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Transcriptomic analysis identifies hub genes involved in age-dependent abdominal fat development in chickens
Wei Wei1, Najun Huang1, Zihan Chen1
1College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China.
Poultry Science
|February 5, 2026
Summary
This study reveals key genes and molecular pathways involved in age-dependent abdominal fat accumulation in Wannan chickens, offering insights into poultry feed efficiency and carcass yield challenges.
Area of Science:
- Poultry genetics and molecular biology
- Animal science and nutrition
- Transcriptomics and bioinformatics
Background:
- Excessive abdominal fat (AF) negatively impacts poultry feed efficiency and carcass yield.
- The molecular mechanisms driving age-dependent AF development in chickens are not fully understood.
Purpose of the Study:
- To investigate the molecular network underlying age-dependent abdominal fat accumulation in Wannan chickens.
- To identify key genes and pathways associated with increased abdominal adipocyte area and fat percentage with age.
Main Methods:
- Quantification of abdominal adipocyte area in 9-week-old and 20-week-old Wannan chickens.
- RNA sequencing of 20 abdominal fat transcriptomes.
- Differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA).
Main Results:
- Significant increase in abdominal adipocyte area and differential expression of 441 genes between the age groups.
- WGCNA identified modules significantly correlated with adipocyte area, abdominal fat percentage, and age.
- Key genes including JUND, PAPSS2, PAK6, PIEZO2, and BUB1B were associated with age-dependent AF development.
Conclusions:
- The study elucidates molecular pathways like cytokine-cytokine receptor interaction and TGF-beta signaling in age-dependent AF development.
- Identified candidate genes provide a valuable resource for future research into poultry fat deposition and metabolic regulation.
Keywords:
Abdominal fatAdipocyte areaMolecular networkWannan chickensWeighted gene co-expression network analysisMore Related Videos
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