Identification of Candidate Gene Signatures and Regulatory Networks in Endometriosis and its Related Infertility by Integrated Analysis

Expression Profiles of Genes Related to Development and Progression of Endometriosis and Their Association with Paraben and Benzophenone Exposure

Increasing evidence has been published over recent years on the implication of endocrine-disrupting chemicals (EDCs), including parabens and benzophenones in the pathogenesis and pathophysiology of endometriosis. However, to the best of our knowledge, no study has been published on the ways in which exposure to EDCs might affect cell-signaling pathways related to endometriosis. We aimed to describe the endometriotic tissue expression profile of a panel of 23 genes related to crucial cell-signaling pathways for the development and progression of endometriosis (cell adhesion, invasion/migration, inflammation, angiogenesis, and cell proliferation/hormone stimulation) and explore its relationship with the exposure of patients to parabens (PBs) and benzophenones (BPs). This cross-sectional study included a subsample of 33 women with endometriosis from the EndEA study, measuring their endometriotic tissue expressions of 23 genes, while urinary concentrations of methyl-, ethyl-, propyl-, butyl-paraben, benzophenone-1, benzophenone-3, and 4-hydroxybenzophenone were determined in 22 women. Spearman's correlations test and linear and logistic regression analyses were performed. The expression of 52.2% of studied genes was observed in >75% of endometriotic tissue samples and the expression of 17.4% (n = 4) of them in 50-75%. Exposure to certain PB and BP congeners was positively associated with the expression of key genes for the development and proliferation of endometriosis. Genes related to the development and progression of endometriosis were expressed in most endometriotic tissue samples studied, suggesting that exposure of women to PBs and BPs may be associated with the altered expression profile of genes related to cellular pathways involved in the development of endometriosis.

Gene expression analysis in endometriosis: Immunopathology insights, transcription factors and therapeutic targets

Background

Endometriosis is recognized as an estrogen-dependent inflammation disorder, estimated to affect 8%-15% of women of childbearing age. Currently, the etiology and pathogenesis of endometriosis are not completely clear. Underlying mechanism for endometriosis is still under debate and needs further exploration. The involvement of transcription factors and immune mediations may be involved in the pathophysiological process of endometriosis, but the specific mechanism remains to be explored. This study aims to investigate the underlying molecular mechanisms in endometriosis.

Methods

The gene expression profile of endometriosis was obtained from the gene expression omnibus (GEO) database. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied to the endometriosis GSE7305 datasets. Cibersort and MCP-counter were used to explore the immune response gene sets, immune response pathway, and immune environment. Differentially expressed genes (DEGs) were identified and screened. Common biological pathways were being investigated using the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Transcription factors were from The Human Transcription Factors. The least absolute shrinkage and selection operator (Lasso) model identified four differential expressions of transcription factors (AEBP1, HOXB6, KLF2, and RORB). Their diagnostic value was calculated by receiver operating characteristic (ROC) curve analysis and validated in the validation cohort (GSE11691, GSE23339). By constructing the interaction network of crucial transcription factors, weighted gene coexpression network analysis (WGCNA) was used to search for key module genes. Metascape was used for enrichment analysis of essential module genes and obtained HOXB6, KLF2. The HOXB6 and KLF2 were further verified as the only two intersection genes according to Support Vector Machine Recursive Feature Elimination (SVM-RFE) and random forest models. We constructed ceRNA (lncRNA-miRNA-mRNA) networks with four potential transcription factors. Finally, we performed molecular docking for goserelin and dienogest with four transcription factors (AEBP1, HOXB6, KLF2, and RORB) to screen potential drug targets.

Results

Immune and metabolic pathways were enriched in GSVA and GSEA. In single sample gene set enrichment analysis (ssGSEA), most immune infiltrating cells, immune response gene sets, and immune response pathways are differentially expressed between endometriosis and non-endometriosis. Twenty-seven transcription factors were screened from differentially expressed genes. Most of the twenty-seven transcription factors were correlated with immune infiltrating cells, immune response gene sets and immune response pathways. Furthermore, Adipocyte enhancer binding protein 1 (AEBP1), Homeobox B6 (HOXB6), Kruppel Like Factor 2 (KLF2) and RAR Related Orphan Receptor B (RORB) were selected out from twenty-seven transcription factors. ROC analysis showed that the four genes had a high diagnostic value for endometriosis. In addition, KLF2 and HOXB6 were found to play particularly important roles in multiple modules (String, WGCNA, SVM-RFE, random forest) on the gene interaction network. Using the ceRNA network, we found that NEAT1 may regulate the expressions of AEBP1, HOXB6 and RORB, while X Inactive Specific Transcript (XIST) may control the expressions of HOXB6, RORB and KLF2. Finally, we found that goserelin and dienogest may be potential drugs to regulate AEBP1, HOXB6, KLF2 and RORB through molecular docking.

Conclusions

AEBP1, HOXB6, KLF2, and RORB may be potential biomarkers for endometriosis. Two of them, KLF2 and HOXB6, are critical molecules in the gene interaction network of endometriosis. Discovered by molecular docking, AEBP1, HOXB6, KLF2, and RORB are targets for goserelin and dienogest.

Genomic insights into the conservation and population genetics of two Chinese native goat breeds

Chinese goats are an important group of goats worldwide. However, there are few studies on the conservation priority, genetic relationship, and potential gene flow between Chinese and global goat breeds. Here, we genotyped 239 goats from conservation populations of the Chinese Guangfeng and Ganxi breeds using the GoatSNP50 BeadChip. The conservation priority, population structure, selection signatures and introgression of these goats were analyzed in the context of 36 global goat breeds. First, we showed that Guangfeng and Ganxi goats had the largest effective population sizes across the global breeds 13 generations ago. Nevertheless, Ganxi goats have recently experienced a high degree of inbreeding, resulting in their conservation priority based on total gene and allelic diversities being lower than that of most other Chinese breeds (including Guangfeng goats). Population structure and admixture analyses showed that an average of 18% of Guangfeng genomic components were introgressed from Boer goats approximately 18-yr ago. Next, we reconstructed the subfamily structure of the core populations of Guangfeng and Ganxi goats, and proposed reasonable conservation strategies for inbreeding management. Moreover, a list of candidate genes under selection for fertility, immunity, growth, and meat quality were detected in Guangfeng and Ganxi goats. Finally, we identified some genes related to body development and reproduction, which were introgressed from Boer goats and may be beneficial for improving performance and productivity of Guangfeng goats. In conclusion, this study not only provides new insights into the conservation and utilization of Guangfeng and Ganxi goats but also enriches our understanding of artificial introgression from exotic goats into Chinese local goats.