比较数量性状基因座方法：脑 RNA-seq 中的总表达和等位基因失衡方法。
Comparison of quantitative trait loci methods: Total expression and allelic imbalance method in brain RNA-seq.
机构信息
Cardiovascular Medicine Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden.
Roskilde Hospital, Roskilde, Denmark.
出版信息
PLoS One. 2019 Jun 17;14(6):e0217765. doi: 10.1371/journal.pone.0217765. eCollection 2019.
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.
背景
在通过全基因组关联研究（GWAS）发现的 108 个精神分裂症（SZ）风险基因座中，有 96 个不改变任何蛋白质的序列。通过表达数量性状基因座（eQTL）可以建立与非编码风险-SNPs 和基因相关的证据。然而，其他方法，如等位基因表达数量性状基因座（aeQTL）也可能有用。
方法
我们应用 eQTL 和 aeQTL 分析方法对来自 680 个背外侧前额叶皮层（DLPFC）样本的深度测序 RNA 生物库进行了分析。对于 340 个靠近 SZ 风险-SNPs 的基因中的每一个，我们询问 SNP 基因型对总表达的影响程度（eQTL），以及风险-SNP 基因型如何导致两个等位基因的表达比率与 1:1 不同（aeQTL）。
结果
我们分析了与可比 eQTL 发现的重叠：已知具有基因水平 eQTL 的 30 个风险-SNPs 中有 16 个也具有基因水平 aeQTL 效应。已知有剪接 eQTL 的 21 个风险-SNPs 中有 6 个具有外显子 aeQTL 效应。使用 aeQTL 方法鉴定了 12 个新的潜在风险基因，而 55 个测试 SNP 对被鉴定为 eQTL 但不是 aeQTL。在测试的 108 个基因座中，我们使用基因水平 aeQTL 可以找到至少一个基因与 21 个风险-SNPs 相关，使用外显子水平 aeQTL 可以找到另外 18 个风险-SNPs 相关。
结论
我们的结果表明，aeQTL 策略补充了易感性基因鉴定的 eQTL 方法。
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