Transcriptomes

A transcriptome is the full range of RNA transcripts produced by the genome under specific conditions and at a given time. It includes messenger RNA, ribosomal RNA, transfer RNA, and a wide array of noncoding RNAs. The transcriptome reflects the gene expression state of a cell or tissue and can vary by tissue type, developmental stage, environment, and disease status. It is distinct from the genome, which is its static DNA sequence.

High-throughput sequencing, particularly RNA sequencing (RNA-seq), is the central method for transcriptome analysis. Libraries are prepared from total RNA or polyadenylated RNA and sequenced to yield short reads. Data are processed by aligning reads to a reference genome or performing de novo assembly, reconstructing transcripts, and estimating abundance in units such as TPM or counts. Downstream analyses include identifying differentially expressed genes, profiling alternative splicing, and discovering novel transcripts or noncoding RNAs. Expression quantification can be gene-level or transcript-level.

Applications include functional genomics, developmental biology, and disease research; benchmarking and annotation of genomes; discovery of diagnostic biomarkers and therapeutic targets; and comparative transcriptomics across species.

Limitations include the snapshot nature of measurements, sample heterogeneity, and sequence biases. Isoform complexity, repetitive regions, and incomplete reference annotations can complicate assembly and quantification. Experimental design, library preparation, and computational tools influence results.

Public data repositories such as the Gene Expression Omnibus, Sequence Read Archive, and ENCODE provide transcriptomic datasets and resources for reanalysis and meta-studies.