The Quick Guide to RNA-Seq: From Data Acquisition to Functional Analysis

RNA sequencing (RNA-Seq) has revolutionized transcriptomics by enabling comprehensive and unbiased gene expression profiling across diverse biological contexts. This review summarizes the key stages of RNA-Seq, from RNA isolation and library preparation to sequencing technologies and computational analyses. We discuss the evolution of sequencing platforms, including second-generation short-read and third-generation long-read technologies, highlighting their applications and limitations. Critical steps such as quality control, read alignment, transcript assembly, normalization, and differential gene expression analysis are detailed, emphasizing the importance of tailored methodological choices and robust statistical approaches. Despite advances, challenges remain, including sequencing biases, errors, and variability introduced by diverse bioinformatic pipelines. Visualization techniques such as MA and volcano plots enhance the interpretation of expression changes. Overall, RNA-Seq remains a powerful tool for understanding gene regulation, alternative splicing, and disease mechanisms, with ongoing improvements needed for standardized, reproducible workflows to maximize biological insight.