Cap analysis gene expression (CAGE) is a high-throughput, tag-based method designed to survey the 5' end of capped full-length cDNAs. CAGE has previously been used to define global transcription start site usage and monitor gene activity in mammals. A drawback of the CAGE approach thus far has been the removal of as many as 40% of CAGE sequence tags due to their mapping to multiple genomic locations. Here, we address the origins of multimap tags and present a novel strategy to assign CAGE tags to their most likely source promoter region. When this approach was applied to the FANTOM3 CAGE libraries, the percentage of protein-coding mouse transcriptional frameworks detected by CAGE improved from 42.9 to 57.8% (an increase of 5516 frameworks) with no reduction in CAGE to microarray correlation. These results suggest that the multimap tags produced by high-throughput, short sequence tag-based approaches can be rescued to augment greatly the transcriptome coverage provided by single-map tags alone.