Improving miRNA-mRNA interaction predictions

Tabas-Madrid, Daniel; Muniategui, Ander; Sánchez-Caballero, Ignacio; Martínez-Herrera, Dannys Jorge; Sorzano, Carlos Óscar S.; Rubio, Ángel; Pascual-Montano, Alberto

doi:10.1186/1471-2164-15-s10-s2

Cited by 31 publications

(60 citation statements)

References 54 publications

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“…These findings reflect that the role of miRNA in T cell activation is spatiotemporal and numerous other factors are involved in their regulation 34 . This also underlines the fact that the miRNA target prediction tools like Targetscan, PicTar, miRanda are powerful but need to be experimentally validated in different disease states 35 …”

Section: Discussionmentioning

confidence: 78%

Differential expression of miRNAs and their target genes: Exploring a new perspective of acquired aplastic anemia pathogenesis

Srivastava

Chaturvedi

Rahman

et al. 2020

Int J Lab Hematology

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Introduction MicroRNAs (miRNAs) play a critical role in orchestrating T cell differentiation and activation and may thus play a vital role in acquired aplastic anemia (aAA). The study aimed to evaluate the differential expression of selected miRNAs and their relevant target genes in bone marrow samples of aAA patients. Methods Differential expression of 8 miRNAs viz; hsa‐miR‐126‐3p, miR‐145‐5p, miR‐155‐5p, miR‐150‐5p, miR‐146b‐5p, miR‐34a, miR‐29a, and miR‐29b was evaluated in the bone marrow mononuclear cells of aAA patients. TaqMan microRNA assay was performed for preparing the cDNA of specific miRNA, followed by expression analysis using qRT‐PCR. Data were normalized using two endogenous controls, RNU6B and RNU48. Delta‐delta CT method was used to calculate the fold change (FC) of miRNA expression in individual samples, and a FC of >1.5 was taken as significant. Target genes of these miRNAs were evaluated by qRT‐PCR. Results Thirty five samples of aAA patients and 20 controls were evaluated. Irrespective of the disease severity, five miRNAs were found to be deregulated; miR‐126 (FC‐0.348; P‐value‐.0001) and miR‐145 (FC‐0.31; P‐value‐.0001) were downregulated, while miR‐155 (FC‐3.50; P‐value‐.0067), miR‐146 (FC‐3.13; P‐value‐.0105), and miR‐150 (FC‐5.78; P‐value‐.0001) were upregulated. Target gene study revealed an upregulation of PIK3R2, MYC, SOCS1, and TRAF‐6, and downregulation of MYB. Conclusion This is the first study from the Indian subcontinent demonstrating the presence of altered miRNA expression in the bone marrow samples of aAA patients, suggesting their role in the pathogenesis of the disease. A comprehensive study focusing on the effect of these miRNA‐mRNA interactions is likely to open new avenues of management.

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Section: Discussionmentioning

confidence: 78%

Differential expression of miRNAs and their target genes: Exploring a new perspective of acquired aplastic anemia pathogenesis

Srivastava

Chaturvedi

Rahman

et al. 2020

Int J Lab Hematology

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“…binding. These included transcripts not predicted as containing a miR-488-3p MRE, as expected from the high false negative rate of MRE prediction algorithms [32][33][34]. As expected, the two negative control transcripts, which are not responsive to Cerox1 transcript levels, and have no predicted MREs for miR-488-3p failed to bind miR-488-3p.…”

Section: Cerox1 Activity Is Mediated By Mir-488-3pmentioning

confidence: 64%

Cerox1 and microRNA-488-3p noncoding RNAs jointly regulate mitochondrial complex I catalytic activity

Roberts

Haerty

et al. 2018

Preprint

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To generate energy efficiently, the cell is uniquely challenged to co-ordinate the abundance of electron transport chain protein subunits expressed from both nuclear and mitochondrial genomes.How an effective stoichiometry of this many constituent subunits is co-ordinated posttranscriptionally remains poorly understood. Here we show that Cerox1, an unusually abundant cytoplasmic long noncoding RNA (lncRNA), modulates the levels of mitochondrial complex I subunit transcripts in a manner that requires binding to microRNA-488-3p. Increased abundance of Cerox1 cooperatively elevates complex I subunit protein abundance and enzymatic activity, decreases reactive oxygen species production, and protects against the complex I inhibitor rotenone. Cerox1 function is conserved across placental mammals: human and mouse orthologues effectively modulate complex I enzymatic activity in mouse and human cells, respectively. Cerox1 is the first lncRNA demonstrated, to our knowledge, to regulate mitochondrial oxidative phosphorylation (OXPHOS) and, with miR-488-3p, represent novel targets for the modulation of complex I activity.

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“…We used this stringent criterion to reduce probably false positive results. It is demonstrated that coding sequences and 5'UTR of genes can be targeted by miRNAs (Tabas-Madrid et al, 2014). However, in the present study, the 3'UTR of target genes were only applied for target prediction.…”

Section: Rna-seq and Micro Rna-seq Data Analysismentioning

confidence: 79%

Integrated regulatory network reveals novel candidate regulators in the development of negative energy balance in cattle

Mozduri

Bakhtiarizadeh

Salehi

2018

Animal

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Negative energy balance (NEB) is an altered metabolic state in modern high-yielding dairy cows. This metabolic state occurs in the early postpartum period when energy demands for milk production and maintenance exceed that of energy intake. Negative energy balance or poor adaptation to this metabolic state has important effects on the liver and can lead to metabolic disorders and reduced fertility. The roles of regulatory factors, including transcription factors (TFs) and micro RNAs (miRNAs) have often been separately studied for evaluating of NEB. However, adaptive response to NEB is controlled by complex gene networks and still not fully understood. In this study, we aimed to discover the integrated gene regulatory networks involved in NEB development in liver tissue. We downloaded data sets including mRNA and miRNA expression profiles related to three and four cows with severe and moderate NEB, respectively. Our method integrated two independent types of information: module inference network by TFs, miRNAs and mRNA expression profiles (RNA-seq data) and computational target predictions. In total, 176 modules were predicted by using gene expression data and 64 miRNAs and 63 TFs were assigned to these modules. By using our integrated computational approach, we identified 13 TF-module and 19 miRNA-module interactions. Most of these modules were associated with liver metabolic processes as well as immune and stress responses, which might play crucial roles in NEB development. Literature survey results also showed that several regulators and gene targets have already been characterized as important factors in liver metabolic processes. These results provided novel insights into regulatory mechanisms at the TF and miRNA levels during NEB. In addition, the method described in this study seems to be applicable to construct integrated regulatory networks for different diseases or disorders.

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Improving miRNA-mRNA interaction predictions

Cited by 31 publications

References 54 publications

Differential expression of miRNAs and their target genes: Exploring a new perspective of acquired aplastic anemia pathogenesis

Differential expression of miRNAs and their target genes: Exploring a new perspective of acquired aplastic anemia pathogenesis

Cerox1 and microRNA-488-3p noncoding RNAs jointly regulate mitochondrial complex I catalytic activity

Integrated regulatory network reveals novel candidate regulators in the development of negative energy balance in cattle

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