Open access peer-reviewed chapter

Mammalian Cis-Acting RNA Sequence Elements

Written By

Irina Vlasova-St. Louis and Calandra Sagarsky

Submitted: July 23rd, 2017 Reviewed: October 31st, 2017 Published: February 21st, 2018

DOI: 10.5772/intechopen.72124

Chapter metrics overview

1,827 Chapter Downloads

View Full Metrics


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.


  • cis-elements
  • posttranscriptional gene regulation
  • mRNA splicing
  • translation
  • mRNA stability
  • decay
  • AU-rich elements (AREs) or GU-rich elements (GREs)

1. Introduction

The control of gene expression is fundamental to mammalian cell life. Although much of this control occurs at the level of transcription, posttranscriptional control is both prevalent and momentous [1]. Work over the past quarter century has resulted in the identification of unifying concepts in posttranscriptional regulation. One unifying concept states that posttranscriptional regulation is mediated by two major molecular components: cis-acting regulatory sequence elements and trans-acting factors. Cis-acting regulatory sequence elements are subsequences contained in the 5′ untranslated region (UTR), 3′ UTR, introns, and coding regions of precursor RNA and mature mRNA that are selectively recognized by a complementary set of one or more trans-acting factors to regulate posttranscriptional gene expression. The lists of conserved cis-elements have been expanding over the past decade, but the mechanisms of the precise assembly of RNA-binding complexes in an orchestrated temporal and spatial manner have not been comprehensively described. Conserved sequences within pre-mRNAs play a major role in determining the mRNA’s configuration, stability, and ultimately the posttranslational fate of protein products. Mammalian pre-mRNAs contain almost as much conserved sequence as that ascribed to transcriptional regulatory elements, and many of these cis-elements can be attributed to known molecular functions, as described in the following paragraphs.

Trans-acting factors include RNA-binding proteins (RNA-BPs) and microRNAs (miRNAs), which are able to influence the fate of mRNA by controlling processes such as translation and mRNA degradation (reviewed in Refs. [2, 3, 4, 5]). The combinatorial interplay between RNA-BPs, various miRNAs, and a given mRNA allows for the transcript-specific regulation critical to many cellular decisions during cell division, cell quiescence, or cell senescence [6]. RNA-BP classification is growing and becoming more defined as more structural data become available. Significant progress has been made in defining RNA-binding domains, such as an RNA recognition motif (RRM), zinc fingers, double-stranded RNA-binding domains, K homology domains, pumilio homology domains, and others, that were recently reviewed in [7, 8].

In the pre-genomic era, very few cis-acting RNA sequences had been discovered, for example, AU-rich elements (AREs) in the 3′ UTR of cytokine mRNAs [9]. Advances in genomic methodologies escalated the discoveries and functional identifications of cis-acting sequences. Microarray-based studies that evaluated mRNA stability and translation on a genome-wide basis have provided valuable information about the role of posttranscriptional regulation of a wide variety of transcripts that have an important physiological function [10, 11, 12]. Genome-wide measurements of mRNA decay and bioinformatic sequence motif discovery methods were used to identify the GU-rich element (GRE) as a highly conserved sequence that was enriched in the 3′ UTR and other regions of mRNA transcripts [13]. Various experimental approaches have been developed to understand the functional importance of cis-acting sequence interactions and the network of transcripts that they regulate. One of the most widely used techniques involves immunopurification of specific RNA-binding proteins from cellular extracts followed by a high-throughput analysis of the co-purified RNA species [14]. The coupling of this technique to powerful bioinformatic analysis has led researchers to understand the binding specificity of cis-acting elements [15]. The advent of new technology such as next generation sequencing (NGS) and chemical cross-linking procedures has allowed for fine-scale mapping of cis-binding motifs as well as for the refinement of RNA-binding protein-binding sites. A variety of methods have been developed to identify the in vivotarget RNAs of a given RNA-BP, including microarray (Chip) or high-throughput sequencing (Seq) of RNA isolated by RNA-BP immunoprecipitation (RIP-Chip, RIP-Seq, and RIPiT-Seq), photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (RIP-CLIP), individual-nucleotide resolution cross-linking and immunoprecipitation (iCLIP), or UV cross-linking and immunoprecipitation (HiTS-CLIP) [16, 17, 18, 19, 20]. These methodologies involve RNA immunoprecipitation techniques with RNA-BP, followed by the NGS analysis of associated mRNA or microRNA transcripts and genome-wide identification of cis-elements within RNA target transcripts. More novel techniques such as sequence-specificity landscapes (SEQRS), HiTS-Kin/HiTS-EQ, and digestion optimized (DO)RIP-Seq focus on the identification of multiple trans-acting factors [7, 21, 22]. These techniques allow for the evaluation of the specificity of cellular RNA-BP/RNA-binding patterns from cell lysates under different conditions and might aid in the interpretation of a multiprotein complex formation and RNA-BP competition for RNA substrate. Identified RNA-binding complexes can then be isolated and interrogated in vitrousing structural and cell-based reporter assays.

This chapter focuses on mammalian cis-acting regulatory elements that have been recently discovered in different regions of mRNA: preprocessed and mature. First, we summarize recent observations of two large networks of mRNAs that contain conserved AREs or GREs in their pre-mRNA splicing sites, polyadenylation sites, and 3′/5′ UTRs. We outline the known roles for ARE and GRE in regulation of mRNA stability or translation and their role in mammalian cell physiology, with a particular emphasis on their role in the dynamic response toward environmental and developmental signals. Second, we describe advances in the identification of other conserved cis-acting elements and their functional role in different steps of RNA maturation and metabolism. We briefly outline the molecular characteristics of pathological cis-acting sequences raised from gene mutation or transcriptional aberration and overview novel approaches to restore normal gene expression. We conclude with an overview of a concise predictive model of the function of posttranscriptional regulatory networks within different cellular compartments.


2. AU-rich element (ARE)

It was noted over a quarter of a century ago that mRNAs exhibit substantial variations in turnover rate upon exposure to different cell stimuli [23, 24, 25]. Of the prominent discoveries in the mammalian cis-acting elements field, the AU-rich element was the most notable as it was the most robust determinant of mRNA instability in cytokines and early response genes [26]. Insight into the biological significance and physiological function of ARE as a coordinate regulator of posttranscriptional network was revealed through the experimental identification of ELAVL1 (HuR) and ZNF36 (TTP) proteins [27, 28, 29]. The structure of AREs is defined as a repeating pentamer (AUUUA) with 1 or 2 A to U substitutions [9]. Bioinformatic searches throughout the human transcriptome have provided computational estimation of sequence characteristics and nucleotide lengths of ARE sequences required for mRNA to be unstable [30, 31]. The number of pentamers has an additive effect on mRNA decay and deadenylation processes. AREs are classified into five clusters depending on their sequence content and position of A or U. Cluster I AREs contain up to five copies of AUUUA motifs with a nearby U-rich region and cause synchronous RNA deadenylation [32]. Cluster II AREs are composed of at least two overlapping copies of the AUUUA with an adjacent (U/A) nonamer region and cause asynchronous deadenylation. Clusters III through V AREs were identified to contain more U-rich regions and were rather ‘poorly structured’ ( Table 1 ), with an inconsistent deadenylation pattern. This classification system has proved to be helpful in understanding the observed behavior and function of ARE-containing transcripts [25].

Trans-acting factorsFunctional categoriesARE sequencesClusterGRE sequencesFunctional categoriesTrans-acting factors
Growth factors;
Cell signaling;
Cell cycle;
Cell metabolism; Cell–cell communication

Table 1.

Structural and functional comparison of AU-rich and GU-rich elements.

ARE and GRE mRNAs were clustered (with allowance for one mismatch) into five subclasses based on the number of pentameric repeats (AUUUA or GUUUG) and surrounding sequences. W indicates A or U. K indicates G or U. This table was made based on previous publications [33, 47, 74, 75, 77]. ARE- or GRE-containing transcripts in clusters I and II contain four or more overlapping AUUUA or GUUUG pentamers and are each represented by only a few hundred transcripts. Most of the transcripts in these clusters are cytokines, transcription factors, and early response genes. Clusters III through V contain shorter sequences with less sequence repetition and contain up to several thousand members.

Trans-acting factors that bind to ARE (far left column) or GRE (far right column) are: ELAVL1,2,4 (embryonic lethal, abnormal vision)-like 1,2,4; ZFP36, zinc finger protein 36; TIA1, T-cell intracellular antigen 1; TIAL1, TIA1-cytotoxic granule associated RNA-binding protein like 1; KSRP, KH-type splicing regulatory protein; HNRNP C1,D, heterogeneous nuclear ribonucleoprotein C1, D; GAPDH, Glyceraldehyde 3-phosphate dehydrogenase; CELF1,2, CUGBP-ELAV-like family member 1,2; RBM38, RNA-binding protein 38; TARDBP, Tat RNA regulatory element (TAR) DNA-binding protein; FUS, fused in sarcoma.

Genome-wide analyses of mRNA transcript half-lives showed that many labile transcripts contain conserved ARE sequence elements in their 3′ UTRs [21]. Overall, 3′ UTR-ARE-containing transcripts represent approximately 5% of the transcriptome [33]. Human mRNAs encoding cytokines and members of the NFkB cascade are particularly enriched for AREs ( Table 1 ). AREs play decisive roles in regulating the effects of cytokines on inflammatory responses since mutation of the ARE in cytokines such as TNF-alpha, IFNG, or IRF5 [34] resulted in profound autoimmune-like inflammatory syndrome [35, 36]. In general, transcripts containing functional AREs have short half-lives, although they can be rapidly stabilized in different cell types or stimulation conditions through complex posttranscriptional mechanisms involving trans-acting factors [10, 37]. Numerous trans-binding factors interact with AREs (e.g., ELAVLs, ZFP36, KSRP, TIA1, TIAL1, HRNPC1, and others, which are described in other chapters of this book) and determine the outcomes for harboring ARE transcripts. The majority of these proteins shuttle between the cytoplasm and the nucleus, where they can affect RNA splicing and 3′-end processing, in addition to altering the rate of decay in the cytoplasm [38]. In this respect, it is interesting to note that AREs are also found in intronic regions of pre-mRNAs [39, 40, 41, 42]. This observation leads to the speculation that trans-acting factors could bind ARE in the nucleus and fulfill a function that is different from their cytoplasmic one. Furthermore, a considerable overlap in the binding sites for ARE-BP with other cis-elements, such as GU-rich and poly-U sequences, warrants further investigation since the formation of secondary RNA structure might involve all of the above and subsequently rule the coordinate behavior of RNA-BPs in different cellular compartments or under different cellular stimuli [43, 44, 45].


3. GU-rich element (GRE)

GU-rich elements (GREs) are recognized as essential regulators of mRNA splicing, stability, and translation in mammalian cells [11, 46]. GU-rich containing RNAs represent approximately 8% of transcripts of the human transcriptome [47]. Genome-wide analyses of mRNA decay rates allowed for discovery of non-ARE-containing cohorts of mRNAs that exhibited rapid turnover. Computational de novomotif search identified conserved sequence elements in their 3′ UTRs in a form of a consensus U(GUUUG)n sequences [13] or GU repeats [48]. These elements were first tested in vivoin reporter systems and conferred instability onto reporter mRNAs. A well-utilized rabbit beta-globin reporter system identified GREs as sequences that regulate the decay of exogenously expressed GRE-containing reporter transcripts within cells [13]. Further verification of GRE-mediated mRNA decay came from the observation that siRNA-mediated knockdown of protein CELF1 led to the stabilization of GRE-containing beta-globin reporter transcripts as well as endogenous GRE-containing transcripts [49, 50, 51]. These studies also showed that both GU-rich sequences and GU repeats are also enriched in unstable mRNAs, though a number of GUUUG pentamers in the GRE do not seem to correlate with the mRNA decay rate. GREs were subsequently tested for RNA-binding specificities to CELF1 and CELF2 proteins in systemic evolution of ligands exponential enrichment, yeast three-hybrid system selection methods, and surface plasmon resonance quantitative binding assays, revealing that the CELF family preferentially bind to 15–22 nucleotide GU-rich RNA sequences [52, 53, 54]. Several studies reported that other proteins bind to very short UG repeats with higher affinity, but dropped once the repeats became longer than 15 nucleotides (e.g., TARDBP, FUS) [55, 56]. Binding to dispersed GRE pentanucleotides (mostly by RRM-containing proteins) have also been reported, although unified functional consequences of it are just beginning to emerge (refer to a comprehensive review in Ref. [57]).

Using whole genome microarrays and high-throughput NGS methodologies, GRE targets have been identified in a number of mammalian cells, for example, resting and activated human T cells, mouse brain cells, and myoblasts or human malignant cell lines [48, 58, 59, 60, 61]. The majority of studies extensively characterized GREs as binding sites located predominantly in 3′ UTRs and caused mRNA decay (or stabilization) depending upon the cellular and environmental context [62]. These UG-rich sequences serve as binding sites for the family of CELF and ELAVL proteins. Interestingly, these two families of RNA-binding proteins share over 80% of sequence conservation within RNA recognition motifs but cause opposite outcomes: the CELF family binding to GRE leads to mRNA degradation, but the ELAVL family function as mRNA stabilizers [63]. In addition, several studies reported that UGU repeat sequences were enriched in introns, with the same frequency as AREs [64, 65]. The authors found significant enrichment of short UG-rich motifs in intronic regions flanking exons, supporting a role for GRE in alternative splicing [66, 67], which activate or repress the splicing of pre-mRNA targets through a competitive binding by MBNL and CELF proteins. This is not surprising, as an estimated 90% of human genes produce alternatively spliced mRNA transcripts [68, 69]. Alignment of the genomic regions adjacent to canonical and alternative polyadenylation sites identified UUCUG and UGUU as conserved cis-elements, which are essential for mRNA maturation and polyadenylation site utilization [70, 71, 72, 73].

Thus, ARE and GRE can regulate pre-mRNA splicing, translation, and/or mRNA deadenylation or decay depending on the repertoire of proteins they interact with in different intracellular settings. The classification of AREs and GREs has been described in multiple manuscripts [74, 75, 76, 77], and an overview is shown in Table 1 . Single nucleotide polymorphism studies in humans demonstrated that SNPs in ARE and GRE sites are associated with higher risk of human diseases that involve adaptive immune response; mutations in these conserved cis-acting elements resulted in changes in RNA stability and binding preferences for RNA-BPs (reviewed in ref. [44, 63, 78, 79]). The opposing effects of RNA-BP on mRNA turnover may have important implications for the role of posttranscriptional regulation in proliferative diseases such as cancer. Most existing data suggest that the unbalanced expression and function of ARE-BPs appears to drive neoplastic growth and proliferation and contribute to cancer pathogenesis [44, 80]. A definitive causal connection, that is clinically relevant to human pathology, has not yet been demonstrated.


4. Poly(A) tail and polyadenylation sequences

The addition and removal of the poly(A) tail are the rate-limiting steps of maturation and degradation processes that the majority of mammalian mRNAs undergo [81, 82, 83]. Two tightly coupled reactions – cleavage and polyadenylation – involve a large number of protein components. Alternative polyadenylation of RNA is a posttranscriptional modification that plays an important role in gene expression, as it produces mRNAs that share the same coding region, but differ in their 3′ UTRs. This process is highly tissue specific and results in the generation of alternative mRNA isoforms with different stability rates and translational efficiency and even subcellular localization [84, 85, 86]. In mammals, the poly(A) cleavage/polyadenylation site is composed of three sets of consensus cis-elements: the highly conserved AAUAAA hexamer and less conserved U/GU-rich and UGUA elements. A bioinformatics analysis showed that an overwhelming majority of mammalian mRNAs harbor a conserved AAUAAA or a close canonical variant, AUUAAA, sequences [87, 88]. Flanking sequences are very important for the poly(A) site to function [89]. For example, two downstream U/GU-rich regions are both necessary for binding of the specific cleavage polyadenylation complex [90, 91]. A number of trans-binding factors regulate poly(A) site utilization and the efficiency of pre-mRNA processing in the nucleus, including five large families of CPSF, HNRNP, CF, MBNL, and CSTF proteins as well as snoRNAs [92, 93, 94, 95]. These families have opposing effects on polyadenylation site utilization in nascent RNAs, determining the final pool of mature mRNA isoforms and subsequent choreography and activity of trans-binding factors in the cytoplasm (reviewed in [96, 97]). Immediately after cleavage, poly(A) polymerases (PAPs) promote lengthening of the poly(A) tail, completing the mRNA maturation process [98, 99]. Genome-wide polyadenylation site (PAS) analysis in mammalian cells identified a great diversity of PAS utilization in different tissues and organs [73, 100]. Mutations can cause the loss of the canonical adenylation signal and subsequent switch to alternative PAS utilization [101].

Another conserved regulatory cis-element is the cytoplasmic polyadenylation element (CPE). Many mammalian RNAs contain a CPE, a UUUUA/U sequence, located in the 3′ UTR. The CPE serves as a binding site for cytoplasmic polyadenylation element-binding (CPEBs) proteins 1–4 [102]. The most obtrusive differences in the CPE usage have been described under conditions of stress [103].

The nuclear poly(A)-binding proteins (PABPs) act as poly(A) keepers during the mRNA processing through first binding to newly added (A)12 nucleotides and allowing the poly(A) tail to grow up to 250 nucleotides before the mRNA is exported into the cytoplasm [104, 105]. In the cytoplasm, the poly(A) tail acts as a cis-regulatory element and mediates mRNA translation. Recently developed methodologies make it affordable to count differentially polyadenylated mRNAs and assess the length of the poly(A) tail [106, 107, 108]. In somatic cells, mRNA deadenylation can lead to the degradation or stabilization of translationally silent transcripts; however, the importance of the poly(A) tail length in these processes is currently under scrutiny as there is an evidence that the translation is regulated independently of their poly(A) tail length in the somatic cell cycle [109]. As for embryonic developmental processes, translationally repressed mRNAs can be reactivated by cytoplasmic poly(A) tail elongation at the precise time when their encoded proteins are needed to be translated [108, 110].


5. Other intermediate cis-elements

A number of ARE-like transcripts have been identified in several mammalian systems to regulate important posttranscriptional networks of gene expression.

Poly (U) sequences are the third most conserved cis-element after ARE and GRE, which have been recently found within sequence composition at cross-link nucleotides site using the CLIP assay [111]. Frequencies of poly(U) are most highly enriched for UUUUU pentanucleotides. The HNRNPC and HNRNPD (AUF1) can recognize and bind to U sequences in pre-mRNAs, mature mRNAs, and non-coding RNAs and influence target transcript diversity in the nucleus through pre-mRNA splicing and the stability in the cytoplasm [41]. It is interesting to note that clusters V of ARE and GRE elements (see Table 1 ) include hundreds of mRNAs harboring U-pentanucleotides in the 3′ UTR, suggesting that CELF and ELAVL families can also bind to poly(U) tracts under certain conditions, perhaps with lower affinity [112].

Uridylation is an independent biochemical process that is facilitated by uridylation enzymes such as ZCCHC11 and ZCCHC6. In mammalian cells, uridylation readily occurs on deadenylated mRNAs through the recognition of short poly(A) tails (<25 nt). Protein PABPC1 antagonizes uridylation of polyadenylated mRNAs, contributing to changes in mRNA half-lives [113]. MicroRNA can also induce uridylation of its targets; however, selectivity of mRNA uridylation has not been decisively demonstrated. The development of novel methods, such as TAIL-Seq, allows for genome-wide discovery of alternative mRNA tailing processes such as uridylation and guanylation at downstream sites of shortened poly(A) tails [114]. Dynamic control of mRNA tailing is implicated in turnover and translational control and is fundamental for early embryonic development [115].

GC-rich sequences were also found to be conserved in coding and non-coding regions of mammalian mRNAs. Classified as GC-rich elements (GCREs), these were identified in NCL (nucleolin), PCBP1 and UPF protein-binding complexes [116]. GCREs regulate mRNA stability, decay, and translational efficiency [117]. Several lines of evidence establish primary function for GCRE as regulators of mRNA transcription [118].

The CU-rich element (CURE) is a target for several RNA- or DNA-binding proteins, for example, PCBP1 [119] and PTBP1 [120, 121] and regulates gene expression via a broad, but poorly defined spectrum of posttranslational mechanisms.

Oligonucleotides (T/C)nGGG/G from four separate strands can be folded into stacked tertiary structures known as G-quadruplexes, forming polymorphic loops of three G-quartet layers with four G-tracts [122, 123, 124]. Folded G-structures (Gs)2–7 are found in 3′ and 5′ UTRs, but are very rare in coding and intergenic regions, and could influence all aspects of RNA metabolism [125, 126]. Studies have shown that 3′ UTR G-quadruplexes can bind more than two dozen proteins that interact with the Gs structure and serve as regulators of transcription, splicing, processing, localization, and stability and have been recently discussed in excellent reviews [127, 128]. Moreover, bioinformatics and computational scans have shown the prevalence of intermolecular DNA–RNA G-quadruplexes and (Gs)4 pairing with miRNA in mammalian cells [129, 130]. These observations imply almost endless possibilities of intermolecular interactions, which undoubtedly would have significant impact on our understanding of transcriptional and posttranscriptional gene expression and regulation in mammalian cells.

Internal ribosome entry sites (IRESs) are heterogeneous cis-acting regulatory elements located primarily in 5′ untranslated regions of mammalian mRNAs. IRESs facilitate alternative mRNA translation, skipping the need for the m7GpppN cap structure and many translation initiation trans-acting factors in the recognition process of the translation initiation codon (e.g., AUG) by ribosomal subunits [131]. Since the length of IRES can be several hundred nucleotides long, it was difficult to identify IRES’ structural elements that are important for the common secondary structures or functions [132, 133]. In depth sequence scans through the human transcriptome identified a variety of poly-U, poly-A, and CU-rich k-mers that seem to be important determinants of the IRES activity [134]. These k-mers represent binding sites for IRES trans-acting factors and are located at positions less than 150 nt upstream of the AUG start-codon [135]. Translation initiation mediated by IRES is commonly presented as a cell survival mechanism in response to stress; however, the significance of this process and implications to human diseases are unknown due to lack of solid in vitroexperimental results that would unambiguously demonstrate the effect in vivo[136].

Pumilio response element (PRE) is another cis-element that is well defined in nonmammalian systems. A consensus 5′- UGUANAUA was derived from gel shift, RIP, PAR-CLIP, and crystal structure approaches [137]. It is present in almost 3000 mammalian mRNAs and serves as a cis-element for the PUM family of proteins [138, 139]. PUMs exert two modes of mRNA translational repression: deadenylation-mediated repression and a deadenylation-independent mechanism [140].

Another novel 3′ UTR motif (UAAC/GUUAU) is also prevalent (7% of mammalian 3′ UTRs contain one or more copies) and has strong species conservation [141]. This motif is a binding target for HNRNP A2/B1 and A1 and is involved in mRNA deadenylation. A fundamental role of UAAC/GUUAU and similar elements as regulators of the mammalian mRNA translational activation or repression is yet to be demonstrated [142].


6. Short multivalent regulatory motifs

Mapping mammalian pre-mRNA positional enrichment of short intronic splicing regulatory elements (ISREs) is another example of the identification of cis-acting elements that are most important for pre-mRNA splicing. De novosearches for multivalent RNA motifs identified a number of conserved tetra- to hexamers that mediate the position-specific combinatorial binding by RNA-binding proteins [143, 144]. The position of short motifs can predict the tissue-specific RNA isoform abundance and can serve as an intronic splicing enhancer or silencer during embryonic development and in adult organisms [145]. Since the consensus sequence elements of splice sites are very short (e.g., 5′-UUAGGU, AAGGAC, AAGAAC, CCUCUG, GCUGCG, CUGCUG-3′), the mechanism by which the spliceosome distinguishes them as authentic splice sites remains a long-standing question. One of the explanations provided in [146, 147] suggests that these sequences form specific secondary structures that increase binding affinities to RNA-binding motifs across many RNA-BPs. The strong association of ISREs with differences in splicing patterns, but poor evolutionary conservation, suggests the role for these motifs to act as cis-acting splice codes that allow for the progressive divergence of alternative splicing in vertebrates [148].


7. MicroRNAs (miRNAs)

MicroRNAs are conserved regulatory sequences that pervasively act, in trans, toward mRNA. miRNA-binding sites are important regulators of mRNA half-life and activity. The majority of miRNAs influence mRNA life span through biochemical interactions with mRNA and/or RNA-BPs [149]. This could be achieved through direct competition for a shared binding site or through remodeling of the mRNA structure to favor (or impede) miRNA association nearby [150]. In support of this, a recent bioinformatics analysis determined that UUUGUUU motifs, which bear an uncanny resemblance to GRE-binding sites, are enriched in the adjacent to many miRNA-binding sites, and their presence tends to augment miRNA activity [151]. On the other hand, any miRNA that contains a UGUKUGU or UAUKUAU seed sequences (K represents G or U) could in theory bind and occlude GRE-BP- or ARE-BP-binding motifs, which prevent any interaction with cis-elements within mRNA. For example, the mir-122 interaction with CELF1 has been demonstrated, proposing that CELF1 can play a role in the degradation of GRE-containing miRNAs [152]. It has been computed that the proximity of RNA-BP-binding sites and residues pairing to miRNA can quantitatively predict mRNA cis-element performance for several intensely studied RNA-BPs and miRNAs [153, 154, 155]. Although mechanistic details of interplay between cis-acting elements, RNA-BPs, and miRNAs are understudied, they perhaps should be a high priority, given recent observations that miRNA expression and/or processing are affected in many human diseases and disorders [156, 157, 158]. Significant progress has been made by bioinformaticians and biologists to better understand system biology of the RNA life cycle; several useful metadata hubs were created, which incorporate existing experimental data and computational approaches [159, 160]. The comprehensive list of available software and websites has been recently reviewed in Ref. [161]. However, we are still far from having a comprehensive understanding of mechanisms of RNA biogenesis and its relevance in physiological and pathological conditions.


8. Pathological cis-elements

The human genome contains a large number of short repetitive sequences that are prone to higher than average mutation rates and transcriptional errors [162], which can engender a tandem repeat expansion in cis-acting elements of 3′ or 5′ UTR, introns, or coding regions, and cause a large variety of inherited human diseases. For example, endogenous nucleotide repeat expansions are implicated in many human autosomal dominant diseases and have emerged as new groups of repeat expansion disorder associated with tri- or pentanucleotide repeat expansion pathogenesis. Pathological repeats can elicit toxicity that is triggered by toxic RNA or abnormally translated protein dipeptide or homopolymeric peptides [163]. Disorders as such include, but are not limited to the following conditions:

  • Spinocerebellar ataxia (SCAs types 1–37) is the largest and the most diverse group of inherited neurological diseases in which neurological dysfunction is driven by defects known as ataxias. Several mutations in tandem repeat expansions were discovered, including coding (CAG)n mutations in SCA1, 2, 3, 6, 7, and 17 genes; non-coding (CTG)n in SCA8[164]; non-coding (CAG)n in SCA12; (ATTCT)n – in SCA10; (TGGAA)n – in SCA31; and (GGCCTG) – in SCA36 (please see for details).

  • Myotonic dystrophies (DM), where (DM1) is associated with >300 CUG, repeats in the DMPK mRNA; and (DM2) – with >CCUG repeats in ZF9 mRNA [165].

  • Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia are associated with GGGGCC/CCCCGG repeat expansion in the non-coding region of the C9orf72 (C9ALS/FTD) gene [166].

  • Huntington’s disease is caused by CAG expansion repeats in the HTT gene [167];

  • Fragile X syndrome (FXS) arises when the FMR1 gene reach <230 CGG repeats.

  • Fragile X-associated tremor/ataxia syndrome (FXTAS) is associated with CGG/CCG repeat expansion in the fragile X gene, FMR1 [168].

Molecular pathogenesis of endogenous nucleotide repeat expansion diseases is complicated and pertained to the presence ofrepeat-associatednon-AUG translation (RAN), where translation of mutant polypeptides is initiated without an AUG-initiation codon or it is driven by the open reading frame shifts due to expanded three-base-pair repeats during skipped mispairing in the course of DNA synthesis (reviewed in [169, 170]). Although the posttranscriptional modification state of these transcripts (e.g., mRNA capping and polyadenylation) is unknown, two translational pathways are described: (1) ATG-initiated translation produces multiple polypeptides if there are multiple ORFs within the transcript. (2) RAN translation of the expanded repeat can produce up to six distinct RAN polypeptides: poly-Gln, poly-Ala, and poly-Ser RAN proteins (from CTG/CAG repeats); and poly-Leu, poly-Ala and poly-Cys polypeptides from the CAG/CUG repeat mRNA. Repeats located in antisense transcripts of above listed genes are also substrates for RAN translation, further expanding the number of pathological dipeptides or homopolymeric RAN proteins produced during disease pathogenesis.

An interesting common aspect of these pathologies is that they are caused by mutated cis-elements and are often produced through bidirectional transcription. Resultant toxic RNA causes intracellular stress and sequestration of RNA-BPs toward expanded sequence repeats [171], which changes the biochemistry of posttranscriptional regulatory networks in affected tissues. The abovementioned diseases represent an incomplete list of a growing number of disorders that can potentially have similar therapeutic opportunities. The recently developed ‘base editor’ CRISPR-Cas9 methodology has demonstrated a high power of nucleotide-level precision editing, making this approach suitable for repeat excision as genetic therapies for the above listed conditions [172] and may also correct many other RNA pathologies, for example, those driven by nonsense-mediated mRNA decay [173].


9. Models for the effects of cis-acting elements

mRNA molecules move through different cellular compartments within messenger ribonucleoprotein (mRNP) complexes in dynamic association with RNA-binding proteins that bind to conserved cis-elements shared by subsets of transcripts [174]. The association of specific trans-binding factors with conserved regulatory cis-elements shared by subsets of mRNAs coordinates the fate of these bound transcripts through posttranscriptional processes such as splicing, intracellular localization, translation, storage, or mRNA decay [175, 176]. Not surprisingly, very few transcripts have only one type of regulatory element. Focusing on individual scenarios, we built a concise predictive model of higher-order complexes that can be formed simultaneously within different cellular compartments, starting in from the nucleus and moving into the cytoplasm.

  1. Regulation of splicing by cis-elements ( Figure 1A ):

    The cis-elements within precursor RNA are catalyzed by different components of the spliceosome during constitutive splicing events [177]. Binding by RNA-BP to short intronic splicing regulatory elements (ISREs) regulates exon inclusion or exon skipping during stage-specific constitutive splicing transitions, in a position-dependent manner [67]. These processes are orchestrated by biochemical recognition and binding on a competitive basis by a family of U proteins that compose the spliceosome.

    RNA-BPs also bind to multivalent intronic sequences in precursor mRNA and regulate the alternative splicing (e.g., exon skipping, alternative splice site retention, or intron retention). Alternatively-spliced transcripts may contain different 3′ or 5′ UTRs that can be subject to differential translational regulation of mature transcripts. An important regulators of alternative splicing efficiency are PTBP, SR, RBM, and HNRNP families of proteins and snRNAs. The use of alternative exons leads to the production of transcripts with different open reading frames (ORFs) and diversifies the repertoire of encoded proteins, giving rise to protein isoforms with alternative N- and C- termini.

  2. Regulation of adenylation by cis-acting elements ( Figure 1B ):

    Alternative polyadenylation (APA) occurs in a tandem manner with splicing. Many splicing factors are also 3′-end processing factors within the mRNA 3′-end cleavage and polyadenylation (CPA) complexes. The recognition of cis-elements upstream of canonical or alternative PAS serves as a docking site for specific RNA-binding proteins (e.g., CPSF, CF, CSTFs, HNRNPs, MBNL, and CPEB), which in turn recruit canonical poly(A) polymerases (PAPOL). The CPA complex requires stabilization by a downstream GU/GC-rich sequence element (DSE) and its interaction with the CPSF-processing factors. The upstream sequence element (USE) is U-rich and serves an auxiliary role, binding to CF and PAPOL, and also stabilizes the cleavage complex.

    The cleavage and polyadenylation specific factor (CPSF) binds weaker noncanonical polyadenylation (AUUAAA) signals and cuts at the proximal polyadenylation site (PAS). The utilization of distal canonical PAS results in the processing of the full mature transcript. Cleavage at the proximal PAS leads to shortening of the 3′ untranslated region and loss of regulatory sequences within the 3′ UTR (e.g., ARE or GRE or miRNA-binding sites). MBNL can mask the region upstream of weak noncanonical PA signals, blocking the binding of cleavage factor I (CF).

    The CPEB1 protein binds the cytoplasmic polyadenylation element (CPE, consensus sequence 5′-UUUUUAU -3′) located upstream of non-canonical PA signals within the mRNA and shuttles it into the cytoplasm. The cytoplasmic CPEB1-CPE complex recruits poly(A) polymerase (PAP), which promotes the lengthening of the poly(A) tail and increases translation efficiency. The greater the distance between CPE and poly(A) tails of transcripts, the weaker the rate of adenylation.

  3. Regulation of translationby cis-acting elements ( Figure 1C ):

    Most eukaryotic mRNAs are translated by the cap-dependent mechanism, which requires recognition of the cap structure (m7GpppN) at the 5′ end by early initiation factor complexes (eIFs). EIFs recruit ribosomal subunits and initiator Met-tRNA and scan along the 5′ UTR of the mRNA to reach the start codon (an AUG triplet). During the scanning, the secondary RNA structure unwinds in an ATP-dependent manner. The 5′ UTR is rich in GC-content and is prone to folding into secondary structures, which may hinder ribosomal assembly [178]. Hairpin loops as secondary structure regulatory elements were described only for a handful of mRNAs, and their role in genome-wide translation is not known. A combination of new ribo-sequencing with fluorescent visualization might shed light on the role of hairpin loops in translation in the near future [179, 180, 181, 182]. Other internal 5′ UTR cis-element structures are AREs and GREs. Their effects on translation are mediated by a combination of RNA-BPs. They are often found to be part of hairpin loops. Visualizing a folded hairpin structure in vivois not possible at current resolution limits.

    The translation initiation via internal ribosomal entry site (IRES) occurs in a cap-independent manner. Mammalian IRES facilitates bypassing of the eIF4E-m7GpppN cap interaction and recruitment of the small and large ribosomal subunits and tRNA to the transcript, initiating translation at the canonical AUG start codon.

    G-quadruplexes within/near IRES may potentiate alternative translation. However, G4 structures in 3′ or 5′ UTRs and an open reading frame mainly repress cap-dependent translation (reviewed in Ref. [183]).

    The poly(A) tail also plays a role in translation as an mRNA stabilizer and a facilitator of mRNA circularization, which promotes translation. De-adenylation processes tend to slowdown the translation rate and eventually lead to mRNA degradation.

  4. Regulation of mRNA stabilization or decay by cis-acting elements ( Figure 1D ):

    In mammalian cells, mRNA stabilization or decay is regulated by cis-elements in the 3′ UTR. Numerous known RNA-BPs serve as trans-binding factors for ARE/GRE and other elements to facilitate transcript deadenylation and subsequent decay by exonucleases. There are also a number of RNA-BPs with the opposite function, which stabilize and promote mRNA translation. Posttranslational alteration of RNA-BPs (particularly within RNA-binding domains) can lead them to dissociate from RNA-binding complexes, and be replaced by other competitors, thereby contributing to mRNA de/stabilization [76]. A fine-tuned balance must be reached in cells for proper function at the organismal level.

  5. Interplay between mRNA, miRNA and RNA-BPs ( Figure 1E ):

    The estimates on how different miRNA and mRNA are loaded into the RNA-BP-bound RISC (RNA-induced silencing complex) were derived from CLIP assays results [184, 185, 186]. Several scenarios are possible to extract from these: If both miRNA and RNA-BP are bound to the 3′ UTR of mRNA, they will be sufficiently close to each other and the complex can be identified by CLIP. They would work cooperatively to promote the assembly of decay machinery. Independent binding by a competitor RNA-BP might disrupt this complex. The strength of miRNA-mRNA canonical and noncanonical bond formation can be computed to project possible biochemical outcomes [187, 188, 189].

    The mRNA 3′ UTR length and secondary structure formation can greatly influence both miRNA and RNA-BP-binding efficiency; it can also disrupt or assuage the assembly of RNA-BP complexes by providing high affinity or multioccupancy binding sites. The outcomes of this scenario could be anywhere from marginal translational repression to accelerated mRNA degradation.

    Cis-acting sequences within miRNAs that resemble cis-elements (ARE or GRE) have perfect complementarity to RNA-BP’s RNA-recognition motifs (RRMs). They can, in theory, occlude RRM-binding sites, acting as alternative inhibitors of RNA-BP activity. This could potentiate (or hinder) translational repression and mRNA degradation of target mRNA, depending on which RNA-BP was affected.

Figure 1.

Predictive scenarios of cis-element effects and trans-binding factors behavior on mRNA splicing, adenylation, translation, and decay. Blunt arrows indicate direct suppression; arrows represent activation. These figures are made by using the ingenuity pathway analysis software based upon the observations from previous studies or suggested regulatory mechanisms. A. Consensus multivalent sequences represent the intronic splice sites that are recognized by a family of small nuclear ribonucleoproteins (U snRNPs). These regulatory cis-elements can be divided into two types: (1) intronic regions which almost always begin with the dinucleotide GU and end with AG; and (2) intronic regions which have either AU and AC termini or GU and AG termini. Introns are also rich with pyrimidine nucleotides that cumulatively compose a pyrimidine binding tract, which also have a unique poly(A) branch point sequence upstream. Of the other four types of cis-acting elements: two are located within exons (exonic splicing enhancers, ESEs, and exonic splicing silencers, ESSs), and two are located within introns (intronic splicing enhancers, ISEs, and intronic splicing silencers, ISSs). The key trans-acting splicing factors are shown: SR, serine/arginine-rich (SR) proteins; U1 small nuclear ribonucleoproteins (U1 snRNPs); HNRNPs, heterogeneous nuclear ribonucleoproteins; PTB, polypyrimidine tract binding protein. B. Adenylation of pre-mRNA is triggered by cis-regulatory sequences named poly(A) signals: AAUAAA or/and AUUAAA; the U/GU-rich and UGUA elements. By direct analogy to splicing, canonical adenylation is regulated by RNA-BPs or snRNAs. CF, cleavage factor; CSTF, cleavage stimulation factor; CPSF, cleavage polyadenylation specificity factor; MBNL, muscle blind like protein; PAP, poly(A) polymerase; PABP, poly(A) binding protein; CPEB, cytoplasmic polyadenylation element binding protein; miRNA BS, miRNA binding sites; S RNA-BP, stabilizing RNA-binding protein; D RNA-BP, destabilizing RNA-binding protein; CPA, cleavage polyadenylation assembly; CPE, cytoplasmic polyadenylation element. C. Cis-mediated regulation of canonical and alternative translation includes sequences in all parts of mRNA. In canonical translation, the initiation factors (RNA-BPs) bind the 5′ m7GpppN cap, and then linearly scan through the 5′ UTR until reaching an AUG start codon. For simplicity, the components of the translation machinery are shown as eIF2 and eIFs (eukaryotic early translation initiation factors). PABP, poly(A) binding protein; IRES, internal ribosomal entry site; P, phosphorylation of RNA-BP. D. Schematic illustration of the cytoplasmic mRNA decay complex formation. The details for this scenario are provided in the text. S RNA-BP, stabilizing RNA-binding proteins; D RNA-BP, destabilizing RNA-binding proteins; PABP, poly(A)-binding protein; eIF2 and eIFs, eukaryotic early translation initiation factors. E. Scenarios for miRNA mediated mRNA translational repression or decay pathways. The details for this scenario are provided in the text. RISC, RNA-induced silencing complex; P, phosphorylation of RNA-BP.


10. Conclusions and perspectives

Examples given in this chapter suggest that mRNA regulation is important in multiple aspects of mammalian biology; however, it is largely unknown how the combinatorial regulation is achieved at the biological complexity of the organisms. Transcriptome-wide mapping of cis-elements and trans-binding sites demonstrates huge regulatory potentials for non-coding parts of mRNA. The more details we learn about cross-talk, molecular assembly, and compartmentalization of RNA-protein complexes, the more unifying principles we may find. Understanding of the factors and elements involved in the regulation of a particular gene expression in a single cell [190] is of paramount importance when designing molecular therapies or when attempting to modulate the expression of a target gene. Thus, scientists and geneticists have exciting opportunities ahead in the field of therapeutic genome editing.


This work is supported by University of Minnesota department of Medicine start-up fund to I. V-S. We acknowledge the University of Minnesota Supercomputing Institute for providing the access to Ingenuity Pathway Assistant.

Conflict of interest

None declared.


3′ UTR3′ untranslated region
AREAU-rich element adenylate(A)- and uridylate(U)-rich element
DMPKDystrophia myotonica protein kinase
GREGU-rich element, guanidine(G)- and uridylate(U)-rich element
m7GpppN cap7-Methylguanosine cap
Met-tRNAMethionine loaded onto transfer RNA
NFkBNuclear factor kappa-light chain enhancer of activated B cells
PTBPPolypyrimidine tract binding protein
RRMRNA-recognition motif
SRSF1Serine/arginine-rich splicing factor
UPF1Up-frameshift protein 1


  1. 1. de Klerk E, t Hoen PA. Alternative mRNA transcription, processing, and translation: Insights from RNA sequencing. Trends in Genetics. 2015;31(3):128-139
  2. 2. Keene JD. Biological clocks and the coordination theory of RNA operons and regulons. Cold Spring Harbor Symposia on Quantitative Biology. 2007;72:157-165
  3. 3. Moroy T, Heyd F. The impact of alternative splicing in vivo: Mouse models show the way. RNA. 2007;13(8):1155-1171
  4. 4. Lee JE, Cooper TA. Pathogenic mechanisms of myotonic dystrophy. Biochemical Society Transactions. 2009;37(Pt 6):1281-1286
  5. 5. Fabian MR, Sonenberg N, Filipowicz W. Regulation of mRNA translation and stability by microRNAs. Annual Review of Biochemistry. 2010;79:351-379
  6. 6. Johnson EL, Robinson DG, Coller HA. Widespread changes in mRNA stability contribute to quiescence-specific gene expression patterns in a fibroblast model of quiescence. BMC Genomics. 2017;18(1):123
  7. 7. Cook KB, Hughes TR, Morris QD. High-throughput characterization of protein-RNA interactions. Briefings in Functional Genomics. 2015;14(1):74-89
  8. 8. Maeda K, Akira S. Regulation of mRNA stability by CCCH-type zinc-finger proteins in immune cells. International Immunology. 2017;29(4):149-155
  9. 9. Chen CY, Xu N, Shyu AB. mRNA decay mediated by two distinct AU-rich elements from c-fos and granulocyte-macrophage colony-stimulating factor transcripts: Different deadenylation kinetics and uncoupling from translation. Molecular and Cellular Biology. 1995;15(10):5777-5788
  10. 10. Vlasova IA, McNabb J, Raghavan A, Reilly C, Williams DA, Bohjanen KA, Bohjanen PR. Coordinate stabilization of growth-regulatory transcripts in T cell malignancies. Genomics. 2005;86(2):159-171
  11. 11. Vlasova-St Louis I, Bohjanen PR. Coordinate regulation of mRNA decay networks by GU-rich elements and CELF1. Current Opinion in Genetics & Development. 2011;21(4):444-451
  12. 12. Blackinton JG, Keene JD. Functional coordination and HuR-mediated regulation of mRNA stability during T cell activation. Nucleic Acids Research. 2016;44(1):426-436
  13. 13. Vlasova IA, Tahoe NM, Fan D, Larsson O, Rattenbacher B, Sternjohn JR, Vasdewani J, Karypis G, Reilly CS, Bitterman PB, Bohjanen PR. Conserved GU-rich elements mediate mRNA decay by binding to CUG-binding protein 1. Molecular Cell. 2008;29(2):263-270
  14. 14. Tenenbaum SA, Carson CC, Lager PJ, Keene JD. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proceedings of the National Academy of Sciences of the United States of America. 2000;97(26):14085-14090
  15. 15. Li YE, Xiao M, Shi B, Yang YT, Wang D, Wang F, Marcia M, Lu ZJ. Identification of high-confidence RNA regulatory elements by combinatorial classification of RNA-protein binding sites. Genome Biology. 2017;18(1):169
  16. 16. Singh G, Ricci EP, Moore MJ. RIPiT-Seq: A high-throughput approach for footprinting RNA:Protein complexes. Methods. 2014;65(3):320-332
  17. 17. Chi SW, Zang JB, Mele A, Darnell RB. Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature. 2009;460(7254):479-486
  18. 18. Licatalosi DD, Mele A, Fak JJ, Ule J, Kayikci M, Chi SW, Clark TA, Schweitzer AC, Blume JE, Wang X, Darnell JC, Darnell RB. HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature. 2008;456(7221):464-469
  19. 19. Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M, Jungkamp AC, Munschauer M, Ulrich A, Wardle GS, Dewell S, Zavolan M, Tuschl T. PAR-CliP – A method to identify transcriptome-wide the binding sites of RNA binding proteins. Journal of Visualized Experiments. 2010;(41)
  20. 20. Keene JD, Komisarow JM, Friedersdorf MB. RIP-Chip: The isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts. Nature Protocols. 2006;1(1):302-307
  21. 21. Jankowsky E, Harris ME. Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing. Methods. 2017;118–119:111–118
  22. 22. Nicholson CO, Friedersdorf MB, Bisogno LS, Keene JD. DO-RIP-seq to quantify RNA binding sites transcriptome-wide. Methods. 2017;118-119:16-23
  23. 23. Shaw G, Kamen R, Pillars article: A conserved AU sequence from the 3′ untranslated region of GM-CSF mRNA mediates selective mRNA degradation. Cell. 1986;46:659–667, Journal of Immunology. 2012;189(1):5–13
  24. 24. Raghavan A, Dhalla M, Bakheet T, Ogilvie RL, Vlasova IA, Khabar KS, Williams BR, Bohjanen PR. Patterns of coordinate down-regulation of ARE-containing transcripts following immune cell activation. Genomics. 2004;84(6):1002-1013
  25. 25. Khabar KS, Bakheet T, Williams BR. AU-rich transient response transcripts in the human genome: Expressed sequence tag clustering and gene discovery approach. Genomics. 2005;85(2):165-175
  26. 26. Peng SS, Chen CY, Shyu AB. Functional characterization of a non-AUUUA AU-rich element from the c-jun proto-oncogene mRNA: Evidence for a novel class of AU-rich elements. Molecular and Cellular Biology. 1996;16(4):1490-1499
  27. 27. Antic D, Keene JD. Embryonic lethal abnormal visual RNA-binding proteins involved in growth, differentiation, and posttranscriptional gene expression. American Journal of Human Genetics. 1997;61(2):273-278
  28. 28. Atasoy U, Curry SL, Lopez de Silanes I, Shyu AB, Casolaro V, Gorospe M, Stellato C. Regulation of eotaxin gene expression by TNF-alpha and IL-4 through mRNA stabilization: Involvement of the RNA-binding protein HuR. Journal of Immunology. 2003;171(8):4369-4378
  29. 29. Ogilvie RL, Abelson M, Hau HH, Vlasova I, Blackshear PJ, Bohjanen PR. Tristetraprolin down-regulates IL-2 gene expression through AU-rich element-mediated mRNA decay. Journal of Immunology. 2005;174(2):953-961
  30. 30. Khabar KS, Dhalla M, Bakheet T, Sy C, al-Haj L. An integrated computational and laboratory approach for selective amplification of mRNAs containing the adenylate uridylate-rich element consensus sequence. Genome Research. 2002;12(6):985-995
  31. 31. Ogilvie RL, Sternjohn JR, Rattenbacher B, Vlasova IA, Williams DA, Hau HH, Blackshear PJ, Bohjanen PR. Tristetraprolin mediates interferon-gamma mRNA decay. The Journal of Biological Chemistry. 2009;284(17):11216-11223
  32. 32. Xu N, Chen CY, Shyu AB. Modulation of the fate of cytoplasmic mRNA by AU-rich elements: Key sequence features controlling mRNA deadenylation and decay. Molecular and Cellular Biology. 1997;17(8):4611-4621
  33. 33. Bakheet T, Frevel M, Williams BR, Greer W, Khabar KS. ARED: Human AU-rich element-containing mRNA database reveals an unexpectedly diverse functional repertoire of encoded proteins. Nucleic Acids Research. 2001;29(1):246-254
  34. 34. Graham R, Kyogoku C, Sigurdsson C, et al. Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus. Proceedings of the National Academy of Sciences of the United States of America. 2007;104(16):6758–6763
  35. 35. Jacob CO, Hwang F, Lewis GD, Stall AM. Tumor necrosis factor alpha in murine systemic lupus erythematosus disease models: Implications for genetic predisposition and immune regulation. Cytokine. 1991;3(6):551-561
  36. 36. Hodge DL, Berthet C, Coppola V, Kastenmuller W, Buschman MD, Schaughency PM, Shirota H, Scarzello AJ, Subleski JJ, Anver MR, Ortaldo JR, Lin F, Reynolds DA, Sanford ME, Kaldis P, Tessarollo L, Klinman DM, Young HA. IFN-gamma AU-rich element removal promotes chronic IFN-gamma expression and autoimmunity in mice. Journal of Autoimmunity. 2014;53:33-45
  37. 37. Tebo J, Der S, Frevel M, Khabar KS, Williams BR, Hamilton TA. Heterogeneity in control of mRNA stability by AU-rich elements. Journal of Biological Chemistry. 2003;278(14):12085-12093
  38. 38. Al-Ahmadi W, Al-Ghamdi M, Al-Haj L, Al-Saif M, Khabar KS. Alternative polyadenylation variants of the RNA binding protein, HuR: Abundance, role of AU-rich elements and auto-regulation. Nucleic Acids Research. 2009;37(11):3612-3624
  39. 39. Lebedeva S, Jens M, Theil K, Schwanhausser B, Selbach M, Landthaler M, Rajewsky N. Transcriptome-wide analysis of regulatory interactions of the RNA-binding protein HuR. Molecular Cell. 2011;43(3):340-352
  40. 40. Mukherjee N, Corcoran DL, Nusbaum JD, Reid DW, Georgiev S, Hafner M, Ascano M Jr, Tuschl T, Ohler U, Keene JD. Integrative regulatory mapping indicates that the RNA-binding protein HuR couples pre-mRNA processing and mRNA stability. Molecular Cell. 2011;43(3):327-339
  41. 41. Yoon JH, De S, Srikantan S, Abdelmohsen K, Grammatikakis I, Kim J, Kim KM, Noh JH, White EJ, Martindale JL, Yang X, Kang MJ, Wood WH, 3rd, Noren Hooten N, Evans MK, Becker KG, Tripathi V, Prasanth KV, Wilson GM, Tuschl T, Ingolia NT, Hafner M, Gorospe M. PAR-CLIP analysis uncovers AUF1 impact on target RNA fate and genome integrity. Nature Communications. 2014;5:5248
  42. 42. Vogel KU, Bell LS, Galloway A, Ahlfors H, Turner M. The RNA-binding proteins Zfp36l1 and Zfp36l2 enforce the thymic beta-selection checkpoint by limiting DNA damage response signaling and cell cycle progression. Journal of Immunology. 2016;197(7):2673-2685
  43. 43. Vlasova-St Louis I, Bohjanen PR. Post-transcriptional regulation of cytokine signaling by AU-rich and GU-rich elements. Journal of Interferon & Cytokine Research. 2014;34(4):233-241
  44. 44. Vlasova-St Louis I, Bohjanen PR. Post-transcriptional regulation of cytokine and growth factor signaling in cancer. Cytokine & Growth Factor Reviews. 2017;33:83-93
  45. 45. Kumagai Y, Vandenbon A, Teraguchi S, Akira S, Suzuki Y. Genome-wide map of RNA degradation kinetics patterns in dendritic cells after LPS stimulation facilitates identification of primary sequence and secondary structure motifs in mRNAs. BMC Genomics. 2016;17(Suppl 13):1032
  46. 46. Vlasova IA, Bohjanen PR. Posttranscriptional regulation of gene networks by GU-rich elements and CELF proteins. RNA Biology. 2008;5(4):201-207
  47. 47. Halees AS, Hitti E, Al-Saif M, Mahmoud L, Vlasova-St Louis IA, Beisang DJ, Bohjanen PR, Khabar K. Global assessment of GU-rich regulatory content and function in the human transcriptome. RNA Biology. 2011;8(4):681-691
  48. 48. Rattenbacher B, Beisang D, Wiesner DL, Jeschke JC, von Hohenberg M, St Louis-Vlasova IA, Bohjanen PR. Analysis of CUGBP1 targets identifies GU-repeat sequences that mediate rapid mRNA decay, Molecular and Cellular Biology 2010;30(16):3970?3980
  49. 49. Beisang D, Bohjanen P, Vlasova-St Louis I. CELF1, a multifunctional regulator of posttranscriptional networks. In: Abdelmohsen K, editor. Binding Protein. Croatia: InTech; 2012. pp. 181-206
  50. 50. Le Tonqueze O, Gschloessl B, Namanda-Vanderbeken A, Legagneux V, Paillard L, Audic Y. Chromosome wide analysis of CUGBP1 binding sites identifies the tetraspanin CD9 mRNA as a target for CUGBP1-mediated down-regulation. Biochemical and Biophysical Research Communications. 2010;394(4):884-889
  51. 51. Russo J, Lee JE, Lopez CM, Anderson J, Nguyen TP, Heck AM, Wilusz J, Wilusz CJ. The CELF1 RNA-binding protein regulates decay of signal recognition particle mRNAs and limits secretion in mouse myoblasts. PLoS One. 2017;12(1):e0170680
  52. 52. Mori D, Sasagawa N, Kino Y, Ishiura S. Quantitative analysis of CUG-BP1 binding to RNA repeats. Journal of Biochemistry. 2008;143(3):377-383
  53. 53. Marquis J, Paillard L, Audic Y, Cosson B, Danos O, Le Bec C, Osborne HB. CUG-BP1/CELF1 requires UGU-rich sequences for high-affinity binding. The Biochemical Journal. 2006;400(2):291-301
  54. 54. Takahashi N, Sasagawa N, Suzuki K, Ishiura S. The CUG-binding protein binds specifically to UG dinucleotide repeats in a yeast three-hybrid system. Biochemical and Biophysical Research Communications. 2000;277(2):518-523
  55. 55. Tollervey JR, Curk T, Rogelj B, Briese M, Cereda M, Kayikci M, Konig J, Hortobagyi T, Nishimura AL, Zupunski V, Patani R, Chandran S, Rot G, Zupan B, Shaw CE, Ule J. Characterizing the RNA targets and position-dependent splicing regulation by TDP-43. Nature Neuroscience. 2011;14(4):452-458
  56. 56. Takeda JI, Masuda A, Ohno K. Six GU-rich (6GUR) FUS-binding motifs detected by normalization of CLIP-seq by nascent-seq. Gene. 2017;618:57-64
  57. 57. Afroz T, Cienikova Z, Clery A, Allain FH. One, two, three, four! How multiple RRMs read the genome sequence. Methods in Enzymology. 2015;558:235-278
  58. 58. Lee JE, Lee JY, Wilusz J, Tian B, Wilusz CJ. Systematic analysis of cis-elements in unstable mRNAs demonstrates that CUGBP1 is a key regulator of mRNA decay in muscle cells. PLoS One. 2010;5(6):e11201
  59. 59. Beisang D, Rattenbacher B, Vlasova-St Louis IA, Bohjanen PR. Regulation of CUG-binding protein 1 (CUGBP1) binding to target transcripts upon T cell activation. The Journal of Biological Chemistry. 2012;287(2):950-960
  60. 60. Bhardwaj A, Myers MP, Buratti E, Baralle FE. Characterizing TDP-43 interaction with its RNA targets. Nucleic Acids Research. 2013;41(9):5062-5074
  61. 61. Bohjanen PR, Moua ML, Guo L, Taye A, Vlasova-St Louis IA. Altered CELF1 binding to target transcripts in malignant T cells. RNA. 2015;21(10):1757-1769
  62. 62. Dembowski JA, Grabowski PJ. The CUGBP2 splicing factor regulates an ensemble of branchpoints from perimeter binding sites with implications for autoregulation. PLoS Genetics. 2009;5(8):e1000595
  63. 63. Vlasova-St Louis I, Dickson AM, Bohjanen PR, Wilusz CJ. CELFish ways to modulate mRNA decay. Biochimica Et Biophysica Acta-Gene Regulatory Mechanisms. 2013;1829(6–7):695-707
  64. 64. Daughters RS, Tuttle DL, Gao W, Ikeda Y, Moseley ML, Ebner TJ, Swanson MS, Ranum LP. RNA gain-of-function in spinocerebellar ataxia type 8. PLoS Genetics. 2009;5(8):e1000600
  65. 65. Le Tonqueze O, Gschloessl B, Legagneux V, Paillard L, Audic Y. Identification of CELF1 RNA targets by CLIP-seq in human HeLa cells. Genomics Data. 2016;8:97-103
  66. 66. Wang ET, Ward AJ, Cherone JM, Giudice J, Wang TT, Treacy DJ, Lambert NJ, Freese P, Saxena T, Cooper TA, Burge CB. Antagonistic regulation of mRNA expression and splicing by CELF and MBNL proteins. Genome Research. 2015;25(6):858-871
  67. 67. Masuda A, Andersen HS, Doktor TK, Okamoto T, Ito M, Andresen BS, Ohno K. CUGBP1 and MBNL1 preferentially bind to 3′ UTRs and facilitate mRNA decay. Scientific Reports. 2012;2:209
  68. 68. Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nature Genetics. 2008;40(12):1413-1415
  69. 69. Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB. Alternative isoform regulation in human tissue transcriptomes. Nature. 2008;456(7221):470-476
  70. 70. Ladd AN, Cooper TA. Finding signals that regulate alternative splicing in the post-genomic era. Genome Biology. 2002;3(11):reviews0008
  71. 71. Voelker RB, Berglund JA. A comprehensive computational characterization of conserved mammalian intronic sequences reveals conserved motifs associated with constitutive and alternative splicing. Genome Research. 2007;17(7):1023-1033
  72. 72. Hu J, Lutz CS, Wilusz J, Tian B. Bioinformatic identification of candidate cis-regulatory elements involved in human mRNA polyadenylation. RNA. 2005;11(10):1485-1493
  73. 73. Tian B, Hu J, Zhang H, Lutz CS. A large-scale analysis of mRNA polyadenylation of human and mouse genes. Nucleic Acids Research. 2005;33(1):201-212
  74. 74. Bakheet T, Williams BR, Khabar KS. ARED 2.0: An update of AU-rich element mRNA database. Nucleic Acids Research. 2003;31(1):421-423
  75. 75. Bakheet T, Williams BR, Khabar KS. ARED 3.0: The large and diverse AU-rich transcriptome. Nucleic Acids Research. 2006;34(Database issue):D111-D114
  76. 76. Vlasova-St Louis I, Bohjanen PR. Feedback regulation of kinase Signaling pathways by AREs and GREs. Cell. 2016;5(1):1-14
  77. 77. Fallmann J, Sedlyarov V, Tanzer A, Kovarik P, Hofacker IL. AREsite2: An enhanced database for the comprehensive investigation of AU/GU/U-rich elements. Nucleic Acids Research. 2016;44(D1):D90-D95
  78. 78. Hitti E, Bakheet T, Al-Souhibani N, Moghrabi W, Al-Yahya S, Al-Ghamdi M, Al-Saif M, Shoukri MM, Lanczky A, Grepin R, Gyorffy B, Pages G, Khabar KS. Systematic analysis of AU-rich element expression in cancer reveals common functional clusters regulated by key RNA-binding proteins. Cancer Research. 2016;76(14):4068-4080
  79. 79. Ohno K, Takeda JI, Masuda A. Rules and tools to predict the splicing effects of exonic and intronic mutations. Wiley Interdiscip Rev RNA. 2017. [Epub ahead of print]
  80. 80. Chaudhury A, Cheema S, Fachini JM, Kongchan N, Lu G, Simon LM, Wang T, Mao S, Rosen DG, Ittmann MM, Hilsenbeck SG, Shaw CA, Neilson JR. CELF1 is a central node in post-transcriptional regulatory programmes underlying EMT. Nature Communications. 2016;7:13362
  81. 81. Sandberg R, Neilson JR, Sarma A, Sharp PA, Burge CB. Proliferating cells express mRNAs with shortened 3′ untranslated regions and fewer microRNA target sites. Science. 2008;320(5883):1643-1647
  82. 82. Chen CY, Shyu AB. Mechanisms of deadenylation-dependent decay. Wiley Interdisciplinary Reviews RNA. 2011;2(2):167-183
  83. 83. Beisang D, Reilly C, Bohjanen PR. Alternative polyadenylation regulates CELF1/CUGBP1 target transcripts following T cell activation. Gene. 2014;550(1):93-100
  84. 84. Mayr C. Evolution and biological roles of alternative 3’ UTRs. Trends in Cell Biology. 2016;26(3):227-237
  85. 85. Weng L, Li Y, Xie X, Shi Y. Poly(A) code analyses reveal key determinants for tissue-specific mRNA alternative polyadenylation. RNA. 2016;22(6):813-821
  86. 86. Mayr C, Bartel DP. Widespread shortening of 3’ UTRs by alternative cleavage and polyadenylation activates oncogenes in cancer cells. Cell. 2009;138(4):673-684
  87. 87. Xiao MS, Zhang B, Li YS, Gao Q, Sun W, Chen W. Global analysis of regulatory divergence in the evolution of mouse alternative polyadenylation. Molecular Systems Biology. 2016;12(12):890
  88. 88. Hoque M, Ji Z, Zheng D, Luo W, Li W, You B, Park JY, Yehia G, Tian B. Analysis of alternative cleavage and polyadenylation by 3′ region extraction and deep sequencing. Nature Methods. 2013;10(2):133-139
  89. 89. Neve J, Patel R, Wang Z, Louey A, Furger AM. Cleavage and polyadenylation: Ending the message expands gene regulation. RNA Biology. 2017;14(7):865-890
  90. 90. Phillips C, Pachikara N, Gunderson SI. U1A inhibits cleavage at the immunoglobulin M heavy-chain secretory poly(A) site by binding between the two downstream GU-rich regions. Molecular and Cellular Biology. 2004;24(14):6162-6171
  91. 91. Li XQ, Du D. Motif types, motif locations and base composition patterns around the RNA polyadenylation site in microorganisms, plants and animals. BMC Evolutionary Biology. 2014;14:162
  92. 92. Nazim M, Masuda A, Rahman MA, Nasrin F, Takeda JI, Ohe K, Ohkawara B, Ito M, Ohno K. Competitive regulation of alternative splicing and alternative polyadenylation by hnRNP H and CstF64 determines acetylcholinesterase isoforms. Nucleic Acids Research. 2017;45(3):1455-1468
  93. 93. Yao C, Biesinger J, Wan J, Weng L, Xing Y, Xie X, Shi Y. Transcriptome-wide analyses of CstF64-RNA interactions in global regulation of mRNA alternative polyadenylation. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(46):18773-18778
  94. 94. Batra R, Charizanis K, Manchanda M, Mohan A, Li M, Finn DJ, Goodwin M, Zhang C, Sobczak K, Thornton CA, Swanson MS. Loss of MBNL leads to disruption of developmentally regulated alternative polyadenylation in RNA-mediated disease. Molecular Cell. 2014;56(2):311-322
  95. 95. Huang C, Shi J, Guo Y, Huang W, Huang S, Ming S, Wu X, Zhang R, Ding J, Zhao W, Jia J, Huang X, Xiang AP, Shi Y, Yao C. A snoRNA modulates mRNA 3′ end processing and regulates the expression of a subset of mRNAs. Nucleic Acids Research. 2017;45(15):8647-8660
  96. 96. Charlesworth A, Meijer HA, de Moor CH. Specificity factors in cytoplasmic polyadenylation, Wiley Interdisciplinary Reviews: RNA. 2013;4(4):437-461
  97. 97. Shi Y, Manley JL. The end of the message: Multiple protein-RNA interactions define the mRNA polyadenylation site. Genes & Development. 2015;29(9):889-897
  98. 98. Li W, Li W, Laishram RS, Hoque M, Ji Z, Tian B, Anderson RA. Distinct regulation of alternative polyadenylation and gene expression by nuclear poly(A) polymerases. Nucleic Acids Research. 2017;45(15):8930-8942
  99. 99. Kashiwabara S, Nakanishi T, Kimura M, Baba T. Non-canonical poly(A) polymerase in mammalian gametogenesis. Biochimica et Biophysica Acta. 2008;1779(4):230-238
  100. 100. Wang H, Li R, Zhou X, Xue L, Xu X, Liu B. Genome-wide analysis and functional characterization of the polyadenylation site in pigs using RNAseq data. Scientific Reports. 2016;6:36388
  101. 101. Curinha A, Oliveira Braz S, Pereira-Castro I, Cruz A, Moreira A. Implications of polyadenylation in health and disease. Nucleus. 2014;5(6):508-519
  102. 102. Tsuda K, Kuwasako K, Nagata T, Takahashi M, Kigawa T, Kobayashi N, Guntert P, Shirouzu M, Yokoyama S, Muto Y. Novel RNA recognition motif domain in the cytoplasmic polyadenylation element binding protein 3. Proteins. 2014;82(10):2879-2886
  103. 103. Maillo C, Martin J, Sebastian D, Hernandez-Alvarez M, Garcia-Rocha M, Reina O, Zorzano A, Fernandez M, Mendez R. Circadian- and UPR-dependent control of CPEB4 mediates a translational response to counteract hepatic steatosis under ER stress. Nature Cell Biology. 2017;19(2):94-105
  104. 104. Keller RW, Kuhn U, Aragon M, Bornikova L, Wahle E, Bear DG. The nuclear poly(A) binding protein, PABP2, forms an oligomeric particle covering the length of the poly(A) tail. Journal of Molecular Biology. 2000;297(3):569-583
  105. 105. Kini HK, Silverman IM, Ji X, Gregory BD, Liebhaber SA. Cytoplasmic poly(A) binding protein-1 binds to genomically encoded sequences within mammalian mRNAs. RNA. 2016;22(1):61-74
  106. 106. Wilkening S, Pelechano V, Steinmetz LM. Genome-wide identification of alternative polyadenylation events using 3’T-fill. Methods in Molecular Biology. 2016;1358:295-302
  107. 107. Zheng D, Liu X, Tian B. 3’READS+, a sensitive and accurate method for 3′ end sequencing of polyadenylated RNA. RNA. 2016;22(10):1631-1639
  108. 108. Subtelny AO, Eichhorn SW, Chen GR, Sive H, Bartel DP. Poly(A)-tail profiling reveals an embryonic switch in translational control. Nature. 2014;508(7494):66-71
  109. 109. Park JE, Yi H, Kim Y, Chang H, Kim VN. Regulation of poly(A) tail and translation during the somatic cell cycle. Molecular Cell. 2016;62(3):462-471
  110. 110. Yang Q, Allard P, Huang M, Zhang W, Clarke HJ. Proteasomal activity is required to initiate and to sustain translational activation of messenger RNA encoding the stem-loop-binding protein during meiotic maturation in mice. Biology of Reproduction. 2010;82(1):123-131
  111. 111. Konig J, Zarnack K, Rot G, Curk T, Kayikci M, Zupan B, Turner DJ, Luscombe NM, Ule J. iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nature Structural & Molecular Biology. 2010;17(7):909-915
  112. 112. Zhu H, Zhou HL, Hasman RA, Lou H. Hu proteins regulate polyadenylation by blocking sites containing U-rich sequences. The Journal of Biological Chemistry. 2007;282(4):2203-2210
  113. 113. Lim J, Ha M, Chang H, Kwon SC, Simanshu DK, Patel DJ, Kim VN. Uridylation by TUT4 and TUT7 marks mRNA for degradation. Cell. 2014;159(6):1365-1376
  114. 114. Chang H, Lim J, Ha M, Kim VN. TAIL-seq: Genome-wide determination of poly(A) tail length and 3′ end modifications. Molecular Cell. 2014;53(6):1044-1052
  115. 115. Morgan M, Much C, DiGiacomo M, Azzi C, Ivanova I, Vitsios DM, Pistolic J, Collier P, Moreira PN, Benes V, Enright AJ, O’Carroll D. mRNA 3′ uridylation and poly(A) tail length sculpt the mammalian maternal transcriptome. Nature. 2017;548(7667):347-351
  116. 116. Saha S, Chakraborty A, Bandyopadhyay SS. Stabilization of oncostatin-M mRNA by binding of nucleolin to a GC-rich element in its 3’UTR. Journal of Cellular Biochemistry. 2016;117(4):988-999
  117. 117. Chakraborty A, Mukherjee S, Saha S, De S, Sengupta Bandyopadhyay S. Phorbol-12-myristate-13-acetate-mediated stabilization of leukemia inhibitory factor (lif) mRNA: Involvement of Nucleolin and PCBP1. The Biochemical Journal. 2017;474(14):2349-2363
  118. 118. Mendenhall EM, Koche RP, Truong T, Zhou VW, Issac B, Chi AS, Ku M, Bernstein BE. GC-rich sequence elements recruit PRC2 in mammalian ES cells. PLoS Genetics. 2010;6(12):e1001244
  119. 119. Cho SJ, Jung YS, Chen X. Poly (C)-binding protein 1 regulates p63 expression through mRNA stability. PLoS One. 2013;8(8):e71724
  120. 120. Xue Y, Zhou Y, Wu T, Zhu T, Ji X, Kwon YS, Zhang C, Yeo G, Black DL, Sun H, Fu XD, Zhang Y. Genome-wide analysis of PTB-RNA interactions reveals a strategy used by the general splicing repressor to modulate exon inclusion or skipping. Molecular Cell. 2009;36(6):996-1006
  121. 121. Hwang CK, Wagley Y, Law PY, Wei LN, Loh HH. Phosphorylation of poly(rC) binding protein 1 (PCBP1) contributes to stabilization of mu opioid receptor (MOR) mRNA via interaction with AU-rich element RNA-binding protein 1 (AUF1) and poly a binding protein (PABP). Gene. 2017;598:113-130
  122. 122. Kearse MG, Green KM, Krans A, Rodriguez CM, Linsalata AE, Goldstrohm AC, Todd PK. CGG repeat-associated non-AUG translation utilizes a cap-dependent scanning mechanism of initiation to produce toxic proteins. Molecular Cell. 2016;62(2):314-322
  123. 123. Harkness RWt, Mittermaier AK. G-quadruplex dynamics. Biochimica et Biophysica Acta. 2017;1865(11):1544-1554
  124. 124. Varizhuk A, Ischenko D, Tsvetkov V, Novikov R, Kulemin N, Kaluzhny D, Vlasenok M, Naumov V, Smirnov I, Pozmogova G. The expanding repertoire of G4 DNA structures. Biochimie. 2017;135:54-62
  125. 125. Bolduc F, Garant JM, Allard F, Perreault JP. Irregular G-quadruplexes found in the untranslated regions of human mRNAs influence translation. The Journal of Biological Chemistry. 2016;291(41):21751-21760
  126. 126. Ishiguro A, Kimura N, Watanabe Y, Watanabe S, Ishihama A. TDP-43 binds and transports G-quadruplex-containing mRNAs into neurites for local translation. Genes to Cells. 2016;21(5):466-481
  127. 127. Fay MM, Lyons SM, Ivanov P. RNA G-Quadruplexes in biology: Principles and molecular mechanisms. Journal of Molecular Biology. 2017;429(14):2127-2147
  128. 128. Kwok CK, Merrick CJ. G-Quadruplexes: Prediction, characterization, and biological application. Trends in Biotechnology. 2017
  129. 129. Zheng KW, Xiao S, Liu JQ, Zhang JY, Hao YH, Tan Z. Co-transcriptional formation of DNA:RNA hybrid G-quadruplex and potential function as constitutional cis element for transcription control. Nucleic Acids Research. 2013;41(10):5533-5541
  130. 130. Rouleau S, Glouzon JS, Brumwell A, Bisaillon M, Perreault JP. 3′ UTR G-quadruplexes regulate miRNA binding. RNA. 2017;23(8):1172-1179
  131. 131. Lacerda R, Menezes J, Romao L. More than just scanning: The importance of cap-independent mRNA translation initiation for cellular stress response and cancer. Cellular and Molecular Life Sciences. 2017;74(9):1659-1680
  132. 132. Wu TY, Hsieh CC, Hong JJ, Chen CY, Tsai YS. IRSS: A web-based tool for automatic layout and analysis of IRES secondary structure prediction and searching system in silico. BMC Bioinformatics. 2009;10:160
  133. 133. Baird SD, Turcotte M, Korneluk RG, Holcik M. Searching for IRES. RNA. 2006;12(10):1755-1785
  134. 134. Weingarten-Gabbay S, Elias-Kirma S, Nir R, Gritsenko AA, Stern-Ginossar N, Yakhini Z, Weinberger A, Segal E, Comparative g. Systematic discovery of cap-independent translation sequences in human and viral genomes. Science. 2016;351(6270):240-249
  135. 135. Gritsenko AA, Weingarten-Gabbay S, Elias-Kirma S, Nir R, de Ridder D, Segal E. Sequence features of viral and human internal ribosome entry sites predictive of their activity, PLoS Computational Biology 2017;13(9):e1005734
  136. 136. Terenin IM, Smirnova VV, Andreev DE, Dmitriev SE, Shatsky IN. A researcher's guide to the galaxy of IRESs. Cellular and Molecular Life Sciences. 2017;74(8):1431-1455
  137. 137. Miles WO, Korenjak M, Griffiths LM, Dyer MA, Provero P, Dyson NJ. Post-transcriptional gene expression control by NANOS is up-regulated and functionally important in pRb-deficient cells. The EMBO Journal. 2014;33(19):2201-2215
  138. 138. Morris AR, Mukherjee N, Keene JD. Ribonomic analysis of human Pum1 reveals cis-trans conservation across species despite evolution of diverse mRNA target sets. Molecular and Cellular Biology. 2008;28(12):4093-4103
  139. 139. Galgano A, Forrer M, Jaskiewicz L, Kanitz A, Zavolan M, Gerber AP. Comparative analysis of mRNA targets for human PUF-family proteins suggests extensive interaction with the miRNA regulatory system. PLoS One. 2008;3(9):e3164
  140. 140. Van Etten J, Schagat TL, Hrit J, Weidmann CA, Brumbaugh J, Coon JJ, Goldstrohm AC. Human Pumilio proteins recruit multiple deadenylases to efficiently repress messenger RNAs. The Journal of Biological Chemistry. 2012;287(43):36370-36383
  141. 141. Geissler R, Grimson A. A position-specific 3’UTR sequence that accelerates mRNA decay. RNA Biology. 2016;13(11):1075-1077
  142. 142. Wissink EM, Fogarty EA, Grimson A. High-throughput discovery of post-transcriptional cis-regulatory elements. BMC Genomics. 2016;17:177
  143. 143. Hui J, Hung LH, Heiner M, Schreiner S, Neumuller N, Reither G, Haas SA, Bindereif A. Intronic CA-repeat and CA-rich elements: A new class of regulators of mammalian alternative splicing. The EMBO Journal. 2005;24(11):1988-1998
  144. 144. Cereda M, Pozzoli U, Rot G, Juvan P, Schweitzer A, Clark T, Ule J. RNAmotifs: Prediction of multivalent RNA motifs that control alternative splicing. Genome Biology. 2014;15(1):R20
  145. 145. Wainberg M, Alipanahi B, Frey B. Does conservation account for splicing patterns? BMC Genomics. 2016;17(1):787
  146. 146. Samatanga B, Clery A, Barraud P, Allain FH, Jelesarov I. Comparative analyses of the thermodynamic RNA binding signatures of different types of RNA recognition motifs. Nucleic Acids Research. 2017;45(10):6037-6050
  147. 147. Rogelj B, Easton LE, Bogu GK, Stanton LW, Rot G, Curk T, Zupan B, Sugimoto Y, Modic M, Haberman N, Tollervey J, Fujii R, Takumi T, Shaw CE, Ule J. Widespread binding of FUS along nascent RNA regulates alternative splicing in the brain. Scientific Reports. 2012;2:603
  148. 148. Barbosa-Morais NL, Irimia M, Pan Q, Xiong HY, Gueroussov S, Lee LJ, Slobodeniuc V, Kutter C, Watt S, Colak R, Kim T, Misquitta-Ali CM, Wilson MD, Kim PM, Odom DT, Frey BJ, Blencowe BJ. The evolutionary landscape of alternative splicing in vertebrate species. Science. 2012;338(6114):1587-1593
  149. 149. Ciafre SA, Galardi S. microRNAs and RNA-binding proteins: A complex network of interactions and reciprocal regulations in cancer. RNA Biology. 2013;10(6):935-942
  150. 150. Jens M, Rajewsky N. Competition between target sites of regulators shapes post-transcriptional gene regulation. Nature Reviews. Genetics. 2015;16(2):113-126
  151. 151. Jacobsen A, Wen J, Marks DS, Krogh A. Signatures of RNA binding proteins globally coupled to effective microRNA target sites. Genome Research. 2010;20(8):1010-1019
  152. 152. Katoh T, Hojo H, Suzuki T. Destabilization of microRNAs in human cells by 3′ deadenylation mediated by PARN and CUGBP1. Nucleic Acids Research. 2015;43(15):7521-7534
  153. 153. Oh M, Rhee S, Moon JH, Chae H, Lee S, Kang J, Kim S. Literature-based condition-specific miRNA-mRNA target prediction. PLoS One. 2017;12(3):e0174999
  154. 154. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP. MicroRNA targeting specificity in mammals: Determinants beyond seed pairing. Molecular Cell. 2007;27(1):91-105
  155. 155. Van Peer G, De Paepe A, Stock M, Anckaert J, Volders PJ, Vandesompele J, De Baets B, Waegeman W. miSTAR: miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure. Nucleic Acids Research. 2017;45(7):e51
  156. 156. Perbellini R, Greco S, Sarra-Ferraris G, Cardani R, Capogrossi MC, Meola G, Martelli F. Dysregulation and cellular mislocalization of specific miRNAs in myotonic dystrophy type 1. Neuromuscular Disorders. 2011;21(2):81-88
  157. 157. Gambardella S, Rinaldi F, Lepore SM, Viola A, Loro E, Angelini C, Vergani L, Novelli G, Botta A. Overexpression of microRNA-206 in the skeletal muscle from myotonic dystrophy type 1 patients. Journal of Translational Medicine. 2010;8:48
  158. 158. Rau F, Freyermuth F, Fugier C, Villemin JP, Fischer MC, Jost B, Dembele D, Gourdon G, Nicole A, Duboc D, Wahbi K, Day JW, Fujimura H, Takahashi MP, Auboeuf D, Dreumont N, Furling D, Charlet-Berguerand N. Misregulation of miR-1 processing is associated with heart defects in myotonic dystrophy. Nature Structural & Molecular Biology. 2011;18(7):840-845
  159. 159. Erhard F, Dolken L, Jaskiewicz L, Zimmer R. PARma: Identification of microRNA target sites in AGO-PAR-CLIP data. Genome Biology. 2013;14(7):R79
  160. 160. Derti A, Garrett-Engele P, Macisaac KD, Stevens RC, Sriram S, Chen R, Rohl CA, Johnson JM, Babak T. A quantitative atlas of polyadenylation in five mammals. Genome Research. 2012;22(6):1173-1183
  161. 161. De S, Gorospe M. Bioinformatic tools for analysis of CLIP ribonucleoprotein data. Wiley Interdisciplinary Reviews RNA. 2017;8(4):1-14
  162. 162. Jansen A, Gemayel R, Verstrepen KJ. Unstable microsatellite repeats facilitate rapid evolution of coding and regulatory sequences. Genome Dynamics. 2012;7:108-125
  163. 163. Goodwin M, Swanson MS. RNA-binding protein misregulation in microsatellite expansion disorders. Advances in Experimental Medicine and Biology. 2014;825:353-388
  164. 164. Ayhan F, Ikeda Y, Dalton JC, Day JW, Ranum LPW. Spinocerebellar ataxia type 8. In: Pagon RA, Adam MP, Ardinger HH, Wallace SE, Amemiya A, Bean LJH, Bird TD, Ledbetter N, Mefford HC, Smith RJH, Stephens K, editors. GeneReviews(R). Seattle: University of Washington; 1993. University of Washington, Seattle. GeneReviews is a registered trademark of the University of Washington, Seattle. All rights reserved, Seattle (WA)
  165. 165. Meola G, Cardani R. Myotonic dystrophies: An update on clinical aspects, genetic, pathology, and molecular pathomechanisms. Biochimica et Biophysica Acta. 2015;1852(4):594-606
  166. 166. Donnelly CJ, Zhang PW, Pham JT, Haeusler AR, Mistry NA, Vidensky S, Daley EL, Poth EM, Hoover B, Fines DM, Maragakis N, Tienari PJ, Petrucelli L, Traynor BJ, Wang J, Rigo F, Bennett CF, Blackshaw S, Sattler R, Rothstein JD. RNA toxicity from the ALS/FTD C9ORF72 expansion is mitigated by antisense intervention. Neuron. 2013;80(2):415-428
  167. 167. Banez-Coronel M, Ayhan F, Tarabochia AD, Zu T, Perez BA, Tusi SK, Pletnikova O, Borchelt DR, Ross CA, Margolis RL, Yachnis AT, Troncoso JC, Ranum LP. RAN translation in Huntington disease. Neuron. 2015;88(4):667-677
  168. 168. Kong HE, Zhao J, Xu S, Jin P, Jin Y. Fragile X-associated tremor/ataxia syndrome: From molecular pathogenesis to development of therapeutics. Frontiers in Cellular Neuroscience. 2017;11:128
  169. 169. Green KM, Linsalata AE, Todd PK. RAN translation-what makes it run? Brain Research. 2016;1647:30-42
  170. 170. Cleary JD, Ranum LP. Repeat associated non-ATG (RAN) translation: New starts in microsatellite expansion disorders. Current Opinion in Genetics & Development. 2014;26:6-15
  171. 171. Singh RK, Cooper TA. Pre-mRNA splicing in disease and therapeutics. Trends in Molecular Medicine. 2012;18(8):472-482
  172. 172. van Agtmaal EL, Andre LM, Willemse M, Cumming SA, van Kessel IDG, van den Broek W, Gourdon G, Furling D, Mouly V, Monckton DG, Wansink DG, Wieringa B. CRISPR/Cas9-induced (CTGCAG)n repeat instability in the myotonic dystrophy type 1 locus: Implications for therapeutic genome editing, Molecular Therapy. 2017;25(1):24–43
  173. 173. Popp MW, Maquat LE. Leveraging rules of nonsense-mediated mRNA decay for genome engineering and personalized medicine. Cell. 2016;165(6):1319-1322
  174. 174. Turner M, Hodson D. Regulation of lymphocyte development and function by RNA-binding proteins. Current Opinion in Immunology. 2012;24(2):160-165
  175. 175. Dassi E, Re A, Leo S, Tebaldi T, Pasini L, Peroni D, Quattrone A. AURA 2: Empowering discovery of post-transcriptional networks. Translation (Austin). 2014;2(1):e27738
  176. 176. Keene JD. RNA regulons: Coordination of post-transcriptional events. Nature Reviews. Genetics. 2007;8(7):533-543
  177. 177. Padgett RA. New connections between splicing and human disease. Trends in Genetics. 2012;28(4):147-154
  178. 178. Babendure JR, Babendure JL, Ding JH, Tsien RY. Control of mammalian translation by mRNA structure near caps. RNA. 2006;12(5):851-861
  179. 179. Wu B, Eliscovich C, Yoon YJ, Singer RH. Translation dynamics of single mRNAs in live cells and neurons. Science. 2016;352(6292):1430-1435
  180. 180. Morisaki T, Lyon K, DeLuca KF, DeLuca JG, English BP, Zhang Z, Lavis LD, Grimm JB, Viswanathan S, Looger LL, Lionnet T, Stasevich TJ. Real-time quantification of single RNA translation dynamics in living cells. Science. 2016;352(6292):1425-1429
  181. 181. Wang C, Han B, Zhou R, Zhuang X. Real-time imaging of translation on single mRNA transcripts in live cells. Cell. 2016;165(4):990-1001
  182. 182. Shirokikh NE, Archer SK, Beilharz TH, Powell D, Preiss T. Translation complex profile sequencing to study the in vivo dynamics of mRNA-ribosome interactions during translation initiation, elongation and termination. Nature Protocols. 2017;12(4):697-731
  183. 183. Song J, Perreault JP, Topisirovic I, Richard S. RNA G-quadruplexes and their potential regulatory roles in translation. Translation (Austin). 2016;4(2):e1244031
  184. 184. Kishore S, Jaskiewicz L, Burger L, Hausser J, Khorshid M, Zavolan M. A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nature Methods. 2011;8(7):559-564
  185. 185. Chen W, Hu XT, Shi QL, Zhang FB, He C. Silencing of Adrm1 by RNA interference suppresses proliferation of colorectal cancer cells. Zhonghua Zhong Liu Za Zhi. 2009;31(11):815-819
  186. 186. Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano Jr M, Jungkamp AC, Munschauer M, Ulrich A, Wardle GD, Dewell S, Zavolan M, Tuschl T. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell. 2010;141(1):129–141
  187. 187. Liu C, Rennie WA, Carmack CS, Kanoria S, Cheng J, Lu J, Ding Y. Effects of genetic variations on microRNA: Target interactions. Nucleic Acids Research. 2014;42(15):9543-9552
  188. 188. Seok H, Ham J, Jang ES, Chi SW. MicroRNA target recognition: Insights from transcriptome-wide non-canonical interactions. Molecules and Cells. 2016;39(5):375-381
  189. 189. Broughton JP, Pasquinelli AE. A tale of two sequences: MicroRNA-target chimeric reads. Genetics, Selection, Evolution. 2016;48:31
  190. 190. Lemus-Diaz N, Boker KO, Rodriguez-Polo I, Mitter M, Preis J, Arlt M, Gruber J. Dissecting miRNA gene repression on single cell level with an advanced fluorescent reporter system. Scientific Reports. 2017;7:45197

Written By

Irina Vlasova-St. Louis and Calandra Sagarsky

Submitted: July 23rd, 2017 Reviewed: October 31st, 2017 Published: February 21st, 2018