78 research outputs found

    Nucleosome DNA sequence structure of isochores

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    <p>Abstract</p> <p>Background</p> <p>Significant differences in G+C content between different isochore types suggest that the nucleosome positioning patterns in DNA of the isochores should be different as well.</p> <p>Results</p> <p>Extraction of the patterns from the isochore DNA sequences by Shannon N-gram extension reveals that while the general motif YRRRRRYYYYYR is characteristic for all isochore types, the dominant positioning patterns of the isochores vary between TAAAAATTTTTA and CGGGGGCCCCCG due to the large differences in G+C composition. This is observed in human, mouse and chicken isochores, demonstrating that the variations of the positioning patterns are largely G+C dependent rather than species-specific. The species-specificity of nucleosome positioning patterns is revealed by dinucleotide periodicity analyses in isochore sequences. While human sequences are showing CG periodicity, chicken isochores display AG (CT) periodicity. Mouse isochores show very weak CG periodicity only.</p> <p>Conclusions</p> <p>Nucleosome positioning pattern as revealed by Shannon N-gram extension is strongly dependent on G+C content and different in different isochores. Species-specificity of the pattern is subtle. It is reflected in the choice of preferentially periodical dinucleotides.</p

    Additive genetic variation in schizophrenia risk is shared by populations of African and European descent

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    Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRβ1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRβ1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPβ1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC

    Worldwide Distribution of the MYH9 Kidney Disease Susceptibility Alleles and Haplotypes: Evidence of Historical Selection in Africa

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    MYH9 was recently identified as renal susceptibility gene (OR 3–8, p<10−8) for major forms of kidney disease disproportionately affecting individuals of African descent. The risk haplotype (E-1) occurs at much higher frequencies in African Americans (≥60%) than in European Americans (<4%), revealing a genetic basis for a major health disparity. The population distributions of MYH9 risk alleles and the E-1 risk haplotype and the demographic and selective forces acting on the MYH9 region are not well explored. We reconstructed MYH9 haplotypes from 4 tagging single nucleotide polymorphisms (SNPs) spanning introns 12–23 using available data from HapMap Phase II, and by genotyping 938 DNAs from the Human Genome Diversity Panel (HGDP). The E-1 risk haplotype followed a cline, being most frequent within sub-Saharan African populations (range 50–80%), less frequent in populations from the Middle East (9–27%) and Europe (0–9%), and rare or absent in Asia, the Americas, and Oceania. The fixation indexes (FST) for pairwise comparisons between the risk haplotypes for continental populations were calculated for MYH9 haplotypes; FST ranged from 0.27–0.40 for Africa compared to other continental populations, possibly due to selection. Uniquely in Africa, the Yoruba population showed high frequency extended haplotype length around the core risk allele (C) compared to the alternative allele (T) at the same locus (rs4821481, iHs = 2.67), as well as high population differentiation (FST(CEU vs. YRI) = 0.51) in HapMap Phase II data, also observable only in the Yoruba population from HGDP (FST = 0.49), pointing to an instance of recent selection in the genomic region. The population-specific divergence in MYH9 risk allele frequencies among the world's populations may prove important in risk assessment and public health policies to mitigate the burden of kidney disease in vulnerable populations

    Ancestral Components of Admixed Genomes in a Mexican Cohort

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    For most of the world, human genome structure at a population level is shaped by interplay between ancient geographic isolation and more recent demographic shifts, factors that are captured by the concepts of biogeographic ancestry and admixture, respectively. The ancestry of non-admixed individuals can often be traced to a specific population in a precise region, but current approaches for studying admixed individuals generally yield coarse information in which genome ancestry proportions are identified according to continent of origin. Here we introduce a new analytic strategy for this problem that allows fine-grained characterization of admixed individuals with respect to both geographic and genomic coordinates. Ancestry segments from different continents, identified with a probabilistic model, are used to construct and study “virtual genomes” of admixed individuals. We apply this approach to a cohort of 492 parent–offspring trios from Mexico City. The relative contributions from the three continental-level ancestral populations—Africa, Europe, and America—vary substantially between individuals, and the distribution of haplotype block length suggests an admixing time of 10–15 generations. The European and Indigenous American virtual genomes of each Mexican individual can be traced to precise regions within each continent, and they reveal a gradient of Amerindian ancestry between indigenous people of southwestern Mexico and Mayans of the Yucatan Peninsula. This contrasts sharply with the African roots of African Americans, which have been characterized by a uniform mixing of multiple West African populations. We also use the virtual European and Indigenous American genomes to search for the signatures of selection in the ancestral populations, and we identify previously known targets of selection in other populations, as well as new candidate loci. The ability to infer precise ancestral components of admixed genomes will facilitate studies of disease-related phenotypes and will allow new insight into the adaptive and demographic history of indigenous people

    Genomic Ancestry of North Africans Supports Back-to-Africa Migrations

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    North African populations are distinct from sub-Saharan Africans based on cultural, linguistic, and phenotypic attributes; however, the time and the extent of genetic divergence between populations north and south of the Sahara remain poorly understood. Here, we interrogate the multilayered history of North Africa by characterizing the effect of hypothesized migrations from the Near East, Europe, and sub-Saharan Africa on current genetic diversity. We present dense, genome-wide SNP genotyping array data (730,000 sites) from seven North African populations, spanning from Egypt to Morocco, and one Spanish population. We identify a gradient of likely autochthonous Maghrebi ancestry that increases from east to west across northern Africa; this ancestry is likely derived from “back-to-Africa” gene flow more than 12,000 years ago (ya), prior to the Holocene. The indigenous North African ancestry is more frequent in populations with historical Berber ethnicity. In most North African populations we also see substantial shared ancestry with the Near East, and to a lesser extent sub-Saharan Africa and Europe. To estimate the time of migration from sub-Saharan populations into North Africa, we implement a maximum likelihood dating method based on the distribution of migrant tracts. In order to first identify migrant tracts, we assign local ancestry to haplotypes using a novel, principal component-based analysis of three ancestral populations. We estimate that a migration of western African origin into Morocco began about 40 generations ago (approximately 1,200 ya); a migration of individuals with Nilotic ancestry into Egypt occurred about 25 generations ago (approximately 750 ya). Our genomic data reveal an extraordinarily complex history of migrations, involving at least five ancestral populations, into North Africa

    Differential endothelial cell gene expression by African Americans versus Caucasian Americans: a possible contribution to health disparity in vascular disease and cancer

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    <p>Abstract</p> <p>Background</p> <p>Health disparities and the high prevalence of cardiovascular disease continue to be perplexing worldwide health challenges. This study addresses the possibility that genetic differences affecting the biology of the vascular endothelium could be a factor contributing to the increased burden of cardiovascular disease and cancer among African Americans (AA) compared to Caucasian Americans (CA).</p> <p>Methods</p> <p>From self-identified, healthy, 20 to 29-year-old AA (n = 21) and CA (n = 17), we established cultures of blood outgrowth endothelial cells (BOEC) and applied microarray profiling. BOEC have never been exposed to <it>in vivo </it>influences, and their gene expression reflects culture conditions (meticulously controlled) and donor genetics. Significance Analysis of Microarray identified differential expression of single genes. Gene Set Enrichment Analysis examined expression of pre-determined gene sets that survey nine biological systems relevant to endothelial biology.</p> <p>Results</p> <p>At the highly stringent threshold of False Discovery Rate (FDR) = 0, 31 single genes were differentially expressed in AA. <it>PSPH </it>exhibited the greatest fold-change (AA > CA), but this was entirely accounted for by a homolog (<it>PSPHL</it>) hidden within the <it>PSPH </it>probe set. Among other significantly different genes were: for AA > CA, <it>SOS1, AMFR, FGFR3; and for AA < CA, ARVCF, BIN3, EIF4B. </it>Many more (221 transcripts for 204 genes) were differentially expressed at the less stringent threshold of FDR <.05. Using the biological systems approach, we identified shear response biology as being significantly different for AA versus CA, showing an apparent tonic increase of expression (AA > CA) for 46/157 genes within that system.</p> <p>Conclusions</p> <p>Many of the genes implicated here have substantial roles in endothelial biology. Shear stress response, a critical regulator of endothelial function and vascular homeostasis, may be different between AA and CA. These results potentially have direct implications for the role of endothelial cells in vascular disease (hypertension, stroke) and cancer (via angiogenesis). Also, they are consistent with our over-arching hypothesis that genetic influences stemming from ancestral continent-of-origin could impact upon endothelial cell biology and thereby contribute to disparity of vascular-related disease burden among AA. The method used here could be productively employed to bridge the gap between information from structural genomics (for example, disease association) and cell function and pathophysiology.</p

    Dissecting the Within-Africa Ancestry of Populations of African Descent in the Americas

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    The ancestry of African-descended Americans is known to be drawn from three distinct populations: African, European, and Native American. While many studies consider this continental admixture, few account for the genetically distinct sources of ancestry within Africa--the continent with the highest genetic variation. Here, we dissect the within-Africa genetic ancestry of various populations of the Americas self-identified as having primarily African ancestry using uniparentally inherited mitochondrial DNA.We first confirmed that our results obtained using uniparentally-derived group admixture estimates are correlated with the average autosomal-derived individual admixture estimates (hence are relevant to genomic ancestry) by assessing continental admixture using both types of markers (mtDNA and Y-chromosome vs. ancestry informative markers). We then focused on the within-Africa maternal ancestry, mining our comprehensive database of published mtDNA variation (∼5800 individuals from 143 African populations) that helped us thoroughly dissect the African mtDNA pool. Using this well-defined African mtDNA variation, we quantified the relative contributions of maternal genetic ancestry from multiple W/WC/SW/SE (West to South East) African populations to the different pools of today's African-descended Americans of North and South America and the Caribbean.Our analysis revealed that both continental admixture and within-Africa admixture may be critical to achieving an adequate understanding of the ancestry of African-descended Americans. While continental ancestry reflects gender-specific admixture processes influenced by different socio-historical practices in the Americas, the within-Africa maternal ancestry reflects the diverse colonial histories of the slave trade. We have confirmed that there is a genetic thread connecting Africa and the Americas, where each colonial system supplied their colonies in the Americas with slaves from African colonies they controlled or that were available for them at the time. This historical connection is reflected in different relative contributions from populations of W/WC/SW/SE Africa to geographically distinct Africa-derived populations of the Americas, adding to the complexity of genomic ancestry in groups ostensibly united by the same demographic label

    Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

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    A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

    A global reference for human genetic variation

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    The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute
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