A Fast Identity-By-Descent Mapping Test for Biobank-Scale Cohorts
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Population Genetic Considerations for Using Biobanks As International
Carress et al. BMC Genomics (2021) 22:351 https://doi.org/10.1186/s12864-021-07618-x REVIEW Open Access Population genetic considerations for using biobanks as international resources in the pandemic era and beyond Hannah Carress1, Daniel John Lawson2 and Eran Elhaik1,3* Abstract The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts. Keywords: Bioinformatics, Population structure, Population stratification bias, Genomic medicine, Biobanks Background individuals, families, communities and populations, ne- Association studies aim to detect whether genetic vari- cessitated genomic biobanks. -
Gene Linkage and Genetic Mapping 4TH PAGES © Jones & Bartlett Learning, LLC
© Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Gene Linkage and © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC 4NOTGenetic FOR SALE OR DISTRIBUTIONMapping NOT FOR SALE OR DISTRIBUTION CHAPTER ORGANIZATION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR4.1 SALELinked OR alleles DISTRIBUTION tend to stay 4.4NOT Polymorphic FOR SALE DNA ORsequences DISTRIBUTION are together in meiosis. 112 used in human genetic mapping. 128 The degree of linkage is measured by the Single-nucleotide polymorphisms (SNPs) frequency of recombination. 113 are abundant in the human genome. 129 The frequency of recombination is the same SNPs in restriction sites yield restriction for coupling and repulsion heterozygotes. 114 fragment length polymorphisms (RFLPs). 130 © Jones & Bartlett Learning,The frequency LLC of recombination differs © Jones & BartlettSimple-sequence Learning, repeats LLC (SSRs) often NOT FOR SALE OR DISTRIBUTIONfrom one gene pair to the next. NOT114 FOR SALEdiffer OR in copyDISTRIBUTION number. 131 Recombination does not occur in Gene dosage can differ owing to copy- Drosophila males. 115 number variation (CNV). 133 4.2 Recombination results from Copy-number variation has helped human populations adapt to a high-starch diet. 134 crossing-over between linked© Jones alleles. & Bartlett Learning,116 LLC 4.5 Tetrads contain© Jonesall & Bartlett Learning, LLC four products of meiosis. -
Natural Selection and the Distribution of Identity-By-Descent in the Human Genome
Copyright Ó 2010 by the Genetics Society of America DOI: 10.1534/genetics.110.113977 Natural Selection and the Distribution of Identity-by-Descent in the Human Genome Anders Albrechtsen,*,1,2 Ida Moltke†,1 and Rasmus Nielsen‡ *Department of Biostatistics, University of Copenhagen, Copenhagen, 1014, Denmark, †Center for Bioinformatics, Copenhagen, 2200, Denmark and ‡Department of Integrative Biology and Statistics, University of California, Berkeley, California 94720 Manuscript received April 30, 2010 Accepted for publication June 14, 2010 ABSTRACT There has recently been considerable interest in detecting natural selection in the human genome. Selection will usually tend to increase identity-by-descent (IBD) among individuals in a population, and many methods for detecting recent and ongoing positive selection indirectly take advantage of this. In this article we show that excess IBD sharing is a general property of natural selection and we show that this fact makes it possible to detect several types of selection including a type that is otherwise difficult to detect: selection acting on standing genetic variation. Motivated by this, we use a recently developed method for identifying IBD sharing among individuals from genome-wide data to scan populations from the new HapMap phase 3 project for regions with excess IBD sharing in order to identify regions in the human genome that have been under strong, very recent selection. The HLA region is by far the region showing the most extreme signal, suggesting that much of the strong recent selection acting on the human genome has been immune related and acting on HLA loci. As equilibrium overdominance does not tend to increase IBD, we argue that this type of selection cannot explain our observations. -
Genetic Linkage Analysis
BASIC SCIENCE SEMINARS IN NEUROLOGY SECTION EDITOR: HASSAN M. FATHALLAH-SHAYKH, MD Genetic Linkage Analysis Stefan M. Pulst, MD enetic linkage analysis is a powerful tool to detect the chromosomal location of dis- ease genes. It is based on the observation that genes that reside physically close on a chromosome remain linked during meiosis. For most neurologic diseases for which the underlying biochemical defect was not known, the identification of the chromo- Gsomal location of the disease gene was the first step in its eventual isolation. By now, genes that have been isolated in this way include examples from all types of neurologic diseases, from neu- rodegenerative diseases such as Alzheimer, Parkinson, or ataxias, to diseases of ion channels lead- ing to periodic paralysis or hemiplegic migraine, to tumor syndromes such as neurofibromatosis types 1 and 2. Arch Neurol. 1999;56:667-672 With the advent of new genetic markers tin gene, diagnosis using flanking mark- and automated genotyping, genetic map- ers requires the analysis of several family ping can be conducted extremely rap- members. idly. Genetic linkage maps have been gen- erated for the human genome and for LINKAGE OF GENES model organisms and have provided the basis for the construction of physical maps When Mendel observed an “independent that permit the rapid mapping of disease assortment of traits” (Mendel’s second traits. law), he was fortunate to have chosen traits As soon as a chromosomal location that were not localized close to one an- for a disease phenotype has been estab- other on the same chromosome.1 Subse- lished, genetic linkage analysis helps quent studies revealed that many genes determine whether the disease pheno- were indeed linked, ie, that traits did not type is only caused by mutation in a assort or segregate independently, but that single gene or mutations in other genes traits encoded by these linked genes were can give rise to an identical or similar inherited together. -
Identity by Descent in Pedigrees and Populations; Methods for Genome-Wide Linkage and Association
Identity by descent in pedigrees and populations Overview - 1 Identity by descent in pedigrees and populations; methods for genome-wide linkage and association. UNE Short Course: Feb 14-18, 2011 Dr Elizabeth A Thompson UNE-Short Course Feb 2011 Identity by descent in pedigrees and populations Overview - 2 Timetable Monday 9:00-10:30am 1: Introduction and Overview. 11:00am-12:30pm 2: Identity by Descent; relationships and relatedness 1:30-3:00pm 3: Genetic variation and allelic association. 3:30-5:00pm 4: Allelic association and population structure. Tuesday 9:00-10:30am 5: Genetic associations for a quantitative trait 11:00am-12:30pm 6: Hidden Markov models; HMM 1:30-3:00pm 7: Haplotype blocks and the coalescent. 3:30-5:00pm 8: LD mapping via coalescent ancestry. Wednesday a.m. 9:00-10:30am 9: The EM algorithm 11:00am-12:30pm 10: MCMC and Bayesian sampling Dr Elizabeth A Thompson UNE-Short Course Feb 2011 Identity by descent in pedigrees and populations Overview - 3 Wednesday p.m. 1:30-3:00pm 11: Association mapping in structured populations 3:30-5:00pm 12: Association mapping in admixed populations Thursday 9:00-10:30am 13: Inferring ibd segments; two chromosomes. 11:00am-12:30pm 14: BEAGLE: Haplotype and ibd imputation. 1:30-3:00pm 15: ibd between two individuals. 3:30-5:00pm 16: ibd among multiple chromosomes. Friday 9:00-10:30am 17: Pedigrees in populations. 11:00am-12:30pm 18: Lod scores within and between pedigrees. 1:30-3:00pm 19: Wrap-up and questions. Bibliography Software notes and links. -
Genetic Linkage of the Huntington's Disease Gene to a DNA Marker James F
LE JOURNAL CANADIEN DES SCIENCES NEUROLOG1QUES SPECIAL FEATURE Genetic Linkage of the Huntington's Disease Gene to a DNA Marker James F. Gusella ABSTRACT: Recombinant DNA techniques have provided the means to generate large numbers of new genetic linkage markers. This technology has been used to identify a DNA marker that coinherits with the Huntington's Disease (HD) gene in family studies. The HD locus has thereby been mapped to human chromosome 4. The discovery of a genetic marker for the inheritance of HD has implications both for patient care and future research. The same approach holds considerable promise for the investigation of other genetic diseases, including Dystonia Musculorum Deformans. RESUME: Les techniques d'ADN recombine ont fourni le moyen de g£nerer un grand nombre de nouveux marqueurs a liason g6n£tique. Cette technologie a He employe" afin d'identifier un marqueur d'ADN qui co-herite avec le gene de la maladie de Huntington (MH) dans les etudes familiales. Le lieu du gene de la MH a ainsi 6te localise sur le chromosome humain numero 4. La d6couverte d'un marqueur g6n6tique pour I'her6dit6 de MH a des implications pour la soin de patients ainsi que pour la recherche dans le futur. La meme approche semble pleine de promesses pour l'investigation d'autres maladies g6ndtiques, incluant la dystonie musculaire deTormante. Can. J. Neurol. Sci. 1984; 11:421-425 Huntington's Disease currently no effective therapy to cure this devastating disease, Huntington's disease (HD) is a genetic neurodegenerative or to slow its inexorable progression. disorder first described by George Huntington in 1873 (Hunting ton, 1972;Hayden, 1981;Chaseetal., 1979). -
Prediction of Identity by Descent Probabilities from Marker-Haplotypes Theo Meuwissen, Mike Goddard
Prediction of identity by descent probabilities from marker-haplotypes Theo Meuwissen, Mike Goddard To cite this version: Theo Meuwissen, Mike Goddard. Prediction of identity by descent probabilities from marker-haplotypes. Genetics Selection Evolution, BioMed Central, 2001, 33 (6), pp.605-634. 10.1051/gse:2001134. hal-00894392 HAL Id: hal-00894392 https://hal.archives-ouvertes.fr/hal-00894392 Submitted on 1 Jan 2001 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Genet. Sel. Evol. 33 (2001) 605–634 605 © INRA, EDP Sciences, 2001 Original article Prediction of identity by descent probabilities from marker-haplotypes a; b Theo H.E. MEUWISSEN ∗, Mike E. GODDARD a Research Institute of Animal Science and Health, Box 65, 8200 AB Lelystad, The Netherlands b Institute of Land and Food Resources, University of Melbourne, Parkville Victorian Institute of Animal Science, Attwood, Victoria, Australia (Received 13 February 2001; accepted 11 June 2001) Abstract – The prediction of identity by descent (IBD) probabilities is essential for all methods that map quantitative trait loci (QTL). The IBD probabilities may be predicted from marker genotypes and/or pedigree information. Here, a method is presented that predicts IBD prob- abilities at a given chromosomal location given data on a haplotype of markers spanning that position. -
Linkage & Genetic Mapping in Eukaryotes
LinLinkkaaggee && GGeenneetticic MMaappppiningg inin EEuukkaarryyootteess CChh.. 66 1 LLIINNKKAAGGEE AANNDD CCRROOSSSSIINNGG OOVVEERR ! IInn eeuukkaarryyoottiicc ssppeecciieess,, eeaacchh lliinneeaarr cchhrroommoossoommee ccoonnttaaiinnss aa lloonngg ppiieeccee ooff DDNNAA – A typical chromosome contains many hundred or even a few thousand different genes ! TThhee tteerrmm lliinnkkaaggee hhaass ttwwoo rreellaatteedd mmeeaanniinnggss – 1. Two or more genes can be located on the same chromosome – 2. Genes that are close together tend to be transmitted as a unit Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display 2 LinkageLinkage GroupsGroups ! Chromosomes are called linkage groups – They contain a group of genes that are linked together ! The number of linkage groups is the number of types of chromosomes of the species – For example, in humans " 22 autosomal linkage groups " An X chromosome linkage group " A Y chromosome linkage group ! Genes that are far apart on the same chromosome can independently assort from each other – This is due to crossing-over or recombination Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display 3 LLiinnkkaaggee aanndd RRecombinationecombination Genes nearby on the same chromosome tend to stay together during the formation of gametes; this is linkage. The breakage of the chromosome, the separation of the genes, and the exchange of genes between chromatids is known as recombination. (we call it crossing over) 4 IndependentIndependent assortment:assortment: -
Frontiers in Coalescent Theory: Pedigrees, Identity-By-Descent, and Sequentially Markov Coalescent Models
Frontiers in Coalescent Theory: Pedigrees, Identity-by-Descent, and Sequentially Markov Coalescent Models The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Wilton, Peter R. 2016. Frontiers in Coalescent Theory: Pedigrees, Identity-by-Descent, and Sequentially Markov Coalescent Models. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493608 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Frontiers in Coalescent Theory: Pedigrees, Identity-by-descent, and Sequentially Markov Coalescent Models a dissertation presented by Peter Richard Wilton to The Department of Organismic and Evolutionary Biology in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Biology Harvard University Cambridge, Massachusetts May 2016 ©2016 – Peter Richard Wilton all rights reserved. Thesis advisor: Professor John Wakeley Peter Richard Wilton Frontiers in Coalescent Theory: Pedigrees, Identity-by-descent, and Sequentially Markov Coalescent Models Abstract The coalescent is a stochastic process that describes the genetic ancestry of individuals sampled from a population. It is one of the main tools of theoretical population genetics and has been used as the basis of many sophisticated methods of inferring the demo- graphic history of a population from a genetic sample. This dissertation is presented in four chapters, each developing coalescent theory to some degree. -
Identity-By-Descent Detection Across 487,409 British Samples Reveals Fine Scale Population Structure and Ultra-Rare Variant Asso
ARTICLE https://doi.org/10.1038/s41467-020-19588-x OPEN Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations ✉ Juba Nait Saada 1 , Georgios Kalantzis 1, Derek Shyr 2, Fergus Cooper 3, Martin Robinson 3, ✉ Alexander Gusev 4,5,7 & Pier Francesco Palamara 1,6,7 1234567890():,; Detection of Identical-By-Descent (IBD) segments provides a fundamental measure of genetic relatedness and plays a key role in a wide range of analyses. We develop FastSMC, an IBD detection algorithm that combines a fast heuristic search with accurate coalescent-based likelihood calculations. FastSMC enables biobank-scale detection and dating of IBD segments within several thousands of years in the past. We apply FastSMC to 487,409 UK Biobank samples and detect ~214 billion IBD segments transmitted by shared ancestors within the past 1500 years, obtaining a fine-grained picture of genetic relatedness in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the use of genomic data to localize a sample’s birth coordinates with a median error of 45 km. We seek evidence of recent positive selection by identifying loci with unusually strong shared ancestry and detect 12 genome-wide significant signals. We devise an IBD-based test for association between phenotype and ultra-rare loss-of-function variation, identifying 29 association sig- nals in 7 blood-related traits. 1 Department of Statistics, University of Oxford, Oxford, UK. 2 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. 3 Department of Computer Science, University of Oxford, Oxford, UK. -
Variation in Meiosis, Across Genomes, and in Populations
REVIEW Identity by Descent: Variation in Meiosis, Across Genomes, and in Populations Elizabeth A. Thompson1 Department of Statistics, University of Washington, Seattle, Washington 98195-4322 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. -
Identity-By-Descent Analyses for Measuring Population Dynamics and Selection in Recombining Pathogens
bioRxiv preprint doi: https://doi.org/10.1101/088039; this version posted March 14, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Identity-by-descent analyses for measuring population dynamics 2 and selection in recombining pathogens 3 4 Lyndal Henden1,2, Stuart Lee3,4, Ivo Mueller1,2, Alyssa Barry1,2, Melanie Bahlo1,2,* 5 6 1. Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical 7 Research, Parkville VIC, Australia 8 2. Department of Medical Biology, University of Melbourne, Parkville VIC, Australia 9 3. Department of Econometrics and Business Statistics, Monash University, Clayton VIC, 10 Australia 11 4. Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, 12 Parkville VIC, Australia 13 14 * Corresponding author 15 E-mail: [email protected] (MB) 16 17 18 19 20 21 22 23 24 25 1 bioRxiv preprint doi: https://doi.org/10.1101/088039; this version posted March 14, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 26 Abstract 27 28 Identification of genomic regions that are identical by descent (IBD) has proven useful for human 29 genetic studies where analyses have led to the discovery of familial relatedness and fine-mapping 30 of disease critical regions.