Background: Gastropoda, with approximately 80,000 living species, is the largest class of Mollusca. Among gastropods, apple snails (family Ampullariidae) are globally distributed in tropical and subtropical freshwater ecosystems and many species are ecologically and economically important. Ampullariids exhibit various morphological and physiological adaptations to their respective habitats, which make them ideal candidates for studying adaptation, population divergence, speciation, and larger-scale patterns of diversity, including the biogeography of native and invasive populations. The limited availability of genomic data, however, hinders in-depth ecological and evolutionary studies of these non-model organisms. Results: Using Illumina Hiseq platforms, we sequenced 1220 million reads for seven species of apple snails. Together with the previously published RNA-Seq data of two apple snails, we conducted de novo transcriptome assembly of eight species that belong to five genera of Ampullariidae, two of which represent Old World lineages and the other three New World lineages. There were 20,730 to 35,828 unigenes with predicted open reading frames for the eight species, with N50 (shortest sequence length at 50% of the unigenes) ranging from 1320 to 1803 bp. 69.7% to 80.2% of these unigenes were functionally annotated by searching against NCBI's non-redundant, Gene Ontology database and the Kyoto Encyclopaedia of Genes and Genomes. With these data we developed AmpuBase, a relational database that features online BLAST functionality for DNA/protein sequences, keyword searching for unigenes/functional terms, and download functions for sequences and whole transcriptomes. Conclusions: In summary, we have generated comprehensive transcriptome data for multiple ampullariid genera and species, and created a publicly accessible database with a user-friendly interface to facilitate future basic and applied studies on ampullariids, and comparative molecular studies with other invertebrates.
Scopus Subject Areas
- (3 to 10) biological invasion
- Genomic database