TY - JOUR
T1 - Comparison of quantitative trait loci methods
T2 - Total expression and allelic imbalance method in brain RNA-seq
AU - The BrainSeq Consortium¶
AU - Gådin, Jesper R.
AU - Buil, Alfonso
AU - Colantuoni, Carlo
AU - Jaffe, Andrew E.
AU - Nielsen, Jacob
AU - Shin, Joo Heon
AU - Hyde, Thomas M.
AU - Kleinman, Joel E.
AU - Plath, Niels
AU - Eriksson, Per
AU - Brunak, Søren
AU - Didriksen, Michael
AU - Weinberger, Daniel R.
AU - Folkersen, Lasse
N1 - Publisher Copyright:
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
PY - 2019/6
Y1 - 2019/6
N2 - Background Of the 108 Schizophrenia (SZ) risk-loci discovered through genome-wide association studies (GWAS), 96 are not altering the sequence of any protein. Evidence linking non-coding risk-SNPs and genes may be established using expression quantitative trait loci (eQTL). However, other approaches such allelic expression quantitative trait loci (aeQTL) also may be of use. Methods We applied both the eQTL and aeQTL analysis to a biobank of deeply sequenced RNA from 680 dorso-lateral pre-frontal cortex (DLPFC) samples. For each of 340 genes proximal to the SZ risk-SNPs, we asked how much SNP-genotype affected total expression (eQTL), as well as how much the expression ratio between the two alleles differed from 1:1 as a consequence of the risk-SNP genotype (aeQTL). Results We analyzed overlap with comparable eQTL-findings: 16 of the 30 risk-SNPs known to have gene-level eQTL also had gene-level aeQTL effects. 6 of 21 risk-SNPs with known splice-eQTL had exon-aeQTL effects. 12 novel potential risk genes were identified with the aeQTL approach, while 55 tested SNP-pairs were found as eQTL but not aeQTL. Of the tested 108 loci we could find at least one gene to be associated with 21 of the risk-SNPs using gene-level aeQTL, and with an additional 18 risk-SNPs using exon-level aeQTL. Conclusion Our results suggest that the aeQTL strategy complements the eQTL approach to susceptibility gene identification.
AB - Background Of the 108 Schizophrenia (SZ) risk-loci discovered through genome-wide association studies (GWAS), 96 are not altering the sequence of any protein. Evidence linking non-coding risk-SNPs and genes may be established using expression quantitative trait loci (eQTL). However, other approaches such allelic expression quantitative trait loci (aeQTL) also may be of use. Methods We applied both the eQTL and aeQTL analysis to a biobank of deeply sequenced RNA from 680 dorso-lateral pre-frontal cortex (DLPFC) samples. For each of 340 genes proximal to the SZ risk-SNPs, we asked how much SNP-genotype affected total expression (eQTL), as well as how much the expression ratio between the two alleles differed from 1:1 as a consequence of the risk-SNP genotype (aeQTL). Results We analyzed overlap with comparable eQTL-findings: 16 of the 30 risk-SNPs known to have gene-level eQTL also had gene-level aeQTL effects. 6 of 21 risk-SNPs with known splice-eQTL had exon-aeQTL effects. 12 novel potential risk genes were identified with the aeQTL approach, while 55 tested SNP-pairs were found as eQTL but not aeQTL. Of the tested 108 loci we could find at least one gene to be associated with 21 of the risk-SNPs using gene-level aeQTL, and with an additional 18 risk-SNPs using exon-level aeQTL. Conclusion Our results suggest that the aeQTL strategy complements the eQTL approach to susceptibility gene identification.
UR - http://www.scopus.com/inward/record.url?scp=85067275727&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067275727&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0217765
DO - 10.1371/journal.pone.0217765
M3 - Article
C2 - 31206532
AN - SCOPUS:85067275727
SN - 1932-6203
VL - 14
JO - PloS one
JF - PloS one
IS - 6
M1 - e0217765
ER -