Uncovering Potential lncRNAs and Nearby mRNAs in Systemic Lupus Erythematosus from the Gene Expression Omnibus Dataset

Cao, Hai-Yu; Li, Dong; Lu, Huixiu; Sun, Jing; Li, Haibin

doi:10.2217/epi-2019-0145

Cited by 7 publications

(5 citation statements)

References 72 publications

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“…The advent of high throughput sequencing technologies and the availability of these data in public databases have facilitated the recognition of the complicated interaction network between lncRNAs, miRNAs and protein-coding genes. A representative study in this regard has identified numerous pairs of lncRNAs and target mRNAs [ 21 ]. Such studies have enabled the recognition of therapeutic targets for SLE.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, lnc-DC has been suggested as a marker for the identification of nephritis in SLE patients [ 20 ]. In an in silico study examining the expression profile of lncRNAs and mRNAs from the Gene Expression Omnibus dataset, numerous interaction pairs of lncRNA-adjacent targeted mRNAs were identified, including NRIR-RSAD2, RP11-153M7.5-TLR2, RP4-758J18.2-CCNL2, RP11-69E11.4-PABPC4 and RP11-496I9.1-IRF7/HRAS/PHRF1 [ 21 ]. Notably, mitogen-activated protein kinase (MAPK) was found among the enriched signaling pathways of differentially expressed transcripts [ 21 ].…”

Section: Lncrnas In Slementioning

confidence: 99%

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Exploring the Role of Non-Coding RNAs in the Pathophysiology of Systemic Lupus Erythematosus

et al. 2020

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Systemic lupus erythematosus (SLE) is a chronic immune-related disorder designated by a lack of tolerance to self-antigens and the over-secretion of autoantibodies against several cellular compartments. Although the exact pathophysiology of SLE has not been clarified yet, this disorder has a strong genetic component based on the results of familial aggregation and twin studies. Variation in the expression of non-coding RNAs has been shown to influence both susceptibility to SLE and the clinical course of this disorder. Several long non-coding RNAs (lncRNAs) such as GAS5, MALAT1 and NEAT1 are dysregulated in SLE patients. Moreover, genetic variants within lncRNAs such as SLEAR and linc00513 have been associated with risk of this disorder. The dysregulation of a number of lncRNAs in the peripheral blood of SLE patients has potentiated them as biomarkers for diagnosis, disease activity and therapeutic response. MicroRNAs (miRNAs) have also been shown to affect apoptosis and the function of immune cells. Taken together, there is a compelling rationale for the better understanding of the involvement of these two classes of non-coding RNAs in the pathogenesis of SLE. Clarification of the function of these transcripts has the potential to elucidate the molecular pathophysiology of SLE and provide new opportunities for the development of targeted therapies for this disorder.

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Section: Discussionmentioning

confidence: 99%

Section: Lncrnas In Slementioning

confidence: 99%

Exploring the Role of Non-Coding RNAs in the Pathophysiology of Systemic Lupus Erythematosus

et al. 2020

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“…miR-132 has been extensively studied as a putative therapeutic biomarker, due to its role in cardiac hypertrophy and heart failure, through its effect on the pro-hypertrophic calcineurin/NFAT pathway [28,29]. The lncRNA encoded by splicing of the gene RP4-758J18.2 has previously been shown to play a role in the progression of systemic lupus erythematosus (SLE) through its interaction with CCNL2 gene [30]. The locus, chr.1p36 also frequent genomic rearrangements, leading to conditions like craniosynostosis and others, which in turn affect the normal functioning of the heart [31,32].…”

Section: Noncoding Rna Databasesmentioning

confidence: 99%

Non-Coding RNA Databases in Cardiovascular Research

Balamurali

Stoll

2020

ncRNA

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Cardiovascular diseases (CVDs) are of multifactorial origin and can be attributed to several genetic and environmental components. CVDs are the leading cause of mortality worldwide and they primarily damage the heart and the vascular system. Non-coding RNA (ncRNA) refers to functional RNA molecules, which have been transcribed into DNA but do not further get translated into proteins. Recent transcriptomic studies have identified the presence of thousands of ncRNA molecules across species. In humans, less than 2% of the total genome represents the protein-coding genes. While the role of many ncRNAs is yet to be ascertained, some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been associated with disease progression, serving as useful diagnostic and prognostic biomarkers. A plethora of data repositories specialized in ncRNAs have been developed over the years using publicly available high-throughput data from next-generation sequencing and other approaches, that cover various facets of ncRNA research like basic and functional annotation, expressional profile, structural and molecular changes, and interaction with other biomolecules. Here, we provide a compendium of the current ncRNA databases relevant to cardiovascular research.

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“…In fact, we recently identified NRIR as an lncRNA upregulated in LPS-stimulated monocytes in a type I IFN-dependent manner and demonstrated that NRIR acts as a positive regulator of the expression of a subset of IFN-stimulated genes (ISGs) (Mariotti et al, 2019). Remarkably, the role of NRIR in the type I IFN pathway has been confirmed by demonstrations of an upregulated expression of this lncRNA in several diseases characterized by activation of the IFN response, such as systemic sclerosis (SSc) (Mariotti et al, 2019;Servaas et al, 2021), primary Sjögren's syndrome (Peng et al, 2020), and systemic lupus erythematosus (Cao et al, 2019). In contrast, NRIR has been shown to play an important role in the pathogenesis of viral infections, where it contributes to viral replication by acting as a negative rather than a positive regulator of the expression of ISGs in hepatocytes or epithelial cells (Kambara et al, 2014;Wróblewska et al, 2017;Xu-Yang et al, 2017;Bayyurt et al, 2021).…”

Section: Introductionmentioning

confidence: 98%

Implementation of a combined bioinformatics and experimental approach to address lncRNA mechanism of action: The example of NRIR

Mariotti

Blas²,

Bazzoni³

2022

Front. Mol. Biosci.

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In this study, we demonstrate the benefit of applying combined strategies to analyze lncRNA action based on bioinformatics and experimental information. This strategy was developed to identify the molecular function of negative regulator of interferon response (NRIR), a type I interferon-stimulated gene (ISG), that we have previously demonstrated to be involved in the upregulation of a subset of ISGs in LPS-stimulated human monocytes. In this study, we provide experimental evidence that NRIR is localized in cellular nuclei, enriched on the chromatin fraction, and upregulates ISGs acting at the transcriptional level. In silico analysis of secondary structures identified distinct NRIR structural domains, comprising putative DNA- and protein-binding regions. In parallel, the presence of a putative DNA-binding domain in NRIR and the five putative NRIR-binding sites in the promoter of NRIR-target genes support the function of NRIR as a transcriptional regulator of its target genes. By use of integrated experimental/bioinformatics approaches, comprising database and literature mining together with in silico analysis of putative NRIR-binding proteins, we identified a list of eight transcription factors (TFs) shared by the majority of NRIR-target genes and simultaneously able to bind TF binding sites enriched in the NRIR-target gene promoters. Among these TFs, the predicted NRIR:STAT interactions were experimentally validated by RIP assay.

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Uncovering Potential lncRNAs and Nearby mRNAs in Systemic Lupus Erythematosus from the Gene Expression Omnibus Dataset

Cited by 7 publications

References 72 publications

Exploring the Role of Non-Coding RNAs in the Pathophysiology of Systemic Lupus Erythematosus

Exploring the Role of Non-Coding RNAs in the Pathophysiology of Systemic Lupus Erythematosus

Non-Coding RNA Databases in Cardiovascular Research

Implementation of a combined bioinformatics and experimental approach to address lncRNA mechanism of action: The example of NRIR

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