BTN25-RV-Hayashizaki R4.indd

Cap analysis gene expression (CAGE) was introduced in 2003 as a method to determine transcription start sites on a genome-wide scale by isolating and sequencing short sequence tags originating from the 5′ end of RNA transcripts (1). Mapping these tags back to the reference genome identifies the transcription start sites from which the transcripts originated. CAGE relies on a cap-trapper system to capture full-length RNAs while avoiding rRNA and tRNA transcripts. First, an oligodT primer is used to reverse-transcribe poly-A terminated RNAs. Alternatively, a random primer can be used for RNAs without a poly-A tail, which may constitute almost half of the transcriptome (2). RNA/ DNA double-stranded hybrids that contain a mature mRNA are selected by biotinylating their 5′ cap structure, allowing capture by streptavidin-coated magnetic beads. Ligation of a linker sequence containing an MmeI recognition site to the 5′ end of the full-length cDNA creates a restriction site about 20 nucleotides downstream, producing a short CAGE tag starting at the 5′ end of eukaryotic mRNAs (3). CAGE tags that map just upstream of known genes may be derived from the corresponding full-length mRNAs, whereas others may reflect the existence of currently unknown transcription start sites or genes. Due to their short size, sequencing CAGE tags is more efficient at detecting transcription start sites than sequencing full-length cDNAs. In early CAGE experiments, the throughput of sequencers limited the achievable sequencing depth such that many CAGE tags were found only once in a given experiment. More recently, a new generation of sequencers excelling at high-throughput sequencing of short tags has enabled deep CAGE tag sequencing, generating upward of a million tags from a single experimental condition. The tag counts found in such experiments are typically much larger than one, allowing an accurate estimate of the cellular concentration of the RNA molecule corresponding to each CAGE tag. Deep CAGE thus detects both the transcription start site as well as its expression level, making it a unique tool in the analysis of transcriptional regulatory networks.