Coordinated Transcriptomic and Epigenetic Approach Reveals Molecular Features Underlying Natural Mating Ability in Captive Male Giant Pandas

转录组学和表观遗传学协同研究揭示圈养雄性大熊猫自然交配能力的分子特征

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Abstract

Natural mating ability is a critical behavioral trait for the reproductive success of captive endangered mammals, and its loss often reflects declining adaptability and potential physiological dysfunctions. However, the underlying molecular regulatory mechanisms remain poorly understood. In this study, we integrated blood transcriptome and whole-genome DNA methylation (whole-genome bisulfite sequencing) data to systematically explore the molecular basis of natural mating ability differences in captive male giant pandas (Ailuropoda melanoleuca). A total of 21 male individuals, which were classified into either capable (with successful natural mating experience) or incapable (with repeated mating failure despite physical health) groups, were sampled from three breeding centers. RNA-seq analysis identified key differentially expressed genes (DEGs) such as ZPBP2, enriched in functional pathways related to GnRH signaling, MAPK cascades, immune modulation, and olfactory perception. Whole-genome bisulfite sequencing (WGBS) analysis revealed significant differences in CpG (CG) methylation density on the X chromosome, and identified promoter- and gene body-associated differentially methylated regions (DMRs) that were inversely correlated with gene expression. Integrative analysis demonstrated a strong association between gene expression and DNA methylation, with the associated genes enriched in reproduction-relevant pathways including axon guidance, cysteine and methionine metabolism, and apoptosis/autophagy. These findings suggest that DNA methylation may influence transcriptional activity involved in natural mating behavior. This multi-omics approach provides valuable insights into the epigenetic regulation of complex reproductive phenotypes in endangered species and offers a theoretical basis for future applications in molecular marker-based individual selection and optimization of captive breeding programs, thereby contributing to wildlife conservation efforts.

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