- Cap Analysis of Gene Expression (CAGE) is a high-throughput sequencing-based technique used to identify transcription start sites (TSSs) and measure gene expression levels at a genome-wide scale.
- The method takes advantage of a unique feature of eukaryotic messenger RNAs: the presence of a 7-methylguanosine cap at their 5′ end. By selectively capturing these capped RNA molecules, CAGE allows researchers to pinpoint the exact nucleotide where transcription begins, offering a precise map of promoter usage and transcriptional regulation.
- Unlike traditional RNA sequencing, which often focuses on the whole transcript, CAGE is specifically designed to analyze the very beginning of transcripts, providing insights into promoter architecture and the diversity of transcript isoforms generated from a single gene.
- The process begins with the isolation of RNA molecules carrying the 5′ cap structure. These capped RNAs are reverse transcribed into complementary DNA (cDNA), but instead of sequencing the entire cDNA, CAGE focuses on generating short tags (typically 20–30 base pairs) from the 5′ end. These tags are then sequenced using next-generation sequencing platforms and mapped back to the reference genome. The clustering of mapped tags reveals active transcription start sites and their relative usage across different conditions or cell types. Because each tag corresponds to an individual RNA molecule, the abundance of tags at a given TSS provides a quantitative measure of gene expression.
- CAGE has proven to be a powerful tool in functional genomics, enabling the discovery of novel promoters, alternative transcription initiation events, and regulatory elements such as enhancers. The technique has been widely used in large-scale projects like FANTOM (Functional Annotation of Mammalian Genomes), which have generated comprehensive promoter atlases for multiple species.
- By combining promoter mapping with expression quantification, CAGE offers unique insights into transcriptional networks and their dynamics in development, disease, and environmental responses. This makes it particularly valuable for understanding how genes are regulated at the very first step of transcription, offering a layer of resolution that conventional RNA-seq or microarray methods cannot provide.
