Genomic exploration of Bemisia tabaci microRNAs using predictive modeling and confirmation through experimental evidence

利用预测模型和实验证据对烟粉虱microRNA进行基因组探索

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Abstract

Bemisia tabaci is a globally recognized pest known for its invasiveness, resistance to many insecticides, and ability to transmit viral diseases in plants. While research has focused on its physiological and ecological adaptations, the role of epigenetic regulators, particularly small non-coding RNAs like miRNAs, remains largely unexplored and may be key to its resilience to stressors. So far, no reference B. tabaci miRNAs are reported. Identifying them will give valuable insights for understanding how these regulatory miRNAs influence biological functions, the mechanisms that lead to management failures and developing next-generation management strategies. To assess the novel miRNAs in B. tabaci, we thoroughly searched various public repositories, such as NCBI, ENSEMBL, and miRBase, to retrieve biological data. This study predicted 81 novel miRNAs in B. tabaci, 37 and 44 from its whole genome and transcriptome sequence data sets. We validated the principal features of these predicted miRNAs using a sensitive algorithm such as RNAfold and RNA families (Rfam). The target prediction of these miRNAs revealed that many are involved in molecular functions, such as signaling, transcriptional factor-activating kinases, and nucleotide-binding proteins. Stem-loop qPCR and small RNA sequencing of predicted miRNAs in the B. tabaci genome confirmed their presence and conservation in related species.

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