Deep cap analysis gene expression (CAGE): genome-wide identification of promoters, quantification of their expression, and network inference

In cap analysis gene expression (CAGE), short(-20 nucleotide) sequence tags originating from the 5' end of full-length mRNAs are sequenced to identify transcription events on a genome-wide scale. The rapid increase in the throughput of present-day sequencers provides much deeper CAGE tag sequencing, where CAGE tags can be found multiple times for each mRNA in a given experiment. CAGE tag counts can then be used to reliably estimate the cellular concentration of the corresponding mRNA. In contrast to micro-array and SAGE expression profiling, CAGE identifies the location of each transcription start site hi addition to its expression level. This makes it possible for its to infer a genome-wide network of transcriptional regulation by searching the promoter region surrounding each CAGE-defined transcription start site for potential transcription factor binding sites. Hence, deep CAGE is a unique tool for the construction of a promoter-based network of transcriptional regulation. CAGE-based expression profiling also allows its to identify dynamic promoter usage in time-course experiments and the specific promoter regulated by a given transcription factor in disruption experiments. The sheer size of the short-tag datasets produced by modern sequencers spurs a need for new software development to handle the amount of data generated by next-generation sequencers. In addition, new visualization methods it-ill be needed to represent a promoter-based transcriptional network.