In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus

Ashraf, Muhammad Aleem; Feng, Xiaoyan; Hu, Xiaowen; Ashraf, Fakiha; Shen, Lin; Iqbal, Muhammad Shahzad; Zhang, Shuzhen

doi:10.1371/journal.pone.0261807

Cited by 17 publications

(18 citation statements)

References 63 publications

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“…The ICMV-Ker is a bipartite begomovirus that spread to India and nearby locales in Southeast Asia during the past two decades. Several studies have investigated potential endogenous host-plant mature microRNAs that may target plant viruses based on in silico criteria [ 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ]. The miRNAs have evolved as key endogenous biomolecules for regulating gene expression.…”

Section: Discussionmentioning

confidence: 99%

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Ashraf

Ali

Brown

et al. 2023

Viruses

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Cassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA–mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants.

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Section: Discussionmentioning

confidence: 99%

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Ashraf

Ali

Brown

et al. 2023

Viruses

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“…In the current study, we have designed an effective computational approach for the validation of miRNA target prediction results by utilizing RNA22, miRanda and RNAhybrid different algorithms with default parameters. These algorithms proposed an effective method to recognize the possible host-derived miRNA targets in virus genomes (Ashraf et al, 2020;Ashraf et al, 2022). The RNA22 is an algorithm for exploring new miRNA-mRNA interactions because of its unique capabilities-although it has a high likelihood of generating false-positive results (Riffo-Campos Á.L et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Prediction of Site Directed miRNAs as Key Players of Transcriptional Regulators Against Influenza C Virus Infection Through Computational Approaches

Hassan

Iqbal

Naqvi

et al. 2022

Front. Mol. Biosci.

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MicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in gene expression, cell differentiation, and immunity against viral infections. In this study, we have used the computational tools, RNA22, RNAhybrid, and miRanda, to predict the microRNA-mRNA binding sites to find the putative microRNAs playing role in the host response to influenza C virus infection. This computational research screened the following four miRNAs: hsa-mir-3155a, hsa-mir-6796-5p, hsa-mir-3194-3p and hsa-mir-4673, which were further investigated for binding site prediction to the influenza C genome. Moreover, multiple sites in protein-coding region (HEF, CM2, M1-M2, NP, NS1- NS2, NSF, P3, PB1 and PB2) were predicted by RNA22, RNAhybrid and miRanda. Furthermore, 3D structures of all miRNAs and HEF were predicted and checked for their binding potential through molecular docking analysis. The comparative results showed that among all proteins, HEF is higher in prevalence throughout the analysis as a potential (human-derived) microRNAs target. The target-site conservation results showed that core nucleotide sequence in three different strains is responsible for potential miRNA binding to different viral strains. Further steps to use these microRNAs may lead to new therapeutic insights on fighting influenza virus infection.

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“…In the previous studies on host-virus interaction, in silico algorithms were used to study the potato virus Y (PVY) [24], and maize chlorotic mottle virus (MCMV) [25]. We have designed the similar studies against sugarcane viruses using computational algorithms to understand the host-virus interaction as well finding the best target in our previous research [26][27][28].…”

Section: Discussionmentioning

confidence: 99%

Computational Biology and Machine Learning Approaches to Identify the Rubber Tree (Hevea brasiliensis L.) Genome Encoded Potential MicroRNAs Targeting Rubber Tree Virus 1

Ashraf¹,

Tariq²,

Khan³

et al. 2022

Preprint

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Tapping panel dryness (TPD) syndrome is a complex disease of Rubber tree (Hevea brasiliensis L.) which causes cessation of latex drainage upon tapping of rubber tree. Rubber tree virus (RTV1) was identified as a novel pathogen associated with rubber tree and a potential causal agent of TPD. RTV1 is a monopartite RNA virus that is linear, non-enveloped and has a single-stranded (ss) positive RNA genome of approximately 6081 nucleotides and is composed of two major open reading frames (ORFs), ORF1 (polyprotein), and ORF2 (movement protein. This study aimed to investigate the possibility of rubber genome encoded tree microRNAs (miRNAs) as novel therapeutic targets against RTV1 using in silico algorithms. Mature rubber tree miRNAs are retrieved from the miRBase database and are used for hybridization of RTV1 using five different five different computational algorithms including miRanda, RNA22, RNAhybrid and psRNATarget. A total of eleven common rubber tree miRNAs were identified based on consensus genomic positions. The consensus of four algorithms predicted the hybridization sites of hbr-miR396a and hbr-miR398 at common locus positions 6676, 1840 respectively. To validate the prediction, secondary structures of the consensual rubber tree miRNAs and free energy of duplex binding were calculated using the RNAfold and RNAcofold algorithms respectively. We created a plot between rubber tree miRNAs and RTV1 ORFs by using Circos algorithm. In this study, we predicted eleven consensual rubber tree miRNAs. Among these miRNAs, hbr-miR398 was identified as the most effectual miRNA that may target the ORF1 gene of the RTV1 genome. The predicted data will be important in the development of rubber trees resistant to RTV1.

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In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus

Cited by 17 publications

References 63 publications

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Prediction of Site Directed miRNAs as Key Players of Transcriptional Regulators Against Influenza C Virus Infection Through Computational Approaches

Computational Biology and Machine Learning Approaches to Identify the Rubber Tree (Hevea brasiliensis L.) Genome Encoded Potential MicroRNAs Targeting Rubber Tree Virus 1

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