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Статті в журналах з теми "MiRNA-mRNA interactions"

Автор: Grafiati

Опубліковано: 13 квітня 2024

Оновлено: 31 липня 2025

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1

Guo, Li, Yang Zhao, Sheng Yang, Hui Zhang, and Feng Chen. "Integrative Analysis of miRNA-mRNA and miRNA-miRNA Interactions." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/907420.

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Анотація:

MicroRNAs (miRNAs) are small, noncoding regulatory molecules. They are involved in many essential biological processes and act by suppressing gene expression. The present work reports an integrative analysis of miRNA-mRNA and miRNA-miRNA interactions and their regulatory patterns using high-throughput miRNA and mRNA datasets. Aberrantly expressed miRNA and mRNA profiles were obtained based on fold change analysis, and qRT-PCR was used for further validation of deregulated miRNAs. miRNAs and target mRNAs were found to show various expression patterns. miRNA-miRNA interactions and clustered/homo

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2

Muniategui, Ander, Rubén Nogales-Cadenas, Miguél Vázquez, et al. "Quantification of miRNA-mRNA Interactions." PLoS ONE 7, no. 2 (2012): e30766. http://dx.doi.org/10.1371/journal.pone.0030766.

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3

Naderi, Elnaz, Mehdi Mostafaei, Akram Pourshams, and Ashraf Mohamadkhani. "Network of microRNAs-mRNAs Interactions in Pancreatic Cancer." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/534821.

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Анотація:

Background.MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death.Methods.56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Function

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4

Subat, Sophia, Kentaro Inamura, Hironori Ninomiya, Hiroko Nagano, Sakae Okumura, and Yuichi Ishikawa. "Unique MicroRNA and mRNA Interactions in EGFR-Mutated Lung Adenocarcinoma." Journal of Clinical Medicine 7, no. 11 (2018): 419. http://dx.doi.org/10.3390/jcm7110419.

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The EGFR gene was one of the first molecules to be selected for targeted gene therapy. EGFR-mutated lung adenocarcinoma, which is responsive to EGFR inhibitors, is characterized by a distinct oncogenic pathway in which unique microRNA (miRNA)–mRNA interactions have been observed. However, little information is available about the miRNA–mRNA regulatory network involved. Both miRNA and mRNA expression profiles were investigated using microarrays in 155 surgically resected specimens of lung adenocarcinoma with a known EGFR mutation status (52 mutated and 103 wild-type cases). An integrative analy

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5

Bencun, Maja, Thiago Britto-Borges, Jessica Eschenbach, and Christoph Dieterich. "New Tricks with Old Dogs: Computational Identification and Experimental Validation of New miRNA–mRNA Regulation in hiPSC-CMs." Biomedicines 10, no. 2 (2022): 391. http://dx.doi.org/10.3390/biomedicines10020391.

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Cardiovascular disease is still the leading cause of morbidity and mortality worldwide. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a valuable widespread in vitro model to study cardiac disease. Herein, we employ the hiPSC-CM model to identify novel miRNA–mRNA interaction partners during cardiac differentiation and β-adrenergic stress. Whole transcriptome and small RNA sequencing data were combined to identify novel miRNA–mRNA interactions. Briefly, mRNA and miRNA expression profiles were integrated with miRNA target predictions to identify significant st

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6

Bhasuran, Balu, Sharanya Manoharan, Oviya Ramalakshmi Iyyappan, Gurusamy Murugesan, Archana Prabahar, and Kalpana Raja. "Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression." Biomedicines 12, no. 7 (2024): 1535. http://dx.doi.org/10.3390/biomedicines12071535.

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Анотація:

microRNA (miRNA)–messenger RNA (mRNA or gene) interactions are pivotal in various biological processes, including the regulation of gene expression, cellular differentiation, proliferation, apoptosis, and development, as well as the maintenance of cellular homeostasis and pathogenesis of numerous diseases, such as cancer, cardiovascular diseases, neurological disorders, and metabolic conditions. Understanding the mechanisms of miRNA–mRNA interactions can provide insights into disease mechanisms and potential therapeutic targets. However, extracting these interactions efficiently from a huge co

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7

Mukushkina, D. D., S. Labeit, and A. T. Ivashchenko. "CHARACTERISTICS OF miRNA INTERACTION WITH mRNA OF ISCHEMIC HEART DISEASE CANDIDATE GENES." REPORTS 335, no. 1 (2021): 74–82. http://dx.doi.org/10.32014/2021.2518-1483.11.

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Ischemic heart disease (IHD) is the most serious cardiovascular disease and one of the leading causes of death worldwide. An important role in the pathophysiology of IHD play such processes as the processes of inflammation and immune response, metabolism of homocysteine and folate, development processes of endothelial dysfunction and oxidative stress and homeostasis system. Accordingly, the identified genes that are directly involved in these processes. In addition, miRNA (mRNA-inhibiting RNA) may affect the expression of these candidate genes. Using bioinformatics methods, the most efficient

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8

Kim, Dayeon, and Younhee Ko. "MIMR: Development of a Web-Based System for miRNA and mRNA Integrated Analysis." International Journal of Molecular Sciences 25, no. 21 (2024): 11819. http://dx.doi.org/10.3390/ijms252111819.

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Анотація:

The human body is a complex network of systems that is harmonized with multiple biological components. To understand these interactions is very challenging. With rapid development of advanced sequencing technologies, massive amounts of data such as mRNA, miRNA are rapidly accumulated. The integrated analysis of mRNA–miRNA has brought an extensive understanding of complex biological systems and pathological mechanisms. MicroRNAs (miRNAs) are small non-coding RNAs that intricately regulate target gene products, resulting in the inhibition of gene expression. While these miRNAs play crucial roles

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9

Roodnat, Anton W., Chelsey Doyle, Breedge Callaghan та ін. "Investigating the miRNA-mRNA interactome of human trabecular meshwork cells treated with TGF-β1 provides insights into the pathogenesis of pseudoexfoliation glaucoma". PLOS ONE 20, № 1 (2025): e0318125. https://doi.org/10.1371/journal.pone.0318125.

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Pseudoexfoliation glaucoma is a severe form of secondary open angle glaucoma and is associated with activation of the TGF-β pathway by TGF-β1. MicroRNAs (miRNAs) are small non-coding RNA species that are involved in regulation of mRNA expression and translation. To investigate what glaucomatous changes occur in the trabecular meshwork and how these changes may be regulated by miRNAs, we performed a bioinformatics analysis resulting in a miRNA-mRNA interactome. Primary human trabecular meshwork cells originating from normal donors were treated with TGF-β1 at 5 ng/mL for 24h; total RNA was extra

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10

Stebel, Sophie, Janina Breuer, and Oliver Rossbach. "Studying miRNA–mRNA Interactions: An Optimized CLIP-Protocol for Endogenous Ago2-Protein." Methods and Protocols 5, no. 6 (2022): 96. http://dx.doi.org/10.3390/mps5060096.

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Анотація:

Transcriptome-wide analysis of RNA-binding partners is commonly achieved using UV crosslinking and immunoprecipitation (CLIP). Individual-nucleotide-resolution CLIP (iCLIP)enables identification of the specific position of the protein–RNA interaction. In addition to RNA-binding proteins (RBPs), microRNA (miRNA)–mRNA interactions also play a crucial role in the regulation of gene expression. Argonaute-2 (Ago2) mediates miRNA binding to a multitude of mRNA target sites, enabling the identification of miRNA–mRNA interactions by employing modified Ago2-CLIP protocols. Here, we describe an Ago2-spe

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11

Alshalalfa, Mohammed. "MicroRNA Response Elements-Mediated miRNA-miRNA Interactions in Prostate Cancer." Advances in Bioinformatics 2012 (November 4, 2012): 1–10. http://dx.doi.org/10.1155/2012/839837.

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Анотація:

The cell is a highly organized system of interacting molecules including proteins, mRNAs, and miRNAs. Analyzing the cell from a systems perspective by integrating different types of data helps revealing the complexity of diseases. Although there is emerging evidence that microRNAs have a functional role in cancer, the role of microRNAs in mediating cancer progression and metastasis remains not fully explored. As the amount of available miRNA and mRNA gene expression data grows, more systematic methods combining gene expression and biological networks become necessary to explore miRNA function.

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12

Bonet, Fernando, Francisco Hernandez-Torres, Mónica Ramos-Sánchez, et al. "Unraveling the Etiology of Dilated Cardiomyopathy through Differential miRNA–mRNA Interactome." Biomolecules 14, no. 5 (2024): 524. http://dx.doi.org/10.3390/biom14050524.

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Dilated cardiomyopathy (DCM) encompasses various acquired or genetic diseases sharing a common phenotype. The understanding of pathogenetic mechanisms and the determination of the functional effects of each etiology may allow for tailoring different therapeutic strategies. MicroRNAs (miRNAs) have emerged as key regulators in cardiovascular diseases, including DCM. However, their specific roles in different DCM etiologies remain elusive. Here, we applied mRNA-seq and miRNA-seq to identify the gene and miRNA signature from myocardial biopsies from four patients with DCM caused by volume overload

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13

Wang, Zixing, Wenlong Xu, Haifeng Zhu, and Yin Liu. "A Bayesian Framework to Improve MicroRNA Target Prediction by Incorporating External Information." Cancer Informatics 13s7 (January 2014): CIN.S16348. http://dx.doi.org/10.4137/cin.s16348.

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MicroRNAs (miRNAs) are small regulatory RNAs that play key gene-regulatory roles in diverse biological processes, particularly in cancer development. Therefore, inferring miRNA targets is an essential step to fully understanding the functional properties of miRNA actions in regulating tumorigenesis. Bayesian linear regression modeling has been proposed for identifying the interactions between miRNAs and mRNAs on the basis of the integrated sequence information and matched miRNA and mRNA expression data; however, this approach does not use the full spectrum of available features of putative miR

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14

Tseng, Chia-Chun, Ling-Yu Wu, Wen-Chan Tsai, et al. "Differential Expression Profiles of the Transcriptome and miRNA Interactome in Synovial Fibroblasts of Rheumatoid Arthritis Revealed by Next Generation Sequencing." Diagnostics 9, no. 3 (2019): 98. http://dx.doi.org/10.3390/diagnostics9030098.

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Using next-generation sequencing to decipher the molecular mechanisms underlying aberrant rheumatoid arthritis synovial fibroblasts (RASF) activation, we performed transcriptome-wide RNA-seq and small RNA-seq on synovial fibroblasts from rheumatoid arthritis (RA) subject and normal donor. Differential expression of mRNA and miRNA was integrated with interaction analysis, functional annotation, regulatory network mapping and experimentally verified miRNA–target interaction data, further validated with microarray expression profiles. In this study, 3049 upregulated mRNA and 3552 downregulated mR

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15

Łuczkowska, Karolina, Dorota Rogińska, Zofia Ulańczyk, Edyta Paczkowska, Christian Andreas Schmidt, and Bogusław Machaliński. "Molecular Mechanisms of Bortezomib Action: Novel Evidence for the miRNA–mRNA Interaction Involvement." International Journal of Molecular Sciences 21, no. 1 (2020): 350. http://dx.doi.org/10.3390/ijms21010350.

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Bortezomib is an anti-tumor agent, which inhibits 26S proteasome degrading ubiquitinated proteins. While apoptotic transcription-associated activation in response to bortezomib has been suggested, mechanisms related to its influence on post-transcriptional gene silencing mediated regulation by non-coding RNAs remain not fully elucidated. In the present study, we examined changes in global gene and miRNA expression and analyzed the identified miRNA–mRNA interactions after bortezomib exposure in human neuroblastoma cells to define pathways affected by this agent in this type of cells. Cell viabi

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16

Wei, Chao, Lei Wang, and Han Zhang. "An ensemble method to predict target genes and pathways in uveal melanoma." Open Life Sciences 13, no. 1 (2018): 90–96. http://dx.doi.org/10.1515/biol-2018-0013.

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AbstractObjectiveThis work proposes to predict target genes and pathways for uveal melanoma (UM) based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC), a causal inference method (IDA) and a regression method (Lasso) utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions

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17

Afonso-Grunz, Fabian, and Sören Müller. "Principles of miRNA–mRNA interactions: beyond sequence complementarity." Cellular and Molecular Life Sciences 72, no. 16 (2015): 3127–41. http://dx.doi.org/10.1007/s00018-015-1922-2.

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18

Zhang, Yunpeng, Wei Liu, Yanjun Xu, et al. "Identification of Subtype Specific miRNA-mRNA Functional Regulatory Modules in Matched miRNA-mRNA Expression Data: Multiple Myeloma as a Case." BioMed Research International 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/501262.

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Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong

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19

Wu, Wei, Lingxiang Wu, Mengyan Zhu, et al. "miRNA Mediated Noise Making of 3′UTR Mutations in Cancer." Genes 9, no. 11 (2018): 545. http://dx.doi.org/10.3390/genes9110545.

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Somatic mutations in 3′-untranslated regions (3′UTR) do not alter amino acids and are considered to be silent in cancers. We found that such mutations can promote tumor progression by altering microRNA (miRNA) targeting efficiency and consequently affecting miRNA–mRNA interactions. We identified 67,159 somatic mutations located in the 3′UTRs of messenger RNAs (mRNAs) which can alter miRNA–mRNA interactions (functional somatic mutations, funcMutations), and 69.3% of these funcMutations (the degree of energy change > 12 kcal/mol) were identified to significantly promote loss of miRNA-mRNA bin

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20

Yan, Li, Demin Jiao, Huizhen Hu, et al. "Identification of lymph node metastasis-related microRNAs in lung adenocarcinoma and analysis of the underlying mechanisms using a bioinformatics approach." Experimental Biology and Medicine 242, no. 7 (2016): 709–17. http://dx.doi.org/10.1177/1535370216677353.

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This study aimed to screen lymphatic metastasis-related microRNAs (miRNAs) in lung adenocarcinoma and explore their underlying mechanisms using bioinformatics. The miRNA expression in primary lung adenocarcinoma, matched adjacent non-tumorigenic and lymph node metastasis tissues of patients were profiled via microarray. The screened metastasis-related miRNAs were then validated using quantitative real-time PCR in a second cohort of lung adenocarcinoma patients with lymphatic metastasis. Significance was determined using a paired t-test. Target genes of the metastasis-related miRNAs were predic

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21

Mukushkina, D. D., A. T. Ivashchenko, and S. Labeit. "FEATURES OF miRNA ASSOCIATIONS WITH mRNA OF MYOCARDIAL INFARCTION CANDIDATE GENES." REPORTS 2, no. 336 (2021): 46–53. http://dx.doi.org/10.32014/2021.2518-1483.29.

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Cardiovascular diseases, in particular myocardial infarction, are one of the most common causes of death in the world. To date, the risk assessment strategy infarction and post-infarction complications represent a significant problem sensitivity and predictive value of modern methods and markers, so the identification of new genetic markers is an actual problem. In this research, functionally significant candidate genes were studied, which are involved in the processes associated with the pathogenesis of myocardial infarction, in lipid metabolism, thrombus formation, endothelial dysfunction, a

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22

Fang, Yi, Xiaoyong Pan, and Hong-Bin Shen. "Recent Deep Learning Methodology Development for RNA–RNA Interaction Prediction." Symmetry 14, no. 7 (2022): 1302. http://dx.doi.org/10.3390/sym14071302.

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Genetic regulation of organisms involves complicated RNA–RNA interactions (RRIs) among messenger RNA (mRNA), microRNA (miRNA), and long non-coding RNA (lncRNA). Detecting RRIs is beneficial for discovering biological mechanisms as well as designing new drugs. In recent years, with more and more experimentally verified RNA–RNA interactions being deposited into databases, statistical machine learning, especially recent deep-learning-based automatic algorithms, have been widely applied to RRI prediction with remarkable success. This paper first gives a brief introduction to the traditional machin

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23

Li, A., J. Zhang, Z. Zhou, L. Wang, X. Sun, and Y. Liu. "Genome-scale identification of miRNA-mRNA and miRNA-lncRNA interactions in domestic animals." Animal Genetics 46, no. 6 (2015): 716–19. http://dx.doi.org/10.1111/age.12329.

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24

Frohn, Anne, H. Christian Eberl, Julia Stöhr, et al. "Dicer-dependent and -independent Argonaute2 Protein Interaction Networks in Mammalian Cells." Molecular & Cellular Proteomics 11, no. 11 (2012): 1442–56. http://dx.doi.org/10.1074/mcp.m112.017756.

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Argonaute (Ago) proteins interact with small regulatory RNAs such as microRNAs (miRNAs) and facilitate gene-silencing processes. miRNAs guide Ago proteins to specific mRNAs leading to translational silencing or mRNA decay. In order to understand the mechanistic details of miRNA function, it is important to characterize Ago protein interactors. Although several proteomic studies have been performed, it is not clear how the Ago interactome changes on miRNA or mRNA binding. Here, we report the analysis of Ago protein interactions in miRNA-containing and miRNA-depleted cells. Using stable isotope

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25

Abu-Halima, Masood, Viktoria Wagner, Lea Simone Becker, et al. "Integrated microRNA and mRNA Expression Profiling Identifies Novel Targets and Networks Associated with Ebstein’s Anomaly." Cells 10, no. 5 (2021): 1066. http://dx.doi.org/10.3390/cells10051066.

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Little is known about abundance level changes of circulating microRNAs (miRNAs) and messenger RNAs (mRNA) in patients with Ebstein’s anomaly (EA). Here, we performed an integrated analysis to identify the differentially abundant miRNAs and mRNA targets and to identify the potential therapeutic targets that might be involved in the mechanisms underlying EA. A large panel of human miRNA and mRNA microarrays were conducted to determine the genome-wide expression profiles in the blood of 16 EA patients and 16 age and gender-matched healthy control volunteers (HVs). Differential abundance level of

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26

Riolo, Giulia, Silvia Cantara, Carlotta Marzocchi, and Claudia Ricci. "miRNA Targets: From Prediction Tools to Experimental Validation." Methods and Protocols 4, no. 1 (2020): 1. http://dx.doi.org/10.3390/mps4010001.

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MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in both animals and plants. By pairing to microRNA responsive elements (mREs) on target mRNAs, miRNAs play gene-regulatory roles, producing remarkable changes in several physiological and pathological processes. Thus, the identification of miRNA-mRNA target interactions is fundamental for discovering the regulatory network governed by miRNAs. The best way to achieve this goal is usually by computational prediction followed by experimental validation of these miRNA-mRNA interactions. This review summarizes the key strateg

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27

Li, Jianqing, Xue Yin, Bingyu Zhang, Chen Li, and Peirong Lu. "Bioinformatical Analysis of miRNA-mRNA Interaction Network Underlying Macrophage Aging and Cholesterol-Responsive Difference between Young and Aged Macrophages." BioMed Research International 2020 (June 13, 2020): 1–11. http://dx.doi.org/10.1155/2020/9267475.

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Purpose. Macrophage aging is involved with the occurrence and progression of age-related macular degeneration (AMD). The purpose of this study was to identify the specific microRNAs (miRNA), mRNAs, and their interactions underlying macrophage aging and response to cholesterol through bioinformatical analysis in order to get a better understanding of the mechanism of AMD. Methods. The microarray data were obtained from Gene Expression Omnibus (accession GSE111304 and GSE111382). The age-related differentially expressed genes in macrophages were identified using R software. Further miRNA-mRNA in

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Balakrishnan, Ilango, Xiaodong Yang, Beverly Torok-Storb, Jay Hesselberth, and Manoj Pillai. "High Throughput Sequencing Following Cross-Linked Immune Precipitation (HITS-CLIP) of Argonaute (AGO) Identifies Mir-193a as a Regulator of Jagged1 In Marrow Stromal Cells." Blood 116, no. 21 (2010): 3847. http://dx.doi.org/10.1182/blood.v116.21.3847.3847.

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Abstract Abstract 3847 MicroRNAs (miRNAs) are small non-coding RNAs with important roles in the post-transcriptional regulation of up to 30% of all vertebrate genes. Traditional methods to determine miRNA-mRNA interactions have included transcriptional profiling of miRNAs, bio-informatic prediction of miRNA-mRNA binding, analysis of 3` untranslated region (3`UTR) binding of miRNAs and over-expression of miRNAs in relevant cell types. These studies however fall short of demonstrating direct interaction between a miRNA and its target mRNAs. We applied a recently described biochemical technique o

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Yu, Liwei, Tengfei Yao, Zhoulei Jiang, and Tong Xu. "Integrated Analysis of miRNA-mRNA Regulatory Networks Associated with Osteonecrosis of the Femoral Head." Evidence-Based Complementary and Alternative Medicine 2021 (August 12, 2021): 1–11. http://dx.doi.org/10.1155/2021/8076598.

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Osteonecrosis of the femoral head (ONFH) accounts for as many as 18% of total hip arthroplasties. Knowledge of genetic changes and molecular abnormalities could help identify individuals considered to be at a higher risk of developing ONFH. In this study, we sought to identify differentially expressed miRNAs (DEmiRs) and genes (DEGs) associated with ONFH by integrated bioinformatics analyses as well as to construct the miRNA-mRNA regulatory network involving in the pathogenesis of ONFH. We performed differential expression analysis using a gene expression profile GSE123568 and a miRNA expressi

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Yang, Zhifeng, Zili Liu, Lingqiu Meng, and Shuyan Ma. "Identification of key pathways regulated by a set of competitive long non-coding RNAs in oral squamous cell carcinoma." Journal of International Medical Research 47, no. 4 (2019): 1758–65. http://dx.doi.org/10.1177/0300060519827190.

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Objective The aim of this study was to identify important pathways regulated by a set of long non-coding RNAs (lncRNAs) in oral squamous cell carcinoma (OSCC). Methods A lncRNA-mediated competitive endogenous RNA network (LMCN) was constructed using information on microRNA (miRNA)–mRNA interactions and lncRNA–miRNA intersections from the E-GEOD-37991 transcription profiling data in the ArrayExpress database. A random walk with restart ranking algorithm was then applied to evaluate the influences of protein-coding genes regulated by competitive lncRNAs. Pathway enrichment scores were calculated

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Tai, Yang, Chong Zhao, Jinhang Gao, Tian Lan, and Huan Tong. "Identification of miRNA-target gene regulatory networks in liver fibrosis based on bioinformatics analysis." PeerJ 9 (August 6, 2021): e11910. http://dx.doi.org/10.7717/peerj.11910.

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Background Liver cirrhosis is one of the leading causes of death worldwide. MicroRNAs (miRNAs) can regulate liver fibrosis, but the underlying mechanisms are not fully understood, and the interactions between miRNAs and mRNAs are not clearly elucidated. Methods miRNA and mRNA expression arrays of cirrhotic samples and control samples were acquired from the Gene Expression Omnibus database. miRNA-mRNA integrated analysis, functional enrichment analysis and protein-protein interaction (PPI) network construction were performed to identify differentially expressed miRNAs (DEMs) and mRNAs (DEGs), m

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Guo, Li, Yang Zhao, Sheng Yang, Hui Zhang, and Feng Chen. "An Integrated Analysis of miRNA, lncRNA, and mRNA Expression Profiles." BioMed Research International 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/345605.

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Increasing amounts of evidence indicate that noncoding RNAs (ncRNAs) have important roles in various biological processes. Here, miRNA, lncRNA, and mRNA expression profiles were analyzed in human HepG2 and L02 cells using high-throughput technologies. An integrative method was developed to identify possible functional relationships between different RNA molecules. The dominant deregulated miRNAs were prone to be downregulated in tumor cells, and the most abnormal mRNAs and lncRNAs were always upregulated. However, the genome-wide analysis of differentially expressed RNA species did not show si

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da Silveira, Willian, Ludivine Renaud, Jonathan Simpson, et al. "miRmapper: A Tool for Interpretation of miRNA–mRNA Interaction Networks." Genes 9, no. 9 (2018): 458. http://dx.doi.org/10.3390/genes9090458.

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It is estimated that 30% of all genes in the mammalian cells are regulated by microRNA (miRNAs). The most relevant miRNAs in a cellular context are not necessarily those with the greatest change in expression levels between healthy and diseased tissue. Differentially expressed (DE) miRNAs that modulate a large number of messenger RNA (mRNA) transcripts ultimately have a greater influence in determining phenotypic outcomes and are more important in a global biological context than miRNAs that modulate just a few mRNA transcripts. Here, we describe the development of a tool, “miRmapper”, which i

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Fan, Weiyang, Rui Shi, Minyi Guan, et al. "The Effects of Naringenin on miRNA-mRNA Profiles in HepaRG Cells." International Journal of Molecular Sciences 22, no. 5 (2021): 2292. http://dx.doi.org/10.3390/ijms22052292.

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Naringenin, a natural flavonoid widely found in citrus fruits, has been reported to possess anti-oxidant, anti-inflammatory, and hepatoprotective properties as a natural dietary supplement. However, the regulatory mechanism of naringenin in human liver remains unclear. In the present study, messenger RNA sequencing (mRNA-seq), microRNA sequencing (miRNA-seq), and real-time qPCR were used to distinguish the expression differences between control and naringenin-treated HepaRG cells. We obtained 1037 differentially expressed mRNAs and 234 miRNAs. According to the target prediction and integration

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Misiak, Danny, Marcus Bauer, Jana Lange, et al. "MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression." Cancers 13, no. 23 (2021): 5913. http://dx.doi.org/10.3390/cancers13235913.

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Anaplastic thyroid carcinoma (ATC) is the most fatal and rapidly evolving endocrine malignancy invading the head and neck region and accounts for up to 50% of thyroid cancer-associated deaths. Deregulation of the microRNA (miRNA) expression promotes thyroid carcinoma progression by modulating the reorganization of the ATC transcriptome. Here, we applied comparative miRNA–mRNA sequencing on a cohort of 28 thyroid carcinomas to unravel the association of deregulated miRNA and mRNA expression. This identified 85 miRNAs significantly deregulated in ATC. By establishing a new analysis pipeline, we

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Williams, Allison Lesher, Vedbar S. Khadka, Ma C. T. Anagaran, et al. "miR-125 family regulates XIRP1 and FIH in response to myocardial infarction." Physiological Genomics 52, no. 8 (2020): 358–68. http://dx.doi.org/10.1152/physiolgenomics.00041.2020.

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MicroRNAs (miRNAs) are powerful regulators of protein expression. Many play important roles in cardiac development and disease. While several miRNAs and targets have been well characterized, the abundance of miRNAs and the numerous potential targets for each suggest that the vast majority of these interactions have yet to be described. The goal of this study was to characterize miRNA expression in the mouse heart after coronary artery ligation (LIG) and identify novel mRNA targets altered during the initial response to ischemic stress. We performed small RNA sequencing (RNA-Seq) of ischemic he

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Nersisyan, Stepan, Alexei Galatenko, Vladimir Galatenko, Maxim Shkurnikov, and Alexander Tonevitsky. "miRGTF-net: Integrative miRNA-gene-TF network analysis reveals key drivers of breast cancer recurrence." PLOS ONE 16, no. 4 (2021): e0249424. http://dx.doi.org/10.1371/journal.pone.0249424.

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Analysis of regulatory networks is a powerful framework for identification and quantification of intracellular interactions. We introduce miRGTF-net, a novel tool for construction of miRNA-gene-TF networks. We consider multiple transcriptional and post-transcriptional interaction types, including regulation of gene and miRNA expression by transcription factors, gene silencing by miRNAs, and co-expression of host genes with their intronic miRNAs. The underlying algorithm uses information on experimentally validated interactions as well as integrative miRNA/mRNA expression profiles in a given se

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Lin, Lihui, Yuting Liang, Tianyu Cao, et al. "Transcriptome profiling and ceRNA network of small extracellular vesicles from resting and degranulated mast cells." Epigenomics 15, no. 17 (2023): 845–62. http://dx.doi.org/10.2217/epi-2023-0175.

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Aim: This study aimed to investigate the transcriptomic characteristics and interactions between competitive endogenous RNAs (ceRNAs) within small extracellular vesicles (sEVs) derived from mast cells (MCs). Methods: Transcriptome sequencing analyzed lncRNA, circRNA and mRNA expression in resting and degranulated MC-derived sEVs. Constructed ceRNA regulatory network through correlation analysis and target gene prediction. Results: Differentially expressed 1673 mRNAs, 173 lncRNAs and 531 circRNAs were observed between resting and degranulated MCs-derived sEVs. Enrichment analysis revealed invol

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Bhaumik, Panchalee, Chandrasekhar Gopalakrishnan, Balu Kamaraj, and Rituraj Purohit. "Single Nucleotide Polymorphisms in MicroRNA Binding Sites: Implications in Colorectal Cancer." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/547154.

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Cancer is a complex genetic disorder, characterised by uncontrolled cell proliferation and caused by altered expression of oncogenes and tumour suppressor genes. When cell proliferation pertains to colon, it is called colorectal cancer. Most of colorectal cancer causing genes are potential targets for the miRNA (microRNA) that bind to 3′UTR (untranslated regions) of mRNA and inhibit translation. Mutations occurring in miRNA binding regions can alter the miRNA, mRNA combination, and can alter gene expression drastically. We hypothesized that 3′UTR mutation in miRNA binding site could alter the

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Thody, Joshua, Vincent Moulton, and Irina Mohorianu. "PAREameters: a tool for computational inference of plant miRNA–mRNA targeting rules using small RNA and degradome sequencing data." Nucleic Acids Research 48, no. 5 (2020): 2258–70. http://dx.doi.org/10.1093/nar/gkz1234.

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Abstract MicroRNAs (miRNAs) are short, non-coding RNAs that modulate the translation-rate of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to sequence-specific targets. In plants, this typically results in cleavage and subsequent degradation of the mRNA. Degradome sequencing is a high-throughput technique developed to capture cleaved mRNA fragments and thus can be used to support miRNA target prediction. The current criteria used for miRNA target prediction were inferred on a limited number of experimentally validated A. thaliana interactions and were adapted to fit the

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Solé, Anna, Núria Mencia, Xenia Villalobos, Véronique Noé, and Carlos J. Ciudad. "Validation of miRNA-mRNA interactions by electrophoretic mobility shift assays." BMC Research Notes 6, no. 1 (2013): 454. http://dx.doi.org/10.1186/1756-0500-6-454.

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Liu, Yanwei, Kai Tang, Wei Yan, et al. "Identifying Ki-67 specific miRNA–mRNA interactions in malignant astrocytomas." Neuroscience Letters 546 (June 2013): 36–41. http://dx.doi.org/10.1016/j.neulet.2013.04.030.

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Cloonan, Nicole. "Re‐thinking miRNA‐mRNA interactions: Intertwining issues confound target discovery." BioEssays 37, no. 4 (2015): 379–88. http://dx.doi.org/10.1002/bies.201400191.

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Xie, Peng, Yu Liu, Yanda Li, Michael Q. Zhang, and Xiaowo Wang. "MIROR: a method for cell-type specific microRNA occupancy rate prediction." Mol. BioSyst. 10, no. 6 (2014): 1377–84. http://dx.doi.org/10.1039/c3mb70610a.

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Yang, Zongxing, Jin Yang, Juan Wang, et al. "Identify Potential Regulators in HIV-1 Latency by Joint microRNA and mRNA Analysis." Cellular Physiology and Biochemistry 36, no. 2 (2015): 569–84. http://dx.doi.org/10.1159/000430121.

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Background/Aims: The main obstacle to cure HIV infection is the existence of long-lasting latent reservoirs. Many efforts have been made to understand basal mechanisms of HIV-1 latency, in which miRNAs play an important role. However, integrated analysis of miRNA and mRNA expression in HIV-1 latency is lacking. Methods and Results: Global miRNA and mRNA expression was determined by microarrays and quantitative reverse transcription PCR in well-characterized HIV-1 latently and actively infected cells, respectively. Interactions of miRNA-mRNA, mRNA-mRNA, and transcription factor-miRNA pairs were

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Pérez-Cremades, Daniel, Ana B. Paes, Xavier Vidal-Gómez, Ana Mompeón, Carlos Hermenegildo, and Susana Novella. "Regulatory Network Analysis in Estradiol-Treated Human Endothelial Cells." International Journal of Molecular Sciences 22, no. 15 (2021): 8193. http://dx.doi.org/10.3390/ijms22158193.

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Background/Aims: Estrogen has been reported to have beneficial effects on vascular biology through direct actions on endothelium. Together with transcription factors, miRNAs are the major drivers of gene expression and signaling networks. The objective of this study was to identify a comprehensive regulatory network (miRNA–transcription factor–downstream genes) that controls the transcriptomic changes observed in endothelial cells exposed to estradiol. Methods: miRNA/mRNA interactions were assembled using our previous microarray data of human umbilical vein endothelial cells (HUVEC) treated wi

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Pushkin, A. A., E. A. Dzenkova, N. N. Timoshkina, and D. Yu Gvaldin. "Data analysis of high-throughput sequencing and microarray to identify key signatures of microribonucleic acids in glioblastoma." Research and Practical Medicine Journal 8, no. 3 (2021): 21–33. http://dx.doi.org/10.17709/2410-1893-2021-8-3-2.

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Purpose of the study. This research was devoted to study of mRNA and miRNA expression patterns in glioglastomas using The Cancer Genome Atlas (TCGA) data, to search for genetic determinants that determine the prognosis of patient survival and to create of interaction networks for glioblastomas.Materials and methods. Based on the data of the open TCGA database groups of glioblastomas and conventionally normal brain tissue samples were formed. Survival gene and miRNA expression data were extracted for each sample. After the data stratification by groups the differential expression analysis and s

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Ma, Xiaoli, and Wen-Xiong Wang. "Molecular Modulation of Threadfin Fish Brain to Hypoxia Challenge and Recovery Revealed by Multi-Omics Profiling." International Journal of Molecular Sciences 26, no. 4 (2025): 1703. https://doi.org/10.3390/ijms26041703.

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Migratory fish often encounter hypoxic zones during migration, which can lead to varying degrees of hypoxic stress. This issue has become increasingly severe due to human activities and climate change, which have resulted in the expansion of hypoxic zones in aquatic environments. However, there is limited research on how these species respond to hypoxic stress and subsequent recovery. In this study, we used Eleutheronema tetradactylum, a well-recognized migratory and economically valuable fish species, as a model organism. Histological analysis revealed extensive neuronal damage during hypoxia

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Xu, Jiatong, Xiaoxuan Cai, Junyang Huang, et al. "Unveiling Novel miRNA–mRNA Interactions and Their Prognostic Roles in Triple-Negative Breast Cancer: Insights into miR-210, miR-183, miR-21, and miR-181b." International Journal of Molecular Sciences 26, no. 5 (2025): 1916. https://doi.org/10.3390/ijms26051916.

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Triple-negative breast cancer (TNBC) poses a major clinical challenge due to its aggressive progression and limited treatment options, making early diagnosis and prognosis critical. MicroRNAs (miRNAs) are crucial post-transcriptional regulators that influence gene expression. In this study, we unveil novel miRNA–mRNA interactions and introduce a prognostic model based on miRNA–target interaction (MTI), integrating miRNA–mRNA regulatory correlation inference and the machine learning method to effectively predict the survival outcomes in TNBC cohorts. Using this method, we identified four key mi

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Ayaz, Hassan, Nouman Aslam, Faryal Mehwish Awan, et al. "Mapping CircRNA–miRNA–mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection." PLOS ONE 18, no. 4 (2023): e0283589. http://dx.doi.org/10.1371/journal.pone.0283589.

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Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fu

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