fulltranscriptome

In genomics, the term full transcriptome refers to the complete set of RNA transcripts produced by the genome in a given cell, tissue, or condition. It includes protein-coding mRNAs, long and short noncoding RNAs, and other RNA species arising from transcriptional activity. The concept emphasizes all transcriptional products and isoforms rather than the underlying DNA sequence alone.

Measuring the full transcriptome relies on RNA sequencing technologies. Short-read bulk RNA-Seq quantifies transcript abundance but often struggles with full-length isoforms. Long-read platforms such as PacBio Iso-Seq or Oxford Nanopore capture full-length transcripts and improve isoform discovery. Single-cell RNA-Seq provides cell-level resolution but may sample only a subset of transcripts per cell.

Sample preparation shapes the observed transcriptome. Poly(A)-selection enriches mRNAs but misses non-polyadenylated RNAs; ribosomal RNA depletion or total RNA sequencing broadens coverage to include noncoding RNAs. Sequencing depth, read length, and replication influence detection of low-abundance and novel transcripts.

Data analysis aligns reads to a reference genome, then assembles transcripts and quantifies expression. Annotation-based workflows rely on existing transcript catalogs, while de novo assembly can reveal novel transcripts. Challenges include isoform complexity, overlapping genes, repetitive regions, and dynamic expression across tissues and time, which complicate reconstruction and interpretation.

Applications of full transcriptome profiling include mapping tissue-specific transcription, comparing healthy and diseased states, cataloging alternative splicing, and discovering novel noncoding RNAs. As sequencing and annotations improve, a comprehensive transcriptional landscape becomes more feasible, though complete catalogs remain an ongoing objective.