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Sticca EL, Belbin GM, Gignoux CR. Current Developments in Detection of Identity-by-Descent Methods and Applications. Front Genet 2021; 12:722602. [PMID: 34567074 PMCID: PMC8461052 DOI: 10.3389/fgene.2021.722602] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 08/24/2021] [Indexed: 01/23/2023] Open
Abstract
Identity-by-descent (IBD), the detection of shared segments inherited from a common ancestor, is a fundamental concept in genomics with broad applications in the characterization and analysis of genomes. While historically the concept of IBD was extensively utilized through linkage analyses and in studies of founder populations, applications of IBD-based methods subsided during the genome-wide association study era. This was primarily due to the computational expense of IBD detection, which becomes increasingly relevant as the field moves toward the analysis of biobank-scale datasets that encompass individuals from highly diverse backgrounds. To address these computational barriers, the past several years have seen new methodological advances enabling IBD detection for datasets in the hundreds of thousands to millions of individuals, enabling novel analyses at an unprecedented scale. Here, we describe the latest innovations in IBD detection and describe opportunities for the application of IBD-based methods across a broad range of questions in the field of genomics.
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Affiliation(s)
- Evan L Sticca
- Human Medical Genetics and Genomics Program and Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Gillian M Belbin
- Institute for Genomic Health, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Christopher R Gignoux
- Human Medical Genetics and Genomics Program and Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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2
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Abney M, ElSherbiny A. Kinpute: using identity by descent to improve genotype imputation. Bioinformatics 2019; 35:4321-4326. [PMID: 30918937 PMCID: PMC6821425 DOI: 10.1093/bioinformatics/btz221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 02/21/2019] [Accepted: 03/26/2019] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Genotype imputation, though generally accurate, often results in many genotypes being poorly imputed, particularly in studies where the individuals are not well represented by standard reference panels. When individuals in the study share regions of the genome identical by descent (IBD), it is possible to use this information in combination with a study-specific reference panel (SSRP) to improve the imputation results. Kinpute uses IBD information-due to recent, familial relatedness or distant, unknown ancestors-in conjunction with the output from linkage disequilibrium (LD) based imputation methods to compute more accurate genotype probabilities. Kinpute uses a novel method for IBD imputation, which works even in the absence of a pedigree, and results in substantially improved imputation quality. RESULTS Given initial estimates of average IBD between subjects in the study sample, Kinpute uses a novel algorithm to select an optimal set of individuals to sequence and use as an SSRP. Kinpute is designed to use as input both this SSRP and the genotype probabilities output from other LD-based imputation software, and uses a new method to combine the LD imputed genotype probabilities with IBD configurations to substantially improve imputation. We tested Kinpute on a human population isolate where 98 individuals have been sequenced. In half of this sample, whose sequence data was masked, we used Impute2 to perform LD-based imputation and Kinpute was used to obtain higher accuracy genotype probabilities. Measures of imputation accuracy improved significantly, particularly for those genotypes that Impute2 imputed with low certainty. AVAILABILITY AND IMPLEMENTATION Kinpute is an open-source and freely available C++ software package that can be downloaded from. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mark Abney
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Aisha ElSherbiny
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
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3
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Abdelfatah N, Chen R, Duff HJ, Seifer CM, Buffo I, Huculak C, Clarke S, Clegg R, Jassal DS, Gordon PMK, Ober C, Frosk P, Gerull B. Characterization of a Unique Form of Arrhythmic Cardiomyopathy Caused by Recessive Mutation in LEMD2. JACC Basic Transl Sci 2019; 4:204-221. [PMID: 31061923 PMCID: PMC6488817 DOI: 10.1016/j.jacbts.2018.12.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 11/02/2018] [Accepted: 12/03/2018] [Indexed: 02/08/2023]
Abstract
Nuclear envelope proteins have been shown to play an important role in the pathogenesis of inherited dilated cardiomyopathy. Here, we present a remarkable cardiac phenotype caused by a homozygous LEMD2 mutation in patients of the Hutterite population with juvenile cataract. Mutation carriers develop arrhythmic cardiomyopathy with mild impairment of left ventricular systolic function but severe ventricular arrhythmias leading to sudden cardiac death. Affected cardiac tissue from a deceased patient and fibroblasts exhibit elongated nuclei with abnormal condensed heterochromatin at the periphery. The patient fibroblasts demonstrate cellular senescence and reduced proliferation capacity, which may suggest an involvement of LEM domain containing protein 2 in chromatin remodeling processes and premature aging.
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Key Words
- ACM, arrhythmogenic cardiomyopathy
- BANF, barrier to autointegration factor
- CMR, cardiac magnetic resonance
- DAPI, 4′,6′-diamidino-2-phenylindole
- DCM, dilated cardiomyopathy
- DNA, deoxyribonucleic acid
- EMD, emerin
- ICD, implantable cardioverter-defibrillator
- LEMD2
- LEMD2, LEM domain containing protein 2
- LGE, late gadolinium enhancement
- LMNA, lamin A/C
- LV, left ventricular
- NE, nuclear envelope
- P, passage
- PBS, phosphate-buffered saline
- SAHF, senescence-associated heterochromatin foci
- SNV, single nucleotide variant
- chromatin remodeling
- dilated cardiomyopathy
- eGFP, enhanced green fluorescent protein
- inner nuclear membrane
- sudden death
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Affiliation(s)
- Nelly Abdelfatah
- Department of Cardiac Sciences, Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Ruping Chen
- Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
| | - Henry J Duff
- Department of Cardiac Sciences, Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Colette M Seifer
- Section of Cardiology, Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Ilan Buffo
- Variety Children's Heart Centre, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Cathleen Huculak
- Department of Medical Genetics, Alberta Health Services, Calgary, Alberta, Canada
| | - Stephanie Clarke
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Robin Clegg
- Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Davinder S Jassal
- Section of Cardiology, Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Paul M K Gordon
- Cumming School of Medicine Centre for Health Genomics and Informatics, University of Calgary, Calgary, Alberta, Canada
| | - Carole Ober
- Department of Human Genetics, The University of Chicago, Chicago, Illinois
| | | | - Patrick Frosk
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Department of Pediatrics and Child Health, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Brenda Gerull
- Department of Cardiac Sciences, Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany.,Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
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4
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Nutile T, Ruggiero D, Herzig AF, Tirozzi A, Nappo S, Sorice R, Marangio F, Bellenguez C, Leutenegger AL, Ciullo M. Whole-Exome Sequencing in the Isolated Populations of Cilento from South Italy. Sci Rep 2019; 9:4059. [PMID: 30858532 PMCID: PMC6411969 DOI: 10.1038/s41598-019-41022-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 02/22/2019] [Indexed: 12/21/2022] Open
Abstract
The present study describes the genetic architecture of the isolated populations of Cilento, through the analysis of exome sequence data of 245 representative individuals of these populations. By annotating the exome variants and cataloguing them according to their frequency and functional effects, we identified 347,684 variants, 67.4% of which are rare and low frequency variants, and 1% of them (corresponding to 319 variants per person) are classified as high functional impact variants; also, 39,946 (11.5% of the total) are novel variants, for which we determined a significant enrichment for deleterious effects. By comparing the allele frequencies in Cilento with those from the Tuscan population from the 1000 Genomes Project Phase 3, we highlighted an increase in allele frequency in Cilento especially for variants which map to genes involved in extracellular matrix formation and organization. Furthermore, among the variants showing increased frequency we identified several known rare disease-causing variants. By different population genetics analyses, we corroborated the status of the Cilento populations as genetic isolates. Finally, we showed that exome data of Cilento represents a useful local reference panel capable of improving the accuracy of genetic imputation, thus adding power to genetic studies of human traits in these populations.
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Affiliation(s)
- T Nutile
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy
| | - D Ruggiero
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy.,IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - A F Herzig
- Inserm, UMR 946, Genetic variation and Human diseases, F-75010, Paris, France.,Université Paris-Diderot, Sorbonne Paris Cité, UMR946, F-75010, Paris, France
| | - A Tirozzi
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - S Nappo
- AORN Santobono-Pausilipon Hospital, Naples, Italy
| | - R Sorice
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy
| | - F Marangio
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy
| | - C Bellenguez
- Inserm, U1167, RID-AGE-Risk factors and molecular determinants of aging-related diseases, F-59000, Lille, France.,Institut Pasteur de Lille, F-59000, Lille, France.,Univ. Lille, U1167-Excellence Laboratory LabEx DISTALZ, F-59000, Lille, France
| | - A L Leutenegger
- Inserm, UMR 946, Genetic variation and Human diseases, F-75010, Paris, France.,Université Paris-Diderot, Sorbonne Paris Cité, UMR946, F-75010, Paris, France
| | - M Ciullo
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy. .,IRCCS Neuromed, Pozzilli, Isernia, Italy.
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5
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Herzig AF, Nutile T, Babron MC, Ciullo M, Bellenguez C, Leutenegger AL. Strategies for phasing and imputation in a population isolate. Genet Epidemiol 2018; 42:201-213. [PMID: 29319195 DOI: 10.1002/gepi.22109] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 11/16/2017] [Accepted: 11/16/2017] [Indexed: 11/05/2022]
Abstract
In the search for genetic associations with complex traits, population isolates offer the advantage of reduced genetic and environmental heterogeneity. In addition, cost-efficient next-generation association approaches have been proposed in these populations where only a subsample of representative individuals is sequenced and then genotypes are imputed into the rest of the population. Gene mapping in such populations thus requires high-quality genetic imputation and preliminary phasing. To identify an effective study design, we compare by simulation a range of phasing and imputation software and strategies. We simulated 1,115,604 variants on chromosome 10 for 477 members of the large complex pedigree of Campora, a village within the established isolate of Cilento in southern Italy. We assessed the phasing performance of identical by descent based software ALPHAPHASE and SLRP, LD-based software SHAPEIT2, SHAPEIT3, and BEAGLE, and new software EAGLE that combines both methodologies. For imputation we compared IMPUTE2, IMPUTE4, MINIMAC3, BEAGLE, and new software PBWT. Genotyping errors and missing genotypes were simulated to observe their effects on the performance of each software. Highly accurate phased data were achieved by all software with SHAPEIT2, SHAPEIT3, and EAGLE2 providing the most accurate results. MINIMAC3, IMPUTE4, and IMPUTE2 all performed strongly as imputation software and our study highlights the considerable gain in imputation accuracy provided by a genome sequenced reference panel specific to the population isolate.
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Affiliation(s)
- Anthony Francis Herzig
- Université Paris-Diderot, Sorbonne Paris Cité, U946, Paris, France.,Inserm, U946, Genetic Variation and Human Diseases, Paris, France
| | - Teresa Nutile
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy
| | - Marie-Claude Babron
- Université Paris-Diderot, Sorbonne Paris Cité, U946, Paris, France.,Inserm, U946, Genetic Variation and Human Diseases, Paris, France
| | - Marina Ciullo
- Institute of Genetics and Biophysics A. Buzzati-Traverso-CNR, Naples, Italy.,IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Céline Bellenguez
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France.,Institut Pasteur de Lille, Lille, France.,Université de Lille, U1167-Excellence Laboratory LabEx DISTALZ, Lille, France
| | - Anne-Louise Leutenegger
- Université Paris-Diderot, Sorbonne Paris Cité, U946, Paris, France.,Inserm, U946, Genetic Variation and Human Diseases, Paris, France
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6
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Vandenplas J, Calus MPL, Sevillano CA, Windig JJ, Bastiaansen JWM. Assigning breed origin to alleles in crossbred animals. Genet Sel Evol 2016; 48:61. [PMID: 27549177 PMCID: PMC4994281 DOI: 10.1186/s12711-016-0240-y] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Accepted: 08/10/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND For some species, animal production systems are based on the use of crossbreeding to take advantage of the increased performance of crossbred compared to purebred animals. Effects of single nucleotide polymorphisms (SNPs) may differ between purebred and crossbred animals for several reasons: (1) differences in linkage disequilibrium between SNP alleles and a quantitative trait locus; (2) differences in genetic backgrounds (e.g., dominance and epistatic interactions); and (3) differences in environmental conditions, which result in genotype-by-environment interactions. Thus, SNP effects may be breed-specific, which has led to the development of genomic evaluations for crossbred performance that take such effects into account. However, to estimate breed-specific effects, it is necessary to know breed origin of alleles in crossbred animals. Therefore, our aim was to develop an approach for assigning breed origin to alleles of crossbred animals (termed BOA) without information on pedigree and to study its accuracy by considering various factors, including distance between breeds. RESULTS The BOA approach consists of: (1) phasing genotypes of purebred and crossbred animals; (2) assigning breed origin to phased haplotypes; and (3) assigning breed origin to alleles of crossbred animals based on a library of assigned haplotypes, the breed composition of crossbred animals, and their SNP genotypes. The accuracy of allele assignments was determined for simulated datasets that include crosses between closely-related, distantly-related and unrelated breeds. Across these scenarios, the percentage of alleles of a crossbred animal that were correctly assigned to their breed origin was greater than 90 %, and increased with increasing distance between breeds, while the percentage of incorrectly assigned alleles was always less than 2 %. For the remaining alleles, i.e. 0 to 10 % of all alleles of a crossbred animal, breed origin could not be assigned. CONCLUSIONS The BOA approach accurately assigns breed origin to alleles of crossbred animals, even if their pedigree is not recorded.
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Affiliation(s)
- Jérémie Vandenplas
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands.
| | - Mario P L Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands
| | - Claudia A Sevillano
- Topigs Norsvin Research Center B.V., 6640 AA, Beuningen, The Netherlands.,Animal Breeding and Genomics Centre, Wageningen University, 6700 AH, Wageningen, The Netherlands
| | - Jack J Windig
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands
| | - John W M Bastiaansen
- Animal Breeding and Genomics Centre, Wageningen University, 6700 AH, Wageningen, The Netherlands
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7
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Livne OE, Han L, Alkorta-Aranburu G, Wentworth-Sheilds W, Abney M, Ober C, Nicolae DL. PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population. PLoS Comput Biol 2015; 11:e1004139. [PMID: 25735005 PMCID: PMC4348507 DOI: 10.1371/journal.pcbi.1004139] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2014] [Accepted: 01/19/2015] [Indexed: 12/31/2022] Open
Abstract
Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.
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Affiliation(s)
- Oren E. Livne
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Lide Han
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Gorka Alkorta-Aranburu
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - William Wentworth-Sheilds
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Mark Abney
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Carole Ober
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Dan L. Nicolae
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
- Departments of Medicine, and Statistics, The University of Chicago, Chicago, Illinois, United States of America
- * E-mail:
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8
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Campbell CD, Mohajeri K, Malig M, Hormozdiari F, Nelson B, Du G, Patterson KM, Eng C, Torgerson DG, Hu D, Herman C, Chong JX, Ko A, O'Roak BJ, Krumm N, Vives L, Lee C, Roth LA, Rodriguez-Cintron W, Rodriguez-Santana J, Brigino-Buenaventura E, Davis A, Meade K, LeNoir MA, Thyne S, Jackson DJ, Gern JE, Lemanske RF, Shendure J, Abney M, Burchard EG, Ober C, Eichler EE. Whole-genome sequencing of individuals from a founder population identifies candidate genes for asthma. PLoS One 2014; 9:e104396. [PMID: 25116239 PMCID: PMC4130548 DOI: 10.1371/journal.pone.0104396] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2014] [Accepted: 07/12/2014] [Indexed: 12/30/2022] Open
Abstract
Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.
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Affiliation(s)
- Catarina D. Campbell
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Kiana Mohajeri
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Maika Malig
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Fereydoun Hormozdiari
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Benjamin Nelson
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Gaixin Du
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Kristen M. Patterson
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Dara G. Torgerson
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Catherine Herman
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Jessica X. Chong
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Arthur Ko
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Brian J. O'Roak
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Niklas Krumm
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Laura Vives
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Choli Lee
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Lindsey A. Roth
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | | | | | - Emerita Brigino-Buenaventura
- Department of Allergy & Immunology, Kaiser Permanente-Vallejo Medical Center, Vallejo, California, United States of America
| | - Adam Davis
- Children's Hospital and Research Center Oakland, Oakland, California, United States of America
| | - Kelley Meade
- Children's Hospital and Research Center Oakland, Oakland, California, United States of America
| | | | - Shannon Thyne
- San Francisco General Hospital, San Francisco, California, and the Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Daniel J. Jackson
- Department of Pediatrics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - James E. Gern
- Department of Pediatrics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Robert F. Lemanske
- Department of Pediatrics, University of Wisconsin, Madison, Wisconsin, United States of America
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Mark Abney
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Esteban G. Burchard
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America
| | - Carole Ober
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Seattle, Washington, United States of America
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9
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Vinson A, Prongay K, Ferguson B. The value of extended pedigrees for next-generation analysis of complex disease in the rhesus macaque. ILAR J 2014; 54:91-105. [PMID: 24174435 DOI: 10.1093/ilar/ilt041] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Complex diseases (e.g., cardiovascular disease and type 2 diabetes, among many others) pose the biggest threat to human health worldwide and are among the most challenging to investigate. Susceptibility to complex disease may be caused by multiple genetic variants (GVs) and their interaction, by environmental factors, and by interaction between GVs and environment, and large study cohorts with substantial analytical power are typically required to elucidate these individual contributions. Here, we discuss the advantages of both power and feasibility afforded by the use of extended pedigrees of rhesus macaques (Macaca mulatta) for genetic studies of complex human disease based on next-generation sequence data. We present these advantages in the context of previous research conducted in rhesus macaques for several representative complex diseases. We also describe a single, multigeneration pedigree of Indian-origin rhesus macaques and a sample biobank we have developed for genetic analysis of complex disease, including power of this pedigree to detect causal GVs using either genetic linkage or association methods in a variance decomposition approach. Finally, we summarize findings of significant heritability for a number of quantitative traits that demonstrate that genetic contributions to risk factors for complex disease can be detected and measured in this pedigree. We conclude that the development and application of an extended pedigree to analysis of complex disease traits in the rhesus macaque have shown promising early success and that genome-wide genetic and higher order -omics studies in this pedigree are likely to yield useful insights into the architecture of complex human disease.
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10
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Abstract
The use of genetically isolated populations can empower next-generation association studies. In this review, we discuss the advantages of this approach and review study design and analytical considerations of genetic association studies focusing on isolates. We cite successful examples of using population isolates in association studies and outline potential ways forward.
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11
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Jiang D, McPeek MS. Robust rare variant association testing for quantitative traits in samples with related individuals. Genet Epidemiol 2013; 38:10-20. [PMID: 24248908 DOI: 10.1002/gepi.21775] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Revised: 10/01/2013] [Accepted: 10/15/2013] [Indexed: 11/08/2022]
Abstract
The recent development of high-throughput sequencing technologies calls for powerful statistical tests to detect rare genetic variants associated with complex human traits. Sampling related individuals in sequencing studies offers advantages over sampling unrelated individuals only, including improved protection against sequencing error, the ability to use imputation to make more efficient use of sequence data, and the possibility of power boost due to more observed copies of extremely rare alleles among relatives. With related individuals, familial correlation needs to be accounted for to ensure correct control over type I error and to improve power. Recognizing the limitations of existing rare-variant association tests for family data, we propose MONSTER (Minimum P-value Optimized Nuisance parameter Score Test Extended to Relatives), a robust rare-variant association test, which generalizes the SKAT-O method for independent samples. MONSTER uses a mixed effects model that accounts for covariates and additive polygenic effects. To obtain a powerful test, MONSTER adaptively adjusts to the unknown configuration of effects of rare-variant sites. MONSTER also offers an analytical way of assessing P-values, which is desirable because permutation is not straightforward to conduct in related samples. In simulation studies, we demonstrate that MONSTER effectively accounts for family structure, is computationally efficient and compares very favorably, in terms of power, to previously proposed tests that allow related individuals. We apply MONSTER to an analysis of high-density lipoprotein cholesterol in the Framingham Heart Study, where we are able to replicate association with three genes.
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Affiliation(s)
- Duo Jiang
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
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Joshi PK, Prendergast J, Fraser RM, Huffman JE, Vitart V, Hayward C, McQuillan R, Glodzik D, Polašek O, Hastie ND, Rudan I, Campbell H, Wright AF, Haley CS, Wilson JF, Navarro P. Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies. PLoS One 2013; 8:e68604. [PMID: 23874685 PMCID: PMC3712964 DOI: 10.1371/journal.pone.0068604] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Accepted: 05/30/2013] [Indexed: 11/18/2022] Open
Abstract
The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10%) in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.
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Affiliation(s)
- Peter K. Joshi
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - James Prendergast
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ross M. Fraser
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Jennifer E. Huffman
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Veronique Vitart
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ruth McQuillan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Dominik Glodzik
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ozren Polašek
- Department of Public Health, University of Split, Split, Croatia
- Centre for Global Health, University of Split, Split, Croatia
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Roslin Institute, University of Edinburgh, Scotland, United Kingdom
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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Abstract
The role of rare variants has become a focus in the search for association with complex traits. Imputation is a powerful and cost-efficient tool to access variants that have not been directly typed, but there are several challenges when imputing rare variants, most notably reference panel selection. Extensions to rare variant association tests to incorporate genotype uncertainty from imputation are discussed, as well as the use of imputed low-frequency and rare variants in the study of population isolates.
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Abstract
Widespread sharing of long, identical-by-descent (IBD) genetic segments is a hallmark of populations that have experienced recent genetic drift. Detection of these IBD segments has recently become feasible, enabling a wide range of applications from phasing and imputation to demographic inference. Here, we study the distribution of IBD sharing in the Wright-Fisher model. Specifically, using coalescent theory, we calculate the variance of the total sharing between random pairs of individuals. We then investigate the cohort-averaged sharing: the average total sharing between one individual and the rest of the cohort. We find that for large cohorts, the cohort-averaged sharing is distributed approximately normally. Surprisingly, the variance of this distribution does not vanish even for large cohorts, implying the existence of "hypersharing" individuals. The presence of such individuals has consequences for the design of sequencing studies, since, if they are selected for whole-genome sequencing, a larger fraction of the cohort can be subsequently imputed. We calculate the expected gain in power of imputation by IBD and subsequently in power to detect an association, when individuals are either randomly selected or specifically chosen to be the hypersharing individuals. Using our framework, we also compute the variance of an estimator of the population size that is based on the mean IBD sharing and the variance in the sharing between inbred siblings. Finally, we study IBD sharing in an admixture pulse model and show that in the Ashkenazi Jewish population the admixture fraction is correlated with the cohort-averaged sharing.
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Chong JX, Ouwenga R, Anderson RL, Waggoner DJ, Ober C. A population-based study of autosomal-recessive disease-causing mutations in a founder population. Am J Hum Genet 2012; 91:608-20. [PMID: 22981120 DOI: 10.1016/j.ajhg.2012.08.007] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2012] [Revised: 06/12/2012] [Accepted: 08/09/2012] [Indexed: 01/18/2023] Open
Abstract
The decreasing cost of whole-genome and whole-exome sequencing has resulted in a renaissance for identifying Mendelian disease mutations, and for the first time it is possible to survey the distribution and characteristics of these mutations in large population samples. We conducted carrier screening for all autosomal-recessive (AR) mutations known to be present in members of a founder population and revealed surprisingly high carrier frequencies for many of these mutations. By utilizing the rich demographic, genetic, and phenotypic data available on these subjects and simulations in the exact pedigree that these individuals belong to, we show that the majority of mutations were most likely introduced into the population by a single founder and then drifted to the high carrier frequencies observed. We further show that although there is an increased incidence of AR diseases overall, the mean carrier burden is likely to be lower in the Hutterites than in the general population. Finally, on the basis of simulations, we predict the presence of 30 or more undiscovered recessive mutations among these subjects, and this would at least double the number of AR diseases that have been reported in this isolated population.
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Affiliation(s)
- Jessica X Chong
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
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Genome-wide association study identifies candidate genes for male fertility traits in humans. Am J Hum Genet 2012; 90:950-61. [PMID: 22633400 DOI: 10.1016/j.ajhg.2012.04.016] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2011] [Revised: 03/26/2012] [Accepted: 04/10/2012] [Indexed: 01/16/2023] Open
Abstract
Despite the fact that hundreds of genes are known to affect fertility in animal models, relatively little is known about genes that influence natural fertility in humans. To broadly survey genes contributing to variation in male fertility, we conducted a genome-wide association study (GWAS) of two fertility traits (family size and birth rate) in 269 married men who are members of a founder population of European descent that proscribes contraception and has large family sizes. Associations between ∼250,000 autosomal SNPs and the fertility traits were examined. A total of 41 SNPs with p ≤ 1 × 10(-4) for either trait were taken forward to a validation study of 123 ethnically diverse men from Chicago who had previously undergone semen analyses. Nine (22%) of the SNPs associated with reduced fertility in the GWAS were also associated with one or more of the ten measures of reduced sperm quantity and/or function, yielding 27 associations with p values < 0.05 and seven with p values < 0.01 in the validation study. On the basis of 5,000 permutations of our data, the probabilities of observing this many or more small p values were 0.0014 and 5.6 × 10(-4), respectively. Among the nine associated loci, outstanding candidates for male fertility genes include USP8, an essential deubiquitinating enzyme that has a role in acrosome assembly; UBD and EPSTI1, which have potential roles in innate immunity; and LRRC32, which encodes a latent transforming growth factor β (TGF-β) receptor on regulatory T cells. We suggest that mutations in these genes that are more severe may account for some of the unexplained infertility (or subfertility) in the general population.
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