De novo sequencing and transcriptome analysis of the central nervous system of mollusc Lymnaea stagnalis by deep RNA sequencing.

Abstract

The pond snail Lymnaea stagnalis is among several mollusc species that have been well investigated due to the simplicity of their nervous systems and large identifiable neurons. Nonetheless, despite the continued attention given to the physiological characteristics of its nervous system, the genetic information of the Lymnaea central nervous system (CNS) has not yet been fully explored. The absence of genetic information is a large disadvantage for transcriptome sequencing because it makes transcriptome assembly difficult. We here performed transcriptome sequencing for Lymnaea CNS using an Illumina Genome Analyzer IIx platform and obtained 81.9 M of 100 base pair (bp) single end reads. For de novo assembly, five programs were used: ABySS, Velvet, OASES, Trinity and Rnnotator. Based on a comparison of the assemblies, we chose the Rnnotator dataset for the following blast searches and gene ontology analyses. The present dataset, 116,355 contigs of Lymnaea transcriptome shotgun assembly (TSA), contained longer sequences and was much larger compared to the previously reported Lymnaea expression sequence tag (EST) established by classical Sanger sequencing. The TSA sequences were subjected to blast analyses against several protein databases and Aplysia EST data. The results demonstrated that about 20,000 sequences had significant similarity to the reported sequences using a cutoff value of 1e-6, and showed the lack of molluscan sequences in the public databases. The richness of the present TSA data allowed us to identify a large number of new transcripts in Lymnaea and molluscan species.