Institution
Government of Victoria
Government•Melbourne, Victoria, Australia•
About: Government of Victoria is a government organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Health care. The organization has 118 authors who have published 94 publications receiving 8423 citations.
Topics: Population, Health care, Genome-wide association study, Public health, Single-nucleotide polymorphism
Papers published on a yearly basis
Papers
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TL;DR: This article identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height, and all common variants together captured 60% of heritability.
Abstract: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
1,872 citations
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TL;DR: It is shown that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait, and indicates that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
1,768 citations
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QIMR Berghofer Medical Research Institute1, National Institutes of Health2, Harvard University3, University of Texas Health Science Center at Houston4, Mayo Clinic5, Statens Serum Institut6, University of Pittsburgh7, Northwestern University8, University of Edinburgh9, University of Minnesota10, Université de Montréal11, Washington University in St. Louis12, Johns Hopkins University13, University of Washington14, Government of Victoria15, University of Melbourne16
TL;DR: The results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.
Abstract: We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ∼45%, ∼17%, ∼25% and ∼21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ∼0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.
912 citations
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Iris M. Heid1, Anne U. Jackson2, Joshua C. Randall3, Tthomas W. Winkler1 +352 more•Institutions (90)
TL;DR: A meta-analysis of genome-wide association studies for WHR adjusted for body mass index provides evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
Abstract: Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
869 citations
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Baylor College of Medicine1, University of Missouri2, United States Department of Agriculture3, Commonwealth Scientific and Industrial Research Organisation4, University of New England (United States)5, Texas A&M University6, Norwegian University of Life Sciences7, George Mason University8, AgResearch9, Catholic University of the Sacred Heart10, International Atomic Energy Agency11, Empresa Brasileira de Pesquisa Agropecuária12, Sao Paulo State University13, International Livestock Research Institute14, Parco Tecnologico Padano15, University of Edinburgh16, Ethiopian Institute of Agricultural Research17, Livestock Improvement Corporation18, Cornell University19, University of Alberta20, Tuscia University21, Wellcome Trust Sanger Institute22, Government of Victoria23, University of Melbourne24, Trinity College, Dublin25, Simon Fraser University26
TL;DR: Data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation.
Abstract: The imprints of domestication and breed development on the genomes of livestock likely differ from those of companion animals. A deep draft sequence assembly of shotgun reads from a single Hereford female and comparative sequences sampled from six additional breeds were used to develop probes to interrogate 37,470 single-nucleotide polymorphisms (SNPs) in 497 cattle from 19 geographically and biologically diverse breeds. These data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation. Domestication and artificial selection appear to have left detectable signatures of selection within the cattle genome, yet the current levels of diversity within breeds are at least as great as exists within humans.
769 citations
Authors
Showing all 118 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jacqueline Batley | 119 | 1212 | 68752 |
Michael E. Goddard | 106 | 424 | 67681 |
Lu Qi | 94 | 566 | 54866 |
P. Eline Slagboom | 93 | 389 | 37286 |
David Edwards | 89 | 703 | 35570 |
Ben J. Hayes | 80 | 346 | 27872 |
Tim D. Spector | 80 | 1570 | 182188 |
John W. Forster | 48 | 171 | 6703 |
German Spangenberg | 47 | 340 | 7906 |
Markus Perola | 46 | 573 | 78670 |
Noel O. I. Cogan | 36 | 144 | 3911 |
Hans D. Daetwyler | 36 | 137 | 6511 |
Alexandra Martiniuk | 34 | 138 | 4126 |
Joe Panozzo | 33 | 107 | 3528 |
Terence I. Walker | 33 | 75 | 3466 |