eQTL Mapping Using Transcription Factor Affinity.


Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2020
Historique:
entrez: 19 12 2019
pubmed: 19 12 2019
medline: 31 12 2020
Statut: ppublish

Résumé

In the last decades, thousands of common genetic variants have been associated with human diseases by genome-wide association studies (GWAS). However, the functional interpretation of GWAS hits is usually nontrivial, especially because most of them lay outside the coding genome. These noncoding variants presumably exert their effect by altering gene expression levels; therefore, expression quantitative trait loci (eQTL) mapping analyses represent an important step in understanding their functional relevance and identifying the target genes. Here we describe an alternative strategy for the detection of eQTL that takes into account the combined effect of genetic variants within regulatory regions and leverages the idea that changes in gene expression often are the consequence of the alteration of transcription factor (TF) binding.

Identifiants

pubmed: 31849006
doi: 10.1007/978-1-0716-0026-9_3
doi:

Substances chimiques

Transcription Factors 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

39-49

Auteurs

Elisa Mariella (E)

Department of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center, University of Turin, Turin, Italy.

Elena Grassi (E)

Department of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center, University of Turin, Turin, Italy.

Paolo Provero (P)

Department of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center, University of Turin, Turin, Italy. paolo.provero@unito.it.
Center for Translational Genomics and Bioinformatics, San Raffaele Scientific Institute IRCCS, Milan, Italy. paolo.provero@unito.it.

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Classifications MeSH