<p><i>Mahanarva fimbriolata</i> (Distant 1909) (Hemiptera: Cercopidae) is a major pest that reduces forage production in Brazil, yet few viable control alternatives exist. The RNA interference (RNAi) gene silencing method is a specific and efficient approach that may aid the development of a sustainable management strategy for this pest. It is known that some genes involved in the RNAi machinery are lacking in certain Hemiptera species; therefore, verifying their presence in each target species is necessary. Here, transcriptome assembly of<i> Mahanarva fimbriolata</i> at different developmental stages (egg, nymph and adult stages) was performed, differentially expressed genes were identified, RNAi-related genes described in the literature were annotated in the transcriptome, and coexpression network modeling for the identification of potential RNAi targets was performed. The analysis revealed that the most significant differences in gene expression were between samples in the egg stage and samples in the other development stages. Enriched Gene Ontology terms related to insect growth (e.g., cell division, metamorphosis and flight) and corresponding pathways (e.g., DNA replication and glycolysis/gluconeogenesis) were identified. Coexpression networks demonstrated the importance of biosynthetic hormone processes within specific modules and revealed potential silencing targets, including hub genes such as RPB7 and Talin-2. Transcript annotation and analysis revealed more than 20 genes related to five major RNAi-related processes and factors (dsRNA cleavage, endonucleases, dsRNA binding, dsRNA transport and uptake, and auxiliary RISC-associated or regulatory factors). This work provides a comprehensive molecular overview of metamorphosis in <i>M. fimbriolata</i>, confirms the presence of active RNAi machinery, and reveals potential targets for future gene silencing approaches.</p>

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Comparative transcriptome analysis of developmental stages and characterization of core RNAi-related genes in the spittlebug Mahanarva fimbriolata

  • Isabela dos Santos Begnami,
  • Gustavo Fernando Ferreira Gonçalves,
  • Ricardo José Gonzaga Pimenta,
  • Aline da Costa Lima Moraes,
  • Wilson Malagó Júnior,
  • Marcos Rafael Gusmão,
  • Anete Pereira de Souza,
  • Bianca Baccili Zanotto Vigna

摘要

Mahanarva fimbriolata (Distant 1909) (Hemiptera: Cercopidae) is a major pest that reduces forage production in Brazil, yet few viable control alternatives exist. The RNA interference (RNAi) gene silencing method is a specific and efficient approach that may aid the development of a sustainable management strategy for this pest. It is known that some genes involved in the RNAi machinery are lacking in certain Hemiptera species; therefore, verifying their presence in each target species is necessary. Here, transcriptome assembly of Mahanarva fimbriolata at different developmental stages (egg, nymph and adult stages) was performed, differentially expressed genes were identified, RNAi-related genes described in the literature were annotated in the transcriptome, and coexpression network modeling for the identification of potential RNAi targets was performed. The analysis revealed that the most significant differences in gene expression were between samples in the egg stage and samples in the other development stages. Enriched Gene Ontology terms related to insect growth (e.g., cell division, metamorphosis and flight) and corresponding pathways (e.g., DNA replication and glycolysis/gluconeogenesis) were identified. Coexpression networks demonstrated the importance of biosynthetic hormone processes within specific modules and revealed potential silencing targets, including hub genes such as RPB7 and Talin-2. Transcript annotation and analysis revealed more than 20 genes related to five major RNAi-related processes and factors (dsRNA cleavage, endonucleases, dsRNA binding, dsRNA transport and uptake, and auxiliary RISC-associated or regulatory factors). This work provides a comprehensive molecular overview of metamorphosis in M. fimbriolata, confirms the presence of active RNAi machinery, and reveals potential targets for future gene silencing approaches.