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