Genome-Wide Identification of Cotton MicroRNAs Predicted for Targeting Cotton Leaf Curl Kokhran Virus-Lucknow

MICROBIOLOGY RESEARCH(2024)

引用 0|浏览1
暂无评分
摘要
Cotton leaf curl Kokhran virus (CLCuKoV) (genus, Begomovirus; family, Geminiviridae) is one of several plant virus pathogens of cotton (Gossypium hirsutum L.) that cause cotton leaf curl disease in Pakistan. Begomoviruses are transmitted by the whitefly Bemisia tabaci cryptic species group and cause economic losses in cotton and other crops worldwide. The CLCuKoV strain, referred to as CLCuKoV-Bur, emerged in the vicinity of Burewala, Pakistan, and was the primary causal virus associated with the second CLCuD epidemic in Pakistan. The monopartite ssDNA genome of (2.7 Kb) contains six open reading frames that encode four predicted proteins. RNA interference (RNAi)-mediated antiviral immunity is a sequence-specific biological process in plants and animals that has evolved to combat virus infection. The objective of this study was to design cotton locus-derived microRNA (ghr-miRNA) molecules to target strains of CLCuKoV, with CLCuKoV-Lu, as a typical CLCuD-begomovirus genome, predicted by four algorithms, miRanda, RNA22, psRNATarget, and RNA hybrid. Mature ghr-miRNA sequences (n = 80) from upland cotton (2n = 4x = 52) were selected from miRBase and aligned with available CLCuKoV-Lu genome sequences. Among the 80 cotton locus-derived ghr-miRNAs analyzed, ghr-miR2950 was identified as the most optimal, effective ghr-miRNA for targeting the CLCuKoV-Lu genome (nucleotide 82 onward), respectively, based on stringent criteria. The miRNA targeting relies on the base pairing of miRNA-mRNA targets. Conservation and potential base pairing of binding sites with the ghr-miR2950 were validated by multiple sequence alignment with all available CLCuKoV sequences. A regulatory interaction network was constructed to evaluate potential miRNA-mRNA interactions with the predicted targets. The efficacy of miRNA targeting of CLCuKoV was evaluated in silico by RNAi-mediated mRNA cleavage. This predicted targets for the development of CLCuD-resistant cotton plants.
更多
查看译文
关键词
computational algorithms,cotton leaf curl Kokhran virus,microRNA prediction,plant host-begomovirus interactions,RNA interference,target binding sites
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要