ArticlePloS one2022
In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- Computational identification and experimental validation of novelPlant signaling & behavior · 2025Article
- Genome Reconstruction of Grapevine Virus M and In Silico miRNA Prediction for Sequence-Specific Gene Silencing.Current microbiology · 2025Article
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- Comprehensive insights into the regulatory mechanisms of lncRNA in alkaline-salt stress tolerance in rice.Molecular biology reports · 2023Article
- Article
- Emerging and Re-Emerging Diseases Caused by Badnaviruses.Pathogens (Basel, Switzerland) · 2023Review
- Developing new sugarcane varieties suitable for mechanized production in China: principles, strategies and prospects.Frontiers in plant science · 2023Article
- Prediction of Site Directed miRNAs as Key Players of Transcriptional Regulators Against Influenza C Virus Infection Through Computational Approaches.Frontiers in molecular biosciences · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames (ORFs) are characterized in the circular, ds-DNA genome of the SCBV; these encode for a hypothetical protein (ORF1), a DNA binding protein (ORF2), and a polyprotein (ORF3). A comprehensive evaluation of sugarcane (Saccharum officinarum L.) miRNAs for the silencing of the SCBV genome using in silico algorithms were carried out in the present study using mature sugarcane miRNAs. miRNAs of sugarcane are retrieved from the miRBase database and assessed in terms of hybridization with the SCBV genome. A total of 14 potential candidate miRNAs from sugarcane were screened out by all used algorithms used for the silencing of SCBV. The consensus of three algorithms predicted the hybridization site of sof-miR159e at common locus 5534. miRNA-mRNA interactions were estimated by computing the free-energy of the miRNA-mRNA duplex using the RNAcofold algorithm. A regulatory network of predicted candidate miRNAs of sugarcane with SCBV-ORFs, generated using Circos-is used to identify novel targets. The predicted data provide useful information for the development of SCBV-resistant sugarcane plants.
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