Project description:The extraocular muscles (EOM) are anatomically and physiologically distinct from other skeletal muscles. EOM are preferentially affected in mitochondrial myopathies, but spared in Duchenne's muscular dystrophy. The anatomical and pathophysiological properties of EOM have been attributed to their unique molecular makeup: an allotype. We used expression profiling to define molecular features of the EOM allotype. We found 346 differentially expressed genes in rat EOM compared with tibialis anterior, based on a twofold difference cutoff. Genes required for efficient, fatigue-resistant, oxidative metabolism were increased in EOM, whereas genes for glycogen metabolism were decreased. EOM also showed increased expression of genes related to structural components of EOM such as vessels, nerves, mitochondria, and neuromuscular junctions. Additionally, genes related to specialized functional roles of EOM such as the embryonic and EOM-specific myosin heavy chains and genes for muscle growth, development, and/or regeneration were increased. The EOM expression profile was validated using biochemical, structural, and molecular methods. Characterization of the EOM expression profile begins to define gene transcription patterns associated with the unique anatomical, metabolic, and pathophysiological properties of EOM.
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.
