1
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Arambepola R, Bérubé S, Freedman B, Taylor SM, Prudhomme O’Meara W, Obala AA, Wesolowski A. Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1058871. [PMID: 38516334 PMCID: PMC10956351 DOI: 10.3389/fepid.2023.1058871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 01/18/2023] [Indexed: 03/23/2024]
Abstract
A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities.
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Affiliation(s)
- Rohan Arambepola
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
| | - Sophie Bérubé
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
| | - Betsy Freedman
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
| | - Steve M. Taylor
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
- Duke Global Health Institute, Durham, NC, United States
| | - Wendy Prudhomme O’Meara
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States
- Duke Global Health Institute, Durham, NC, United States
| | | | - Amy Wesolowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Batlimore, MD, United States
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2
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Balagué-Dobón L, Cáceres A, González JR. Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure. Brief Bioinform 2022; 23:bbac043. [PMID: 35211719 PMCID: PMC8921734 DOI: 10.1093/bib/bbac043] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 01/25/2022] [Accepted: 01/28/2022] [Indexed: 12/12/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.
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3
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Ahmar S, Ballesta P, Ali M, Mora-Poblete F. Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing. Int J Mol Sci 2021; 22:10583. [PMID: 34638922 PMCID: PMC8508745 DOI: 10.3390/ijms221910583] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022] Open
Abstract
Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.
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Affiliation(s)
- Sunny Ahmar
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
| | - Paulina Ballesta
- The National Fund for Scientific and Technological Development, Av. del Agua 3895, Talca 3460000, Chile
| | - Mohsin Ali
- Department of Forestry and Range Management, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan;
| | - Freddy Mora-Poblete
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
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4
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Kling D, Phillips C, Kennett D, Tillmar A. Investigative genetic genealogy: Current methods, knowledge and practice. Forensic Sci Int Genet 2021; 52:102474. [PMID: 33592389 DOI: 10.1016/j.fsigen.2021.102474] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 01/12/2021] [Accepted: 01/27/2021] [Indexed: 12/15/2022]
Abstract
Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.
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Affiliation(s)
- Daniel Kling
- Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden; Department of Forensic Sciences, Oslo University Hospital, Oslo, Norway.
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain.
| | - Debbie Kennett
- Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | - Andreas Tillmar
- Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden; Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden
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5
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Zhou Y, Browning SR, Browning BL. A Fast and Simple Method for Detecting Identity-by-Descent Segments in Large-Scale Data. Am J Hum Genet 2020; 106:426-437. [PMID: 32169169 PMCID: PMC7118582 DOI: 10.1016/j.ajhg.2020.02.010] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 02/12/2020] [Indexed: 12/24/2022] Open
Abstract
Segments of identity by descent (IBD) are used in many genetic analyses. We present a method for detecting identical-by-descent haplotype segments in phased genotype data. Our method, called hap-IBD, combines a compressed representation of haplotype data, the positional Burrows-Wheeler transform, and multi-threaded execution to produce very fast analysis times. An attractive feature of hap-IBD is its simplicity: the input parameters clearly and precisely define the IBD segments that are reported, so that program correctness can be confirmed by users. We evaluate hap-IBD and four state-of-the-art IBD segment detection methods (GERMLINE, iLASH, RaPID, and TRUFFLE) using UK Biobank chromosome 20 data and simulated sequence data. We show that hap-IBD detects IBD segments faster and more accurately than competing methods, and that hap-IBD is the only method that can rapidly and accurately detect short 2-4 centiMorgan (cM) IBD segments in the full UK Biobank data. Analysis of 485,346 UK Biobank samples through the use of hap-IBD with 12 computational threads detects 231.5 billion autosomal IBD segments with length ≥2 cM in 24.4 h.
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Affiliation(s)
- Ying Zhou
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA.
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6
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Taylor AR, Jacob PE, Neafsey DE, Buckee CO. Estimating Relatedness Between Malaria Parasites. Genetics 2019; 212:1337-1351. [PMID: 31209105 PMCID: PMC6707449 DOI: 10.1534/genetics.119.302120] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 06/03/2019] [Indexed: 11/18/2022] Open
Abstract
Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent. Estimates based on IBS are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on IBD. To generate estimates with errors below an arbitrary threshold of 0.1, we recommend ∼100 polyallelic or 200 biallelic markers. Marker requirements are immediately applicable to haploid malaria parasites and other haploid eukaryotes. C.I.s facilitate comparison when different marker sets are used. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology. We hope it will provide a basis for statistically informed prospective study design and surveillance strategies.
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Affiliation(s)
- Aimee R Taylor
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
| | - Pierre E Jacob
- Department of Statistics, Harvard University, Cambridge, Massachusetts 02138
| | - Daniel E Neafsey
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
| | - Caroline O Buckee
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts 02115
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7
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Thompson EA. Correlations between relatives: From Mendelian theory to complete genome sequence. Genet Epidemiol 2019; 43:577-591. [PMID: 31045279 PMCID: PMC6559867 DOI: 10.1002/gepi.22206] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 03/04/2019] [Accepted: 03/25/2019] [Indexed: 12/19/2022]
Abstract
It is 100 years since R. A. Fisher proposed that a Mendelian model of genetic variant effects, additive over loci, could explain the patterns of observed phenotypic correlations between relatives. His loci were hypothetical and his model theoretical. It is only about 50 years since the first genetic markers allowed the detection of even variants with major effects on phenotype, and only 20 years since the development of single-nucleotide polymorphism technology provided dense markers over the genome. Then both mappings in defined pedigrees and population-based genome-wide association studies samples allowed the detection of multiple contributing variants of smaller effect. Finally, with methods based on genotypic correlations between individuals, or on allelic associations between loci, the additive heritability contributions of the genome can be estimated from large population samples. In this review we trace, from 1918 to 2018, the analysis of observed phenotypic correlations between relatives to estimate underlying genetic components of traits in human populations. As with studies from 1918 onward, we use height as the example trait where not only data are readily available, but where Fisher's model of large numbers of variants of infinitesimal effect appears to provide a good approximation to reality. However, we also trace the use of phenotypic and genotypic correlations between relatives in mapping causal variants and resolving genetic contributions to more complex human traits. With the availability of DNA sequence data, we can hope to not only estimate the total genetic contribution to a trait, but to resolve effects of individual genetic variants on biological function.
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8
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Efficient Estimation of Realized Kinship from Single Nucleotide Polymorphism Genotypes. Genetics 2017; 205:1063-1078. [PMID: 28100587 DOI: 10.1534/genetics.116.197004] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 12/31/2016] [Indexed: 01/06/2023] Open
Abstract
Realized kinship is a key statistic in analyses of genetic data involving relatedness of individuals or structure of populations. There are several estimators of kinship that make use of dense SNP genotypes. We introduce a class of estimators, of which some existing estimators are special cases. Within this class, we derive properties of the estimators and determine an optimal estimator. Additionally, we introduce an alternative marker weighting that takes allelic associations [linkage disequilibrium (LD)] into account, and apply this weighting to several estimators. In a simulation study, we show that improved estimators are obtained (1) by optimal weighting of markers, (2) by taking physical contiguity of genome into account, and (3) by weighting on the basis of LD.
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9
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Henden L, Freytag S, Afawi Z, Baldassari S, Berkovic SF, Bisulli F, Canafoglia L, Casari G, Crompton DE, Depienne C, Gecz J, Guerrini R, Helbig I, Hirsch E, Keren B, Klein KM, Labauge P, LeGuern E, Licchetta L, Mei D, Nava C, Pippucci T, Rudolf G, Scheffer IE, Striano P, Tinuper P, Zara F, Corbett M, Bahlo M. Identity by descent fine mapping of familial adult myoclonus epilepsy (FAME) to 2p11.2-2q11.2. Hum Genet 2016; 135:1117-25. [PMID: 27368338 DOI: 10.1007/s00439-016-1700-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Accepted: 06/21/2016] [Indexed: 02/03/2023]
Abstract
Familial adult myoclonus epilepsy (FAME) is a rare autosomal dominant disorder characterized by adult onset, involuntary muscle jerks, cortical myoclonus and occasional seizures. FAME is genetically heterogeneous with more than 70 families reported worldwide and five potential disease loci. The efforts to identify potential causal variants have been unsuccessful in all but three families. To date, linkage analysis has been the main approach to find and narrow FAME critical regions. We propose an alternative method, pedigree free identity-by-descent (IBD) mapping, that infers regions of the genome between individuals that have been inherited from a common ancestor. IBD mapping provides an alternative to linkage analysis in the presence of allelic and locus heterogeneity by detecting clusters of individuals who share a common allele. Succeeding IBD mapping, gene prioritization based on gene co-expression analysis can be used to identify the most promising candidate genes. We performed an IBD analysis using high-density single nucleotide polymorphism (SNP) array data followed by gene prioritization on a FAME cohort of ten European families and one Australian/New Zealander family; eight of which had known disease loci. By identifying IBD regions common to multiple families, we were able to narrow the FAME2 locus to a 9.78 megabase interval within 2p11.2-q11.2. We provide additional evidence of a founder effect in four Italian families and allelic heterogeneity with at least four distinct founders responsible for FAME at the FAME2 locus. In addition, we suggest candidate disease genes using gene prioritization based on gene co-expression analysis.
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Affiliation(s)
- Lyndal Henden
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia.,Department of Medical Biology, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Saskia Freytag
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia.,Department of Medical Biology, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Zaid Afawi
- Tel Aviv University Medical School, 69978, Tel Aviv, Israel
| | - Sara Baldassari
- Medical Genetics Unit, Polyclinic Sant'Orsola-Malpighi-Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, University of Melbourne Austin Health, Melbourne, VIC, 3084, Australia
| | - Francesca Bisulli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Laura Canafoglia
- Neurophysiopathology and Epilepsy Center, IRCCS Foundation C. Besta Neurological Institute, Milan, Italy
| | - Giorgio Casari
- Division of Genetics and Cell Biology, Università Vita-Salute San Raffaele, San Raffaele Scientific Institute, Milan, Italy
| | | | - Christel Depienne
- Département de Médicine translationnelle et Neurogénétique, IGBMC, CNRS UMR 7104/INSERM U964/Université de Strasbourg, Illkirch, France.,Laboratoire de diagnostic génétique, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Jozef Gecz
- Robinson Institute and School of Medicine, The University of Adelaide, Adelaide, SA, 5005, Australia.,School of Biological Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia
| | - Renzo Guerrini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, A Meyer Children's Hospital, University of Florence, Florence, Italy.,IRCCS Stella Maris Foundation, Pisa, Italy
| | - Ingo Helbig
- Department of Neuropediatrics, Christian-Albrechts-University of Kiel and University Medical Center, Kiel, Schleswig-Holstein, Germany.,Departments of Brain and Cognitive Sciences, Physiology and Cell Biology, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Negev, Israel.,Division of Neurology, The Children's Hospital of Philadelphia, Philadelphia, USA
| | - Edouard Hirsch
- Medical and Surgical Epilepsy Unit, Hautepierre Hospital, University of Strasbourg, Strasbourg, France
| | - Boris Keren
- Département de Génétique, Hôpital de la Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, 75013, Paris, France.,Sorbonne Universités, UPMC Univ Paris 06,UMR S 1127, ICM, 75013, Paris, France
| | - Karl Martin Klein
- Department of Neurology, Epilepsy Center Frankfurt Rhine-Main, Center of Neurology and Neurosurgery, University Hospital, Goethe-University Frankfurt, Frankfurt, Germany.,Department of Neurology, Epilepsy Center Hessen, University Hospitals Giessen and Marburg, Philipps-University Marburg, Marburg, Germany
| | - Pierre Labauge
- Department of Neurology, Montpellier University, Gui de Chauliac, 34295, Montpellier, Cedex 5, France
| | - Eric LeGuern
- Sorbonne Universités, UPMC Univ Paris 06,UMR S 1127, ICM, 75013, Paris, France.,INSERM, U 1127; CNRS, UMR 7225; INSERM UMR 975; Institut du Cerveau et de la Moelle Epinière; and Département de Génétique et de Cytogénétique, Hôpital de la Pitié-Salpêtrière, Assistance Publique-Hôpitaux De Paris (AP-HP), Paris, France.,Université Pierre et Marie Curie (Paris 6) (UPMC), UMRS 975, Paris, France
| | - Laura Licchetta
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Davide Mei
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, A Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Caroline Nava
- Département de Génétique, Hôpital de la Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, 75013, Paris, France.,Sorbonne Universités, UPMC Univ Paris 06,UMR S 1127, ICM, 75013, Paris, France
| | - Tommaso Pippucci
- Medical Genetics Unit, Polyclinic Sant'Orsola-Malpighi-Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Gabrielle Rudolf
- Département de Médicine translationnelle et Neurogénétique, IGBMC, CNRS UMR 7104/INSERM U964/Université de Strasbourg, Illkirch, France.,Department of Neurology, Hautepierre Hospital, University of Strasbourg, Strasbourg, France
| | - Ingrid Eileen Scheffer
- Epilepsy Research Centre, Department of Medicine, University of Melbourne Austin Health, Melbourne, VIC, 3084, Australia.,Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, 3084, Australia.,Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Melbourne, VIC, 3052, Australia
| | - Pasquale Striano
- Pediatric Neurology and Muscular Diseases Unit, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Gaslini Institute, Genoa, Italy
| | - Paolo Tinuper
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Federico Zara
- Laboratory of Neurogenetics, Department of Neurosciences, Gaslini Institute, Genoa, Italy
| | - Mark Corbett
- Robinson Institute and School of Medicine, The University of Adelaide, Adelaide, SA, 5005, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia. .,Department of Medical Biology, University of Melbourne, Melbourne, VIC, 3010, Australia.
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10
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Henden L, Wakeham D, Bahlo M. XIBD: software for inferring pairwise identity by descent on the X chromosome. ACTA ACUST UNITED AC 2016; 32:2389-91. [PMID: 27153693 DOI: 10.1093/bioinformatics/btw124] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 03/01/2016] [Indexed: 11/13/2022]
Abstract
UNLABELLED XIBD performs pairwise relatedness mapping on the X chromosome using dense single nucleotide polymorphism (SNP) data from either SNP chips or next generation sequencing data. It correctly accounts for the difference in chromosomal numbers between males and females and estimates global relatedness as well as regions of the genome that are identical by descent (IBD). XIBD also generates novel graphical summaries of all pairwise IBD tracts for a cohort making it very useful for disease locus mapping. AVAILABILITY AND IMPLEMENTATION XIBD is written in R/Rcpp and executed from shell scripts that are freely available from http://bioinf.wehi.edu.au/software/XIBD along with accompanying reference datasets. CONTACT henden.l@wehi.edu.au SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Lyndal Henden
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia Department of Medical Biology
| | | | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia Department of Medical Biology School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
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11
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Gazal S, Génin E, Leutenegger AL. Relationship inference from the genetic data on parents or offspring: A comparative study. Theor Popul Biol 2015; 107:31-8. [PMID: 26431644 DOI: 10.1016/j.tpb.2015.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Revised: 09/16/2015] [Accepted: 09/17/2015] [Indexed: 02/08/2023]
Abstract
Relationship inference in a population is of interest for many areas of research from anthropology to genetics. It is possible to directly infer the relationship between the two individuals in a couple from their genetic data or to indirectly infer it from the genetic data of one of their offspring. For this reason, one can wonder if it is more advantageous to sample couples or single individuals to study relationships of couples in a population. Indeed, sampling two individuals is more informative than sampling one as we are looking at four haplotypes instead of two, but it also doubles the cost of the study and is a more complex sampling scheme. To answer this question, we performed simulations of 1000 trios from 10 different relationships using real human haplotypes to have realistic genome-wide genetic data. Then, we compared the genome sharing coefficients and the relationship inference obtained from either a pair of individuals or one of their offspring using both single-point and multi-point approaches. We observed that for relationships closer than 1st cousin, pairs of individuals were more informative than one of their offspring for relationship inference, and kinship coefficients obtained from single-point methods gave more accurate or equivalent genome sharing estimations. For more remote relationships, offspring were more informative for relationship inference, and inbreeding coefficients obtained from multi-point methods gave more accurate genome sharing estimations. In conclusion, relationship inference on a parental pair or on one of their offspring provides complementary information. When possible, sampling trios should be encouraged as it could allow spanning a wider range of potential relationships.
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Affiliation(s)
- Steven Gazal
- Inserm, UMR 1137, IAME, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, UMR 1137, Paris, France; Plateforme de Génétique constitutionnelle-Nord (PfGC-Nord), Paris, France
| | - Emmanuelle Génin
- Inserm, UMR 1078, Brest, France; Université Bretagne Occidentale, Brest, France; Centre Hospitalier Régional Universitaire, Brest, France
| | - Anne-Louise Leutenegger
- Inserm, U946, Genetic Variation and Human Diseases Lab, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, UMR 946, Paris, France.
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12
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Abstract
Segments of the genome inherited from a common ancestor by related individuals are said to be identical by descent (IBD). Modern genetic marker data provide information to infer such segments among multiple related members of a population, even when pedigree relationships are unknown. Previous methods have been proposed for the detection of pairwise IBD, but the computation of probabilities of trait data under many trait models requires an IBD estimate jointly consistent among individuals and slowly varying across genome locations; we refer to such an estimate as an 'IBD graph'. In this paper, we develop a novel method that builds IBD graphs sequentially among related individuals from a population sample using either phased or unphased genetic marker data. We show how IBD graphs realized conditionally on marker data provide a form of linkage mapping score, analogous to a LOD score, and propose a permutation approach to normalize this mapping score. Using a simulated quantitative trait dependent on the (unobserved) genotype at a major locus, we apply the approach to two samples containing both closely and remotely related individuals, among whom there are complex patterns of IBD. We compare the results of our approach with an alternate approach based on the estimation of local kinship. We show that pairwise estimates derived from a joint IBD graph give significant improvements in LOD score estimation over estimates derived from an intrinsically pairwise approach.
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Affiliation(s)
- Chris Glazner
- Department of Statistics, University of Washington, Seattle, Wash., USA
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13
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Zheng C, Kuhner MK, Thompson EA. Joint inference of identity by descent along multiple chromosomes from population samples. J Comput Biol 2014; 21:185-200. [PMID: 24606562 DOI: 10.1089/cmb.2013.0140] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
There has been much interest in detecting genomic identity by descent (IBD) segments from modern dense genetic marker data and in using them to identify human disease susceptibility loci. Here we present a novel Bayesian framework using Markov chain Monte Carlo (MCMC) realizations to jointly infer IBD states among multiple individuals not known to be related, together with the allelic typing error rate and the IBD process parameters. The data are phased single nucleotide polymorphism (SNP) haplotypes. We model changes in latent IBD state along homologous chromosomes by a continuous time Markov model having the Ewens sampling formula as its stationary distribution. We show by simulation that this model for the IBD process fits quite well with the coalescent predictions. Using simulation data sets of 40 haplotypes over regions of 1 and 10 million base pairs (Mbp), we show that the jointly estimated IBD states are very close to the true values, although the presence of linkage disequilibrium decreases the accuracy. We also present comparisons with the ibd_haplo program, which estimates IBD among sets of four haplotypes. Our new IBD detection method focuses on the scale between genome-wide methods using simple IBD models and complex coalescent-based methods that are limited to short genome segments. At the scale of a few Mbp, our approach offers potentially more power for fine-scale IBD association mapping.
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Affiliation(s)
- Chaozhi Zheng
- 1 Department of Statistics, University of Washington , Seattle, Washington
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14
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Carmi S, Wilton PR, Wakeley J, Pe'er I. A renewal theory approach to IBD sharing. Theor Popul Biol 2014; 97:35-48. [PMID: 25149691 DOI: 10.1016/j.tpb.2014.08.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Revised: 07/30/2014] [Accepted: 08/08/2014] [Indexed: 10/24/2022]
Abstract
A long genomic segment inherited by a pair of individuals from a single, recent common ancestor is said to be identical-by-descent (IBD). Shared IBD segments have numerous applications in genetics, from demographic inference to phasing, imputation, pedigree reconstruction, and disease mapping. Here, we provide a theoretical analysis of IBD sharing under Markovian approximations of the coalescent with recombination. We describe a general framework for the IBD process along the chromosome under the Markovian models (SMC/SMC'), as well as introduce and justify a new model, which we term the renewal approximation, under which lengths of successive segments are independent. Then, considering the infinite-chromosome limit of the IBD process, we recover previous results (for SMC) and derive new results (for SMC') for the mean number of shared segments longer than a cutoff and the fraction of the chromosome found in such segments. We then use renewal theory to derive an expression (in Laplace space) for the distribution of the number of shared segments and demonstrate implications for demographic inference. We also compute (again, in Laplace space) the distribution of the fraction of the chromosome in shared segments, from which we obtain explicit expressions for the first two moments. Finally, we generalize all results to populations with a variable effective size.
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Affiliation(s)
- Shai Carmi
- Department of Computer Science, Columbia University, New York, NY, 10027, USA.
| | - Peter R Wilton
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - John Wakeley
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Itsik Pe'er
- Department of Computer Science, Columbia University, New York, NY, 10027, USA
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15
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Balliu B, Uh HW, Tsonaka R, Boehringer S, Helmer Q, Houwing-Duistermaat JJ. Combining information from linkage and association mapping for next-generation sequencing longitudinal family data. BMC Proc 2014; 8:S34. [PMID: 25519382 PMCID: PMC4143620 DOI: 10.1186/1753-6561-8-s1-s34] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
In this analysis, we investigate the contributions that linkage-based methods, such as identical-by-descent mapping, can make to association mapping to identify rare variants in next-generation sequencing data. First, we identify regions in which cases share more segments identical-by-descent around a putative causal variant than do controls. Second, we use a two-stage mixed-effect model approach to summarize the single-nucleotide polymorphism data within each region and include them as covariates in the model for the phenotype. We assess the impact of linkage disequilibrium in determining identical-by-descent states between individuals by using markers with and without linkage disequilibrium for the first part and the impact of imputation in testing for association by using imputed genome-wide association studies or raw sequence markers for the second part. We apply the method to next-generation sequencing longitudinal family data from Genetic Association Workshop 18 and identify a significant region at chromosome 3: 40249244-41025167 (p-value = 2.3 × 10−3).
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Affiliation(s)
- Brunilda Balliu
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
| | - Hae-Won Uh
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands ; Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Roula Tsonaka
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
| | - Stefan Boehringer
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
| | - Quinta Helmer
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands ; Netherlands Consortium for Healthy Ageing, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Jeanine J Houwing-Duistermaat
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
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16
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Zheng C, Kuhner MK, Thompson EA. Bayesian inference of local trees along chromosomes by the sequential Markov coalescent. J Mol Evol 2014; 78:279-92. [PMID: 24817610 PMCID: PMC4104301 DOI: 10.1007/s00239-014-9620-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Accepted: 04/18/2014] [Indexed: 11/30/2022]
Abstract
We propose a genealogy-sampling algorithm, Sequential Markov Ancestral Recombination Tree (SMARTree), that provides an approach to estimation from SNP haplotype data of the patterns of coancestry across a genome segment among a set of homologous chromosomes. To enable analysis across longer segments of genome, the sequence of coalescent trees is modeled via the modified sequential Markov coalescent (Marjoram and Wall, Genetics 7:16, 2006). To assess performance in estimating these local trees, our SMARTree implementation is tested on simulated data. Our base data set is of the SNPs in 10 DNA sequences over 50 kb. We examine the effects of longer sequences and of more sequences, and of a recombination and/or mutational hotspot. The model underlying SMARTree is an approximation to the full recombinant-coalescent distribution. However, in a small trial on simulated data, recovery of local trees was similar to that of LAMARC (Kuhner et al. Genetics 156:1393-1401, 2000a), a sampler which uses the full model.
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Affiliation(s)
- Chaozhi Zheng
- Department of Statistics, Box 354322, University of Washington, Seattle, WA 98115-4322, USA, Tel.: (206) 543-7237, Fax: (206) 685-7419
| | - Mary K. Kuhner
- Department of Genome Sciences, Box 355065, University of Washington, Seattle, WA 98115-5065, USA, Tel.: (206) 543-8751, Fax: (206) 685-7301
| | - Elizabeth A. Thompson
- Department of Statistics, Box 354322, University of Washington, Seattle, WA 98115-4322, USA, Tel.: (206) 685-0108, Fax: (206) 685-7419
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17
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Durand EY, Eriksson N, McLean CY. Reducing pervasive false-positive identical-by-descent segments detected by large-scale pedigree analysis. Mol Biol Evol 2014; 31:2212-22. [PMID: 24784137 PMCID: PMC4104314 DOI: 10.1093/molbev/msu151] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Analysis of genomic segments shared identical-by-descent (IBD) between individuals is fundamental to many genetic applications, from demographic inference to estimating the heritability of diseases, but IBD detection accuracy in nonsimulated data is largely unknown. In principle, it can be evaluated using known pedigrees, as IBD segments are by definition inherited without recombination down a family tree. We extracted 25,432 genotyped European individuals containing 2,952 father-mother-child trios from the 23andMe, Inc. data set. We then used GERMLINE, a widely used IBD detection method, to detect IBD segments within this cohort. Exploiting known familial relationships, we identified a false-positive rate over 67% for 2-4 centiMorgan (cM) segments, in sharp contrast with accuracies reported in simulated data at these sizes. Nearly all false positives arose from the allowance of haplotype switch errors when detecting IBD, a necessity for retrieving long (>6 cM) segments in the presence of imperfect phasing. We introduce HaploScore, a novel, computationally efficient metric that scores IBD segments proportional to the number of switch errors they contain. Applying HaploScore filtering to the IBD data at a precision of 0.8 produced a 13-fold increase in recall when compared with length-based filtering. We replicate the false IBD findings and demonstrate the generalizability of HaploScore to alternative data sources using an independent cohort of 555 European individuals from the 1000 Genomes project. HaploScore can improve the accuracy of segments reported by any IBD detection method, provided that estimates of the genotyping error rate and switch error rate are available.
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18
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Gauvin H, Moreau C, Lefebvre JF, Laprise C, Vézina H, Labuda D, Roy-Gagnon MH. Genome-wide patterns of identity-by-descent sharing in the French Canadian founder population. Eur J Hum Genet 2013; 22:814-21. [PMID: 24129432 PMCID: PMC4023206 DOI: 10.1038/ejhg.2013.227] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2013] [Revised: 08/07/2013] [Accepted: 09/04/2013] [Indexed: 12/16/2022] Open
Abstract
In genetics the ability to accurately describe the familial relationships among a group of individuals can be very useful. Recent statistical tools succeeded in assessing the degree of relatedness up to 6-7 generations with good power using dense genome-wide single-nucleotide polymorphism data to estimate the extent of identity-by-descent (IBD) sharing. It is therefore important to describe genome-wide patterns of IBD sharing for more remote and complex relatedness between individuals, such as that observed in a founder population like Quebec, Canada. Taking advantage of the extended genealogical records of the French Canadian founder population, we first compared different tools to identify regions of IBD in order to best describe genome-wide IBD sharing and its correlation with genealogical characteristics. Results showed that the extent of IBD sharing identified with FastIBD correlates best with relatedness measured using genealogical data. Total length of IBD sharing explained 85% of the genealogical kinship's variance. In addition, we observed significantly higher sharing in pairs of individuals with at least one inbred ancestor compared with those without any. Furthermore, patterns of IBD sharing and average sharing were different across regional populations, consistent with the settlement history of Quebec. Our results suggest that, as expected, the complex relatedness present in founder populations is reflected in patterns of IBD sharing. Using these patterns, it is thus possible to gain insight on the types of distant relationships in a sample from a founder population like Quebec.
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Affiliation(s)
- Héloïse Gauvin
- 1] Département de médecine sociale et préventive, Université de Montréal, Montréal, Québec, Canada [2] Centre de recherche, Centre hospitalier universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Claudia Moreau
- Centre de recherche, Centre hospitalier universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Jean-François Lefebvre
- Centre de recherche, Centre hospitalier universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Catherine Laprise
- Département des sciences fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Québec, Canada
| | - Hélène Vézina
- Département des sciences humaines, Université du Québec à Chicoutimi, Chicoutimi, Québec, Canada
| | - Damian Labuda
- 1] Centre de recherche, Centre hospitalier universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada [2] Département de pédiatrie, Université de Montréal, Montréal, Québec, Canada
| | - Marie-Hélène Roy-Gagnon
- 1] Centre de recherche, Centre hospitalier universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada [2] Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
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19
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Koepke H, Thompson E. Efficient identification of equivalences in dynamic graphs and pedigree structures. J Comput Biol 2013; 20:551-70. [PMID: 23899011 PMCID: PMC3728728 DOI: 10.1089/cmb.2013.0032] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
We propose a new framework for designing test and query functions for complex structures that vary across a given parameter such as genetic marker position. The operations we are interested in include equality testing, set operations, isolating unique states, duplication counting, or finding equivalence classes under identifiability constraints. A motivating application is locating equivalence classes in identity-by-descent (IBD) graphs, which are graph structures in pedigree analysis that change over genetic marker location. The nodes of these graphs are unlabeled and identified only by their connecting edges, a constraint easily handled by our approach. The general framework introduced is powerful enough to build a range of testing functions for IBD graphs, dynamic populations, and other structures using a minimal set of operations. The theoretical and algorithmic properties of our approach are analyzed and proved. Computational results on several simulations demonstrate the effectiveness of our approach.
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Affiliation(s)
- Hoyt Koepke
- University of Washington, Department of Statistics, Washington 98195, USA.
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20
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Thompson EA. Identity by descent: variation in meiosis, across genomes, and in populations. Genetics 2013; 194:301-26. [PMID: 23733848 PMCID: PMC3664843 DOI: 10.1534/genetics.112.148825] [Citation(s) in RCA: 199] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2012] [Accepted: 03/10/2013] [Indexed: 01/04/2023] Open
Abstract
Gene identity by descent (IBD) is a fundamental concept that underlies genetically mediated similarities among relatives. Gene IBD is traced through ancestral meioses and is defined relative to founders of a pedigree, or to some time point or mutational origin in the coalescent of a set of extant genes in a population. The random process underlying changes in the patterns of IBD across the genome is recombination, so the natural context for defining IBD is the ancestral recombination graph (ARG), which specifies the complete ancestry of a collection of chromosomes. The ARG determines both the sequence of coalescent ancestries across the chromosome and the extant segments of DNA descending unbroken by recombination from their most recent common ancestor (MRCA). DNA segments IBD from a recent common ancestor have high probability of being of the same allelic type. Non-IBD DNA is modeled as of independent allelic type, but the population frame of reference for defining allelic independence can vary. Whether of IBD, allelic similarity, or phenotypic covariance, comparisons may be made to other genomic regions of the same gametes, or to the same genomic regions in other sets of gametes or diploid individuals. In this review, I present IBD as the framework connecting evolutionary and coalescent theory with the analysis of genetic data observed on individuals. I focus on the high variance of the processes that determine IBD, its changes across the genome, and its impact on observable data.
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Affiliation(s)
- Elizabeth A Thompson
- Department of Statistics, University of Washington, Seattle, WA 98195-4322, USA.
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21
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Ralph P, Coop G. The geography of recent genetic ancestry across Europe. PLoS Biol 2013; 11:e1001555. [PMID: 23667324 PMCID: PMC3646727 DOI: 10.1371/journal.pbio.1001555] [Citation(s) in RCA: 192] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Accepted: 03/27/2013] [Indexed: 01/11/2023] Open
Abstract
A genomic survey of recent genealogical relatedness reveals the close ties of kinship and the impact of events across the past 3,000 years of European history. The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (in the Population Reference Sample [POPRES] dataset) to conduct one of the first surveys of recent genealogical ancestry over the past 3,000 years at a continental scale. We detected 1.9 million shared long genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 2–12 genetic common ancestors from the last 1,500 years, and upwards of 100 genetic ancestors from the previous 1,000 years. These numbers drop off exponentially with geographic distance, but since these genetic ancestors are a tiny fraction of common genealogical ancestors, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1,000 years. There is also substantial regional variation in the number of shared genetic ancestors. For example, there are especially high numbers of common ancestors shared between many eastern populations that date roughly to the migration period (which includes the Slavic and Hunnic expansions into that region). Some of the lowest levels of common ancestry are seen in the Italian and Iberian peninsulas, which may indicate different effects of historical population expansions in these areas and/or more stably structured populations. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world. Few of us know our family histories more than a few generations back. It is therefore easy to overlook the fact that we are all distant cousins, related to one another via a vast network of relationships. Here we use genome-wide data from European individuals to investigate these relationships over the past 3,000 years, by looking for long stretches of genome that are shared between pairs of individuals through their inheritance from common genetic ancestors. We quantify this ubiquitous recent common ancestry, showing for instance that even pairs of individuals from opposite ends of Europe share hundreds of genetic common ancestors over this time period. Despite this degree of commonality, there are also striking regional differences. Southeastern Europeans, for example, share large numbers of common ancestors that date roughly to the era of the Slavic and Hunnic expansions around 1,500 years ago, while most common ancestors that Italians share with other populations lived longer than 2,500 years ago. The study of long stretches of shared genetic material promises to uncover rich information about many aspects of recent population history.
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Affiliation(s)
- Peter Ralph
- Department of Evolution and Ecology & Center for Population Biology, University of California, Davis, California, United States of America
- * E-mail: (PR); (GC)
| | - Graham Coop
- Department of Evolution and Ecology & Center for Population Biology, University of California, Davis, California, United States of America
- * E-mail: (PR); (GC)
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22
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Abstract
Segments of indentity-by-descent (IBD) detected from high-density genetic data are useful for many applications, including long-range phase determination, phasing family data, imputation, IBD mapping, and heritability analysis in founder populations. We present Refined IBD, a new method for IBD segment detection. Refined IBD achieves both computational efficiency and highly accurate IBD segment reporting by searching for IBD in two steps. The first step (identification) uses the GERMLINE algorithm to find shared haplotypes exceeding a length threshold. The second step (refinement) evaluates candidate segments with a probabilistic approach to assess the evidence for IBD. Like GERMLINE, Refined IBD allows for IBD reporting on a haplotype level, which facilitates determination of multi-individual IBD and allows for haplotype-based downstream analyses. To investigate the properties of Refined IBD, we simulate SNP data from a model with recent superexponential population growth that is designed to match United Kingdom data. The simulation results show that Refined IBD achieves a better power/accuracy profile than fastIBD or GERMLINE. We find that a single run of Refined IBD achieves greater power than 10 runs of fastIBD. We also apply Refined IBD to SNP data for samples from the United Kingdom and from Northern Finland and describe the IBD sharing in these data sets. Refined IBD is powerful, highly accurate, and easy to use and is implemented in Beagle version 4.
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23
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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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Browning SR, Browning BL. Identity by descent between distant relatives: detection and applications. Annu Rev Genet 2012; 46:617-33. [PMID: 22994355 DOI: 10.1146/annurev-genet-110711-155534] [Citation(s) in RCA: 114] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Short segments of identity by descent (IBD) between individuals with no known relationship can be detected using genome-wide single nucleotide polymorphism data and recently developed statistical methodology. Emerging applications for the detected IBD segments include IBD mapping, haplotype phase inference, genotype imputation, and inference of population structure. In this review, we explain the principles behind methods for IBD segment detection, describe recently developed methods, discuss approaches to comparing methods, and give an overview of applications.
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Affiliation(s)
- Sharon R Browning
- Department of Statistics, University of Washington, Seattle, Washington 98195, USA.
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25
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Abstract
Identity-by-descent (IBD) mapping tests whether cases share more segments of IBD around a putative causal variant than do controls. These segments of IBD can be accurately detected from genome-wide SNP data. We investigate the power of IBD mapping relative to that of SNP association testing for genome-wide case-control SNP data. Our focus is particularly on rare variants, as these tend to be more recent and hence more likely to have recent shared ancestry. We simulate data from both large and small populations and find that the relative performance of IBD mapping and SNP association testing depends on population demographic history and the strength of selection against causal variants. We also present an IBD mapping analysis of a type 1 diabetes data set. In those data we find that we can detect association only with the HLA region using IBD mapping. Overall, our results suggest that IBD mapping may have higher power than association analysis of SNP data when multiple rare causal variants are clustered within a gene. However, for outbred populations, very large sample sizes may be required for genome-wide significance unless the causal variants have strong effects.
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26
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Improving pedigree-based linkage analysis by estimating coancestry among families. Stat Appl Genet Mol Biol 2012; 11:/j/sagmb.2012.11.issue-2/1544-6115.1718/1544-6115.1718.xml. [PMID: 22499699 DOI: 10.2202/1544-6115.1718] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
We present a method for improving the power of linkage analysis by detecting chromosome segments shared identical by descent (IBD) by individuals not known to be related. Existing Markov chain Monte Carlo methods sample descent patterns on pedigrees conditional on observed marker data. These patterns can be stored as IBD graphs, which express shared ancestry only, rather than specific family relationships. A model for IBD between unrelated individuals allows the estimation of coancestry between individuals in different pedigrees. IBD graphs on separate pedigrees can then be combined using these estimates. We report results from analyses of three sets of simulated marker data on two different pedigrees. We show that when families share a gene for a trait due to shared ancestry on the order of tens of generations, our method can detect a linkage signal when independent analyses of the families do not.
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