Large scale RNAi screen in Tribolium reveals novel target genes for pest control and the proteasome as prime target

• Published in: BMC genomics Vol. 16; no. 1; p. 674
• Main Authors: Ulrich, Julia, Dao, Van Anh, Majumdar, Upalparna, Schmitt-Engel, Christian, Schwirz, Jonas, Schultheis, Dorothea, Ströhlein, Nadi, Troelenberg, Nicole, Grossmann, Daniela, Richter, Tobias, Dönitz, Jürgen, Gerischer, Lizzy, Leboulle, Gérard, Vilcinskas, Andreas, Stanke, Mario, Bucher, Gregor
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 03.09.2015; BioMed Central
• Subjects: Analysis; Animals; Base Sequence; Cluster Analysis; Conserved Sequence; Gene Ontology; Genes, Insect; Genetic aspects; Genetically modified plants; Genomics; Methods; Pest Control, Biological; Proteasome Endopeptidase Complex - metabolism; RNA Interference; Tribolium - genetics
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-015-1880-y

Insect pest control is challenged by insecticide resistance and negative impact on ecology and health. One promising pest specific alternative is the generation of transgenic plants, which express double stranded RNAs targeting essential genes of a pest species. Upon feeding, the dsRNA induces gene silencing in the pest resulting in its death. However, the identification of efficient RNAi target genes remains a major challenge as genomic tools and breeding capacity is limited in most pest insects impeding whole-animal-high-throughput-screening. We use the red flour beetle Tribolium castaneum as a screening platform in order to identify the most efficient RNAi target genes. From about 5,000 randomly screened genes of the iBeetle RNAi screen we identify 11 novel and highly efficient RNAi targets. Our data allowed us to determine GO term combinations that are predictive for efficient RNAi target genes with proteasomal genes being most predictive. Finally, we show that RNAi target genes do not appear to act synergistically and that protein sequence conservation does not correlate with the number of potential off target sites. Our results will aid the identification of RNAi target genes in many pest species by providing a manageable number of excellent candidate genes to be tested and the proteasome as prime target. Further, the identified GO term combinations will help to identify efficient target genes from organ specific transcriptomes. Our off target analysis is relevant for the sequence selection used in transgenic plants.