Sexual Dimorphism in Gene Expression: A Multi-Tissue Genome-Wide Study in BXD Mice and Potential Insights into Human Biology
Abstract
Abstract Sex-biased gene expression contributes to physiological and disease differences between females and males. This study re-analyzed publicly available GeneNetwork expression datasets from BXD recombinant inbred mice across seven tissues, including adrenal gland, amygdala, hypothalamus, kidney, spleen, liver, and pituitary gland, to characterize tissue-dependent sex-biased expression and prioritize candidate regulatory loci. Because these datasets were generated using microarray platforms rather than RNA-seq, probe-level expression traits were analyzed and then mapped to genes. Male and female strain-level mean expression values were compared using paired two-tailed t-tests across matched BXD strains, followed by Bonferroni correction, and sex-biased probes were defined as q < 0.05. Functional enrichment, correlation-network analysis, eQTL mapping, and contextual comparison with human GTEx data were performed. Sex-biased expression was strongly tissue-dependent, with liver, adrenal gland, kidney, and pituitary showing larger proportions of sex-biased probes than amygdala, hypothalamus, and spleen. No autosomal gene was shared across all seven tissues, whereas X-linked genes showed more consistent sex-biased expression. Liver EDEGs were enriched for xenobiotic, steroid, bile-acid, and lipid-metabolic functions, while smaller DEG sets in amygdala, hypothalamus, and spleen were associated with neuronal signalling, reproductive regulation, heme metabolism, and immune response. Overall, this re-analysis supports strong tissue specificity in sex-biased expression in BXD mice and highlights candidate genes and regulatory loci for future experimental validation.
Fields of Study & Subjects
Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Sex and Gender in Healthcare
Bioinformatics and Genomic Networks
Publication details
- Journal / source
- Research Square
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Preprint