The data displayed through this website is a result of the
Fung et al., 2017
paper, published in Human Reproduction.
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Please cite the article if you use this data or browser in your research
Do genetic effects regulate gene expression in human endometrium?
This study demonstrated strong genetic effects on endometrial gene expression and some evidence for genetic regulation of gene expression in a menstrual cycle stage-specific manner.
What is known already:
Genetic effects on expression levels for many genes are tissue specific. Endometrial gene expression varies across menstrual cycle stages and between individuals, but there are limited data on genetic control of expression in endometrium.
Study design, size, duration:
We analysed genome-wide genotype and gene expression data to map cis expression quantitative trait loci (eQTL) in endometrium.
Participants/materials, setting, methods:
We recruited 123 women of European ancestry. DNA samples from blood were genotyped on Illumina HumanCoreExome chips. Total RNA was extracted from endometrial tissues. Whole-transcriptome profiles were characterized using Illumina Human HT-12 v4.0 Expression Beadchips. We performed eQTL mapping with ~8,000,000 genotyped and imputed single nucleotide polymorphisms (SNPs) and 12,329 genes.
Main results and the role of chance:
We identified a total of 18,595 cis SNP-probe associations at a study-wide level of significance (p < 1x10-7), which correspond to independent eQTLs for 198 unique genes. The eQTLs with the largest effect in endometrial tissue were rs4902335 for CHURC1 (p=1.05x10-32) and rs147253019 for ZP3 (p=8.22x10-30). We further performed a context-specific eQTL analysis to investigate if genetic effects on gene expression regulation act in a menstrual cycle-specific manner. Interestingly, five cis-eQTLs were identified with a significant stage-by-genotype interaction. The strongest stage interaction was the eQTL for C10ORF33 (PYROXD2) with SNP rs2296438 (p=2.0x10-4), where we observe a two-fold difference in the average expression levels of heterozygous samples depending on the stage of the menstrual cycle.
Large scale data:
The summary eQTL results are publicly available to browse or download.
Limitations, reasons for caution:
A limitation of the present study was the relatively modest sample size. It was not powered to identify trans-eQTLs and larger sample sizes will also be needed to provide better power to detect cis-eQTLs and cycle-stage specific effects, given the substantial changes in expression across the menstrual cycle for many genes.
Wider implications of the findings:
Identification of endometrial eQTLs provides a platform for better understanding genetic effects on endometriosis risk and other endometrial-related pathologies.
Download supplementary tables from the paper:
.zip file containing supplementary data