1. Genetic regulation of disease risk and endometrial gene expression highlights potential target genes for endometriosis and polycystic ovarian syndrome.
- Author
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Fung JN, Mortlock S, Girling JE, Holdsworth-Carson SJ, Teh WT, Zhu Z, Lukowski SW, McKinnon BD, McRae A, Yang J, Healey M, Powell JE, Rogers PAW, and Montgomery GW
- Subjects
- Adult, Alleles, Case-Control Studies, Chromosomes, Human, Pair 5 genetics, Female, Gene Frequency genetics, Genome-Wide Association Study, Humans, Menstrual Cycle genetics, Meta-Analysis as Topic, Molecular Sequence Annotation, Quantitative Trait Loci genetics, Risk Factors, Signal Transduction genetics, Endometriosis genetics, Endometrium metabolism, Endometrium pathology, Gene Expression Regulation, Genetic Predisposition to Disease, Polycystic Ovary Syndrome genetics
- Abstract
Gene expression varies markedly across the menstrual cycle and expression levels for many genes are under genetic control. We analyzed gene expression and mapped expression quantitative trait loci (eQTLs) in endometrial tissue samples from 229 women and then analyzed the overlap of endometrial eQTL signals with genomic regions associated with endometriosis and other reproductive traits. We observed a total of 45,923 cis-eQTLs for 417 unique genes and 2,968 trans-eQTLs affecting 82 unique genes. Two eQTLs were located in known risk regions for endometriosis including LINC00339 on chromosome 1 and VEZT on chromosome 12 and there was evidence for eQTLs that may be target genes in genomic regions associated with other reproductive diseases. Dynamic changes in expression of individual genes across cycle include alterations in both mean expression and transcriptional silencing. Significant effects of cycle stage on mean expression levels were observed for (2,427/15,262) probes with detectable expression in at least 90% of samples and for (2,877/9,626) probes expressed in some, but not all samples. Pathway analysis supports similar biological control of both altered expression levels and transcriptional silencing. Taken together, these data identify strong genetic effects on genes with diverse functions in human endometrium and provide a platform for better understanding genetic effects on endometrial-related pathologies.
- Published
- 2018
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