De novo Assembly and Characterization of the Global Transcriptome for Rhyacionia leptotubula Using Illumina Paired-End Sequencing

Background: The pine tip moth, Rhyacionia leptotubula (Lepidoptera: Tortricidae) is one of the most destructive forestry pests in Yunnan Province, China. Despite its importance, less is known regarding all aspects of this pest. Understanding the genetic information of it is essential for exploring the specific traits at the molecular level. Thus, we here sequenced the transcriptome of R. leptotubula with high-throughput Illumina sequencing. Methodology/Principal Findings: In a single run, more than 60 million sequencing reads were generated. De novo assembling was performed to generate a collection of 46,910 unigenes with mean length of 642 bp. Based on Blastx search with an E-value cut-off of 10(-5), 22,581 unigenes showed significant similarities to known proteins from National Center for Biotechnology Information (NCBI) non-redundant (Nr) protein database. Of these annotated unigenes, 10,360, 6,937 and 13,894 were assigned to Gene Ontology (GO), Clusters of Orthologous Group (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. A total of 5,926 unigenes were annotated with domain similarity derived functional information, of which 55 and 39 unigenes respectively encoding the insecticide resistance related enzymes, cytochrome P450 and carboxylesterase. Using the transcriptome data, 47 unigenes belonging to the typical "stress" genes of heat shock protein (Hsp) family were retrieved. Furthermore, 1,450 simple sequence repeats (SSRs) were detected; 3.09% of the unigenes contained SSRs. Large numbers of SSR primer pairs were designed and out of randomly verified primer pairs 80% were successfully yielded amplicons. Conclusions/Significance: A large of putative R. leptotubula transcript sequences has been obtained from the deep sequencing, which extensively increases the comprehensive and integrated genomic resources of this pest. This large-scale transcriptome dataset will be an important information platform for promoting our investigation of the molecular mechanisms from various aspects in this species.