ARED 3.0: the large and diverse AU-rich transcriptome

A comprehensive search that utilized a large set of mRNA data from human genome databases and additionally, expressed sequence tag (EST) database characterized this latest update of AU-rich elements (AREs) containing mRNA database (ARED). A large number of ARE-mRNA, as much as 4000, were recovered and include many of ARE alternative forms. This number represents as much as 5–8% of the human genes depending on the entire number of genes. The new ARED does not contain only larger and diverse number of ARE-mRNAs but additional functionality and enhanced search capabilities are given in the database website . These include class and cluster of AREs, source mRNAs, EST evidence, buildup information, retrieval of lists of genes, and integration with current and new NCBI data, such as Entrez ID and Unigene. Gene Ontology analysis shows there are significant differences in functional diversity of ARED when compared with the overall genome. Many of ARE-genes mediate regulatory processes, reactions to outside stimuli, RNA metabolism, and developmental processes particularly those of early and transient responses. The wide interest in mRNA turnover and importance of AREs in health and disease signify the compilation of ARE-genes

ARED Organism: expansion of ARED reveals AU-rich element cluster variations between human and mouse

ARED Organism represents the expansion of the adenylate uridylate (AU)-rich element (ARE)-containing human mRNA database into the transcriptomes of mouse and rat. As a result, we performed quantitative assessment of ARE conservation in human, mouse and rat transcripts. We found that a significant proportion (∼25%) of human genes differ in their ARE patterns from mouse and rat transcripts. ARED-Integrated, another updated and expanded version of ARED, is a compilation of ARED versions 1.0 to 3.0 and updated version 4.0 that is devoted to human mRNAs. Thus, ARED-Integrated and ARED-Organism databases, both publicly available at http://brp.kfshrc.edu.sa/ARED, offer scientists a comprehensive view of AREs in the human transcriptome and the ability to study the comparative genomics of AREs in model organisms. This ultimately will help in inferring the biological consequences of ARE variation in these key animal models as opposed to humans, particularly, in relationships to the role of RNA stability in disease

Temporally Regulated Traffic of HuR and Its Associated ARE-Containing mRNAs from the Chromatoid Body to Polysomes during Mouse Spermatogenesis

International audienceBACKGROUND: In mammals, a temporal disconnection between mRNA transcription and protein synthesis occurs during late steps of germ cell differentiation, in contrast to most somatic tissues where transcription and translation are closely linked. Indeed, during late stages of spermatogenesis, protein synthesis relies on the appropriate storage of translationally inactive mRNAs in transcriptionally silent spermatids. The factors and cellular compartments regulating mRNA storage and the timing of their translation are still poorly understood. The chromatoid body (CB), that shares components with the P. bodies found in somatic cells, has recently been proposed to be a site of mRNA processing. Here, we describe a new component of the CB, the RNA binding protein HuR, known in somatic cells to control the stability/translation of AU-rich containing mRNAs (ARE-mRNAs). METHODOLOGY/PRINCIPAL FINDINGS: Using a combination of cell imagery and sucrose gradient fractionation, we show that HuR localization is highly dynamic during spermatid differentiation. First, in early round spermatids, HuR colocalizes with the Mouse Vasa Homolog, MVH, a marker of the CB. As spermatids differentiate, HuR exits the CB and concomitantly associates with polysomes. Using computational analyses, we identified two testis ARE-containing mRNAs, Brd2 and GCNF that are bound by HuR and MVH. We show that these target ARE-mRNAs follow HuR trafficking, accumulating successively in the CB, where they are translationally silent, and in polysomes during spermatid differentiation. CONCLUSIONS/SIGNIFICANCE: Our results reveal a temporal regulation of HuR trafficking together with its target mRNAs from the CB to polysomes as spermatids differentiate. They strongly suggest that through the transport of ARE-mRNAs from the CB to polysomes, HuR controls the appropriate timing of ARE-mRNA translation. HuR might represent a major post-transcriptional regulator, by promoting mRNA storage and then translation, during male germ cell differentiation

Genome-Wide Assessment of AU-Rich Elements by the AREScore Algorithm

In mammalian cells, AU-rich elements (AREs) are well known regulatory sequences located in the 3′ untranslated region (UTR) of many short-lived mRNAs. AREs cause mRNAs to be degraded rapidly and thereby suppress gene expression at the posttranscriptional level. Based on the number of AUUUA pentamers, their proximity, and surrounding AU-rich regions, we generated an algorithm termed AREScore that identifies AREs and provides a numerical assessment of their strength. By analyzing the AREScore distribution in the transcriptomes of 14 metazoan species, we provide evidence that AREs were selected for in several vertebrates and Drosophila melanogaster. We then measured mRNA expression levels genome-wide to address the importance of AREs in SL2 cells derived from D. melanogaster hemocytes. Tis11, a zinc finger RNA–binding protein homologous to mammalian tristetraprolin, was found to target ARE–containing reporter mRNAs for rapid degradation in SL2 cells. Drosophila mRNAs whose expression is elevated upon knock down of Tis11 were found to have higher AREScores. Moreover high AREScores correlate with reduced mRNA expression levels on a genome-wide scale. The precise measurement of degradation rates for 26 Drosophila mRNAs revealed that the AREScore is a very good predictor of short-lived mRNAs. Taken together, this study introduces AREScore as a simple tool to identify ARE–containing mRNAs and provides compelling evidence that AREs are widespread regulatory elements in Drosophila

IL-3 and oncogenic Abl regulate the myeloblast transcriptome by altering mRNA stability

The growth factor interleukin-3 (IL-3) promotes the survival and growth of multipotent hematopoietic progenitors and stimulates myelopoiesis. It has also been reported to oppose terminal granulopoiesis and to support leukemic cell growth through autocrine or paracrine mechanisms. The degree to which IL-3 acts at the posttranscriptional level is largely unknown. We have conducted global mRNA decay profiling and bioinformatic analyses in 32Dcl3 myeloblasts indicating that IL-3 caused immediate early stabilization of hundreds of transcripts in pathways relevant to myeloblast function. Stabilized transcripts were enriched for AU-Response elements (AREs), and an ARE-containing domain from the interleukin-6 (IL-6) 3′-UTR rendered a heterologous gene responsive to IL-3-mediated transcript stabilization. Many IL-3-stabilized transcripts had been associated with leukemic transformation. Deregulated Abl kinase shared with IL-3 the ability to delay turnover of transcripts involved in proliferation or differentiation blockade, relying, in part, on signaling through the Mek/ Erk pathway. These findings support a model of IL-3 action through mRNA stability control and suggest that aberrant stabilization of an mRNA network linked to IL-3 contributes to leukemic cell growth. © 2009 Ernst et al

Mammalian Cis-Acting RNA Sequence Elements

Cis-acting regulatory sequence elements are sequences contained in the 3′ and 5′ untranslated region, introns, or coding regions of precursor RNAs and mature mRNAs that are selectively recognized by a complementary set of one or more trans-acting factors to regulate posttranscriptional gene expression. This chapter focuses on mammalian cis-acting regulatory elements that had been recently discovered in different regions: pre-processed and mature. The chapter begins with an overview of two large networks of mRNAs that contain conserved AU-rich elements (AREs) or GU-rich elements (GREs), and their role in mammalian cell physiology. Other, less conserved, cis-acting elements and their functional role in different steps of RNA maturation and metabolism will be discussed. The molecular characteristics of pathological cis-acting sequences that rose from gene mutations or transcriptional aberrations are briefly outlined, with the proposed approach to restore normal gene expression. Concise models of the function of posttranscriptional regulatory networks within different cellular compartments conclude this chapter

Mining Functional Elements in Messenger RNAs: Overview, Challenges, and Perspectives

Eukaryotic messenger RNA (mRNA) contains not only protein-coding regions but also a plethora of functional cis-elements that influence or coordinate a number of regulatory aspects of gene expression, such as mRNA stability, splicing forms, and translation rates. Understanding the rules that apply to each of these element types (e.g., whether the element is defined by primary or higher-order structure) allows for the discovery of novel mechanisms of gene expression as well as the design of transcripts with controlled expression. Bioinformatics plays a major role in creating databases and finding non-evident patterns governing each type of eukaryotic functional element. Much of what we currently know about mRNA regulatory elements in eukaryotes is derived from microorganism and animal systems, with the particularities of plant systems lagging behind. In this review, we provide a general introduction to the most well-known eukaryotic mRNA regulatory motifs (splicing regulatory elements, internal ribosome entry sites, iron-responsive elements, AU-rich elements, zipcodes, and polyadenylation signals) and describe available bioinformatics resources (databases and analysis tools) to analyze eukaryotic transcripts in search of functional elements, focusing on recent trends in bioinformatics methods and tool development. We also discuss future directions in the development of better computational tools based upon current knowledge of these functional elements. Improved computational tools would advance our understanding of the processes underlying gene regulations. We encourage plant bioinformaticians to turn their attention to this subject to help identify novel mechanisms of gene expression regulation using RNA motifs that have potentially evolved or diverged in plant species

Post-transcriptional control during chronic inflammation and cancer: a focus on AU-rich elements

A considerable number of genes that code for AU-rich mRNAs including cytokines, growth factors, transcriptional factors, and certain receptors are involved in both chronic inflammation and cancer. Overexpression of these genes is affected by aberrations or by prolonged activation of several signaling pathways. AU-rich elements (ARE) are important cis-acting short sequences in the 3′UTR that mediate recognition of an array of RNA-binding proteins and affect mRNA stability and translation. This review addresses the cellular and molecular mechanisms that are common between inflammation and cancer and that also govern ARE-mediated post-transcriptional control. The first part examines the role of the ARE-genes in inflammation and cancer and sequence characteristics of AU-rich elements. The second part addresses the common signaling pathways in inflammation and cancer that regulate the ARE-mediated pathways and how their deregulations affect ARE-gene regulation and disease outcome

Apobec-1 Complementation Factor (ACF) Binds and Regulates Multiple RNAs

AU-Rich Elements: ARE) are cis-acting RNA sequences in the 3\u27UTRs of a wide range of transcripts that function to regulate mRNA stability, localization, and/or translation through interaction with ARE-Binding Proteins. Apobec-1 Complementation Factor: ACF) was originally identified as a co-factor in ApoB mRNA C to U editing, but has recently been implicated in regulation of mRNA stability as an ARE-Binding Protein. Here we have used tissue culture models with RNA turnover assays to show that the stability of reporters cloned upstream of the Interleukin-6: IL-6) 3\u27UTR or portions of the Cox-2 3\u27UTR is regulated by levels of ACF expression. Surprisingly, ACF expression results in stabilization of a reporter associated with the IL-6 3\u27UTR while resulting in destabilization of a reporter associated with the Cox-2 3\u27UTR. In order to more fully probe this dual ability of ACF, we examined its behavior as an RNA-binding protein. Purified recombinant truncations of ACF were used to probe the affinity and specificity of ACF binding to a panel of RNAs including ApoB mRNA: its canonical target) as well as IL-6 and Cox-2 RNAs, which we have shown are regulated in cellulo by ACF expression The first 380 amino acids of ACF, which contain three RNA recognition motifs: RRM), bind IL-6 and Cox-2 RNAs with higher affinity than ApoB mRNA. This protein is also capable of binding a C/U-rich RNA: GABA Intron), indicating that ACF has a broader target preference than simply AU-Rich RNAs. Furthermore, in vitro binding assays reveal that RRM1 of ACF binds IL-6, Cox-2, and GABA Intron RNA but not ApoB, while RRM3 does not detectably bind any of the RNAs probed. This indicates that RRM1 participates in RNA binding of some targets but not others and RRM3 is not part of the RNA-binding domain. These observations were extended using tryptophan fluorescence to determine that Cox-2 RNA interacts with ACF RRM2, suggesting that RRMs 1 and 2 together bind at least some RNA targets. UV-crosslinking assays identified discrete ACF binding sites within both the IL-6 3\u27UTR and the Cox-2 3\u27UTR. On both RNAs, these sites are consistent with regions that confer ACF-dependent mRNA stabilization or destabilization in RNA turnover assays. UV-crosslinking assays also revealed a structural preference in the ACF:Cox-2 interaction. Finally, these observations were examined in the context of ACF structural predictions. While little experimentally determined structural data exists for ACF, homology modeling was used to predict possible secondary and tertiary three-dimensional structures that may account for the physiological and binding activities observed. We propose that ACF binds RNA targets by multiple mechanisms, using one or more of its RRMs, and that the resulting complex displays the RNA to facilitate RNA editing, stabilization, or destabilization. We suggest that the geometry of the complex also impacts ACF interactions with co-factors such as Apobec-1 in mRNA editing or other ARE-Binding proteins that together regulate the stability of common RNA targets

Identification of a set of KSRP target transcripts upregulated by PI3K-AKT signaling

BACKGROUND: KSRP is a AU-rich element (ARE) binding protein that causes decay of select sets of transcripts in different cell types. We have recently described that phosphatidylinositol 3-kinase/AKT (PI3K-AKT) activation induces stabilization and accumulation of the labile β-catenin mRNA through an impairment of KSRP function. RESULTS: Aim of this study was to identify additional KSRP targets whose stability and steady-state levels are enhanced by PI3K-AKT activation. First, through microarray analyses of the AU-rich transcriptome in pituitary αT3-1 cells, we identified 34 ARE-containing transcripts upregulated in cells expressing a constitutively active form of AKT1. In parallel, by an affinity chromatography-based technique followed by microarray analyses, 12 mRNAs target of KSRP, additional to β-catenin, were identified. Among them, seven mRNAs were upregulated in cells expressing activated AKT1. Both steady-state levels and stability of these new KSRP targets were consistently increased by either KSRP knock-down or PI3K-AKT activation. CONCLUSION: Our study identified a set of transcripts that are targets of KSRP and whose expression is increased by PI3K-AKT activation. These mRNAs encode RNA binding proteins, signaling molecules and a replication-independent histone. The increased expression of these gene products upon PI3K-AKT activation could play a role in the cellular events initiated by this signaling pathway