scholarly journals Comprehensive analysis of micro RNAs in recurrent implantation failures patients and construction of prediction models based on circulating micro RNAs

2021 ◽  
Author(s):  
Peigen Chen ◽  
Yingchun Guo ◽  
Tingting Li ◽  
Lei Jia ◽  
Yanfang Wang ◽  
...  
Keyword(s):  
Target Genes ◽  
Prediction Models ◽  
Reproductive Technology ◽  
Control Group ◽  
Circulating Mirnas ◽  
Competing Endogenous Rna ◽  
Micro Rnas ◽  
Non Coding Rnas ◽  
Analytical Tools ◽  
The Relationship

Abstract BackgroundRecurrent implantation failure (RIF) is an obstacle in the process of assisted reproductive technology (ART). At present, there was limited research on its pathogenesis, diagnosis and treatment methods.ResultsIn this study, a series of analytical tools were used to analyze differences in miRNAs, mRNAs and lncRNAs in the endometrium of patients in the RIF group and the control group. At the same time, multiple databases are used to predict the target genes of non-coding RNAs. Then the competing endogenous RNA (ceRNA) network was built to describe the relationship between gene regulation in the endometrium of the RIF.ConcludesBased on the results of the logistic regression of co-expression miRNAs between serum and endometrial samples, we built a predictive model based on circulating miRNAs.

scholarly journals Construction of Circulating MicroRNAs-Based Non-invasive Prediction Models of Recurrent Implantation Failure by Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Peigen Chen ◽  
Tingting Li ◽  
Yingchun Guo ◽  
Lei Jia ◽  
Yanfang Wang ◽  
...  
Keyword(s):  
Prediction Models ◽  
Control Group ◽  
Implantation Failure ◽  
Competing Endogenous Rna ◽  
Recurrent Implantation Failure ◽  
Circulating Micrornas ◽  
Non Invasive ◽  
The Stability ◽  
Analytical Tools ◽  
The Relationship

BackgroundRecurrent implantation failure (RIF) is an obstacle in the process of assisted reproductive technology (ART). At present, there is limited research on its pathogenesis, diagnosis, and treatment methods.Methods and ResultsIn this study, a series of analytical tools were used to analyze differences in miRNAs, mRNAs, and lncRNAs in the endometrium of patients in a RIF group and a control group. Then the competing endogenous RNA (ceRNA) network was built to describe the relationship between gene regulation in the endometrium of the RIF group. Based on the results of the logistic regression of co-expression miRNAs between serum and endometrial samples, we built a predictive model based on circulating miRNAs.ConclusionThe stability and non-invasiveness of the circular miRNA prediction model provided a new method for diagnosis in RIF patients.

scholarly journals Aberrant Expression of Long Non-Coding RNAs in Newly Diagnosed Type 2 Diabetes Indicates Potential Roles in Chronic Inflammation and Insulin Resistance

2017 ◽  
Vol 43 (6) ◽  
pp. 2367-2378 ◽  
Author(s):  
Xiaoli Wang ◽  
Xiangyun Chang ◽  
Peipei Zhang ◽  
Ling Fan ◽  
Ting Zhou ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Target Genes ◽  
Chinese Patients ◽  
Control Group ◽  
Newly Diagnosed ◽  
Aberrant Expression ◽  
Healthy Control ◽  
Non Coding Rnas

Background/Aims: Long non-coding RNAs (lncRNAs) have emerged as key players in several biological processes and complex diseases. The risk of type 2 diabetes (T2D) is determined by a combination of environmental factors and genetic susceptibility. The purpose of this study was to identify aberrant lncRNAs involved in T2D pathogenesis. Methods: Microarray analysis was performed using whole blood samples from patients newly diagnosed with T2D and healthy controls. Pathway and Gene Ontology (GO) analyses were utilized to annotate the target genes. Coding non-coding co-expression (CNC) analysis was performed to construct a co-expression network. Results: We found 55 lncRNAs and 202 mRNAs were differentially expressed in the T2D group compared to the healthy control group. Pathway and GO analyses demonstrated that dysregulated mRNAs were mainly associated with immune regulation, inflammation, and insulin resistance, whereas CNC analysis identified 10 pairs of co-expressed lncRNA-mRNAs in our patient cohort (R > 0.99). Furthermore, expression of the top three upregulated lncRNAs in the T2D group was correlated with measures of glycometabolism (P < 0.05). Conclusion: This study identified aberrantly expressed lncRNAs and mRNAs in Han Chinese patients with T2D, and demonstrated that dysregulated lncRNAs may have roles in T2D pathogenesis through regulation of inflammation and insulin resistance.

Abstract 403: Identification of CHROME as a Competing Endogenous RNA that Regulates Cholesterol Homeostasis

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
Coen van Solingen ◽  
Elizabeth J Hennessy ◽  
Mireille Ouimet ◽  
Kaitlyn Rinehold ◽  
Maryem Hussein ◽  
...  
Keyword(s):  
Cholesterol Efflux ◽  
Target Genes ◽  
Hdl Cholesterol ◽  
Cholesterol Homeostasis ◽  
Competing Endogenous Rna ◽  
Cellular Cholesterol ◽  
Expression Of Genes ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
X Receptors

The discovery of microRNAs (miRNA) targeting gene pathways involved in HDL and LDL metabolism illuminated the potent role of non-coding RNAs in the regulation of cholesterol homeostasis. Long non-coding RNAs (lncRNA) have also been identified as crucial regulators of gene expression; however, few have been fully characterized. Here we report a novel human lncRNA, CHROME (Cholesterol Homeostasis Regulator Of MicroRNA Expression), that functions as a competing endogenous RNA to regulate cellular cholesterol homeostasis. We show that CHROME has 7 broadly expressed variants that are transcriptionally regulated by the cholesterol-sensing liver X receptors. Computational analyses revealed that CHROME harbors binding sites for multiple (11) miRNAs involved in cholesterol homeostasis, including miR-27b and miR-33a/b, which function as hubs controlling the expression of genes involved in cholesterol efflux and HDL metabolism. Using CHROME knock-down and overexpression, we demonstrate that CHROME acts as a ‘miRNA sponge’ that sequesters these miRNAs, limiting their ability to repress target genes, including ABCA1, OSBPL6 and ANGPTL3. Consistent with this, we show that overexpression of CHROME increases cholesterol efflux, whereas its silencing reduces cholesterol efflux from primary human hepatocytes and macrophages. As hepatic cholesterol efflux via ABCA1 plays a central role in HDL biogenesis, we investigated the relationship of CHROME to its miRNA targets and plasma levels of HDL cholesterol in liver samples from a cohort of 200 healthy individuals. This analysis showed that CHROME is inversely correlated with miR-27b and miR-33a/b levels, and positively correlated with levels of their target genes and plasma HDL cholesterol. Collectively, these findings identify CHROME as a key regulatory component of the non-coding RNA circuitry that controls cellular cholesterol efflux and plasma HDL levels in humans.

scholarly journals Computational Model for Predicting the Relationship Between Micro-RNAs and Their Target Messenger RNAs in Breast and Colon Cancers

2018 ◽  
Vol 17 ◽  
pp. 117693511878514
Author(s):  
Shinuk Kim
Keyword(s):  
Breast Cancer ◽  
Colon Cancer ◽  
Target Gene ◽  
Target Genes ◽  
Computational Method ◽  
Numerical Code ◽  
Messenger Rnas ◽  
Unknown Parameters ◽  
Micro Rnas ◽  
The Relationship

Motivation: Uncovering the relationship between micro-RNAs (miRNAs) and their target messenger RNAs (mRNAs) can provide critical information regarding the mechanisms underlying certain types of cancers. In this context, we have proposed a computational method, referred to as prediction analysis by optimization method (PAOM), to predict miRNA-mRNA relations using data from normal and cancer tissues, and then applying the relevant algorithms to colon and breast cancers. Specifically, we used 26 miRNAs and 26 mRNAs with 676 (= 26 × 26) relationships to be recovered as unknown parameters. Results: Optimization methods were used to detect 61 relationships in breast cancer and 32 relationships in colon cancer. Using sequence filtering, we detected 18 relationships in breast cancer and 15 relationships in colon cancer. Among the 18 relationships, CD24 is the target gene of let-7a and miR-98, and E2F1 is the target gene of miR-20. In addition, the frequencies of the target genes of miR-223, miR-23a, and miR-20 were significant in breast cancer, and the frequencies of the target genes of miR-17, miR-124, and miR-30a were found to be significant in colon cancer. Availability: The numerical code is available from the authors on request.

scholarly journals Coordinative control of G2/M phase of the cell cycle by non-coding RNAs in hepatocellular carcinoma

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5787 ◽  
Author(s):  
Jun Shi ◽  
Guangqiang Ye ◽  
Guoliang Zhao ◽  
Xuedong Wang ◽  
Chunhui Ye ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Target Genes ◽  
Expression Profiles ◽  
M Phase ◽  
Non Coding Rnas ◽  
Regulatory Model ◽  
Microarray Analyses ◽  
The Relationship

Objective To investigate the interaction of non-coding RNAs (ncRNAs) in hepatocellular carcinoma. Methods We compared the ncRNAs and mRNAs expression profiles of hepatocellular carcinoma and adjacent tissue by microarray and RT-PCR. The relationship between different ncRNAs and mRNA was analyzed using bioinformatics tools. A regulatory model of ncRNAs in hepatocellular carcinoma cells was developed. Results A total of 1,704 differentially expressed lncRNAs, 57 miRNAs, and 2,093 mRNAs were identified by microarray analyses. There is a co-expression relationship between two ncRNAs (miRNA-125b-2-3p and lncRNA P26302). Bioinformatics analysis demonstrated cyclin-dependent kinases 1 and CyclinA2 as potential targets of miR-125b-2-3p and Polo-like kinase 1 as potential target of lncRNAP26302. All three gene are important components in the G2/M phase of cell cycle. Subsequently real-time polymerase chain reaction (PCR) studies confirmed these microarray results. Conclusion MiR-125b-2-3p and lncRNAP26302 may affect the G2/M phase of the cell cycle through the regulation of their respective target genes. This study shows a role of ncRNAs in pathogenesis of hepatocellular carcinoma at molecular level, providing a basis for the future investigation aiming at early diagnosis and novel treatment of hepatocellular carcinoma.

scholarly journals The role of micro-RNA in the regulation of signal pathways in gliomas

2017 ◽  
Vol 63 (6) ◽  
pp. 481-498
Author(s):  
O.I. Kit ◽  
D.I. Vodolazhsky ◽  
E.E. Rostorguev ◽  
D.H. Porksheyan ◽  
S.B. Panina
Keyword(s):  
Target Genes ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Micro Rna ◽  
Present Review ◽  
Signal Pathways ◽  
Aberrant Expression ◽  
Micro Rnas ◽  
Non Coding Rnas

Gliomas are invasive brain tumors with high rates of recurrence and mortality. Glioblastoma multiforme (GBM) is the most deadly form of glioma with nearly 100% rate of recurrence and unfavorable prognosis in patients. Micro-RNAs (miR) are the class of wide-spread short non-coding RNAs that inhibit translation via binding to the mRNA of target genes. The aim of the present review is to analyze recent studies and experimental results concerning aberrant expression profiles of miR, which target components of the signaling pathways Hedgehog, Notch, Wnt, EGFR, TGFb, HIF1a in glioma/glioblastoma. Particularly, the interactions of miR with targets of 2-hydroxyglutarate (the product of mutant isocytrate dehydrogenase, R132H IDH1, which is specific for the glioma pathogenesis) have been considered in the present review. Detecting specific miRNAs in tissue and serum may serve as a diagnostic and prognostic tool for glioma, as well as for predicting treatment response of an individual patient, and potentially serving as a mechanism for creating personalized treatment strategies

scholarly journals miR-152 inhibits the proliferation and invasion of chordoma cells by targeting HOXC8

2019 ◽  
Vol 47 (10) ◽  
pp. 5185-5193
Author(s):  
Xinyun Fang ◽  
Renchun Yan
Keyword(s):  
Target Genes ◽  
Luciferase Reporter ◽  
Cell Behavior ◽  
Downstream Effectors ◽  
Normal Human ◽  
Direct Target ◽  
Non Coding Rnas ◽  
The Relationship ◽  
Proliferation And Invasion

Objective MicroRNAs (miRNAs) are non-coding RNAs that affect the expression of their target genes by binding to the 3′-untranslated region. miR-152 has been identified as a critical modulator in tumorigenesis, but its role in chordoma has not been explored. We therefore investigated the role of miR-152 in regulating chordoma cell behavior, and examined the downstream effectors of miR-152. Materials and methods We examined the expression of miR-152 in two human chordoma cell lines and in a normal human embryonic kidney cell line. We also analyzed the relationship between miR-152 and homeobox C8 ( HOXC8) by bioinformatics analysis and luciferase reporter assay. We determined the effects of miR-152 and HOXC8 expression on chordoma cell behavior. Results miR-152 expression was downregulated in chordoma compared with normal cells. Meanwhile, miR-152 overexpression inhibited chordoma cell proliferation and invasion. The oncogene HOXC8 was a direct target of miR-152, as shown by luciferase reporter and western blot assays. Conclusions HOXC8 acted as an effector for the suppressive role of miR-152 in chordoma, thereby providing a potential therapeutic target in patients with chordoma.

The role of non-coding RNAs

2019 ◽  
pp. 69-79
Author(s):  
John C. Lucchesi
Keyword(s):  
Target Genes ◽  
Centromeric Heterochromatin ◽  
Small Interfering Rnas ◽  
Protein Coding ◽  
Heterochromatin Formation ◽  
Short Rnas ◽  
Micro Rnas ◽  
Rrna Maturation ◽  
Non Coding Rnas

Most of the genome is transcribed into non-coding transcripts that far exceed in number the transcripts of protein-coding genes. These RNAs are subdivided into different classes. Long non-coding RNAs (lncRNAs) are at least 200 nucleotides in length and are transcribed from promoter, coding, intergenic or enhancer regions (eRNAs). These RNAs repress or enhance the transcription of target genes by facilitating the interaction between promoters and enhancers or by interacting with transcription factors and targeting histone-modifying enzymes. Short non-coding RNAs include a diverse group of functional types: miRNAs (micro RNAs) and siRNAs (small interfering RNAs) are negative regulators of gene expression; piRNAs (Piwi-interacting RNAs) suppress the action of transposable elements in the germline; snRNAs (small nuclear RNAs) are involved in mRNA splicing and rRNA maturation; tRNA-derived non-coding RNAs are involved in the cellular reaction to stress and in the repression of gene function. Additional short RNAs are rasiRNAs (repeat-associated small interfering RNAs) that appear to be involved in centromeric heterochromatin formation.

scholarly journals tRFTar: predicting the targets of tRNA-derived fragments

2020 ◽  
Author(s):  
Qiong Xiao ◽  
Peng Gao ◽  
Xuanzhang Huang ◽  
Xiaowan Chen ◽  
Quan Chen ◽  
...  
Keyword(s):  
Target Genes ◽  
Prediction Models ◽  
Support Vector ◽  
Folding Energy ◽  
Sequence Context ◽  
Inhibit Gene Expression ◽  
Non Coding Rnas ◽  
User Friendly ◽  
Regulatory Functions ◽  
Free Folding Energy

Abstract Background: tRNA-derived fragments (tRFs) are 14–40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes. Methods: We used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models. Results: We first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977-0.983) in the training process and an AUC = 0.847 (0.83-0.861) in the test process. The model was applied to all the sites with perfect Watson-Crick complementarity to the seed in the 3' untranslated region (3'-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. Conclusions: Predictions can be obtained online, tRFTar, freely available at http://trftar.cmuzhenninglab.org:3838/tar/, which is the first tool to predict targets of tRFs in humans with a user-friendly interface.

scholarly journals Non-randomness distribution of micro-RNAs on human chromosomes

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Fariba Boroumand ◽  
Iraj Saadat ◽  
Mostafa Saadat
Keyword(s):  
Human Genome ◽  
Target Genes ◽  
Current Data ◽  
Micro Rna ◽  
Human Chromosomes ◽  
Human Genomes ◽  
Micro Rnas ◽  
Non Coding Rnas ◽  
Chromosomal Bands ◽  
Chromosome Bands

Abstract Background Micro-RNA (miRNA) is one of the non-coding RNAs that exist in human genome. miRNAs play an important role in the expression of target genes. Several studies have indicated that organization of human genome is not random. In order to investigate the distribution of miRNAs on human chromosomes, the present study was carried out. Results Using the data from miRBase database, we found 1913 loci coding for miRNAs (MIRs). Human chromosome bands 1p36, 1q22, 1q24, 2q13, 2q35, 3p21, 6p21, 7q22, 8p23, 8q24, 9q22, 9q34, 11q12-q13, 12q13, 14q32, 16p13, 16q24, 17p13, 17q11, 17q21, 17q25, 19p13, 19q13, 20q13, 21p11, 22q13, and Xq26-q28 were significantly bearing higher number of MIRs. The 14q32 and 19q13 with 4.11 and 3.59 MIRs per mega-base pair, respectively, were the most MIR-richest human chromosomal bands. The number of MIRs on chromosomal bands significantly decreased as a function of distance from telomere (r = − 0.949, df = 5, P = 0.001). Conclusions Our current data suggest that MIRs are not randomly distributed on human genomes.

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