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Background  Recent studies indicate that infestations of psocids pose a new risk for global food security. Among the psocids species,  Liposcelis bostrychophila  Badonnel has gained recognition in importance because of its parthenogenic reproduction, rapid adaptation, and increased worldwide distribution. To date, the molecular data available for  L .  bostrychophila  is largely limited to genes identified through homology. Also, no transcriptome data relevant to psocids infection is available.    Methodology and Principal Findings  In this study, we generated  de novo  assembly of  L. bostrychophila  transcriptome performed through the short read sequencing technology (Illumina). In a single run, we obtained more than 51 million sequencing reads that were assembled into 60,012 unigenes (mean size = 711 bp) by Trinity. The transcriptome sequences from different developmental stages of  L. bostrychophila  including egg, nymph and adult were annotated with non-redundant (Nr) protein database, gene ontology (GO), cluster of orthologous groups of proteins (COG), and KEGG orthology (KO). The analysis revealed three major enzyme families involved in insecticide metabolism as differentially expressed in the  L. bostrychophila  transcriptome. A total of 49 P450-, 31 GST- and 21 CES-specific genes representing the three enzyme families were identified. Besides, 16 transcripts were identified to contain target site sequences of resistance genes. Furthermore, we profiled gene expression patterns upon insecticide (malathion and deltamethrin) exposure using the tag-based digital gene expression (DGE) method.    Conclusion  The  L. bostrychophila  transcriptome and DGE data provide gene expression data that would further our understanding of molecular mechanisms in psocids. In particular, the findings of this investigation will facilitate identification of genes involved in insecticide resistance and designing of new compounds for control of psocids.

Mining Genes Involved in Insecticide Resistance of Liposcelis bostrychophila Badonnel by Transcriptome and Expression Profile Analysis