Whole-body transcriptome mining for candidate effectors from Diuraphis noxia

Proteins within aphid saliva play a crucial role as the molecular interface between aphids and their host plants. These salivary effectors modulate plant responses to favour aphid feeding and facilitate infestation. The identification of effectors from economically important pest species is central in understanding the molecular events during the aphid-plant interaction. The Russian wheat aphid (Diuraphis noxia, Kurdjumov) is one such pest that causes devastating losses to wheat and barley yields worldwide. Despite the severe threat to food security posed by D. noxia, the non-model nature of this pest and its host has hindered progress towards understanding this interaction. In this study, in the absence of a salivary gland transcriptome, whole-body transcriptomics data was mined to generate a candidate effector catalogue for D. noxia.

Mining the transcriptome identified 725 transcripts encoding putatively secreted proteins amongst which were transcripts specific to D. noxia. Six of the seven examined D. noxia putative effectors, termed DnE's (Diuraphis noxia effectors) exhibited salivary gland-specific expression. A comparative analysis between whole-body D. noxia transcriptome data versus the head and body transcriptomes from three other aphid species allowed us to define a catalogue of transcripts putatively upregulated in D. noxia head tissue. Five of these were selected for RT-qPCR confirmation, and were found to corroborate the differential expression predictions, with a further three confirmed to be highly expressed in D. noxia salivary gland tissue.

Determining a putative effector catalogue for D. noxia from whole-transcriptome data, particularly the identification of salivary-specific sequences potentially unique to D. noxia, provide the basis for future functional characterisation studies to gain further insight into this aphid-plant interaction. Furthermore, due to a lack of publicly available aphid salivary gland transcriptome data, the capacity to use comparative transcriptomics to compile a list of putative effector candidates from whole-body transcriptomics data will further the study of effectors in various aphid species.