Regulation of B‐cell development and function by microRNA s
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Summary Micro RNA s (mi RNA s) have emerged as a new class of gene expression regulators whose functions influence a myriad of biological processes, from developmental decisions through immune responses and numerous pathologies, including cancer and autoimmunity. mi RNA s are small RNA molecules that drive post‐transcriptional negative regulation of gene expression by promoting the degradation or translational block of their target m RNA s. Here, we review some of the data relating to the role of mi RNA s in the regulation of the B‐cell lineage, with a special focus on results obtained in vivo . We start by giving a general overview of mi RNA activity, including the issue of target specificity and the experimental approaches more widely used to analyze the function of these molecules. We then go on to discuss the function of mi RNA s during B‐cell differentiation in the bone marrow and in the periphery as well as during the humoral immune response. Finally, we describe a few examples of the contribution of mi RNA s, both as oncogenes and tumor suppressors, to the development of B‐cell neoplasias.Nutrients as external elements of gene expression has important effect in regulation of gene expression.The anthor introduce nutrimental regulation of gene expression on mechanisms and path,and regulation of several nutriments in gene expression.
Expression (computer science)
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Regulation of gene expression levels is essential for all living systems and transcription factors (TFs) are the main regulators of gene expression through their ability to repress or induce transcription. A balance between synthesis and degradation rates controls gene expression levels. To determine which rate is dominant, we analyzed the correlation between expression levels of a TF and its regulated gene based on a mathematical model. We selected about 280,000 expression patterns of 355 TFs and 647 regulated genes using DNA microarray data from the Gene Expression Omnibus (GEO) data repository. Based on our model, correlation between the expressions of TF-regulated gene pairs corresponds to tuning of the synthesis rate, whereas no correlation indicates excessive synthesis and requires tuning of the degradation rate. The gene expression relationships between TF-regulated gene pairs were classified into four types that correspond to different gene regulatory mechanisms. It was surprising that fewer than 20% of these genes were governed by the familiar regulatory mechanism, i.e., through the synthesis rate. Moreover, we performed pathway analysis and found that each classification type corresponded to distinct gene functions: cellular regulation pathways were dominant in the type with synthesis rate regulation and terms associated with diseases such as cancer, Parkinson's disease, and Alzheimer's disease were dominant in the type with degradation rate regulation. Interestingly, these diseases are caused by the accumulation of proteins. These results indicated that gene expression is regulated structurally, not arbitrarily, according to the gene function. This funding is indicative of a systematic control of transcription processes at the whole-cell level.
Gene regulatory network
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Adenosine deaminases acting on RNA (ADARs) catalyze the editing of adenosine residues to inosine (A-to-I) within RNA sequences, mostly in the introns and UTRs (un-translated regions). The significance of editing within non-coding regions of RNA is poorly understood. Here, we demonstrate that association of ADAR2 with RNA stabilizes a subset of transcripts. ADAR2 interacts with and edits the 3΄UTR of nuclear-retained Cat2 transcribed nuclear RNA (Ctn RNA). In absence of ADAR2, the abundance and half-life of Ctn RNA are significantly reduced. Furthermore, ADAR2-mediated stabilization of Ctn RNA occurred in an editing-independent manner. Unedited Ctn RNA shows enhanced interaction with the RNA-binding proteins HuR and PARN [Poly(A) specific ribonuclease deadenylase]. HuR and PARN destabilize Ctn RNA in absence of ADAR2, indicating that ADAR2 stabilizes Ctn RNA by antagonizing its degradation by PARN and HuR. Transcriptomic analysis identified other RNAs that are regulated by a similar mechanism. In summary, we identify a regulatory mechanism whereby ADAR2 enhances target RNA stability by limiting the interaction of RNA-destabilizing proteins with their cognate substrates.
Riboswitch
Inosine
Small nuclear RNA
ADAR
Post-transcriptional modification
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Ribonucleic acid (RNA) molecules are indispensable for cellular homeostasis in healthy and malignant cells. However, the functions of RNA extend well beyond that of a protein-coding template. Rather, both coding and non-coding RNA molecules function through critical interactions with a plethora of cellular molecules, including other RNAs, DNA, and proteins. Deconvoluting this RNA interactome, including the interacting partners, the nature of the interaction, and dynamic changes of these interactions in malignancies has yielded fundamental advances in knowledge and are emerging as a novel therapeutic strategy in cancer. Here, we present an RNA-centric review of recent advances in the field of RNA-RNA, RNA-protein, and RNA-DNA interactomic network analysis and their impact across the Hallmarks of Cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.
Interactome
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RNA degradation is a key process in the regulation of gene expression. In all organisms, RNA degradation participates in controlling coding and non-coding RNA levels in response to developmental and environmental cues. RNA degradation is also crucial for the elimination of defective RNAs. Those defective RNAs are mostly produced by ‘mistakes’ made by the RNA processing machinery during the maturation of functional transcripts from their precursors. The constant control of RNA quality prevents potential deleterious effects caused by the accumulation of aberrant non-coding transcripts or by the translation of defective messenger RNAs (mRNAs). Prokaryotic and eukaryotic organisms are also under the constant threat of attacks from pathogens, mostly viruses, and one common line of defence involves the ribonucleolytic digestion of the invader's RNA. Finally, mutations in components involved in RNA degradation are associated with numerous diseases in humans, and this together with the multiplicity of its roles illustrates the biological importance of RNA degradation. RNA degradation is mostly viewed as a default pathway: any functional RNA (including a successful pathogenic RNA) must be protected from the scavenging RNA degradation machinery. Yet, this protection must be temporary, and it will be overcome at one point because the ultimate fate of any cellular RNA is to be eliminated. This special issue focuses on modifications deposited at the 5′ or the 3′ extremities of RNA, and how these modifications control RNA stability or degradation. This article is part of the theme issue ‘5′ and 3′ modifications controlling RNA degradation’.
RNA Silencing
RNA-induced transcriptional silencing
Post-transcriptional modification
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RNA-protein interactions are the structural and functional basis of significant numbers of RNA molecules. RNA-protein interaction assays though, still mainly depend on biochemical tests in vitro. Here, we establish a convenient and reliable RNA fluorescent three-hybrid (rF3H) method to detect/interrogate the interactions between RNAs and proteins in cells. A GFP tagged highly specific RNA trap is constructed to anchor the RNA of interest to an artificial or natural subcellular structure, and RNA-protein interactions can be detected and visualized by the enrichment of RNA binding proteins (RBPs) at these structures. Different RNA trapping systems are developed and detection of RNA-protein complexes at multiple subcellular structures are assayed. With this new toolset, interactions between proteins and mRNA or noncoding RNAs are characterized, including the interaction between a long noncoding RNA and an epigenetic modulator. Our approach provides a flexible and reliable method for the characterization of RNA-protein interactions in living cells.
Nucleic acid structure
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Degradosome
RNase MRP
RNase H
Nuclease protection assay
Small nuclear RNA
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Abstract The secretion of biomolecules into the extracellular milieu is a common and well‐conserved phenomenon in biology. In bacteria, secreted biomolecules are not only involved in intra‐species communication but they also play roles in inter‐kingdom exchanges and pathogenicity. To date, released products, such as small molecules, DNA , peptides, and proteins, have been well studied in bacteria. However, the bacterial extracellular RNA complement has so far not been comprehensively characterized. Here, we have analyzed, using a combination of physical characterization and high‐throughput sequencing, the extracellular RNA complement of both outer membrane vesicle ( OMV )‐associated and OMV ‐free RNA of the enteric Gram‐negative model bacterium Escherichia coli K‐12 substrain MG 1655 and have compared it to its intracellular RNA complement. Our results demonstrate that a large part of the extracellular RNA complement is in the size range between 15 and 40 nucleotides and is derived from specific intracellular RNA s. Furthermore, RNA is associated with OMV s and the relative abundances of RNA biotypes in the intracellular, OMV and OMV ‐free fractions are distinct. Apart from rRNA fragments, a significant portion of the extracellular RNA complement is composed of specific cleavage products of functionally important structural noncoding RNA s, including tRNA s, 4.5S RNA , 6S RNA , and tm RNA . In addition, the extracellular RNA pool includes RNA biotypes from cryptic prophages, intergenic, and coding regions, of which some are so far uncharacterised, for example, transcripts mapping to the fimA‐fimL and ves‐spy intergenic regions. Our study provides the first detailed characterization of the extracellular RNA complement of the enteric model bacterium E. coli . Analogous to findings in eukaryotes, our results suggest the selective export of specific RNA biotypes by E. coli , which in turn indicates a potential role for extracellular bacterial RNA s in intercellular communication.
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Transcription
Therapeutic gene modulation
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Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context.
Gene regulatory network
Expression (computer science)
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