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Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs.
van der Wijst, Monique G P; Brugge, Harm; de Vries, Dylan H; Deelen, Patrick; Swertz, Morris A; Franke, Lude.
Afiliação
  • van der Wijst MGP; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • Brugge H; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • de Vries DH; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • Deelen P; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • Swertz MA; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • Franke L; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. lude@ludesign.nl.
Nat Genet ; 50(4): 493-497, 2018 04.
Article em En | MEDLINE | ID: mdl-29610479
ABSTRACT
Genome-wide association studies have identified thousands of genetic variants that are associated with disease 1 . Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large 2 and celltype-specific3-5. To identify these celltype-specific eQTLs using an unbiased approach, we used single-cell RNA sequencing to generate expression profiles of ~25,000 peripheral blood mononuclear cells from 45 donors. We identified previously reported cis-eQTLs, but also identified new celltype-specific cis-eQTLs. Finally, we generated personalized co-expression networks and identified genetic variants that significantly alter co-expression relationships (which we termed 'co-expression QTLs'). Single-cell eQTL analysis thus allows for the identification of genetic variants that impact regulatory networks.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Sequência de RNA / Locos de Características Quantitativas / Análise de Célula Única Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nat Genet Assunto da revista: GENETICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Sequência de RNA / Locos de Características Quantitativas / Análise de Célula Única Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nat Genet Assunto da revista: GENETICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Holanda