1
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. Nat Genet 2025:10.1038/s41588-024-02051-8. [PMID: 39779957 DOI: 10.1038/s41588-024-02051-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/04/2024] [Indexed: 01/11/2025]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution and diversity but have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies (from 85 samples representing 38 Africans and 47 non-Africans) in which the majority of autosomal SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms and sex chromosomes, we identify 173.2 Mb of duplicated sequence (47.4 Mb not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable, with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy numbers than non-African samples. Comparison to a resource of 563 million full-length isoform sequencing reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children's Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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2
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Adele R, Hussein R, Tavares E, Ahmed K, Di Scipio M, Charish J, Liang M, Monis S, Tumber A, Chen X, Paton TA, Roslin NM, Eileen C, Ivakine E, Sunny NE, Wilson MD, Campos E, Rajala RV, Maynes JT, Monnier PP, Paterson AD, Héon E, Vincent A. Autosomal-dominant macular dystrophy linked to a chromosome 17 tandem duplication. JCI Insight 2024; 9:e178768. [PMID: 39436697 PMCID: PMC11623951 DOI: 10.1172/jci.insight.178768] [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: 12/21/2023] [Accepted: 10/11/2024] [Indexed: 10/25/2024] Open
Abstract
Hereditary macular dystrophies (HMDs) are a genetically diverse group of disorders that cause central vision loss due to photoreceptor and retinal pigment epithelium (RPE) damage. We investigated a family with a presumed novel autosomal-dominant HMD characterized by faint, hypopigmented RPE changes involving the central retina. Genome and RNA sequencing identified the disease-causing variant to be a 560 kb tandem duplication on chromosome 17 [NC_000017.10 (hg19): g.4012590_4573014dup], which led to the formation of a novel ZZEF1-ALOX15 fusion gene, which upregulates ALOX15. ALOX15 encodes a lipoxygenase involved in polyunsaturated fatty acid metabolism. Functional studies showed retinal disorganization and photoreceptor and RPE damage following electroporation of the chimera transcript in mouse retina. Photoreceptor damage also occurred following electroporation with a native ALOX15 transcript but not with a near-null ALOX15 transcript. Affected patients' lymphoblasts demonstrated lower levels of ALOX15 substrates and an accumulation of neutral lipids. We implicated the fusion gene as the cause of this family's HMD, due to mislocalization and overexpression of ALOX15, driven by the ZZEF1 promoter. To our knowledge, this is the first reported instance of a fusion gene leading to HMD or inherited retinal dystrophy, highlighting the need to prioritize duplication analysis in unsolved retinal dystrophies.
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Affiliation(s)
- Rabiat Adele
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Rowaida Hussein
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Erika Tavares
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Kashif Ahmed
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Matteo Di Scipio
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Jason Charish
- Vision Division, Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Minggao Liang
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto (U of T), Toronto, Ontario, Canada
| | - Simon Monis
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto (U of T), Toronto, Ontario, Canada
| | | | - Xiaoyan Chen
- Vision Division, Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Tara A. Paton
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
- The Centre for Applied Genomics, HSC, Toronto, Ontario, Canada
| | - Nicole M. Roslin
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Christabel Eileen
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Evgueni Ivakine
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Nishanth E. Sunny
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland, USA
| | - Michael D. Wilson
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Eric Campos
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Raju V.S. Rajala
- Departments of Ophthalmology, Physiology, and Cell Biology and Dean McGee Eye Institute, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Jason T. Maynes
- Molecular Medicine program and
- Department of Anesthesia and Pain Medicine, HSC, Toronto, Ontario, Canada
| | - Philippe P. Monnier
- Vision Division, Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
- Department of Physiology, Faculty of Medicine, and
| | - Andrew D. Paterson
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
| | - Elise Héon
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
- Department of Ophthalmology and Visual Sciences and
- Department of Ophthalmology and Visual Sciences, U of T, Toronto, Ontario, Canada
| | - Ajoy Vincent
- Genetics & Genome Biology program, Hospital for Sick Children (HSC), Toronto, Ontario, Canada
- Department of Ophthalmology and Visual Sciences and
- Department of Ophthalmology and Visual Sciences, U of T, Toronto, Ontario, Canada
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3
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Sasako T, Ilboudo Y, Liang KYH, Chen Y, Yoshiji S, Richards JB. The Influence of Trinucleotide Repeats in the Androgen Receptor Gene on Androgen-related Traits and Diseases. J Clin Endocrinol Metab 2024; 109:3234-3244. [PMID: 38701087 PMCID: PMC11570371 DOI: 10.1210/clinem/dgae302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/05/2024]
Abstract
CONTEXT Trinucleotide repeats in the androgen receptor have been proposed to influence testosterone signaling in men, but the clinical relevance of these trinucleotide repeats remains controversial. OBJECTIVE To examine how androgen receptor trinucleotide repeat lengths affect androgen-related traits and disease risks and whether they influence the clinical importance of circulating testosterone levels. METHODS We quantified CAG and GGC repeat lengths in the androgen receptor (AR) gene of European-ancestry male participants in the UK Biobank from whole-genome and whole-exome sequence data using ExpansionHunter and tested associations with androgen-related traits and diseases. We also examined whether the associations between testosterone levels and these outcomes were affected by adjustment for the repeat lengths. RESULTS We successfully quantified the repeat lengths from whole-genome and/or whole-exome sequence data in 181 217 males. Both repeat lengths were shown to be positively associated with circulating total testosterone level and bone mineral density, whereas CAG repeat length was negatively associated with male-pattern baldness, but their effects were relatively small and were not associated with most of the other outcomes. Circulating total testosterone level was associated with various outcomes, but this relationship was not affected by adjustment for the repeat lengths. CONCLUSION In this large-scale study, we found that longer CAG and GGC repeats in the AR gene influence androgen resistance, elevate circulating testosterone level via a feedback loop, and play a role in some androgen-targeted tissues. Generally, however, circulating testosterone level is a more important determinant of androgen action in males than repeat lengths.
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Affiliation(s)
- Takayoshi Sasako
- McGill University, Montréal, Québec H3T 1E2, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Tanaka Diabetes Clinic Omiya, Saitama 330-0846, Japan
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo 113-0033, Japan
| | - Yann Ilboudo
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Kevin Y H Liang
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Quantitative Life Sciences Program, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Yiheng Chen
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Human Genetics, McGill University, Montréal, Québec H3T 1E2, Canada
| | - Satoshi Yoshiji
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Human Genetics, McGill University, Montréal, Québec H3T 1E2, Canada
- Kyoto-McGill International Collaborative Program in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Human Genetics, McGill University, Montréal, Québec H3T 1E2, Canada
- Five Prime Sciences Inc, Montréal, Québec H3Y 2W4, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec H3T 1E2, Canada
- Department of Twin Research, King's College London, London WC2R 2LS, UK
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4
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Harris L, McDonagh EM, Zhang X, Fawcett K, Foreman A, Daneck P, Sergouniotis PI, Parkinson H, Mazzarotto F, Inouye M, Hollox EJ, Birney E, Fitzgerald T. Genome-wide association testing beyond SNPs. Nat Rev Genet 2024:10.1038/s41576-024-00778-y. [PMID: 39375560 DOI: 10.1038/s41576-024-00778-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2024] [Indexed: 10/09/2024]
Abstract
Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.
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Affiliation(s)
- Laura Harris
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Ellen M McDonagh
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Xiaolei Zhang
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Katherine Fawcett
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Amy Foreman
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Petr Daneck
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Panagiotis I Sergouniotis
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Helen Parkinson
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Francesco Mazzarotto
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Michael Inouye
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Edward J Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Ewan Birney
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK
| | - Tomas Fitzgerald
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, UK.
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5
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Grimes K, Jeong H, Amoah A, Xu N, Niemann J, Raeder B, Hasenfeld P, Stober C, Rausch T, Benito E, Jann JC, Nowak D, Emini R, Hoenicka M, Liebold A, Ho A, Shuai S, Geiger H, Sanders AD, Korbel JO. Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells. Nat Genet 2024; 56:1134-1146. [PMID: 38806714 PMCID: PMC11176070 DOI: 10.1038/s41588-024-01754-2] [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: 07/03/2023] [Accepted: 04/17/2024] [Indexed: 05/30/2024]
Abstract
The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.
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Affiliation(s)
- Karen Grimes
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Hyobin Jeong
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Systems Biology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea
| | - Amanda Amoah
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Nuo Xu
- Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Julian Niemann
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Benjamin Raeder
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Patrick Hasenfeld
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Catherine Stober
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Tobias Rausch
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
- Bridging Research Division on Mechanisms of Genomic Variation and Data Science, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eva Benito
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Johann-Christoph Jann
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Mannheim, Germany
| | - Daniel Nowak
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Mannheim, Germany
| | - Ramiz Emini
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Markus Hoenicka
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Andreas Liebold
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Anthony Ho
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
- Department of Medicine V, Hematology, Oncology and Rheumatology, University of Heidelberg, Heidelberg, Germany
| | - Shimin Shuai
- Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Hartmut Geiger
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
- Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Charité-Universitätsmedizin Berlin, Berlin, Germany.
| | - Jan O Korbel
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.
- Bridging Research Division on Mechanisms of Genomic Variation and Data Science, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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6
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Hujoel MLA, Handsaker RE, Sherman MA, Kamitaki N, Barton AR, Mukamel RE, Terao C, McCarroll SA, Loh PR. Protein-altering variants at copy number-variable regions influence diverse human phenotypes. Nat Genet 2024; 56:569-578. [PMID: 38548989 PMCID: PMC11018521 DOI: 10.1038/s41588-024-01684-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: 06/23/2023] [Accepted: 02/08/2024] [Indexed: 04/09/2024]
Abstract
Copy number variants (CNVs) are among the largest genetic variants, yet CNVs have not been effectively ascertained in most genetic association studies. Here we ascertained protein-altering CNVs from UK Biobank whole-exome sequencing data (n = 468,570) using haplotype-informed methods capable of detecting subexonic CNVs and variation within segmental duplications. Incorporating CNVs into analyses of rare variants predicted to cause gene loss of function (LOF) identified 100 associations of predicted LOF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 conferred one of the strongest protective effects of gene LOF on hypertension risk (odds ratio = 0.86 (0.82-0.90)). Protein-coding variation in rapidly evolving gene families within segmental duplications-previously invisible to most analysis methods-generated some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
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Affiliation(s)
- Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Serinus Biosciences Inc., New York, NY, USA
| | - Nolan Kamitaki
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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7
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Yeo NKW, Lim CK, Yaung KN, Khoo NKH, Arkachaisri T, Albani S, Yeo JG. Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus. Front Genet 2024; 15:1341272. [PMID: 38501057 PMCID: PMC10944961 DOI: 10.3389/fgene.2024.1341272] [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: 11/20/2023] [Accepted: 02/20/2024] [Indexed: 03/20/2024] Open
Abstract
Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.
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Affiliation(s)
- Nicholas Kim-Wah Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Che Kang Lim
- Duke-NUS Medical School, Singapore, Singapore
- Department of Clinical Translation Research, Singapore General Hospital, Singapore, Singapore
| | - Katherine Nay Yaung
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Nicholas Kim Huat Khoo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
| | - Thaschawee Arkachaisri
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Salvatore Albani
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Joo Guan Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women’s and Children’s Hospital, Singapore, Singapore
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8
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Auwerx C, Jõeloo M, Sadler MC, Tesio N, Ojavee S, Clark CJ, Mägi R, Reymond A, Kutalik Z. Rare copy-number variants as modulators of common disease susceptibility. Genome Med 2024; 16:5. [PMID: 38185688 PMCID: PMC10773105 DOI: 10.1186/s13073-023-01265-5] [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: 07/17/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. METHODS Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. RESULTS We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. CONCLUSIONS Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
| | - Maarja Jõeloo
- Institute of Molecular and Cell Biology, University of Tartu, 51010, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland
| | - Nicolò Tesio
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Sven Ojavee
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Charlie J Clark
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
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9
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Saadat M. Enrichment analysis and chromosomal distribution of gout susceptible loci identified by genome-wide association studies. EXCLI JOURNAL 2023; 22:1146-1154. [PMID: 38204969 PMCID: PMC10776878 DOI: 10.17179/excli2023-6481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/06/2023] [Indexed: 01/12/2024]
Abstract
Gout is an inherited and common inflammatory arthritic disease. Many researchers will identify polymorphic loci of gout susceptibility by conducting genome-wide association studies (GWAS). In the present study, the enrichment analysis and chromosomal distribution were performed using predicted polymorphic loci associated with gout risk. The polymorphic loci associated to gout were obtained from the GWAS database. Overall, this database contains 64,806 gout patients and 2,856,174 controls. Gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using the Enrichr online server. A total of 110 common polymorphic protein-coding loci associated with gout risk were identified and included in the analysis. The results of the KEGG analysis showed that the gout-associated loci were mainly related to ABC transporters, endocrine and other factor-regulated calcium reabsorption, and gastric acid secretion pathways. The gene ontology analysis showed that the biological processes of the gout-associated loci were vascular transport, transport across the blood-brain barrier, positive regulation of transporter activity, and positive regulation of transcription by RNA polymerase II. The top cellular component was the external side of the apical plasma membrane. Statistical analysis revealed that the human chromosome segments 1q22, 4p16.1, 6p21.1-p21.2, 11q13.1-q13.2, 12q13.11-q13.3, and 12q24.1 had significantly bearing higher numbers of gout susceptibility loci.
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Affiliation(s)
- Mostafa Saadat
- Department of Biology, School of Science, Shiraz University, Shiraz 71467-13565, Iran
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10
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Høgdall EVS, Christensen IJ, Høgdall C. Are we ready for translational research based on material and data from the Danish CancerBiobank and can we gain new knowledge from biobank registration? APMIS 2023; 131:536-542. [PMID: 37653613 DOI: 10.1111/apm.13348] [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: 07/10/2023] [Accepted: 08/10/2023] [Indexed: 09/02/2023]
Abstract
Bio-and GenomeBank, Denmark (RBGB) is a nationwide infra-structure. Danish CancerBiobank (DCB) is a biobank in RBGB. The aim is to describe the degree of biological material collected and stored in DCB for patients diagnosed with primary ovarian cancer registered in The Danish Gynecologic Cancer Database (DGCD). Furthermore, to investigate the concordance between predicted organ of disease registered in RBGB at time of sampling (presumed diagnosis) with final diagnosis for patient. Data extraction from DGCD and DCB. Biological materials are present for 1.347 (62%) of 2.172 patients with primary ovarian cancer (OC). The median age of OC patients were 68 years (range: 18-90 years). Median age of patients with biological material in DCB was 67 years and for patients without biological material in DCB 69 years (p ≤ 0.0001). The histological subtypes for the 1347 OC patients with biological material were 911 (68%) serous adenocarcinoma, 97 (7%) endometrioid adenocarcinoma, 80 (6%) mucinous adenocarcinoma, 58 (4%) clear cell carcinoma, and for 201 (15%) no information were registered. For 327 patients (24%), the presumed diagnosis was hematological with a final diagnosis of OC. Using clinical data and biological material including pre-analytical data regarding the biological material the possibility for translational research is optimal. Furthermore, information registered through daily working procedures may propose the need for additional biomarkers to aid clinicians to stratify patients to treatment in correct fast-track packages.
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Affiliation(s)
- Estrid V S Høgdall
- Molecular Unit, Department of Pathology, Bio- and GenomeBank Denmark, Herlev Hospital, Copenhagen University, Herlev, Denmark
| | - Ib Jarle Christensen
- Molecular Unit, Department of Pathology, Bio- and GenomeBank Denmark, Herlev Hospital, Copenhagen University, Herlev, Denmark
| | - Claus Høgdall
- Department of Gynecology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
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11
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Babadi M, Fu JM, Lee SK, Smirnov AN, Gauthier LD, Walker M, Benjamin DI, Zhao X, Karczewski KJ, Wong I, Collins RL, Sanchis-Juan A, Brand H, Banks E, Talkowski ME. GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data. Nat Genet 2023; 55:1589-1597. [PMID: 37604963 PMCID: PMC10904014 DOI: 10.1038/s41588-023-01449-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/16/2023] [Indexed: 08/23/2023]
Abstract
Copy number variants (CNVs) are major contributors to genetic diversity and disease. While standardized methods, such as the genome analysis toolkit (GATK), exist for detecting short variants, technical challenges have confounded uniform large-scale CNV analyses from whole-exome sequencing (WES) data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, we developed GATK-gCNV, a flexible algorithm to discover rare CNVs from sequencing read-depth information, complete with open-source distribution via GATK. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data, finding up to 95% recall of rare coding CNVs at a resolution of more than two exons. We used GATK-gCNV to generate a reference catalog of rare coding CNVs in WES data from 197,306 individuals in the UK Biobank, and observed strong correlations between per-gene CNV rates and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in WES data, with broad applications.
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Affiliation(s)
- Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Jack M Fu
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Samuel K Lee
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrey N Smirnov
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura D Gauthier
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Walker
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - David I Benjamin
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xuefang Zhao
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Konrad J Karczewski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Isaac Wong
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ryan L Collins
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alba Sanchis-Juan
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Harrison Brand
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric Banks
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael E Talkowski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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12
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Hujoel ML, Handsaker RE, Sherman MA, Kamitaki N, Barton AR, Mukamel RE, Terao C, McCarroll SA, Loh PR. Hidden protein-altering variants influence diverse human phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544066. [PMID: 37333244 PMCID: PMC10274781 DOI: 10.1101/2023.06.07.544066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82-0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications-previously invisible to most analysis methods-appeared to generate some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
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Affiliation(s)
- Margaux L.A. Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert E. Handsaker
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Maxwell A. Sherman
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nolan Kamitaki
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Alison R. Barton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ronen E. Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Steven A. McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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13
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Lovšin N. Copy Number Variation and Osteoporosis. Curr Osteoporos Rep 2023; 21:167-172. [PMID: 36795294 PMCID: PMC10105686 DOI: 10.1007/s11914-023-00773-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2022] [Indexed: 02/17/2023]
Abstract
PURPOSE OF REVIEW The purpose of this review is to summarize recent findings on copy number variations and susceptibility to osteoporosis. RECENT FINDINGS Osteoporosis is highly influenced by genetic factors, including copy number variations (CNVs). The development and accessibility of whole genome sequencing methods has accelerated the study of CNVs and osteoporosis. Recent findings include mutations in novel genes and validation of previously known pathogenic CNVs in monogenic skeletal diseases. Identification of CNVs in genes previously associated with osteoporosis (e.g. RUNX2, COL1A2, and PLS3) has confirmed their importance in bone remodelling. This process has been associated also with the ETV1-DGKB, AGBL2, ATM, and GPR68 genes, identified by comparative genomic hybridisation microarray studies. Importantly, studies in patients with bone pathologies have associated bone disease with the long non-coding RNA LINC01260 and enhancer sequences residing in the HDAC9 gene. Further functional investigation of genetic loci harbouring CNVs associated with skeletal phenotypes will reveal their role as molecular drivers of osteoporosis.
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Affiliation(s)
- Nika Lovšin
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva 7, 1000, Ljubljana, Slovenia.
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14
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Sollis E, Mosaku A, Abid A, Buniello A, Cerezo M, Gil L, Groza T, Güneş O, Hall P, Hayhurst J, Ibrahim A, Ji Y, John S, Lewis E, MacArthur JL, McMahon A, Osumi-Sutherland D, Panoutsopoulou K, Pendlington Z, Ramachandran S, Stefancsik R, Stewart J, Whetzel P, Wilson R, Hindorff L, Cunningham F, Lambert S, Inouye M, Parkinson H, Harris L. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res 2023; 51:D977-D985. [PMID: 36350656 PMCID: PMC9825413 DOI: 10.1093/nar/gkac1010] [Citation(s) in RCA: 634] [Impact Index Per Article: 317.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/13/2022] [Accepted: 10/20/2022] [Indexed: 11/11/2022] Open
Abstract
The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.
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Affiliation(s)
- Elliot Sollis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Abayomi Mosaku
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ala Abid
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Annalisa Buniello
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Maria Cerezo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Laurent Gil
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Tudor Groza
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Osman Güneş
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Peggy Hall
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - James Hayhurst
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Arwa Ibrahim
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Yue Ji
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sajo John
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Elizabeth Lewis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jacqueline A L MacArthur
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Aoife McMahon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - David Osumi-Sutherland
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kalliope Panoutsopoulou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Zoë Pendlington
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Santhi Ramachandran
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ray Stefancsik
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jonathan Stewart
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Patricia Whetzel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Robert Wilson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Samuel A Lambert
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Laura W Harris
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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15
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Association between copy number variations in the OCA2-HERC2 locus and human eye colour. FORENSIC SCIENCE INTERNATIONAL GENETICS SUPPLEMENT SERIES 2022. [DOI: 10.1016/j.fsigss.2022.09.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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