701
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Magi A, Tattini L, Palombo F, Benelli M, Gialluisi A, Giusti B, Abbate R, Seri M, Gensini GF, Romeo G, Pippucci T. H 3 M 2 : detection of runs of homozygosity from whole-exome sequencing data. Bioinformatics 2014; 30:2852-9. [DOI: 10.1093/bioinformatics/btu401] [Citation(s) in RCA: 71] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
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702
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McWhirter RE, Thomson RJ, Marthick JR, Rumbold AR, Brown MA, Taylor-Thomson D, Maypilama EL, Condon JR, Dickinson JL. Runs of homozygosity and a cluster of vulvar cancer in young Australian Aboriginal women. Gynecol Oncol 2014; 133:421-6. [PMID: 24690477 DOI: 10.1016/j.ygyno.2014.03.566] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2014] [Revised: 03/20/2014] [Accepted: 03/23/2014] [Indexed: 11/20/2022]
Abstract
OBJECTIVE A cluster of vulvar cancer exists in young Aboriginal women living in remote communities in Arnhem Land, Australia. A genetic case-control study was undertaken involving 30 cases of invasive vulvar cancer and its precursor lesion, high-grade vulvar intraepithelial neoplasia (VIN), and 61 controls, matched for age and community of residence. It was hypothesized that this small, isolated population may exhibit increased autozygosity, implicating recessive effects as a possible mechanism for increased susceptibility to vulvar cancer. METHODS Genotyping data from saliva samples were used to identify runs of homozygosity (ROH) in order to calculate estimates of genome-wide homozygosity. RESULTS No evidence of an effect of genome-wide homozygosity on vulvar cancer and VIN in East Arnhem women was found, nor was any individual ROH found to be significantly associated with case status. This study found further evidence supporting an association between previous diagnosis of CIN and diagnosis of vulvar cancer or VIN, but found no association with any other medical history variable. CONCLUSIONS These findings do not eliminate the possibility of genetic risk factors being involved in this cancer cluster, but rather suggest that alternative analytical strategies and genetic models should be explored.
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Affiliation(s)
- Rebekah E McWhirter
- Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia; Menzies Research Institute Tasmania, University of Tasmania, Hobart, TAS 7000, Australia.
| | - Russell J Thomson
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, TAS 7000, Australia
| | - James R Marthick
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, TAS 7000, Australia
| | - Alice R Rumbold
- Obstetrics and Gynaecology, University of Adelaide, Adelaide, SA 5005, Australia
| | - Matthew A Brown
- University of Queensland, Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital, Woolloongabba, QLD 4102, Australia
| | - Debbie Taylor-Thomson
- Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - Elaine L Maypilama
- Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - John R Condon
- Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia
| | - Joanne L Dickinson
- Menzies School of Health Research, Charles Darwin University, Casuarina, NT 0811, Australia; Menzies Research Institute Tasmania, University of Tasmania, Hobart, TAS 7000, Australia
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703
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Lee HJ, Kim J, Lee T, Son JK, Yoon HB, Baek KS, Jeong JY, Cho YM, Lee KT, Yang BC, Lim HJ, Cho K, Kim TH, Kwon EG, Nam J, Kwak W, Cho S, Kim H. Deciphering the genetic blueprint behind Holstein milk proteins and production. Genome Biol Evol 2014; 6:1366-74. [PMID: 24920005 PMCID: PMC4079194 DOI: 10.1093/gbe/evu102] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Holstein is known to provide higher milk yields than most other cattle breeds, and the dominant position of Holstein today is the result of various selection pressures. Holstein cattle have undergone intensive selection for milk production in recent decades, which has left genome-wide footprints of domestication. To further characterize the bovine genome, we performed whole-genome resequencing analysis of 10 Holstein and 11 Hanwoo cattle to identify regions containing genes as outliers in Holstein, including CSN1S1, CSN2, CSN3, and KIT whose products are likely involved in the yield and proteins of milk and their distinctive black-and-white markings. In addition, genes indicative of positive selection were associated with cardiovascular disease, which is related to simultaneous propagation of genetic defects, also known as inbreeding depression in Holstein.
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Affiliation(s)
- Hyun-Jeong Lee
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Suwon, Republic of KoreaDepartment of Agricultural Biotechnology and Research Institute of Population Genomics, Seoul National University, Seoul, Republic of KoreaInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea
| | - Jaemin Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, KoreaCHO&KIM Genomics, SNU Research Park, Seoul National University Mt.4-2, Seoul, Republic of Korea
| | - Taeheon Lee
- Department of Agricultural Biotechnology and Research Institute of Population Genomics, Seoul National University, Seoul, Republic of Korea
| | - Jun Kyu Son
- Division of Dairy Science, National Institute of Animal Science, Suwon, Republic of Korea
| | - Ho-Baek Yoon
- Division of Dairy Science, National Institute of Animal Science, Suwon, Republic of Korea
| | - Kwang-Soo Baek
- Division of Dairy Science, National Institute of Animal Science, Suwon, Republic of Korea
| | - Jin Young Jeong
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Suwon, Republic of Korea
| | - Yong-Min Cho
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Suwon, Republic of Korea
| | - Kyung-Tai Lee
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Suwon, Republic of Korea
| | - Byoung-Chul Yang
- Division of Animal Biotechnology, National Institute of Animal Science, Suwon, Republic of Korea
| | - Hyun-Joo Lim
- Division of Dairy Science, National Institute of Animal Science, Suwon, Republic of Korea
| | - Kwanghyeon Cho
- Division of Animal Breeding & Genetics, National Institute of Animal Science, Cheonan, Republic of Korea
| | - Tae-Hun Kim
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Suwon, Republic of Korea
| | - Eung Gi Kwon
- Division of Dairy Science, National Institute of Animal Science, Suwon, Republic of Korea
| | - Jungrye Nam
- Department of Agricultural Biotechnology and Research Institute of Population Genomics, Seoul National University, Seoul, Republic of Korea
| | - Woori Kwak
- CHO&KIM Genomics, SNU Research Park, Seoul National University Mt.4-2, Seoul, Republic of Korea
| | - Seoae Cho
- CHO&KIM Genomics, SNU Research Park, Seoul National University Mt.4-2, Seoul, Republic of Korea
| | - Heebal Kim
- Department of Agricultural Biotechnology and Research Institute of Population Genomics, Seoul National University, Seoul, Republic of KoreaInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea
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704
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Huson HJ, Kim ES, Godfrey RW, Olson TA, McClure MC, Chase CC, Rizzi R, O'Brien AMP, Van Tassell CP, Garcia JF, Sonstegard TS. Genome-wide association study and ancestral origins of the slick-hair coat in tropically adapted cattle. Front Genet 2014; 5:101. [PMID: 24808908 PMCID: PMC4010767 DOI: 10.3389/fgene.2014.00101] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Accepted: 04/08/2014] [Indexed: 11/13/2022] Open
Abstract
The slick hair coat (SLICK) is a dominantly inherited trait typically associated with tropically adapted cattle that are from Criollo descent through Spanish colonization of cattle into the New World. The trait is of interest relative to climate change, due to its association with improved thermo-tolerance and subsequent increased productivity. Previous studies localized the SLICK locus to a 4 cM region on chromosome (BTA) 20 and identified signatures of selection in this region derived from Senepol cattle. The current study compares three slick-haired Criollo-derived breeds including Senepol, Carora, and Romosinuano and three additional slick-haired cross-bred lineages to non-slick ancestral breeds. Genome-wide association (GWA), haplotype analysis, signatures of selection, runs of homozygosity (ROH), and identity by state (IBS) calculations were used to identify a 0.8 Mb (37.7-38.5 Mb) consensus region for the SLICK locus on BTA20 in which contains SKP2 and SPEF2 as possible candidate genes. Three specific haplotype patterns are identified in slick individuals, all with zero frequency in non-slick individuals. Admixture analysis identified common genetic patterns between the three slick breeds at the SLICK locus. Principal component analysis (PCA) and admixture results show Senepol and Romosinuano sharing a higher degree of genetic similarity to one another with a much lesser degree of similarity to Carora. Variation in GWA, haplotype analysis, and IBS calculations with accompanying population structure information supports potentially two mutations, one common to Senepol and Romosinuano and another in Carora, effecting genes contained within our refined location for the SLICK locus.
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Affiliation(s)
- Heather J Huson
- Department of Animal Science, Cornell University Ithaca, NY, USA ; Bovine Functional Genomics Laboratory, United States Department of Agriculture, Agricultural Research Services Beltsville, MD, USA
| | - Eui-Soo Kim
- Bovine Functional Genomics Laboratory, United States Department of Agriculture, Agricultural Research Services Beltsville, MD, USA ; Department of Animal Science, Iowa State University Ames, IA, USA
| | - Robert W Godfrey
- Agricultural Experiment Station, University of the Virgin Islands St. Croix, Virgin Islands
| | - Timothy A Olson
- Department of Animal Science, University of Florida Gainsville, FL, USA
| | - Matthew C McClure
- Bovine Functional Genomics Laboratory, United States Department of Agriculture, Agricultural Research Services Beltsville, MD, USA ; Irish Cattle Breeding Federation Cork, Ireland
| | - Chad C Chase
- Meat Animal Research Center, United States Department of Agriculture, Agricultural Research Services Clay Center, NE, USA
| | - Rita Rizzi
- Department of Veterinary Medicine, Milan University Milan, Italy
| | - Ana M P O'Brien
- Division of Livestock Sciences, BOKU University of Natural Resources and Life Sciences Vienna, Austria
| | - Curt P Van Tassell
- Bovine Functional Genomics Laboratory, United States Department of Agriculture, Agricultural Research Services Beltsville, MD, USA
| | - José F Garcia
- Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista Brazil
| | - Tad S Sonstegard
- Bovine Functional Genomics Laboratory, United States Department of Agriculture, Agricultural Research Services Beltsville, MD, USA
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705
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O'Connell J, Gurdasani D, Delaneau O, Pirastu N, Ulivi S, Cocca M, Traglia M, Huang J, Huffman JE, Rudan I, McQuillan R, Fraser RM, Campbell H, Polasek O, Asiki G, Ekoru K, Hayward C, Wright AF, Vitart V, Navarro P, Zagury JF, Wilson JF, Toniolo D, Gasparini P, Soranzo N, Sandhu MS, Marchini J. A general approach for haplotype phasing across the full spectrum of relatedness. PLoS Genet 2014; 10:e1004234. [PMID: 24743097 PMCID: PMC3990520 DOI: 10.1371/journal.pgen.1004234] [Citation(s) in RCA: 420] [Impact Index Per Article: 38.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Accepted: 01/27/2014] [Indexed: 01/20/2023] Open
Abstract
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.
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Affiliation(s)
- Jared O'Connell
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom; Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Deepti Gurdasani
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom; Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Olivier Delaneau
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Nicola Pirastu
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, University of Trieste, Trieste, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, Italy
| | - Massimiliano Cocca
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Jie Huang
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Jennifer E Huffman
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ruth McQuillan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ross M Fraser
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Gershim Asiki
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI), Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Kenneth Ekoru
- Laboratoire Génomique, Bioinformatique, et Applications (EA4627), Conservatoire National des Arts et Métiers, Paris, France
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Alan F Wright
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Jean-Francois Zagury
- Laboratoire Génomique, Bioinformatique, et Applications (EA4627), Conservatoire National des Arts et Métiers, Paris, France
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Paolo Gasparini
- Institute for Maternal and Child Health - IRCCS Burlo Garofolo, University of Trieste, Trieste, Italy
| | - Nicole Soranzo
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Manjinder S Sandhu
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom; Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jonathan Marchini
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom; Department of Statistics, University of Oxford, Oxford, United Kingdom
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706
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Sardinians genetic background explained by runs of homozygosity and genomic regions under positive selection. PLoS One 2014; 9:e91237. [PMID: 24651212 PMCID: PMC3961211 DOI: 10.1371/journal.pone.0091237] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2013] [Accepted: 02/10/2014] [Indexed: 11/19/2022] Open
Abstract
The peculiar position of Sardinia in the Mediterranean sea has rendered its population an interesting biogeographical isolate. The aim of this study was to investigate the genetic population structure, as well as to estimate Runs of Homozygosity and regions under positive selection, using about 1.2 million single nucleotide polymorphisms genotyped in 1077 Sardinian individuals. Using four different methods--fixation index, inflation factor, principal component analysis and ancestry estimation--we were able to highlight, as expected for a genetic isolate, the high internal homogeneity of the island. Sardinians showed a higher percentage of genome covered by RoHs>0.5 Mb (F(RoH%0.5)) when compared to peninsular Italians, with the only exception of the area surrounding Alghero. We furthermore identified 9 genomic regions showing signs of positive selection and, we re-captured many previously inferred signals. Other regions harbor novel candidate genes for positive selection, like TMEM252, or regions containing long non coding RNA. With the present study we confirmed the high genetic homogeneity of Sardinia that may be explained by the shared ancestry combined with the action of evolutionary forces.
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707
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Saarela J, Finnäs F. Infant mortality and ethnicity in an indigenous European population: novel evidence from the Finnish population register. Sci Rep 2014; 4:4214. [PMID: 24572973 PMCID: PMC5379437 DOI: 10.1038/srep04214] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2013] [Accepted: 02/06/2014] [Indexed: 11/09/2022] Open
Abstract
We provide the first analyses of infant mortality rates by indigenous ethnic group in Finland, a country that has one of the lowest relative numbers of infant deaths in the world. Using files from the Finnish population register, we identified both of the parents of children born in the period from 1975-2003 according to ethnic affiliation, socioeconomic profile, and demographic position. The infant mortality rate in homogamous Finnish unions is similar to that in homogamous Swedish unions, which reflects a lack of social disparities between the two groups. Surprisingly, infants from ethnically mixed unions have markedly lower mortality rates, with an adjusted rate ratio of 0.81 relative to homogamous Swedish unions (95% CI: 0.67-0.98). Although not empirically verified, we argue that the lower infant mortality rate in ethnically mixed unions may be due to lower levels of inbreeding, and hence related to historically low intermarriage rates between the two ethnic groups, remote consanguinities, and restricted inter-community gene flow.
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Affiliation(s)
- Jan Saarela
- University of Helsinki and Åbo Akademi University, Finland, Jan Saarela, Åbo Akademi University, PO Box 311, FIN-65101 Vasa, Finland
| | - Fjalar Finnäs
- Fjalar Finnäs, Åbo Akademi University, PO Box 311, FIN-65101 Vasa, Finland
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708
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The application of genome-wide SNP genotyping methods in studies on livestock genomes. J Appl Genet 2014; 55:197-208. [PMID: 24566962 DOI: 10.1007/s13353-014-0202-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 01/14/2014] [Accepted: 02/04/2014] [Indexed: 01/07/2023]
Abstract
Animal genomics is currently undergoing dynamic development, which is driven by the flourishing of high-throughput genome analysis methods. Recently, a large number of animals has been genotyped with the use of whole-genome genotyping assays in the course of genomic selection programmes. The results of such genotyping can also be used for studies on different aspects of livestock genome functioning and diversity. In this article, we review the recent literature concentrating on various aspects of animal genomics, including studies on linkage disequilibrium, runs of homozygosity, selection signatures, copy number variation and genetic differentiation of animal populations. Our work is aimed at providing insight into certain achievements of animal genomics and to arouse interest in basic research on the complexity and structure of the genomes of livestock.
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709
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Nikolac Perkovic M, Pucic Bakovic M, Kristic J, Novokmet M, Huffman JE, Vitart V, Hayward C, Rudan I, Wilson JF, Campbell H, Polasek O, Lauc G, Pivac N. The association between galactosylation of immunoglobulin G and body mass index. Prog Neuropsychopharmacol Biol Psychiatry 2014; 48:20-5. [PMID: 24012618 DOI: 10.1016/j.pnpbp.2013.08.014] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2013] [Revised: 08/28/2013] [Accepted: 08/28/2013] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Obesity is becoming a fast-growing health problem worldwide. Glycosylation of proteins and their variations significantly affect protein structure and function, thus altering numerous physiological and pathophysiological cellular processes. Since plasma glycans were significantly associated with body mass index (BMI) in both Croatian and Chinese populations, the study evaluated the association between immunoglobulin G (IgG) glycome, which is closer to biological function, and BMI. METHOD The study included individuals from two Croatian Adriatic islands, Vis and Korčula, and individuals from Northern Scottish Orkney Islands. A hydrophilic interaction chromatography on Waters BEH Glycan chromatography column was used to analyze N-glycans attached to IgG in plasma samples from a total of 3515 individuals. RESULTS A small but significant positive correlation between BMI and the level of neutral glycans without galactoses was detected. After taking into account the influence of age and gender, correlation coefficients indicated that BMI was responsible for up to 2.0% of variation in the level of neutral glycans without galactoses. Furthermore, after adjusting the effects of age and gender, the level of neutral glycans with two terminal galactoses was negatively associated with BMI in analyzed sample groups, suggesting that BMI could be responsible for up to 3.2% of variation in this glycan feature. CONCLUSION Our study is the first large-scale study to indicate the association of BMI and changes in IgG galactosylation. The observed loss of galactose which is associated with increased BMI might be related to chronic inflammation that accompanies the development of obesity.
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710
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The Role of Genomics in Conservation and Reproductive Sciences. REPRODUCTIVE SCIENCES IN ANIMAL CONSERVATION 2014; 753:71-96. [DOI: 10.1007/978-1-4939-0820-2_5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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711
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Alsalem AB, Halees AS, Anazi S, Alshamekh S, Alkuraya FS. Autozygome sequencing expands the horizon of human knockout research and provides novel insights into human phenotypic variation. PLoS Genet 2013; 9:e1004030. [PMID: 24367280 PMCID: PMC3868571 DOI: 10.1371/journal.pgen.1004030] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Accepted: 10/31/2013] [Indexed: 11/19/2022] Open
Abstract
The use of autozygosity as a mapping tool in the search for autosomal recessive disease genes is well established. We hypothesized that autozygosity not only unmasks the recessiveness of disease causing variants, but can also reveal natural knockouts of genes with less obvious phenotypic consequences. To test this hypothesis, we exome sequenced 77 well phenotyped individuals born to first cousin parents in search of genes that are biallelically inactivated. Using a very conservative estimate, we show that each of these individuals carries biallelic inactivation of 22.8 genes on average. For many of the 169 genes that appear to be biallelically inactivated, available data support involvement in modulating metabolism, immunity, perception, external appearance and other phenotypic aspects, and appear therefore to contribute to human phenotypic variation. Other genes with biallelic inactivation may contribute in yet unknown mechanisms or may be on their way to conversion into pseudogenes due to true recent dispensability. We conclude that sequencing the autozygome is an efficient way to map the contribution of genes to human phenotypic variation that goes beyond the classical definition of disease.
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Affiliation(s)
- Ahmed B. Alsalem
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
- Department of Internal Medicine, College of Medicine, King Saud bin-Abdul-Aziz University for Health Sciences, King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - Anason S. Halees
- Molecular Biomedicine Program, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Shamsa Anazi
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Shomoukh Alshamekh
- Department of Ophthalmology, King Abdul-Aziz University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - Fowzan S. Alkuraya
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
- Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
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712
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Grote L, Myers M, Lovell A, Saal H, Sund KL. Variable approaches to genetic counseling for microarray regions of homozygosity associated with parental relatedness. Am J Med Genet A 2013; 164A:87-98. [DOI: 10.1002/ajmg.a.36206] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Accepted: 08/08/2013] [Indexed: 02/06/2023]
Affiliation(s)
- Lauren Grote
- Division of Human Genetics, Department of Pediatrics; Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
- Division of Clinical Genetics; The Children's Mercy Hospital; Kansas City Missouri
| | - Melanie Myers
- Division of Human Genetics, Department of Pediatrics; Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
| | - Anne Lovell
- Division of Human Genetics, Department of Pediatrics; Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
| | - Howard Saal
- Division of Human Genetics, Department of Pediatrics; Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
| | - Kristen Lipscomb Sund
- Division of Human Genetics, Department of Pediatrics; Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
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713
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Kim ES, Cole JB, Huson H, Wiggans GR, Van Tassell CP, Crooker BA, Liu G, Da Y, Sonstegard TS. Effect of artificial selection on runs of homozygosity in u.s. Holstein cattle. PLoS One 2013; 8:e80813. [PMID: 24348915 PMCID: PMC3858116 DOI: 10.1371/journal.pone.0080813] [Citation(s) in RCA: 142] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2013] [Accepted: 10/16/2013] [Indexed: 02/04/2023] Open
Abstract
The intensive selection programs for milk made possible by mass artificial insemination increased the similarity among the genomes of North American (NA) Holsteins tremendously since the 1960s. This migration of elite alleles has caused certain regions of the genome to have runs of homozygosity (ROH) occasionally spanning millions of continuous base pairs at a specific locus. In this study, genome signatures of artificial selection in NA Holsteins born between 1953 and 2008 were identified by comparing changes in ROH between three distinct groups under different selective pressure for milk production. The ROH regions were also used to estimate the inbreeding coefficients. The comparisons of genomic autozygosity between groups selected or unselected since 1964 for milk production revealed significant differences with respect to overall ROH frequency and distribution. These results indicate selection has increased overall autozygosity across the genome, whereas the autozygosity in an unselected line has not changed significantly across most of the chromosomes. In addition, ROH distribution was more variable across the genomes of selected animals in comparison to a more even ROH distribution for unselected animals. Further analysis of genome-wide autozygosity changes and the association between traits and haplotypes identified more than 40 genomic regions under selection on several chromosomes (Chr) including Chr 2, 7, 16 and 20. Many of these selection signatures corresponded to quantitative trait loci for milk, fat, and protein yield previously found in contemporary Holsteins.
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Affiliation(s)
- Eui-Soo Kim
- Bovine Functional Genomics Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - John B. Cole
- Animal Improvement Programs Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - Heather Huson
- Bovine Functional Genomics Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - George R. Wiggans
- Animal Improvement Programs Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - Curtis P. Van Tassell
- Bovine Functional Genomics Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
- Animal Improvement Programs Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - Brian A. Crooker
- Department of Animal Science, University of Minnesota, Saint Paul, Minnesota, United States of America
| | - George Liu
- Bovine Functional Genomics Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
| | - Yang Da
- Department of Animal Science, University of Minnesota, Saint Paul, Minnesota, United States of America
| | - Tad S. Sonstegard
- Bovine Functional Genomics Laboratory, USDA-ARS, Beltsville, Maryland, United States of America
- * E-mail:
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714
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Bhopal RS, Petherick ES, Wright J, Small N. Potential social, economic and general health benefits of consanguineous marriage: results from the Born in Bradford cohort study. Eur J Public Health 2013; 24:862-9. [DOI: 10.1093/eurpub/ckt166] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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715
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Gialluisi A, Incollu S, Pippucci T, Lepori MB, Zappu A, Loudianos G, Romeo G. The homozygosity index (HI) approach reveals high allele frequency for Wilson disease in the Sardinian population. Eur J Hum Genet 2013; 21:1308-11. [PMID: 23486543 PMCID: PMC3798848 DOI: 10.1038/ejhg.2013.43] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2012] [Revised: 01/13/2013] [Accepted: 02/07/2013] [Indexed: 12/28/2022] Open
Abstract
Wilson disease (WD) is an autosomal recessive disorder resulting in pathological progressive copper accumulation in liver and other tissues. The worldwide prevalence (P) is about 30/million, while in Sardinia it is in the order of 1/10,000. However, all of these estimates are likely to suffer from an underdiagnosis bias. Indeed, a recent molecular neonatal screening in Sardinia reported a WD prevalence of 1:2707. In this study, we used a new approach that makes it possible to estimate the allelic frequency (q) of an autosomal recessive disorder if one knows the proportion between homozygous and compound heterozygous patients (the homozygosity index or HI) and the inbreeding coefficient (F) in a sample of affected individuals. We applied the method to a set of 178 Sardinian individuals (3 of whom born to consanguineous parents), each with a clinical and molecular diagnosis of WD. Taking into account the geographical provenance of the parents of every patient within Sardinia (to make F computation more precise), we obtained a q=0.0191 (F=7.8 × 10(-4), HI=0.476) and a corresponding prevalence P=1:2732. This result confirms that the prevalence of WD is largely underestimated in Sardinia. On the other hand, the general reliability and applicability of the HI approach to other autosomal recessive disorders is confirmed, especially if one is interested in the genetic epidemiology of populations with high frequency of consanguineous marriages.
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Affiliation(s)
- Alessandro Gialluisi
- Unità Operativa di Genetica Medica, Dipartimento di Scienze Mediche e Chirurgiche Policlinico Sant'Orsola-Malpighi, Bologna, Italy
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Simona Incollu
- Dipartimento delle Scienze Biomediche e Biotecnologie, Università di Cagliari, Cagliari, Italy
| | - Tommaso Pippucci
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Maria Barbara Lepori
- Dipartimento delle Scienze Biomediche e Biotecnologie, Università di Cagliari, Cagliari, Italy
| | - Antonietta Zappu
- Dipartimento delle Scienze Biomediche e Biotecnologie, Università di Cagliari, Cagliari, Italy
| | | | - Giovanni Romeo
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- European Genetics Foundation, Bologna, Italy
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716
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Herrero-Medrano JM, Megens HJ, Groenen MAM, Ramis G, Bosse M, Pérez-Enciso M, Crooijmans RPMA. Conservation genomic analysis of domestic and wild pig populations from the Iberian Peninsula. BMC Genet 2013; 14:106. [PMID: 24172017 PMCID: PMC3840735 DOI: 10.1186/1471-2156-14-106] [Citation(s) in RCA: 76] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2013] [Accepted: 10/24/2013] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Inbreeding is among the major concerns in management of local livestock populations. The effective population size of these populations tends to be small, which enhances the risk of fitness reduction and extinction. High-density SNP data make it possible to undertake novel approaches in conservation genetics of endangered breeds and wild populations.A total of 97 representative samples of domestic and wild pig populations from the Iberian Peninsula, subjected to different levels of threat with extinction, were genotyped with a 60 K SNP panel. Data analyses based on: (i) allele frequency differences; (ii) linkage disequilibrium and (iii) runs of homozygosity were integrated to study population relationships, inbreeding and demographic history. RESULTS The domestic pigs analyzed belonged to local Spanish and Portuguese breeds: Iberian ─ including the variants Retinto Iberian, Negro Iberian and Manchado de Jabugo ─, Bisaro and Chato Murciano. The population structure and persistence of phase analysis suggested high genetic relations between Iberian variants, with recent crossbreeding of Manchado de Jabugo with other pig populations. Chato Murciano showed a high frequency of long runs of homozygosity indicating recent inbreeding and reflecting the recent bottleneck reported by historical records. The Chato Murciano and the Manchado de Jabugo breeds presented the lowest effective population sizes in accordance with their status of highly inbred breeds. The Iberian wild boar presented a high frequency of short runs of homozygosity indicating past small population size but no signs of recent inbreeding. The Iberian breed showed higher genetic similarities with Iberian wild boar than the other domestic breeds. CONCLUSIONS High-density SNP data provided a consistent overview of population structure, demographic history and inbreeding of minority breeds and wild pig populations from the Iberian Peninsula. Despite the very different background of the populations used, we found a good agreement between the different analyses. Our results are also in agreement with historical reports and provide insight in the events that shaped the current genetic variation of pig populations from the Iberian Peninsula. The results exposed will aid to design and implement strategies for the future management of endangered minority pig breeds and wild populations.
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717
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Glodzik D, Navarro P, Vitart V, Hayward C, McQuillan R, Wild SH, Dunlop MG, Rudan I, Campbell H, Haley C, Wright AF, Wilson JF, McKeigue P. Inference of identity by descent in population isolates and optimal sequencing studies. Eur J Hum Genet 2013; 21:1140-5. [PMID: 23361219 PMCID: PMC3778345 DOI: 10.1038/ejhg.2012.307] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Revised: 12/18/2012] [Accepted: 12/28/2012] [Indexed: 01/24/2023] Open
Abstract
In an isolated population, individuals are likely to share large genetic regions inherited from common ancestors. Identity by descent (IBD) can be inferred from SNP genotypes, which is useful in a number of applications, including identifying genetic variants influencing complex disease risk, and planning efficient cohort-sequencing strategies. We present ANCHAP--a method for detecting IBD in isolated populations. We compare accuracy of the method against other long-range and local phasing methods, using parent-offspring trios. In our experiments, we show that ANCHAP performs similarly as the other long-range method, but requires an order-of-magnitude less computational resources. A local phasing model is able to achieve similar sensitivity, but only at the cost of higher false discovery rates. In some regions of the genome, the studied individuals share haplotypes particularly often, which hints at the history of the populations studied. We demonstrate the method using SNP genotypes from three isolated island populations, as well as in a cohort of unrelated individuals. In samples from three isolated populations of around 1000 individual each, an average individual shares a haplotype at a genetic locus with 9-12 other individuals, compared with only 1 individual within the non-isolated population. We describe an application of ANCHAP to optimally choose samples in resequencing studies. We find that with sample sizes of 1000 individuals from an isolated population genotyped using a dense SNP array, and with 20% of these individuals sequenced, 65% of sequences of the unsequenced subjects can be partially inferred.
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Affiliation(s)
- Dominik Glodzik
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Pau Navarro
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Veronique Vitart
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Caroline Hayward
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Ruth McQuillan
- College of Medicine and Veterinary Medicine, Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Sarah H Wild
- College of Medicine and Veterinary Medicine, Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Malcolm G Dunlop
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Igor Rudan
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Harry Campbell
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Chris Haley
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Alan F Wright
- MRC Institute of Genetics and Molecular Medicine (MRC IGMM), MRC Human Genetics Unit, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - James F Wilson
- College of Medicine and Veterinary Medicine, Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Paul McKeigue
- College of Medicine and Veterinary Medicine, Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
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718
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Huang Y, Hidalgo-Bravo A, Zhang E, Cotton VE, Mendez-Bermudez A, Wig G, Medina-Calzada Z, Neumann R, Jeffreys AJ, Winney B, Wilson JF, Clark DA, Dyer MJ, Royle NJ. Human telomeres that carry an integrated copy of human herpesvirus 6 are often short and unstable, facilitating release of the viral genome from the chromosome. Nucleic Acids Res 2013; 42:315-27. [PMID: 24057213 PMCID: PMC3874159 DOI: 10.1093/nar/gkt840] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Linear chromosomes are stabilized by telomeres, but the presence of short dysfunctional telomeres triggers cellular senescence in human somatic tissues, thus contributing to ageing. Approximately 1% of the population inherits a chromosomally integrated copy of human herpesvirus 6 (CI-HHV-6), but the consequences of integration for the virus and for the telomere with the insertion are unknown. Here we show that the telomere on the distal end of the integrated virus is frequently the shortest measured in somatic cells but not the germline. The telomere carrying the CI-HHV-6 is also prone to truncations that result in the formation of a short telomere at a novel location within the viral genome. We detected extra-chromosomal circular HHV-6 molecules, some surprisingly comprising the entire viral genome with a single fully reconstituted direct repeat region (DR) with both terminal cleavage and packaging elements (PAC1 and PAC2). Truncated CI-HHV-6 and extra-chromosomal circular molecules are likely reciprocal products that arise through excision of a telomere-loop (t-loop) formed within the CI-HHV-6 genome. In summary, we show that the CI-HHV-6 genome disrupts stability of the associated telomere and this facilitates the release of viral sequences as circular molecules, some of which have the potential to become fully functioning viruses.
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Affiliation(s)
- Yan Huang
- Department of Genetics, University of Leicester, University Road, Leicester, LE1 7RH, UK, Department of Oncology, ORCRB, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7DQ, UK, Centre for Population Health Sciences, College of Medicine and Veterinary Medicine, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, Department of Virology, Barts Health NHS Trust, Pathology and Pharmacy Building, 80 Newark St, London E1 2ES, UK and Department of Cancer Studies and Molecular Medicine, University of Leicester, University Road, Leicester, LE1 7RH, UK
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719
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Rosenberg NA, Pemberton TJ, Li JZ, Belmont JW. Runs of homozygosity and parental relatedness. Genet Med 2013; 15:753-4. [PMID: 24008258 DOI: 10.1038/gim.2013.108] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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720
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Association between autozygosity and major depression: stratification due to religious assortment. Behav Genet 2013; 43:455-67. [PMID: 23978897 DOI: 10.1007/s10519-013-9610-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2013] [Accepted: 08/12/2013] [Indexed: 10/26/2022]
Abstract
The effects of inbreeding on the health of offspring can be studied by measuring genome-wide autozygosity as the proportion of the genome in runs of homozygosity (F roh) and relate F roh to outcomes such as psychiatric phenotypes. To successfully conduct these studies, the main patterns of variation for genome-wide autozygosity between and within populations should be well understood and accounted for. Within population variation was investigated in the Dutch population by comparing autozygosity between religious and non-religious groups. The Netherlands have a history of societal segregation and assortment based on religious affiliation, which may have increased parental relatedness within religious groups. Religion has been associated with several psychiatric phenotypes, such as major depressive disorder (MDD). We investigated whether there is an association between autozygosity and MDD, and the extent to which this association can be explained by religious affiliation. All F roh analyses included adjustment for ancestry-informative principal components (PCs) and geographic factors. Religious affiliation was significantly associated with autozygosity, showing that F roh has the ability to capture within population differences that are not captured by ancestry-informative PCs or geographic factors. The non-religious group had significantly lower F roh values and significantly more MDD cases, leading to a nominally significant negative association between autozygosity and depression. After accounting for religious affiliation, MDD was not associated with F roh, indicating that the relation between MDD and inbreeding was due to stratification. This study shows how past religious assortment and recent secularization can have genetic consequences in a relatively small country. This warrants accounting for the historical social context and its effects on genetic variation in association studies on psychiatric and other related traits.
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721
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Joshi PK, Prendergast J, Fraser RM, Huffman JE, Vitart V, Hayward C, McQuillan R, Glodzik D, Polašek O, Hastie ND, Rudan I, Campbell H, Wright AF, Haley CS, Wilson JF, Navarro P. Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies. PLoS One 2013; 8:e68604. [PMID: 23874685 PMCID: PMC3712964 DOI: 10.1371/journal.pone.0068604] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Accepted: 05/30/2013] [Indexed: 11/18/2022] Open
Abstract
The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10%) in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.
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Affiliation(s)
- Peter K. Joshi
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - James Prendergast
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ross M. Fraser
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Jennifer E. Huffman
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Veronique Vitart
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ruth McQuillan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Dominik Glodzik
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Ozren Polašek
- Department of Public Health, University of Split, Split, Croatia
- Centre for Global Health, University of Split, Split, Croatia
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- Roslin Institute, University of Edinburgh, Scotland, United Kingdom
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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722
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Szpiech Z, Xu J, Pemberton T, Peng W, Zöllner S, Rosenberg N, Li J. Long runs of homozygosity are enriched for deleterious variation. Am J Hum Genet 2013; 93:90-102. [PMID: 23746547 DOI: 10.1016/j.ajhg.2013.05.003] [Citation(s) in RCA: 201] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Revised: 03/22/2013] [Accepted: 05/01/2013] [Indexed: 02/02/2023] Open
Abstract
Exome sequencing offers the potential to study the population-genomic variables that underlie patterns of deleterious variation. Runs of homozygosity (ROH) are long stretches of consecutive homozygous genotypes probably reflecting segments shared identically by descent as the result of processes such as consanguinity, population size reduction, and natural selection. The relationship between ROH and patterns of predicted deleterious variation can provide insight into the way in which these processes contribute to the maintenance of deleterious variants. Here, we use exome sequencing to examine ROH in relation to the distribution of deleterious variation in 27 individuals of varying levels of apparent inbreeding from 6 human populations. A significantly greater fraction of all genome-wide predicted damaging homozygotes fall in ROH than would be expected from the corresponding fraction of nondamaging homozygotes in ROH (p < 0.001). This pattern is strongest for long ROH (p < 0.05). ROH, and especially long ROH, harbor disproportionately more deleterious homozygotes than would be expected on the basis of the total ROH coverage of the genome and the genomic distribution of nondamaging homozygotes. The results accord with a hypothesis that recent inbreeding, which generates long ROH, enables rare deleterious variants to exist in homozygous form. Thus, just as inbreeding can elevate the occurrence of rare recessive diseases that represent homozygotes for strongly deleterious mutations, inbreeding magnifies the occurrence of mildly deleterious variants as well.
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723
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Rietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polašek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiriksdottir G, Elderson MF, Eriksson JG, et alRietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polašek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiriksdottir G, Elderson MF, Eriksson JG, Evans DM, Faul JD, Ferrucci L, Garcia ME, Grönberg H, Gudnason V, Hall P, Harris JM, Harris TB, Hastie ND, Heath AC, Hernandez DG, Hoffmann W, Hofman A, Holle R, Holliday EG, Hottenga JJ, Iacono WG, Illig T, Järvelin MR, Kähönen M, Kaprio J, Kirkpatrick RM, Kowgier M, Latvala A, Launer LJ, Lawlor DA, Lehtimäki T, Li J, Lichtenstein P, Lichtner P, Liewald DC, Madden PA, Magnusson PKE, Mäkinen TE, Masala M, McGue M, Metspalu A, Mielck A, Miller MB, Montgomery GW, Mukherjee S, Nyholt DR, Oostra BA, Palmer LJ, Palotie A, Penninx B, Perola M, Peyser PA, Preisig M, Räikkönen K, Raitakari OT, Realo A, Ring SM, Ripatti S, Rivadeneira F, Rudan I, Rustichini A, Salomaa V, Sarin AP, Schlessinger D, Scott RJ, Snieder H, Pourcain BS, Starr JM, Sul JH, Surakka I, Svento R, Teumer A, The LifeLines Cohort Study, Tiemeier H, Rooij FJA, Van Wagoner DR, Vartiainen E, Viikari J, Vollenweider P, Vonk JM, Waeber G, Weir DR, Wichmann HE, Widen E, Willemsen G, Wilson JF, Wright AF, Conley D, Davey-Smith G, Franke L, Groenen PJF, Hofman A, Johannesson M, Kardia SL, Krueger RF, Laibson D, Martin NG, Meyer MN, Posthuma D, Thurik AR, Timpson NJ, Uitterlinden AG, van Duijn CM, Visscher PM, Benjamin DJ, Cesarini D, Koellinger PD. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 2013; 340:1467-71. [PMID: 23722424 PMCID: PMC3751588 DOI: 10.1126/science.1235488] [Show More Authors] [Citation(s) in RCA: 505] [Impact Index Per Article: 42.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
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Affiliation(s)
- Cornelius A. Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Sarah E. Medland
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Jaime Derringer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309–0447, USA
| | - Jian Yang
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Nicolas W. Martin
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland 4072, Australia
| | - Harm-Jan Westra
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Konstantin Shakhbazov
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Abdel Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Behrooz Z. Alizadeh
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - John Barnard
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | | | - Kelly S. Benke
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario M5G 1X5, Canada
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Jeffrey A. Boatman
- Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Patricia A. Boyle
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Gail Davies
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Christiaan de Leeuw
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
| | - Niina Eklund
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107–1728, USA
| | - Rudolf Ferhmann
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Håkon K. Gjessing
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Sara Hägg
- Molecular Epidemiology, Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Jennifer R. Harris
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Caroline Hayward
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Christina Holzapfel
- Else Kroener-Fresenius-Centre for Nutritional Medicine, Technische Universität München, 81675 Munich, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Carla A. Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Erik Ingelsson
- Molecular Epidemiology, Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Bo Jacobsson
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
- Department of Obstetrics and Gynecology, Institute of Public Health, Sahlgrenska Academy, Sahgrenska University Hospital, Gothenburg, 413 45, Sweden
| | - Peter K. Joshi
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Astanand Jugessur
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Marika Kaakinen
- Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
- Biocenter Oulu, University of Oulu, Oulu 90014, Finland
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Juha Karjalainen
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Ivana Kolcic
- Faculty of Medicine, University of Split, 21000 Split, Croatia
| | - Kati Kristiansson
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Zoltán Kutalik
- Department of Medical Genetics, University of Lausanne, 1005 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Jari Lahti
- Institute of Behavioral Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Sang H. Lee
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Peng Lin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Penelope A. Lind
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157–1063, USA
| | - Kurt Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157–1063, USA
| | - Marisa Loitfelder
- Division for Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz 8036, Austria
| | - George McMahon
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Pedro Marques Vidal
- Institute of Social and Preventive Medicine, Lausanne University Hospital, 1005 Lausanne, Switzerland
| | - Osorio Meirelles
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Ronny Myhre
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Nydalen, N-0403 Oslo, Norway
| | - Marja-Liisa Nuotio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Christopher J. Oldmeadow
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Katja E. Petrovic
- Division of General Neurology, Department of Neurology, General Hospital and Medical University of Graz, Graz 8036, Austria
| | - Wouter J. Peyrot
- Department of Psychiatry, VU University Medical Center, 1081 HL Amsterdam, The Netherlands
| | - Ozren Polašek
- Faculty of Medicine, University of Split, 21000 Split, Croatia
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Eva Reinmaa
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - John P. Rice
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Thais S. Rizzi
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
| | - Helena Schmidt
- Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz 8036, Austria
| | - Reinhold Schmidt
- Division for Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz 8036, Austria
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur 201, Iceland
- Department of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Toshiko Tanaka
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Antonio Terracciano
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
- College of Medicine, Florida State University, Tallahassee, FL 32306–4300, USA
| | - Matthijs J.H.M. van der Loos
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Veronique Vitart
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany
| | - Jürgen Wellmann
- Institute of Epidemiology and Social Medicine, University of Muenster, 48129 Muenster, Germany
| | - Lei Yu
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Jüri Allik
- Department of Psychology, University of Tartu, Tartu 50410, Estonia
| | - John R. Attia
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | | | - François Bastardot
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | | | - David A. Bennett
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL 60612, USA
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Muenster, 48129 Muenster, Germany
| | - Laura J. Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - Ute Bültmann
- Department of Health Sciences, Community & Occupational Medicine, University Medical Center Groningen, 9700 AD Groningen, The Netherlands
| | - Harry Campbell
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | | | - Lynn Cherkas
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Mina K. Chung
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, 09042, Cagliari, Italy
- Dipartimento di Scienze Biomediche, Università di Sassari, 07100 SS, Italy
| | - Mariza de Andrade
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
| | - Philip L. De Jager
- Program in Translational Neuropsychiatric Genomics, Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Jan-Emmanuel De Neve
- School of Public Policy, University College London, London WC1H 9QU, UK
- Centre for Economic Performance, London School of Economics, London WC2A 2AE, UK
| | - Ian J. Deary
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
- Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - George V. Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Maria Dimitriou
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 17671, Greece
| | | | - Martin F. Elderson
- LifeLines Cohort Study, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki 00014, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki 00280, Finland
- Folkhälsan Research Center, Helsinki 00250, Finland
- Vaasa Central Hospital, Vaasa 65130, Finland
| | - David M. Evans
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Melissa E. Garcia
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur 201, Iceland
- Department of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Juliette M. Harris
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Tamara B. Harris
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Nicholas D. Hastie
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Andrew C. Heath
- Division of Biology and Biomedical Sciences, Washington University, St. Louis, MO 63110–1093, USA
| | - Dena G. Hernandez
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Wolfgang Hoffmann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany
| | - Adriaan Hofman
- Faculty of Behavioral and Social Sciences, University of Groningen, 9747 AD Groningen, The Netherlands
| | - Rolf Holle
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Elizabeth G. Holliday
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, 30625 Hannover, Germany
| | - Marjo-Riitta Järvelin
- Institute of Health Sciences, University of Oulu, Oulu 90014, Finland
- Biocenter Oulu, University of Oulu, Oulu 90014, Finland
- Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, Imperial College London, London W2 1PG, UK
- Unit of Primary Care, Oulu University Hospital, Oulu 90220, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu 90101, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere 33520, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, 00300 Helsinki, Finland
| | | | - Matthew Kowgier
- Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Antti Latvala
- Department of Public Health, University of Helsinki, 00014 Helsinki, Finland
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, 00300 Helsinki, Finland
| | - Lenore J. Launer
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Debbie A. Lawlor
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University Hospital, Tampere 33520, Finland
| | - Jingmei Li
- Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Peter Lichtner
- Institute of Human Genetics, Helmholtz Centre Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - David C. Liewald
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Pamela A. Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Tomi E. Mäkinen
- Department of Health, Functional Capacity and Welfare, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Marco Masala
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, 09042, Cagliari, Italy
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Andreas Mielck
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Michael B. Miller
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - Grant W. Montgomery
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Sutapa Mukherjee
- Western Australia Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia
- Department of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Women’s College Research Institute, University of Toronto, Toronto, Ontario M5G 1N8, Canada
| | - Dale R. Nyholt
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Ben A. Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Lyle J. Palmer
- Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
- Department of Medical Genetics, University of Helsinki, 00014 Helsinki, Finland
| | - Brenda Penninx
- Department of Psychiatry, VU University Medical Center, 1081 HL Amsterdam, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Martin Preisig
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - Katri Räikkönen
- Institute of Behavioral Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Anu Realo
- Department of Psychology, University of Tartu, Tartu 50410, Estonia
| | - Susan M. Ring
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Igor Rudan
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Aldo Rustichini
- Department of Economics, University of Minnesota, Minneapolis, MN 55455–0462, USA
| | - Veikko Salomaa
- Chronic Disease Epidemiology Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - David Schlessinger
- National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Rodney J. Scott
- Hunter Medical Research Institute and Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Beate St Pourcain
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol BS1 2LY, UK
| | - John M. Starr
- Centre for Cognitive Aging and Cognitive Epidemiology, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh EH8 9JZ, Scotland, UK
| | - Jae Hoon Sul
- Department of Computer Science, University of California, Los Angeles, CA 90095, USA
| | - Ida Surakka
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, The National Institute for Health and Welfare, Helsinki 00014, Finland
| | - Rauli Svento
- Department of Economics, Oulu Business School, University of Oulu, Oulu 90014, Finland
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald 17487, Germany
| | | | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, 3000 CB Rotterdam, The Netherlands
| | - Frank JAan Rooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - David R. Van Wagoner
- Heart and Vascular and Lerner Research Institutes, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Erkki Vartiainen
- Division of Welfare and Health Promotion, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Jorma Viikari
- Department of Medicine, Turku University Hospital, Turku 20520, Finland
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - Judith M. Vonk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Gérard Waeber
- Department of Internal Medicine, University Hospital, 1011 Lausanne, Switzerland
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
| | - H.-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, 81377 Munich, Germany
- Klinikum Grosshadern, 81377 Munich, Germany
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Centre for Environmental Health, 85764 Neuherberg, Germany
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - James F. Wilson
- Centre for Population Health Sciences, The University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Alan F. Wright
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Dalton Conley
- Department of Sociology, New York University, New York, NY 10012, USA
| | - George Davey-Smith
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Patrick J. F. Groenen
- Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam 3000 DR, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm 113 83, Sweden
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109–2029, USA
| | - Robert F. Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455–0344, USA
| | - David Laibson
- Department of Economics, Harvard University, Cambridge, MA 02138, USA
| | - Nicholas G. Martin
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
| | - Michelle N. Meyer
- Petrie-Flom Center for Health Law Policy, Biotechnology, & Bioethics, Harvard Law School, Cambridge, MA 02138, USA
- Nelson A. Rockefeller Institute of Government, State University of New York, Albany, NY 12203–1003, USA
| | - Danielle Posthuma
- Department of Functional Genomics, VU University Amsterdam and VU Medical Center, 1081 HV Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, 3000 CB Rotterdam, The Netherlands
- Department of Clinical Genetics, VU University Medical Centrer, 1081 BT Amsterdam, The Netherlands
| | - A. Roy Thurik
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Panteia, Zoetermeer 2701 AA, Netherlands
- GSCM-Montpellier Business School, Montpellier 34185, France
| | - Nicholas J. Timpson
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Centre for Medical Systems Biology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
| | - Peter M. Visscher
- Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | | | - David Cesarini
- Center for Experimental Social Science, Department of Economics, New York University, New York, NY 10012, USA
- Division of Social Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE
- Research Institute of Industrial Economics, Stockholm 102 15, Sweden
| | - Philipp D. Koellinger
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
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724
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Wiszniewska J, Bi W, Shaw C, Stankiewicz P, Kang SHL, Pursley AN, Lalani S, Hixson P, Gambin T, Tsai CH, Bock HG, Descartes M, Probst FJ, Scaglia F, Beaudet AL, Lupski JR, Eng C, Cheung SW, Bacino C, Patel A. Combined array CGH plus SNP genome analyses in a single assay for optimized clinical testing. Eur J Hum Genet 2013; 22:79-87. [PMID: 23695279 PMCID: PMC3865406 DOI: 10.1038/ejhg.2013.77] [Citation(s) in RCA: 93] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2012] [Revised: 01/28/2013] [Accepted: 03/12/2013] [Indexed: 02/06/2023] Open
Abstract
In clinical diagnostics, both array comparative genomic hybridization (array CGH) and single nucleotide polymorphism (SNP) genotyping have proven to be powerful genomic technologies utilized for the evaluation of developmental delay, multiple congenital anomalies, and neuropsychiatric disorders. Differences in the ability to resolve genomic changes between these arrays may constitute an implementation challenge for clinicians: which platform (SNP vs array CGH) might best detect the underlying genetic cause for the disease in the patient? While only SNP arrays enable the detection of copy number neutral regions of absence of heterozygosity (AOH), they have limited ability to detect single-exon copy number variants (CNVs) due to the distribution of SNPs across the genome. To provide comprehensive clinical testing for both CNVs and copy-neutral AOH, we enhanced our custom-designed high-resolution oligonucleotide array that has exon-targeted coverage of 1860 genes with 60 000 SNP probes, referred to as Chromosomal Microarray Analysis – Comprehensive (CMA-COMP). Of the 3240 cases evaluated by this array, clinically significant CNVs were detected in 445 cases including 21 cases with exonic events. In addition, 162 cases (5.0%) showed at least one AOH region >10 Mb. We demonstrate that even though this array has a lower density of SNP probes than other commercially available SNP arrays, it reliably detected AOH events >10 Mb as well as exonic CNVs beyond the detection limitations of SNP genotyping. Thus, combining SNP probes and exon-targeted array CGH into one platform provides clinically useful genetic screening in an efficient manner.
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Affiliation(s)
- Joanna Wiszniewska
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Weimin Bi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Chad Shaw
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Pawel Stankiewicz
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Sung-Hae L Kang
- Allina Cytogenetics Laboratory, Abbott Northwestern Hospital, Minneapolis, MN, USA
| | - Amber N Pursley
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Seema Lalani
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Patricia Hixson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Tomasz Gambin
- Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland
| | - Chun-hui Tsai
- 1] Department of Molecular and Medical Genetics, Oregon Health and Sciences University-OHSU, Portland, OR, USA [2] Department of Pediatrics, The Children's Hospital, University of Colorado School of Medicine, Aurora, CO, USA
| | - Hans-Georg Bock
- Department of Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Maria Descartes
- Department of Genetics, University of Alabama, Birmingham, AL, USA
| | - Frank J Probst
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Fernando Scaglia
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Arthur L Beaudet
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - James R Lupski
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Christine Eng
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Sau Wai Cheung
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Carlos Bacino
- 1] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA [2] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Ankita Patel
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
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725
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Transcription factor gene MNX1 is a novel cause of permanent neonatal diabetes in a consanguineous family. DIABETES & METABOLISM 2013; 39:276-80. [DOI: 10.1016/j.diabet.2013.02.007] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Revised: 02/15/2013] [Accepted: 02/21/2013] [Indexed: 11/21/2022]
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726
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Wang C, Xu Z, Jin G, Hu Z, Dai J, Ma H, Jiang Y, Hu L, Chu M, Cao S, Shen H. Genome-wide analysis of runs of homozygosity identifies new susceptibility regions of lung cancer in Han Chinese. J Biomed Res 2013; 27:208-14. [PMID: 23720676 PMCID: PMC3664727 DOI: 10.7555/jbr.27.20130017] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Revised: 02/27/2013] [Accepted: 03/14/2013] [Indexed: 12/02/2022] Open
Abstract
Runs of homozygosity (ROHs) are a class of important but poorly studied genomic variations and may be involved in individual susceptibility to diseases. To better understand ROH and its relationship with lung cancer, we performed a genome-wide ROH analysis of a subset of a previous genome-wide case-control study (1,473 cases and 1,962 controls) in a Han Chinese population. ROHs were classified into two classes, based on lengths, intermediate and long ROHs, to evaluate their association with lung cancer risk using existing genome-wide single nucleotide polymorphism (SNP) data. We found that the overall level of intermediate ROHs was significantly associated with a decreased risk of lung cancer (odds ratio = 0.63; 95% confidence interval: 0.51-0.77; P = 4.78×10−6 ), while the long ROHs seemed to be a risk factor of lung cancer. We also identified one ROH region at 14q23.1 that was consistently associated with lung cancer risk in the study. These results indicated that ROHs may be a new class of variation which may be associated with lung cancer risk, and genetic variants at 14q23.1 may be involved in the development of lung cancer.
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Affiliation(s)
- Cheng Wang
- Department of Epidemiology and Biostatistics and Ministry of Education (MOE) Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 210029, China
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727
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Khrunin AV, Khokhrin DV, Filippova IN, Esko T, Nelis M, Bebyakova NA, Bolotova NL, Klovins J, Nikitina-Zake L, Rehnström K, Ripatti S, Schreiber S, Franke A, Macek M, Krulišová V, Lubinski J, Metspalu A, Limborska SA. A genome-wide analysis of populations from European Russia reveals a new pole of genetic diversity in northern Europe. PLoS One 2013; 8:e58552. [PMID: 23505534 PMCID: PMC3591355 DOI: 10.1371/journal.pone.0058552] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2012] [Accepted: 02/06/2013] [Indexed: 11/18/2022] Open
Abstract
Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia (Tver, Murom, and Kursk) exhibited similarities with populations from central-eastern Europe, and were distant from Russian sample from the northern Russia (Mezen district, Archangelsk region). Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe (in addition to the pole, occupied by Finns), as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations.
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Affiliation(s)
- Andrey V Khrunin
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia.
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728
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Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers. PLoS Genet 2013; 9:e1003225. [PMID: 23382691 PMCID: PMC3561084 DOI: 10.1371/journal.pgen.1003225] [Citation(s) in RCA: 281] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2012] [Accepted: 11/21/2012] [Indexed: 12/22/2022] Open
Abstract
Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF mass spectrometry (MS) in a replication cohort of 1,848 Europeans. Meta-analysis of genome-wide association study (GWAS) results identified 9 genome-wide significant loci (P<2.27×10−9) in the discovery analysis and two of the same loci (B4GALT1 and MGAT3) in the replication cohort. Four loci contained genes encoding glycosyltransferases (ST6GAL1, B4GALT1, FUT8, and MGAT3), while the remaining 5 contained genes that have not been previously implicated in protein glycosylation (IKZF1, IL6ST-ANKRD55, ABCF2-SMARCD3, SUV420H1, and SMARCB1-DERL3). However, most of them have been strongly associated with autoimmune and inflammatory conditions (e.g., systemic lupus erythematosus, rheumatoid arthritis, ulcerative colitis, Crohn's disease, diabetes type 1, multiple sclerosis, Graves' disease, celiac disease, nodular sclerosis) and/or haematological cancers (acute lymphoblastic leukaemia, Hodgkin lymphoma, and multiple myeloma). Follow-up functional experiments in haplodeficient Ikzf1 knock-out mice showed the same general pattern of changes in IgG glycosylation as identified in the meta-analysis. As IKZF1 was associated with multiple IgG N-glycan traits, we explored biomarker potential of affected N-glycans in 101 cases with SLE and 183 matched controls and demonstrated substantial discriminative power in a ROC-curve analysis (area under the curve = 0.842). Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. The results may also provide an explanation for the reported pleiotropy and antagonistic effects of loci involved in autoimmune diseases and haematological cancer. After analysing glycans attached to human immunoglobulin G in 4,095 individuals, we performed the first genome-wide association study (GWAS) of the glycome of an individual protein. Nine genetic loci were found to associate with glycans with genome-wide significance. Of these, four were enzymes that directly participate in IgG glycosylation, thus the observed associations were biologically founded. The remaining five genetic loci were not previously implicated in protein glycosylation, but the most of them have been reported to be relevant for autoimmune and inflammatory conditions and/or haematological cancers. A particularly interesting gene, IKZF1 was found to be associated with multiple IgG N-glycans. This gene has been implicated in numerous diseases, including systemic lupus erythematosus (SLE). We analysed N-glycans in 101 cases with SLE and 183 matched controls and demonstrated their substantial biomarker potential. Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. Our results may also provide an explanation for opposite effects of some genes in autoimmune diseases and haematological cancer.
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729
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Silió L, Rodríguez MC, Fernández A, Barragán C, Benítez R, Óvilo C, Fernández AI. Measuring inbreeding and inbreeding depression on pig growth from pedigree or SNP-derived metrics. J Anim Breed Genet 2013; 130:349-60. [PMID: 24074172 DOI: 10.1111/jbg.12031] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2012] [Accepted: 12/20/2012] [Indexed: 12/22/2022]
Abstract
Multilocus homozygosity, measured as the proportion of the autosomal genome in homozygous genotypes or in runs of homozygosity, was compared with the respective pedigree inbreeding coefficients in 64 Iberian pigs genotyped using the Porcine SNP60 Beadchip. Pigs were sampled from a set of experimental animals with a large inbreeding variation born in a closed strain with a completely recorded multi-generation genealogy. Individual inbreeding coefficients calculated from pedigree were strongly correlated with the different SNP-derived metrics of homozygosity (r = 0.814-0.919). However, unequal correlations between molecular and pedigree inbreeding were observed at chromosomal level being mainly dependent on the number of SNPs and on the correlation between heterozygosities measured across different loci. A panel of 192 SNPs of intermediate frequencies was selected for genotyping 322 piglets to test inbreeding depression on postweaning growth performance (daily gain and weight at 90 days). The negative effects on these traits of homozygosities calculated from the genotypes of 168 quality-checked SNPs were similar to those of inbreeding coefficients. The results support that few hundreds of SNPs may be useful for measuring inbreeding and inbreeding depression, when the population structure or the mating system causes a large variance of inbreeding.
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Affiliation(s)
- L Silió
- Departamento de Mejora Genética Animal, INIA, Madrid, Spain
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730
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Rehder CW, David KL, Hirsch B, Toriello HV, Wilson CM, Kearney HM. American College of Medical Genetics and Genomics: standards and guidelines for documenting suspected consanguinity as an incidental finding of genomic testing. Genet Med 2013; 15:150-2. [DOI: 10.1038/gim.2012.169] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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731
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Esko T, Mezzavilla M, Nelis M, Borel C, Debniak T, Jakkula E, Julia A, Karachanak S, Khrunin A, Kisfali P, Krulisova V, Aušrelé Kučinskiené Z, Rehnström K, Traglia M, Nikitina-Zake L, Zimprich F, Antonarakis SE, Estivill X, Glavač D, Gut I, Klovins J, Krawczak M, Kučinskas V, Lathrop M, Macek M, Marsal S, Meitinger T, Melegh B, Limborska S, Lubinski J, Paolotie A, Schreiber S, Toncheva D, Toniolo D, Wichmann HE, Zimprich A, Metspalu M, Gasparini P, Metspalu A, D'Adamo P. Genetic characterization of northeastern Italian population isolates in the context of broader European genetic diversity. Eur J Hum Genet 2012; 21:659-65. [PMID: 23249956 PMCID: PMC3658181 DOI: 10.1038/ejhg.2012.229] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
Population genetic studies on European populations have highlighted Italy as one of genetically most diverse regions. This is possibly due to the country's complex demographic history and large variability in terrain throughout the territory. This is the reason why Italy is enriched for population isolates, Sardinia being the best-known example. As the population isolates have a great potential in disease-causing genetic variants identification, we aimed to genetically characterize a region from northeastern Italy, which is known for isolated communities. Total of 1310 samples, collected from six geographically isolated villages, were genotyped at >145 000 single-nucleotide polymorphism positions. Newly genotyped data were analyzed jointly with the available genome-wide data sets of individuals of European descent, including several population isolates. Despite the linguistic differences and geographical isolation the village populations still show the greatest genetic similarity to other Italian samples. The genetic isolation and small effective population size of the village populations is manifested by higher levels of genomic homozygosity and elevated linkage disequilibrium. These estimates become even more striking when the detected substructure is taken into account. The observed level of genetic isolation in Friuli-Venezia Giulia region is more extreme according to several measures of isolation compared with Sardinians, French Basques and northern Finns, thus proving the status of an isolate.
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Affiliation(s)
- Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
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732
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Mendizabal I, Lao O, Marigorta UM, Wollstein A, Gusmão L, Ferak V, Ioana M, Jordanova A, Kaneva R, Kouvatsi A, Kučinskas V, Makukh H, Metspalu A, Netea MG, de Pablo R, Pamjav H, Radojkovic D, Rolleston SJH, Sertic J, Macek M, Comas D, Kayser M. Reconstructing the population history of European Romani from genome-wide data. Curr Biol 2012; 22:2342-2349. [PMID: 23219723 DOI: 10.1016/j.cub.2012.10.039] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2012] [Revised: 08/22/2012] [Accepted: 10/23/2012] [Indexed: 01/21/2023]
Abstract
The Romani, the largest European minority group with approximately 11 million people, constitute a mosaic of languages, religions, and lifestyles while sharing a distinct social heritage. Linguistic and genetic studies have located the Romani origins in the Indian subcontinent. However, a genome-wide perspective on Romani origins and population substructure, as well as a detailed reconstruction of their demographic history, has yet to be provided. Our analyses based on genome-wide data from 13 Romani groups collected across Europe suggest that the Romani diaspora constitutes a single initial founder population that originated in north/northwestern India ~1.5 thousand years ago (kya). Our results further indicate that after a rapid migration with moderate gene flow from the Near or Middle East, the European spread of the Romani people was via the Balkans starting ~0.9 kya. The strong population substructure and high levels of homozygosity we found in the European Romani are in line with genetic isolation as well as differential gene flow in time and space with non-Romani Europeans. Overall, our genome-wide study sheds new light on the origins and demographic history of European Romani.
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Affiliation(s)
- Isabel Mendizabal
- Departament de Ciències de la Salut i de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, 08003 Barcelona, Spain
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733
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Ben Halim N, Ben Alaya Bouafif N, Romdhane L, Kefi Ben Atig R, Chouchane I, Bouyacoub Y, Arfa I, Cherif W, Nouira S, Talmoudi F, Lasram K, Hsouna S, Ghazouani W, Azaiez H, El Matri L, Abid A, Tebib N, Ben Dridi MF, Kachboura S, Amouri A, Mokni M, Ben Arab S, Dellagi K, Abdelhak S. Consanguinity, endogamy, and genetic disorders in Tunisia. J Community Genet 2012. [PMID: 23208456 DOI: 10.1007/s12687-012-0128-7] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Affiliation(s)
- Nizar Ben Halim
- Laboratory of Biomedical Genomics and Oncogenetics, Pasteur Institute of Tunis, BP 74, 13 Place Pasteur, Tunis, Le Belvédère, 1002, Tunisia,
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734
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Palamara PF, Lencz T, Darvasi A, Pe'er I. Length distributions of identity by descent reveal fine-scale demographic history. Am J Hum Genet 2012; 91:809-22. [PMID: 23103233 DOI: 10.1016/j.ajhg.2012.08.030] [Citation(s) in RCA: 170] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2011] [Revised: 03/18/2012] [Accepted: 08/29/2012] [Indexed: 11/28/2022] Open
Abstract
Data-driven studies of identity by descent (IBD) were recently enabled by high-resolution genomic data from large cohorts and scalable algorithms for IBD detection. Yet, haplotype sharing currently represents an underutilized source of information for population-genetics research. We present analytical results on the relationship between haplotype sharing across purportedly unrelated individuals and a population's demographic history. We express the distribution of IBD sharing across pairs of individuals for segments of arbitrary length as a function of the population's demography, and we derive an inference procedure to reconstruct such demographic history. The accuracy of the proposed reconstruction methodology was extensively tested on simulated data. We applied this methodology to two densely typed data sets: 500 Ashkenazi Jewish (AJ) individuals and 56 Kenyan Maasai (MKK) individuals (HapMap 3 data set). Reconstructing the demographic history of the AJ cohort, we recovered two subsequent population expansions, separated by a severe founder event, consistent with previous analysis of lower-throughput genetic data and historical accounts of AJ history. In the MKK cohort, high levels of cryptic relatedness were detected. The spectrum of IBD sharing is consistent with a demographic model in which several small-sized demes intermix through high migration rates and result in enrichment of shared long-range haplotypes. This scenario of historically structured demographies might explain the unexpected abundance of runs of homozygosity within several populations.
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735
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Milosevic JD, Puda A, Malcovati L, Berg T, Hofbauer M, Stukalov A, Klampfl T, Harutyunyan AS, Gisslinger H, Gisslinger B, Burjanivova T, Rumi E, Pietra D, Elena C, Vannucchi AM, Doubek M, Dvorakova D, Robesova B, Wieser R, Koller E, Suvajdzic N, Tomin D, Tosic N, Colinge J, Racil Z, Steurer M, Pavlovic S, Cazzola M, Kralovics R. Clinical significance of genetic aberrations in secondary acute myeloid leukemia. Am J Hematol 2012; 87:1010-6. [PMID: 22887079 DOI: 10.1002/ajh.23309] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2012] [Accepted: 07/02/2012] [Indexed: 12/30/2022]
Abstract
The study aimed to identify genetic lesions associated with secondary acute myeloid leukemia (sAML) in comparison with AML arising de novo (dnAML) and assess their impact on patients' overall survival (OS). High-resolution genotyping and loss of heterozygosity mapping was performed on DNA samples from 86 sAML and 117 dnAML patients, using Affymetrix Genome-Wide Human SNP 6.0 arrays. Genes TP53, RUNX1, CBL, IDH1/2, NRAS, NPM1, and FLT3 were analyzed for mutations in all patients. We identified 36 recurrent cytogenetic aberrations (more than five events). Mutations in TP53, 9pUPD, and del7q (targeting CUX1 locus) were significantly associated with sAML, while NPM1 and FLT3 mutations associated with dnAML. Patients with sAML carrying TP53 mutations demonstrated lower 1-year OS rate than those with wild-type TP53 (14.3% ± 9.4% vs. 35.4% ± 7.2%; P = 0.002), while complex karyotype, del7q (CUX1) and del7p (IKZF1) showed no significant effect on OS. Multivariate analysis confirmed that mutant TP53 was the only independent adverse prognostic factor for OS in sAML (hazard ratio 2.67; 95% CI: 1.33-5.37; P = 0.006). Patients with dnAML and complex karyotype carried sAML-associated defects (TP53 defects in 54.5%, deletions targeting FOXP1 and ETV6 loci in 45.4% of the cases). We identified several co-occurring lesions associated with either sAML or dnAML diagnosis. Our data suggest that distinct genetic lesions drive leukemogenesis in sAML. High karyotype complexity of sAML patients does not influence OS. Somatic mutations in TP53 are the only independent adverse prognostic factor in sAML. Patients with dnAML and complex karyotype show genetic features associated with sAML and myeloproliferative neoplasms.
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Affiliation(s)
- Jelena D Milosevic
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
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736
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Ferenčaković M, Hamzić E, Gredler B, Solberg TR, Klemetsdal G, Curik I, Sölkner J. Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations. J Anim Breed Genet 2012; 130:286-93. [PMID: 23855630 DOI: 10.1111/jbg.12012] [Citation(s) in RCA: 171] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2012] [Accepted: 09/14/2012] [Indexed: 11/27/2022]
Abstract
Using genome-wide SNP data, we calculated genomic inbreeding coefficients (FROH > 1 Mb , FROH > 2 Mb , FROH > 8 Mb and FROH > 16 Mb ) derived from runs of homozygosity (ROH) of different lengths (>1, >2, >8 and > 16 Mb) as well as from levels of homozygosity (FHOM ). We compared these values of inbreeding coefficients with those calculated from pedigrees (FPED ) of 1422 bulls comprising Brown Swiss (304), Fleckvieh (502), Norwegian Red (499) and Tyrol Grey (117) cattle breeds. For all four breeds, population inbreeding levels estimated by the genomic inbreeding coefficients FROH > 8 Mb and FROH > 16 Mb were similar to the levels estimated from pedigrees. The lowest values were obtained for Fleckvieh (FPED = 0.014, FROH > 8 Mb = 0.019 and FROH > 16 Mb = 0.008); the highest, for Brown Swiss (FPED = 0.048, FROH > 8 Mb = 0.074 and FROH > 16 Mb = 0.037). In contrast, inbreeding estimates based on the genomic coefficients FROH > 1 Mb and FROH > 2 Mb were considerably higher than pedigree-derived estimates. Standard deviations of genomic inbreeding coefficients were, on average, 1.3-1.7-fold higher than those obtained from pedigrees. Pearson correlations between genomic and pedigree inbreeding coefficients ranged from 0.50 to 0.62 in Norwegian Red (lowest correlations) and from 0.64 to 0.72 in Tyrol Grey (highest correlations). We conclude that the proportion of the genome present in ROH provides a good indication of inbreeding levels and that analysis based on ROH length can indicate the relative amounts of autozygosity due to recent and remote ancestors.
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Affiliation(s)
- M Ferenčaković
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Zagreb, Croatia
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737
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Analysis of the canine genome and canine health: a commentary. Vet J 2012; 194:265-9. [PMID: 23088856 DOI: 10.1016/j.tvjl.2012.09.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2012] [Revised: 08/31/2012] [Accepted: 09/01/2012] [Indexed: 11/23/2022]
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738
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Uncovering networks from genome-wide association studies via circular genomic permutation. G3-GENES GENOMES GENETICS 2012; 2:1067-75. [PMID: 22973544 PMCID: PMC3429921 DOI: 10.1534/g3.112.002618] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 06/29/2012] [Indexed: 11/24/2022]
Abstract
Genome-wide association studies (GWAS) aim to detect single nucleotide polymorphisms (SNP) associated with trait variation. However, due to the large number of tests, standard analysis techniques impose highly stringent significance thresholds, leaving potentially associated SNPs undetected, and much of the trait genetic variation unexplained. Pathway- and network-based methodologies applied to GWAS aim to detect associations missed by standard single-marker approaches. The complex and non-random architecture of the genome makes it a challenge to derive an appropriate testing framework for such methodologies. We developed a rapid and simple permutation approach that uses GWAS SNP association results to establish the significance of pathway associations while accounting for the linkage disequilibrium structure of SNPs and the clustering of functionally related elements in the genome. All SNPs used in the GWAS are placed in a “circular genome” according to their location. Then the complete set of SNP association P values are permuted by rotation with respect to the genomic locations of the SNPs. Once these “simulated” P values are assigned, the joint gene P values are calculated using Fisher’s combination test, and the association of pathways is tested using the hypergeometric test. The circular genomic permutation approach was applied to a human genome-wide association dataset. The data consists of 719 individuals from the ORCADES study genotyped for ∼300,000 SNPs and measured for 51 traits ranging from physical to biochemical measurements. KEGG pathways (n = 225) were used as the sets of pathways to be tested. Our results demonstrate that the circular genomic permutations provide robust association P values. The non-permuted hypergeometric analysis generates ∼1400 pathway-trait combination results with an association P value more significant than P ≤ 0.05, whereas applying circular genomic permutation reduces the number of significant results to a more credible 40% of that value. The circular permutation software (“genomicper”) is available as an R package at http://cran.r-project.org/.
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739
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Luciano M, Huffman JE, Arias-Vásquez A, Vinkhuyzen AAE, Middeldorp CM, Giegling I, Payton A, Davies G, Zgaga L, Janzing J, Ke X, Galesloot T, Hartmann AM, Ollier W, Tenesa A, Hayward C, Verhagen M, Montgomery GW, Hottenga JJ, Konte B, Starr JM, Vitart V, Vos PE, Madden PAF, Willemsen G, Konnerth H, Horan MA, Porteous DJ, Campbell H, Vermeulen SH, Heath AC, Wright A, Polasek O, Kovacevic SB, Hastie ND, Franke B, Boomsma DI, Martin NG, Rujescu D, Wilson JF, Buitelaar J, Pendleton N, Rudan I, Deary IJ. Genome-wide association uncovers shared genetic effects among personality traits and mood states. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:684-95. [PMID: 22628180 PMCID: PMC3795298 DOI: 10.1002/ajmg.b.32072] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2012] [Accepted: 05/03/2012] [Indexed: 12/27/2022]
Abstract
Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (~2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546-1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta-analysis of the cohort results was performed, with follow-up associations of the top SNPs and genes investigated in independent cohorts (n = 527-6,032). Suggestive association (P = 8 × 10(-8)) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10(-6)) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene-based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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740
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Purfield DC, Berry DP, McParland S, Bradley DG. Runs of homozygosity and population history in cattle. BMC Genet 2012; 13:70. [PMID: 22888858 PMCID: PMC3502433 DOI: 10.1186/1471-2156-13-70] [Citation(s) in RCA: 366] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Accepted: 08/03/2012] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that are present in an individual due to parents transmitting identical haplotypes to their offspring. The extent and frequency of ROHs may inform on the ancestry of an individual and its population. Here we use high density (n = 777,962) bi-allelic SNPs in a range of cattle breed samples to correlate ROH with the pedigree-based inbreeding coefficients and to validate subsequent analyses using 54,001 SNP genotypes. This study provides a first testing of the inference drawn from ROH through comparison with estimates of inbreeding from calculations based on the detailed pedigree data available for several breeds. RESULTS All animals genotyped on the HD panel displayed at least one ROH that was between 1-5 Mb in length with certain regions of the genome more likely to be involved in a ROH than others. Strong correlations (r = 0.75, p < 0.0001) existed between the pedigree-based inbreeding coefficient and a statistic based on sum of ROH of length > 0.5 KB and suggests that in the absence of an animal's pedigree data, the extent of a genome under ROH may be used to infer aspects of recent population history even from relatively few samples. CONCLUSIONS Our findings suggest that ROH are frequent across all breeds but differing patterns of ROH length and burden illustrate variations in breed origins and recent management.
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Affiliation(s)
- Deirdre C Purfield
- Smurfit Institute of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland
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741
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Genomic patterns of homozygosity in worldwide human populations. Am J Hum Genet 2012; 91:275-92. [PMID: 22883143 DOI: 10.1016/j.ajhg.2012.06.014] [Citation(s) in RCA: 355] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2012] [Revised: 05/09/2012] [Accepted: 06/25/2012] [Indexed: 12/20/2022] Open
Abstract
Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes-short, intermediate, and long-with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases.
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742
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Regions of homozygosity identified by SNP microarray analysis aid in the diagnosis of autosomal recessive disease and incidentally detect parental blood relationships. Genet Med 2012; 15:70-8. [PMID: 22858719 DOI: 10.1038/gim.2012.94] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
PURPOSE The purpose of this study was to document the ability of single-nucleotide polymorphism microarray to identify copy-neutral regions of homozygosity, demonstrate clinical utility of regions of homozygosity, and discuss ethical/legal implications when regions of homozygosity are associated with a parental blood relationship. METHODS Study data were compiled from consecutive samples sent to our clinical laboratory over a 3-year period. A cytogenetics database identified patients with at least two regions of homozygosity >10 Mb on two separate chromosomes. A chart review was conducted on patients who met the criteria. RESULTS Of 3,217 single-nucleotide polymorphism microarrays, 59 (1.8%) patients met inclusion criteria. The percentage of homozygosity ranged from 0.9 to 30.1%, indicating parental relationships from distant to first-degree relatives. First-degree kinship was suspected in the parents of at least 11 patients with regions of homozygosity covering >21.3% of their autosome. In four patients from two families, homozygosity mapping discovered a candidate gene that was sequenced to identify a clinically significant mutation. CONCLUSION This study demonstrates clinical utility in the identification of regions of homozygosity, as these regions may aid in diagnosis of the patient. This study establishes the need for careful reporting, thorough pretest counseling, and careful electronic documentation, as microarray has the capability of detecting previously unknown/unreported relationships.
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743
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Abstract
Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance. Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.
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744
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Grote L, Myers M, Lovell A, Saal H, Lipscomb Sund K. Variability in laboratory reporting practices for regions of homozygosity indicating parental relatedness as identified by SNP microarray testing. Genet Med 2012; 14:971-6. [DOI: 10.1038/gim.2012.83] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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745
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Robberecht C, Pexsters A, Deprest J, Fryns JP, D'Hooghe T, Vermeesch JR. Cytogenetic and morphological analysis of early products of conception following hystero-embryoscopy from couples with recurrent pregnancy loss. Prenat Diagn 2012; 32:933-42. [PMID: 22763612 DOI: 10.1002/pd.3936] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Revised: 05/11/2012] [Accepted: 06/08/2012] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Our knowledge about miscarriages mainly concerns pregnancies of at least 8 weeks' gestation. Information about the morphology and the genetic determinants of early aborted embryos remains limited. In addition, it is known that aneuploidies account for less than half of recurrent spontaneous abortions. We hypothesized that (recurrent) early pregnancy losses might have other genetic causes. METHOD Products of conception from 51 couples with at least one previous miscarriage were collected by hystero-embryoscopy. The extracted DNA was analyzed by low resolution array comparative genomic hybridization and high resolution single nucleotide polymorphism arrays to detect aneuploidies, polyploidies, submicroscopic copy number variants or copy neutral loss of heterozygosity. RESULTS Chromosomal aberrations were identified in 65.6% (21/32) of miscarriages and in 89% (8/9) of anembryonic cases. Interestingly, 4/11 chromosomally euploid embryos contained regions of loss of heterozygosity >5 Mb, suggesting the miscarriages might be due to an underlying lethal recessive disease. CONCLUSION Hystero-embryoscopic biopsy followed by array comparative genomic hybridization is a valuable diagnostic tool for early and recurrent miscarriages. Genome-wide high resolution single nucleotide polymorphism microarray analysis of a larger group of miscarriages could provide more insight into the genetic causes of recurrent spontaneous abortion.
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746
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Small effective population size and genetic homogeneity in the Val Borbera isolate. Eur J Hum Genet 2012; 21:89-94. [PMID: 22713810 DOI: 10.1038/ejhg.2012.113] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Population isolates are a valuable resource for medical genetics because of their reduced genetic, phenotypic and environmental heterogeneity. Further, extended linkage disequilibrium (LD) allows accurate haplotyping and imputation. In this study, we use nuclear and mitochondrial DNA data to determine to what extent the geographically isolated population of the Val Borbera valley also presents features of genetic isolation. We performed a comparative analysis of population structure and estimated effective population size exploiting LD data. We also evaluated haplotype sharing through the analysis of segments of autozygosity. Our findings reveal that the valley has features characteristic of a genetic isolate, including reduced genetic heterogeneity and reduced effective population size. We show that this population has been subject to prolonged genetic drift and thus we expect many variants that are rare in the general population to reach significant frequency values in the valley, making this population suitable for the identification of rare variants underlying complex traits.
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747
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Naidoo N, Pawitan Y, Soong R, Cooper DN, Ku CS. Human genetics and genomics a decade after the release of the draft sequence of the human genome. Hum Genomics 2012; 5:577-622. [PMID: 22155605 PMCID: PMC3525251 DOI: 10.1186/1479-7364-5-6-577] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade.
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Affiliation(s)
- Nasheen Naidoo
- Centre for Molecular Epidemiology, Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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748
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Ameur A, Enroth S, Johansson Å, Zaboli G, Igl W, Johansson A, Rivas M, Daly M, Schmitz G, Hicks A, Meitinger T, Feuk L, van Duijn C, Oostra B, Pramstaller P, Rudan I, Wright A, Wilson J, Campbell H, Gyllensten U. Genetic adaptation of fatty-acid metabolism: a human-specific haplotype increasing the biosynthesis of long-chain omega-3 and omega-6 fatty acids. Am J Hum Genet 2012; 90:809-20. [PMID: 22503634 DOI: 10.1016/j.ajhg.2012.03.014] [Citation(s) in RCA: 171] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2011] [Revised: 02/03/2012] [Accepted: 03/15/2012] [Indexed: 10/28/2022] Open
Abstract
Omega-3 and omega-6 long-chain polyunsaturated fatty acids (LC-PUFAs) are essential for the development and function of the human brain. They can be obtained directly from food, e.g., fish, or synthesized from precursor molecules found in vegetable oils. To determine the importance of genetic variability to fatty-acid biosynthesis, we studied FADS1 and FADS2, which encode rate-limiting enzymes for fatty-acid conversion. We performed genome-wide genotyping (n = 5,652 individuals) and targeted resequencing (n = 960 individuals) of the FADS region in five European population cohorts. We also analyzed available genomic data from human populations, archaic hominins, and more distant primates. Our results show that present-day humans have two common FADS haplotypes-defined by 28 closely linked SNPs across 38.9 kb-that differ dramatically in their ability to generate LC-PUFAs. No independent effects on FADS activity were seen for rare SNPs detected by targeted resequencing. The more efficient, evolutionarily derived haplotype appeared after the lineage split leading to modern humans and Neanderthals and shows evidence of positive selection. This human-specific haplotype increases the efficiency of synthesizing essential long-chain fatty acids from precursors and thereby might have provided an advantage in environments with limited access to dietary LC-PUFAs. In the modern world, this haplotype has been associated with lifestyle-related diseases, such as coronary artery disease.
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749
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A genome-wide homozygosity association study identifies runs of homozygosity associated with rheumatoid arthritis in the human major histocompatibility complex. PLoS One 2012; 7:e34840. [PMID: 22536334 PMCID: PMC3335047 DOI: 10.1371/journal.pone.0034840] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2011] [Accepted: 03/08/2012] [Indexed: 12/02/2022] Open
Abstract
Rheumatoid arthritis (RA) is a chronic inflammatory disorder with a polygenic mode of inheritance. This study examined the hypothesis that runs of homozygosity (ROHs) play a recessive-acting role in the underlying RA genetic mechanism and identified RA-associated ROHs. Ours is the first genome-wide homozygosity association study for RA and characterized the ROH patterns associated with RA in the genomes of 2,000 RA patients and 3,000 normal controls of the Wellcome Trust Case Control Consortium. Genome scans consistently pinpointed two regions within the human major histocompatibility complex region containing RA-associated ROHs. The first region is from 32,451,664 bp to 32,846,093 bp (−log10(p)>22.6591). RA-susceptibility genes, such as HLA-DRB1, are contained in this region. The second region ranges from 32,933,485 bp to 33,585,118 bp (−log10(p)>8.3644) and contains other HLA-DPA1 and HLA-DPB1 genes. These two regions are physically close but are located in different blocks of linkage disequilibrium, and ∼40% of the RA patients' genomes carry these ROHs in the two regions. By analyzing homozygote intensities, an ROH that is anchored by the single nucleotide polymorphism rs2027852 and flanked by HLA-DRB6 and HLA-DRB1 was found associated with increased risk for RA. The presence of this risky ROH provides a 62% accuracy to predict RA disease status. An independent genomic dataset from 868 RA patients and 1,194 control subjects of the North American Rheumatoid Arthritis Consortium successfully validated the results obtained using the Wellcome Trust Case Control Consortium data. In conclusion, this genome-wide homozygosity association study provides an alternative to allelic association mapping for the identification of recessive variants responsible for RA. The identified RA-associated ROHs uncover recessive components and missing heritability associated with RA and other autoimmune diseases.
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750
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Edvardson S, Cinnamon Y, Jalas C, Shaag A, Maayan C, Axelrod FB, Elpeleg O. Hereditary sensory autonomic neuropathy caused by a mutation in dystonin. Ann Neurol 2012; 71:569-72. [DOI: 10.1002/ana.23524] [Citation(s) in RCA: 101] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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