RESUMO
Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
Assuntos
Antropometria , Genoma Humano , Estudo de Associação Genômica Ampla , Locos de Características Quantitativas/genética , Análise de Sequência de DNA/métodos , Estatura/genética , Estudos de Coortes , Metilação de DNA/genética , Bases de Dados Genéticas , Feminino , Variação Genética , Humanos , Lipodistrofia/genética , Masculino , Metanálise como Assunto , Obesidade/genética , Mapeamento Físico do Cromossomo , Caracteres Sexuais , Síndrome , Reino UnidoRESUMO
During the 2014-15 influenza season, 13/168 respiratory samples from students with influenza-like illness (ILI) at a college in New York, USA, were positive for human adenovirus (HAdV); 4/13 samples were positive for HAdV-B14p1. During influenza season, HAdV should be included in the differential diagnostic panel used to determine the etiology of ILI.
Assuntos
Infecções por Adenovirus Humanos/epidemiologia , Infecções por Adenovirus Humanos/virologia , Adenovírus Humanos/classificação , Adenovírus Humanos/genética , Infecções Respiratórias/epidemiologia , Infecções Respiratórias/virologia , Infecções por Adenovirus Humanos/diagnóstico , Infecções por Adenovirus Humanos/história , Diagnóstico Diferencial , Variação Genética , Genoma Viral , História do Século XXI , Humanos , Influenza Humana/diagnóstico , New York/epidemiologia , Filogenia , Infecções Respiratórias/diagnóstico , Infecções Respiratórias/história , Análise de Sequência de DNA , Avaliação de SintomasRESUMO
DA (D-blood group of Palm and Agouti, also known as Dark Agouti) and F344 (Fischer) are two inbred rat strains with differences in several phenotypes, including susceptibility to autoimmune disease models and inflammatory responses. While these strains have been extensively studied, little information is available about the DA and F344 genomes, as only the Brown Norway (BN) and spontaneously hypertensive rat strains have been sequenced to date. Here we report the sequencing of the DA and F344 genomes using next-generation Illumina paired-end read technology and the first de novo assembly of a rat genome. DA and F344 were sequenced with an average depth of 32-fold, covered 98.9% of the BN reference genome, and included 97.97% of known rat ESTs. New sequences could be assigned to 59 million positions with previously unknown data in the BN reference genome. Differences between DA, F344, and BN included 19 million positions in novel scaffolds, 4.09 million single nucleotide polymorphisms (SNPs) (including 1.37 million new SNPs), 458,224 short insertions and deletions, and 58,174 structural variants. Genetic differences between DA, F344, and BN, including high-impact SNPs and short insertions and deletions affecting >2500 genes, are likely to account for most of the phenotypic variation between these strains. The new DA and F344 genome sequencing data should facilitate gene discovery efforts in rat models of human disease.