Variation in gene expression has been observed in natural populations and associated with complex traits or phenotypes such as disease susceptibility and drug response. Gene expression itself is controlled by various genetic and non-genetic factors. The binding of a class of small RNA molecules, microRNAs (miRNAs), to mRNA transcript targets has recently been demonstrated to be an important mechanism of gene regulation.
The economic importance of Solanaceae plant species is well documented and tomato has become a model for functional genomics studies. In plants, important processes are regulated by microRNAs (miRNA).
A useful step for understanding the function of microRNAs (miRNA) or siRNAs is the detection of their effects on genome-wide expression profiles. Typically, approaches look for enrichment of words in the 3(')UTR sequences of the most deregulated genes. A number of tools are available for this purpose, but they require either in-depth computational knowledge, filtered 3(')UTR sequences for the genome of interest, or a set of genes acquired through an arbitrary expression cutoff.
Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited.
MicroRNAs are small non-coding RNA transcripts that regulate post-transcriptional gene expression. The millions of short sequence reads generated by next generation sequencing technologies make this technique explicitly suitable for profiling of known and novel microRNAs. A modification to the small-RNA expression kit (SREK, Ambion) library preparation method for the SOLiD sequencing platform is described to generate microRNA sequencing libraries that are compatible with the Illumina Genome Analyzer.
Xenbase (http://www.xenbase.org), the Xenopus frog model organism database, integrates a wide variety of data from this biomedical model genus. Two closely related species are represented: the allotetraploid Xenopus laevis that is widely used for microinjection and tissue explant-based protocols, and the diploid Xenopus tropicalis which is used for genetics and gene targeting. The two species are extremely similar and protocols, reagents and results from each species are often interchangeable.
Identification of microRNA regulatory modules (MiRMs) will aid deciphering aberrant transcriptional regulatory network in cancer but is computationally challenging. Existing methods are stochastic or require a fixed number of regulatory modules.
MicroRNA (miRNA) locus has been found that can generate a series of varied isomiR sequences. Most studies always focus on determining miRNA level, however, the canonical miRNA sequence is only a specific member in the multiple isomiRs. Some studies have shown that isomiR sequences play versatile roles in biological progress, and the analysis and research should be simultaneously performed at the miRNA/isomiR levels.
MicroRNAs (miRNAs) play key regulatory roles in various biological processes and diseases. A comprehensive analysis of large scale small RNA sequencing data (smRNA-seq) will be very helpful to explore tissue or disease specific miRNA markers and uncover miRNA variants. Here, we systematically analyzed 410 human smRNA-seq datasets, which samples are from 24 tissue/disease/cell lines. We tested the mapping strategies and found that it was necessary to make multiple-round mappings with different mismatch parameters.
MicroRNAs (miRNAs) are involved in various biological processes by suppressing gene expression. A recent work has indicated that host miRNAs are also capable of regulating viral gene expression by targeting the virus genomes. To investigate regulatory relationships between host miRNAs and related viruses, we present a novel database, namely ViTa, to curate the known virus miRNA genes and the known/putative target sites of human, mice, rat and chicken miRNAs. Known miRNAs are obtained from miRBase. Virus data are collected and referred from ICTVdB, VBRC and VirGen.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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