ArticleVeterinary sciences2024
Comparative Transcriptome Analysis Unveils Regulatory Factors Influencing Fatty Liver Development in Lion-Head Geese under High-Intake Feeding Compared to Normal Feeding.
Article in Veterinary sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Review
- Multi-omics analysis provides new insights into molecular mechanisms for waterfowl fatty liver formation.Poultry science · 2025Article
- Impacts of feeding different lipid sources on serum biochemical indices, dietary fatty acid metabolism, raw foie gras quality characteristics and gene expression related to fat deposition in the Landes goose.Animal nutrition (Zhongguo xu mu shou yi xue hui) · 2025Article
- Integrative Transcriptomic and Metabolomic Analysis of Muscle and Liver Reveals Key Molecular Pathways Influencing Growth Traits in Zhedong White Geese.Animals : an open access journal from MDPI · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
The lion-head goose is the only large goose species in China, and it is one of the largest goose species in the world. Lion-head geese have a strong tolerance for massive energy intake and show a priority of fat accumulation in liver tissue through special feeding. Therefore, the aim of this study was to investigate the impact of high feed intake compared to normal feeding conditions on the transcriptome changes associated with fatty liver development in lion-head geese. In this study, 20 healthy adult lion-head geese were randomly assigned to a control group (CONTROL, n = 10) and high-intake-fed group (CASE, n = 10). After 38 d of treatment, all geese were sacrificed, and liver samples were collected. Three geese were randomly selected from the CONTROL and CASE groups, respectively, to perform whole-transcriptome analysis to analyze the key regulatory genes. We identified 716 differentially expressed mRNAs, 145 differentially expressed circRNAs, and 39 differentially expressed lncRNAs, including upregulated and downregulated genes. GO enrichment analysis showed that these genes were significantly enriched in molecular function. The node degree analysis and centrality metrics of the mRNA-lncRNA-circRNA triple regulatory network indicate the presence of crucial functional nodes in the network. We identified differentially expressed genes, including
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Registered trials
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