titoli, abstracts, parole chiave >>>
The EQTLs Catalog and LinDA browser: a platform for determining the effects on transcription of GWAS variants

Onano, Stefano (2019) The EQTLs Catalog and LinDA browser: a platform for determining the effects on transcription of GWAS variants. Doctoral Thesis.

[img]Full text disponibile come PDF Richiede visualizzatore di PDF come GSview, Xpdf o Adobe Acrobat Reader
Restricted to until 15 July 2020.

1621Kb

Abstract

The expression Quantitative Traits Locus (eQTL) is a genetic polymorphism associated with changes in gene expression levels. They have been successfully used to pioritize the target genes of the variants associated with complex traits and diseases (GWAS variants). Existing eQTLs databases collect only a small portion of the available datasets. We planned to build the largest publically available catalog of eQTLs, coupled with a browser, to optimize and simplify their interrogation. We collected and manually curated 51 eQTL public studies ranging from 2007 to date, corresponding to more than 94 tissues/cells/conditions and 15 human populations for a total of 275,727 cis-eQTLs and 33,241 genes with at least one cis-eQTL (cis-eGenes). We found that for 93% of the known protein-coding genes were eGenes, 22% of them intersecting (r2≥0.8) with the NHGRI-EBI GWAS Catalog and 26% of whom considered as druggable. Furthermore, for those GWAS variants for which at least an eGene was known, we found that the NHGRI-EBI GWAS Catalog proposed at least one of the same genes as candidate target only for the 70% of the times. Our eQTL-Catalog can be used as a reference to measure the degree of novelty for future eQTLs studies; it is provided within a platform with the web-browser LinDA (http://linda.irgb.cnr.it) implemented with other types of quantitative traits (i.e. epigenetic, proteomic) to better dissect the pleiotropy of the GWAS variants.

Item Type:Doctoral Thesis
ID Code:11971
Contributors:Cucca, Francesco and Pala, Mauro
Publisher:Universita' degli studi di Sassari
Uncontrolled Keywords:EQTL, GWAS, genetics, transcriptomics, database
Subjects:Area 06 - Scienze mediche > MED/03 Genetica medica
Divisions:001 Università di Sassari > 01-a Nuovi Dipartimenti dal 2012 > Scienze Biomediche
Cicli, scuole e corsi:Ciclo 31 > Scienze biomediche > Genetica medica
Deposited On:19 Apr 2019 13:06

I documenti depositati in UnissResearch sono protetti dalle leggi che regolano il diritto d'autore

Repository Staff Only: item control page