DOCSLIB.ORG

Identifying Envirogenomic Signatures for Predicting the Clinical Outcomes of Crohn's Disease

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Identifying Envirogenomic Signatures for Predicting the Clinical Outcomes of Crohn's Disease Identifying Envirogenomic Signatures for Predicting the Clinical Outcomes of Crohn's Disease Author Nasir, Bushra Farah Published 2013 Thesis Type Thesis (PhD Doctorate) School School of Medical Sciences DOI https://doi.org/10.25904/1912/1046 Copyright Statement The author owns the copyright in this thesis, unless stated otherwise. Downloaded from http://hdl.handle.net/10072/366228 Griffith Research Online https://research-repository.griffith.edu.au Identifying Envirogenomic Signatures for Predicting the Clinical Outcomes of Crohn’s Disease Bushra Farah Nasir M. Medical Research (Biomedical Science) School of Medical Sciences Griffith Institute of Health and Medical Research Genomics Research Centre Griffith University Submitted in fulfilment for the Degree of Doctor of Philosophy April 2013 2 3 4 ABSTRACT A complex interplay between genetic susceptibility, environmental factors and clinical indicators seem to cause the development of Crohn’s disease (CD). Few disorders in clinical medicine are associated with as much chronic morbidity as CD. Genetic factors are the predetermined cause, whereas non-genetic factors seem to further trigger the development of CD. From epidemiological data, based on concordance statistics in family studies, via linkage analysis to Genome Wide Association Studies (GWAS) and Whole Genome Analysis (WGA), robust evidence have been gathered, implicating distinct genomic loci involved in genetic susceptibility to CD. Most recently, a meta-analysis has been able to implicate 71 distinct genomic loci that seem to be associated with CD development. A study published in the American Journal of Human Genetics has also recently identified more than 200 genes associated with CD, which is more than what have been found for any other disease so far. Monozygotic twins show approximately 50-60% disease concordance, with much lower rates in dizygotic twins (~10%), highlighting the role of both environmental and genetic components in the development of CD. In earlier decades, CD patients suffered a lack of effective treatment preferences, and patients with moderate to severe CD were often consigned to prolonged systemic corticosteroid therapy and surgery as their only options. From the late 1990s onward, there has been a significant improvement in CD treatment therapy, specifically the widespread adoption of maintenance of immunomodulaters and the advent of biologic agents. The understanding of the natural history of those patients at-risk of severe and complicated CD patient subgroups, particularly an early identification of 5 patients with the potential for severe disease and its associated complications, would ultimately determine an optimal clinical approach that incorporates appropriate risk- benefit assessment for disease modifying therapy. The advent of chips for high-throughput genotyping of single nucleotide polymorphisms (SNPs) in 2004 provided researchers with a powerful new tool for unlocking the genetic basis of complex human diseases. GWAS using SNP chips have since identified risk loci for many complex disease traits, though the amount of disease heritability explained by any single SNP has been typically very minor (odds ratios < 1.5). Whilst the SNP chip technologies supporting GWAS are now scientifically well established (more than 1 million SNPs can currently be typed rapidly in a single assay), the bioinformatics methods for GWAS are still underdeveloped and require more empirical experimentation with model traits before widespread application is possible. In particular, for accurately identifying disease risk factors, there is an urgent need to move beyond the single SNP analysis, and into the statistical assessment of multiple SNPs acting independently and/or interactively with other environmental and clinical risk factors. Association studies are a major tool for identifying genes conferring susceptibility to complex disorders. These traits and diseases are being termed as “complex” because both genetic and environmental factors contribute to the susceptibility of risk development. Extensive experiments in genetic studies for many complex disorders have confirmed that many different genetic variants control disease risk, with each variant having only a subtle effect. Therefore genomic data needs to be integrated with patient environmental and clinical information so that it can be interpreted by trained clinicians who can provide personalised predictive profiles for patients, thus allowing for a more specifically tailored treatment regimen. Furthermore, this will 6 allow clinical researchers to translate novel disease biomarkers and drug responses into improved treatments, which in turn can be tailored to each patient’s individual genome. It is anticipated that such developments would be readily applicable to CD along with other multifaceted diseases. This research project adapts the basic GWAS design towards identifying envirogenomic signatures of disease, with a major focus on CD. By combining clinical, environmental and genetic factors and analysing them collectively, “envirogenomic signatures” can be created. Through the use of a multi-factor analysis procedure, it is expected that a greater proportion of the disease variance would be explained and therefore the coupled factor set would be of greater predictive value. This study would be a step forward in identifying envirogenomic signatures that may predict clinical outcomes in CD patients with an improved accuracy. CD associated SNPs play an important part in disease progression and severity, and information from clinical outcomes can be used to identify disease risk prospects for patients, when used with other clinical patient history data. A replicated multi- factorial model was developed and analysed in this section. This model was able to illustrate an 82% risk of requiring surgery for patients diagnosed with both the NOD2 gene and smoking variables. When clinical and/or environmental predictors and genetic predictors are combined to create envirogenomic signatures, high association to clinical severity of disease outcomes is demonstrated (Chapter Four) and this can potentially assist in creating individual risk profiles, useful for subsequent accurate treatment and early diagnosis of disease severity. 7 This project (Chapter Five) also involved the development of a novel Genomic Signature Analysis (GSA) bioinformatics method which is a comprehensive, step- wise approach for analysing genomic data in order to produce a precise genomic signature for predicting the level of disease risk. Originally outlaid in 2009 by Lea et al, further analyses has been able to provide progressive developments of the GSA method. With the inclusion of some modifications, the GSA process has been further improved. A 7-SNP genetic signature was identified using the GSA method by using the Wellcome Trust Case Control Consortium (WTCCC) CD dataset. The completed model was able to achieve an 86% risk of CD for those patients with the set of 7 SNPs identified from the GSA. The GSA method outlined in this study demonstrated a significantly important process to help classify high risk patients of CD and empower clinicians with the ability to diagnose such patients accurately and provide personalised treatment therapies accordingly. The field of medicine today is rapidly accelerating from inefficient and experimental practices to data-driven and practical clinical applications. Very soon, treatments, diagnosis, prognosis and disease prevention would be custom-made to each individual’s specific genotypic and phenotypic dataset. In the near future we anticipate that, through the incorporation of genomic research innovations, personalized medicine advances would no doubt transform the practice of medicine, thereby altering the global healthcare industry and with time, would pave the way for a lengthier and healthier quality of life. 8 ACKNOWLEDGEMENTS Throughout my academic career I have been blessed with countless opportunities that have come my way, making my career path more achievable. I am extremely grateful to all those who have walked along with me on every step of this journey, those who I am blessed enough to be able to take for granted. The past three years of my Doctoral research work have been extremely fulfilling and full of cooperation from many people in my life, some of whom I would like to appreciate here. It goes without saying, that I am eternally grateful to God for providing me this opportunity in life and bestowing me with the capabilities to accomplish this task. First and foremost, my supervisors Dr Rodney Lea and Dr Lyn Griffiths cannot be accredited enough, for all their support and guidance that they have provided so unassumingly. Making special considerations for me to attend meetings with my children, at my home and through teleconferences, I greatly appreciate the kindness and respect that they have always endowed upon me. Without these two people, I am genuinely positive that I would not have been able to complete such an immense undertaking as that is required for a Doctoral degree. I am sincerely thankful to both of these mentors for giving me the guidance and space to learn, so that I could really call this work my own. The past few years of my academic learning would also not have been possible without the abundant love, support and encouragement of my friends and family. I am extremely thankful to have been blessed with parents who have always encouraged me to excel and push my limits and always provided me with immense
Load more

Recommended publications
  • Universidade Federal Do Rio Grande Do Sul Faculdade De Agronomia Programa De Pós-Graduaçao Em Zootecnia
    UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL FACULDADE DE AGRONOMIA PROGRAMA DE PÓS-GRADUAÇAO EM ZOOTECNIA GENÉTICA DE PAISAGEM DE SUÍNOS NO BRASIL: IDENTIFICAÇÃO DE ASSINATURAS DE SELEÇÃO PARA ESTUDOS DE CONSERVAÇÃO E CARACTERIZAÇÃO DE REBANHOS ROBSON JOSÉ CESCONETO Médico Veterinário/UFPeL Mestre em Ciências/UFPeL Tese apresentada ao Programa de Pós-Graduação em Zootecnia da UFRGS como requisito para obtenção do titulo de Doutor em Ciências, área de concentração Produção Animal. Porto Alegre (RS), Brasil Julho de 2016 CIP - Catalogação na Publicação Cesconeto, Robson José GENÉTICA DE PAISAGEM DE SUÍNOS NO BRASIL: Identificação de assinaturas de seleção para estudos de conservação e caracterização de rebanhos / Robson José Cesconeto. -- 2016. 131 f. Orientador: José Braccini Neto. Coorientadores: C. Mc Manus, S. Joost. Tese (Doutorado) -- Universidade Federal do Rio Grande do Sul, Faculdade de Agronomia, Programa de Pós-Graduação em Zootecnia, Porto Alegre, BR-RS, 2016. 1. Suínos brasileiros. 2. Genética de Populações. 3. Estrutura Genética de Populações Naturais. 4. Recursos Genéticos. 5. Sus scrofa. I. Braccini Neto, José, orient. II. Mc Manus, C., coorient. III. Joost, S., coorient. IV. Título. Elaborada pelo Sistema de Geração Automática de Ficha Catalográfica da UFRGS com os dados fornecidos pelo(a) autor(a). 3 AGRADECIMENTOS A Deus, pelo dom da vida, pela inspiração e, por não me permitir desanimar diante das dificuldades encontradas durante a caminhada; Aos meus pais pelo que sou hoje; Àquela que me apoiou e “suportou” desde a minha
    [Show full text]
  • Allele Frequency Difference AFD–An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation
    G C A T T A C G G C A T genes Opinion Allele Frequency Difference AFD–An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation Daniel Berner Department of Environmental Sciences, Zoology, University of Basel, Vesalgasse 1, CH-4051 Basel, Switzerland; [email protected]; Tel.: +41-(0)-61-207-03-28 Received: 21 February 2019; Accepted: 12 April 2019; Published: 18 April 2019 Abstract: Measuring the magnitude of differentiation between populations based on genetic markers is commonplace in ecology, evolution, and conservation biology. The predominant differentiation metric used for this purpose is FST. Based on a qualitative survey, numerical analyses, simulations, and empirical data, I here argue that FST does not express the relationship to allele frequency differentiation between populations generally considered interpretable and desirable by researchers. In particular, FST (1) has low sensitivity when population differentiation is weak, (2) is contingent on the minor allele frequency across the populations, (3) can be strongly affected by asymmetry in sample sizes, and (4) can differ greatly among the available estimators. Together, these features can complicate pattern recognition and interpretation in population genetic and genomic analysis, as illustrated by empirical examples, and overall compromise the comparability of population differentiation among markers and study systems. I argue that a simple differentiation metric displaying intuitive properties, the absolute allele frequency difference AFD, provides a valuable alternative to FST. I provide a general definition of AFD applicable to both bi- and multi-allelic markers and conclude by making recommendations on the sample sizes needed to achieve robust differentiation estimates using AFD.
    [Show full text]
  • S41467-019-13480-Z OPEN Insights Into Malaria Susceptibility Using Genome- Wide Data on 17,000 Individuals from Africa, Asia and Oceania
    ARTICLE https://doi.org/10.1038/s41467-019-13480-z OPEN Insights into malaria susceptibility using genome- wide data on 17,000 individuals from Africa, Asia and Oceania Malaria Genomic Epidemiology Network The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and 1234567890():,; population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replic- able associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus. Previously reported HLA associations do not replicate in these sam- ples. This large dataset will provide a foundation for further research on the genetic deter- minants of malaria resistance in diverse populations. A full list of authors and their affiliations appears at the end of the paper. NATURE COMMUNICATIONS | (2019) 10:5732 | https://doi.org/10.1038/s41467-019-13480-z | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-13480-z enome-wide association studies (GWASs) have been very passed our quality control process (Methods). Subsets of these successful in identifying common genetic variants data from The Gambia, Malawi and Kenya7, from Tanzania8 and G 9 underlying chronic non-communicable diseases, but have from selected control samples have been reported previously proved to be more difficult for acute infectious diseases that (Supplementary Table 2).
    [Show full text]
  • Basic Principles and Laboratory Analysis of Genetic Variation Jesus Gonzalez-Bosquet and Stephen J
    UNIT 2. BIOMARKERS: PRACTICAL ASPECTS CHAPTER 6. Basic principles and laboratory analysis of genetic variation Jesus Gonzalez-Bosquet and Stephen J. Chanock UNIT 2 CHAPTER 6 CHAPTER Summary With the draft of the human genome of their functional significance. agnostically using dense data sets and advances in technology, the Understanding the true effect of with billions of data points. These approach toward mapping complex genetic variability on the risk of developments have transformed diseases and traits has changed. complex diseases is paramount. the field, moving it away from the Human genetics has evolved into The importance of designing pursuit of hypothesis-driven, limited the study of the genome as a high-quality studies to assess candidate studies to large-scale complex structure harbouring clues environmental contributions, as well scans across the genome. Together for multifaceted disease risk with as the interactions between genes these developments have spurred a the majority still unknown. The and exposures, cannot be stressed dramatic increase in the discovery discovery of new candidate regions enough. This chapter will address of genetic variants associated with by genome-wide association studies the basic issues of genetic variation, or linked to human diseases and (GWAS) has changed strategies for including population genetics, as traits, many through genome-wide the study of genetic predisposition. well as analytical platforms and association studies (GWAS) (1). More genome-wide, “agnostic” tools needed to investigate the Already over 7400 novel regions of approaches, with increasing contribution of genetics to human the genome have been associated numbers of participants from high- diseases and traits. with more than 75 human diseases quality epidemiological studies are or traits in large-scale GWAS (2).
    [Show full text]
  • Allele Frequency Determination of Publicly Available Csnps in The
    November/December 2002 ⅐ Vol. 4 ⅐ No. 6, Supplement Allele frequency determination of publicly available cSNPs in the Korean population Seong-Gene Lee, PhD1, Yongsook Yoon2, Sunghee Hong2, Jieun Yoo2, Insil Yang2, and Kyuyoung Song, PhD1,2 Purpose: As a first step toward the construction of a single-nucleotide polymorphism (SNP) database of the Korean population, the authors determined the allele frequencies of 406 cSNPs selected from the public database. Methods: A pooled DNA sequencing approach was used to determine the allele frequencies of 406 cSNPs selected from 120 genes in 24 individuals. Results: Of 406 cSNPs, 53% were monomorphic in the Korean samples. Among tested SNPs, 292 SNPs (72%) were uncommon (minor allele Ͻ20%) and 114 SNPs (28%) were common (minor allele Ն20%) in our population. Conclusion: An extensive SNP characterization would be necessary, and the ethnic and population-based differences should be considered in the selection of SNPs for the study of complex diseases with association mapping methods. Genet Med 2002:4(6, Supplement):49S–51S. Key Words: publicly available cSNPs, allele frequency, ethnic variation, pooled DNA sequencing approach, Korean population, comparison of allele frequencies The central aim of genetics is to correlate specific molecular population. For an association mapping study, SNP allele fre- variation with particular phenotype changes. Since the human quencies in the population would be critical. genome draft sequence was announced in June 2000, it has We decided to characterize publicly available cSNPs in the Ko- become possible to understand the spectrum of genetic varia- rean population because (1) many SNPs are publicly available tion in the human gene pool and its relation to diseases, indi- already, (2) those SNPs were discovered using rather limited sam- vidual responses to environmental factors, and biological pro- ples, (3) some SNPs may not be common in a given population, cesses such as development and aging.
    [Show full text]
  • A Hapmap Harvest of Insights Into the Genetics of Common Disease Teri A
    Science in medicine A HapMap harvest of insights into the genetics of common disease Teri A. Manolio, Lisa D. Brooks, and Francis S. Collins National Human Genome Research Institute, Bethesda, Maryland, USA. The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the ini- tial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science. The International HapMap Project was designed to create a public, cally susceptible individual to produce disease (7, 8). Unlike Mende- genome-wide database of patterns of common human sequence lian disorders such as sickle cell disease and cystic fibrosis, in which variation to guide genetic studies of human health and disease alterations in a single gene explain all or nearly all occurrences of (1–3). With the publication of the draft human genome sequence disease, genes underlying common diseases are likely to be multiple, in 2001 (4) and the essentially finished version in 2003 (5), the each with a relatively small effect, but act in concert or with environ- HapMap emerged as a logical next step in characterizing human mental influences to lead to clinical disease (Figure 1) (9).
    [Show full text]
  • Novel Alzheimer's Disease Risk Variants Identified Based on Whole
    Park et al. Translational Psychiatry (2021) 11:296 https://doi.org/10.1038/s41398-021-01412-9 Translational Psychiatry ARTICLE Open Access Novel Alzheimer’s disease risk variants identified based on whole-genome sequencing of APOE ε4 carriers Jong-Ho Park1,InhoPark2,3, Emilia Moonkyung Youm4, Sejoon Lee5,June-HeePark6, Jongan Lee7, Dong Young Lee8, Min Soo Byun9,JunHoLee 10,DahyunYi11, Sun Ju Chung12,KyeWonPark12, Nari Choi12, Seong Yoon Kim13, Woon Yoon13, Hoyoung An 14, Ki woong Kim9,15,16, Seong Hye Choi17, Jee Hyang Jeong18,Eun-JooKim19, Hyojin Kang20,JunehawkLee 20, Younghoon Kim20, Eunjung Alice Lee21,22,SangWonSeo23,DukL.Na23 and Jong-Won Kim 1,4,24 Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative disease associated with a complex genetic etiology. Besides the apolipoprotein E ε4(APOE ε4) allele, a few dozen other genetic loci associated with AD have been identified through genome-wide association studies (GWAS) conducted mainly in individuals of European ancestry. Recently, several GWAS performed in other ethnic groups have shown the importance of replicating studies that identify previously established risk loci and searching for novel risk loci. APOE-stratified GWAS have yielded novel AD risk loci that might be masked by, or be dependent on, APOE alleles. We performed whole-genome sequencing (WGS) on DNA from blood samples of 331 AD patients and 169 elderly controls of Korean ethnicity who were APOE ε4 carriers. Based on WGS data, we designed a customized AD chip (cAD chip) for further analysis on an independent set 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; of 543 AD patients and 894 elderly controls of the same ethnicity, regardless of their APOE ε4 allele status.
    [Show full text]
  • The International Hapmap Project
    feature The International HapMap Project The International HapMap Consortium* *Lists of participants and affiliations appear at the end of the paper ........................................................................................................................................................................................................................... The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention. ommon diseases such as cardiovascular disease, cancer, feasible to study variants in candidate genes, chromosome regions obesity, diabetes, psychiatric illnesses and inflammatory or across the whole genome. Prior knowledge of putative functional diseases are caused by combinations of multiple genetic variants is not required. Instead, the approach uses information and environmental factors1. Discovering these genetic from a relatively small set of variants that capture most of factors will provide fundamental new insights into the the common patterns of variation in the genome, so that any Cpathogenesis, diagnosis and treatment of human disease. Searches region or gene can be tested for association with a particular disease, for causative variants in chromosome regions identified by linkage with a high likelihood that such an association will be detectable if it analysis have been highly successful for many rare single-gene exists.
    [Show full text]
  • Dna Sequencing – Methods and Applications
    DNA SEQUENCING – METHODS AND APPLICATIONS Edited by Anjana Munshi DNA Sequencing – Methods and Applications Edited by Anjana Munshi Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Bojan Rafaj Technical Editor Teodora Smiljanic Cover Designer InTech Design Team First published April, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from [email protected] DNA Sequencing – Methods and Applications, Edited by Anjana Munshi p.
    [Show full text]
  • On Rare Variants in Principal Component Analysis of Population Stratifcation
    On Rare Variants in Principal Component Analysis of Population Stratication Shengqing Ma Xidian University Gang Shi ( [email protected] ) Xidian University https://orcid.org/0000-0001-6049-0492 Research article Keywords: rare variants; population stratication; principal component analysis; single nucleotide polymorphism Posted Date: April 10th, 2019 DOI: https://doi.org/10.21203/rs.2.9120/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published at BMC Genetics on March 17th, 2020. See the published version at https://doi.org/10.1186/s12863-020-0833-x. Page 1/16 Abstract Background Population stratication is a known confounder of genome-wide association studies, as it can lead to false positive or false negative results. Principal component analysis (PCA) method is widely applied in the analysis of population structure with common variants. It is still controversial whether this method is effective when using rare variants to distinguish population stratication. Results In this work, we derive a mathematical expectation of the genetic relationship matrix. Variance and covariance elements of the expected matrix depend explicitly on allele frequencies of the genetic markers used in the PCA analysis. We show analytically that inter-population variance is contained in K principal components (PCs) and mostly in the largest K-1 PCs, where K is the number of populations in the samples. When allele frequencies become small, the ratio of the inter-population variance in the K PCs to the intra-population variance abates, the portion of variance explained by the K PCs decreases, and the distance among populations diminishes.
    [Show full text]
  • Evaluating the Quality of the 1000 Genomes Project Data
    Belsare et al. BMC Genomics (2019) 20:620 https://doi.org/10.1186/s12864-019-5957-x RESEARCH ARTICLE Open Access Evaluating the quality of the 1000 genomes project data Saurabh Belsare1* , Michal Levy-Sakin2, Yulia Mostovoy2, Steffen Durinck3, Subhra Chaudhuri3, Ming Xiao4, Andrew S. Peterson3, Pui-Yan Kwok1,2,5, Somasekar Seshagiri3 and Jeffrey D. Wall1,6* Abstract Background: Data from the 1000 Genomes project is quite often used as a reference for human genomic analysis. However, its accuracy needs to be assessed to understand the quality of predictions made using this reference. We present here an assessment of the genotyping, phasing, and imputation accuracy data in the 1000 Genomes project. We compare the phased haplotype calls from the 1000 Genomes project to experimentally phased haplotypes for 28 of the same individuals sequenced using the 10X Genomics platform. Results: We observe that phasing and imputation for rare variants are unreliable, which likely reflects the limited sample size of the 1000 Genomes project data. Further, it appears that using a population specific reference panel does not improve the accuracy of imputation over using the entire 1000 Genomes data set as a reference panel. We also note that the error rates and trends depend on the choice of definition of error, and hence any error reporting needs to take these definitions into account. Conclusions: The quality of the 1000 Genomes data needs to be considered while using this database for further studies. This work presents an analysis that can be used for these assessments. Keywords: 1000 genomes, Phasing, Imputation Background the variant calls.
    [Show full text]
  • A Map of Human Genome Variation from Population-Scale Sequencing
    ARTICLE doi:10.1038/nature09534 A map of human genome variation from population-scale sequencing The 1000 Genomes Project Consortium* The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother–father–child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 1028 per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites.
    [Show full text]