Abstract Background The pond snail Lymnaea stagnalis (L. stagnalis) has been widely used as a model organism in neurobiology, ecotoxicology, and parasitology due to the relative simplicity of its central nervous system (CNS). However, its usefulness is restricted by a limited availability of transcriptome data. While sequence information for the L. stagnalis CNS transcripts has been obtained from EST libraries and a de novo RNA-seq assembly, the quality of these assemblies is limited by a combination of low coverage of EST libraries, the fragmented nature of de novo assemblies, and lack of reference genome. Results In this study, taking advantage of the recent availability of a preliminary L. stagnalis genome, we generated an RNA-seq library from the adult L. stagnalis CNS, using a combination of genome-guided and de novo assembly programs to identify 17,832 protein-coding L. stagnalis transcripts. We combined our library with existing resources to produce a transcript set with greater sequence length, completeness, and diversity than previously available ones. Using our assembly and functional domain analysis, we profiled L. stagnalis CNS transcripts encoding ion channels and ionotropic receptors, which are key proteins for CNS function, and compared their sequences to other vertebrate and invertebrate model organisms. Interestingly, L. stagnalis transcripts encoding numerous putative Ca 2+ channels showed the most sequence similarity to those of Mus musculus , Danio rerio , Xenopus tropicalis , Drosophila melanogaster , and Caenorhabditis elegans , suggesting that many calcium channel-related signaling pathways may be evolutionarily conserved. Conclusions Our study provides the most thorough characterization to date of the L. stagnalis transcriptome and provides insights into differences between vertebrates and invertebrates in CNS transcript diversity, according to function and protein class. Furthermore, this study provides a complete characterization of the ion channels of Lymnaea stagnalis , opening new avenues for future research on fundamental neurobiological processes in this model system.