BackgroundLiver is an important metabolic organ that plays a critical role in lipid synthesis, degradation, and transport; however, the molecular regulatory mechanisms of lipid metabolism remain unclear in chicken. In this study, RNA-Seq technology was used to investigate differences in expression profiles of hepatic lipid metabolism-related genes and associated pathways between juvenile and laying hens. The study aimed to broaden the understanding of liver lipid metabolism in chicken, and thereby to help improve laying performance in the poultry industry.ResultsRNA-Seq analysis was carried out on total RNA harvested from the liver of juvenile (n = 3) and laying (n = 3) hens. Compared with juvenile hens, 2567 differentially expressed genes (1082 up-regulated and 1485 down-regulated) with P ≤ 0.05 were obtained in laying hens, and 960 of these genes were significantly differentially expressed (SDE) at a false discovery rate (FDR) of ≤0.05 and fold-change ≥2 or ≤0.5. In addition, most of the 198 SDE novel genes (91 up-regulated and 107 down-regulated) were discovered highly expressed, and 332 SDE isoforms were identified. Gene ontology (GO) enrichment and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis showed that the SDE genes were most enrichment in steroid biosynthesis, PPAR signaling pathway, biosynthesis of unsaturated fatty acids, glycerophospholipid metabolism, three amino acid pathways, and pyruvate metabolism (P ≤ 0.05). The top significantly enriched GO terms among the SDE genes included lipid biosynthesis, cholesterol and sterol metabolic, and oxidation reduction, indicating that principal lipogenesis occurred in the liver of laying hens.ConclusionsThis study suggests that the majority of changes at the transcriptome level in laying hen liver were closely related to fat metabolism. Some of the SDE uncharacterized novel genes and alternative splicing isoforms that were detected might also take part in lipid metabolism, although this needs further investigation. This study provides valuable information about the expression profiles of mRNAs from chicken liver, and in-depth functional investigations of these mRNAs could provide new insights into the molecular networks of lipid metabolism in chicken liver.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1943-0) contains supplementary material, which is available to authorized users.
BackgroundThe detection and functional characterization of genomic structural variations are important for understanding the landscape of genetic variation in the chicken. A recently recognized aspect of genomic structural variation, called copy number variation (CNV), is gaining interest in chicken genomic studies. The aim of the present study was to investigate the pattern and functional characterization of CNVs in five characteristic chicken breeds, which will be important for future studies associating phenotype with chicken genome architecture.ResultsUsing a commercial 385 K array-based comparative genomic hybridization (aCGH) genome array, we performed CNV discovery using 10 chicken samples from four local Chinese breeds and the French breed Houdan chicken. The female Anka broiler was used as a reference. A total of 281 copy number variation regions (CNVR) were identified, covering 12.8 Mb of polymorphic sequences or 1.07% of the entire chicken genome. The functional annotation of CNVRs indicated that these regions completely or partially overlapped with 231 genes and 1032 quantitative traits loci, suggesting these CNVs have important functions and might be promising resources for exploring differences among various breeds. In addition, we employed quantitative PCR (qPCR) to further validate several copy number variable genes, such as prolactin receptor, endothelin 3 (EDN3), suppressor of cytokine signaling 2, CD8a molecule, with important functions, and the results suggested that EDN3 might be a molecular marker for the selection of dark skin color in poultry production. Moreover, we also identified a new CNVR (chr24: 3484617–3512275), encoding the sortilin-related receptor gene, with copy number changes in only black-bone chicken.ConclusionsHere, we report a genome-wide analysis of the CNVs in five chicken breeds using aCGH. The association between EDN3 and melanoblast proliferation was further confirmed using qPCR. These results provide additional information for understanding genomic variation and related phenotypic characteristics.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-934) contains supplementary material, which is available to authorized users.
Background Estrogen plays an essential role in female development and reproductive function. In chickens, estrogen is critical for lipid metabolism in the liver. The regulatory molecular network of estrogen in chicken liver is poorly understood. To identify estrogen-responsive genes and estrogen functional sites on a genome-wide scale, we determined expression profiles of mRNAs, lncRNAs, and miRNAs in estrogen-treated ((17β-estradiol)) and control chicken livers using RNA-Sequencing (RNA-Seq) and studied the estrogen receptor α binding sites by ChIP-Sequencing (ChIP-Seq). Results We identified a total of 990 estrogen-responsive genes, including 962 protein-coding genes, 11 miRNAs, and 17 lncRNAs. Functional enrichment analyses showed that the estrogen-responsive genes were highly enriched in lipid metabolism and biological processes. Integrated analysis of the data of RNA-Seq and ChIP-Seq, identified 191 genes directly targeted by estrogen, including 185 protein-coding genes, 4 miRNAs, and 2 lncRNAs. In vivo and in vitro experiments showed that estrogen decreased the mRNA expression of PPARGC1B, which had been reported to be linked with lipid metabolism, by directly increasing the expression of miR-144-3p. Conclusions These results increase our understanding of the functional network of estrogen in chicken liver and also reveal aspects of the molecular mechanism of estrogen-related lipid metabolism.
Few studies have been conducted regarding the biological function and regulation role of gga-miR-221-5p in the liver. We compared the conservation of miR-221-5p among species and investigated the expression pattern of gga-miR-221-5p, validating the direct target genes of gga-miR-221-5p by dual luciferase reporter assay, the biological function of gga-miR-221-5p in the liver was studied by gga-miR-221-5p overexpression and inhibition. Furthermore, we explored the regulation of gga-miR-221-5p and its target genes by treatment with estrogen and estrogen antagonists in vivo and in vitro. The results showed that miR-221-5p was highly conserved among species, expressed in all tested tissues and significantly downregulated in peak-laying hen liver compared to pre-laying hen liver. Gga-miR-221-5p could directly target the expression of elongase of very long chain fatty acids 6 (ELOVL6) and squalene epoxidase (SQLE) genes to affect triglyceride and total cholesterol content in the liver. 17β-estradiol could significantly inhibit the expression of gga-miR-221-5p but promote the expression of ELOVL6 and SQLE genes. In conclusion, the highly conservative gga-miR-221-5p could directly target ELOVL6 and SQLE mRNAs to affect the level of intracellular triglyceride and total cholesterol. Meanwhile, 17β-estradiol could repress the expression of gga-miR-221-5p but increase the expression of ELOVL6 and SQLE, therefore promoting the synthesis of intracellular triglyceride and cholesterol levels in the liver of egg-laying chicken.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.