transcriptomica

Transcriptomics, often referred to as transcriptomica in Spanish and Portuguese, is the branch of molecular biology that studies the transcriptome—the complete set of RNA transcripts produced by the genome under defined conditions or in a particular cell or tissue. The goal is to measure gene expression, characterize transcript structure, and understand how transcription responds to biological stimuli, development, and disease.

Technologies used in transcriptomics are predominantly high-throughput. The most common method is RNA sequencing (RNA-Seq), which provides quantitative data on thousands of transcripts simultaneously. Earlier approaches included microarrays and expressed sequence tags, while newer long-read sequencing contributes to full-length transcript analysis. Data analysis typically involves preprocessing, alignment to a reference genome, transcript assembly and quantification, normalization (such as TPM or FPKM), and statistical testing for differential expression. Bioinformatic tools for quantification (e.g., Kallisto, Salmon) and for differential expression analysis (e.g., DESeq2, edgeR) are widely employed, along with pipelines for isoform-level analysis.

Applications of transcriptomics span development, physiology, and disease research. It supports the identification of tissue- and condition-specific expression patterns, the discovery of biomarkers, the study of regulatory programs and alternative splicing, and the investigation of non-coding RNAs. In oncology and other complex diseases, transcriptomic profiling helps classify subtypes, elucidate pathogenesis, and predict treatment response.

Challenges and scope include managing data variability and batch effects, ensuring robust normalization, dealing with incomplete annotations, and integrating transcriptomic data with other omics layers. Ethical considerations and data sharing practices are important in human studies. In English, the field is commonly called transcriptomics; transcriptomica is the term used in Spanish and Portuguese.