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Journal articles on the topic 'Bioinformatics, microRNA'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Jamali, Ali Akbar, Anthony Kusalik, and Fang-Xiang Wu. "MDIPA: a microRNA–drug interaction prediction approach based on non-negative matrix factorization." Bioinformatics 36, no. 20 (2020): 5061–67. http://dx.doi.org/10.1093/bioinformatics/btaa577.

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Abstract Motivation Evidence has shown that microRNAs, one type of small biomolecule, regulate the expression level of genes and play an important role in the development or treatment of diseases. Drugs, as important chemical compounds, can interact with microRNAs and change their functions. The experimental identification of microRNA–drug interactions is time-consuming and expensive. Therefore, it is appealing to develop effective computational approaches for predicting microRNA–drug interactions. Results In this study, a matrix factorization-based method, called the microRNA–drug interaction prediction approach (MDIPA), is proposed for predicting unknown interactions among microRNAs and drugs. Specifically, MDIPA utilizes experimentally validated interactions between drugs and microRNAs, drug similarity and microRNA similarity to predict undiscovered interactions. A path-based microRNA similarity matrix is constructed, while the structural information of drugs is used to establish a drug similarity matrix. To evaluate its performance, our MDIPA is compared with four state-of-the-art prediction methods with an independent dataset and cross-validation. The results of both evaluation methods confirm the superior performance of MDIPA over other methods. Finally, the results of molecular docking in a case study with breast cancer confirm the efficacy of our approach. In conclusion, MDIPA can be effective in predicting potential microRNA–drug interactions. Availability and implementation All code and data are freely available from https://github.com/AliJam82/MDIPA. Supplementary information Supplementary data are available at Bioinformatics online.

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Gaffo, Enrico, Michele Bortolomeazzi, Andrea Bisognin, et al. "MiR&moRe2: A Bioinformatics Tool to Characterize microRNAs and microRNA-Offset RNAs from Small RNA-Seq Data." International Journal of Molecular Sciences 21, no. 5 (2020): 1754. http://dx.doi.org/10.3390/ijms21051754.

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MicroRNA-offset RNAs (moRNAs) are microRNA-like small RNAs generated by microRNA precursors. To date, little is known about moRNAs and bioinformatics tools to inspect their expression are still missing. We developed miR&moRe2, the first bioinformatics method to consistently characterize microRNAs, moRNAs, and their isoforms from small RNA sequencing data. To illustrate miR&moRe2 discovery power, we applied it to several published datasets. MoRNAs identified by miR&moRe2 were in agreement with previous research findings. Moreover, we observed that moRNAs and new microRNAs predicted by miR&moRe2 were downregulated upon the silencing of the microRNA-biogenesis pathway. Further, in a sizeable dataset of human blood cell populations, tens of novel miRNAs and moRNAs were discovered, some of them with significantly varied expression levels among the cell types. Results demonstrate that miR&moRe2 is a valid tool for a comprehensive study of small RNAs generated from microRNA precursors and could help to investigate their biogenesis and function.

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Miskiewicz, J., K. Tomczyk, A. Mickiewicz, J. Sarzynska, and M. Szachniuk. "Bioinformatics Study of Structural Patterns in Plant MicroRNA Precursors." BioMed Research International 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/6783010.

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According to the RNA world theory, RNAs which stored genetic information and catalyzed chemical reactions had their contribution in the formation of current living organisms. In recent years, researchers studied this molecule diversity, i.a. focusing on small non-coding regulatory RNAs. Among them, of particular interest is evolutionarily ancient, 19–24 nt molecule of microRNA (miRNA). It has been already recognized as a regulator of gene expression in eukaryotes. In plants, miRNA plays a key role in the response to stress conditions and it participates in the process of growth and development. MicroRNAs originate from primary transcripts (pri-miRNA) encoded in the nuclear genome. They are processed from single-stranded stem-loop RNA precursors containing hairpin structures. While the mechanism of mature miRNA production in animals is better understood, its biogenesis in plants remains less clear. Herein, we present the results of bioinformatics analysis aimed at discovering how plant microRNAs are recognized within their precursors (pre-miRNAs). The study has been focused on sequential and structural motif identification in the neighbourhood of microRNA.

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Vrahatis, Aristidis G., Konstantina Dimitrakopoulou, Panos Balomenos, Athanasios K. Tsakalidis, and Anastasios Bezerianos. "CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis." Bioinformatics 32, no. 6 (2015): 884–92. http://dx.doi.org/10.1093/bioinformatics/btv673.

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Abstract Motivation: In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific ‘active parts’ of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical ‘themes’—in the form of enriched biologically relevant microRNA-mediated subpathways—that determine the functionality of signaling networks across time. Results: To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. Availability and implementation: CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/. Contact: tassos.bezerianos@nus.edu.sg. Supplementary information: Supplementary data are available at Bioinformatics online.

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Zhu, Yujie, Yuxin Lin, Wenying Yan, et al. "Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach." BioMed Research International 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/4618323.

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Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis.

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6

Moore, Alyssa C., Jonathan S. Winkjer, and Tsai-Tien Tseng. "Bioinformatics Resources for MicroRNA Discovery." Biomarker Insights 10s4 (January 2015): BMI.S29513. http://dx.doi.org/10.4137/bmi.s29513.

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Biomarker identification is often associated with the diagnosis and evaluation of various diseases. Recently, the role of microRNA (miRNA) has been implicated in the development of diseases, particularly cancer. With the advent of next-generation sequencing, the amount of data on miRNA has increased tremendously in the last decade, requiring new bioinformatics approaches for processing and storing new information. New strategies have been developed in mining these sequencing datasets to allow better understanding toward the actions of miRNAs. As a result, many databases have also been established to disseminate these findings. This review focuses on several curated databases of miRNAs and their targets from both predicted and validated sources.

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Jiang, Limin, Jingjun Zhang, Ping Xuan, and Quan Zou. "BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species." BioMed Research International 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/9565689.

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MicroRNAs (miRNAs) are a set of short (21–24 nt) noncoding RNAs that play significant regulatory roles in cells. In the past few years, research on miRNA-related problems has become a hot field of bioinformatics because of miRNAs’ essential biological function. miRNA-related bioinformatics analysis is beneficial in several aspects, including the functions of miRNAs and other genes, the regulatory network between miRNAs and their target mRNAs, and even biological evolution. Distinguishing miRNA precursors from other hairpin-like sequences is important and is an essential procedure in detecting novel microRNAs. In this study, we employed backpropagation (BP) neural network together with 98-dimensional novel features for microRNA precursor identification. Results show that the precision and recall of our method are 95.53% and 96.67%, respectively. Results further demonstrate that the total prediction accuracy of our method is nearly 13.17% greater than the state-of-the-art microRNA precursor prediction software tools.

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Phuong, Ho Thi Bich, Vien Ngoc Thach, Luong Hoang Ngan, and Le Thi Truc Linh. "Using Bioinformatics to predict potential targets of Microrna-144 in osteoarthritis." ENGINEERING AND TECHNOLOGY 8, no. 1 (2020): 43–52. http://dx.doi.org/10.46223/hcmcoujs.tech.en.8.1.335.2018.

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MicroRNAs are short endogenous non-coding RNA molecules, typically 19-25 nucleotides in length, which negatively regulate gene expression through binding to 3’UTR of target mRNAs, leading to repression of protein translation or target mRNA degradation. MicroRNA-144 (miR-144) was found as an abnormal expression in various diseases, including osteoarthritis (OA). We have identified increased microRNA-144 expression in early phase and end stage of OA. However, the molecular mechanism of this increase has not been yet to be determined yet. Using bioinformatics tools, we found more than 4,000 mRNAs that are predicted to be potential direct targets of miR-144, including mRNAs involved in the critical signaling pathways in OA e.g. TGFβ/Smad2/3 and WNT/β-catenin. Results from this research provide information for future ex periments to validate miR-144 potential targets.

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Huntley, Rachael P., Barbara Kramarz, Tony Sawford, et al. "Expanding the horizons of microRNA bioinformatics." RNA 24, no. 8 (2018): 1005–17. http://dx.doi.org/10.1261/rna.065565.118.

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10

Ghosh, Zhumur, Jayprokas Chakrabarti, and Bibekanand Mallick. "miRNomics—The bioinformatics of microRNA genes." Biochemical and Biophysical Research Communications 363, no. 1 (2007): 6–11. http://dx.doi.org/10.1016/j.bbrc.2007.08.030.

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11

Zhang, Wei, Kai Liao, and Dongning Liu. "MiRNA-12129 Suppresses Cell Proliferation and Block Cell Cycle Progression by Targeting SIRT1 in GASTRIC Cancer." Technology in Cancer Research & Treatment 19 (January 1, 2020): 153303382092814. http://dx.doi.org/10.1177/1533033820928144.

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Gastric cancer is the most commonly occurring cancer with a rapidly increasing incidence rate worldwide. The underlying molecular mechanisms of gastric cancer require further investigation. MicroRNAs exhibit tissue sensitivity as tumor biomarkers that play a role by promoting tumor growth as oncogenes or tumor suppressor genes. We evaluated the effects of microRNA-12129 on gastric cancer and identified the underlying mechanisms of microRNA-12129. Quantitative real-time polymerase chain reaction was conducted to determine the expression levels of microRNA-12129 and sirtuin 1 in vivo and in vitro, and Western blot analysis was performed to detect sirtuin 1 at the protein level in gastric cancer cell lines. Cell proliferation and cell cycle progression were detected by Cell Counting Kit-8 assay and flow cytometry analysis, respectively. The potential targets of microRNA-12129 were predicted by bioinformatics analysis. The targets of microRNA-12129 were confirmed by luciferase reporter assay and rescue assay. We found that microRNA-12129 was downregulated in gastric cancer tissues and gastric cancer cell lines and was significantly associated with the prognosis of patients with gastric cancer. In addition, microRNA-12129 overexpression suppressed tumor cell proliferation and blocked cell cycle progression. Bioinformatics analysis and luciferase reporter assay suggested that sirtuin 1 was a target of microRNA-12129, and sirtuin 1 expression was negatively related to microRNA-12129. Restoration of sirtuin 1 partly reduced the inhibition of cell proliferation and cell cycle progression induced by microRNA-144. Our results collectively suggested that microRNA-12129 suppressed cell proliferation and cell cycle progression in gastric cancer by targeting sirtuin 1. These findings indicated that manipulation of microRNA-12129 expression could help develop a novel therapeutic strategy for gastric cancer.

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Alexiou, Panagiotis, Manolis Maragkakis, and Artemis G. Hatzigeorgiou. "Online resources for microRNA analysis." Journal of Nucleic Acids Investigation 2, no. 1 (2011): 4. http://dx.doi.org/10.4081/jnai.2011.2161.

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The use of online tools for bioinformatics analyses is becoming increasingly widespread. Resources specific to the field of microRNAs are available, varying in scope and usability. Online tools are the most useful for casual as well as power users since they need no installation, are hardware independent and are used mostly through graphic user interfaces and links to external sources. Here, we present an overview of useful online resources that have to do with microRNA genomics, gene finding, target prediction and functional analysis.

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Han, De Ming, Zi Jun Shen, and Li Hui Zhao. "Study on the Function of miRNA-155 Target Using Bioinformatics Methods." Advanced Materials Research 709 (June 2013): 858–61. http://dx.doi.org/10.4028/www.scientific.net/amr.709.858.

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MicroRNAs are small non-coding RNAs that act at the post-transcriptional level, regulating protein expression by repressing translation or destabilizing mRNA target. We searched information about miR-155 in miRBase. Target genes of miR-155 are predicted by four miRNA target gene prediction softwares. The result shows that miR-155 was involved in proliferation, differentiation and apoptosis. These results can contribute to further study on the role of microRNA in diagnosis and treatment of cancer.

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Gulyaeva, L. F., M. D. Chanyshev, S. K. Kolmykov, D. S. Ushakov, and S. S. Nechkin. "Effect of xenobiotics on microrna expression in rat liver." Biomeditsinskaya Khimiya 62, no. 2 (2016): 154–59. http://dx.doi.org/10.18097/pbmc20166202154.

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Using bioinformatics analysis we selected microRNAs which could bind 3'-UTR-region of cytochrome P450 (CYP) genes. Three microRNA miR-21, -221, -222, their potential targets might be mRNA for CYP1A1, and two microRNA miR-143, miR-152 for CYP2B1 accordingly were selected for experimental verification. Expression level of these microRNAs in rat liver upon benzo(a)pyrene (BP), phenobarbital (PB), and DDT induction was determined using RT-qPCR method. In rats treated by both BP, and DDT the hepatic content of miR-21, -221, -222 significantly demonstrated a 2-3-fold decrease. The decrease in miR expression was accompanied by a considerable (5.5-8.7-fold) increase in the CYP1A1-mediated EROD activity. The expression of miR-143 remained unchanged after the PB treatment, while the expression of miR-152 increased by 2 times, however, the (10.5-fold) increase in PROD activity of CYP2B was much higher. In the DDT-treated liver PROD activity increased by 20 times, the expression of miR-152 didn't change, and the expression of miR-143 increased by 2 times. The bioinformatics analysis of interactions between microRNAs and targets showed that the studied miRs can potentially bind 3'-end of AhR, ESR1, GR, CCND1, PTEN mRNA. Thus, the expression profile of miR-21, -221, -222, -143, -152 might change under the xenobiotics exposure. In silico analysis confirmed, that microRNAs target not only cytochrome P450 mRNA but also other genes, including those involved in hormonal carcinogenesis, they also can be regulated with studied miRs

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Yousef, Malik, Segun Jung, Andrew V. Kossenkov, Louise C. Showe, and Michael K. Showe. "Naïve Bayes for microRNA target predictions—machine learning for microRNA targets." Bioinformatics 23, no. 22 (2007): 2987–92. http://dx.doi.org/10.1093/bioinformatics/btm484.

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Potla, Pratibha, Shabana Amanda Ali, and Mohit Kapoor. "A bioinformatics approach to microRNA-sequencing analysis." Osteoarthritis and Cartilage Open 3, no. 1 (2021): 100131. http://dx.doi.org/10.1016/j.ocarto.2020.100131.

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17

Wang, Xiaoxia, Chun Song, Xiao Zhou, et al. "Mitochondria Associated MicroRNA Expression Profiling of Heart Failure." BioMed Research International 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/4042509.

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Heart failure (HF) is associated with mitochondrial dysfunction and energy metabolism impairment. MicroRNAs are implicated in the development of heart failure. However, the mitochondria enriched microRNA during heart failure remains elusive. Here, we generated a pressure overload-induced early and late stage heart failure model at 4 weeks and 8 weeks following transverse aortic constriction (TAC) in mice. We found that expression of mitochondrion protein COX4 was highly enriched in isolated mitochondria from cardiac tissues while GAPDH could hardly be detected. Furthermore, small RNA sequencing for mitochondria RNAs from failing hearts was performed. It was found that 69 microRNAs were upregulated and 2 were downregulated in early heart failure, while 16 microRNAs were upregulated and 6 were downregulated in late heart failure. 15 microRNA candidates were measured in both mitochondria and total cardiac tissues of heart failure by real-time PCR. MiR-696, miR-532, miR-690, and miR-345-3p were enriched in mitochondria from the failing heart at early stage. Bioinformatics analysis showed that mitochondria enriched microRNAs in HF were associated with energy metabolism and oxidative stress pathway. For the first time, we demonstrated microRNAs were enriched in mitochondria during heart failure, which established a link between microRNA and mitochondrion in heart failure.

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Georgantas, Robert W., Richard Hildreth, Sebastien Morisot, Jonathan Alder, and Curt I. Civin. "MicroRNA hsa-mir-155 Blocks Myeloid and Erythroid Differentiation of Human CD34+ Cells." Blood 108, no. 11 (2006): 1337. http://dx.doi.org/10.1182/blood.v108.11.1337.1337.

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Abstract In a large microRNA-array and bioinformatics study, we determined all of the microRNAs (miRs) expressed by human CD34+ hematopoietic stem-progenitor cells (HSPCs) from bone marrow and G-CSF mobilized blood. When we combined miR expression data, mRNA expression data from a previous study (Georgantas et al, Cancer Research 64:4434), and data from various published miR-target prediction algorithms, we were able to bioinformaticly predict the actions of miRs within the hematopoietic system. MircoRNA hsa-mir-155 was highly expressed in CD34+ HSPCs, and was predicted by our bioinformatics database to target several HSPC-expressed mRNAs (CREBBP, CXCR4, Jun, Meis-1, PU.1, AGTRI, AGTRII, Fos, and GATA3) that encode proteins known to be involved in myeloid and/or erythroid differentiation. We used luciferase-3′UTR reporter constructs to confirm that protein expression from these mRNAs were in fact down regulated by microRNA. As an initial test of mir-155′s effect on hematopoietic differentiation, K562 cells were transduced with hsa-mir-155 lentivirus and then exposed to TPA to induce megakaryocyte differentiation, or to hemin to induce erythroid differentiation. Compared to controls, miR-155 reduced K562 megakaryocyte differentiation by ~70%, and erythroid differentiation by &gt;90%. Thus, mir-155 appears to be sufficient to inhibit both megakayrocyte and erythroid differentiation. K562 proliferation was not affected by mir-155, showing that the differentiation block was not due to cell cycle arrest. MicroRNA hsa-mir-155-transduced human mobilized blood CD34+ cells generated &gt;70% fewer myeloid and erythroid colonies than controls in colony forming (CFC) assays, further indicating that mir-155 blocks both myeloid and erythroid differentiation. We are currently further testing the effects of mir-155 on differentiation of CD34+ cells in vitro, and also in vivo on their ability to engraft immunodeficient mice.

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Shao, Yang, Bin Liang, Fei Long, and Shu-Juan Jiang. "Diagnostic MicroRNA Biomarker Discovery for Non-Small-Cell Lung Cancer Adenocarcinoma by Integrative Bioinformatics Analysis." BioMed Research International 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/2563085.

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Lung cancer is the leading cause of cancer death and its incidence is ranked high in men and women worldwide. Non-small-cell lung cancer (NSCLC) adenocarcinoma is one of the most frequent histological subtypes of lung cancer. The aberration profile and the molecular mechanism driving its progression are the key for precision therapy of lung cancer, while the screening of biomarkers is essential to the precision early diagnosis and treatment of the cancer. In this work, we applied a bioinformatics method to analyze the dysregulated interaction network of microRNA-mRNA in NSCLC, based on both the gene expression data and the microRNA-gene regulation network. Considering the properties of the substructure and their biological functions, we identified the putative diagnostic biomarker microRNAs, some of which have been reported on the PubMed citations while the rest, that is, miR-204-5p, miR-567, miR-454-3p, miR-338-3p, and miR-139-5p, were predicted as the putative novel microRNA biomarker for the diagnosis of NSCLC adenocarcinoma. They were further validated by functional enrichment analysis of their target genes. These findings deserve further experimental validations for future clinical application.

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Liu, Zhenyang, Junyu Wang, Yunjun Li, Juan Fan, Lihua Chen, and Ruxiang Xu. "MicroRNA-153 regulates glutamine metabolism in glioblastoma through targeting glutaminase." Tumor Biology 39, no. 2 (2017): 101042831769142. http://dx.doi.org/10.1177/1010428317691429.

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Glioblastoma is the most aggressive manifestation of malignant gliomas and considered to be among the deadliest forms of human cancers. MicroRNAs are found to tightly regulate diverse biological processes and considered to play important roles in cancer etiology. In this study, we found that microRNA-153 was significantly downregulated in glioblastoma tissues compared to matched non-tumor tissues and in glioblastoma cell lines. To investigate the potential function of microRNA-153 in glioblastoma, we transfected glioblastoma cell line U87MG as well as U373MG with synthetic microRNA-153 oligos and observed decreased cell proliferation and increased apoptosis. We further found that microRNA-153 restrained glutamine utilization and glutamate generation. Bioinformatics analysis revealed that glutaminase, which catalyzed the formation of glutamate from glutamine, is the potential target of microRNA-153. Indeed, microRNA-153 cannot further reduce glutamine utilization when glutaminase was knocked down. Overexpression of glutaminase abrogates the effect of microRNA-153 on glutamine utilization. Furthermore, the relative expression of microRNA-153 and glutaminase in glioblastoma versus matched non-tumor tissues showed a reverse correlation, further indicating that microRNA-153 may negatively regulate glutaminase in vivo. These results demonstrate an unexpected role of microRNA-153 in regulating glutamine metabolism and strengthen the role of microRNA-153 as a therapeutic target in glioblastoma.

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Kuijjer, Marieke L., Maud Fagny, Alessandro Marin, John Quackenbush, and Kimberly Glass. "PUMA: PANDA Using MicroRNA Associations." Bioinformatics 36, no. 18 (2020): 4765–73. http://dx.doi.org/10.1093/bioinformatics/btaa571.

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Abstract Motivation Conventional methods to analyze genomic data do not make use of the interplay between multiple factors, such as between microRNAs (miRNAs) and the messenger RNA (mRNA) transcripts they regulate, and thereby often fail to identify the cellular processes that are unique to specific tissues. We developed PUMA (PANDA Using MicroRNA Associations), a computational tool that uses message passing to integrate a prior network of miRNA target predictions with target gene co-expression information to model genome-wide gene regulation by miRNAs. We applied PUMA to 38 tissues from the Genotype-Tissue Expression project, integrating RNA-Seq data with two different miRNA target predictions priors, built on predictions from TargetScan and miRanda, respectively. We found that while target predictions obtained from these two different resources are considerably different, PUMA captures similar tissue-specific miRNA–target regulatory interactions in the different network models. Furthermore, the tissue-specific functions of miRNAs we identified based on regulatory profiles (available at: https://kuijjer.shinyapps.io/puma_gtex/) are highly similar between networks modeled on the two target prediction resources. This indicates that PUMA consistently captures important tissue-specific miRNA regulatory processes. In addition, using PUMA we identified miRNAs regulating important tissue-specific processes that, when mutated, may result in disease development in the same tissue. Availability and implementation PUMA is available in C++, MATLAB and Python on GitHub (https://github.com/kuijjerlab and https://netzoo.github.io/). Supplementary information Supplementary data are available at Bioinformatics online.

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Hoffman, Yonit, Dvir Dahary, Debora Rosa Bublik, Moshe Oren, and Yitzhak Pilpel. "The majority of endogenous microRNA targets within Alu elements avoid the microRNA machinery." Bioinformatics 29, no. 7 (2013): 894–902. http://dx.doi.org/10.1093/bioinformatics/btt044.

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Dezulian, T., M. Remmert, J. F. Palatnik, D. Weigel, and D. H. Huson. "Identification of plant microRNA homologs." Bioinformatics 22, no. 3 (2005): 359–60. http://dx.doi.org/10.1093/bioinformatics/bti802.

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Wang, Dong, Juan Wang, Ming Lu, Fei Song, and Qinghua Cui. "Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases." Bioinformatics 26, no. 13 (2010): 1644–50. http://dx.doi.org/10.1093/bioinformatics/btq241.

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Lv, Jinlin, Lixia Yang, Ruiwei Guo, Yankun Shi, Ziwei Zhang, and Jinshan Ye. "Ox-LDL-Induced MicroRNA-155 Promotes Autophagy in Human Endothelial Cells via Repressing the Rheb/ mTOR Pathway." Cellular Physiology and Biochemistry 43, no. 4 (2017): 1436–48. http://dx.doi.org/10.1159/000481875.

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Background/Aims: Autophagy, an evolutionary conserved biological process, is activated in cells to cope with various types of stress. MicroRNAs control several activities related to autophagy. However, the role of autophagy-related microRNAs during atherosclerosis is far from known. MicroRNA-155 was identified to be a crucial regulator of atherosclerosis. The objectives of the study were to analyze the effect of microRNA-155 on autophagic signaling and explore its mechanism in human endothelial cells under ox-LDL stress. Methods: The study included human endothelial cells surrogate EA.hy926 lines (EA.hy926 cells). The expression of microRNA-155 was analyzed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The effect of microRNA-155 on endothelial autophagy was observed along with the expression levels of Rheb, LC3B, Beclin1, and P62/SQSTM1 by western blotting (WB) and immunofluorescence through microRNA-155 overexpression or inhibition. Bioinformatics analysis and Luciferase reporter assay were used to explore the target gene of microRNA-155. Cell viability and apoptosis were examined by 3-[4,5-dimethylthiazol-2-yl]-5- [3-carboxy-methoxyphenyl]-2-[4-sulfophenyl]-2H-tetrazolium inner salt (MTS) assay and TdT-mediated dUTP Nick-End Labeling (TUNEL) apoptosis assay. Results: MicroRNA-155 expression was significantly increased under ox-LDL stress. MicroRNA-155 increased autophagic activity, while inhibition of it alleviated ox-LDL-induced autophagy in EA.hy926 endothelial cells. In addition, dual-luciferase reporter assays showed that microRNA-155 suppressed Rheb transcription. MicroRNA-155 increased autophagic activity in EA.hy926 cells via inhibition of Rheb-mediated mTOR/P70S6kinase/4EBP signaling pathway. Furthermore, we demonstrated that microRNA-155 could regulate not only autophagy but also apoptosis in EA.hy926 cells. Conclusions: MicroRNA-155 works as a regulator of endothelial function under ox-LDL stress, making it a potential candidate for the novel therapeutic strategies against atherosclerotic diseases.

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Liu, Bin, Longyun Fang, Junjie Chen, Fule Liu, and Xiaolong Wang. "miRNA-dis: microRNA precursor identification based on distance structure status pairs." Molecular BioSystems 11, no. 4 (2015): 1194–204. http://dx.doi.org/10.1039/c5mb00050e.

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Li, Jian-Rong, Chun-Yip Tong, Tsai-Jung Sung, Ting-Yu Kang, Xianghong Jasmine Zhou, and Chun-Chi Liu. "CMEP: a database for circulating microRNA expression profiling." Bioinformatics 35, no. 17 (2019): 3127–32. http://dx.doi.org/10.1093/bioinformatics/btz042.

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Abstract Motivation In recent years, several experimental studies have revealed that the microRNAs (miRNAs) in serum, plasma, exosome and whole blood are dysregulated in various types of diseases, indicating that the circulating miRNAs may serve as potential noninvasive biomarkers for disease diagnosis and prognosis. However, no database has been constructed to integrate the large-scale circulating miRNA profiles, explore the functional pathways involved and predict the potential biomarkers using feature selection between the disease conditions. Although there have been several studies attempting to generate a circulating miRNA database, they have not yet integrated the large-scale circulating miRNA profiles or provided the biomarker-selection function using machine learning methods. Results To fill this gap, we constructed the Circulating MicroRNA Expression Profiling (CMEP) database for integrating, analyzing and visualizing the large-scale expression profiles of phenotype-specific circulating miRNAs. The CMEP database contains massive datasets that were manually curated from NCBI GEO and the exRNA Atlas, including 66 datasets, 228 subsets and 10 419 samples. The CMEP provides the differential expression circulating miRNAs analysis and the KEGG functional pathway enrichment analysis. Furthermore, to provide the function of noninvasive biomarker discovery, we implemented several feature-selection methods, including ridge regression, lasso regression, support vector machine and random forests. Finally, we implemented a user-friendly web interface to improve the user experience and to visualize the data and results of CMEP. Availability and implementation CMEP is accessible at http://syslab5.nchu.edu.tw/CMEP.

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Li, Wen, Ming Xi Jia, Jing Deng, et al. "MicroRNA Response and Toxicity of Potential Pathways in Human Colon Cancer Cells Exposed to Titanium Dioxide Nanoparticles." Cancers 12, no. 5 (2020): 1236. http://dx.doi.org/10.3390/cancers12051236.

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Titanium dioxide nanoparticles (TiO2-NPs) are widely used for biomedical and food applications, the toxicity of TiO2-NPs in vivo and in vitro has been elucidated, but the underlying cytotoxicity of TiO2-NPs against microRNA remains largely unknown. The purpose of this study was to analyze microRNA profiling induced by TiO2-NPs against NCM460 and HCT116 cell lines. Comparative analysis identified 34 and 24 microRNAs were significantly altered in the TiO2-NPs treated cells at concentrations of 3 μg/mL and 30 μg/mL, respectively. Functional classification demonstrated that a large proportion of genes involved in metabolism, human disease, and environmental information process were significantly upregulated by TiO2-NPs. Bioinformatics analysis suggested that microRNA 378 might be an early indicator of cellular response to exogenous stimuli with apoptotic signals. Furthermore, TiO2-NPs significantly altered the expression of microRNA 378b and 378g in HCT116 and NCM460 cell lines at different concentrations from 3 to 6 μg/mL. These concentrations elicit high-sensitivity of stimuli response in colon cancer cells when exposed to the slight doses of TiO2-NPs. Our study indicated that microRNAs 378b and 378g may play an important role in TiO2-NPs-mediated colonic cytotoxicity, which may provide a valuable insight into the molecular mechanisms of potential risks in colitis and colon cancer.

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Hildreth, Richard, Robert W. Georgantas, Roshan Patel, Sebastien Morisot, Jonathan Alder, and Curt I. Civin. "MicroRNA hsa-mir-16 Contributes to Regulation of Myeloid Differentiation of Human CD34+ Cells." Blood 108, no. 11 (2006): 1343. http://dx.doi.org/10.1182/blood.v108.11.1343.1343.

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Abstract In a large microRNA-array and bioinformatics study, we determined all of the microRNAs (miRs) expressed by human CD34+ hematopoietic stem-progenitor cells (HSPCs) from bone marrow and G-CSF mobilized blood. When we combined miR expression data, mRNA expression data fro a previous study (Georgantas et al, Cancer Research 64:4434), and data from various published mir-target prediction algorithms, we were able to bioinformaticly predict the actions of miRs within the hematopoietic system. MicroRNA hsa-mir-16 was highly expressed in CD34+ HSPCs, and was predicted to target several HSPC-expressed mRNAs (CXCR4, HoxB7, Runx-1, ETS-1, and Myb) that encode proteins known to be critically involved specifically in myelopoiesis within the hematopoietic system. We first confirmed that protein expression from each of these putative target mRNAs was in fact regulated by mir-16. The 3′UTR sequence from each of these mRNAs was cloned behind a luciferase reporter. Each reporter construct was transfected into K562 cells, which strongly express mir-16. In all cases, protein expression from the predicted target mRNA was greatly reduced in K562 cells, as compared to controls. As a first determination of mir-16’s function in hematopoietic cells, HL60 and K562 cells were transduced with hsa-mir-16 lentivirus, then treated with various chemical differentiation inducers. As was predicted by bioinformatics, hsa-mir-16 halted myeloid differentiation of HL60 cells, but did not affect megakaryocytic differentiation or erythroid differentiation of K562 cells. These initial findings suggest that mir-16 is a specific negative regulator of myelopoiesis. We are currently evaluating the effects of mir-16 on normal human CD34+ cells by in vitro CFC and suspension culture assays, as well as in vivo by transplantation of hsa-mir-16 lentivirus transduced cells in immunodeficient mice.

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Golan, David, Carmit Levy, Brad Friedman, and Noam Shomron. "Biased hosting of intronic microRNA genes." Bioinformatics 26, no. 8 (2010): 992–95. http://dx.doi.org/10.1093/bioinformatics/btq077.

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31

Bleazard, Thomas, Janine A. Lamb, and Sam Griffiths-Jones. "Bias in microRNA functional enrichment analysis." Bioinformatics 31, no. 10 (2015): 1592–98. http://dx.doi.org/10.1093/bioinformatics/btv023.

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Wang, Xiaowei. "Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies." Bioinformatics 32, no. 9 (2016): 1316–22. http://dx.doi.org/10.1093/bioinformatics/btw002.

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DeCicco, Danielle, Haisun Zhu, Anthony Brureau, James S. Schwaber, and Rajanikanth Vadigepalli. "MicroRNA network changes in the brain stem underlie the development of hypertension." Physiological Genomics 47, no. 9 (2015): 388–99. http://dx.doi.org/10.1152/physiolgenomics.00047.2015.

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Hypertension is a major chronic disease whose molecular mechanisms remain poorly understood. We compared neuroanatomical patterns of microRNAs in the brain stem of the spontaneous hypertensive rat (SHR) to the Wistar Kyoto rat (WKY, control). We quantified 419 well-annotated microRNAs in the nucleus of the solitary tract (NTS) and rostral ventrolateral medulla (RVLM), from SHR and WKY rats, during three main stages of hypertension development. Changes in microRNA expression were stage- and region-dependent, with a majority of SHR vs. WKY differential expression occurring at the hypertension onset stage in NTS versus at the prehypertension stage in RVLM. Our analysis identified 24 microRNAs showing time-dependent differential expression in SHR compared with WKY in at least one brain region. We predicted potential gene regulatory targets corresponding to catecholaminergic processes, neuroinflammation, and neuromodulation using the miRWALK and RNA22 databases, and we tested those bioinformatics predictions using high-throughput quantitative PCR to evaluate correlations of differential expression between the microRNAs and their predicted gene targets. We found a novel regulatory network motif consisting of microRNAs likely downregulating a negative regulator of prohypertensive processes such as angiotensin II signaling and leukotriene-based inflammation. Our results provide new evidence on the dynamics of microRNA expression in the development of hypertension and predictions of microRNA-mediated regulatory networks playing a region-dependent role in potentially altering brain-stem cardiovascular control circuit function leading to the development of hypertension.

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Mei, Fang, Junguo Wang, Zhijun Chen, and Zhilan Yuan. "Potentially Important MicroRNAs in Form-Deprivation Myopia Revealed by Bioinformatics Analysis of MicroRNA Profiling." Ophthalmic Research 57, no. 3 (2017): 186–93. http://dx.doi.org/10.1159/000452421.

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35

Li, Kun, Peng Wei, Yanwen Qin, and Yongxiang Wei. "MicroRNA expression profiling and bioinformatics analysis of dysregulated microRNAs in obstructive sleep apnea patients." Medicine 96, no. 34 (2017): e7917. http://dx.doi.org/10.1097/md.0000000000007917.

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Yan, Wenying, Shouli Wang, Zhandong Sun, et al. "Identification of MicroRNAs as Potential Biomarker for Gastric Cancer by System Biological Analysis." BioMed Research International 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/901428.

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Gastric cancers (GC) have the high morbidity and mortality rates worldwide and there is a need to identify sufficiently sensitive biomarkers for GC. MicroRNAs (miRNAs) could be promising potential biomarkers for GC diagnosis. We employed a systematic and integrative bioinformatics framework to identify GC-related microRNAs from the public microRNA and mRNA expression dataset generated by RNA-seq technology. The performance of the 17 candidate miRNAs was evaluated by hierarchal clustering, ROC analysis, and literature mining. Fourteen have been found to be associated with GC and three microRNAs (miR-211, let-7b, and miR-708) were for the first time reported to associate with GC and may be used for diagnostic biomarkers for GC.

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Chen, R., S. Patel, L. Bemis, W. Robinson, and H. Myint. "MicroRNA regulation in mantle cell lymphoma." Journal of Clinical Oncology 25, no. 18_suppl (2007): 8056. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.8056.

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8056 Mantle Cell Lymphoma (MCL) represents only 5–10% of all non-Hodgkins lymphomas, making it an uncommon but difficult form of lymphoma to treat. It has the worst prognosis among the B cell lymphomas with median survival of three years. The genetic hallmark of MCL is a t(11;14) q32 translocation which results in ectopic and dysregulated expression of cyclin D1. Recent comparative genomic hybridization studies have identied Syk as another gene important in the pathogenesis of MCL. Previous studies have suggested that post transcriptional regulation of Cyclin D1 and Syk may be important the pathogenesis of in MCL. MicroRNAs are a new class of abundant small RNAs that play important regulatory roles at the post transcriptional level by binding to the 3’ untranslated region (UTR) of mRNAs blocking either their translation or initiating their degradation. There have been numerous reports of misregulation of microRNAs and their targets in human cancers. We hypothesized that altered microRNA regulation of cyclin D1 and/or Syk may be present in MCL. Based on bioinformatics, we identified 8 microRNAs and their putative docking sites in either Cyclin D1 and Syk. We then examined their integrity in MCL cell lines, and identified a mutation in the 3’UTR of Syk at the docking site of 1 mir-452* and a SNP in mir-458. Using a GFP reporter construct with the mutated Syk 3’UTR we demonstrated that this mutation resulted in altered microRNA function. We also show that mimics of the microRNA leads to down regulation of Syk protein. This data suggests that microRNA regulation of important genes in MCL may be compromised and play a role in the development and progression of this disease. No significant financial relationships to disclose.

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Reczko, Martin, Manolis Maragkakis, Panagiotis Alexiou, Ivo Grosse, and Artemis G. Hatzigeorgiou. "Functional microRNA targets in protein coding sequences." Bioinformatics 28, no. 6 (2012): 771–76. http://dx.doi.org/10.1093/bioinformatics/bts043.

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Loher, Phillipe, and Isidore Rigoutsos. "Interactive exploration of RNA22 microRNA target predictions." Bioinformatics 28, no. 24 (2012): 3322–23. http://dx.doi.org/10.1093/bioinformatics/bts615.

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de Oliveira, Luiz Felipe Valter, Ana Paula Christoff, and Rogerio Margis. "isomiRID: a framework to identify microRNA isoforms." Bioinformatics 29, no. 20 (2013): 2521–23. http://dx.doi.org/10.1093/bioinformatics/btt424.

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Vergoulis, Thanasis, Ilias Kanellos, Nikos Kostoulas, et al. "mirPub: a database for searching microRNA publications." Bioinformatics 31, no. 9 (2014): 1502–4. http://dx.doi.org/10.1093/bioinformatics/btu819.

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Hua, Xu, Luxiao Chen, Jin Wang, Jie Li, and Edgar Wingender. "Identifying cell-specific microRNA transcriptional start sites." Bioinformatics 32, no. 16 (2016): 2403–10. http://dx.doi.org/10.1093/bioinformatics/btw171.

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Garcia-Garcia, Francisco, Joaquin Panadero, Joaquin Dopazo, and David Montaner. "Integrated gene set analysis for microRNA studies." Bioinformatics 32, no. 18 (2016): 2809–16. http://dx.doi.org/10.1093/bioinformatics/btw334.

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Gusev, Yuriy, and Daniel J. Brackett. "MicroRNA expression profiling in cancer from a bioinformatics prospective." Expert Review of Molecular Diagnostics 7, no. 6 (2007): 787–92. http://dx.doi.org/10.1586/14737159.7.6.787.

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Banwait, Jasjit K., and Dhundy R. Bastola. "Contribution of bioinformatics prediction in microRNA-based cancer therapeutics." Advanced Drug Delivery Reviews 81 (January 2015): 94–103. http://dx.doi.org/10.1016/j.addr.2014.10.030.

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46

Liu, Yiwen, Minglei Ma, Jie Yu, et al. "Decreased Serum microRNA-21, microRNA-25, microRNA-146a, and microRNA-181a in Autoimmune Diabetes: Potential Biomarkers for Diagnosis and Possible Involvement in Pathogenesis." International Journal of Endocrinology 2019 (September 9, 2019): 1–9. http://dx.doi.org/10.1155/2019/8406438.

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Objective. Previous studies have revealed dysregulated circulating microRNAs (miRNAs) in patients with type 1 diabetes (T1D). Here, we explored the serum levels of miR-21, miR-25, miR-146a, and miR-181a in patients with autoimmune diabetes (T1D and latent autoimmune diabetes of adults (LADA)) compared with type 2 diabetes (T2D) and nondiabetic individuals. Design, patients, and measurements. The serum levels of miR-21, miR-25, miR-146a, and miR-181a in patients with T1D (n = 29), LADA (n = 16), and T2D (n = 31) and in nondiabetic individuals (n = 19) were determined by quantitative real-time polymerase chain reaction, and receiver-operating characteristic (ROC) curves were evaluated to determine the discriminatory performances of these four miRNAs. Furthermore, target genes and pathways potentially modulated by these four miRNAs were predicted by bioinformatics analysis to investigate the possible functions of these miRNAs in autoimmune diabetes. Subsequently, multiple logistic regression analysis was performed to identify independent predictors for autoimmune diabetes, and a nomogram was established. Results. miR-21, miR-25, miR-146a, and miR-181a were significantly downregulated in the serum of patients with autoimmune diabetes compared with those in T2D patients and nondiabetic individuals (p<0.001). The areas under the ROC curves of these four miRNAs were greater than 0.80 (p<0.001). Bioinformatics analysis suggested that miR-21, miR-25, miR-146a, and miR-181a regulated multiple genes in pathways associated with immunity, inflammatory responses, hyperglycemia, and metabolism, which are involved in the pathogenesis of autoimmune diabetes. Multiple logistic regression analysis identified miR-25 (odds ratio (OR): 0.001, p<0.05), miR-146a (OR: 0.136, p<0.05), and fasting C-peptide levels (OR: 0.064, p<0.05) as independent predictors of autoimmune diabetes. Conclusions. miR-25 and miR-146a may serve as potential circulating biomarkers and provide insights into the pathogenesis of autoimmune diabetes.

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Zhou, Lei, Wentao Zhu, Guanxi Wang, Xuefeng Cao, Xingyuan Zhang, and Qiangpu Chen. "Investigation of microRNA expression signatures in HCC via microRNA Gene Chip and bioinformatics analysis." Pathology - Research and Practice 216, no. 6 (2020): 152982. http://dx.doi.org/10.1016/j.prp.2020.152982.

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48

Edwardson, Matthew A., Xiaogang Zhong, Amrita Cheema, and Alexander Dromerick. "2016 Plasma microRNA markers of upper limb recovery following human stroke." Journal of Clinical and Translational Science 2, S1 (2018): 45. http://dx.doi.org/10.1017/cts.2018.176.

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OBJECTIVES/SPECIFIC AIMS: MicroRNAs are small, non-coding RNAs that control gene expression by inhibiting protein translation. Preclinical studies in rodent stroke models suggest that changes in microRNA expression contribute to neural repair mechanisms. To our knowledge, no one has previously assessed microRNA changes during the recovery phase of human stroke. Our goal was to determine whether patients with significant upper limb recovery following stroke have alteration of neural repair-related microRNA expression when compared to those with poor recovery. METHODS/STUDY POPULATION: Plasma was collected at 19 days post-stroke from 27 participants with mild-moderate upper extremity impairment enrolled in the Critical Periods After Stroke Study. MicroRNA expression was assessed using TaqMan microRNA assays (Thermo Fisher Scientific). Good recovery was defined as ≥6 point change in the Action Research Arm Test (ARAT) score from baseline to 6 months. Bioinformatics analysis compared the plasma microRNA expression profiles of participants with good Versus poor recovery. Candidate biomarkers were identified after correcting for multiple comparisons using a false discovery rate <0.05. RESULTS/ANTICIPATED RESULTS: Eleven microRNAs had significantly altered expression in the good (n=22) Versus poor (n=5) recovery groups, with 2 showing increased expression—miR-371-3p and miR-520g, and 9 showing decreased expression—miR-449b, miR-519b, miR-581, miR-616, miR-892b, miR-941, miR-1179, miR-1292, and miR1296. Three of these could be implicated in neural repair mechanisms. Elevated miR-371-3p levels increase the likelihood that pluripotent stem cells will differentiate into neural progenitors. MiR-892b decreases levels of amyloid precursor protein, which has been implicated as a regulator of synapse formation. Finally miR-941, the only known human-specific microRNA, downregulates the CSPα protein which is involved in neurotransmitter release. DISCUSSION/SIGNIFICANCE OF IMPACT: This preliminary study suggests that circulating microRNAs in the plasma may help serve as biomarkers of neural repair and aid in understanding human neural repair mechanisms. If validated in larger studies with appropriate controls, these markers could aid in timing rehabilitation therapy or designing recovery-based therapeutics.

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Ritchie, William, Stephane Flamant, and John E. J. Rasko. "mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets." Bioinformatics 26, no. 2 (2009): 223–27. http://dx.doi.org/10.1093/bioinformatics/btp649.

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50

Yang, Xiang, Kai-Xun Feng, Hu Li, Li Wang, and Hong Xia. "MicroRNA-199a Inhibits Cell Proliferation, Migration, and Invasion and Activates AKT/mTOR Signaling Pathway by Targeting B7-H3 in Cervical Cancer." Technology in Cancer Research & Treatment 19 (January 1, 2020): 153303382094224. http://dx.doi.org/10.1177/1533033820942245.

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Cervical cancer is a deadly disease. Some microRNAs are involved in tumor invasion and metastasis. Decreased expression of microRNA-199a has been correlated with tumorigenesis. In our study, the quantitative real-time polymerase chain reaction results indicated that microRNA-199a was expressed at lower levels in cervical cancer tissues, and the expression level of B7-H3 was significantly increased compared with that in the adjacent normal tissues, and the expression levels of B7-H3 and microRNA-199a in cervical cancer tissues and in adjacent normal tissues were inversely correlated. We also found that the expression of microRNA-199a was downregulated in cervical cancer cell lines when compared to immortalized cells. In this study, B7-H3 was identified as a novel target of microRNA-199a in cervical cancer. TargetScan ( http://www.targetscan.org/ ) bioinformatics analysis was used to predict that the 3′-untranslated region of B7-H3 is a direct target of microRNA-199a. The result was also verified by the luciferase reporter assay. MicroRNA-199a could directly target the 3′-untranslated region of B7-H3, but the specific signaling pathways that were involved in regulating B7-H3 expression remained unclear. To clarify whether the suppressive effect of microRNA-199a was mediated through B7-H3, a series of experiments were performed. We found that the overexpression of microRNA-199a inhibited cell proliferation, migration, and invasion via direct binding to B7-H3. Epithelial–mesenchymal transition is a major factor involved in cervical cancer metastasis. Quantitative real-time polymerase chain reaction and western blot results indicated that microRNA-199a inhibits tumor progression in cervical cancer by targeting B7-H3. The microRNAs regulatory network is quite complex. We further examined the effect of microRNA-199a on the AKT/mTOR signaling pathway. We explored the regulatory role of microRNA-199a and first demonstrated that highly expressed microRNA-199a inhibits tumor growth and activates the AKT/mTOR signaling pathway by targeting B7-H3 in vivo and in vitro. Our findings not only provide a better understanding of the pathogenesis of cervical cancer but also provide novel findings and theoretical support for potential targeted therapeutic tools for cervical cancer.

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