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Separation of Avian Preovulatory Follicle Granulosa and Theca Cell Layers for Downstream Applications
Published on: October 25, 2024
Deciphering the uterine transcriptional mechanisms underlying eggshell strength through multi-stage analysis in
Liyuan Wang1, Lei Liu2, Ying Bai3
1Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China.
Abstract:
Eggshell strength is a critical economic trait that declines with hen age, yet the molecular mechanisms distinguishing stable genetic determinants from age-responsive pathways remain unclear. This study implemented a multi-stage comparative framework using uterine transcriptomes from Rhode Island Red hens at peak lay (60 weeks) and late lay (90 weeks) to address this question. At each age, hens were stratified into Weak and Strong shell strength groups based on longitudinal records (5 time points for the 90-week cohort), with 5 individuals per group selected for RNA-seq analysis. Uterine transcriptomic analysis revealed a conserved core of 86 differentially expressed genes associated with shell strength at both ages, with 96.5% exhibiting concordant regulation direction and highly correlated fold-changes (r = 0.84). Weighted gene co-expression network analysis identified two pivotal modules: a stable intrinsic module (MElightcyan) at 60 weeks correlated with peak-lay strength, and an aging-amplified module (MEyellow) at 90 weeks whose correlation with strength progressively increased from mid- to late lay (r = 0.57 at 40 weeks to 0.72 at 90 weeks). Functionally, enriched pathways shifted from cellular structure (MElightcyan) to calcium signaling and hormone regulation (MEyellow) with age. Transcriptional network analysis identified 8 conserved transcription factors (including SATB1 and RXRG) orchestrating this core program. Integrative analysis prioritizing differential expression, longitudinal phenotypic correlation, and QTL mapping highlighted high-confidence candidate genes, including CNTNAP5 (peak-lay) and SLCO1C1 (late-lay). We propose a two-tiered regulatory model wherein a stable core genetic program interacts with dynamic, age-adapted effector networks to determine shell strength. This model provides a dual-strategy framework, distinguishing targets for genetic selection (core program) from pathways for precision management (age-adapted networks) to mitigate age-related decline in shell quality.
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