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Transcriptome Analysis of Gene Families Involved in Chemosensory Function in Spodoptera littoralis (Lepidoptera:
William B Walker1, Amit Roy2,3, Peter Anderson2
1Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Sundsvägen 14, 230 53, Alnarp, Sweden. william.b.walker.iii@slu.se.
Background:
Deciphering the molecular mechanisms mediating the chemical senses, taste, and smell has been of vital importance for understanding the nature of how insects interact with their chemical environment. Several gene families are implicated in the uptake, recognition, and termination of chemical signaling, including binding proteins, chemosensory receptors and degrading enzymes. The cotton leafworm, Spodoptera littoralis, is a phytophagous pest and current focal species for insect chemical ecology and neuroethology.
Results:
We produced male and female Illumina-based transcriptomes from chemosensory and non-chemosensory tissues of S. littoralis, including the antennae, proboscis, brain and body carcass. We have annotated 306 gene transcripts from eight gene families with known chemosensory function, including 114 novel candidate genes. Odorant receptors responsive to floral compounds are expressed in the proboscis and may play a role in guiding proboscis probing behavior. In both males and females, expression of gene transcripts with known chemosensory function, including odorant receptors and pheromone-binding proteins, has been observed in brain tissue, suggesting internal, non-sensory function for these genes.
Conclusions:
A well-curated set of annotated gene transcripts with putative chemosensory function is provided. This will serve as a resource for future chemosensory and transcriptomic studies in S. littoralis and closely related species. Collectively, our results expand current understanding of the expression patterns of genes with putative chemosensory function in insect sensory and non-sensory tissues. When coupled with functional data, such as the deorphanization of odorant receptors, the gene expression data can facilitate hypothesis generation, serving as a substrate for future studies.
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