scholarly journals Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9369 ◽  
Author(s):  
Müşerref Duygu Saçar Demirci ◽  
Aysun Adan
Keyword(s):  
Transcription Factors ◽  
Rna Viruses ◽  
Function Analysis ◽  
Virus Genome ◽  
E Proteins ◽  
Basal Transcription ◽  
Viral Mirnas ◽  
Human Mirnas ◽  
Human Genes ◽  
Viral Genes

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs, there are examples of miRNA like sequences from RNA viruses with regulatory functions. In the case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with viral replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA-based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Overall, 950 hairpin structured sequences were extracted from the virus genome and based on the prediction results, 29 of them could be precursor miRNAs. Targeting analysis showed that 30 viral mature miRNA-like sequences could target 1,367 different human genes. PANTHER gene function analysis results indicated that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription, metabolism, defense system and several signaling pathways such as Wnt and EGFR signalings. Protein class-based grouping of targeted human genes showed that host transcription might be one of the main targets of the virus since 96 genes involved in transcriptional processes were potential targets of predicted viral miRNAs. For instance, basal transcription machinery elements including several components of human mediator complex (MED1, MED9, MED12L, MED19), basal transcription factors such as TAF4, TAF5, TAF7L and site-specific transcription factors such as STAT1 were found to be targeted. In addition, many known human miRNAs appeared to be able to target viral genes involved in viral life cycle such as S, M, N, E proteins and ORF1ab, ORF3a, ORF8, ORF7a and ORF10. Considering the fact that miRNA-based therapies have been paid attention, based on the findings of this study, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.

scholarly journals Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection

2020 ◽  
Author(s):  
Müşerref Duygu Saçar Demirci ◽  
Aysun Adan
Keyword(s):  
Gene Expression ◽  
Computational Analysis ◽  
Defense Mechanism ◽  
Function Analysis ◽  
Antiviral Defense ◽  
Cellular Processes ◽  
Human Mirnas ◽  
Human Genes ◽  
Viral Genes ◽  
Gene Function Analysis

AbstractMicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that have been found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs that would target their own genes or alter the host gene expression, there are examples of miRNAs functioning as an antiviral defense mechanism. In the case of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA – based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Our PANTHER gene function analysis results indicate that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription. For instance, a transcriptional regulator, STAT1 and transcription machinery might be targeted by virus-derived miRNAs. In addition, many known human miRNAs appear to be able to target viral genes. Considering the fact that miRNA-based therapies have been successful before, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.

The Role of microRNAs in the Viral Infections

2019 ◽  
Vol 24 (39) ◽  
pp. 4659-4667 ◽  
Author(s):  
Mona Fani ◽  
Milad Zandi ◽  
Majid Rezayi ◽  
Nastaran Khodadad ◽  
Hadis Langari ◽  
...  
Keyword(s):  
Viral Infections ◽  
Rna Viruses ◽  
Regulation Of Gene Expression ◽  
Molecular Structures ◽  
Main Function ◽  
Cellular Functions ◽  
Viral Genes ◽  
Non Coding Rnas ◽  
Post Transcriptional Regulation

MicroRNAs (miRNAs) are non-coding RNAs with 19 to 24 nucleotides which are evolutionally conserved. MicroRNAs play a regulatory role in many cellular functions such as immune mechanisms, apoptosis, and tumorigenesis. The main function of miRNAs is the post-transcriptional regulation of gene expression via mRNA degradation or inhibition of translation. In fact, many of them act as an oncogene or tumor suppressor. These molecular structures participate in many physiological and pathological processes of the cell. The virus can also produce them for developing its pathogenic processes. It was initially thought that viruses without nuclear replication cycle such as Poxviridae and RNA viruses can not code miRNA, but recently, it has been proven that RNA viruses can also produce miRNA. The aim of this articles is to describe viral miRNAs biogenesis and their effects on cellular and viral genes.

VirusTaxo: Taxonomic classification of virus genome using multi-class hierarchical classification by k-mer enrichment

2021 ◽  
Author(s):  
Rajan Saha Raju ◽  
Abdullah Al Nahid ◽  
Preonath Shuvo ◽  
Rashedul Islam
Keyword(s):  
Genome Sequence ◽  
Rna Viruses ◽  
Hierarchical Classification ◽  
Classification Problem ◽  
Virus Genome ◽  
Taxonomic Classification ◽  
Dna Viruses ◽  
Dna And Rna ◽  
Full Length Genome

AbstractTaxonomic classification of viruses is a multi-class hierarchical classification problem, as taxonomic ranks (e.g., order, family and genus) of viruses are hierarchically structured and have multiple classes in each rank. Classification of biological sequences which are hierarchically structured with multiple classes is challenging. Here we developed a machine learning architecture, VirusTaxo, using a multi-class hierarchical classification by k-mer enrichment. VirusTaxo classifies DNA and RNA viruses to their taxonomic ranks using genome sequence. To assign taxonomic ranks, VirusTaxo extracts k-mers from genome sequence and creates bag-of-k-mers for each class in a rank. VirusTaxo uses a top-down hierarchical classification approach and accurately assigns the order, family and genus of a virus from the genome sequence. The average accuracies of VirusTaxo for DNA viruses are 99% (order), 98% (family) and 95% (genus) and for RNA viruses 97% (order), 96% (family) and 82% (genus). VirusTaxo can be used to detect taxonomy of novel viruses using full length genome or contig sequences.AvailabilityOnline version of VirusTaxo is available at https://omics-lab.com/virustaxo/.

scholarly journals The Long Noncoding RNA Differential Expression in Peripheral Blood Leukocyte from Schizophrenia Patients by RNA Sequencing

2020 ◽  
Author(s):  
Jie Wu ◽  
Zijun Liu ◽  
Yunqiao Zhang ◽  
Zhaowei Teng ◽  
Xu You ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Correlation Coefficient ◽  
Peripheral Blood ◽  
Noncoding Rna ◽  
Clinical Symptoms ◽  
Function Analysis ◽  
Hierarchical Classification ◽  
Peripheral Blood Leukocyte ◽  
Protein Coding ◽  
Functional Sites

Abstract Background: The diagnosis of schizophrenia (SCZ) depends on the evaluation of clinical symptoms, and there is no objective biomarker. Surveys have found that long non-coding RNA (lncRNA) may be affected in the pathogenesis of SCZ. There are also different genes in the expression of peripheral blood (PBL) in SCZ patients.Methods: We profiled transcriptome analysis of PBL in 50 patients with schizophrenia and 50 controls without psychiatric diagnoses, reconstructed PBL transcriptome information using RNA-seq, predicted lncRNA-mRNA interaction via “RNAplex”, a hierarchical classification-Spielman correlation coefficient approach was used to analyze the correlation between lncRNA and protein-coding gene expression among samples, and used systematic bioinformatics methods (Go/Pathway) to perform lncRNA functional annotation and qPCR experimental verification. Predicting functional sites for sequences using the database PROSITE, NCBI, UCSC, JASPAR.Results: We screened 94 lncRNA and 1179 mRNA differential expressions in PBL, of which 46 new lncRNAs were identified for the first time. Enrichment into lncRNA involves biological processes and signaling pathways related to the neutrophil activation involved in immune response. According to Spearman correlation coefficient analysis, 81 lncRNA and 410 mRNA have expression correlation (p<0.01 and |r|≥0.4), QPCR in independent samples verified that the core node of the lncRNA-mRNA co-expression network IL1RAP-TCONS_00138311 variable shear is indeed highly expressed in SCZ patients, 2^-△△Ct is 0.56, the area under the ROC curve is 0.924. The top four ranked transcription factors were predicted to be HSF1, HSF2, HSF4, and FOXA1.Conclusions: Combined with sequence function analysis, it showed that the transcription factors FOXA1, HSF1, HSF2, HSF4, etc. may mediate the activation of IL1B-induced NF-kβ pathway and other inflammatory pathways through the regulation of IL1RAP alternative splicing transcripts TCONS_00138311, thereby participating in the pathogenesis of SCZ. We propose that the frequency of Differential lncRNA in peripheral blood could be used as novel biomarker for distinguishing SCZ from health.

Function Analysis of Drought Resistance Related Gene TaGAPCs and TaWRKYs in Wheat

2021 ◽  
Author(s):  
Qiuzhu Wang ◽  
Lin Zhang ◽  
Shushen Yang
Keyword(s):  
Transcription Factors ◽  
Drought Stress ◽  
Function Analysis ◽  
Severe Drought ◽  
Primary Metabolism ◽  
Wild Type ◽  
Drought Treatment ◽  
Biological Regulation ◽  
Wheat Seedlings ◽  
Differential Genes

Abstract Backgrounds: Wheat (Triticum aestivum L.) is one of the most important food crops in the world. It faces various abiotic stresses during its growth. Drought is one of the main factors limiting the growth and development of wheat. Severe drought stress will Lead to a decline in wheat production. Cytoplasmic glyceraldehyde-3-phosphate dehydrogenase (GAPC) is an important member of the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) family, which is widely present in plant cytoplasm. Plants play an important role in the process of primary metabolism and stress resistance.Result: In this study, a comparative transcriptomic analysis of the TaGAPCs-RNAi strain of Changwu 134 and the wild-type wheat seedlings of Changwu 134 under natural drought conditions was carried out. A total of 30067 differentially expressed genes were screened in RNAi strains and wild-type strains, of which 19,959 genes were up-regulated in RNAi strains and 10,108 genes were down-regulated in transcription. GO analysis shows that differential genes are mainly enriched in biological regulation, cellular processes, metabolic processes, and responses to stimuli. KEGG analysis showed that the differential genes were mainly concentrated in the biosynthesis of phenylpropane, plant hormone signal transduction and flavonoid biosynthesis pathways. By analyzing the expression levels of differential transcription factors, the significantly down-regulated transcription factor WRKY family member TaWRKY2 / 22/28/29/33/40/47/52 in wheat was screened out. The TaWRKY28/33/40/47 gene silencing line was successfully obtained using the barley stripe mosaic virus (BSMV-VIGS) technology. The plants with TaWRKY28/33/40/47 gene silenced were subjected to natural drought treatment, and physiological and biochemical index tests were carried out. The results showed that the growth status of gene-silenced plants was worse than that of wild-type plants, and the relative water content and chlorophyll content decreased. The content of MDA, H2O2 and superoxide anion increases, the activity of antioxidant enzymes (SOD, POD, CAT) decreases, and the content of proline decreases. Conclusion: The results showed that TaGAPCs regulates the expression of some TaWRKYs transcription factors, activates antioxidant pathways, enhances tolerance of wheat to drought stress.

scholarly journals Activation of viral transcription by stepwise largescale folding of an RNA virus genome

2020 ◽  
Vol 48 (16) ◽  
pp. 9285-9300
Author(s):  
Tamari Chkuaseli ◽  
K Andrew White
Keyword(s):  
Rna Structure ◽  
Rna Viruses ◽  
Rna Virus ◽  
Initial Step ◽  
Binding Pocket ◽  
Regulatory Elements ◽  
Virus Genome ◽  
Genomic Rna ◽  
Stem Loop ◽  
Rna Complex

Abstract The genomes of RNA viruses contain regulatory elements of varying complexity. Many plus-strand RNA viruses employ largescale intra-genomic RNA-RNA interactions as a means to control viral processes. Here, we describe an elaborate RNA structure formed by multiple distant regions in a tombusvirus genome that activates transcription of a viral subgenomic mRNA. The initial step in assembly of this intramolecular RNA complex involves the folding of a large viral RNA domain, which generates a discontinuous binding pocket. Next, a distally-located protracted stem-loop RNA structure docks, via base-pairing, into the binding site and acts as a linchpin that stabilizes the RNA complex and activates transcription. A multi-step RNA folding pathway is proposed in which rate-limiting steps contribute to a delay in transcription of the capsid protein-encoding viral subgenomic mRNA. This study provides an exceptional example of the complexity of genome-scale viral regulation and offers new insights into the assembly schemes utilized by large intra-genomic RNA structures.

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