A comprehensive transcriptome analysis has been performed on protein-coding RNAs of Strongylocentrotus purpuratus, including 10 different embryonic stages, six feeding larval and metamorphosed juvenile stages, and six adult tissues. In this study, we pooled the transcriptomes from all of these sources and focused on the insights they provide for gene structure in the genome of this recently sequenced model system. The genome had initially been annotated by use of computational gene model prediction algorithms. A large fraction of these predicted genes were recovered in the transcriptome when the reads were mapped to the genome and appropriately filtered and analyzed. However, in a manually curated subset, we discovered that more than half the computational gene model predictions were imperfect, containing errors such as missing exons, prediction of nonexistent exons, erroneous intron/exon boundaries, fusion of adjacent genes, and prediction of multiple genes from single genes. The transcriptome data have been used to provide a systematic upgrade of the gene model predictions throughout the genome, very greatly improving the research usability of the genomic sequence. We have constructed new public databases that incorporate information from the transcriptome analyses. The transcript-based gene model data were used to define average structural parameters for S. purpuratus protein-coding genes. In addition, we constructed a custom sea urchin gene ontology, and assigned about 7000 different annotated transcripts to 24 functional classes. Strong correlations became evident between given functional ontology classes and structural properties, including gene size, exon number, and exon and intron size.