1231, 21000 Dijon, France.
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Yuan M, Goovaerts S, Hoskens H, Richmond S, Walsh S, Shriver MD, Shaffer JR, Marazita ML, Weinberg SM, Peeters H, Claes P. Data-driven trait heritability-based extraction of human facial phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.13.553129. [PMID: 37645810 PMCID: PMC10462092 DOI: 10.1101/2023.08.13.553129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.
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Yankee TN, Oh S, Winchester EW, Wilderman A, Robinson K, Gordon T, Rosenfeld JA, VanOudenhove J, Scott DA, Leslie EJ, Cotney J. Integrative analysis of transcriptome dynamics during human craniofacial development identifies candidate disease genes. Nat Commun 2023; 14:4623. [PMID: 37532691 PMCID: PMC10397224 DOI: 10.1038/s41467-023-40363-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/25/2023] [Indexed: 08/04/2023] Open
Abstract
Craniofacial disorders arise in early pregnancy and are one of the most common congenital defects. To fully understand how craniofacial disorders arise, it is essential to characterize gene expression during the patterning of the craniofacial region. To address this, we performed bulk and single-cell RNA-seq on human craniofacial tissue from 4-8 weeks post conception. Comparisons to dozens of other human tissues revealed 239 genes most strongly expressed during craniofacial development. Craniofacial-biased developmental enhancers were enriched +/- 400 kb surrounding these craniofacial-biased genes. Gene co-expression analysis revealed that regulatory hubs are enriched for known disease causing genes and are resistant to mutation in the normal healthy population. Combining transcriptomic and epigenomic data we identified 539 genes likely to contribute to craniofacial disorders. While most have not been previously implicated in craniofacial disorders, we demonstrate this set of genes has increased levels of de novo mutations in orofacial clefting patients warranting further study.
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Affiliation(s)
- Tara N Yankee
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Sungryong Oh
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | | | - Andrea Wilderman
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Kelsey Robinson
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Tia Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Baylor Genetics Laboratory, Houston, TX, 77021, USA
| | - Jennifer VanOudenhove
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | - Daryl A Scott
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Justin Cotney
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, 06269, USA.
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22
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Palominos MF, Muhl V, Richards EJ, Miller CT, Martin CH. Jaw size variation is associated with a novel craniofacial function for galanin receptor 2 in an adaptive radiation of pupfishes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.02.543513. [PMID: 37333213 PMCID: PMC10274624 DOI: 10.1101/2023.06.02.543513] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Understanding the genetic basis of novel adaptations in new species is a fundamental question in biology that also provides an opportunity to uncover new genes and regulatory networks with potential clinical relevance. Here we demonstrate a new role for galr2 in vertebrate craniofacial development using an adaptive radiation of trophic specialist pupfishes endemic to San Salvador Island in the Bahamas. We confirmed the loss of a putative Sry transcription factor binding site in the upstream region of galr2 in scale-eating pupfish and found significant spatial differences in galr2 expression among pupfish species in Meckel's cartilage and premaxilla using in situ hybridization chain reaction (HCR). We then experimentally demonstrated a novel function for Galr2 in craniofacial development and jaw elongation by exposing embryos to drugs that inhibit Galr2 activity. Galr2-inhibition reduced Meckel's cartilage length and increased chondrocyte density in both trophic specialists but not in the generalist genetic background. We propose a mechanism for jaw elongation in scale-eaters based on the reduced expression of galr2 due to the loss of a putative Sry binding site. Fewer Galr2 receptors in the scale-eater Meckel's cartilage may result in their enlarged jaw lengths as adults by limiting opportunities for a postulated Galr2 agonist to bind to these receptors during development. Our findings illustrate the growing utility of linking candidate adaptive SNPs in non-model systems with highly divergent phenotypes to novel vertebrate gene functions.
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Affiliation(s)
- M Fernanda Palominos
- Department of Integrative Biology, University of California, Berkeley
- Museum of Vertebrate Zoology, University of California, Berkeley
| | - Vanessa Muhl
- Department of Integrative Biology, University of California, Berkeley
- Museum of Vertebrate Zoology, University of California, Berkeley
| | - Emilie J Richards
- Department of Ecology, Evolution, and Behavior, University of Minnesota
| | - Craig T Miller
- Department of Molecular & Cell Biology, University of California, Berkeley
| | - Christopher H Martin
- Department of Integrative Biology, University of California, Berkeley
- Museum of Vertebrate Zoology, University of California, Berkeley
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23
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Li Q, Chen J, Faux P, Delgado ME, Bonfante B, Fuentes-Guajardo M, Mendoza-Revilla J, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Barquera R, Everardo-Martínez P, Sánchez-Quinto M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Wu S, Du S, Giardina A, Paria SS, Khokan MR, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Rojas W, Rothhammer F, Navarro N, Wang S, Adhikari K, Ruiz-Linares A. Automatic landmarking identifies new loci associated with face morphology and implicates Neanderthal introgression in human nasal shape. Commun Biol 2023; 6:481. [PMID: 37156940 PMCID: PMC10167347 DOI: 10.1038/s42003-023-04838-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
We report a genome-wide association study of facial features in >6000 Latin Americans based on automatic landmarking of 2D portraits and testing for association with inter-landmark distances. We detected significant associations (P-value <5 × 10-8) at 42 genome regions, nine of which have been previously reported. In follow-up analyses, 26 of the 33 novel regions replicate in East Asians, Europeans, or Africans, and one mouse homologous region influences craniofacial morphology in mice. The novel region in 1q32.3 shows introgression from Neanderthals and we find that the introgressed tract increases nasal height (consistent with the differentiation between Neanderthals and modern humans). Novel regions include candidate genes and genome regulatory elements previously implicated in craniofacial development, and show preferential transcription in cranial neural crest cells. The automated approach used here should simplify the collection of large study samples from across the world, facilitating a cosmopolitan characterization of the genetics of facial features.
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Affiliation(s)
- Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
| | - Jieyi Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Pierre Faux
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Miguel Eduardo Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, República Argentina
| | - Betty Bonfante
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - J Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Mirsha Sánchez-Quinto
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), Mexico City, 06320, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Sijie Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrea Giardina
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Soumya Subhra Paria
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Mahfuzur Rahman Khokan
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Arica, 1000000, Chile
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon, 21000, France
- EPHE, PSL University, Paris, 75014, France
| | - Sijia Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China.
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
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24
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Kayser M, Branicki W, Parson W, Phillips C. Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age. Forensic Sci Int Genet 2023; 65:102870. [PMID: 37084623 DOI: 10.1016/j.fsigen.2023.102870] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023]
Abstract
Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.
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Affiliation(s)
- Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland,; Institute of Forensic Research, Kraków, Poland
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
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25
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Cheng H, Zhang Z, Wen J, Lenstra JA, Heller R, Cai Y, Guo Y, Li M, Li R, Li W, He S, Wang J, Shao J, Song Y, Zhang L, Billah M, Wang X, Liu M, Jiang Y. Long divergent haplotypes introgressed from wild sheep are associated with distinct morphological and adaptive characteristics in domestic sheep. PLoS Genet 2023; 19:e1010615. [PMID: 36821549 PMCID: PMC9949681 DOI: 10.1371/journal.pgen.1010615] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 01/13/2023] [Indexed: 02/24/2023] Open
Abstract
The worldwide sheep population comprises more than 1000 breeds. Together, these exhibit a considerable morphological diversity, which has not been extensively investigated at the molecular level. Here, we analyze whole-genome sequencing individuals of 1,098 domestic sheep from 154 breeds, and 69 wild sheep from seven Ovis species. On average, we detected 6.8%, 1.0% and 0.2% introgressed sequence in domestic sheep originating from Iranian mouflon, urial and argali, respectively, with rare introgressions from other wild species. Interestingly, several introgressed haplotypes contributed to the morphological differentiations across sheep breeds, such as a RXFP2 haplotype from Iranian mouflon conferring the spiral horn trait, a MSRB3 haplotype from argali strongly associated with ear morphology, and a VPS13B haplotype probably originating from urial and mouflon possibly associated with facial traits. Our results reveal that introgression events from wild Ovis species contributed to the high rate of morphological differentiation in sheep breeds, but also to individual variation within breeds. We propose that long divergent haplotypes are a ubiquitous source of phenotypic variation that allows adaptation to a variable environment, and that these remain intact in the receiving population probably due to reduced recombination.
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Affiliation(s)
- Hong Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhuangbiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Jiayue Wen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Johannes A. Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yingwei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Wenrong Li
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Sangang He
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Jintao Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Junjie Shao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yuxuan Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Lei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Masum Billah
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Mingjun Liu
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
- * E-mail: (ML); (YJ)
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- * E-mail: (ML); (YJ)
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26
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Fabi SG, Hernandez C, Montes JR, Cotofana S, Dayan S. Aesthetic considerations when treating the Latin American patient: Thriving in diversity international roundtable series. J Cosmet Dermatol 2023; 22:593-602. [PMID: 36468194 DOI: 10.1111/jocd.15516] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/10/2022] [Accepted: 11/03/2022] [Indexed: 12/07/2022]
Abstract
BACKGROUND The Hispanic/Latin American population is the fastest growing non-Caucasian group in the United States. Within this group, demand for aesthetic procedures is on the rise. High ethnic variability among these patients influences treatment approaches and patient priorities. Understanding these ethnic differences is central to providing optimal care. AIMS To discuss similarities and differences in anatomy and treatment preferences of Hispanic/Latin American patients both within the United States and internationally and explore how these differences may influence or inform aesthetic practices. PATIENTS/METHODS In support of clinicians who wish to serve a diverse patient population, a 6-part, international roundtable series focused on diversity in aesthetics was conducted from August 24, 2021 to May 16, 2022. In this roundtable, held in Medellin, Columbia, expert clinicians from across Latin America and the United States were invited to contribute and share best practices. RESULTS The results of the second roundtable in the series, the Latin American Patient, are described here. A special emphasis is placed on procedures that address the most commonly encountered concerns in these patients. CONCLUSIONS Hispanic and Latino patients represent a broad demographic with unique anatomical features, aesthetic preferences, and treatment priorities. Clinicians should consider these differences when treating this patient population.
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Affiliation(s)
| | | | - José Raúl Montes
- Ophthalmology Department, University of Puerto Rico School of Medicine, San Juan, Puerto Rico.,Jose Raul Montes Eyes & Facial Rejuvenation, San Juan, Puerto Rico
| | | | - Steve Dayan
- Division of Facial Plastic and Reconstructive Surgery, Department of Otolaryngology, University of Illinois at Chicago, Chicago, Illinois, USA
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27
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Advancement in Human Face Prediction Using DNA. Genes (Basel) 2023; 14:genes14010136. [PMID: 36672878 PMCID: PMC9858985 DOI: 10.3390/genes14010136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/15/2022] [Accepted: 12/21/2022] [Indexed: 01/05/2023] Open
Abstract
The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.
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28
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Xiong Z, Gao X, Chen Y, Feng Z, Pan S, Lu H, Uitterlinden AG, Nijsten T, Ikram A, Rivadeneira F, Ghanbari M, Wang Y, Kayser M, Liu F. Combining genome-wide association studies highlight novel loci involved in human facial variation. Nat Commun 2022; 13:7832. [PMID: 36539420 PMCID: PMC9767941 DOI: 10.1038/s41467-022-35328-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance.
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Affiliation(s)
- Ziyi Xiong
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xingjian Gao
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China ,grid.440259.e0000 0001 0115 7868National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing, Jiangsu China
| | - Yan Chen
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhanying Feng
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Siyu Pan
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Haojie Lu
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andre G. Uitterlinden
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tamar Nijsten
- grid.5645.2000000040459992XDepartment of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Arfan Ikram
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Yong Wang
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Manfred Kayser
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fan Liu
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
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29
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Winchester EW, Hardy A, Cotney J. Integration of multimodal data in the developing tooth reveals candidate regulatory loci driving human odontogenic phenotypes. FRONTIERS IN DENTAL MEDICINE 2022; 3:1009264. [PMID: 37034481 PMCID: PMC10078798 DOI: 10.3389/fdmed.2022.1009264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Human odontogenic aberrations such as abnormal tooth number and delayed tooth eruption can occur as a symptom of rare syndromes or, more commonly, as nonsyndromic phenotypes. These phenotypes can require extensive and expensive dental treatment, posing a significant burden. While many dental phenotypes are heritable, most nonsyndromic cases have not been linked to causal genes. We demonstrate the novel finding that common sequence variants associated with human odontogenic phenotypes are enriched in developmental craniofacial enhancers conserved between human and mouse. However, the bulk nature of these samples obscures if this finding is due to the tooth itself or the surrounding tissues. We therefore sought to identify enhancers specifically active in the tooth anlagen and quantify their contribution to the observed genetic enrichments. We systematically identified 22,001 conserved enhancers active in E13.5 mouse incisors using ChIP-seq and machine learning pipelines and demonstrated biologically relevant enrichments in putative target genes, transcription factor binding motifs, and in vivo activity. Multi-tissue comparisons of human and mouse enhancers revealed that these putative tooth enhancers had the strongest enrichment of odontogenic phenotype-associated variants, suggesting a role for dysregulation of tooth developmental enhancers in human dental phenotypes. The large number of these regions genome-wide necessitated prioritization of enhancer loci for future investigations. As enhancers modulate gene expression, we prioritized regions based on enhancers' putative target genes. We predicted these target genes and prioritized loci by integrating chromatin state, bulk gene expression and coexpression, GWAS variants, and cell type resolved gene expression to generate a prioritized list of putative odontogenic phenotype-driving loci active in the developing tooth. These genomic regions are of particular interest for downstream experiments determining the role of specific dental enhancer:gene pairs in odontogenesis.
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Affiliation(s)
| | - Alexis Hardy
- Master of Genetics Program, Paris Diderot University,
Paris, France
| | - Justin Cotney
- Department of Genetics and Genome Sciences, University of
Connecticut School of Medicine, Farmington, CT, United States
- Institute for Systems Genomics, University of Connecticut,
Storrs, CT, United States
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30
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Naqvi S, Hoskens H, Wilke F, Weinberg SM, Shaffer JR, Walsh S, Shriver MD, Wysocka J, Claes P. Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology. Annu Rev Genomics Hum Genet 2022; 23:383-412. [PMID: 35483406 PMCID: PMC9482780 DOI: 10.1146/annurev-genom-120121-102607] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Variations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.
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Affiliation(s)
- Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, USA; ,
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Hanne Hoskens
- Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium; ,
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Franziska Wilke
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA; ,
| | - Seth M Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; ,
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - John R Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; ,
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Susan Walsh
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA; ,
| | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, Pennsylvania, USA;
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, USA; ,
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Peter Claes
- Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium; ,
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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31
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Cha MY, Hong YJ, Choi JE, Kwon TS, Kim IJ, Hong KW. Classification of early age facial growth pattern and identification of the genetic basis in two Korean populations. Sci Rep 2022; 12:13828. [PMID: 35970861 PMCID: PMC9378761 DOI: 10.1038/s41598-022-18127-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/05/2022] [Indexed: 11/11/2022] Open
Abstract
Childhood to adolescence is an accelerated growth period, and genetic features can influence differences of individual growth patterns. In this study, we examined the genetic basis of early age facial growth (EAFG) patterns. Facial shape phenotypes were defined using facial landmark distances, identifying five growth patterns: continued-decrease, decrease-to-increase, constant, increase-to-decrease, and continued-increase. We conducted genome-wide association studies (GWAS) for 10 horizontal and 11 vertical phenotypes. The most significant association for horizontal phenotypes was rs610831 (TRIM29; β = 0.92, p-value = 1.9 × 10−9) and for vertical phenotypes was rs6898746 (ZSWIM6; β = 0.1103, p-value = 2.5 × 10−8). It is highly correlated with genes already reported for facial growth. This study is the first to classify and characterize facial growth patterns and related genetic polymorphisms.
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Affiliation(s)
- Mi-Yeon Cha
- Theragen Bio Co., Ltd., 240 Pangyoyeok-ro, Seongnam-si, Gyeonggi-do, 13493, Republic of Korea
| | - Yu-Jin Hong
- Center for Imaging Media Research, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
| | - Ja-Eun Choi
- Theragen Bio Co., Ltd., 240 Pangyoyeok-ro, Seongnam-si, Gyeonggi-do, 13493, Republic of Korea
| | - Tae-Song Kwon
- Human ICT CO., Ltd., 111, Dogok-ro, Gangnam-gu, Seoul, 06253, Republic of Korea
| | - Ig-Jae Kim
- Center for Imaging Media Research, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
| | - Kyung-Won Hong
- Theragen Bio Co., Ltd., 240 Pangyoyeok-ro, Seongnam-si, Gyeonggi-do, 13493, Republic of Korea.
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32
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Zhang M, Wu S, Du S, Qian W, Chen J, Qiao L, Yang Y, Tan J, Yuan Z, Peng Q, Liu Y, Navarro N, Tang K, Ruiz-Linares A, Wang J, Claes P, Jin L, Li J, Wang S. Genetic variants underlying differences in facial morphology in East Asian and European populations. Nat Genet 2022; 54:403-411. [PMID: 35393595 DOI: 10.1038/s41588-022-01038-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 01/19/2022] [Accepted: 02/25/2022] [Indexed: 11/09/2022]
Abstract
Facial morphology-a conspicuous feature of human appearance-is highly heritable. Previous studies on the genetic basis of facial morphology were performed mainly in European-ancestry cohorts (EUR). Applying a data-driven phenotyping and multivariate genome-wide scanning protocol to a large collection of three-dimensional facial images of individuals with East Asian ancestry (EAS), we identified 244 variants in 166 loci (62 new) associated with typical-range facial variation. A newly proposed polygenic shape analysis indicates that the effects of the variants on facial shape in EAS can be generalized to EUR. Based on this, we further identified 13 variants related to differences between facial shape in EUR and EAS populations. Evolutionary analyses suggest that the difference in nose shape between EUR and EAS populations is caused by a directional selection, due mainly to a local adaptation in Europeans. Our results illustrate the underlying genetic basis for facial differences across populations.
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Affiliation(s)
- Manfei Zhang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Computer Science, Fudan University, Shanghai, China
| | - Sijie Wu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wei Qian
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Computer Science, Fudan University, Shanghai, China
| | - Jieyi Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Lu Qiao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS-EPHE, Université Bourgogne Franche-Comté, Dijon, France.,Ecole Pratique des Hautes Etudes, PSL University, Paris, France
| | - Kun Tang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Andrés Ruiz-Linares
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Aix-Marseille Université, CNRS, EFS, ADES, Marseille, France.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, UK
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,Fudan-Taizhou Institute of Health Sciences, Taizhou, China
| | - Peter Claes
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.,Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.,Department of Human Genetics, KU Leuven, Leuven, Belgium.,Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. .,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Fudan-Taizhou Institute of Health Sciences, Taizhou, China.
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium. .,Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
| | - Sijia Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. .,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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33
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Qian W, Zhang M, Wan K, Xie Y, Du S, Li J, Mu X, Qiu J, Xue X, Zhuang X, Wu Y, Liu F, Wang S. Genetic evidence for facial variation being a composite phenotype of cranial variation and facial soft tissue thickness. J Genet Genomics 2022; 49:934-942. [DOI: 10.1016/j.jgg.2022.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/17/2022] [Accepted: 02/20/2022] [Indexed: 10/18/2022]
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34
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Qian Y, Xiong Z, Li Y, Kayser M, Liu L, Liu F. The effects of Tbx15 and Pax1 on facial and other physical morphology in mice. FASEB Bioadv 2021; 3:1011-1019. [PMID: 34938962 PMCID: PMC8664010 DOI: 10.1096/fba.2021-00094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 12/13/2022] Open
Abstract
DNA variants in or close to the human TBX15 and PAX1 genes have been repeatedly associated with facial morphology in independent genome-wide association studies, while their functional roles in determining facial morphology remain to be understood. We generated Tbx15 knockout (Tbx15 -/-) and Pax1 knockout (Pax1 -/-) mice by applying the one-step CRISPR/Cas9 method. A total of 75 adult mice were used for subsequent phenotype analysis, including 38 Tbx15 mice (10 homozygous Tbx15 -/-, 18 heterozygous Tbx15 +/-, 10 wild-type Tbx15 +/+ WT littermates) and 37 Pax1 mice (12 homozygous Pax1 -/-, 15 heterozygous Pax1 +/-, 10 Pax1 +/+ WT littermates). Facial and other physical morphological phenotypes were obtained from three-dimensional (3D) images acquired with the HandySCAN BLACK scanner. Compared to WT littermates, the Tbx15 -/- mutant mice had significantly shorter faces (p = 1.08E-8, R2 = 0.61) and their ears were in a significantly lower position (p = 3.54E-8, R2 = 0.62) manifesting a "droopy ear" characteristic. Besides these face alternations, Tbx15 -/- mutant mice displayed significantly lower weight as well as shorter body and limb length. Pax1 -/- mutant mice showed significantly longer noses (p = 1.14E-5, R2 = 0.46) relative to WT littermates, but otherwise displayed less obvious morphological alterations than Tbx15 -/- mutant mice did. We provide the first direct functional evidence that two well-known and replicated human face genes, Tbx15 and Pax1, impact facial and other body morphology in mice. The general agreement between our findings in knock-out mice with those from previous GWASs suggests that the functional evidence we established here in mice may also be relevant in humans.
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Affiliation(s)
- Yu Qian
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Ziyi Xiong
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Yi Li
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Manfred Kayser
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Lei Liu
- Department of Plastic and Burn SurgeryThe Second HospitalCheeloo College of MedicineShandong UniversityJinanChina
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
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35
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Suvorov A, Scornavacca C, Fujimoto MS, Bodily P, Clement M, Crandall KA, Whiting MF, Schrider DR, Bybee SM. Deep ancestral introgression shapes evolutionary history of dragonflies and damselflies. Syst Biol 2021; 71:526-546. [PMID: 34324671 PMCID: PMC9017697 DOI: 10.1093/sysbio/syab063] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 07/20/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
Introgression is an important biological process affecting at least 10% of the extant species in the animal kingdom. Introgression significantly impacts inference of phylogenetic species relationships where a strictly binary tree model cannot adequately explain reticulate net-like species relationships. Here we use phylogenomic approaches to understand patterns of introgression along the evolutionary history of a unique, non-model insect system: dragonflies and damselflies (Odonata). We demonstrate that introgression is a pervasive evolutionary force across various taxonomic levels within Odonata. In particular, we show that the morphologically "intermediate" species of Anisozygoptera (one of the three primary suborders within Odonata besides Zygoptera and Anisoptera), which retain phenotypic characteristics of the other two suborders, experienced high levels of introgression likely coming from zygopteran genomes. Additionally, we find evidence for multiple cases of deep inter-superfamilial ancestral introgression.
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Affiliation(s)
- Anton Suvorov
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Celine Scornavacca
- Institut des Sciences de l'Evolution Université de Montpellier, CNRS, IRD, EPHE CC 064, Place Eugène Bataillon, 34095 Montpellier Cedex 05, France
| | - M Stanley Fujimoto
- Department of Computer Science, Brigham Young University, Provo, UT, United States
| | - Paul Bodily
- Department of Computer Science, Idaho State University, Pocatello, ID, United States
| | - Mark Clement
- Department of Computer Science, Brigham Young University, Provo, UT, United States
| | - Keith A Crandall
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC, United States
| | - Michael F Whiting
- Department of Biology, Brigham Young University, Provo, UT, United States.,M.L. Bean Museum, Brigham Young University, Provo, UT, United States
| | - Daniel R Schrider
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Seth M Bybee
- Department of Biology, Brigham Young University, Provo, UT, United States.,M.L. Bean Museum, Brigham Young University, Provo, UT, United States
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36
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37
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Bu D, Wang X, Tang H. Haplotype-based membership inference from summary genomic data. Bioinformatics 2021; 37:i161-i168. [PMID: 34252973 PMCID: PMC8275351 DOI: 10.1093/bioinformatics/btab305] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Motivation The availability of human genomic data, together with the enhanced capacity to process them, is leading to transformative technological advances in biomedical science and engineering. However, the public dissemination of such data has been difficult due to privacy concerns. Specifically, it has been shown that the presence of a human subject in a case group can be inferred from the shared summary statistics of the group, e.g. the allele frequencies, or even the presence/absence of genetic variants (e.g. shared by the Beacon project) in the group. These methods rely on the availability of the target’s genome, i.e. the DNA profile of a target human subject, and thus are often referred to as the membership inference method. Results In this article, we demonstrate the haplotypes, i.e. the sequence of single nucleotide variations (SNVs) showing strong genetic linkages in human genome databases, may be inferred from the summary of genomic data without using a target’s genome. Furthermore, novel haplotypes that did not appear in the database may be reconstructed solely from the allele frequencies from genomic datasets. These reconstructed haplotypes can be used for a haplotype-based membership inference algorithm to identify target subjects in a case group with greater power than existing methods based on SNVs. Availability and implementation The implementation of the membership inference algorithms is available at https://github.com/diybu/Haplotype-based-membership-inferences.
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Affiliation(s)
- Diyue Bu
- Department of Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Xiaofeng Wang
- Department of Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Haixu Tang
- Department of Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
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Chen Y, André M, Adhikari K, Blin M, Bonfante B, Mendoza-Revilla J, Fuentes-Guajardo M, Palmal S, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Lozano RB, Everardo-Martínez P, Gómez-Valdés J, Villamil-Ramírez H, de Cerqueira CCS, Hünemeier T, Ramallo V, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Balding D, Tobin DJ, Wang S, Faux P, Ruiz-Linares A. A genome-wide association study identifies novel gene associations with facial skin wrinkling and mole count in Latin Americans. Br J Dermatol 2021; 185:988-998. [PMID: 33959940 DOI: 10.1111/bjd.20436] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified genes influencing skin ageing and mole count in Europeans, but little is known about the relevance of these (or other genes) in non-Europeans. OBJECTIVES To conduct a GWAS for facial skin ageing and mole count in adults < 40 years old, of mixed European, Native American and African ancestry, recruited in Latin America. METHODS Skin ageing and mole count scores were obtained from facial photographs of over 6000 individuals. After quality control checks, three wrinkling traits and mole count were retained for genetic analyses. DNA samples were genotyped with Illumina's HumanOmniExpress chip. Association testing was performed on around 8 703 729 single-nucleotide polymorphisms (SNPs) across the autosomal genome. RESULTS Genome-wide significant association was observed at four genome regions: two were associated with wrinkling (in 1p13·3 and 21q21·2), one with mole count (in 1q32·3) and one with both wrinkling and mole count (in 5p13·2). Associated SNPs in 5p13·2 and in 1p13·3 are intronic within SLC45A2 and VAV3, respectively, while SNPs in 1q32·3 are near the SLC30A1 gene, and those in 21q21·2 occur in a gene desert. Analyses of SNPs in IRF4 and MC1R are consistent with a role of these genes in skin ageing. CONCLUSIONS We replicate the association of wrinkling with variants in SLC45A2, IRF4 and MC1R reported in Europeans. We identify VAV3 and SLC30A1 as two novel candidate genes impacting on wrinkling and mole count, respectively. We provide the first evidence that SLC45A2 influences mole count, in addition to variants in this gene affecting melanoma risk in Europeans.
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Affiliation(s)
- Y Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China
| | - M André
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - K Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, UK.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
| | - M Blin
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - B Bonfante
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú.,Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - M Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - S Palmal
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J C Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - M Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - C Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - W Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - R B Lozano
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico.,Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - P Everardo-Martínez
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - J Gómez-Valdés
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - H Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | | | - T Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - V Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil.,Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - R Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - L Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - M-C Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - V Acuña-Alonzo
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - S Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | - C Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - F Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Chile
| | - D Balding
- Melbourne Integrative Genomics, Schools of BioSciences and Mathematics & Statistics, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - D J Tobin
- The Charles Institute of Dermatology, University College Dublin, Dublin, Ireland
| | - S Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Shanghai, 200031, China
| | - P Faux
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - A Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China.,UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
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