PsRNA: A Computing Engine for the Comparative Identification of Putative Small RNA Locations within Intergenic Regions

Sridhar, Jayavel; Sowmiya, Govindaraj; Sekar, K.; Rafi, Ziauddin Ahamed

doi:10.1016/s1672-0229(10)60014-9

Cited by 7 publications

(4 citation statements)

References 23 publications

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“…in/psrna/). 55 The PsRNA method is applicable solely for the comparative analysis of a known sRNA group among related genomes. It cannot be used for the identification of 'novel' sRNA groups.…”

Section: Transcriptional Signal-based Methodsmentioning

confidence: 99%

“…PsRNA server was tested with the 22 enterobacterial genomes and is currently available online (http://bioserver1.physics.iisc.ernet.in/psrna/). 55 The PsRNA method is applicable solely for the comparative analysis of a known sRNA group among related genomes. It cannot be used for the identification of ‘novel’ sRNA groups.…”

Section: Transcriptional Signal-based Methodsmentioning

confidence: 99%

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Computational Small RNA Prediction in Bacteria

Sridhar

Gunasekaran

2013

Bioinform Biol Insights

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Bacterial, small RNAs were once regarded as potent regulators of gene expression and are now being considered as essential for their diversified roles. Many small RNAs are now reported to have a wide array of regulatory functions, ranging from environmental sensing to pathogenesis. Traditionally, noncoding transcripts were rarely detected by means of genetic screens. However, the availability of approximately 2200 prokaryotic genome sequences in public databases facilitates the efficient computational search of those molecules, followed by experimental validation. In principle, the following four major computational methods were applied for the prediction of sRNA locations from bacterial genome sequences: (1) comparative genomics, (2) secondary structure and thermodynamic stability, (3) ‘Orphan’ transcriptional signals and (4) ab initio methods regardless of sequence or structure similarity; most of these tools were applied to locate the putative genomic sRNA locations followed by experimental validation of those transcripts. Therefore, computational screening has simplified the sRNA identification process in bacteria. In this review, a plethora of small RNA prediction methods and tools that have been reported in the past decade are discussed comprehensively and assessed based on their attributes, compatibility, and their prediction accuracy.

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Section: Transcriptional Signal-based Methodsmentioning

confidence: 99%

Section: Transcriptional Signal-based Methodsmentioning

confidence: 99%

Computational Small RNA Prediction in Bacteria

Sridhar

Gunasekaran

2013

Bioinform Biol Insights

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“…The first mature miRNA from the PmiREM server ( https://www.pmiren.com/ ) was used to determine the target site of chilli's 11 CaZHD gene family. The CDS of the 11 genes was then compared to the mature miRNA using the PsRNA online server tool ( https://www.zhaolab.org/psRNATarget/ ) using the default setting [ 32 ]. Using the Cytoscape program ( https://www.omicshare.com/tools/ ), a connection between the predicted miRNA was created [ 29 , 30 ].…”

Section: Methodsmentioning

confidence: 99%

In silico and computational analysis of zinc finger motif-associated homeodomain (ZF-HD) family genes in chilli (Capsicum annuum L)

Islam,

Nupur,

Shafiq

et al. 2023

BMC Genomics

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Zinc finger-homeodomain (ZHD) proteins are mostly expressed in plants and are involved in proper growth and development and minimizing biotic and abiotic stress. A recent study identified and characterized the ZHD gene family in chilli (Capsicum annuum L.) to determine their probable molecular function. ZHD genes with various physicochemical characteristics were discovered on twelve chromosomes in chilli. We separated ZHD proteins into two major groups using sequence alignment and phylogenetic analysis. These groups differ in gene structure, motif distribution, and a conserved ZHD and micro-zinc finger ZF domain. The majority of the CaZHDs genes are preserved, early duplication occurred recently, and significant pure selection took place throughout evolution, according to evolutionary study. According to expression profiling, the genes were found to be equally expressed in tissues above the ground, contribute to plant growth and development and provide tolerance to biotic and abiotic stress. This in silico analysis, taken as a whole, hypothesized that these genes perform distinct roles in molecular and phytohormone signaling processes, which may serve as a foundation for subsequent research into the roles of these genes in other crops.

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“…The multiple sequence comparison of the miR-16a target site was also reported using the TargetScan prediction tools. The potential binding sites of bta-miRNA-16a targeting the BCoV genomes were predicted using three online miRNA target prediction tools, including RNA22 v2 (https://cm.jefferson.edu/rna22/), miRanda (25), and psRNA (26). The targeted site selection was based on the minimum free energy and the complementarity between the miRNA seed region and the viral genes binding sites (nucleotide 2-8 on candidate miRNAs).…”

Section: In Silico Mirna Target Gene Predictionmentioning

confidence: 99%

The dual actions of the host miRNA-16a in restricting Bovine coronavirus (BCoV) replication through targeting host cell Furin and in enhancing the host immune response

Shah,

Hemida

2024

Preprint

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The roles of host cell miRNAs have not been studied well in the context of BCoV replication and immune regulation. The main aim of this study was to identify some miRNA candidates that regulate essential host genes involved in BCoV replication, tissue tropism, and immune regulation. To achieve these goals, we used two isolates of BCoV (enteric and respiratory) to infect the bovine endothelial cells (BEC) and Madine Darby Bovine Kidney (MDBK) cells. This is in addition to the ex vivo model using the peripheral bovine blood mononuclear cells (PBMC). We determined the miRNA expression profiles in these cells after BCoV infection. miRA-16a is one of the differentially altered during BCoV infection. Our data shows that miRNA-16a is a significantly downregulated miRNA in both in vitro and ex vivo models. We confirmed the miRNA-16a expression profile by the qRT-PCR. Overexpression of the pre-miRNA-16a in BEC and MDBK cell lines resulted in marked inhibition of BCoV infection based on the viral genome copy numbers measured by qRT-PCR, the viral protein expression (S and N) measured by Western blot, and the virus infectivity using plaque assay. Our bioinformatic prediction showed that Furin is a potential target for the miRNA-16a. We checked the Furin protein expression level in the pre-miRNA-16a transfected/BCoV infected cells compared to the pre-miRNA scrambled to validate that. Our data shows marked inhibition of the Furin expression levels on the mRNA levels by qRT-PCR and the protein level by Western blot. The BCoV-S protein expression was markedly inhibited on both the mRNA and protein levels. To further confirm the impacts of the downregulation of the Furin enzyme on the replication of BCoV, we used transfected cells with specific Furin-siRNA parallel to the scrambled siRNA. A marked inhibition of BCoV replication was observed in the Furin-siRNA-treated group. To further validate Furin as a novel target for miRNA-16a, we cloned the 3'UTR of the bovine Furin carrying the seed region of the miRNA-16a in the dual luciferase vector. Our data shows luciferase activity in the pre-miRNA-16a transfected cells decreased by more than 50% compared to the cells transfected with the construct carrying the mutated Furin seed region. Our data confirms miRNA-16a inhibits BCoV replication by targeting the host cell Furin and the BCoV-S glycoprotein. It will also enhance the host immune response, which contributes to the inhibition of viral replication. To our knowledge, this is the first study to confirm that Furin is a valid target for the miRNA-16a. Our findings highlight the clinical applications of the host miRNA-16a as a potential miRNA-based vaccine/antiviral therapy.

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PsRNA: A Computing Engine for the Comparative Identification of Putative Small RNA Locations within Intergenic Regions

Cited by 7 publications

References 23 publications

Computational Small RNA Prediction in Bacteria

Computational Small RNA Prediction in Bacteria

In silico and computational analysis of zinc finger motif-associated homeodomain (ZF-HD) family genes in chilli (Capsicum annuum L)

The dual actions of the host miRNA-16a in restricting Bovine coronavirus (BCoV) replication through targeting host cell Furin and in enhancing the host immune response

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