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Uyenoyama MK. Joint identity among loci under mutation and regular inbreeding. Theor Popul Biol 2024; 159:74-90. [PMID: 39208993 DOI: 10.1016/j.tpb.2024.08.002] [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: 06/27/2023] [Revised: 08/09/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024]
Abstract
This study describes a compact method for determining joint probabilities of identity-by-state (IBS) within and between loci in populations evolving under genetic drift, crossing-over, mutation, and regular inbreeding (partial self-fertilization). Analogues of classical indices of associations among loci arise as functions of these joint identities. This coalescence-based analysis indicates that multi-locus associations reflect simultaneous coalescence events across loci. Measures of association depend on genetic diversity rather than allelic frequencies, as do linkage disequilibrium and its relatives. Scaled indices designed to show monotonic dependence on rates of crossing-over, inbreeding, and mutation may prove useful for interpreting patterns of genome-scale variation.
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Affiliation(s)
- Marcy K Uyenoyama
- Department of Biology, Duke University, Box 90338, Durham, NC 27708-0338, USA.
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2
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Senthivel V, Jolly B, Vr A, Bajaj A, Bhoyar R, Imran M, Vignesh H, Divakar MK, Sharma G, Rai N, Kumar K, Mp J, Krishna M, Shenthar J, Ali M, Abqari S, Nadri G, Scaria V, Naik N, Sivasubbu S. Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing. J Hum Genet 2024; 69:455-465. [PMID: 38890497 DOI: 10.1038/s10038-024-01265-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 03/07/2024] [Accepted: 06/02/2024] [Indexed: 06/20/2024]
Abstract
Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.
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Affiliation(s)
- Vigneshwar Senthivel
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Bani Jolly
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Arvinden Vr
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Anjali Bajaj
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Rahul Bhoyar
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
| | - Mohamed Imran
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Harie Vignesh
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
| | - Mohit Kumar Divakar
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Gautam Sharma
- Department of Cardiology, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Nitin Rai
- Department of Cardiology, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Kapil Kumar
- Department of Cardiology, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Jayakrishnan Mp
- Government Medical College, Kozhikode, Kerala, 673008, India
| | - Maniram Krishna
- Tiny Hearts Fetal and Pediatric Clinic, Thanjavur, Tamil Nadu, 613001, India
| | - Jeyaprakash Shenthar
- Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, 560069, India
| | - Muzaffar Ali
- Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, 560069, India
| | - Shaad Abqari
- Jawaharlal Nehru Medical College and Hospital, Aligarh Muslim University, Aligarh, Uttar Pradesh, 202002, India
| | - Gulnaz Nadri
- Jawaharlal Nehru Medical College and Hospital, Aligarh Muslim University, Aligarh, Uttar Pradesh, 202002, India
| | - Vinod Scaria
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Nitish Naik
- Department of Cardiology, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Sridhar Sivasubbu
- CSIR- Institute of Genomics and Integrative Biology, Mathura Road, Sukhdev Vihar, New Delhi, 110025, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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Mikhaylova V, Rzepka M, Kawamura T, Xia Y, Chang PL, Zhou S, Paasch A, Pham L, Modi N, Yao L, Perez-Agustin A, Pagans S, Boles TC, Lei M, Wang Y, Garcia-Bassets I, Chen Z. Targeted phasing of 2-200 kilobase DNA fragments with a short-read sequencer and a single-tube linked-read library method. Sci Rep 2024; 14:7988. [PMID: 38580715 PMCID: PMC10997766 DOI: 10.1038/s41598-024-58733-0] [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: 08/15/2023] [Accepted: 04/02/2024] [Indexed: 04/07/2024] Open
Abstract
In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.
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Affiliation(s)
| | - Madison Rzepka
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | | | - Yu Xia
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Peter L Chang
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | | | - Amber Paasch
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Long Pham
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Naisarg Modi
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA
| | - Likun Yao
- Department of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Adrian Perez-Agustin
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | - Sara Pagans
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | | | - Ming Lei
- Universal Sequencing Technology Corp., Canton, MA, 02021, USA
| | - Yong Wang
- Universal Sequencing Technology Corp., Canton, MA, 02021, USA
| | | | - Zhoutao Chen
- Universal Sequencing Technology Corp., Carlsbad, CA, 92011, USA.
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Mallick S, Micco A, Mah M, Ringbauer H, Lazaridis I, Olalde I, Patterson N, Reich D. The Allen Ancient DNA Resource (AADR) a curated compendium of ancient human genomes. Sci Data 2024; 11:182. [PMID: 38341426 PMCID: PMC10858950 DOI: 10.1038/s41597-024-03031-7] [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: 08/10/2023] [Accepted: 01/31/2024] [Indexed: 02/12/2024] Open
Abstract
More than two hundred papers have reported genome-wide data from ancient humans. While the raw data for the vast majority are fully publicly available testifying to the commitment of the paleogenomics community to open data, formats for both raw data and meta-data differ. There is thus a need for uniform curation and a centralized, version-controlled compendium that researchers can download, analyze, and reference. Since 2019, we have been maintaining the Allen Ancient DNA Resource (AADR), which aims to provide an up-to-date, curated version of the world's published ancient human DNA data, represented at more than a million single nucleotide polymorphisms (SNPs) at which almost all ancient individuals have been assayed. The AADR has gone through six public releases at the time of writing and review of this manuscript, and crossed the threshold of >10,000 individuals with published genome-wide ancient DNA data at the end of 2022. This note is intended as a citable descriptor of the AADR.
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Affiliation(s)
- Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Howard Hughes Medical Institute, Boston, MA, 02115, USA.
| | - Adam Micco
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Boston, MA, 02115, USA
| | - Matthew Mah
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Boston, MA, 02115, USA
| | - Harald Ringbauer
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
| | - Iosif Lazaridis
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Iñigo Olalde
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA
- BIOMICs Research Group, University of the Basque Country, 01006, Vitoria-Gasteiz, Spain
| | - Nick Patterson
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - David Reich
- Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Howard Hughes Medical Institute, Boston, MA, 02115, USA.
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA.
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Perini JA, Basta PC, Suarez-Kurtz G. NUDT15 and TPMT polymorphisms in three distinct native populations of the Brazilian Amazon. Front Pharmacol 2024; 15:1359570. [PMID: 38379902 PMCID: PMC10876798 DOI: 10.3389/fphar.2024.1359570] [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: 12/21/2023] [Accepted: 01/18/2024] [Indexed: 02/22/2024] Open
Abstract
This is the first report of the distribution of TPMT and NUDT15 single nucleotide polymorphisms and metabolic phenotypes associated with cytotoxicity of thiopurine drugs, in indigenous groups of Brazilian Amazon: Munduruku, Paiter-Suruí and Yanomami. The minor allele frequency (MAF) of NUDT15 rs116855232 did not differ significantly across the groups; TPMT rs1800462 was absent, while rs1800460 and rs1142345 were in strong linkage disequilibrium, and 10- and 30-fold more common in Paiter-Suruí. Indeed, the MAFs in Paiter-Surui (0.193 and 0.188) are the largest report globally. The distribution of combined NUDT15/TPMT metabolic phenotypes differed significantly (p < 0.0001) and largely (Cramér´s V = 0.37) across cohorts. This has important pharmacogenetic implications: the Clinical Pharmacogenetics Implementation Consortium recommendations to reduce or consider reduction of thiopurine dose applies to 4.4% Yanomami, 5.6% Munduruku, versus 41% Paiter-Suruí. The proportion of Paiter-Suruí at risk of thiopurine intolerance is 3- to 4-fold higher than any other population worldwide.
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Affiliation(s)
- Jamila Alessandra Perini
- Laboratório de Pesquisa de Ciências Farmacêuticas (LAPESF), Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, Brazil
| | - Paulo Cesar Basta
- Departamento de Endemias Samuel Pessoa, Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz (ENSP/Fiocruz), Rio de Janeiro, Brazil
| | - Guilherme Suarez-Kurtz
- Divisão de Pesquisa Clínica e Desenvolvimento Tecnológico, Coordenação de Pesquisa, Instituto Nacional de Câncer, Rio de Janeiro, Brazil
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6
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Oketch DJA, Giulietti M, Piva F. Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility. Int J Mol Sci 2023; 25:391. [PMID: 38203561 PMCID: PMC10779192 DOI: 10.3390/ijms25010391] [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: 11/24/2023] [Revised: 12/20/2023] [Accepted: 12/24/2023] [Indexed: 01/12/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.
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Affiliation(s)
| | - Matteo Giulietti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
| | - Francesco Piva
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
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7
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Tang TS, Liao F, Webber D, Gold N, Cao J, Dominguez D, Gladman D, Knight A, Levy DM, Ng L, Paterson AD, Touma Z, Urowitz MB, Wither J, Silverman ED, Pullenayegum EM, Hiraki LT. Genetics of longitudinal kidney function in children and adults with systemic lupus erythematosus. Rheumatology (Oxford) 2023; 62:3749-3756. [PMID: 36916720 PMCID: PMC10629779 DOI: 10.1093/rheumatology/kead119] [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: 10/27/2022] [Revised: 01/30/2023] [Accepted: 03/04/2023] [Indexed: 03/15/2023] Open
Abstract
OBJECTIVES Genome-wide association studies (GWAS) have identified loci associated with estimated glomerular filtration rate (eGFR). Few LN risk loci have been identified to date. We tested the association of SLE and eGFR polygenic risk scores (PRS) with repeated eGFR measures from children and adults with SLE. METHODS Patients from two tertiary care lupus clinics that met ≥4 ACR and/or SLICC criteria for SLE were genotyped on the Illumina MEGA or Omni1-Quad arrays. PRSs were calculated for SLE and eGFR, using published weighted GWA-significant alleles. eGFR was calculated using the CKD-EPI and Schwartz equations. We tested the effect of eGFR- and SLE-PRSs on eGFR mean and variance, adjusting for age at diagnosis, sex, ancestry, follow-up time, and clinical event flags. RESULTS We included 1158 SLE patients (37% biopsy-confirmed LN) with 36 733 eGFR measures over a median of 7.6 years (IQR: 3.9-15.3). LN was associated with lower within-person mean eGFR [LN: 93.8 (s.d. 26.4) vs non-LN: 101.6 (s.d. 17.7) mL/min per 1.73 m2; P < 0.0001] and higher variance [LN median: 157.0 (IQR: 89.5, 268.9) vs non-LN median: 84.9 (IQR: 46.9, 138.2) (mL/min per 1.73 m2)2; P < 0.0001]. Increasing SLE-PRSs were associated with lower mean eGFR and greater variance, while increasing eGFR-PRS was associated with increased eGFR mean and variance. CONCLUSION We observed significant associations between SLE and eGFR PRSs and repeated eGFR measurements, in a large cohort of children and adults with SLE. Longitudinal eGFR may serve as a powerful alternative outcome to LN categories for discovery of LN risk loci.
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Affiliation(s)
- Thai-Son Tang
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Fangming Liao
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Declan Webber
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Nicholas Gold
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jingjing Cao
- The Centre for Applied Genomics, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Daniela Dominguez
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Dafna Gladman
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Andrea Knight
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Deborah M Levy
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Lawrence Ng
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Andrew D Paterson
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Zahi Touma
- Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Murray B Urowitz
- Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Joan Wither
- Krembil Research Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Earl D Silverman
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Translational Medicine, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Eleanor M Pullenayegum
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Linda T Hiraki
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Genetics & Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
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8
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Bouassida M, Egloff M, Levy J, Chatron N, Bernardini L, Le Guyader G, Tabet AC, Schluth-Bolard C, Brancati F, Giuffrida MG, Dard R, Clorennec J, Coursimault J, Vialard F, Hervé B. 2p25.3 microduplications involving MYT1L: further phenotypic characterization through an assessment of 16 new cases and a literature review. Eur J Hum Genet 2023; 31:895-904. [PMID: 37188826 PMCID: PMC10400587 DOI: 10.1038/s41431-023-01379-9] [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: 10/02/2022] [Revised: 04/03/2023] [Accepted: 04/26/2023] [Indexed: 05/17/2023] Open
Abstract
Microduplications involving the MYT1L gene have mostly been described in series of patients with isolated schizophrenia. However, few reports have been published, and the phenotype has still not been well characterized. We sought to further characterize the phenotypic spectrum of this condition by describing the clinical features of patients with a pure 2p25.3 microduplication that includes all or part of MYT1L. We assessed 16 new patients with pure 2p25.3 microduplications recruited through a French national collaboration (n = 15) and the DECIPHER database (n = 1). We also reviewed 27 patients reported in the literature. For each case, we recorded clinical data, the microduplication size, and the inheritance pattern. The clinical features were variable and included developmental and speech delays (33%), autism spectrum disorder (ASD, 23%), mild-to-moderate intellectual disability (ID, 21%), schizophrenia (23%), or behavioral disorders (16%). Eleven patients did not have an obvious neuropsychiatric disorder. The microduplications ranged from 62.4 kb to 3.8 Mb in size and led to duplication of all or part of MYT1L; seven of these duplications were intragenic. The inheritance pattern was available for 18 patients: the microduplication was inherited in 13 cases, and all parents but one had normal phenotype. Our comprehensive review and expansion of the phenotypic spectrum associated with 2p25.3 microduplications involving MYT1L should help clinicians to better assess, counsel and manage affected individuals. MYT1L microduplications are characterized by a spectrum of neuropsychiatric phenotypes with incomplete penetrance and variable expressivity, which are probably due to as-yet unknown genetic and nongenetic modifiers.
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Affiliation(s)
- Malek Bouassida
- Département de Génétique, Laboratoire de Biologie Médicale, CHI de Poissy-St Germain en Laye, F-78300, Poissy, France.
| | - Matthieu Egloff
- Service de Génétique, Centre Hospitalier Universitaire de Poitiers, F-86021, Poitiers, France
| | - Jonathan Levy
- Département de Génétique, Hôpital Robert Debré, APHP, F-75019, Paris, France
| | - Nicolas Chatron
- Service de cytogénétique, Groupement Hospitalier Est, Hospices Civils de Lyon, F-69500, Bron, France
| | | | - Gwenaël Le Guyader
- Service de Génétique, Centre Hospitalier Universitaire de Poitiers, F-86021, Poitiers, France
| | - Anne-Claude Tabet
- Département de Génétique, Hôpital Robert Debré, APHP, F-75019, Paris, France
| | - Caroline Schluth-Bolard
- Service de cytogénétique, Groupement Hospitalier Est, Hospices Civils de Lyon, F-69500, Bron, France
| | - Francesco Brancati
- Department of Life, Health and Environmental Sciences, University of L'Aquila Piazzale Salvatore Tommasi, It-67100, Coppito - L'Aquila, Italy
- San Raffaele Roma, IRCCS, It-00163, Roma, Italy
| | | | - Rodolphe Dard
- Département de Génétique, Laboratoire de Biologie Médicale, CHI de Poissy-St Germain en Laye, F-78300, Poissy, France
- RHuMA Team, UMR-BREED, INRA-UVSQ-ENVA, UFR Simone Veil Santé, F-78380, Montigny-le-Bretonneux, France
| | - Juliette Clorennec
- Département de Génétique, Laboratoire de Biologie Médicale, CHI de Poissy-St Germain en Laye, F-78300, Poissy, France
- RHuMA Team, UMR-BREED, INRA-UVSQ-ENVA, UFR Simone Veil Santé, F-78380, Montigny-le-Bretonneux, France
| | - Juliette Coursimault
- Department of Genetics and Reference Center for Developmental Disorders, Normandie Univ, UNIROUEN, Inserm U1245 and CHU Rouen, F-76000, Rouen, France
| | - François Vialard
- Département de Génétique, Laboratoire de Biologie Médicale, CHI de Poissy-St Germain en Laye, F-78300, Poissy, France.
- RHuMA Team, UMR-BREED, INRA-UVSQ-ENVA, UFR Simone Veil Santé, F-78380, Montigny-le-Bretonneux, France.
| | - Bérénice Hervé
- Département de Génétique, Laboratoire de Biologie Médicale, CHI de Poissy-St Germain en Laye, F-78300, Poissy, France
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9
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Soto DC, Uribe-Salazar JM, Shew CJ, Sekar A, McGinty S, Dennis MY. Genomic structural variation: A complex but important driver of human evolution. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181 Suppl 76:118-144. [PMID: 36794631 PMCID: PMC10329998 DOI: 10.1002/ajpa.24713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/21/2023] [Accepted: 02/05/2023] [Indexed: 02/17/2023]
Abstract
Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.
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Affiliation(s)
- Daniela C. Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - José M. Uribe-Salazar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Aarthi Sekar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Sean McGinty
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
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10
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Kaivola K, Chia R, Ding J, Rasheed M, Fujita M, Menon V, Walton RL, Collins RL, Billingsley K, Brand H, Talkowski M, Zhao X, Dewan R, Stark A, Ray A, Solaiman S, Alvarez Jerez P, Malik L, Dawson TM, Rosenthal LS, Albert MS, Pletnikova O, Troncoso JC, Masellis M, Keith J, Black SE, Ferrucci L, Resnick SM, Tanaka T, Topol E, Torkamani A, Tienari P, Foroud TM, Ghetti B, Landers JE, Ryten M, Morris HR, Hardy JA, Mazzini L, D'Alfonso S, Moglia C, Calvo A, Serrano GE, Beach TG, Ferman T, Graff-Radford NR, Boeve BF, Wszolek ZK, Dickson DW, Chiò A, Bennett DA, De Jager PL, Ross OA, Dalgard CL, Gibbs JR, Traynor BJ, Scholz SW. Genome-wide structural variant analysis identifies risk loci for non-Alzheimer's dementias. CELL GENOMICS 2023; 3:100316. [PMID: 37388914 PMCID: PMC10300553 DOI: 10.1016/j.xgen.2023.100316] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/21/2023] [Accepted: 04/06/2023] [Indexed: 07/01/2023]
Abstract
We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.
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Affiliation(s)
- Karri Kaivola
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Ruth Chia
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Jinhui Ding
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Memoona Rasheed
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Masashi Fujita
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY, USA
| | - Ronald L. Walton
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
| | - Ryan L. Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.), Cambridge, MA, USA
- Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kimberley Billingsley
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Centre for Alzheimer’s and Related Dementias, National Institute on Aging, Bethesda, MD, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.), Cambridge, MA, USA
- Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Michael Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.), Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.), Cambridge, MA, USA
| | - Ramita Dewan
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Ali Stark
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Anindita Ray
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Sultana Solaiman
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pilar Alvarez Jerez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Centre for Alzheimer’s and Related Dementias, National Institute on Aging, Bethesda, MD, USA
| | - Laksh Malik
- Centre for Alzheimer’s and Related Dementias, National Institute on Aging, Bethesda, MD, USA
| | - Ted M. Dawson
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Neuroregeneration and Stem Cell Programs, Institute of Cell Engineering, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Department of Pharmacology and Molecular Science, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Liana S. Rosenthal
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Marilyn S. Albert
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Olga Pletnikova
- Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University of Buffalo, Buffalo, NY, USA
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Juan C. Troncoso
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Mario Masellis
- Cognitive & Movement Disorders Clinic, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
| | - Julia Keith
- Department of Anatomical Pathology, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
| | - Sandra E. Black
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
| | - Luigi Ferrucci
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Toshiko Tanaka
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA
| | - PROSPECT Consortium
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY, USA
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.), Cambridge, MA, USA
- Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA, USA
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Centre for Alzheimer’s and Related Dementias, National Institute on Aging, Bethesda, MD, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Neuroregeneration and Stem Cell Programs, Institute of Cell Engineering, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Department of Pharmacology and Molecular Science, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University of Buffalo, Buffalo, NY, USA
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA
- Cognitive & Movement Disorders Clinic, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, University of Toronto, 2075 Bayview Avenue, Toronto, ON, Canada
- Department of Anatomical Pathology, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, University of Toronto, 1 King’s College Circle, Room 2374, Toronto, ON, Canada
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
- Translational Immunology, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA
- Department of Genetics and Genomic Medicine Research & Teaching, UCL GOS Institute of Child Health, University College London, London, UK
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
- UK Dementia Research Institute, Department of Neurogenerative Disease and Reta Lila Weston Institute, London, UK
- Institute of Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Maggiore della Carita University Hospital, Novara, Italy
- Department of Health Sciences, University of Eastern Piedmont, Novara, Italy
- Rita Levi Montalcini Department of Neuroscience, University of Turin, Turin, Italy
- Azienda Ospedaliero Universitaria Città, della Salute e della Scienza, Corso Bramante, 88, Turin, Italy
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
- Department of Psychiatry and Psychology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
- Center for Sleep Medicine, Mayo Clinic, Rochester, MN, USA
- Institute of Cognitive Sciences and Technologies, C.N.R., Via S. Martino della Battaglia, 44, Rome, Italy
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The American Genome Center, Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- RNA Therapeutics Laboratory, Therapeutics Development Branch, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - Eric Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Ali Torkamani
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Pentti Tienari
- Translational Immunology, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - John E. Landers
- Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Mina Ryten
- Department of Genetics and Genomic Medicine Research & Teaching, UCL GOS Institute of Child Health, University College London, London, UK
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
| | - Huw R. Morris
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - John A. Hardy
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
- UK Dementia Research Institute, Department of Neurogenerative Disease and Reta Lila Weston Institute, London, UK
- Institute of Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | | | - Sandra D'Alfonso
- Department of Health Sciences, University of Eastern Piedmont, Novara, Italy
| | - Cristina Moglia
- Rita Levi Montalcini Department of Neuroscience, University of Turin, Turin, Italy
- Azienda Ospedaliero Universitaria Città, della Salute e della Scienza, Corso Bramante, 88, Turin, Italy
| | - Andrea Calvo
- Rita Levi Montalcini Department of Neuroscience, University of Turin, Turin, Italy
- Azienda Ospedaliero Universitaria Città, della Salute e della Scienza, Corso Bramante, 88, Turin, Italy
| | - Geidy E. Serrano
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Thomas G. Beach
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Tanis Ferman
- Department of Psychiatry and Psychology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
| | | | | | - Zbigniew K. Wszolek
- Institute of Cognitive Sciences and Technologies, C.N.R., Via S. Martino della Battaglia, 44, Rome, Italy
| | - Dennis W. Dickson
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
| | - Adriano Chiò
- Rita Levi Montalcini Department of Neuroscience, University of Turin, Turin, Italy
- Azienda Ospedaliero Universitaria Città, della Salute e della Scienza, Corso Bramante, 88, Turin, Italy
- Institute of Cognitive Sciences and Technologies, C.N.R., Via S. Martino della Battaglia, 44, Rome, Italy
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Philip L. De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY, USA
| | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL, USA
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The American Genome Center, Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - J. Raphael Gibbs
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Bryan J. Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
- RNA Therapeutics Laboratory, Therapeutics Development Branch, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - Sonja W. Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
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11
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Cotter DJ, Hofgard EF, Novembre J, Szpiech ZA, Rosenberg NA. A rarefaction approach for measuring population differences in rare and common variation. Genetics 2023; 224:iyad070. [PMID: 37075098 PMCID: PMC10213490 DOI: 10.1093/genetics/iyad070] [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: 12/20/2022] [Revised: 12/20/2022] [Accepted: 04/07/2023] [Indexed: 04/20/2023] Open
Abstract
In studying allele-frequency variation across populations, it is often convenient to classify an allelic type as "rare," with nonzero frequency less than or equal to a specified threshold, "common," with a frequency above the threshold, or entirely unobserved in a population. When sample sizes differ across populations, however, especially if the threshold separating "rare" and "common" corresponds to a small number of observed copies of an allelic type, discreteness effects can lead a sample from one population to possess substantially more rare allelic types than a sample from another population, even if the two populations have extremely similar underlying allele-frequency distributions across loci. We introduce a rarefaction-based sample-size correction for use in comparing rare and common variation across multiple populations whose sample sizes potentially differ. We use our approach to examine rare and common variation in worldwide human populations, finding that the sample-size correction introduces subtle differences relative to analyses that use the full available sample sizes. We introduce several ways in which the rarefaction approach can be applied: we explore the dependence of allele classifications on subsample sizes, we permit more than two classes of allelic types of nonzero frequency, and we analyze rare and common variation in sliding windows along the genome. The results can assist in clarifying similarities and differences in allele-frequency patterns across populations.
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Affiliation(s)
- Daniel J Cotter
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Elyssa F Hofgard
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Zachary A Szpiech
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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12
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Reitz C, Pericak-Vance MA, Foroud T, Mayeux R. A global view of the genetic basis of Alzheimer disease. Nat Rev Neurol 2023; 19:261-277. [PMID: 37024647 PMCID: PMC10686263 DOI: 10.1038/s41582-023-00789-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 04/08/2023]
Abstract
The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.
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Affiliation(s)
- Christiane Reitz
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
- Department of Epidemiology, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Richard Mayeux
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA.
- Department of Neurology, Columbia University, New York, NY, USA.
- Department of Epidemiology, Columbia University, New York, NY, USA.
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13
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Chan MHM, Merrill SM, Konwar C, Kobor MS. An integrative framework and recommendations for the study of DNA methylation in the context of race and ethnicity. DISCOVER SOCIAL SCIENCE AND HEALTH 2023; 3:9. [PMID: 37122633 PMCID: PMC10118232 DOI: 10.1007/s44155-023-00039-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 03/27/2023] [Indexed: 05/02/2023]
Abstract
Human social epigenomics research is critical to elucidate the intersection of social and genetic influences underlying racial and ethnic differences in health and development. However, this field faces major challenges in both methodology and interpretation with regard to disentangling confounded social and biological aspects of race and ethnicity. To address these challenges, we discuss how these constructs have been approached in the past and how to move forward in studying DNA methylation (DNAm), one of the best-characterized epigenetic marks in humans, in a responsible and appropriately nuanced manner. We highlight self-reported racial and ethnic identity as the primary measure in this field, and discuss its implications in DNAm research. Racial and ethnic identity reflects the biological embedding of an individual's sociocultural experience and environmental exposures in combination with the underlying genetic architecture of the human population (i.e., genetic ancestry). Our integrative framework demonstrates how to examine DNAm in the context of race and ethnicity, while considering both intrinsic factors-including genetic ancestry-and extrinsic factors-including structural and sociocultural environment and developmental niches-when focusing on early-life experience. We reviewed DNAm research in relation to health disparities given its relevance to race and ethnicity as social constructs. Here, we provide recommendations for the study of DNAm addressing racial and ethnic differences, such as explicitly acknowledging the self-reported nature of racial and ethnic identity, empirically examining the effects of genetic variants and accounting for genetic ancestry, and investigating race-related and culturally regulated environmental exposures and experiences. Supplementary Information The online version contains supplementary material available at 10.1007/s44155-023-00039-z.
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Affiliation(s)
- Meingold Hiu-ming Chan
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC Canada
- British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC Canada
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC Canada
| | - Sarah M. Merrill
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC Canada
- British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC Canada
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC Canada
| | - Chaini Konwar
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC Canada
- British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC Canada
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC Canada
| | - Michael S. Kobor
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC Canada
- British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC Canada
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC Canada
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC Canada
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14
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Iltis AS, Rolf L, Yaeger L, Goodman MS, DuBois JM. Attitudes and beliefs regarding race-targeted genetic testing of Black people: A systematic review. J Genet Couns 2023; 32:435-461. [PMID: 36644818 PMCID: PMC10349658 DOI: 10.1002/jgc4.1653] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 10/25/2022] [Accepted: 10/28/2022] [Indexed: 01/17/2023]
Abstract
Geographical ancestry has been associated with an increased risk of various genetic conditions. Race and ethnicity often have been used as proxies for geographical ancestry. Despite numerous problems associated with the crude reliance on race and ethnicity as proxies for geographical ancestry, some genetic testing in the clinical, research, and employment settings has been and continues to be race- or ethnicity-based. Race-based or race-targeted genetic testing refers to genetic testing offered only or primarily to people of particular racial or ethnic groups because of presumed differences among groups. One current example is APOL1 testing of Black kidney donors. Race-based genetic testing raises numerous ethical and policy questions. Given the ongoing reliance on the Black race in genetic testing, it is important to understand the views of people who identify as Black or are identified as Black (including African American, Afro-Caribbean, and Hispanic Black) regarding race-based genetic testing that targets Black people because of their race. We conducted a systematic review of studies and reports of stakeholder-engaged projects that examined how people who identify as or are identified as Black perceive genetic testing that specifically presumes genetic differences exist among racial groups or uses race as a surrogate for ancestral genetic variation and targets Black people. Our review identified 14 studies that explicitly studied this question and another 13 that implicitly or tacitly studied this matter. We found four main factors that contribute to a positive attitude toward race-targeted genetic testing (facilitators) and eight main factors that are associated with concerns regarding race-targeted genetic testing (barriers). This review fills an important gap. These findings should inform future genetic research and the policies and practices developed in clinical, research, public health, or other settings regarding genetic testing.
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Affiliation(s)
| | - Liz Rolf
- Washington University in St. Louis School of Medicine
| | - Lauren Yaeger
- Washington University in St. Louis School of Medicine
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15
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Zhu H, Oâ Shaughnessy B. Actomyosin pulsing rescues embryonic tissue folding from disruption by myosin fluctuations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.533016. [PMID: 36993262 PMCID: PMC10055118 DOI: 10.1101/2023.03.16.533016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
During early development, myosin II mechanically reshapes and folds embryo tissue. A much-studied example is ventral furrow formation in Drosophila , marking the onset of gastrulation. Furrowing is driven by contraction of actomyosin networks on apical cell surfaces, but how the myosin patterning encodes tissue shape is unclear, and elastic models failed to reproduce essential features of experimental cell contraction profiles. The myosin patterning exhibits substantial cell-to-cell fluctuations with pulsatile time-dependence, a striking but unexplained feature of morphogenesis in many organisms. Here, using biophysical modeling we find viscous forces offer the principle resistance to actomyosin-driven apical constriction. In consequence, tissue shape is encoded in the direction-dependent curvature of the myosin patterning which orients an anterior-posterior furrow. Tissue contraction is highly sensitive to cell-to-cell myosin fluctuations, explaining furrowing failure in genetically perturbed embryos whose fluctuations are temporally persistent. In wild-type embryos, this catastrophic outcome is averted by pulsatile myosin time-dependence, a time-averaging effect that rescues furrowing. This low pass filter mechanism may underlie the usage of actomyosin pulsing in diverse morphogenetic processes across many organisms.
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16
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Corcoran M, Chernyshev M, Mandolesi M, Narang S, Kaduk M, Ye K, Sundling C, Färnert A, Kreslavsky T, Bernhardsson C, Larena M, Jakobsson M, Karlsson Hedestam GB. Archaic humans have contributed to large-scale variation in modern human T cell receptor genes. Immunity 2023; 56:635-652.e6. [PMID: 36796364 DOI: 10.1016/j.immuni.2023.01.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/21/2022] [Accepted: 01/23/2023] [Indexed: 02/18/2023]
Abstract
Human T cell receptors (TCRs) are critical for mediating immune responses to pathogens and tumors and regulating self-antigen recognition. Yet, variations in the genes encoding TCRs remain insufficiently defined. Detailed analysis of expressed TCR alpha, beta, gamma, and delta genes in 45 donors from four human populations-African, East Asian, South Asian, and European-revealed 175 additional TCR variable and junctional alleles. Most of these contained coding changes and were present at widely differing frequencies in the populations, a finding confirmed using DNA samples from the 1000 Genomes Project. Importantly, we identified three Neanderthal-derived, introgressed TCR regions including a highly divergent TRGV4 variant, which mediated altered butyrophilin-like molecule 3 (BTNL3) ligand reactivity and was frequent in all modern Eurasian population groups. Our results demonstrate remarkable variation in TCR genes in both individuals and populations, providing a strong incentive for including allelic variation in studies of TCR function in human biology.
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Affiliation(s)
- Martin Corcoran
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm, Sweden.
| | - Mark Chernyshev
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Marco Mandolesi
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Sanjana Narang
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Mateusz Kaduk
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Kewei Ye
- Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Christopher Sundling
- Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Anna Färnert
- Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Taras Kreslavsky
- Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Carolina Bernhardsson
- Department of Organismal Biology, Human Evolution, Norbyvägen 18C, 752 63 Uppsala, Sweden
| | - Maximilian Larena
- Department of Organismal Biology, Human Evolution, Norbyvägen 18C, 752 63 Uppsala, Sweden
| | - Mattias Jakobsson
- Department of Organismal Biology, Human Evolution, Norbyvägen 18C, 752 63 Uppsala, Sweden
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17
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Mikhaylova V, Rzepka M, Kawamura T, Xia Y, Chang PL, Zhou S, Pham L, Modi N, Yao L, Perez-Agustin A, Pagans S, Boles TC, Lei M, Wang Y, Garcia-Bassets I, Chen Z. Targeted Phasing of 2-200 Kilobase DNA Fragments with a Short-Read Sequencer and a Single-Tube Linked-Read Library Method. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.05.531179. [PMID: 36945366 PMCID: PMC10028795 DOI: 10.1101/2023.03.05.531179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
In the human genome, heterozygous sites are genomic positions with different alleles inherited from each parent. On average, there is a heterozygous site every 1-2 kilobases (kb). Resolving whether two alleles in neighboring heterozygous positions are physically linked-that is, phased-is possible with a short-read sequencer if the sequencing library captures long-range information. TELL-Seq is a library preparation method based on millions of barcoded micro-sized beads that enables instrument-free phasing of a whole human genome in a single PCR tube. TELL-Seq incorporates a unique molecular identifier (barcode) to the short reads generated from the same high-molecular-weight (HMW) DNA fragment (known as 'linked-reads'). However, genome-scale TELL-Seq is not cost-effective for applications focusing on a single locus or a few loci. Here, we present an optimized TELL-Seq protocol that enables the cost-effective phasing of enriched loci (targets) of varying sizes, purity levels, and heterozygosity. Targeted TELL-Seq maximizes linked-read efficiency and library yield while minimizing input requirements, fragment collisions on microbeads, and sequencing burden. To validate the targeted protocol, we phased seven 180-200 kb loci enriched by CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis, four 20 kb loci enriched by CRISPR/Cas9-mediated protection from exonuclease digestion, and six 2-13 kb loci amplified by PCR. The selected targets have clinical and research relevance (BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA). These analyses reveal that targeted TELL-Seq provides a reliable way of phasing allelic variants within targets (2-200 kb in length) with the low cost and high accuracy of short-read sequencing.
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Affiliation(s)
| | - Madison Rzepka
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | | | - Yu Xia
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Peter L. Chang
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | | | - Long Pham
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Naisarg Modi
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
| | - Likun Yao
- Department of Medicine, University of California, San Diego, La Jolla, CA 92093 USA
| | - Adrian Perez-Agustin
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | - Sara Pagans
- Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain
| | | | - Ming Lei
- Universal Sequencing Technology Corp., Canton, MA 02021, USA
| | - Yong Wang
- Universal Sequencing Technology Corp., Canton, MA 02021, USA
| | | | - Zhoutao Chen
- Universal Sequencing Technology Corp., Carlsbad, CA 92011, USA
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18
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Yang G, Mishra M, Perera MA. Multi-Omics Studies in Historically Excluded Populations: The Road to Equity. Clin Pharmacol Ther 2023; 113:541-556. [PMID: 36495075 PMCID: PMC10323857 DOI: 10.1002/cpt.2818] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/01/2022] [Indexed: 12/14/2022]
Abstract
Over the past few decades, genomewide association studies (GWASs) have identified the specific genetics variants contributing to many complex diseases by testing millions of genetic variations across the human genome against a variety of phenotypes. However, GWASs are limited in their ability to uncover mechanistic insight given that most significant associations are found in non-coding region of the genome. Furthermore, the lack of diversity in studies has stymied the advance of precision medicine for many historically excluded populations. In this review, we summarize most popular multi-omics approaches (genomics, transcriptomics, proteomics, and metabolomics) related to precision medicine and highlight if diverse populations have been included and how their findings have advance biological understanding of disease and drug response. New methods that incorporate local ancestry have been to improve the power of GWASs for admixed populations (such as African Americans and Latinx). Because most signals from GWAS are in the non-coding region, other machine learning and omics approaches have been developed to identify the potential causative single-nucleotide polymorphisms and genes that explain these phenotypes. These include polygenic risk scores, expression quantitative trait locus mapping, and transcriptome-wide association studies. Analogous protein methods, such as proteins quantitative trait locus mapping, proteome-wide association studies, and metabolomic approaches provide insight into the consequences of genetic variation on protein abundance. Whereas, integrated multi-omics studies have improved our understanding of the mechanisms for genetic association, we still lack the datasets and cohorts for historically excluded populations to provide equity in precision medicine and pharmacogenomics.
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Affiliation(s)
- Guang Yang
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Mrinal Mishra
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Minoli A. Perera
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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19
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Kelly DE, Ramdas S, Ma R, Rawlings-Goss RA, Grant GR, Ranciaro A, Hirbo JB, Beggs W, Yeager M, Chanock S, Nyambo TB, Omar SA, Woldemeskel D, Belay G, Li H, Brown CD, Tishkoff SA. The genetic and evolutionary basis of gene expression variation in East Africans. Genome Biol 2023; 24:35. [PMID: 36829244 PMCID: PMC9951478 DOI: 10.1186/s13059-023-02874-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 02/13/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Mapping of quantitative trait loci (QTL) associated with molecular phenotypes is a powerful approach for identifying the genes and molecular mechanisms underlying human traits and diseases, though most studies have focused on individuals of European descent. While important progress has been made to study a greater diversity of human populations, many groups remain unstudied, particularly among indigenous populations within Africa. To better understand the genetics of gene regulation in East Africans, we perform expression and splicing QTL mapping in whole blood from a cohort of 162 diverse Africans from Ethiopia and Tanzania. We assess replication of these QTLs in cohorts of predominantly European ancestry and identify candidate genes under selection in human populations. RESULTS We find the gene regulatory architecture of African and non-African populations is broadly shared, though there is a considerable amount of variation at individual loci across populations. Comparing our analyses to an equivalently sized cohort of European Americans, we find that QTL mapping in Africans improves the detection of expression QTLs and fine-mapping of causal variation. Integrating our QTL scans with signatures of natural selection, we find several genes related to immunity and metabolism that are highly differentiated between Africans and non-Africans, as well as a gene associated with pigmentation. CONCLUSION Extending QTL mapping studies beyond European ancestry, particularly to diverse indigenous populations, is vital for a complete understanding of the genetic architecture of human traits and can reveal novel functional variation underlying human traits and disease.
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Affiliation(s)
- Derek E Kelly
- Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Shweta Ramdas
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Rong Ma
- Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - Jibril B Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - William Beggs
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Meredith Yeager
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Institutes of Health, Rockville, MD, USA
| | - Thomas B Nyambo
- Department of Biochemistry, Kampala International University in Tanzania, Dar Es Salaam, Tanzania
| | - Sabah A Omar
- Center for Biotechnology Research and Development, Kenya Medical Research Institute, Nairobi, Kenya
| | - Dawit Woldemeskel
- Microbial Cellular and Molecular Biology Department, Addis Ababa University, Addis Ababa, Ethiopia
| | - Gurja Belay
- Microbial Cellular and Molecular Biology Department, Addis Ababa University, Addis Ababa, Ethiopia
| | - Hongzhe Li
- Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher D Brown
- Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah A Tishkoff
- Genetics, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biology, University of Pennsylvania, Philadelphia, USA.
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20
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Yuan M, Hoskens H, Goovaerts S, Herrick N, Shriver MD, Walsh S, Claes P. Hybrid autoencoder with orthogonal latent space for robust population structure inference. Sci Rep 2023; 13:2612. [PMID: 36788253 PMCID: PMC9929087 DOI: 10.1038/s41598-023-28759-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
Analysis of population structure and genomic ancestry remains an important topic in human genetics and bioinformatics. Commonly used methods require high-quality genotype data to ensure accurate inference. However, in practice, laboratory artifacts and outliers are often present in the data. Moreover, existing methods are typically affected by the presence of related individuals in the dataset. In this work, we propose a novel hybrid method, called SAE-IBS, which combines the strengths of traditional matrix decomposition-based (e.g., principal component analysis) and more recent neural network-based (e.g., autoencoders) solutions. Namely, it yields an orthogonal latent space enhancing dimensionality selection while learning non-linear transformations. The proposed approach achieves higher accuracy than existing methods for projecting poor quality target samples (genotyping errors and missing data) onto a reference ancestry space and generates a robust ancestry space in the presence of relatedness. We introduce a new approach and an accompanying open-source program for robust ancestry inference in the presence of missing data, genotyping errors, and relatedness. The obtained ancestry space allows for non-linear projections and exhibits orthogonality with clearly separable population groups.
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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.
| | - Hanne Hoskens
- 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
| | - Noah Herrick
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - 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, VIC, Australia.
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21
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De Oliveira TC, Secolin R, Lopes-Cendes I. A review of ancestrality and admixture in Latin America and the caribbean focusing on native American and African descendant populations. Front Genet 2023; 14:1091269. [PMID: 36741309 PMCID: PMC9893294 DOI: 10.3389/fgene.2023.1091269] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 01/09/2023] [Indexed: 01/21/2023] Open
Abstract
Genomics can reveal essential features about the demographic evolution of a population that may not be apparent from historical elements. In recent years, there has been a significant increase in the number of studies applying genomic epidemiological approaches to understand the genetic structure and diversity of human populations in the context of demographic history and for implementing precision medicine. These efforts have traditionally been applied predominantly to populations of European origin. More recently, initiatives in the United States and Africa are including more diverse populations, establishing new horizons for research in human populations with African and/or Native ancestries. Still, even in the most recent projects, the under-representation of genomic data from Latin America and the Caribbean (LAC) is remarkable. In addition, because the region presents the most recent global miscegenation, genomics data from LAC may add relevant information to understand population admixture better. Admixture in LAC started during the colonial period, in the 15th century, with intense miscegenation between European settlers, mainly from Portugal and Spain, with local indigenous and sub-Saharan Africans brought through the slave trade. Since, there are descendants of formerly enslaved and Native American populations in the LAC territory; they are considered vulnerable populations because of their history and current living conditions. In this context, studying LAC Native American and African descendant populations is important for several reasons. First, studying human populations from different origins makes it possible to understand the diversity of the human genome better. Second, it also has an immediate application to these populations, such as empowering communities with the knowledge of their ancestral origins. Furthermore, because knowledge of the population genomic structure is an essential requirement for implementing genomic medicine and precision health practices, population genomics studies may ensure that these communities have access to genomic information for risk assessment, prevention, and the delivery of optimized treatment; thus, helping to reduce inequalities in the Western Hemisphere. Hoping to set the stage for future studies, we review different aspects related to genetic and genomic research in vulnerable populations from LAC countries.
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Affiliation(s)
- Thais C. De Oliveira
- Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Rodrigo Secolin
- Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
| | - Iscia Lopes-Cendes
- Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
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22
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Halabian R, Makałowski W. A Map of 3' DNA Transduction Variants Mediated by Non-LTR Retroelements on 3202 Human Genomes. BIOLOGY 2022; 11:1032. [PMID: 36101413 PMCID: PMC9311842 DOI: 10.3390/biology11071032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 05/03/2023]
Abstract
As one of the major structural constituents, mobile elements comprise more than half of the human genome, among which Alu, L1, and SVA elements are still active and continue to generate new offspring. One of the major characteristics of L1 and SVA elements is their ability to co-mobilize adjacent downstream sequences to new loci in a process called 3' DNA transduction. Transductions influence the structure and content of the genome in different ways, such as increasing genome variation, exon shuffling, and gene duplication. Moreover, given their mutagenicity capability, 3' transductions are often involved in tumorigenesis or in the development of some diseases. In this study, we analyzed 3202 genomes sequenced at high coverage by the New York Genome Center to catalog and characterize putative 3' transduced segments mediated by L1s and SVAs. Here, we present a genome-wide map of inter/intrachromosomal 3' transduction variants, including their genomic and functional location, length, progenitor location, and allelic frequency across 26 populations. In total, we identified 7103 polymorphic L1s and 3040 polymorphic SVAs. Of these, 268 and 162 variants were annotated as high-confidence L1 and SVA 3' transductions, respectively, with lengths that ranged from 7 to 997 nucleotides. We found specific loci within chromosomes X, 6, 7, and 6_GL000253v2_alt as master L1s and SVAs that had yielded more transductions, among others. Together, our results demonstrate the dynamic nature of transduction events within the genome and among individuals and their contribution to the structural variations of the human genome.
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Affiliation(s)
| | - Wojciech Makałowski
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, 48149 Münster, Germany;
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23
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Ahmad SF, Singh A, Panda S, Malla WA, Kumar A, Dutt T. Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle. Gene 2022; 830:146510. [PMID: 35447249 DOI: 10.1016/j.gene.2022.146510] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 03/23/2022] [Accepted: 04/14/2022] [Indexed: 11/17/2022]
Abstract
The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.
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Affiliation(s)
- Sheikh Firdous Ahmad
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India.
| | - Akansha Singh
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
| | - Snehasmita Panda
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
| | - Waseem Akram Malla
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
| | - Amit Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India.
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, Uttar Pradesh, India
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24
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Cholesterol and matrisome pathways dysregulated in astrocytes and microglia. Cell 2022; 185:2213-2233.e25. [PMID: 35750033 DOI: 10.1016/j.cell.2022.05.017] [Citation(s) in RCA: 136] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/07/2020] [Accepted: 05/16/2022] [Indexed: 12/12/2022]
Abstract
The impact of apolipoprotein E ε4 (APOE4), the strongest genetic risk factor for Alzheimer's disease (AD), on human brain cellular function remains unclear. Here, we investigated the effects of APOE4 on brain cell types derived from population and isogenic human induced pluripotent stem cells, post-mortem brain, and APOE targeted replacement mice. Population and isogenic models demonstrate that APOE4 local haplotype, rather than a single risk allele, contributes to risk. Global transcriptomic analyses reveal human-specific, APOE4-driven lipid metabolic dysregulation in astrocytes and microglia. APOE4 enhances de novo cholesterol synthesis despite elevated intracellular cholesterol due to lysosomal cholesterol sequestration in astrocytes. Further, matrisome dysregulation is associated with upregulated chemotaxis, glial activation, and lipid biosynthesis in astrocytes co-cultured with neurons, which recapitulates altered astrocyte matrisome signaling in human brain. Thus, APOE4 initiates glia-specific cell and non-cell autonomous dysregulation that may contribute to increased AD risk.
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25
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Fadista J, Skotte L, Karjalainen J, Abner E, Sørensen E, Ullum H, Werge T, Esko T, Milani L, Palotie A, Daly M, Melbye M, Feenstra B, Geller F. Comprehensive genome-wide association study of different forms of hernia identifies more than 80 associated loci. Nat Commun 2022; 13:3200. [PMID: 35680855 PMCID: PMC9184475 DOI: 10.1038/s41467-022-30921-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 05/18/2022] [Indexed: 11/08/2022] Open
Abstract
Hernias are characterized by protrusion of an organ or tissue through its surrounding cavity and often require surgical repair. In this study we identify 65,492 cases for five hernia types in the UK Biobank and perform genome-wide association study scans for these five types and two combined groups. Our results show associated variants in all scans. Inguinal hernia has the most associations and we conduct a follow-up study with 23,803 additional cases from four study groups giving 84 independently associated variants. Identified variants from all scans are collapsed into 81 independent loci. Further testing shows that 26 loci are associated with more than one hernia type, suggesting substantial overlap between the underlying genetic mechanisms. Pathway analyses identify several genes with a strong link to collagen and/or elastin (ADAMTS6, ADAMTS16, ADAMTSL3, LOX, ELN) in the vicinity of associated loci for inguinal hernia, which substantiates an essential role of connective tissue morphology.
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Affiliation(s)
- João Fadista
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Clinical Sciences, Lund University Diabetes Centre, Malmö, Sweden
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Line Skotte
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Erik Abner
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Henrik Ullum
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Werge
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Lundbeck Foundation Center for GeoGenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen and Aarhus, Aarhus, Denmark
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Analytic and Translational Genetics Unit, Department of Medicine, and the Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mark Daly
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mads Melbye
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
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26
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Association between TAP gene polymorphisms and tuberculosis susceptibility in a Han Chinese population in Guangdong. Mol Genet Genomics 2022; 297:779-790. [PMID: 35325275 PMCID: PMC8943507 DOI: 10.1007/s00438-022-01885-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 03/08/2022] [Indexed: 12/02/2022]
Abstract
Tuberculosis (TB) is an important public health problem. Studies indicated that TAP plays a key role in the presentation and transport of antigenic peptides during anti-M.tb infection. Given the important biological role of the TAP gene involved in anti-M.tb infection, a family-based case–control study including 133 tuberculosis patients, 107 healthy household contacts, and 173 healthy controls was conducted to assess the association between TAP gene polymorphisms and TB susceptibility. The basic information of subjects and their blood samples were collected. Four SNPs including rs1135216, rs1057141, rs241447, and rs3819721 were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP). Our results suggested that BMI, residence, bedroom crowding, indoor humidity, fitness activities, history of smoking, and TB exposure history were associated with the occurrence of tuberculosis (P < 0.05). A significant association was observed between the TAP1 rs1135216 CT/CC genotype and increased TB risk, and the ORs were 2.56 (95% CI 1.31–4.99) and 6.73 (95% CI 1.33–34.02), respectively. TAP2 rs3819721 GG genotype carriers also showed an increased risk of TB when compared TB patients to healthy household contacts. Haplotype analysis revealed that the haplotype CT at rs1057141 and rs1135216 (OR = 11.34, 95% CI 1.49–86.56; OR = 7.45, 95% CI 1.43–38.76), as well as TA at rs241447 and rs3819721 (OR = 2.20, 95% CI 1.07–4.56) had a significantly increased risk of TB. The genetic risk scores (GRS) analysis of the four loci indicated that the risk of tuberculosis increased with increasing GRS scores in TB vs HHC (Ptrend = 0.010) and in TB vs HC (Ptrend = 0.001). In conclusion, our findings suggested that the SNPs of rs1135216 and rs3819721 were associated with TB susceptibility among the tuberculosis-prone families in the Chinese Han population and the risk of developing tuberculosis increases with the number of risk alleles, which could help identify high-risk groups in time and take scientific preventive measures. Further cohort studies with large samples are needed to validate the role of TAP gene variants on TB susceptibility.
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Ausmees K, Nettelblad C. A deep learning framework for characterization of genotype data. G3 GENES|GENOMES|GENETICS 2022; 12:6515290. [PMID: 35078229 PMCID: PMC8896001 DOI: 10.1093/g3journal/jkac020] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 01/18/2022] [Indexed: 01/05/2023]
Abstract
Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are principal component analysis, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns. Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and have been shown to present a promising alternative to traditional statistical methods for various applications in omics research. In this study, we propose a deep learning model based on a convolutional autoencoder architecture for dimensionality reduction of genotype data. Using a highly diverse cohort of human samples, we demonstrate that the model can identify population clusters and provide richer visual information in comparison to principal component analysis, while preserving global geometry to a higher extent than t-SNE and UMAP, yielding results that are comparable to an alternative deep learning approach based on variational autoencoders. We also discuss the use of the methodology for more general characterization of genotype data, showing that it preserves spatial properties in the form of decay of linkage disequilibrium with distance along the genome and demonstrating its use as a genetic clustering method, comparing results to the ADMIXTURE software frequently used in population genetic studies.
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Affiliation(s)
- Kristiina Ausmees
- Division of Scientific Computing, Department of Information Technology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Carl Nettelblad
- Division of Scientific Computing, Department of Information Technology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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Amanzougaghene N, Drali R, Shako JC, Davoust B, Fenollar F, Raoult D, Mediannikov O. High Genetic Diversity and Rickettsia felis in Pediculus humanus Lice Infesting Mbuti (pygmy people), -Democratic Republic of Congo. Front Cell Infect Microbiol 2022; 12:834388. [PMID: 35310843 PMCID: PMC8924665 DOI: 10.3389/fcimb.2022.834388] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 02/08/2022] [Indexed: 11/14/2022] Open
Abstract
Pediculus humanus is an obligate bloodsucking parasite of humans that has two ecotypes, the head louse and the body louse, which share an intimate history of coevolution with their human host. In the present work, we obtained and analysed head and body lice collected from Mbuti pygmies living in the Orientale province of the Democratic Republic of the Congo. Cytochrome b DNA analysis was performed in order to type the six known lice clades (A, D, B, F, C and E). The results revealed the presence of two mitochondrial clades. Clade D was the most frequent (61.7% of 47), followed by clade A (38.3% of 47). Sixteen haplotypes were found in 47 samples, of which thirteen were novel haplotypes, indicating an unusually high genetic diversity that closely mirrors the diversity of their hosts. Moreover, we report for the first time the presence of the DNA of R. felis in three (6.4% of 47) head and body lice belonging to both clades A and D. Additional studies are needed to clarify whether the Pediculus lice can indeed transmit this emerging zoonotic bacterium to their human hosts.
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Affiliation(s)
- Nadia Amanzougaghene
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Institut Hospitalo-Universitaire (IHU)-Méditerranée Infection, Marseille, France
| | - Rezak Drali
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Institut Hospitalo-Universitaire (IHU)-Méditerranée Infection, Marseille, France
- Plateforme Génomique - Bioinformatique, Institut Pasteur d’Algérie, Rue du Petit Staouéli, Algiers, Algeria
| | | | - Bernard Davoust
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Institut Hospitalo-Universitaire (IHU)-Méditerranée Infection, Marseille, France
| | - Florence Fenollar
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Aix Marseille Univ, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Vecteurs – Infections Tropicales et Méditeranéennes (VITROME), Marseille, France
| | - Didier Raoult
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Institut Hospitalo-Universitaire (IHU)-Méditerranée Infection, Marseille, France
| | - Oleg Mediannikov
- Aix Marseille Univ Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (APHM), Microbes, Evolution (MEPHI), Phylogénie et Infection, Marseille, France
- Institut Hospitalo-Universitaire (IHU)-Méditerranée Infection, Marseille, France
- *Correspondence: Oleg Mediannikov,
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Vicente M, Lankheet I, Russell T, Hollfelder N, Coetzee V, Soodyall H, Jongh MD, Schlebusch CM. Male-biased migration from East Africa introduced pastoralism into southern Africa. BMC Biol 2021; 19:259. [PMID: 34872534 PMCID: PMC8650298 DOI: 10.1186/s12915-021-01193-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 11/12/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Hunter-gatherer lifestyles dominated the southern African landscape up to ~ 2000 years ago, when herding and farming groups started to arrive in the area. First, herding and livestock, likely of East African origin, appeared in southern Africa, preceding the arrival of the large-scale Bantu-speaking agro-pastoralist expansion that introduced West African-related genetic ancestry into the area. Present-day Khoekhoe-speaking Namaqua (or Nama in short) pastoralists show high proportions of East African admixture, linking the East African ancestry with Khoekhoe herders. Most other historical Khoekhoe populations have, however, disappeared over the last few centuries and their contribution to the genetic structure of present-day populations is not well understood. In our study, we analyzed genome-wide autosomal and full mitochondrial data from a population who trace their ancestry to the Khoekhoe-speaking Hessequa herders from the southern Cape region of what is now South Africa. RESULTS We generated genome-wide data from 162 individuals and mitochondrial DNA data of a subset of 87 individuals, sampled in the Western Cape Province, South Africa, where the Hessequa population once lived. Using available comparative data from Khoe-speaking and related groups, we aligned genetic date estimates and admixture proportions to the archaeological proposed dates and routes for the arrival of the East African pastoralists in southern Africa. We identified several Afro-Asiatic-speaking pastoralist groups from Ethiopia and Tanzania who share high affinities with the East African ancestry present in southern Africa. We also found that the East African pastoralist expansion was heavily male-biased, akin to a pastoralist migration previously observed on the genetic level in ancient Europe, by which Pontic-Caspian Steppe pastoralist groups represented by the Yamnaya culture spread across the Eurasian continent during the late Neolithic/Bronze Age. CONCLUSION We propose that pastoralism in southern Africa arrived through male-biased migration of an East African Afro-Asiatic-related group(s) who introduced new subsistence and livestock practices to local southern African hunter-gatherers. Our results add to the understanding of historical human migration and mobility in Africa, connected to the spread of food-producing and livestock practices.
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Affiliation(s)
- Mário Vicente
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
- Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
- Centre for Palaeogenetics, Stockholm, Sweden
| | - Imke Lankheet
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Thembi Russell
- School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg, South Africa
| | - Nina Hollfelder
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Vinet Coetzee
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Himla Soodyall
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Academy of Science of South Africa, Pretoria, South Africa
| | - Michael De Jongh
- Department of Anthropology and Archaeology, University of South Africa, Pretoria, South Africa
| | - Carina M Schlebusch
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden.
- Palaeo-Research Institute, University of Johannesburg, Johannesburg, South Africa.
- SciLife Lab, Uppsala, Sweden.
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30
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Trost B, Loureiro LO, Scherer SW. Discovery of genomic variation across a generation. Hum Mol Genet 2021; 30:R174-R186. [PMID: 34296264 PMCID: PMC8490016 DOI: 10.1093/hmg/ddab209] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/09/2021] [Accepted: 07/19/2021] [Indexed: 11/12/2022] Open
Abstract
Over the past 30 years (the timespan of a generation), advances in genomics technologies have revealed tremendous and unexpected variation in the human genome and have provided increasingly accurate answers to long-standing questions of how much genetic variation exists in human populations and to what degree the DNA complement changes between parents and offspring. Tracking the characteristics of these inherited and spontaneous (or de novo) variations has been the basis of the study of human genetic disease. From genome-wide microarray and next-generation sequencing scans, we now know that each human genome contains over 3 million single nucleotide variants when compared with the ~ 3 billion base pairs in the human reference genome, along with roughly an order of magnitude more DNA—approximately 30 megabase pairs (Mb)—being ‘structurally variable’, mostly in the form of indels and copy number changes. Additional large-scale variations include balanced inversions (average of 18 Mb) and complex, difficult-to-resolve alterations. Collectively, ~1% of an individual’s genome will differ from the human reference sequence. When comparing across a generation, fewer than 100 new genetic variants are typically detected in the euchromatic portion of a child’s genome. Driven by increasingly higher-resolution and higher-throughput sequencing technologies, newer and more accurate databases of genetic variation (for instance, more comprehensive structural variation data and phasing of combinations of variants along chromosomes) of worldwide populations will emerge to underpin the next era of discovery in human molecular genetics.
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Affiliation(s)
- Brett Trost
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Livia O Loureiro
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Stephen W Scherer
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada.,McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
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31
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Chattopadhyay A, Teoh ZH, Wu CY, Juang JMJ, Lai LC, Tsai MH, Wu CH, Lu TP, Chuang EY. CNVIntegrate: the first multi-ethnic database for identifying copy number variations associated with cancer. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2021; 2021:6321046. [PMID: 34259866 PMCID: PMC8278790 DOI: 10.1093/database/baab044] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/29/2021] [Accepted: 07/02/2021] [Indexed: 11/14/2022]
Abstract
Human copy number variations (CNVs) and copy number alterations (CNAs) are DNA segments (>1000 base pairs) of duplications or deletions with respect to the reference genome, potentially causing genomic imbalance leading to diseases such as cancer. CNVs further cause genetic diversity in healthy populations and are predominant drivers of gene/genome evolution. Initiatives have been taken by the research community to establish large-scale databases to comprehensively characterize CNVs in humans. Exome Aggregation Consortium (ExAC) is one such endeavor that catalogs CNVs, of nearly 60 000 healthy individuals across five demographic clusters. Furthermore, large projects such as the Catalogue of Somatic Mutations in Cancer (COSMIC) and the Cancer Cell Line Encyclopedia (CCLE) combine CNA data from cancer-affected individuals and large panels of human cancer cell lines, respectively. However, we lack a structured and comprehensive CNV/CNA resource including both healthy individuals and cancer patients across large populations. CNVIntegrate is the first web-based system that hosts CNV and CNA data from both healthy populations and cancer patients, respectively, and concomitantly provides statistical comparisons between copy number frequencies of multiple ethnic populations. It further includes, for the first time, well-cataloged CNV and CNA data from Taiwanese healthy individuals and Taiwan Breast Cancer data, respectively, along with imported resources from ExAC, COSMIC and CCLE. CNVIntegrate offers a CNV/CNA-data hub for structured information retrieval for clinicians and scientists towards important drug discoveries and precision treatments. Database URL: http://cnvintegrate.cgm.ntu.edu.tw/.
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Affiliation(s)
- Amrita Chattopadhyay
- Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Zi Han Teoh
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
| | - Chi-Yun Wu
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
| | - Jyh-Ming Jimmy Juang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei 10008, Taiwan.,College of Medicine, National Taiwan University, Taipei 10051, Taiwan
| | - Liang-Chuan Lai
- Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan.,Graduate Institute of Physiology, National Taiwan University, Taipei 10051, Taiwan
| | - Mong-Hsun Tsai
- Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan.,Institute of Biotechnology, National Taiwan University, Taipei 10672, Taiwan.,Center for Biotechnology, National Taiwan University, Taipei 10672, Taiwan
| | - Chia-Hsin Wu
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
| | - Tzu-Pin Lu
- Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan.,Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Eric Y Chuang
- Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.,Master Program for Biomedical Engineering, China Medical University, Taichung 40402, Taiwan
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32
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Kumar H, Panigrahi M, Saravanan KA, Rajawat D, Parida S, Bhushan B, Gaur GK, Dutt T, Mishra BP, Singh RK. Genome-wide detection of copy number variations in Tharparkar cattle. Anim Biotechnol 2021; 34:448-455. [PMID: 34191685 DOI: 10.1080/10495398.2021.1942027] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Copy number variations (CNVs) are major forms of genetic variation with an increasing importance in animal genomics. This study used the Illumina BovineSNP 50 K BeadChip to detect the genome-wide CNVs in the Tharparkar cattle. With the aid of PennCNV software, we noticed a total of 447 copy number variation regions (CNVRs) across the autosomal genome, occupying nearly 2.17% of the bovine genome. The average size of detected CNVRs was found to be 122.2 kb, the smallest CNVR being 50.02 kb in size, to the largest being 1,232.87 Kb. Enrichment analyses of the genes in these CNVRs gave significant associations with molecular adaptation-related Gene Ontology (GO) terms. Most CNVR genes were significantly enriched for specific biological functions; signaling pathways, sensory responses to stimuli, and various cellular processes. In addition, QTL analysis of CNVRs described them to be linked with economically essential traits in cattle. The findings here provide crucial information for constructing a more comprehensive CNVR map for the indigenous cattle genome.
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Affiliation(s)
- Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - K A Saravanan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Bareilly, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - G K Gaur
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Bareilly, India
| | - B P Mishra
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Bareilly, India
| | - R K Singh
- Division of Animal Biotechnology, ICAR-Indian Veterinary Research Institute, Bareilly, India
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33
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Koganebuchi K, Sato K, Fujii K, Kumabe T, Haneji K, Toma T, Ishida H, Joh K, Soejima H, Mano S, Ogawa M, Oota H. An analysis of the demographic history of the risk allele R4810K in RNF213 of moyamoya disease. Ann Hum Genet 2021; 85:166-177. [PMID: 34013582 PMCID: PMC8453937 DOI: 10.1111/ahg.12424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/07/2021] [Accepted: 04/08/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Ring finger protein 213 (RNF213) is a susceptibility gene of moyamoya disease (MMD). A previous case-control study and a family analysis demonstrated a strong association of the East Asian-specific variant, R4810K (rs112735431), with MMD. Our aim is to uncover evolutionary history of R4810K in East Asian populations. METHODS The RNF213 locus of 24 MMD patients in Japan were sequenced using targeted-capture sequencing. Based on the sequence data, we conducted population genetic analysis and estimated the age of R4810K using coalescent simulation. RESULTS The diversity of the RNF213 gene was higher in Africans than non-Africans, which can be explained by bottleneck effect of the out-of-Africa migration. Coalescent simulation showed that the risk variant was born in East Asia 14,500-5100 years ago and came to the Japanese archipelago afterward, probably in the period when the known migration based on archaeological evidences occurred. CONCLUSIONS Although clinical data show that the symptoms varies, all sequences harboring the risk allele are almost identical with a small number of exceptions, suggesting the MMD phenotypes are unaffected by the variants of this gene and rather would be more affected by environmental factors.
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Affiliation(s)
- Kae Koganebuchi
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Faculty of Medicine, Advanced Medical Research Center, University of the Ryukyus, Nishihara, Okinawa, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo, Japan
| | - Kimitoshi Sato
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Kiyotaka Fujii
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Toshihiro Kumabe
- Department of Neurosurgery, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Kuniaki Haneji
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Takashi Toma
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Hajime Ishida
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, Okinawa, Japan
| | - Keiichiro Joh
- Division of Molecular Genetics and Epigenetics, Faculty of Medicine, Department of Biomolecular Sciences, Saga University, Saga, Saga, Japan
| | - Hidenobu Soejima
- Division of Molecular Genetics and Epigenetics, Faculty of Medicine, Department of Biomolecular Sciences, Saga University, Saga, Saga, Japan
| | - Shuhei Mano
- Department of Mathematical Analysis and Statistical Inference, The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan
| | - Motoyuki Ogawa
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Department of Anatomy, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan
| | - Hiroki Oota
- Department of Biological Structure, Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, Japan.,Department of Anatomy, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan.,Department of Biological Sciences, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo, Japan
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Svensson E, Günther T, Hoischen A, Hervella M, Munters AR, Ioana M, Ridiche F, Edlund H, van Deuren RC, Soficaru A, de-la-Rua C, Netea MG, Jakobsson M. Genome of Peştera Muierii skull shows high diversity and low mutational load in pre-glacial Europe. Curr Biol 2021; 31:2973-2983.e9. [PMID: 34010592 DOI: 10.1016/j.cub.2021.04.045] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 04/09/2021] [Accepted: 04/19/2021] [Indexed: 11/24/2022]
Abstract
Few complete human genomes from the European Early Upper Palaeolithic (EUP) have been sequenced. Using novel sampling and DNA extraction approaches, we sequenced the genome of a woman from "Peştera Muierii," Romania who lived ∼34,000 years ago to 13.5× coverage. The genome shows similarities to modern-day Europeans, but she is not a direct ancestor. Although her cranium exhibits both modern human and Neanderthal features, the genome shows similar levels of Neanderthal admixture (∼3.1%) to most EUP humans but only half compared to the ∼40,000-year-old Peştera Oase 1. All EUP European hunter-gatherers display high genetic diversity, demonstrating that the severe loss of diversity occurred during and after the Last Glacial Maximum (LGM) rather than just during the out-of-Africa migration. The prevalence of genetic diseases is expected to increase with low diversity; however, pathogenic variant load was relatively constant from EUP to modern times, despite post-LGM hunter-gatherers having the lowest diversity ever observed among Europeans.
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Affiliation(s)
- Emma Svensson
- Human Evolution, Department of Organismal Biology, Uppsala University, 752 36 Uppsala, Sweden
| | - Torsten Günther
- Human Evolution, Department of Organismal Biology, Uppsala University, 752 36 Uppsala, Sweden.
| | - Alexander Hoischen
- Department of Human Genetics, Radboud University Medical Center, 6526 Nijmegen, the Netherlands; Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, 6526 Nijmegen, the Netherlands
| | - Montserrat Hervella
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), B° Sarriena s/n 48940 Leioa, Bizkaia, Spain
| | - Arielle R Munters
- Human Evolution, Department of Organismal Biology, Uppsala University, 752 36 Uppsala, Sweden
| | - Mihai Ioana
- Laboratory of Human Genetics, University of Medicine and Pharmacy, Craiova, Romania
| | | | - Hanna Edlund
- Human Evolution, Department of Organismal Biology, Uppsala University, 752 36 Uppsala, Sweden
| | - Rosanne C van Deuren
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, 6526 Nijmegen, the Netherlands
| | - Andrei Soficaru
- "Francisc J. Rainer" Institute of Anthropology, Romanian Academy, 050474 Bucharest, Romania
| | - Concepción de-la-Rua
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), B° Sarriena s/n 48940 Leioa, Bizkaia, Spain
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, 6526 Nijmegen, the Netherlands; Laboratory of Human Genetics, University of Medicine and Pharmacy, Craiova, Romania
| | - Mattias Jakobsson
- Human Evolution, Department of Organismal Biology, Uppsala University, 752 36 Uppsala, Sweden.
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35
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Carress H, Lawson DJ, Elhaik E. Population genetic considerations for using biobanks as international resources in the pandemic era and beyond. BMC Genomics 2021; 22:351. [PMID: 34001009 PMCID: PMC8127217 DOI: 10.1186/s12864-021-07618-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 04/14/2021] [Indexed: 12/11/2022] Open
Abstract
The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts.
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Affiliation(s)
- Hannah Carress
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
| | - Daniel John Lawson
- School of Mathematics and Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK. .,Department of Biology, Lund University, Lund, Sweden.
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36
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Hollfelder N, Breton G, Sjödin P, Jakobsson M. The deep population history in Africa. Hum Mol Genet 2021; 30:R2-R10. [PMID: 33438014 PMCID: PMC8117439 DOI: 10.1093/hmg/ddab005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 12/28/2022] Open
Abstract
Africa is the continent with the greatest genetic diversity among humans and the level of diversity is further enhanced by incorporating non-majority groups, which are often understudied. Many of today's minority populations historically practiced foraging lifestyles, which were the only subsistence strategies prior to the rise of agriculture and pastoralism, but only a few groups practicing these strategies remain today. Genomic investigations of Holocene human remains excavated across the African continent show that the genetic landscape was vastly different compared to today's genetic landscape and that many groups that today are population isolate inhabited larger regions in the past. It is becoming clear that there are periods of isolation among groups and geographic areas, but also genetic contact over large distances throughout human history in Africa. Genomic information from minority populations and from prehistoric remains provide an invaluable source of information on the human past, in particular deep human population history, as Holocene large-scale population movements obscure past patterns of population structure. Here we revisit questions on the nature and time of the radiation of early humans in Africa, the extent of gene-flow among human populations as well as introgression from archaic and extinct lineages on the continent.
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Affiliation(s)
- Nina Hollfelder
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Gwenna Breton
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Per Sjödin
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Mattias Jakobsson
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
- Palaeo-Research Institute, University of Johannesburg, Physical, Cnr Kingsway & University Roads, Auckland Park, Johannesburg 2092, South Africa
- SciLifeLab, Stockholm and Uppsala, Entrance C11, BMC, Husargatan 3, 752 37 Uppsala, Sweden
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37
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Harris AM, DeGiorgio M. A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data. Mol Biol Evol 2021; 37:3023-3046. [PMID: 32392293 PMCID: PMC7530616 DOI: 10.1093/molbev/msaa115] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.
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Affiliation(s)
- Alexandre M Harris
- Department of Biology, Pennsylvania State University, University Park, PA.,Molecular, Cellular, and Integrative Biosciences, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL
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38
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Lucek K, Willi Y. Drivers of linkage disequilibrium across a species' geographic range. PLoS Genet 2021; 17:e1009477. [PMID: 33770075 PMCID: PMC8026057 DOI: 10.1371/journal.pgen.1009477] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 04/07/2021] [Accepted: 03/09/2021] [Indexed: 11/25/2022] Open
Abstract
While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system. Nearby genomic variants are often co-inherited because of limited recombination. The extent of non-random association of alleles at different loci is called linkage disequilibrium (LD) and is commonly used in genomic analyses, for example to detect regions under selection or to determine effective population size. Here we reversed testing and addressed how demographic history may affect LD within a species. Using genomic data from more than a thousand individuals of North American Arabidopsis lyrata from across the entire species’ range, we quantified the effect of postglacial range expansion and a shift in mating system from outcrossing to selfing on LD. We show that both factors lead to increased LD, and that the maximal effect of range expansion is comparable with a shift in mating system to selfing. Heightened LD involves deleterious mutations, and therefore, LD can also serve as an indicator of mutation accumulation. Furthermore, we provide evidence that some genes experienced stronger increases in LD possibly due to selection associated with the two demographic changes. Our results provide a novel and broad view on the evolutionary factors shaping LD that may also apply to the very many species that underwent postglacial range expansion.
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Affiliation(s)
- Kay Lucek
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
- * E-mail:
| | - Yvonne Willi
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
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39
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Pharmacogenomics of thiopurines: distribution of TPMT and NUDT15 polymorphisms in the Brazilian Amazon. Pharmacogenet Genomics 2021; 30:184-189. [PMID: 32453263 DOI: 10.1097/fpc.0000000000000411] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Reduced function alleles in the TPMT and NUDT15 genes are risk factors for thiopurine toxicity. This study evaluated the influence of Native ancestry on the distribution of TPMT (rs1142345, rs1800460 and rs1800462) and NUDT15 (rs116855232) polymorphisms and compound metabolic phenotypes in 128 healthy males from the Brazilian Amazon. The average proportion of Native and European ancestry differed greatly and significantly between self-declared Amerindians and non-Amerindians, although extensive admixture in both groups was evident. Native ancestry was not significantly associated with the frequency distribution of the TPMT or NUDT15 polymorphisms investigated. The apparent discrepancy with our previous results for NUDT15 rs116855232 in the Ad Mixed American superpopulation of the 1000 Genomes Project is ascribed to the diversity of the Native populations of the Americas. Based on the inferred TPMT/NUDT15 compound metabolic phenotypes, the Clinical Pharmacogenetics Implementation Consortium recommendations for starting thiopurine therapy with reduced doses or to consider dose reduction applied respectively to 3-5% and to 12-20% of the study cohorts.
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40
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Borrell LN, Elhawary JR, Fuentes-Afflick E, Witonsky J, Bhakta N, Wu AHB, Bibbins-Domingo K, Rodríguez-Santana JR, Lenoir MA, Gavin JR, Kittles RA, Zaitlen NA, Wilkes DS, Powe NR, Ziv E, Burchard EG. Race and Genetic Ancestry in Medicine - A Time for Reckoning with Racism. N Engl J Med 2021; 384:474-480. [PMID: 33406325 PMCID: PMC8979367 DOI: 10.1056/nejmms2029562] [Citation(s) in RCA: 367] [Impact Index Per Article: 122.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Luisa N Borrell
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Jennifer R Elhawary
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Elena Fuentes-Afflick
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Jonathan Witonsky
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Nirav Bhakta
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Alan H B Wu
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Kirsten Bibbins-Domingo
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - José R Rodríguez-Santana
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Michael A Lenoir
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - James R Gavin
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Rick A Kittles
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Noah A Zaitlen
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - David S Wilkes
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Neil R Powe
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Elad Ziv
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
| | - Esteban G Burchard
- From the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York (L.N.B.); the Departments of Medicine (J.R.E., J.W., N.B., N.R.P., E.Z., E.G.B.), Pediatrics (E.F.-A., J.W.), Laboratory Medicine (A.H.B.W.), and Epidemiology and Biostatistics (K.B.-D.), Priscilla Chan and Mark Zuckerberg San Francisco General Hospital (K.B.-D., N.R.P.), the Division of General Internal Medicine and the Institute of Human Genetics, Helen Diller Family Comprehensive Cancer Center (E.Z.), and the Department of Bioengineering and Therapeutic Sciences (E.G.B.), University of California, San Francisco, San Francisco, Bay Area Pediatrics, Oakland (M.A.L.), the Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte (R.A.K.), and the Department of Neurogenetics, University of California, Los Angeles, Los Angeles (N.A.Z.) - all in California; the Centro de Neumología Pediátrica, San Juan, PR (J.R.R.-S.); Emory University School of Medicine, Atlanta (J.R.G.); and the School of Medicine, University of Virginia, Charlottesville (D.S.W.)
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41
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Sarihan EI, Pérez-Palma E, Niestroj LM, Loesch D, Inca-Martinez M, Horimoto AR, Cornejo-Olivas M, Torres L, Mazzetti P, Cosentino C, Sarapura-Castro E, Rivera-Valdivia A, Dieguez E, Raggio V, Lescano A, Tumas V, Borges V, Ferraz HB, Rieder CR, Schumacher-Schuh AF, Santos-Lobato BL, Velez-Pardo C, Jimenez-Del-Rio M, Lopera F, Moreno S, Chana-Cuevas P, Fernandez W, Arboleda G, Arboleda H, Arboleda-Bustos CE, Yearout D, Zabetian CP, Thornton TA, O’Connor TD, Lal D, Mata IF. Genome-Wide Analysis of Copy Number Variation in Latin American Parkinson's Disease Patients. Mov Disord 2021; 36:434-441. [PMID: 33150996 PMCID: PMC8059262 DOI: 10.1002/mds.28353] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/01/2020] [Accepted: 09/10/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Parkinson's disease is the second most common neurodegenerative disorder and affects people from all ethnic backgrounds, yet little is known about the genetics of Parkinson's disease in non-European populations. In addition, the overall identification of copy number variants at a genome-wide level has been understudied in Parkinson's patients. The objective of this study was to understand the genome-wide burden of copy number variants in Latinos and its association with Parkinson's disease. METHODS We used genome-wide genotyping data from 747 Parkinson's disease patients and 632 controls from the Latin American Research Consortium on the Genetics of Parkinson's disease. RESULTS Genome-wide copy number burden analysis showed that patients were significantly enriched for copy number variants overlapping known Parkinson's disease genes compared with controls (odds ratio, 3.97; 95%CI, 1.69-10.5; P = 0.018). PRKN showed the strongest copy number burden, with 20 copy number variant carriers. These patients presented an earlier age of disease onset compared with patients with other copy number variants (median age at onset, 31 vs 57 years, respectively; P = 7.46 × 10-7 ). CONCLUSIONS We found that although overall genome-wide copy number variant burden was not significantly different, Parkinson's disease patients were significantly enriched with copy number variants affecting known Parkinson's disease genes. We also identified that of 250 patients with early-onset disease, 5.6% carried a copy number variant on PRKN in our cohort. Our study is the first to analyze genome-wide copy number variant association in Latino Parkinson's disease patients and provides insights about this complex disease in this understudied population. © 2020 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Elif Irem Sarihan
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Eduardo Pérez-Palma
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | | | - Douglas Loesch
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Miguel Inca-Martinez
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Andrea R.V.R. Horimoto
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Mario Cornejo-Olivas
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurologicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Luis Torres
- Movement Disorders Unit, Instituto Nacional de Ciencias Neurologicas, Lima, Peru
- School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Pilar Mazzetti
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurologicas, Lima, Peru
- School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Carlos Cosentino
- Movement Disorders Unit, Instituto Nacional de Ciencias Neurologicas, Lima, Peru
- School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | | | | | - Elena Dieguez
- Neurology Institute, Universidad de la República, Montevideo, Uruguay
| | - Victor Raggio
- Department of Genetics, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Andres Lescano
- Neurology Institute, Universidad de la República, Montevideo, Uruguay
| | - Vitor Tumas
- Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Vanderci Borges
- Movement Disorders Unit, Department of Neurology and Neurosurgery, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Henrique B. Ferraz
- Movement Disorders Unit, Department of Neurology and Neurosurgery, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Carlos R. Rieder
- Departamento de Neurologia, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
| | - Artur F. Schumacher-Schuh
- Serviço de Neurologia, Hospital de Clínicas de Porto Alegre and Departamento de Farmacologia Universidade Federal do Rio Grande do Su, Porto Alegre, Brazil
| | | | - Carlos Velez-Pardo
- Neuroscience Research Group, Medical Research Institute, Faculty of Medicine, Universidad de Antioquia (UdeA), Medellín, Colombia
| | - Marlene Jimenez-Del-Rio
- Neuroscience Research Group, Medical Research Institute, Faculty of Medicine, Universidad de Antioquia (UdeA), Medellín, Colombia
| | - Francisco Lopera
- Neuroscience Research Group, Medical Research Institute, Faculty of Medicine, Universidad de Antioquia (UdeA), Medellín, Colombia
| | - Sonia Moreno
- Neuroscience Research Group, Medical Research Institute, Faculty of Medicine, Universidad de Antioquia (UdeA), Medellín, Colombia
| | - Pedro Chana-Cuevas
- CETRAM, Facultad de Ciencias Medicas, Universidad de Santiago de Chile, Santiago de Chile, Chile
| | - William Fernandez
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Gonzalo Arboleda
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Humberto Arboleda
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Carlos E. Arboleda-Bustos
- Neuroscience and Cell Death Research Groups, Medical School and Genetic Institute, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Dora Yearout
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Neurology, University of Washington, Seattle, Washington, USA
| | - Cyrus P. Zabetian
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Neurology, University of Washington, Seattle, Washington, USA
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Timothy D. O’Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Dennis Lal
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, Ohio, USA
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
- Stanley Center for Psychiatric Research, Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA
- Epilepsy Center & Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ignacio F. Mata
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, Ohio, USA
- Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Neurology, University of Washington, Seattle, Washington, USA
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42
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Bergström A, Stringer C, Hajdinjak M, Scerri EML, Skoglund P. Origins of modern human ancestry. Nature 2021; 590:229-237. [PMID: 33568824 DOI: 10.1038/s41586-021-03244-5] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 12/14/2020] [Indexed: 01/30/2023]
Abstract
New finds in the palaeoanthropological and genomic records have changed our view of the origins of modern human ancestry. Here we review our current understanding of how the ancestry of modern humans around the globe can be traced into the deep past, and which ancestors it passes through during our journey back in time. We identify three key phases that are surrounded by major questions, and which will be at the frontiers of future research. The most recent phase comprises the worldwide expansion of modern humans between 40 and 60 thousand years ago (ka) and their last known contacts with archaic groups such as Neanderthals and Denisovans. The second phase is associated with a broadly construed African origin of modern human diversity between 60 and 300 ka. The oldest phase comprises the complex separation of modern human ancestors from archaic human groups from 0.3 to 1 million years ago. We argue that no specific point in time can currently be identified at which modern human ancestry was confined to a limited birthplace, and that patterns of the first appearance of anatomical or behavioural traits that are used to define Homo sapiens are consistent with a range of evolutionary histories.
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Affiliation(s)
- Anders Bergström
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK
| | - Chris Stringer
- Department of Earth Sciences, Natural History Museum, London, UK.
| | - Mateja Hajdinjak
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK
| | - Eleanor M L Scerri
- Pan-African Evolution Research Group, Max Planck Institute for Science of Human History, Jena, Germany.,Department of Classics and Archaeology, University of Malta, Msida, Malta.,Institute of Prehistoric Archaeology, University of Cologne, Cologne, Germany
| | - Pontus Skoglund
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK.
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43
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Romdhane L, Mezzi N, Dallali H, Messaoud O, Shan J, Fakhro KA, Kefi R, Chouchane L, Abdelhak S. A map of copy number variations in the Tunisian population: a valuable tool for medical genomics in North Africa. NPJ Genom Med 2021; 6:3. [PMID: 33420067 PMCID: PMC7794582 DOI: 10.1038/s41525-020-00166-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 11/18/2020] [Indexed: 11/24/2022] Open
Abstract
Copy number variation (CNV) is considered as the most frequent type of structural variation in the human genome. Some CNVs can act on human phenotype diversity, encompassing rare Mendelian diseases and genomic disorders. The North African populations remain underrepresented in public genetic databases in terms of single-nucleotide variants as well as for larger genomic mutations. In this study, we present the first CNV map for a North African population using the Affymetrix Genome-Wide SNP (single-nucleotide polymorphism) array 6.0 array genotyping intensity data to call CNVs in 102 Tunisian healthy individuals. Two softwares, PennCNV and Birdsuite, were used to call CNVs in order to provide reliable data. Subsequent bioinformatic analyses were performed to explore their features and patterns. The CNV map of the Tunisian population includes 1083 CNVs spanning 61.443 Mb of the genome. The CNV length ranged from 1.017 kb to 2.074 Mb with an average of 56.734 kb. Deletions represent 57.43% of the identified CNVs, while duplications and the mixed loci are less represented. One hundred and three genes disrupted by CNVs are reported to cause 155 Mendelian diseases/phenotypes. Drug response genes were also reported to be affected by CNVs. Data on genes overlapped by deletions and duplications segments and the sequence properties in and around them also provided insights into the functional and health impacts of CNVs. These findings represent valuable clues to genetic diversity and personalized medicine in the Tunisian population as well as in the ethnically similar populations from North Africa.
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Affiliation(s)
- Lilia Romdhane
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia.
- Department of Biology, Faculty of Science of Bizerte, Jarzouna, Tunisia.
| | - Nessrine Mezzi
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia
| | - Hamza Dallali
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia
| | - Olfa Messaoud
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia
| | - Jingxuan Shan
- Department of Genetic Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY, USA
- Genetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar
| | - Khalid A Fakhro
- Department of Genetic Medicine, Weill Cornell Medical College in Qatar, Doha, Qatar
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | - Rym Kefi
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia
| | - Lotfi Chouchane
- Department of Genetic Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY, USA
- Genetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar
| | - Sonia Abdelhak
- Biomedical Genomics and Oncogenetics Laboratory (LR16IPT05), Institut Pasteur de Tunis, Tunis, Tunisia
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44
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Unal-Aydin P, Aydin O, Arslan A. Genetic Architecture of Depression: Where Do We Stand Now? ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:203-230. [PMID: 33834402 DOI: 10.1007/978-981-33-6044-0_12] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The research of depression genetics has been occupied by historical candidate genes which were tested by candidate gene association studies. However, these studies were mostly not replicable. Thus, genetics of depression have remained elusive for a long time. As research moves from candidate gene association studies to GWAS, the hypothesis-free non-candidate gene association studies in genome-wide level, this trend will likely change. Despite the fact that the earlier GWAS of depression were not successful, the recent GWAS suggest robust findings for depression genetics. These altogether will catalyze a new wave of multidisciplinary research to pin down the neurobiology of depression.
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Affiliation(s)
- Pinar Unal-Aydin
- Psychology Program, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina
| | - Orkun Aydin
- Psychology Program, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina
| | - Ayla Arslan
- School of Advanced Studies, University of Tyumen, Tyumen, Russia.
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45
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Sarovic D. A Unifying Theory for Autism: The Pathogenetic Triad as a Theoretical Framework. Front Psychiatry 2021; 12:767075. [PMID: 34867553 PMCID: PMC8637925 DOI: 10.3389/fpsyt.2021.767075] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 10/27/2021] [Indexed: 12/27/2022] Open
Abstract
This paper presents a unifying theory for autism by applying the framework of a pathogenetic triad to the scientific literature. It proposes a deconstruction of autism into three contributing features (an autistic personality dimension, cognitive compensation, and neuropathological risk factors), and delineates how they interact to cause a maladaptive behavioral phenotype that may require a clinical diagnosis. The autistic personality represents a common core condition, which induces a set of behavioral issues when pronounced. These issues are compensated for by cognitive mechanisms, allowing the individual to remain adaptive and functional. Risk factors, both exogenous and endogenous ones, show pathophysiological convergence through their negative effects on neurodevelopment. This secondarily affects cognitive compensation, which disinhibits a maladaptive behavioral phenotype. The triad is operationalized and methods for quantification are presented. With respect to the breadth of findings in the literature that it can incorporate, it is the most comprehensive model yet for autism. Its main implications are that (1) it presents the broader autism phenotype as a non-pathological core personality domain, which is shared across the population and uncoupled from associated features such as low cognitive ability and immune dysfunction, (2) it proposes that common genetic variants underly the personality domain, and that rare variants act as risk factors through negative effects on neurodevelopment, (3) it outlines a common pathophysiological mechanism, through inhibition of neurodevelopment and cognitive dysfunction, by which a wide range of endogenous and exogenous risk factors lead to autism, and (4) it suggests that contributing risk factors, and findings of immune and autonomic dysfunction are clinically ascertained rather than part of the core autism construct.
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Affiliation(s)
- Darko Sarovic
- Gillberg Neuropsychiatry Centre, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden.,MedTech West, Gothenburg, Sweden
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46
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Biddanda A, Rice DP, Novembre J. A variant-centric perspective on geographic patterns of human allele frequency variation. eLife 2020; 9:60107. [PMID: 33350384 PMCID: PMC7755386 DOI: 10.7554/elife.60107] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 11/12/2020] [Indexed: 12/14/2022] Open
Abstract
A key challenge in human genetics is to understand the geographic distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, drawing inferences over many variants. Here, we introduce an alternative representation of genetic variation that reveals the relative abundance of different allele frequency patterns. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are found globally, regardless of whether the individuals are from the same region or different regions. Our variant-centric visualization clarifies the geographic patterns of human variation and can help address misconceptions about genetic differentiation among populations.
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Affiliation(s)
- Arjun Biddanda
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - Daniel P Rice
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, United States
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47
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Gene Copy Number Variation Does Not Reflect Structure or Environmental Selection in Two Recently Diverged California Populations of Suillus brevipes. G3 (BETHESDA, MD.) 2020; 10:4591-4597. [PMID: 33051263 PMCID: PMC7718732 DOI: 10.1534/g3.120.401735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Gene copy number variation across individuals has been shown to track population structure and be a source of adaptive genetic variation with significant fitness impacts. In this study, we report opposite results for both predictions based on the analysis of gene copy number variants (CNVs) of Suillus brevipes, a mycorrhizal fungus adapted to coastal and montane habitats in California. In order to assess whether gene copy number variation mirrored population structure and selection in this species, we investigated two previously studied locally adapted populations showing a highly differentiated genomic region encompassing a gene predicted to confer salt tolerance. In addition, we examined whether copy number in the genes related to salt homeostasis was differentiated between the two populations. Although we found many instances of CNV regions across the genomes of S. brevipes individuals, we also found CNVs did not recover population structure and known salt-tolerance-related genes were not under selection across the coastal population. Our results contrast with predictions of CNVs matching single-nucleotide polymorphism divergence and showed CNVs of genes for salt homeostasis are not under selection in S. brevipes.
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48
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Walsh S, Izquierdo-Serra M, Acosta S, Edo A, Lloret M, Moret R, Bosch E, Oliva B, Bertranpetit J, Fernández-Fernández JM. Adaptive selection drives TRPP3 loss-of-function in an Ethiopian population. Sci Rep 2020; 10:20999. [PMID: 33268808 PMCID: PMC7710729 DOI: 10.1038/s41598-020-78081-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 11/20/2020] [Indexed: 11/15/2022] Open
Abstract
TRPP3 (also called PKD2L1) is a nonselective, cation-permeable channel activated by multiple stimuli, including extracellular pH changes. TRPP3 had been considered a candidate for sour sensor in humans, due to its high expression in a subset of tongue receptor cells detecting sour, along with its membership to the TRP channel family known to function as sensory receptors. Here, we describe the functional consequences of two non-synonymous genetic variants (R278Q and R378W) found to be under strong positive selection in an Ethiopian population, the Gumuz. Electrophysiological studies and 3D modelling reveal TRPP3 loss-of-functions produced by both substitutions. R278Q impairs TRPP3 activation after alkalinisation by mislocation of H+ binding residues at the extracellular polycystin mucolipin domain. R378W dramatically reduces channel activity by altering conformation of the voltage sensor domain and hampering channel transition from closed to open state. Sour sensitivity tests in R278Q/R378W carriers argue against both any involvement of TRPP3 in sour detection and the role of such physiological process in the reported evolutionary positive selection past event.
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Affiliation(s)
- Sandra Walsh
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Mercè Izquierdo-Serra
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Sandra Acosta
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Albert Edo
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - María Lloret
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Roser Moret
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), 43206, Reus, Spain
| | - Baldo Oliva
- Structural Bioinformatics Lab, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain.
| | - José Manuel Fernández-Fernández
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain.
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49
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El Bitar F, Al Sudairy N, Qadi N, Al Rajeh S, Alghamdi F, Al Amari H, Al Dawsari G, Alsubaie S, Al Sudairi M, Abdulaziz S, Al Tassan N. A Comprehensive Analysis of Unique and Recurrent Copy Number Variations in Alzheimer's Disease and its Related Disorders. Curr Alzheimer Res 2020; 17:926-938. [PMID: 33256577 DOI: 10.2174/1567205017666201130111424] [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: 04/25/2020] [Revised: 08/20/2020] [Accepted: 10/29/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Copy number variations (CNVs) play an important role in the genetic etiology of various neurological disorders, including Alzheimer's disease (AD). Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) were shown to have share mechanisms and signaling pathways with AD. OBJECTIVE We aimed to assess CNVs regions that may harbor genes contributing to AD, T2DM, and MDD in 67 Saudi familial and sporadic AD patients, with no alterations in the known genes of AD and genotyped previously for APOE. METHODS DNA was analyzed using the CytoScan-HD array. Two layers of filtering criteria were applied. All the identified CNVs were checked in the Database of Genomic Variants (DGV). RESULTS A total of 1086 CNVs (565 gains and 521 losses) were identified in our study. We found 73 CNVs harboring genes that may be associated with AD, T2DM or MDD. Nineteen CNVs were novel. Most importantly, 42 CNVs were unique in our studied cohort existing only in one patient. Two large gains on chromosomes 1 and 13 harbored genes implicated in the studied disorders. We identified CNVs in genes that encode proteins involved in the metabolism of amyloid-β peptide (AGRN, APBA2, CR1, CR2, IGF2R, KIAA0125, MBP, RER1, RTN4R, VDR and WISPI) or Tau proteins (CACNAIC, CELF2, DUSP22, HTRA1 and SLC2A14). CONCLUSION The present work provided information on the presence of CNVs related to AD, T2DM, and MDD in Saudi Alzheimer's patients.
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Affiliation(s)
- Fadia El Bitar
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Nourah Al Sudairy
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Najeeb Qadi
- Department of Neurosciences, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | | | - Fatimah Alghamdi
- Institute of Biology and Environmental Research, National Center for Biotechnology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Hala Al Amari
- Institute of Biology and Environmental Research, National Center for Biotechnology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Ghadeer Al Dawsari
- Institute of Biology and Environmental Research, National Center for Genomics Technology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Sahar Alsubaie
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Mishael Al Sudairi
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sara Abdulaziz
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Nada Al Tassan
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
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50
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Graffelman J. Goodness-of-fit filtering in classical metric multidimensional scaling with large datasets. J Appl Stat 2020; 47:2011-2024. [PMID: 33041421 DOI: 10.1080/02664763.2019.1702929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Metric multidimensional scaling (MDS) is a widely used multivariate method with applications in almost all scientific disciplines. Eigenvalues obtained in the analysis are usually reported in order to calculate the overall goodness-of-fit of the distance matrix. In this paper, we refine MDS goodness-of-fit calculations, proposing additional point and pairwise goodness-of-fit statistics that can be used to filter poorly represented observations in MDS maps. The proposed statistics are especially relevant for large data sets that contain outliers, with typically many poorly fitted observations, and are helpful for improving MDS output and emphasising the most important features of the dataset. Several goodness-of-fit statistics are considered, and both Euclidean and non-Euclidean distance matrices are considered. Some examples with data from demographic, genetic and geographic studies are shown.
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Affiliation(s)
- Jan Graffelman
- Department of Statistics and Operations Research, Universitat Politècnica de Catalunya.,Department of Biostatistics, University of Washington
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