Transcriptomic profiling of LPS-treated and sham control mouse samples using RNA-seq
This study employs RNA sequencing to profile the transcriptomic landscape of a mouse model following lipopolysaccharide (LPS) challenge, a canonical trigger of systemic inflammation. By comparing three biological replicates each of LPS-treated and sham control groups, the research aims to dissect the comprehensive molecular response to innate immune activation. The primary goals are to identify and characterize key differentially expressed genes, unravel perturbed biological pathways (e.g., immune response, extracellular matrix organization), and discover regulatory events such as alternative splicing and genetic variants associated with the inflammatory state. Furthermore, advanced analyses including weighted gene co-expression network analysis (WGCNA) are applied to uncover core gene modules and hub genes that may drive the response. The relevance of this work lies in providing a detailed, multi-faceted genomic resource that elucidates fundamental mechanisms of inflammation, serving as a valuable reference for research into sepsis, autoimmune diseases, and other inflammatory conditions. The identified candidate genes, pathways, and regulatory networks offer potential targets for further functional validation and therapeutic development.