RESUMEN
BACKGROUND: Thrips tabaci is a severe pest of onion and cotton. Due to lack of information on its genome or transcriptome, not much is known about this insect at the molecular level. To initiate molecular studies in this insect, RNA was sequenced; de novo transcriptome assembly and analysis were performed. The RNAseq data was used to identify reference and RNAi pathway genes in this insect. Additionally, feeding RNAi was demonstrated in T. tabaci for the first time. RESULTS: From the assembled transcriptome, 27,836 coding sequence (CDS) with an average size of 1236 bp per CDS were identified. About 85.4% of CDS identified showed positive Blast hits. The homologs of most of the core RNAi machinery genes were identified in this transcriptome. To select reference genes for reverse-transcriptase real-time quantitative PCR (RT-qPCR) experiments, 14 housekeeping genes were identified in the transcriptome and their expression was analyzed by (RT-qPCR). UbiCE in adult, 28s in nymphs and SOD under starvation stress were identified as the most stable reference genes for RT-qPCR. Feeding dsSNF7 and dsAQP caused 16.4- and 14.47-fold reduction in SNF7 and AQP mRNA levels respectively, when compared to their levels in dsGFP fed control insects. Feeding dsSNF7 or dsAQP also caused 62 and 72% mortality in T. tabaci. Interestingly, simultaneous feeding of dsRNAs targeting SNF7 or AQP and one of the RNAi pathway genes (Dicer-2/Aubergine/Staufen) resulted in a significant reduction in RNAi of target genes. These data suggest the existence of robust RNAi machinery in T. tabaci. CONCLUSION: The current research is the first report of the assembled, analyzed and annotated RNAseq resource for T. tabaci, which may be used for future molecular studies in this insect. Reference genes validated across stages and starvation stress provides first-hand information on stable genes in T. tabaci. The information on RNAi machinery genes and significant knockdown of the target gene through dsRNA feeding in synthetic diet confirms the presence of efficient RNAi in this insect. These data provide a solid foundation for further research on developing RNAi as a method to manage this pest.