Integrated ATAC-seq and mRNA-seq analyses on granulosa cells identify key regulators of follicle selection in chickens

BACKGROUND: The differences in egg production performance among hens are closely linked to the efficiency of follicle selection, which is characterized by granulosa cell differentiation and progesterone production. In this study, by integrating ATAC-seq and mRNA-seq analyses on granulosa cells from pre-hierarchical (Pre-GCs) and hierarchical (Post-GCs) follicles, we set out to identify key regulatory factors involved in chicken follicle selection. RESULTS: FC|) identified 106 upregulated and 81 downregulated genes encoding transcription factors (TFs). mRNA-seq analysis showed 1,337 upregulated and 2,282 downregulated differentially expressed genes in Post-GCs compared to Pre-GCs. Among these, 146 genes were uniquely expressed in Pre-GCs, and 40 genes were uniquely expressed in Post-GCs. Integrated ATAC-seq and mRNA-seq analyses revealed that chromatin accessibility and gene expression were not always positively correlated. Additionally, four significantly upregulated core TFs (CREM, ESRRB, NR5A1, GATA6) and one significantly downregulated TF (ETS1) genes were identified. The upregulated TFs were associated with 651 significantly upregulated target genes across both mRNA and ATAC-seq data, while the downregulated TFs were associated with 236 significantly downregulated target genes. KEGG enrichment of these target genes identified core genes enriched in pathways closely related to follicle selection, such as Wnt signaling pathway. In the protein-protein interaction (PPI) network of core upregulated target genes, genes such as SMAD2 and PPARA occupied central positions, while genes such as LEF1 and RAC2 were central in the PPI network of core downregulated target genes. Among these core TFs, GATA6 is confirmed to promote the expression of key cholesterol and progesterone synthesis genes to enhance both cholesterol and progesterone production, with follicle-stimulating hormone further amplifying its effect on progesterone synthesis. CONCLUSIONS: Our integrated ATAC-seq and mRNA-seq analyses define key epigenetic and transcriptional changes during chicken follicle selection. We highlight core transcription factors, including CREM, ESRRB, NR5A1, GATA6 and ETS1, and their stage-specific target networks. Functional assays show that GATA6 promotes cholesterol and progesterone synthesis, providing mechanistic insight and candidate targets for improving hen reproductive performance.