Comprehensive promoter level expression quantitative trait loci analysis of the human frontal lobe

Abstract

BackgroundExpression quantitative trait loci (eQTL) analysis is a powerful method to detect correlations between gene expression and genomic variants and is widely used to interpret the biological mechanism underlying identified genome wide association studies (GWAS) risk loci. Numerous eQTL studies have been performed on different cell types and tissues of which the majority has been based on microarray technology.MethodsWe present here an eQTL analysis based on cap analysis gene expression sequencing (CAGEseq) data created from human postmortem frontal lobe tissue combined with genotypes obtained through genotyping arrays, exome sequencing, and CAGEseq. Using CAGEseq as an expression profiling technique combined with these different genotyping techniques allows measurement of the molecular effect of variants on individual transcription start sites and increases the resolution of eQTL analysis by also including the non-annotated parts of the genome.ResultsWe identified 2410 eQTLs and show that non-coding transcripts are more likely to contain an eQTL than coding transcripts, in particular antisense transcripts. We provide evidence for how previously identified GWAS loci for schizophrenia (NRGN), Parkinson’s disease, and Alzheimer’s disease (PARK16 and MAPT loci) could increase the risk for disease at a molecular level. Furthermore, we demonstrate that CAGEseq improves eQTL analysis because variants obtained from CAGEseq are highly enriched for having a functional effect and thus are an efficient method towards the identification of causal variants.ConclusionOur data contain both coding and non-coding transcripts and has the added value that we have identified eQTLs for variants directly adjacent to TSS. Future eQTL studies would benefit from combining CAGEseq with RNA sequencing for a more complete interpretation of the transcriptome and increased understanding of eQTL signals.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-016-0320-1) contains supplementary material, which is available to authorized users.

A comprehensive analysis of SNCA‐related genetic risk in sporadic parkinson disease

“…17 Samples with complete data for the relevant SNPs included 77 males and 33 females with mean age = 51 years (range = 2–95), mean RNA integrity number (RIN) = 7.6 (range = 5.4–9.1), and mean postmortem interval = 11 hours (range = 2–28). Findings were followed up in available data from an ongoing RNA sequencing (RNAseq) study by the North American Brain Expression Consortium (dbGAP phs001300.v1.p1).…”

“…We reanalyzed postmortem frontal cortex cap analysis gene expression sequencing (CAGEseq) data and imputed genotypes from the SNCA locus from 117 neurologically normal individuals, where materials and methods have been described in detail in a previous publication. 17 Samples with complete data for the relevant SNPs included 77 males and 33 females with mean Samples overlapping with CAGEseq were removed, leaving a total of 150 nonneurological frontal cortex samples with nonmissing genotype data for 55 males and 86 females with mean age = 59 years (range =15-97), mean RIN = 7.7 (range = 6.0-9.5), and mean postmortem interval = 10.0 hours (range = 1.2-36.0). The use of human brain samples from both of these datasets was approved by the NIH Office for Human Subjects Research.…”

“…rs356182 Is Associated with a Specific 5 0 UTR Transcript Isoform of SNCA Previously published brain eQTL data have failed to show robust associations between GWAS SNPs and gene-level SNCA expression. 5,17,34 However, the 5 0 region of SNCA harbors multiple alternative transcription start sites, giving rise to distinct mRNA isoforms with variable 5 0 UTR. Hypothesizing that risk-relevant gene regulation, either pre-or posttranscriptional, may be specific to transcript variant, we performed eQTL analysis individually for each of the major 5 0 UTR isoforms in 2 existing large sequencing datasets from postmortem human frontal cortex and a third, independent sample set analyzed by qPCR.…”

“…2 However, investigations of SNCA susceptibility SNPs as expression quantitative trait loci (eQTLs) in brain have thus far not yielded sufficient evidence to firmly corroborate this hypothesis. 5,17 The SNCA top hit signal for PD risk has consistently been located near the 3 0 end of the gene, and 2 recent studies have proposed different functional explanations and causal variants underlying this strong disease association, which have yet to be followed up in independent investigations. 18,19 The present study aimed to refine our understanding of the SNCA association with PD using several different approaches.…”

MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies

“…We also applied MOSTWAS to transcriptomic data on samples of prefrontal cortex, a tissue that has been used previously in studying neuropsychiatric traits and disorders with TWAS [58,59]. There has been ample evidence in brain tissue, especially the prefrontal cortex, that non-coding variants may regulate distal genes [58,60,61]; in fact, an eQTL analysis by Sng et al found that approximately 20-40% of eQTLs in the frontal cortex can be considered trans-acting [62]. Thus, the prefrontal cortex in the context of neuropsychiatric disorders provides a prime example to assess MOSTWAS.…”