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Argonaute (AGO)

The Argonaute protein family plays a central role in RNA silencing processes, as essential catalytic components of the RNA-induced silencing complex (RISC). RISC is responsible for the gene silencing phenomenon known as RNA interference (RNAi). Argonaute proteins bind different classes of small non-coding RNAs, including microRNAs (miRNAs), small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs). Small RNAs guide Argonaute proteins to their specific targets through sequence complementarity (base pairing), which then leads to mRNA cleavage or translation inhibition. [Source: Wikipedia]

Antar

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Microarray expression analyses following miRNA transfection/inhibition and, more recently, Argonaute cross-linked immunoprecipitation (CLIP)-seq assays have been used to detect miRNA target sites. CLIP and expression approaches measure differing stages of miRNA functioning-initial binding of the miRNP complex and subsequent message repression. We use nonparametric predictive models to characterize a large number of known target and flanking features, utilizing miRNA transfection, HITS-CLIP, and PAR-CLIP data.

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MicroMUMMIE

Submitted by ChenLiang on Sun, 09/10/2017 - 20:22

High-throughput sequencing has opened numerous possibilities for the identification of regulatory RNA-binding events. Cross-linking and immunoprecipitation of Argonaute proteins can pinpoint a microRNA (miRNA) target site within tens of bases but leaves the identity of the miRNA unresolved. A flexible computational framework, microMUMMIE, integrates sequence with cross-linking features and reliably identifies the miRNA family involved in each binding event.

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PARalyzer

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Crosslinking and immunoprecipitation (CLIP) protocols have made it possible to identify transcriptome-wide RNA-protein interaction sites. In particular, PAR-CLIP utilizes a photoactivatable nucleoside for more efficient crosslinking. We present an approach, centered on the novel PARalyzer tool, for mapping high-confidence sites from PAR-CLIP deep-sequencing data. We show that PARalyzer delineates sites with a high signal-to-noise ratio.

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CleaveLand

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs (miRNAs) are approximately 20- to 22-nt long endogenous RNA sequences that play a critical role in the regulation of gene expression in eukaryotic genomes. Confident identification of miRNA targets is vital to understand their functions. Currently available computational algorithms for miRNA target prediction have diverse degrees of sensitivity and specificity and as a consequence each predicted target generally requires experimental confirmation.

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Lasso_miR

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Construction of miRNA-target regulatory networks can provide useful information for the study and diagnosis of complex diseases. Many sequence-based and evolutionary information-based methods have been developed to identify miRNA-mRNA targeting relationships.

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Average: 5 (1 vote)

miRandola

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs are small noncoding RNAs that play an important role in the regulation of various biological processes through their interaction with cellular messenger RNAs. They are frequently dysregulated in cancer and have shown great potential as tissue-based markers for cancer classification and prognostication. microRNAs are also present in extracellular human body fluids such as serum, plasma, saliva, and urine. Most of circulating microRNAs are present in human plasma and serum cofractionate with the Argonaute2 (Ago2) protein.

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Average: 5 (2 votes)

MiClip

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip) to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets.

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Average: 5 (1 vote)

PARma

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

PARma is a complete data analysis software for AGO-PAR-CLIP experiments to identify target sites of microRNAs as well as the microRNA binding to these sites. It integrates specific characteristics of the experiments into a generative model. The model and a novel pattern discovery tool are iteratively applied to data to estimate seed activity probabilities, cluster confidence scores and to assign the most probable microRNA. Based on differential PAR-CLIP analysis and comparison to RIP-Chip data, we show that PARma is more accurate than existing approaches.

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Average: 5 (1 vote)

CLIPSeqTools

Submitted by ChenLiang on Thu, 04/06/2017 - 17:39

Immunoprecipitation of RNA binding proteins (RBPs) after in vivo crosslinking, coupled with sequencing of associated RNA footprints (HITS-CLIP, CLIP-seq), is a method of choice for the identification of RNA targets and binding sites for RBPs. Compared with RNA-seq, CLIP-seq analysis is widely diverse and depending on the RBPs that are analyzed, the approaches vary significantly, necessitating the development of flexible and efficient informatics tools.

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Average: 5 (1 vote)

mythology

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Post ENCODE, regulatory sRNAs (rsRNAs) like miRNAs have established their status as one of the core regulatory elements of cell systems. However, large number of rsRNAs are compromised due to traditional approaches to identify miRNAs, limiting the otherwise vast world of rsRNAs mainly to hair-pin loop bred typical miRNAs. The present study has analyzed for the first time a huge volume of sequencing data from 4997 individuals and 25 cancer types to report 11 234 potentially regulatory small RNAs which appear to have deep reaching impact.

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