scholarly journals Computational Identification of Dengue Virus MicroRNA-Like Structures and Their Cellular Targets

2014 ◽  
Vol 8 ◽  
pp. BBI.S13649 ◽  
Author(s):  
Maicol Ospina-Bedoya ◽  
Natalia Campillo-Pedroza ◽  
Juan P. Franco-Salazar ◽  
Juan C. Gallego-Gómez
Keyword(s):  
Dengue Virus ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Rna Virus ◽  
Mature Mirnas ◽  
Virus Genome ◽  
Support Vector ◽  
Direct Role ◽  
Cellular Targets ◽  
Small Noncoding Rna

MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate transcriptional and posttranscriptional gene regulation of the cell. Experimental evidence shows that miRNAs have a direct role in different cellular processes, such as immune function, apoptosis, and tumorigenesis. In a viral infection context, miRNAs have been connected with the interplay between host and pathogen, occupying a major role in pathogenesis. While numerous viral miRNAs from DNA viruses have been identified, characterization of functional RNA virus-encoded miRNAs and their potential targets is still ongoing. Here, we used an in silico approach to analyze dengue Virus genome sequences. Pre-miRNAs were extracted through VMir software, and the identification of putative pre-miRNAs and mature miRNAs was accessed using Support Vector Machine web tools. The targets were scanned using miRanda software and functionally annotated using ClueGo. Via computational tools, eight putative miRNAs were found to hybridize with numerous targets of morphogenesis, differentiation, migration, and growth pathways that may play a major role in the interaction of the virus and its host. Future approaches will focus on experimental validation of their presence and target messenger RNA genes to further elucidate their biological functions in human and mosquito cells.

scholarly journals Inhibition of Ebola Virus by Anti-Ebola miRNAs in silico

2016 ◽  
Vol 10 (06) ◽  
pp. 626-634 ◽  
Author(s):  
Zhabiz Golkar ◽  
Roshan Battaria ◽  
Donald G Pace ◽  
Omar Bagasra
Keyword(s):  
In Silico ◽  
Noncoding Rna ◽  
Ebola Virus ◽  
Mature Mirnas ◽  
Virus Genome ◽  
Immune Defense ◽  
The Body ◽  
Parasitic Infections ◽  
Rna Molecules ◽  
Small Noncoding Rna

Introduction: MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate transcriptional and posttranscriptional gene regulation of the organisms. miRNA provides immune defense when the body is faced with challenges intracellular agents. miRNA molecules trigger gene silencing in eukaryotic cells. More than 3,000 different human miRNAs (hsa-miRs) have been identified thus far. During ontogenesis, viral or intracellular parasitic infections, miRNAs are differentially expressed to protect the host from intracellular invaders. In a viral infection context, miRNAs have been connected with the interplay between host and pathogen, and occupy a major role in pathogenesis. Methodology: An in silico approach was used to analyze the four major Ebola Virus genome sequences including the recently characterized Ebola virus responsible for West African epidemic that has killed over 10,000 people. All totaled, 2,543 mature human miRNA sequences were retrieved through an miR-database, and the identification of mature miRNAs were aligned with full length sequences of the four major Ebola viruses via computational tools. Results: We identified 32 miRNAs that exhibited significant inhibitory capacity to block more than one EBV strains. miR-607 showed capacity to quell all four major EBVs. Ten putative miRNAs were found to have near perfect identity at seed sequences with numerous targets of Ebola virus that may completely degrade the viral transcripts. Conclusion: We hypothesize that a miRNA-based vaccine can quell Ebola virus infection. Future approaches will focus on validation of these miRNAs in quelling the Ebola virus to further elucidate their biological functions in primate and other animal models.

scholarly journals PERAN GEN STRUKTURAL, GEN NON-STRUKTURAL, DAN UNTRANSLATED REGION DALAM PERAKITAN VIRUS DENGUE

2015 ◽  
Vol 7 (2) ◽  
Author(s):  
Meiranty C. Pangerapan ◽  
Beivy J. Kolondam
Keyword(s):  
Aedes Aegypti ◽  
Dengue Virus ◽  
Dengue Fever ◽  
Aedes Albopictus ◽  
Untranslated Region ◽  
Rna Virus ◽  
Virus Genome ◽  
Interferon Response ◽  
Endoplasmic Reticulum Membrane ◽  
Structural Genes

Abstract: Dengue virus is a single-stranded RNA virus that belongs to Flaviviridae family. This virus causes dengue fever which is transmitted by Aedes aegypti dan Aedes albopictus. There are four serotypes of dengue virus; all of them can cause dengue fever. Understanding the genomics of dengue virus is important for research and diagnostics. The genome of dengue virus is 11 kilo-base long. It consists of 5’-untranslated region (5’-UTR), three structural genes (coding capsid protein, pre-membrane/membrane, and envelope), seven non-structural genes (coding NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5 proteins) and 3’-UTR. Non-structural genes are encoding proteins of viral RNA replication, interferon response, viral assembly and secretion, endoplasmic reticulum membrane invagination induction, immune-mediator induction, and RNA 5’-caping.Keywords: dengue virus, genome, structural genes, non-structural genes, untranslated region.Abstrak: Virus dengue merupakan virus RNA beruntai tunggal yang termasuk dalam famili Flaviviridae. Virus ini adalah penyebab penyakit demam berdarah dengue yang ditransmisikan melalui nyamuk Aedes aegypti dan Aedes albopictus. Ada empat serotipe virus dengue yang telah dikenal secara luas yang ada semuanya dapat menimbulkan penyakit demam berdarah. Pemahaman tentang genomik virus dengue sangat penting untuk pengembangan penelitian dan juga untuk keperluan diagnostik. Genom virus dengue memiliki panjang 11 kilo basa. Genomnya tersusun atas 5’-untranslated region (5’-UTR), tiga gen struktural (mengodekan protein kapsid, premembran/membran dan amplop), tujuh gen non-struktural (mengodekan protein NS1, NS2A, NS2B, NS3, NS4A, NS4B dan NS5) dan 3’-UTR. Gen-gen non-struktural mengodekan protein untuk replikasi RNA virus, respon interferon, perakitan, sekresi partikel virus, menginduksi invaginasi membran retikulum endoplasma, induksi imunomediator dan penambahan tudung pada ujung 5’ RNA.Kata kunci: virus dengue, genom, gen struktural, gen non-struktural, untranslated region

scholarly journals MicroRNA in Diabetic Nephropathy: Renin Angiotensin, AGE/RAGE, and Oxidative Stress Pathway

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Shinji Hagiwara ◽  
Aaron McClelland ◽  
Phillip Kantharidis
Keyword(s):  
Oxidative Stress ◽  
Diabetic Nephropathy ◽  
Noncoding Rna ◽  
Renin Angiotensin System ◽  
Renin Angiotensin ◽  
Cellular Targets ◽  
Rna Molecules ◽  
Small Noncoding Rna ◽  
Disease States ◽  
Oxidative Stress Pathway

MicroRNAs (miRNA) are a novel class of small, noncoding RNA molecules that have gained the attention of many researchers in recent years due to their ability to posttranscriptionally regulate the expression of families of genes simultaneously. Their role in normal physiology and pathobiology is intriguing and their regulation in normal and disease states is fascinating. That the cells can return to a state of homeostasis when these small molecules are perturbed is truly remarkable given the multiple cellular targets of each miRNA and that many mRNAs are targeted by multiple miRNAs. Several reviews have covered aspects of miRNA function in biology and disease. Here, we review the role of miRNA in regulating the renin-angiotensin system, AGE/RAGE signalling, and under conditions of oxidative stress in the context of diabetic nephropathy.

scholarly journals Investigating the association of rs2910164 with cancer predisposition in an Irish cohort

2017 ◽  
Vol 6 (8) ◽  
pp. 614-624 ◽  
Author(s):  
T P McVeigh ◽  
R J Mulligan ◽  
U M McVeigh ◽  
P W Owens ◽  
N Miller ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Thyroid Cancer ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Differentiated Thyroid Cancer ◽  
Study Group ◽  
Gene Encoding ◽  
Rna Molecules ◽  
Small Noncoding Rna ◽  
Genes Encoding

Introduction MicroRNAs (miRNAs) are small noncoding RNA molecules that exert post-transcriptional effects on gene expression by binding with cis-regulatory regions in target messenger RNA (mRNA). Polymorphisms in genes encoding miRNAs or in miRNA–mRNA binding sites confer deleterious epigenetic effects on cancer risk. miR-146a has a role in inflammation and may have a role as a tumour suppressor. The polymorphism rs2910164 in the MIR146A gene encoding pre-miR-146a has been implicated in several inflammatory pathologies, including cancers of the breast and thyroid, although evidence for the associations has been conflicting in different populations. We aimed to further investigate the association of this variant with these two cancers in an Irish cohort. Methods The study group comprised patients with breast cancer (BC), patients with differentiated thyroid cancer (DTC) and unaffected controls. Germline DNA was extracted from blood or from saliva collected using the DNA Genotek Oragene 575 collection kit, using crystallisation precipitation, and genotyped using TaqMan-based PCR. Data were analysed using SPSS, v22. Results The total study group included 1516 participants. This comprised 1386 Irish participants; 724 unaffected individuals (controls), 523 patients with breast cancer (BC), 136 patients with differentiated thyroid cancer (DTC) and three patients with dual primary breast and thyroid cancer. An additional cohort of 130 patients with DTC from the South of France was also genotyped for the variant. The variant was detected with a minor allele frequency (MAF) of 0.19 in controls, 0.22 in BC and 0.27 and 0.26 in DTC cases from Ireland and France, respectively. The variant was not significantly associated with BC (per allele odds ratio = 1.20 (0.98–1.46), P = 0.07), but was associated with DTC in Irish patients (per allele OR = 1.59 (1.18–2.14), P = 0.002). Conclusion The rs2910164 variant in MIR146A is significantly associated with DTC, but is not significantly associated with BC in this cohort.

scholarly journals Engineering a Circular Riboregulator in Escherichia coli

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
William Rostain ◽  
Shensi Shen ◽  
Teresa Cordero ◽  
Guillermo Rodrigo ◽  
Alfonso Jaramillo
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Circular Rna ◽  
Circular Rnas ◽  
Fluorescent Reporter ◽  
Small Noncoding Rna ◽  
E Coli ◽  
Group I

RNAs of different shapes and sizes, natural or synthetic, can regulate gene expression in prokaryotes and eukaryotes. Circular RNAs have recently appeared to be more widespread than previously thought, but their role in prokaryotes remains elusive. Here, by inserting a riboregulatory sequence within a group I permuted intron-exon ribozyme, we created a small noncoding RNA that self-splices to produce a circular riboregulator in Escherichia coli. We showed that the resulting riboregulator can trans-activate gene expression by interacting with a cis-repressed messenger RNA. We characterized the system with a fluorescent reporter and with an antibiotic resistance marker, and we modeled this novel posttranscriptional mechanism. This first reported example of a circular RNA regulating gene expression in E. coli adds to an increasing repertoire of RNA synthetic biology parts, and it highlights that topological molecules can play a role in the case of prokaryotic regulation.

scholarly journals COT-04 Circulating biomarker for glioblastoma and primary central nervous system lymphoma -Next Generation Sequencing of small noncoding RNA-

2020 ◽  
Vol 2 (Supplement_3) ◽  
pp. ii21-ii21
Author(s):  
Shumpei Onishi ◽  
Fumiyuki Yamasaki ◽  
Motoki Takano ◽  
Ushio Yonezawa ◽  
Kazuhiko Sugiyama ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Noncoding Rna ◽  
Central Nervous System Lymphoma ◽  
Serum Samples ◽  
Small Noncoding Rna ◽  
Non Invasive ◽  
Diagnostic Models ◽  
Healthy Control ◽  
Generation Sequencing

Abstract Objective: Glioblastoma (GBM) and Primary Central Nervous System Lymphoma (PCNSL) are common intracranial malignant tumors. They sometimes present similar radiological findings and diagnoses could be difficult without surgical biopsy. For improving the current management, development of non-invasive biomarkers are desired. In this study, we explored the differently expressed circulating small noncoding RNA (sncRNA) in serum for specific diagnostic tool of GBM and PCNSL. Material & Methods: Serum samples were obtained from three groups: 1) GBM patients (N=26), 2) PCNSL patients (N=14) 3) healthy control (N=114). The total small RNAs were extracted from serum. The whole expression profiles of serum sncRNAs were measured using Next-Generation Sequencing System. We analyzed serum levels of sncRNAs (15–55 nt) in each serum samples. The difference of sncRNAs expression profile among three groups were compared. Data analysis was performed by logistic regression analysis followed by leave-one-out cross-validation (LOOCV). The accuracy of diagnostic models of sncRNAs combination were evaluated by receiver operating characteristic (ROC) analysis. Results: We created the combination models using three sncRNA in each models based on the logistic regression analysis. The model 1 (based on sncRNA-X1, X2 and X3) enabled to differentiate GBM patients form healthy control with a sensitivity of 92.3% and a specificity of 99.2% (AUC: 0.993). The model 2 (based on sncRNA-Y1, Y2 and Y3) enabled to differentiate PCNSL patients form healthy control with a sensitivity of 100% and a specificity of 93.9% (AUC: 0.984). The model 3 (based on sncRNA-Z1, Z2 and Z3) enabled to differentiate GBM patients form PCNSL patients with a sensitivity of 92.3% and a specificity of 78.6% (AUC: 0.920). Conclusion: We found three diagnostic models of serum sncRNAs as non-invasive biomarkers potentially useful for detection of GBM and PCNSL from healthy control, and for differentiation GBM from PCNSL.

scholarly journals Ever-increasing viral diversity associated with the red imported fire ant Solenopsis invicta (Formicidae: Hymenoptera)

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
César Augusto Diniz Xavier ◽  
Margaret Louise Allen ◽  
Anna Elizabeth Whitfield
Keyword(s):  
Solenopsis Invicta ◽  
De Novo ◽  
Rna Virus ◽  
Housekeeping Genes ◽  
Virus Genome ◽  
Single Strand ◽  
Viral Diversity ◽  
Red Imported Fire Ant ◽  
Sequence Comparisons ◽  
Data Set

Abstract Background Advances in sequencing and analysis tools have facilitated discovery of many new viruses from invertebrates, including ants. Solenopsis invicta is an invasive ant that has quickly spread worldwide causing significant ecological and economic impacts. Its virome has begun to be characterized pertaining to potential use of viruses as natural enemies. Although the S. invicta virome is the best characterized among ants, most studies have been performed in its native range, with less information from invaded areas. Methods Using a metatranscriptome approach, we further identified and molecularly characterized virus sequences associated with S. invicta, in two introduced areas, U.S and Taiwan. The data set used here was obtained from different stages (larvae, pupa, and adults) of S. invicta life cycle. Publicly available RNA sequences from GenBank’s Sequence Read Archive were downloaded and de novo assembled using CLC Genomics Workbench 20.0.1. Contigs were compared against the non-redundant protein sequences and those showing similarity to viral sequences were further analyzed. Results We characterized five putative new viruses associated with S. invicta transcriptomes. Sequence comparisons revealed extensive divergence across ORFs and genomic regions with most of them sharing less than 40% amino acid identity with those closest homologous sequences previously characterized. The first negative-sense single-stranded RNA virus genomic sequences included in the orders Bunyavirales and Mononegavirales are reported. In addition, two positive single-strand virus genome sequences and one single strand DNA virus genome sequence were also identified. While the presence of a putative tenuivirus associated with S. invicta was previously suggested to be a contamination, here we characterized and present strong evidence that Solenopsis invicta virus 14 (SINV-14) is a tenui-like virus that has a long-term association with the ant. Furthermore, based on virus sequence abundance compared to housekeeping genes, phylogenetic relationships, and completeness of viral coding sequences, our results suggest that four of five virus sequences reported, those being SINV-14, SINV-15, SINV-16 and SINV-17, may be associated to viruses actively replicating in the ant S. invicta. Conclusions The present study expands our knowledge about viral diversity associated with S. invicta in introduced areas with potential to be used as biological control agents, which will require further biological characterization.

scholarly journals PlncRNA-HDeep: plant long noncoding RNA prediction using hybrid deep learning based on two encoding styles

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Jun Meng ◽  
Qiang Kang ◽  
Zheng Chang ◽  
Yushi Luan
Keyword(s):  
Deep Learning ◽  
Noncoding Rna ◽  
Nearest Neighbor ◽  
Short Term Memory ◽  
Biological Activities ◽  
Support Vector ◽  
Multiple Perspectives ◽  
K Nearest Neighbor ◽  
Rna Sequences ◽  
Deep Learning Model

Abstract Background Long noncoding RNAs (lncRNAs) play an important role in regulating biological activities and their prediction is significant for exploring biological processes. Long short-term memory (LSTM) and convolutional neural network (CNN) can automatically extract and learn the abstract information from the encoded RNA sequences to avoid complex feature engineering. An ensemble model learns the information from multiple perspectives and shows better performance than a single model. It is feasible and interesting that the RNA sequence is considered as sentence and image to train LSTM and CNN respectively, and then the trained models are hybridized to predict lncRNAs. Up to present, there are various predictors for lncRNAs, but few of them are proposed for plant. A reliable and powerful predictor for plant lncRNAs is necessary. Results To boost the performance of predicting lncRNAs, this paper proposes a hybrid deep learning model based on two encoding styles (PlncRNA-HDeep), which does not require prior knowledge and only uses RNA sequences to train the models for predicting plant lncRNAs. It not only learns the diversified information from RNA sequences encoded by p-nucleotide and one-hot encodings, but also takes advantages of lncRNA-LSTM proposed in our previous study and CNN. The parameters are adjusted and three hybrid strategies are tested to maximize its performance. Experiment results show that PlncRNA-HDeep is more effective than lncRNA-LSTM and CNN and obtains 97.9% sensitivity, 95.1% precision, 96.5% accuracy and 96.5% F1 score on Zea mays dataset which are better than those of several shallow machine learning methods (support vector machine, random forest, k-nearest neighbor, decision tree, naive Bayes and logistic regression) and some existing tools (CNCI, PLEK, CPC2, LncADeep and lncRNAnet). Conclusions PlncRNA-HDeep is feasible and obtains the credible predictive results. It may also provide valuable references for other related research.

scholarly journals Sequence Variations of Epstein-Barr Virus-Encoded Small Noncoding RNA and Latent Membrane Protein 1 in Hematologic Tumors in Northern China

Intervirology ◽  
2021 ◽  
Vol 64 (2) ◽  
pp. 69-80
Author(s):  
Hai-Yu Wang ◽  
Lingling Sun ◽  
Ping Li ◽  
Wen Liu ◽  
Zhong-Guang Zhang ◽  
...  
Keyword(s):  
Membrane Protein ◽  
Nested Pcr ◽  
Noncoding Rna ◽  
Epstein Barr Virus ◽  
Northern China ◽  
Latent Membrane Protein ◽  
Latent Membrane Protein 1 ◽  
Small Noncoding Rna ◽  
Barr Virus ◽  
Epstein Barr

<b><i>Objective:</i></b> To investigate the relationship between hematologic tumors and Epstein-Barr virus (EBV)-encoded small noncoding RNA (EBER) variations as well as latent membrane protein 1 (LMP1) variations. <b><i>Methods:</i></b> Patients with leukemia and myelodysplastic syndrome (MDS) were selected as subjects. Genotypes 1/2 and genotypes F/f were analyzed using the nested PCR technology, while EBER and LMP1 subtypes were analyzed by the nested PCR and DNA sequencing. <b><i>Results:</i></b> Type 1 was more dominant than type 2, found in 59 out of 82 (72%) leukemia and in 31 out of 35 (88.6%) MDS, while type F was more prevalent than type f in leukemia (83/85, 97.6%) and MDS (29/31, 93.5%) samples. The distribution of EBV genotypes 1/2 was not significantly different among leukemia, MDS, and healthy donor groups, neither was that of EBV genotypes F/f. EB-6m prototype was the dominant subtype of EBER in leukemia and MDS (73.2% [30/41] and 83.3% [10/12], respectively). The frequency of EB-6m was lower than that of healthy people (96.7%, 89/92), and the difference was significant (<i>p</i> &#x3c; 0.05). China 1 subtype was the dominant subtype of LMP1 in leukemia and MDS (70% [28/40] and 90% [9/10], respectively), and there was no significant difference in the distribution of LMP1 subtypes among the 3 groups (<i>p</i> &#x3e; 0.05). <b><i>Conclusion:</i></b> The distribution of EBV 1/2, F/f, EBER, and LMP1 subtypes in leukemia and MDS was similar to that in the background population in Northern China, which means that these subtypes may be rather region-restricted but not associated with leukemia and MDS pathogenesis.

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