Articles written in Journal of Biosciences
Volume 31 Issue 5 December 2006 pp 565-573
Microarray analysis of adipose tissue gene expression profiles between two chicken breeds
Hongbao Wang Hui Li Qigui Wang Yuxiang Wang Huabin Han Hui Shi
The chicken is an important model organism that bridges the evolutionary gap between mammals and other vertebrates and provides a major protein source from meat and eggs throughout the world. Excessive accumulation of lipids in the adipose tissue is one of the main problems faced by the broiler industry nowadays. In order to visualize the mechanisms involved in the gene expression and regulation of lipid metabolism in adipose tissue, cDNA microarray containing 9 024 cDNA was used to construct gene expression profile and screen differentially expressed genes in adipose tissue between broilers and layers of 10 wk of age. Sixty-seven differentially expressed sequences were screened out, and 42 genes were found when blasted with the GenBank database. These genes are mainly related to lipid metabolism, energy metabolism, transcription and splicing factor, protein synthesis and degradation. The remained 25 sequences had no annotation available in the GenBank database. Furthermore, Northern blot and semi-quantitative RT-PCR were developed to confirm 4 differentially expressed genes screened by cDNA microarray, and it showed great consistency between the microarray data and Northern blot results or semi-quantitative RT-PCR results. The present study will be helpful for clarifying the molecular mechanism of obesity in chickens.
Volume 47 All articles Published: 27 January 2022 Article ID 0013 Article
CAV1 is a prognostic predictor for patients with idiopathic pulmonary fibrosis and lung cancer
DONGDONG YIN JIAYANG QIU SUXIA HU LONGQIANG CHENG HUI LI XINGPU CHENG SHUN WANG JUN LU
The extremely high mortality of both lung cancer and Idiopathic pulmonary fibrosis (IPF) is a global threat. Early detection and diagnosis can reduce their mortality. Since fibrosis is a necessary process of cancer, identifying the common potential prognostic genes involved in these two diseases will significantly contribute to disease prevention and targeted therapy. Microarray datasets of IPF and lung cancer were extracted from the GEO database. GEO2R was exploited to retrieve the differentially expressed genes (DEGs). The intersecting DEGs were obtained by the Venn tool. DAVID tools were used to perform GO and KEGG pathway enrichment analysis of DEGs. Then, the Kaplan–Meier plotter was employed to determine the prognostic value and verify the expression, pathological stage, and phosphorylation level of the hub gene in the TCGA and GTEx database. Finally, the extent of immune cell infiltration in lung cancer was estimated by the TIMER2 tool. The Venn diagram revealed 1 upregulated gene and 15 downregulated genes from GSE32863, GSE43458, GSE118370, and GSE75037 of lung cancer, as well as GSE2052 and GSE53845 of IPF. CytoHubba identified the top three genes [TEK receptor tyrosine kinase (TEK), caveolin 1 (CAV1), and endomucin (EMCN)] as hub genes following the connectivity degree. Survival analysis claimed the association of only TEK and CAV1 expression to both overall survival (OS) and first progression (FP). Pathological stage analyses revealed the relationship of only CAV1 expression to the pathological stage and the significant correlation of only CAV1 phosphorylation expression level for lung cancer. Furthermore, a statistically positive correlation was observed between the immune infiltration of cancer-associated fibroblasts, endothelial, and neutrophils with the CAV1 expression in lung cancer, whereas the contradictory result was noted for the immune infiltration of T cell follicular helper. Early detection and diagnostic potential of lung cancer are ameliorated by the combined selection of key genes among IPF and lung cancer.
Volume 48, 2023
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