RNA-Seq is an important tool for understanding the molecular pathways underlying interactions between plants and agricultural pests, including vectors of damaging plant pathogens. Thus far, bulk RNA-Seq has been the main approach for non-model insects. This method relies on pooling large numbers of whole organisms or hundreds of individually dissected organs. The latter approach is logistically challenging, may introduce artefacts of handling and storage, and is hardly compatible with biological replication. Here, we tested an approach to generate transcriptomes of individual salivary glands and other low-input body tissues developed using whiteflies (Bemisia tabaci MEAM1) (Hemiptera: Aleyrodidae), which are major vectors of plant viruses. By comparing our outputs to published bulk RNA-Seq datasets for whole whitefly bodies and pools of salivary glands, we demonstrate that this approach recovers similar numbers of transcripts relative to bulk RNA-Seq in a tissue-specific manner, and for some metrics, exceeds performance of bulk tissue RNA-Seq. Libraries generated from individual salivary glands also yielded additional novel transcripts not identified in pooled salivary gland datasets, and had hundreds of enriched transcripts when compared with whole head tissues. We have then further tested this method using single salivary glands of infected and uninfected Diaphorina citri (Hemiptera: Liviidae) Overall, our study demonstrates that it is feasible to produce high quality, replicated transcriptomes of whitefly and psyllid salivary glands and other low input tissues. We anticipate that our approach will expand hypothesis-driven research on salivary glands of Hemipteran pests, thus enabling novel control strategies to disrupt feeding and virus transmission.
A reproducible and sensitive method for generating high-quality transcriptomes from single salivary glands of whiteflies and psyllids / Gebiola, Marco; Le, Brandon H.; Mauck, Kerry E.. - (2022). (Intervento presentato al convegno Entomological Society of America Pacific Branch 106th annual meeting tenutosi a Santa Rosa, CA, USA nel 12 aprile 2022).
A reproducible and sensitive method for generating high-quality transcriptomes from single salivary glands of whiteflies and psyllids.
Marco Gebiola;
2022
Abstract
RNA-Seq is an important tool for understanding the molecular pathways underlying interactions between plants and agricultural pests, including vectors of damaging plant pathogens. Thus far, bulk RNA-Seq has been the main approach for non-model insects. This method relies on pooling large numbers of whole organisms or hundreds of individually dissected organs. The latter approach is logistically challenging, may introduce artefacts of handling and storage, and is hardly compatible with biological replication. Here, we tested an approach to generate transcriptomes of individual salivary glands and other low-input body tissues developed using whiteflies (Bemisia tabaci MEAM1) (Hemiptera: Aleyrodidae), which are major vectors of plant viruses. By comparing our outputs to published bulk RNA-Seq datasets for whole whitefly bodies and pools of salivary glands, we demonstrate that this approach recovers similar numbers of transcripts relative to bulk RNA-Seq in a tissue-specific manner, and for some metrics, exceeds performance of bulk tissue RNA-Seq. Libraries generated from individual salivary glands also yielded additional novel transcripts not identified in pooled salivary gland datasets, and had hundreds of enriched transcripts when compared with whole head tissues. We have then further tested this method using single salivary glands of infected and uninfected Diaphorina citri (Hemiptera: Liviidae) Overall, our study demonstrates that it is feasible to produce high quality, replicated transcriptomes of whitefly and psyllid salivary glands and other low input tissues. We anticipate that our approach will expand hypothesis-driven research on salivary glands of Hemipteran pests, thus enabling novel control strategies to disrupt feeding and virus transmission.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.