DOCSLIB.ORG

Population Genetic Considerations for Using Biobanks As International

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
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. ants found in different individuals are associated with a The completion of the human genome allowed gen- trait or disease of interest, by comparing the DNA of in- omic biobanks to be envisioned. The International Hap- dividuals that vary in relation to the phenotypes [1]. For Map Project, practically the first international biobank example, the major-histocompatibility-complex antigen [3], facilitated the routine collection of data for genome- loci are the prototypical candidates that modulate the wide association studies (GWAS) [4]. GWAS to improve genetic susceptibility to infectious diseases. As a result, clarity soon after became the leading genetic tool for association studies aim to identify which loci may pro- phenotype-genotype investigations. Over time, GWAS vide valuable information for strategising prevention, have been used to identify associations between thou- treatment, vaccination and clinical approaches [2]. Such sands of variants for a wide variety of traits and diseases, cardinal questions striking the core differences between with mixed results. GWAS drew much criticism con- cerning their validity, error rate, interpretation, applica- tion, biological causation [5] and replication [6]. Since * Correspondence: [email protected] 1Department of Animal and Plant Sciences, University of Sheffield, Sheffield, much of this criticism was due to spurious associations UK yielded from small sample sizes with reduced power of 3Department of Biology, Lund University, Lund, Sweden association analyses, major efforts were taken to recruit Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Carress et al. BMC Genomics (2021) 22:351 Page 2 of 19 tens of thousands of participants into studies where their remained largely inaccessible, and the company filed for biological data and prognosis were collected. These col- bankruptcy [19]. The experience of deCODE highlighted lections served as the basis for what is considered today the risks in entrusting private companies to manage gen- as a (genomic) biobank [7]. omic databases, promoting similar efforts to have at least Today, biobanks are known as massive scale datasets partial government control in the dozens of newly containing many hundreds of thousands of participants founded biobanks (reviewed in [20]), as illustrated in from specified populations. Biobanks have brought enor- Fig. 1. Moreover, as the use of biobanks is expanding be- mous power to association studies. Although it was un- yond their locality, for example, in the case of rare con- clear whether these new databases would deliver their ditions where samples need to be pooled from multiple most ambitious promises, the potential of biobanks in biobanks, the view of biobanks should be changed from enabling personalised treatment was noted before the locally-managed resources to more global resources. technology matured. It was initially expected that these These should adhere to international standards to in- databases would lead to the rapid discovery of a better crease the accuracy of association studies and the use of genetic understanding of complex disorders, allowing for biobanks [21]. personalised treatments [8]. However, it is now clear Even past the formation of biobanks, many associa- that this expectation was exaggerated [8]. For example, a tions results failed to replicate (e.g., [22]) or show a dif- comprehensive review of the genomics of hypertension ference in the effect across worldwide populations, in on its way to personalised medicine concluded that des- traits and disorders like body-mass index (BMI) [23], pite the wealth of identified genomic signals, actionable schizophrenia [24], hypertension [25] and Parkinsons’ results are lacking [9]. No new drugs for the treatment disease [26]. Although strong associations between gen- of hypertension were approved for more than two de- etic variants and a phenotype typically replicated within cades. Moreover, the tailoring of therapy to each patient the population that was studied, they may not have been has not progressed beyond considering self-reported Af- replicated elsewhere. This leads naturally to further rican ancestry and serum renin levels [9]. Another ex- questioning the value and cost-effectiveness of associ- ample is autism, the most extensively studied (40 years) ation studies and biobanks [27] – what do the associa- and heavily funded ($2.4B in NIH funding over the past tions mean, and what are they useful for? How can we ten years [10]) mental disorder with nearly three dozen decide whether the association is relevant for different biobanks [11]. Despite these major efforts at understand- individuals, particularly those of mixed origins or those ing the disorder, there is still no single genetic test for who may not know their origins? What are the consider- autism, not to mention genetic treatment [12]. These ations when designing a new biobank or merging data gloomy reports of the state of knowledge in two of the from multiple biobanks? most studied complex disorders, which typically harness We argue that understanding population structure is a massive biobanks, were not what the biobank enthusiasts key component to answering these questions and con- envisioned at the beginning of the century [8]. tributing to the usefulness of biobanks and their ability Back then, both private and government-sponsored to serve the general population [28–30]. In the following, banks began amassing tissues and data. For example, we review the current state of knowledge on the import- Generation Scotland [13] includes DNA, tissues and ance of population structure to association studies and phenotypic information from nearly 30,000 Scots [14]; biobanks and the implications to downstream analyses. the 100,000 Genomes Project sequenced the genomes of We then review biobank relevant models that describe over 100,000 NHS patients with rare diseases, aiming to population structure. We end with the challenges and understand the aetiology of their conditions from their benefits of the tools that implement these models. genomic data [15]; and the UK Biobank project se- quenced the complete genomes of over half a million in- Main text dividuals [16] with the aim of improving the prevention, Population diversity diagnosis and treatment of a wide range of diseases [17]. Human genetic variation is a significant contributor to Pending projects include the Genome Russia Project, phenotypic variation among individuals and populations, which aims to fill the gap in the mapping of human pop- with single-nucleotide polymorphisms (SNPs) being the ulations by providing the whole-genome sequences
Load more

Recommended publications
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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).
    [Show full text]
  • 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:
    [Show full text]
  • Classical Linkage Mapping
    Mapping the Genome/Clawicul Linku,~c Muppin<y Classical Linkage Mapping Classical linkage analysis is used to determine the arrangement of genes on the chromosomes of an organism. By tmcing how often different forms of two variable traits are co-inherited, we can infer whether the genes for the traits are on the same chromosome (such genes are said to be linked), and if so, we can calculate the genetic distance separating the Ioci of the linked genes. The order of and pairwise distances between the loci of three or more linked genes are displayed as a genetic-linkage map. For simplicity, we will consider traits of the type that Mendel studied, namely, traits exhibiting two forms, or phenotypes, one dominant and one recessive. Each such Mendelian trait is determined by a single pair of genes, either AA, Ao, or aa, where A is the dominant allele (form) of the gene and a is the recessive allele. Many inherited human diseases fall into this category. The two phenotypes are the presence or absence of the disease, and they are determined by a single gene pair, either DD, DN, or NN, where D is the defective allele that causes disease and N is the normal allele. If D is dominant, as in Huntington’s disease and retinoblastoma, a person who inherits only one copy of D, and therefore has the genotype DN, can manifest the disease. Alternatively, if D is recessive, as in neurofibromatosis, cystic fibrosis, and most other inheritable human diseases, a person must inherit a copy of D from each parent (genotype DD) to manifest the disease phenotype.
    [Show full text]
  • Genetic Basis of Falling Risk Susceptibility in the UK Biobank Study
    ARTICLE https://doi.org/10.1038/s42003-020-01256-x OPEN Genetic basis of falling risk susceptibility in the UK Biobank Study Katerina Trajanoska 1, Lotta J. Seppala2, Carolina Medina-Gomez 1, Yi-Hsiang Hsu3,4,5, Sirui Zhou6, Natasja M. van Schoor7, Lisette C. P. G. M. de Groot 8, David Karasik 3,9, J. Brent Richards 6,10,11, Douglas P. Kiel 3,4,12, Andre G. Uitterlinden 1,2, John R. B. Perry1,13, Nathalie van der Velde2, 1234567890():,; ✉ Felix R. Day 1,13,14 & Fernando Rivadeneira 1,14 Both extrinsic and intrinsic factors predispose older people to fall. We performed a genome- wide association analysis to investigate how much of an individual’s fall susceptibility can be attributed to genetics in 89,076 cases and 362,103 controls from the UK Biobank Study. The analysis revealed a small, but significant SNP-based heritability (2.7%) and identified three −8 novel fall-associated loci (Pcombined ≤ 5×10 ). Polygenic risk scores in two independent settings showed patterns of polygenic inheritance. Risk of falling had positive genetic correlations with fractures, identifying for the first time a pathway independent of bone mineral density. There were also positive genetic correlations with insomnia, neuroticism, depressive symptoms, and different medications. Negative genetic correlations were identi- fied with muscle strength, intelligence and subjective well-being. Brain, and in particular cerebellum tissue, showed the highest gene expression enrichment for fall-associated variants. Overall, despite the highly heterogenic nature underlying fall risk, a proportion of the susceptibility can be attributed to genetics. 1 Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
    [Show full text]
  • Genetic Interactions and Linkage
    Genetic Interactions and Linkage Lecture 3 Applied Animal and Plant Breeding GENE 251/351 School of Environment and Rural Science (Genetics) 1 Topics – Relating Genotype to Phenotype – Mendelian genetics and the single locus model – Interactions between alleles at one locus – Interactions between alleles at different loci – Sex specific traits – Linkage – Comparative mapping of genes – Polyploidy 2 Remember Recombination occurs in the gametes to give rise to new combinations of alleles Chromosome number is halved in the gametes Parents pass on only 1 allele of a pair Parents transmit 50% of their genes Progeny receive 2 alleles ( chromosome sets) one from each parent Gene interactions Interactions between alleles at one locus •Dominant/recessive •Co-dominant •Incomplete dominance Interaction between alleles at different genes (loci) can result in Epistatis •Can have varying effects on the phenotype 4 Examples of inheritance model • dominance /recessive model • polledness in cattle, 2 alleles: P and p PP = polled Pp= polled pp = horned • co-dominant • (ABO blood groups) • phenotypes are: A, AB and B (and O) • sex linked – females CC Cc cc – males C- c- example: sex linked genetic defects Additional Examples of Co-dominant traits Colour in Carnations White carnations crossed with red carnations results in pink carnations Feather colour in birds White feathered chickens crossed with black feathered chickens gives chickens with black and white feathers Dominant and Recessive Alleles • For example: Two heterozygous dogs with black coats are crossed. What would their pups look like? (Alternative is brown coat) Parents Phenotype Black x Black Genotype Bb Bb Gametes ½ B, ½ B, ½ b ½ b 7 Offspring Male Gametes B b Female B BB Bb gametes black black b Bb bb black brown Punnett Square • Genotype summary • ¼ BB :½ Bb :¼ bb • Phenotype summary • ¾ Black dogs : ¼ Brown dogs or 3 Black dogs : 1 Brown dog 8 Sex determination • In mammals • Females are the homogametic sex, i.e.
    [Show full text]
  • A Fast Identity-By-Descent Mapping Test for Biobank-Scale Cohorts
    medRxiv preprint doi: https://doi.org/10.1101/2021.06.30.21259773; this version posted July 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license . FiMAP: A Fast Identity-by-Descent Mapping Test for Biobank-scale Cohorts Han Chen1,2,*, Ardalan Naseri2, Degui Zhi1,2,* 1 Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. 2 Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. * Correspondence: [email protected], [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2021.06.30.21259773; this version posted July 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license . Abstract Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants.
    [Show full text]
  • Basic Molecular Genetics for Epidemiologists F Calafell, N Malats
    398 GLOSSARY Basic molecular genetics for epidemiologists F Calafell, N Malats ............................................................................................................................. J Epidemiol Community Health 2003;57:398–400 This is the first of a series of three glossaries on CHROMOSOME molecular genetics. This article focuses on basic Linear or (in bacteria and organelles) circular DNA molecule that constitutes the basic physical molecular terms. block of heredity. Chromosomes in diploid organ- .......................................................................... isms such as humans come in pairs; each member of a pair is inherited from one of the parents. general increase in the number of epide- Humans carry 23 pairs of chromosomes (22 pairs miological research articles that apply basic of autosomes and two sex chromosomes); chromo- science methods in their studies, resulting somes are distinguished by their length (from 48 A to 257 million base pairs) and by their banding in what is known as both molecular and genetic epidemiology, is evident. Actually, genetics has pattern when stained with appropriate methods. come into the epidemiological scene with plenty Homologous chromosome of new sophisticated concepts and methodologi- cal issues. Each of the chromosomes in a pair with respect to This fact led the editors of the journal to offer the other. Homologous chromosomes carry the you a glossary of terms commonly used in papers same set of genes, and recombine with each other applying genetic methods to health problems to during meiosis. facilitate your “walking” around the journal Sex chromosome issues and enjoying the articles while learning. Sex determining chromosome. In humans, as in Obviously, the topics are so extensive and inno- all other mammals, embryos carrying XX sex vative that a single short glossary would not be chromosomes develop as females, whereas XY sufficient to provide you with the minimum embryos develop as males.
    [Show full text]
  • Most Chromatin Interactions Are Not in Linkage Disequilibrium
    Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Most chromatin interactions are not in linkage disequilibrium Sean Whalen1 and Katherine S. Pollard∗1,2,3 1Gladstone Institutes, San Francisco, CA 94158, USA 2Department of Epidemiology and Biostatistics, Institute for Human Genetics, Quantitative Biology Institute, and Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA 3Chan-Zuckerberg Biohub, San Francisco, CA, USA December 4, 2018 1 Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Chromatin interactions and linkage disequilibrium (LD) are both pairwise measurements between genomic loci that show block patterns along mammalian chromosomes. Their values are generally high for sites that are nearby in the linear genome but abruptly drop across block boundaries. One function of chromatin boundaries is to insulate regulatory domains from one another. Since recombination is depressed within genes and between distal regulatory elements and their promoters, we hypothesized that LD and chromatin contact frequency might be correlated genome-wide with the boundaries of LD blocks and chromatin domains frequently coinciding. To comprehensively address this question, we compared chromatin contacts in 22 cell types to LD across billions of pairs of loci in the human genome. These computationally intensive analyses revealed that there is no concordance between LD and chromatin interactions, even at genomic distances below 25 kilobases where both tend to be high. At genomic distances where LD is approximately zero, chromatin interactions are frequent. While LD is somewhat elevated between distal regulatory elements and their promoters, LD block boundaries are depleted|not enriched|at chromatin boundaries.
    [Show full text]
  • Genetic Linkage and Bipolar Affective Disorder: Progress and Pitfalls M Baron
    Molecular Psychiatry (1997) 2, 200–210 1997 Stockton Press All rights reserved 1359–4184/97 $12.00 PERSPECTIVE Genetic linkage and bipolar affective disorder: progress and pitfalls M Baron Department of Psychiatry, Columbia University College of Physicians and Surgeons, and Department of Medical Genetics, New York State Psychiatric Institute, 722 West 168th Street, New York, NY, USA The history of linkage studies in bipolar affective disorder is a convoluted affair punctuated by upswings and setbacks, hope and skepticism. Advances in genomics and statistical tech- niques, and the availability of well-characterized clinical samples, have bolstered the search for disease genes, leading to a new crop of findings. Indeed, recent reports of putative loci on chromosomes 18, 21, X, 4, 6, 13 and 15 have rekindled a sense of optimism. The new findings are reviewed and scrutinized, with implications for future research. Keywords: molecular genetics; DNA markers; genes; linkage analysis; bipolar disorder Linkage studies of bipolar affective disorder (manic nostic procedures and in statistical techniques appli- depression) have charted an unsteady course marred cable to complex traits.4–15 The availability of dense by fits and starts.1 Findings that appeared at first unas- genomic maps and suitable clinical samples is an sailable could not be replicated or faltered on further added asset. Indeed, the emergence of promising new scrutiny of the evidence. The highs and lows of this findings in the last 2 years may signal the turning of decades-long search were aptly dubbed ‘a manic the tide, though the problems posed for geneticists are depressive history’:2 bouts of optimism alternating far from over.
    [Show full text]
  • A Compilation of Tri-Allelic Snps from 1000 Genomes and Use of the Most Polymorphic Loci for a Large-Scale Human Identification Panel T
    Forensic Science International: Genetics 46 (2020) 102232 Contents lists available at ScienceDirect Forensic Science International: Genetics journal homepage: www.elsevier.com/locate/fsigen A compilation of tri-allelic SNPs from 1000 Genomes and use of the most polymorphic loci for a large-scale human identification panel T C. Phillipsa,*, J. Amigob, A.O. Tillmarc,d, M.A. Pecke, M. de la Puentea, J. Ruiz-Ramíreza, F. Bittnere, Š. Idrizbegoviće, Y. Wangf, T.J. Parsonse, M.V. Lareua a Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain b Fundación Pública Galega de Medicina Xenómica SERGAS, Grupo de Medicina Xenómica USC, IDIS, Santiago de Compostela, Spain c Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden d Department of Clinical and Experimental Medicine, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden e International Commission on Missing Persons, Koninginnegracht 12a, The Hague, Netherlands f Qiagen, 6951 Executive Way, Frederick, MD 21703, US ARTICLE INFO ABSTRACT Keywords: In a directed search of 1000 Genomes Phase III variation data, 271,934 tri-allelic single nucleotide poly- Tri-allelic SNPs morphisms (SNPs) were identified amongst the genotypes of 2,504 individuals from 26 populations. The ma- 1000 Genomes jority of tri-allelic SNPs have three nucleotide substitution-based alleles at the same position, while a much fi Missing persons identi cation smaller proportion, which we did not compile, have a nucleotide insertion/deletion plus substitution alleles. Massively parallel sequencing SNPs with three alleles have higher discrimination power than binary loci but keep the same characteristic of optimum amplification of the fragmented DNA found in highly degraded forensic samples.
    [Show full text]