The sugarcane borer (Diatraea saccharalis, Fabricius, 1794) is a devastating pest that causes millions of dollars of losses each year to sugarcane producers by reducing sugar and ethanol yields. The control of this pest is difficult due to its endophytic behavior and rapid development. Pest management through biotechnological approaches has emerged in recent years as an alternative to currently applied methods. Genetic information about the target pests is often required to perform biotechnology-based management. The genomic and transcriptomic data for D. saccharalis are very limited. Herein, we report a tissue-specific transcriptome of D. saccharalis larvae and a differential expression analysis highlighting the physiological characteristics of this pest in response to two different diets: sugarcane and an artificial diet. Sequencing was performed on the Illumina HiSeq 2000 platform, and a de novo assembly was generated. A total of 27,626 protein-coding unigenes were identified, among which 1,934 sequences were differentially expressed between treatments. Processes such as defence, digestion, detoxification, signaling, and transport were highly represented among the differentially expressed genes (DEGs). Furthermore, seven aminopeptidase genes were identified as candidates to encode receptors of Cry proteins, which are toxins of Bacillus thuringiensis used to control lepidopteran pests. Since plant-insect interactions have produced a considerable number of adaptive responses in hosts and herbivorous insects, the success of phytophagous insects relies on their ability to overcome challenges such as the response to plant defences and the intake of nutrients. In this study, we identified metabolic pathways and specific genes involved in these processes. Thus, our data strongly contribute to the knowledge advancement of insect transcripts, which can be a source of target genes for pest management.

The sugarcane giant borer (SGB), Telchin licus licus, is a pest that has strong economic relevance for sugarcane producers. Due to the endophytic behavior of the larva, current methods of management are inefficient. A promising biotechnological management option has been proposed based on RNA interference (RNAi), a process that uses molecules of double-stranded RNA (dsRNA) to specifically knock down essential genes and reduce insect survival. The selection of suitable target genes is often supported by omic sciences. Studies have shown that genes related to feeding adaptation processes are good candidates to be targeted by RNAi for pest management. Among those genes, esterases are highlighted because of their impact on insect development. In this study, the objective was to evaluate the transcriptome responses of the SGB's gut in order to provide curated data of genes that could be used for pest management by RNAi in future studies. Further, we validated the function of an esterase-coding gene and its potential as a target for RNAi-based control. We sequenced the gut transcriptome of SGB larvae by Illumina HiSeq and evaluated its gene expression profiles in response to different diets (sugarcane stalk and artificial diet). We obtained differentially expressed genes (DEGs) involved in detoxification, digestion, and transport, which suggest a generalist mechanism of adaptation in SGB larvae. Among the DEGs, was identified and characterized a candidate juvenile hormone esterase gene (Tljhe). We knocked down the Tljhe gene by oral delivery of dsRNA molecules and evaluated gene expression in the gut. The survival and nutritional parameters of the larvae were measured along the developmental cycle of treated insects. We found that the gene Tljhe acts as a regulator of feeding behavior. The knockdown of Tljhe triggered a forced starvation state in late larval instars that significantly reduced the fitness of the larvae. However, the mechanism of action of this gene remains unclear, and the correlation between the expression of Tljhe and the levels of juvenile hormone (JH) metabolites in the hemolymph of the SGB must be assessed in future research.