1
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Gerard D. Bayesian tests for random mating in polyploids. Mol Ecol Resour 2023; 23:1812-1822. [PMID: 37578636 DOI: 10.1111/1755-0998.13856] [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: 09/02/2022] [Revised: 07/24/2023] [Accepted: 08/03/2023] [Indexed: 08/15/2023]
Abstract
Hardy-Weinberg proportions (HWP) are often explored to evaluate the assumption of random mating. However, in autopolyploids, organisms with more than two sets of homologous chromosomes, HWP and random mating are different hypotheses that require different statistical testing approaches. Currently, the only available methods to test for random mating in autopolyploids (i) heavily rely on asymptotic approximations and (ii) assume genotypes are known, ignoring genotype uncertainty. Furthermore, these approaches are all frequentist, and so do not carry the benefits of Bayesian analysis, including ease of interpretability, incorporation of prior information, and consistency under the null. Here, we present Bayesian approaches to test for random mating, bringing the benefits of Bayesian analysis to this problem. Our Bayesian methods also (i) do not rely on asymptotic approximations, being appropriate for small sample sizes, and (ii) optionally account for genotype uncertainty via genotype likelihoods. We validate our methods in simulations and demonstrate on two real datasets how testing for random mating is more useful for detecting genotyping errors than testing for HWP (in a natural population) and testing for Mendelian segregation (in an experimental S1 population). Our methods are implemented in Version 2.0.2 of the hwep R package on the Comprehensive R Archive Network https://cran.r-project.org/package=hwep.
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Affiliation(s)
- David Gerard
- Department of Mathematics and Statistics, American University, Washington DC, USA
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2
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Antinucci M, Comas D, Calafell F. Population history modulates the fitness effects of Copy Number Variation in the Roma. Hum Genet 2023; 142:1327-1343. [PMID: 37311904 PMCID: PMC10449987 DOI: 10.1007/s00439-023-02579-5] [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: 04/17/2023] [Accepted: 06/02/2023] [Indexed: 06/15/2023]
Abstract
We provide the first whole genome Copy Number Variant (CNV) study addressing Roma, along with reference populations from South Asia, the Middle East and Europe. Using CNV calling software for short-read sequence data, we identified 3171 deletions and 489 duplications. Taking into account the known population history of the Roma, as inferred from whole genome nucleotide variation, we could discern how this history has shaped CNV variation. As expected, patterns of deletion variation, but not duplication, in the Roma followed those obtained from single nucleotide polymorphisms (SNPs). Reduced effective population size resulting in slightly relaxed natural selection may explain our observation of an increase in intronic (but not exonic) deletions within Loss of Function (LoF)-intolerant genes. Over-representation analysis for LoF-intolerant gene sets hosting intronic deletions highlights a substantial accumulation of shared biological processes in Roma, intriguingly related to signaling, nervous system and development features, which may be related to the known profile of private disease in the population. Finally, we show the link between deletions and known trait-related SNPs reported in the genome-wide association study (GWAS) catalog, which exhibited even frequency distributions among the studied populations. This suggests that, in general human populations, the strong association between deletions and SNPs associated to biomedical conditions and traits could be widespread across continental populations, reflecting a common background of potentially disease/trait-related CNVs.
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Affiliation(s)
- Marco Antinucci
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - David Comas
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Francesc Calafell
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
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3
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Parejo M, Talenti A, Richardson M, Vignal A, Barnett M, Wragg D. AmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap. Sci Data 2023; 10:198. [PMID: 37037860 PMCID: PMC10086014 DOI: 10.1038/s41597-023-02097-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/22/2023] [Indexed: 04/12/2023] Open
Abstract
Honey bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen's alleles and none from the many drones she mated with. Thus the ordered combination or 'phase' of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses.
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Affiliation(s)
- M Parejo
- Applied Genomics and Bioinformatics, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - A Talenti
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, UK
| | - M Richardson
- University of Edinburgh, King's Buildings Campus, Edinburgh, UK
- Beebytes Analytics CIC, Roslin Innovation Centre, Easter Bush Campus, Midlothian, UK
| | - A Vignal
- GenPhySE, Université de Toulouse, INRAE, INPT, INP-ENVT, 31326, Castanet Tolosan, France
| | - M Barnett
- Beebytes Analytics CIC, Roslin Innovation Centre, Easter Bush Campus, Midlothian, UK
| | - D Wragg
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, UK.
- Beebytes Analytics CIC, Roslin Innovation Centre, Easter Bush Campus, Midlothian, UK.
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4
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Cruz A, Sedano J, Burgos A, Gutiérrez JP, Wurzinger M, Gutiérrez-Reynoso G. Genomic selection improves genetic gain for fiber traits in a breeding program for alpacas. Livest Sci 2023. [DOI: 10.1016/j.livsci.2023.105195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
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5
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Dapas M, Thompson EE, Wentworth-Sheilds W, Clay S, Visness CM, Calatroni A, Sordillo JE, Gold DR, Wood RA, Makhija M, Khurana Hershey GK, Sherenian MG, Gruchalla RS, Gill MA, Liu AH, Kim H, Kattan M, Bacharier LB, Rastogi D, Altman MC, Busse WW, Becker PM, Nicolae D, O’Connor GT, Gern JE, Jackson DJ, Ober C. Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings. PLoS Genet 2023; 19:e1010594. [PMID: 36638096 PMCID: PMC9879483 DOI: 10.1371/journal.pgen.1010594] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 01/26/2023] [Accepted: 12/23/2022] [Indexed: 01/14/2023] Open
Abstract
Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06-0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.
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Affiliation(s)
- Matthew Dapas
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | - Emma E. Thompson
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | | | - Selene Clay
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | | | | | - Joanne E. Sordillo
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Robert A. Wood
- Department of Pediatrics, Johns Hopkins University Medical Center, Baltimore, Maryland, United States of America
| | - Melanie Makhija
- Division of Allergy and Immunology, Ann & Robert H. Lurie Children’s Hospital, Chicago, Illinois, United States of America
| | - Gurjit K. Khurana Hershey
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Michael G. Sherenian
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Rebecca S. Gruchalla
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Michelle A. Gill
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Andrew H. Liu
- Department of Allergy and Immunology, Children’s Hospital Colorado, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Haejin Kim
- Department of Medicine, Henry Ford Health System, Detroit, Michigan, United States of America
| | - Meyer Kattan
- Columbia University College of Physicians and Surgeons, New York, New York, United States of America
| | - Leonard B. Bacharier
- Monroe Carell Jr. Children’s Hospital at Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Deepa Rastogi
- Children’s National Health System, Washington, District of Columbia, United States of America
| | - Matthew C. Altman
- Department of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, United States of America
| | - William W. Busse
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Patrice M. Becker
- National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, United States of America
| | - Dan Nicolae
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - George T. O’Connor
- Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - James E. Gern
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Daniel J. Jackson
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
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6
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Alvarado AT, Muñoz AM, Bartra MS, Valderrama-Wong M, González D, Quiñones LA, Varela N, Bendezú MR, García JA, Loja-Herrera B. Frequency of CYP1A1*2A polymorphisms and deletion of the GSMT1 gene in a Peruvian mestizo population. PHARMACIA 2021. [DOI: 10.3897/pharmacia.68.e71621] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The polymorphic variants of CYP1A1 and the deletion of GSTM1 are present in the Peruvian mestizo population. Wild type and mutated genotypes (WT/*2A and *2A/ *2A) were identified, whose allele frequencies are 0.31 (T allele) and 0.69 (C allele), respectively; 53% with wild type GSTM1 (+) and 47% with null GSTM1. The frequency in Iquiteño emigrants was 0.72 CYP1A1*2A and 25% GSTM1 (-); from Lima 0.67 CYP1A1*2A and 33% of GSTM1 (-). The Hardy-Weinberg equilibrium test for the studied population showed that both frequencies are out of balance, p > .05.
The presence of the risk allele of the CYP1A1*2A polymorphism and the deletion in the GSTM1 gene are high, which could be indicative of a phase I and II metabolic imbalance in this group of Peruvian populations, with potential risks of activating agents procarcinogens thus affecting the incidence of tumor pathologies with an environmental component.
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7
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Kwong AM, Blackwell TW, LeFaive J, de Andrade M, Barnard J, Barnes KC, Blangero J, Boerwinkle E, Burchard EG, Cade BE, Chasman DI, Chen H, Conomos MP, Cupples LA, Ellinor PT, Eng C, Gao Y, Guo X, Irvin MR, Kelly TN, Kim W, Kooperberg C, Lubitz SA, Mak ACY, Manichaikul AW, Mathias RA, Montasser ME, Montgomery CG, Musani S, Palmer ND, Peloso GM, Qiao D, Reiner AP, Roden DM, Shoemaker MB, Smith JA, Smith NL, Su JL, Tiwari HK, Weeks DE, Weiss ST, Scott LJ, Smith AV, Abecasis GR, Boehnke M, Kang HM. Robust, flexible, and scalable tests for Hardy-Weinberg equilibrium across diverse ancestries. Genetics 2021; 218:iyab044. [PMID: 33720349 PMCID: PMC8128395 DOI: 10.1093/genetics/iyab044] [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: 11/24/2020] [Accepted: 02/03/2021] [Indexed: 11/13/2022] Open
Abstract
Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.
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Affiliation(s)
- Alan M Kwong
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Thomas W Blackwell
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jonathon LeFaive
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - John Barnard
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Kathleen C Barnes
- Department of Medicine, Anschultz Medical Campus, University of Colorado, Aurora, CO 80045, USA
| | - John Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics Center, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Esteban G Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA 02215, USA
| | - Han Chen
- Department of Epidemiology, Human Genetics Center, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA 01702, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02124, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Yan Gao
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216 USA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Marguerite Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University, New Orleans, LA 70112, USA
| | - Wonji Kim
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | | | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02124, USA
| | - Angel C Y Mak
- Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Ani W Manichaikul
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Rasika A Mathias
- GeneSTAR Research Program and Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Courtney G Montgomery
- Sarcoidosis Research Unit, Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Solomon Musani
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | | | - Dan M Roden
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - M Benjamin Shoemaker
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA 98101, USA
- Department of Veterans Affairs, Seattle Epidemiologic Research and Information Center, Office of Research and Development, Seattle, WA 98108, USA
| | - Jessica Lasky Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Daniel E Weeks
- Departments of Human Genetics and Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | | | | | - Laura J Scott
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Albert V Smith
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Gonçalo R Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hyun Min Kang
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
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8
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López ME, Cádiz MI, Rondeau EB, Koop BF, Yáñez JM. Detection of selection signatures in farmed coho salmon (Oncorhynchus kisutch) using dense genome-wide information. Sci Rep 2021; 11:9685. [PMID: 33958603 PMCID: PMC8102513 DOI: 10.1038/s41598-021-86154-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 02/08/2021] [Indexed: 01/01/2023] Open
Abstract
Animal domestication and artificial selection give rise to gradual changes at the genomic level in populations. Subsequent footprints of selection, known as selection signatures or selective sweeps, have been traced in the genomes of many animal livestock species by exploiting variation in linkage disequilibrium patterns and/or reduction of genetic diversity. Domestication of most aquatic species is recent in comparison with land animals, and salmonids are one of the most important fish species in aquaculture. Coho salmon (Oncorhynchus kisutch), cultivated primarily in Chile, has been subjected to breeding programs to improve growth, disease resistance traits, and flesh color. This study aimed to identify selection signatures that may be involved in adaptation to culture conditions and traits of productive interest. To do so, individuals of two domestic populations cultured in Chile were genotyped with 200 thousand SNPs, and analyses were conducted using iHS, XP-EHH and CLR. Several signatures of selection on different chromosomal regions were detected across both populations. Some of the identified regions under selection contained genes such anapc2, alad, chp2 and myn, which have been previously associated with body weight in Atlantic salmon, or sec24d and robo1, which have been associated with resistance to Piscirickettsia salmonis in coho salmon. Findings in our study can contribute to an integrated genome-wide map of selection signatures, to help identify the genetic mechanisms of phenotypic diversity in coho salmon.
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Affiliation(s)
- M E López
- Department of Aquatic Resources, Swedish University of Agricultural Sciences, Drottningholm, Sweden
| | - M I Cádiz
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - E B Rondeau
- Department of Biology, University of Victoria, Victoria, British Columbia, Canada
| | - B F Koop
- Department of Biology, University of Victoria, Victoria, British Columbia, Canada
| | - J M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile. .,Núcleo Milenio INVASAL, Concepción, Chile.
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9
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Ferreira GD, Fernandes GMDM, Penteado C, Cória VR, Galbiatti-Dias ALDS, Russo A, Castanhole-Nunes MMU, Silva RFD, Silva RDCMAD, Pavarino ÉC, Torreglosa Ruiz Cintra M, Goloni-Bertollo EM. Polymorphisms in xenobiotic metabolism-related genes in patients with hepatocellular carcinoma: a case-control study. Xenobiotica 2021; 51:737-744. [PMID: 33896378 DOI: 10.1080/00498254.2021.1893408] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
This study was performed to investigate the relationship between polymorphisms in microsomal epoxide hydrolase (mEH; Tyr113His and His139Arg substitution) and glutathione S-transferase (GST; GSTM1 deletion, GSTT1 deletion, and GSTP1.Ala114Val substitution) and their correlation with clinico-histopathological features in hepatocellular carcinoma (HCC).We evaluated environmental risk factors and genetic alterations in 556 individuals (86 cases and 470 controls). PCR multiplex for GSTM1 and GSTT1, polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) for GSTP1, and real-time PCR for mEH were performed. Statistical analyses were performed using multiple logistic regression tests.Age over 48 years (p < 0.001) and alcohol consumption (p = 0.021) were the predictors of increased risk of developing HCC. GSTP1.Ala114Val for all regression models (p < 0.05), except the recessive model, and the GSTT1 null genotype (odds ratio [OR] = 0.43, 95% confidence interval [CI] = 0.21-0.87, p = 0.019) were predictors of an increased risk of developing HCC. Polymorphic GSTT1, GSTM1, GSTP1.Ala114Val, and mEH.His139Arg and wild-type mEH.Tyr113His (OR = 5.04; 95% CI = 1.59-16.04; p = 0.006) were associated with HCC.Age over 48 years, alcohol consumption, and the presence of polymorphic variants of GSTP1 and GSTT1 were associated with the risk of developing HCC.
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Affiliation(s)
- Gislaine Dionísio Ferreira
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil
| | - Glaucia Maria de Mendonça Fernandes
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil
| | - Camila Penteado
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil
| | - Vivian Romanholi Cória
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil
| | - Ana Lívia da Silva Galbiatti-Dias
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
| | - Anelise Russo
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil
| | - Márcia Maria Urbanin Castanhole-Nunes
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
| | - Renato Ferreira da Silva
- Study Group of Liver Tumors - GETF, Surgery Department, São José do Rio Preto Medical School Fundation - FAMERP/FUNFARME, São José do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
| | - Rita de Cássia Martins Alves da Silva
- Study Group of Liver Tumors - GETF, Surgery Department, São José do Rio Preto Medical School Fundation - FAMERP/FUNFARME, São José do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
| | - Érika Cristina Pavarino
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
| | | | - Eny Maria Goloni-Bertollo
- Molecular Biology Department, Genetics and Molecular Biology Research Unit - UPGEM, São José do Rio Preto Medical School - FAMERP, São Jose do Rio Preto, Brazil.,São José do Rio Preto Regional Medical School Foundation - FUNFARME, São José do Rio Preto, Brazil
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Cabreros I, Storey JD. A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis. Genetics 2019; 212:1009-1029. [PMID: 31028112 PMCID: PMC6707457 DOI: 10.1534/genetics.119.302159] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 04/08/2019] [Indexed: 11/18/2022] Open
Abstract
We introduce a simple and computationally efficient method for fitting the admixture model of genetic population structure, called ALStructure The strategy of ALStructure is to first estimate the low-dimensional linear subspace of the population admixture components, and then search for a model within this subspace that is consistent with the admixture model's natural probabilistic constraints. Central to this strategy is the observation that all models belonging to this constrained space of solutions are risk-minimizing and have equal likelihood, rendering any additional optimization unnecessary. The low-dimensional linear subspace is estimated through a recently introduced principal components analysis method that is appropriate for genotype data, thereby providing a solution that has both principal components and probabilistic admixture interpretations. Our approach differs fundamentally from other existing methods for estimating admixture, which aim to fit the admixture model directly by searching for parameters that maximize the likelihood function or the posterior probability. We observe that ALStructure typically outperforms existing methods both in accuracy and computational speed under a wide array of simulated and real human genotype datasets. Throughout this work, we emphasize that the admixture model is a special case of a much broader class of models for which algorithms similar to ALStructure may be successfully employed.
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Affiliation(s)
- Irineo Cabreros
- Program in Applied and Computational Mathematics, Princeton University, New Jersey 08544
| | - John D Storey
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, New Jersey 08544
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11
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Backenroth D, Carmi S. A test for deviations from expected genotype frequencies on the X chromosome for sex-biased admixed populations. Heredity (Edinb) 2019; 123:470-478. [PMID: 31101879 DOI: 10.1038/s41437-019-0233-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 04/19/2019] [Accepted: 04/29/2019] [Indexed: 11/09/2022] Open
Abstract
Genome-wide scans for deviations from expected genotype frequencies, as determined by the Hardy-Weinberg equilibrium (HWE), are commonly applied to detect genotyping errors and deviations from random mating. In contrast to the autosomes, genotype frequencies on the X chromosome do not reach HWE within a single generation. Instead, if allele frequencies in males and females initially differ, they oscillate for a few generations toward equilibrium. Allele frequency differences between the sexes are expected in populations that have experienced recent sex-biased admixture, namely, their male and female founders differed in ancestry. Sex-biased admixture does not allow testing for HWE on X, because deviations are naturally expected, even under random mating (post admixture) and error-free genotyping. In this paper, we develop a likelihood ratio test and a χ2 test to detect deviations from expected genotype frequencies on X, beyond natural deviations due to sex-biased admixture. We demonstrate by simulations that our tests are powerful for detecting deviations due to non-random mating, while at the same time they do not reject the null under historical sex-biased admixture and random mating thereafter. We also demonstrate that when applied to 1000 Genomes project populations, our likelihood ratio test rejects fewer SNPs than other tests, but we describe limitations in the interpretation of the results.
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Affiliation(s)
- Daniel Backenroth
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
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