Author(s): ARRAES, F. B. M.; MARTINS-DE-SA, D; VASQUEZ, D. D. N.; MELO, B. P.; FAHEEM, M.; MACEDO, L. L. P. de; MORGANTE, C. V.; BARBOSA, J. A. R. G.; TOGAWA, R. C.; MOREIRA, V. J. V.; DANCHIN, E. G. J.; SA, M. F. G. de

Summary: RNA interference (RNAi)-mediated gene silencing can be used to control specific insect pest populations. Unfortunately, the variable efficiency in the knockdown levels of target genes has narrowed the applicability of this technology to a few species. Here, we examine the current state of knowledge regarding the miRNA (micro RNA) and siRNA (small interfering RNA) pathways in insects and investigate the structural variability at key protein domains of the RNAi machinery. Our goal was to correlate domain variability with mechanisms affecting the gene silencing efficiency. To this end, the protein domains of 168 insect species, encompassing the orders Coleoptera, Diptera, Hemiptera, Hymenoptera, and Lepidoptera, were analysed using our pipeline, which takes advantage of meticulous structure-based sequence alignments. We used phylogenetic inference and the evolutionary rate coefficient (K) to outline the variability across domain regions and surfaces. Our results show that four domains, namely dsrm, Helicase, PAZ and Ribonuclease III, are the main contributors of protein variability in the RNAi machinery across different insect orders. We discuss the potential roles of these domains in regulating RNAi-mediated gene silencing and the role of loop regions in fine-tuning RNAi efficiency. Additionally, we identified several order-specific singularities which indicate that lepidopterans have evolved differently from other insect orders, possibly due to constant coevolution with plants and viruses. In conclusion, our results highlight several variability hotspots that deserve further investigation in order to improve the application of RNAi technology in the control of insect pests.

Publication year: 2021

Types of publication: Journal article

Unit: Embrapa Semi-arid Region

Keywords: Argonaute, Controle Genético, DCR1, Dicer, Drosha, DsRBDs, Evolução da proteína, Genoma, In silico analysis, Insect control, Inseto, Loquacious, Pasha, Pest control, Praga, Protein evolution, Protein structure, Proteins, Proteína, R2D2, RIIID II, Sequência de proteínas inteira, Structure-function relationship