Project description:Right ventricular heart failure (RVF) associated with pulmonary hypertension (PH) is characterized by a distinct gene expression pattern when compared with functional compensatory hypertrophy. Carvedilol treatment after RVF has been established reduces right ventricle (RV) hypertrophy and improves the RV function. In addition, carvedilol treatment has been shown to alter the gene expression of select genes. We sought to identify, on a genome-wide basis, the effect of carvedilol on gene expression. RVF was induced in male Sprague-Dawley rats by the combination of VEGF-receptor blockade and chronic hypoxia; thereafter, one group was treated with carvedilol. RNA was isolated from the RV and subjected to microarray analysis. A prediction analysis of the carvedilol-treated RVs showed that carvedilol treated RVs most resembled in their expression pattern the RVF pattern. However, an analysis beyond the boundaries of the prediction set revealed a small set of genes associated with carvedilol reversal of RVF. Pathway analysis of this set of genes revealed expression changes of genes involved in cardiac hypertrophy, mitochondrial dysfunction, protein ubiquitination, and sphingolipid metabolism. Genes encoding proteins in the cardiac hypertrophy and protein ubiquitination pathways were downregulated in the RV by carvedilol, while genes encoding proteins in the mitochondrial dysfunction and sphingolipid metabolism pathways were upregulated by carvedilol.
Project description:Inflammation is a key component of pathological angiogenesis. Here we induce cornea neovascularisation using sutures placed into the cornea, and sutures are removed to induce a regression phase. We used whole transcriptome microarray to monitor gene expression profies of several genes
Project description:Living organisms are intricate systems with dynamic internal processes. Their RNA, protein, and metabolite levels fluctuate in response to variations in health and environmental conditions. Among these, RNA expression is particularly accessible for comprehensive analysis, thanks to the evolution of high throughput sequencing technologies in recent years. This progress has enabled researchers to identify unique RNA patterns associated with various diseases, as well as to develop predictive and prognostic biomarkers for therapy response. Such cross-sectional studies allow for the identification of differentially expressed genes (DEGs) between groups, but they have limitations. Specifically, they often fail to capture the temporal changes in gene expression following individual perturbations and may lead to significant false discoveries due to inherent noise in RNA sequencing sample preparation and data collection. To address these challenges, our study hypothesized that frequent, longitudinal RNA sequencing (RNAseq) analysis of blood samples could offer a more profound understanding of the temporal dynamics of gene expression in response to drug interventions, while also enhancing the accuracy of identifying genes influenced by these drugs. In this research, we conducted RNAseq on 829 blood samples collected from 84 Sprague-Dawley lab rats. Excluding the control group, each rat was administered one of four different compounds known for liver toxicity: tetracycline, isoniazid, valproate, and carbon tetrachloride. We developed specialized bioinformatics tools to pinpoint genes that exhibit temporal variation in response to these treatments.
Project description:Analysis of LBNF1 rat testes from controls, containing both somatic and all germ cell types and from irradiated rats in which all cells germ cells except type A spermatgogonia are eliminated. Results provide insight into distinguishing germ and somatic cell genes and identification of somatic cell genes that are upregulated after irradiation.