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The anatomical distribution of genetic associations.
Wells, Alan; Kopp, Nathan; Xu, Xiaoxiao; O'Brien, David R; Yang, Wei; Nehorai, Arye; Adair-Kirk, Tracy L; Kopan, Raphael; Dougherty, J D.
Afiliação
  • Wells A; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Kopp N; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Xu X; The Preston M. Green Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA.
  • O'Brien DR; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Yang W; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Nehorai A; The Preston M. Green Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA.
  • Adair-Kirk TL; Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Kopan R; Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
  • Dougherty JD; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA jdougherty@genetics.wustl.edu.
Nucleic Acids Res ; 43(22): 10804-20, 2015 Dec 15.
Article em En | MEDLINE | ID: mdl-26586807
ABSTRACT
Deeper understanding of the anatomical intermediaries for disease and other complex genetic traits is essential to understanding mechanisms and developing new interventions. Existing ontology tools provide functional, curated annotations for many genes and can be used to develop mechanistic hypotheses; yet information about the spatial expression of genes may be equally useful in interpreting results and forming novel hypotheses for a trait. Therefore, we developed an approach for statistically testing the relationship between gene expression across the body and sets of candidate genes from across the genome. We validated this tool and tested its utility on three applications. First, we show that the expression of genes in associated loci from GWA studies implicates specific tissues for 57 out of 98 traits. Second, we tested the ability of the tool to identify novel relationships between gene expression and phenotypes. Specifically, we experimentally confirmed an underappreciated prediction highlighted by our tool that white blood cell count--a quantitative trait of the immune system--is genetically modulated by genes expressed in the skin. Finally, using gene lists derived from exome sequencing data, we show that human genes under selective constraint are disproportionately expressed in nervous system tissues.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Estudo de Associação Genômica Ampla Tipo de estudo: Risk_factors_studies Limite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Estudo de Associação Genômica Ampla Tipo de estudo: Risk_factors_studies Limite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos