Geese, descendants of migratory birds, have preserved the distinct reproductive and lipid metabolism traits of their wild ancestors.  Therefore, compared to other poultry, geese have lower egg production ability and greater susceptibility to fatty liver.  Recent research underscores the impact of lipid metabolism disorders on female reproductive health.  In this context, we observed reproductive disorders (RD) and lipid metabolism anomalies in certain geese populations.  This study systematically elucidated the differences between RD and normal geese at various levels, including genomics, transcriptomics, bile acid metabolomics, and microbiomics, revealing the crucial role of microorganisms.  Our study provides a thorough examination of the ovarian anatomical, histological, and transcriptomic profiles between normal and RD geese.  Genomic analyses pinpoint mutations in genes associated with bile acid metabolism, highlighting their potential role in RD pathogenesis.  The genomic discoveries are substantiated by precise bile acid assays and ileum transcriptome analyses, which expose a significant disruption in bile acid absorption, activation of FXR, and an increase in serum chenodeoxycholic acid (CDCA) concentrations within RD geese.  Notably, 16S rRNA sequencing uncovers significantly greater beta diversity in the ileum microbiota of RD geese than in the normal group.  Both Wilcoxon rank sum test and LEfSe analyses highlighted a marked increase in Romboutsia abundance in RD geese.  Experimental cultivation of microbiota with CDCA supplementation confirms the impact of CDCA on Romboutsia lituseburensis proliferation.  Gavage experiments with R. lituseburensis elucidate its involvement in primary follicle reduction via immune-mediated pathways.  Collectively, our multifaceted analysis unravels the intricate involvement of Romboutsia in goose RD, offering insights from genetic, physiological, and microbial dimensions.  Our findings not only deepen understanding of the etiology of RD in geese but also suggest potential avenues for therapeutic interventions targeting bile acid metabolism and modulation of specific microbiota components.

intelligent pest-monitoring light trap  /  insect dataset construction  /  few-shot learning  /  self-supervised learning  /  insect detection and classification  /  automated insect annotation