Sex differences in physiology and disease in mammals result from the effects of three classes of factors that are inherently unequal in males and females: reversible (activational) effects of gonadal hormones, permanent (organizational) effects of gonadal hormones, and cell-autonomous effects of sex chromosomes, as well as genes driven by these classes of factors. Often, these factors act together to cause sex differences in specific phenotypes, but the relative contribution of each and the interactions among them remain unclear. Here, we used the Four Core Genotypes (FCG) mouse model with or without hormone replacement to distinguish the effects of each class of sex-biasing factors on transcriptome regulation in liver and adipose tissues. We found that the activational hormone levels have the strongest influence on gene expression, followed by the organizational gonadal sex effect and, lastly, sex chromosomal effect, along with interactions among the three factors. Tissue specificity was prominent, with a major impact of estradiol on adipose tissue gene regulation, and of testosterone on the liver transcriptome. The networks affected by the three sex-biasing factors include development, immunity and metabolism, and tissue-specific regulators were identified for these networks. Furthermore, the genes affected by individual sex-biasing factors and interactions among factors are associated with human disease traits such as coronary artery disease, diabetes, and inflammatory bowel disease. Our study offers a tissue-specific account of the individual and interactive contributions of major sex-biasing factors to gene regulation that have broad impact on systemic metabolic, endocrine, and immune functions.
Sex differences in physiology and disease in mammals result from the effects of three classes of factors that are inherently unequal in males and females: reversible (activational) effects of gonadal hormones, permanent (organizational) effects of gonadal hormones, and cell-autonomous effects of sex chromosomes, as well as genes driven by these classes of factors. Often, these factors act together to cause sex differences in specific phenotypes, but the relative contribution of each and the interactions among them remain unclear. Here, we used the Four Core Genotypes (FCG) mouse model with or without hormone replacement to distinguish the effects of each class of sex-biasing factors on transcriptome regulation in liver and adipose tissues. We found that the activational hormone levels have the strongest influence on gene expression, followed by the organizational gonadal sex effect and, lastly, sex chromosomal effect, along with interactions among the three factors. Tissue specificity was prominent, with a major impact of estradiol on adipose tissue gene regulation, and of testosterone on the liver transcriptome. The networks affected by the three sex-biasing factors include development, immunity and metabolism, and tissue-specific regulators were identified for these networks. Furthermore, the genes affected by individual sex-biasing factors and interactions among factors are associated with human disease traits such as coronary artery disease, diabetes, and inflammatory bowel disease. Our study offers a tissue-specific account of the individual and interactive contributions of major sex-biasing factors to gene regulation that have broad impact on systemic metabolic, endocrine, and immune functions.
Background: This study aimed to identify potential genes and transcription factors involved in postradiation cognitive dysfunction using bioinformatics analysis.Methods: Bioinformatics tools were used to identify differentially expressed mRNAs between postradiation cognitive dysfunctional and control tissue. The GSE115735 dataset containing mRNA expression profiles was downloaded from the Gene Expression Omnibus database. The mRNA expression data corresponded to three hippocampus and three brain lateral ventricles from postradiation cognitive dysfunctional mice and controls. The differentially expressed mRNAs between the two groups were identified, and protein-protein interaction network was constructed. This was followed by functional enrichment and pathway analysis with further prediction of transcription factors that targeted differentially expressed mRNAs. Network analysis was conducted between the differentially expressed mRNAs and these potential transcription factors.Results: A total of 134 differentially expressed mRNAs were obtained, including 64 mRNAs in the hippocampus and 84 in the posterior lateral ventricles. Fourteen mRNAs were expressed differentially in both tissues. Furthermore, genes in the network were strongly enriched in neuroactive ligand-receptor interactions, regulation of calcium ion transport, mitotic spindle associated pathway, and TGF-beta signaling pathways. Six transcription factors associated with the regulation of target genes were identified. Conclusions: Most of the genes identified were involved in transcriptional regulation, including TFAP4, RUNX1, and CUX2, which may play important roles in the development of postradiation cognitive dysfunction.
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