eprintid: 10088808
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/08/88/08
datestamp: 2020-01-13 11:37:27
lastmod: 2021-12-27 01:44:34
status_changed: 2020-01-13 11:37:27
type: article
metadata_visibility: show
creators_name: Sng, LMF
creators_name: Thomson, PC
creators_name: Trabzuni, D
title: Genome-wide human brain eQTLs: In-depth analysis and insights using the UKBEC dataset
ispublished: pub
divisions: UCL
divisions: B02
divisions: C07
divisions: D07
divisions: F86
keywords: Gene expression, Genome-wide association studies, Neuroscience
note: © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
abstract: Understanding the complexity of the human brain transcriptome architecture is one of the most important human genetics study areas. Previous studies have applied expression quantitative trait loci (eQTL) analysis at the genome-wide level of the brain to understand the underlying mechanisms relating to neurodegenerative diseases, primarily at the transcript level. To increase the resolution of our understanding, the current study investigates multi/single-region, transcript/exon-level and cis versus trans-acting eQTL, across 10 regions of the human brain. Some of the key findings of this study are: (i) only a relatively small proportion of eQTLs will be detected, where the sensitivity is under 5%; (ii) when an eQTL is acting in multiple regions (MR-eQTL), it tends to have very similar effects on gene expression in each of these regions, as well as being cis-acting; (iii) trans-acting eQTLs tend to have larger effects on expression compared to cis-acting eQTLs and tend to be specific to a single region (SR-eQTL) of the brain; (iv) the cerebellum has a very large number of eQTLs that function exclusively in this region, compared with other regions of the brain; (v) importantly, an interactive visualisation tool (Shiny app) was developed to visualise the MR/SR-eQTL at transcript and exon levels.
date: 2019
date_type: published
official_url: https://doi.org/10.1038/s41598-019-55590-0
oa_status: green
full_text_type: pub
pmcid: PMC6915738
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1733369
doi: 10.1038/s41598-019-55590-0
pii: 10.1038/s41598-019-55590-0
lyricists_name: Trabzuni, Daniah
lyricists_id: DTRAB86
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
publication: Scientific Reports
volume: 9
number: 1
article_number: 19201
event_location: England
citation:        Sng, LMF;    Thomson, PC;    Trabzuni, D;      (2019)    Genome-wide human brain eQTLs: In-depth analysis and insights using the UKBEC dataset.                   Scientific Reports , 9  (1)    , Article 19201.  10.1038/s41598-019-55590-0 <https://doi.org/10.1038/s41598-019-55590-0>.       Green open access   
 
document_url: https://discovery-pp.ucl.ac.uk/id/eprint/10088808/1/s41598-019-55590-0.pdf