transzkriptomika

Transzkriptomika, or transcriptomics, is the study of the transcriptome—the complete set of RNA transcripts produced by the genome under a given condition, in a specific cell type, tissue, or organism. It aims to measure which genes are expressed, at what levels, and how expression changes in response to internal or external stimuli.

Modern transcriptomics relies on high-throughput technologies. RNA sequencing (RNA-Seq) provides genome-wide, quantitative data on coding and noncoding RNAs. Microarrays, once common, are largely superseded by sequencing-based methods. In addition, long-read sequencing can resolve full-length isoforms, while single-cell transcriptomics (scRNA-Seq) profiles gene expression at the level of individual cells.

Analyses typically include quality control, alignment to a reference genome, and quantification of transcripts or genes. Data are normalized to account for sequencing depth and composition effects, followed by differential expression testing. Downstream steps include annotation, functional enrichment, and pathway or network analysis. Outputs include expression matrices, lists of differentially expressed genes, and transcript-level information.

Two main flavors exist: bulk transcriptomics, using RNA from many cells, and single-cell transcriptomics, which reveals cellular heterogeneity. Applications span basic biology, cancer research, immunology, developmental biology, neuroscience, and biomarker discovery for diagnosis or therapy monitoring.

Challenges include RNA quality, technical variability and batch effects, isoform complexity, and data interpretation. Standards and repositories such as MINSEQE, GEO, the Sequence Read Archive, and ENA support data sharing. Ongoing methodological advances continue to improve sensitivity, accuracy, and integration with other omics data.