Abstract <p>Quantitative analysis of gene transcription is widely used across various fields of biology and, in particular, in medicine, it serves as a tool for diagnostics and transcriptomic profiling of diseases. In recent years, transcriptome analysis methods based on large-scale next-generation sequencing have become widely adopted. Transcriptomic studies enable the identification of cellular processes that are active at specific time points, the investigation of transcriptome dynamics in different tissues or physiological states (such as during ontogenesis or adaptive responses) and the detection of differentially expressed genes in pathological conditions. A pronounced change in the transcription level of one or more genes under pathological conditions may be sufficient for diagnosis, serving as a transcriptional biomarker of disease. However, in some cases, altered transcription levels may indicate the presence of mutations, including those leading to disruption of splicing, activation of mobile elements, or pseudogenes. This review discusses cases in which transcriptional changes can provide insights into the genetic causes of disease, as well as the challenges that must be considered when using transcription as a diagnostic marker. In the future, specialized targeted panels based on transcriptome analysis are expected to be used not only as diagnostic and prognostic tools, but also as predictors of structural genomic abnormalities, thereby contributing to the development of novel strategies for effective disease treatment.</p>