Databases of experimentally generated and computationally derived transcript sequences are valuable resources for genome analysis and annotation. The utility of such databases is enhanced when the sequences they contain are integrated with such biological information as genomic location, gene function, gene expression and phenotypic variation. We present the analysis and results of a semi-automated process of connecting transcript assemblies with highly curated biological information for mouse genes that is available through the Mouse Genome Informatics (MGI) database.