Similar Datasets
Project description:Purpose: To understand the function differences of goose at broody and breeding stage Methods: RNA-seq analysis of oviduct tissues in reproductive and broody goose Results: Our study screened differential expressed mRNA and pathways involved in broodiness Conclusions:The differential expressed mRNA and pathways identified in this study may contribute to understand the broodiness occurs in goose
2019-04-25 | GSE130245 | GEO
Project description:The unique fat storage and metabolic characteristics of goose liver is an important model for studying lipid metabolism in animals or humans. In this study, RNA sequencing technology was used to obtain the liver transcriptome of Sichuan white goose with significant weight difference in the same population, and differentially expressed genes and their pathways were identified, which may help to understand the mechanism of goose weight change. In addition, the identified candidate genes may be useful for molecular breeding of geese.
2020-02-28 | GSE132921 | GEO
Project description:Lion-head goose is the only large goose species in China, and it was one of the largest goose species in the world. Our previous study firstly reported a chromosome-level genome assembly of Lion-head goose (Anser cygnoides), a native breed in South China, through the combination of PacBio, Bionano, and Hi-C technologies. The fat content of foie gras is augmented during its preparation due to the special feeding regimen. Lion-head geese have a strong tolerance of massive energy intake and show a priority of fat accumulation in liver tissue. In this study, we studied for the first time the important differential genes that regulate fatty liver in Lion-head goose. After high-intake feeding, the fatty livers of Lion-head geese were distinctly characterized. The revelation of gene regulation is an important basis for the study of liver development and molecular characteristics for the Lion-head goose. To analyze the excellent fatty liver performance of Lion-head goose at the molecular level, we performed whole transcriptome analysis by high-throughput RNA sequencing to analyze the key regulatory genes that determine the fatty livers in high-intake feeding group compared with the normal livers in normally-fed Lion-head geese. We identified 716 differentially expressed mRNAs, 145 differentially expressed circRNAs, and 39 differentially expressed lncRNAs in the fatty livers in high-intake feeding group compared with the normal livers in normally-fed Lion-head geese, including upregulated and downregulated genes, respectively. GO enrichment analysis showed that these genes were significantly enriched in molecular function, involved in extracellular regions, DNA-binding transcription factor activity, extracellular matrix, heme binding and other life activities. We chose differentially expressed genes involved in either upregulation or downregulation, and we additionally confirmed the accuracy of sequencing at the RNA level. In summary, our research suggested that these differentially expressed genes may play important roles in fatty liver development in Lion-head goose. However, the functions and mechanisms of these significantly differentially expressed genes should be investigated in future studies.
2023-11-16 | GSE243829 | GEO
Project description:To further understand the roles of miRNA during influenza A virus infection, we performed miRNA profiling in human alveolar adenocarcinoma cell lines, A549 cells, infected with influenza A virus A/Beijing/501/2009(H1N1) and A/goose/Jilin/hb/2003(H5N1).
2017-03-22 | GSE96857 | GEO
Project description:We identified the differentially expressed miRNAs in Landes goose liver after overfeeding for 21 days using high-throughput sequencing. We obtained 21453493 and 21525819 clean reads in normal liver and fatty liver by high-throughput sequencing, respectively. Of these clean reads, we respectively gained 9244896 and 9847086 miRNAs sequences in two groups by filtering the known non-miRNA reads, such as rRNA, tRNA, snRNA, and snoRNA by screening against ncRNA deposited in the GenBank and Rfam databases. These findings provided insights into the expression profiles of miRNAs in goose liver, and deepened our understanding of miRNAs in hepatic steatosis of geese.
2017-05-24 | GSE99200 | GEO
Project description:The lipid metabolism of granulosa cells plays a pivotal role in the development of goose follicles. However, the mechanisms by which lipid droplet-associated proteins regulate lipid droplets and influence cellular lipid metabolism remain poorly understood. To address this, our study systematically identified lipid droplet-associated proteins in goose follicular granulosa cells and analyzed these proteins at five distinct time points, in both pre-hierarchical granulosa cells and hierarchical granulosa cells, thereby obtaining relevant information on lipid droplet-associated proteins.
2025-03-26 | PXD061272 | Pride
Project description:Geese have a high tolerance of massive energy intake and exhibit little pathological development. We assessed phenotypes and transcriptomes of Tianfu geese to investigate the dynamic expression network behind goose adipogenesis. Goose liver exhibited higher fat accumulation than adipose tissues during fattening. We identified differentially expressed genes that function in several important lipid metabolism pathways, immune response, regulation of cancer, and differentially expressed long noncoding RNAs that might be involved in regulation of these pathways. We found that genes like BGE1 and SCD, which have key roles in glycolysis and synthesis of fatty acids, had higher fold change in liver than in adipose tissue. we suppose that the evolutionary split from mammals in adipogenesis is a result of adaptive evolution to long-distance migration.
2019-01-01 | GSE119421 | GEO
Project description:In this study, we cultured lion-headed goose myoblasts and induced their differentiation, followed by RNA-seq extraction of total RNA from proliferative and differentiated cells, respectively. The identified lncRNAs and mRNAs were analyzed, including enrichment analysis, alternative splicing, and construction of interaction networks.
2022-09-15 | GSE213147 | GEO