Genetic regulation of disease risk and endometrial gene expression highlights potential target genes for endometriosis and polycystic ovarian syndrome

Scientific Reports, Jul 2018

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.

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Genetic regulation of disease risk and endometrial gene expression highlights potential target genes for endometriosis and polycystic ovarian syndrome

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. Introduction Variation in gene expression in human endometrium is strongly influenced by stage of the menstrual cycle1,2 and subject to the effects of genetic variation3. Understanding regulation of gene expression in this tissue is important because the endometrium is essential for female fertility including the establishment and maintenance of pregnancy4,5. Each menstrual cycle, under the influence of circulating steroid hormones, the endometrium regenerates with changes in cellular and molecular events in preparation for possible pregnancy2,6,7. Common genetic effects alter expression of many genes and are known as expression quantitative traits (eQTLs). The eQTLs play an important role in mediating effects of genetic factors increasing risk for common diseases8,9. The genetic effects may be tissue specific or influence expression across multiple tissues, and may interact with other factors including changing hormonal environments10,11. Major international projects like The Genotype-Tissue Expression (GTEx) project12,13 and the Epigenetic RoadMap14 are designed to identify eQTLs and understand genetic regulation of gene expression across multiple tissues and cell types. Results from the latest GTEx study in more than 400 samples across 42 distinct tissues show local cis-acting genetic variants tend to be of two classes, either affecting most tissues or active in only a small number of tissues12. In contrast, trans-eQTL effects tend to be tissue-specific and enriched in enhancer regions12. We analyzed genetic regulation of gene expression in endometrium, a tissue not included in the GTEx study, and the overlap of endometrial eQTL signals with signals for genetic risk factors in genomic regions associated with endometriosis and other reproductive traits available in GWAS catalogue including endometrial cancer and Polycystic ovary syndrome (PCOS). Endometriosis is a common disease affecting 7–10% of women15. The endometrium is considered an important source of cells that initiate the peritoneal lesions characteristic of endometriosis16,17 and we initiated studies of genetic regulation of gene expression in the endometrium as part of functional analyses to follow up genomic regions associated with endometriosis risk18,19,20,21,22,23. Our initial study identified eQTLs for 198 unique genes in endometrium3. The aims of this study were to expand the sample size to increase the power of our eQTL studies in endometrium and conduct formal analyses of the overlap between endometrial eQTLs and genetic variants associated with risk for endometriosis and other reproductive traits. Results Identification of complex structure of gene expression data in endometrium We analysed gene expression in endometrial samples collected from 229 women of European ancestry attending clinics at the Royal Women’s Hospital in Melbourne (the RWH dataset; n = 165) and Melbourne IVF in Melbourne (the IVF dataset; n = 64). Principle component analysis (PCA) of overall gene expression showed both sample groups cluster together within the same stages of the menstrual cycle with no apparent differences in the overall expression levels of genes between the two sample groups (Fig. S1a,b). Most of the IVF samples were collected during the early and mid-secretory phases of the cycle. Samples at this stage of the cycle clustered well together with early and mid-secretory phase samples from the RWH set (Fig. S1c). Some IVF patients (29/64) had an IVF cycle prior to the sample collection cycle. We did not detect any si (...truncated)


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Jenny N. Fung, Sally Mortlock, Jane E. Girling, Sarah J. Holdsworth-Carson, Wan Tinn Teh, Zhihong Zhu, Samuel W. Lukowski, Brett D. McKinnon, Allan McRae, Jian Yang, Martin Healey, Joseph E. Powell, Peter A. W. Rogers, Grant W. Montgomery. Genetic regulation of disease risk and endometrial gene expression highlights potential target genes for endometriosis and polycystic ovarian syndrome, Scientific Reports, 2018, Issue: 8, DOI: 10.1038/s41598-018-29462-y