Construction of siRNA/miRNA expression vectors based on a one-step PCR process

Background  

RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems.     

New miRNA labeling method for bead-based quantification

Background  

microRNAs (miRNAs) are small single-stranded non-coding RNAs that act as crucial regulators of gene expression. Different methods have been developed for miRNA expression profiling in order to better understand gene regulation in normal and pathological conditions. miRNAs expression values obtained from large scale methodologies such as microarrays still need a validation step with alternative technologies.     

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

Background

MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.

Results

We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.

Conclusions

Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-255) contains supplementary material, which is available to authorized users.     

HIV-1 TAR element is processed by Dicer to yield a viral micro-RNA involved in chromatin remodeling of the viral LTR

Background  

RNA interference (RNAi) is a regulatory mechanism conserved in higher eukaryotes. The RNAi pathway generates small interfering RNA (siRNA) or micro RNA (miRNA) from either long double stranded stretches of RNA or RNA hairpins, respectively. The siRNA or miRNA then guides an effector complex to a homologous sequence of mRNA and regulates suppression of gene expression through one of several mechanisms. The suppression of gene expression through these mechanisms serves to regulate endogenous gene expression and protect the cell from foreign nucleic acids. There is growing evidence that many viruses have developed in the context of RNAi and express either a suppressor of RNAi or their own viral miRNA.     

Deep sequencing on genome-wide scale reveals the unique composition and expression patterns of microRNAs in developing pollen of <Emphasis Type="Italic">Oryza sativa</Emphasis>

Background  

Pollen development in flowering plants requires strict control of the gene expression program and genetic information stability by mechanisms possibly including the miRNA pathway. However, our understanding of the miRNA pathway in pollen development remains limited, and the dynamic profile of miRNAs in developing pollen is unknown.     

Identifying miRNA sponge modules using biclustering and regulatory scores

Background

MicroRNA (miRNA) sponges with multiple tandem miRNA binding sequences can sequester miRNAs from their endogenous target mRNAs. Therefore, miRNA sponge acting as a decoy is extremely important for long-term loss-of-function studies both in vivo and in silico. Recently, a growing number of in silico methods have been used as an effective technique to generate hypotheses for in vivo methods for studying the biological functions and regulatory mechanisms of miRNA sponges. However, most existing in silico methods only focus on studying miRNA sponge interactions or networks in cancer, the module-level properties of miRNA sponges in cancer is still largely unknown.

Results

We propose a novel in silico method, called miRSM (miRNA Sponge Module) to infer miRNA sponge modules in breast cancer. We apply miRSM to the breast invasive carcinoma (BRCA) dataset provided by The Cancer Genome Altas (TCGA), and make functional validation of the computational results. We discover that most miRNA sponge interactions are module-conserved across two modules, and a minority of miRNA sponge interactions are module-specific, existing only in a single module. Through functional annotation and differential expression analysis, we also find that the modules discovered using miRSM are functional miRNA sponge modules associated with BRCA. Moreover, the module-specific miRNA sponge interactions among miRNA sponge modules may be involved in the progression and development of BRCA. Our experimental results show that miRSM is comparable to the benchmark methods in recovering experimentally confirmed miRNA sponge interactions, and miRSM outperforms the benchmark methods in identifying interactions that are related to breast cancer.

Conclusions

Altogether, the functional validation results demonstrate that miRSM is a promising method to identify miRNA sponge modules and interactions, and may provide new insights for understanding the roles of miRNA sponges in cancer progression and development.

     

Prediction and preliminary validation of oncogene regulation by miRNAs

Background  

MicroRNAs (miRNAs) are one of the most abundant groups of regulatory genes in multicellular organisms, playing important roles in many fundamental cellular processes. More than four hundred miRNAs have been identified in humans and the deregulation of miRNA expression has been also shown in many cancers. Despite the postulated involvement of miRNAs in tumourigenesis, there are only a few examples where an oncogene or a tumour suppressor has been identified as a miRNA target.     

A scoring matrix approach to detecting miRNA target sites

Background  

Experimental identification of microRNA (miRNA) targets is a difficult and time consuming process. As a consequence several computational prediction methods have been devised in order to predict targets for follow up experimental validation. Current computational target prediction methods use only the miRNA sequence as input. With an increasing number of experimentally validated targets becoming available, utilising this additional information in the search for further targets may help to improve the specificity of computational methods for target site prediction.     

Real-Time Monitoring of miRNA Function in Pancreatic Cell Lines Using Recombinant AAV-Based miRNA Asensors

Background

MicroRNAs (miRNAs) are reportedly involved in pancreatic ductal adenocarcinoma (PDAC) development. Current methods do not allow us to reliably monitor miRNA function. Asensors are adeno-associated virus (AAV) vector miRNA sensors for real-time consecutive functional monitoring of miRNA profiling in living cells.

Methods

miR-200a, -200b, -21, -96, -146a, -10a, -155, and -221 in three PDAC cell lines (BxPC-3, CFPAC-1, SW1990), pancreatic epithelioid carcinoma cells (PANC-1), and human pancreatic nestin-expressing cells (hTERT-HPNE) were monitored by Asensors. Subsequently, the real-time consecutive functional profile of all miRNAs was evaluated.

Results

Selected miRNAs were detectable in all cell lines with high sensitivity and reproducibility. In the three PDAC cell lines, BxPC-3, CFPAC-1, and SW1990, the calibrated signal unit of the eight miRNAs Asensors was significantly lower than that of the Asensor control. However, in PANC-1 cells, miR-200a and -155 showed upregulation of target gene expression at 24 hours after infection with the sensors; at 48 hours, miR-200b and -155 displayed upregulation of reporter expression; and at 72 hours, reporter gene expression was upregulated by miR-200a and -200b. The result that miRNA could upregulate gene expression was further confirmed in miR-155 of hTERT-HPNE cells. Furthermore, miRNA activity varied among cell/tissue types and time.

Conclusion

It is possible that miRNA participates in the pathophysiology of pancreatic cancer, but the current popular methods do not accurately reveal the real-time miRNA function. Thus, this report provided a convenient, accurate, and sensitive approach to miRNA research.     

miRAS: a data processing system for miRNA expression profiling study

Background  

The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.     

Mirna expression profiles identify drivers in colorectal and pancreatic cancers

Background and Aim

Altered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways.

Methods

Expression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed.

Results

The merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers.

Conclusion

MiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.