Noncoding RNAs: couplers of analog and digital information in nervous system function?

Opinion

TRENDS in Neurosciences

Vol.30 No.12

Noncoding RNAs: couplers of analog and digital information in nervous system function? Georges St. Laurent III1,2 and Claes Wahlestedt3 1

The George Washington University Medical Center, Department of Biochemistry and Molecular Biology, 2300 I Street, NW, Ross Hall 232, Washington, D.C. 20037, USA 2 Immunovirology – Biogenesis Group, University of Antioquia, A.A. 1226, Medellı´n, Colombia 3 The Scripps Research Institute, Molecular and Integrative Neurosciences Department (MIND), 5353 Parkside Drive, Jupiter, FL 33458, USA

The mammalian nervous system expresses numerous noncoding RNAs (ncRNAs). We propose that ncRNAs are capable of coupling the digital information universe of nucleic acids with the analog universe of cellular protein interactions. ncRNAs could contribute to the success of the organism’s information processing in several ways. First, ncRNAs would allow for efficient coupling of energy with information, wherein less energy is required to represent and process more information, condensed in analog and digital form, into smaller spatial and temporal domains, ideal for the environments found in neural tissues. Second, ncRNAs would permit the rapid acquisition of information from the environment, along with the rapid flexible processing and elimination of that information when it is no longer necessary. Third, ncRNAs would facilitate accelerated evolution of an organism’s information content and functional computational systems. This emerging panorama might open new dimensions of information processing in the nervous system. Introduction A primary objective of higher life forms is to gather larger amounts of more relevant information, and to apply that information toward the improvement of its future information-gathering ability. The brain must rapidly acquire, process, utilize, and finally discard information. It is unique in its ability to convert free energy into a temporally and spatially elaborate information universe. The newest horizon in this universe includes a panorama of tens of thousands, or even hundreds of thousands, of noncoding RNAs (ncRNAs) of various categories (Table 1; Box 1). The half-century-old ‘‘central dogma’’ of molecular biology, and its stipulated flow of genetic information through the transcription and translation processes—‘‘DNA to (messenger) RNA to protein’’—is currently under some degree of revision to reflect new dimensions of genomic information, not least of which is ncRNA. Potentially adding a new dimension to ncRNA research, we propose here that neural tissues require the unique informationcoding capacities of ncRNA to help elaborate the sensing, Corresponding author: Wahlestedt, C. ([email protected]). Available online 8 November 2007. www.sciencedirect.com

processing, computing, and control features necessary to drive the brain’s highly complex information-gathering activities. This review focuses on the neuroscience implications of three growing bodies of evidence: (1) accumulating reports of large and expanding numbers of functional ncRNAs in the human genome; (2) studies indicating that ncRNA function is driven by a language that couples analog with digital information, resulting in more adaptable and complex information processing than previously recognized; and (3) novel functionalities for ncRNAs, important in the molecular mechanisms of neuroscience. Glossary The Cambrian explosion: describes the geologically sudden appearance of hard-bodied animals in the fossil record, around 530 million years ago. This period was accompanied by a profound diversification of life on Earth. The encyclopedia of DNA elements (ENCODE): is a public research consortium that aims to carry out a project to identify all functional elements in a portion of the human genome sequence. Functional annotation of the transcriptome of the mouse/mammal (FANTOM): is a long-standing international consortium primarily focusing on high throughput sequencing of cDNA libraries and aims at providing the ultimate characterization of the mammalian transcriptome. Long interspersed nucleotide elements (LINE): constitute one of the major classes of retrotransposons, which have invaded eukaryotic genomes, and account for 17% of the human genome. They transduce their 30 flanking sequences to new genomic loci and might create pseudogenes by reverse transcribing different cellular RNAs. Noncoding RNAs: (ncRNA) are different classes of transcribed RNA with no obvious protein-coding potential. Riboswitch: is a part of an RNA molecule with specialized secondary structure that can directly sense the environmental milieu or bind a small target molecule and whose binding of the target affects the translational activity. Thus, an mRNA that contains a riboswitch is directly involved in regulating its own activity, depending on the presence or absence of environmental factor or ligand. RNA editing: describes those molecular processes in which the information content is altered in a RNA molecule through a chemical change in the base makeup. To date, such changes have been observed in tRNA, rRNA, and mRNA molecules of eukaryotes, but not prokaryotes. RNA editing in mRNAs might alter the amino acid sequence of the encoded protein so that it differs from that predicted by the genomic DNA sequence. Short interspersed nucleotide elements (SINE): which are represented by Alu repeats, are transposons and transposon-like repetitive elements. Recent evidence indicates that there are 35–40 subfamilies of Alu, L1, and SVA elements that remain actively mobile in the human genome. The adenosine deaminases acting on RNA (ADARs): specifically target single nucleotides for editing within the partially double-stranded pre-mRNAs of their substrates, such as neuronal glutamate and serotonin receptor transcripts. The enzymes are responsible for A-to-I editing, and because inosines are read as guanosines by the translation machinery, A-to-I editing might alter the encoded protein.

0166-2236/$ – see front matter ß 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.tins.2007.10.002

Opinion

TRENDS in Neurosciences

Vol.30 No.12

613

Table 1. Mammalian RNA species mRNA

Regulatory RNA mRNA-like noncoding RNA (e.g. many natural antisense transcripts) Average 2 kb, but some extremely long (>100 kb) Yes or no

microRNA, snoRNA, snRNA, piRNA, 21U-RNAs, mirtrons 20–300 nucleotides

Length

Average 2 kb

Polyadenylated

Yes a

Spliced

In almost all cases, many alternatively Yes Yes Yes

Yes or no No No

No, but precursors might be; some encoded in introns No, but processed by other pathways from longer precursors No No No

Cytoplasmic a

Nuclear or cytoplasmic

Nuclear or cytoplasmic

Cap Translation Significant open reading frame (ORF) Localization

In many cases, some alternatively

Abbreviations: piRNA, PIWI-interacting RNA; snoRNA, small nucleolar RNA; snRNA, small nuclear (spliceosomal) RNA. a There might be exceptions.

Large numbers of ncRNAs transcribed from the mammalian genome In the 6 years since the publication of the human genome [1,2], the number and general architecture of coding genes Box 1. Some mammalian RNA species MRNAs (mRNAs) are members of a well known class of RNA with an average size of 2 kb. It is transcribed from DNA and processed before leaving the nucleus. The processed mRNA, which is located in cytoplasm, contains a poly A tail, a cap structure, and an open reading frame, and it is frequently spliced, in many cases alternatively. microRNAs (miRNAs) are small noncoding regulatory RNAs. The miRNA precursor (pri-premiRNA) is transcribed into a singlestranded RNA transcript that is 150–250 nucleotides long. A ‘‘hairpin’’ secondary structure is formed in pri-premiRNA, which is then processed by the enzyme Drosha and exported to the cytoplasm. Pre-miRNA is further processed by the enzyme Dicer to create a stable, 22 nucleotide, single-stranded, mature miRNA from one arm of the hairpin. The mature miRNA sequence tends to be highly conserved. Small nucleolar RNAs (snoRNAs) are a class of small RNA molecules that guide chemical modifications (methylation or pseudouridylation) of rRNAs (rRNAs) and other RNA genes (tRNAs and other small nuclear RNAs [snRNAs]). snoRNAs are commonly referred to as guide RNAs, but they should not be confused with the guide RNAs (gRNA) that direct RNA editing in trypanosomes. The snoRNAs are less than 70 nucleotides in length including 10–20 nucleotides of antisense elements for base pairing. Small nuclear RNAs (snRNAs) are a class of small RNA molecules that are found within the nucleus of eukaryotic cells. They are involved in a variety of processes such as RNA splicing, regulation of transcription factors (7SK RNA) or RNA polymerase II (B2 RNA), and maintaining the telomeres. Piwi-interacting RNAs (piRNAs) are a class of small RNA molecules that is expressed in mammalian testes and forms RNA-protein complexes with Piwi proteins. These piRNA complexes (piRCs) have been linked to transcriptional gene silencing of retrotransposons and other genetic elements in germline cells, particularly those in spermatogenesis. Purification of these complexes has revealed that these oligonucleotides are 29–30 nucleotides long. Natural antisense transcripts (NATs) are single-stranded RNAs that are complementary to mRNAs. NATs regulate mRNAs in a concordant or discordant manner. The average length of NAT is 2 kb, but, in some cases, it is extremely long (over 100 kb). NAT in some cases is spliced and contains a poly A tail, a cap structure, or even an open reading frame. Other long noncoding RNA transcripts (sometimes referred to as macroRNA) are diverse and not necessarily well conserved; they are often processed and contain a poly A tail and/or a cap structure. There is no significant open reading frame for macroRNAs, and their functions are largely unknown. rRNAs (rRNAs) and tRNAs (tRNAs) are well-studied components of the protein synthesis machinery. www.sciencedirect.com

has remained remarkably stable. By contrast, surprising changes have come from noncoding regions, which, together with pioneering concepts introduced by Mattick [3–5] and others, including Herbert and Rich [6,7], have created an entirely new paradigm for the human genome. Several high-throughput efforts have provided strong evidence that, in contrast to earlier understanding, a great majority of the mammalian genome is transcribed. The FANTOM Consortium produced organism-wide cDNA libraries of mouse transcripts, including a surprising 23,000 noncoding transcripts, compared to 20,929 conventional mRNAs found [8–11]. An exhaustive analysis of this data set has concluded that a majority of transcripts in mouse are noncoding [12]. Gingeras and colleagues found equally surprising results in human tissues by using genomic tiling chips, confirming those of the FANTOM Consortium [13,14]. Likewise, it was estimated that over 450,000 ncRNAs are transcribed from the human genome [15]. A more recent analysis by the Gingeras group of large and small ncRNAs revealed new families of small RNAs, provisionally termed ‘‘promoter-associated RNAs’’ (PASRs) and ‘‘termini-associated RNAs’’ (TASRs) [16]. Evidence for their biological relevance includes their location, flanking the 50 and 30 boundaries of over 50% of human genes; their expression correlation with their associated genes; and their conservation with mouse. Many of these small RNAs appear to be cleaved from longer sense and antisense transcripts, suggesting a complex network of cis- and trans-regulatory interactions. Most recently, the ENCODE pilot project has, by studying small regions of the genome in great detail, identified many novel noncoding transcripts and strongly substantiated the notion that the human genome is pervasively transcribed [17], but is not necessarily translated. Bioinformatics techniques have played an increasing role in the near geometric growth in numbers of identified mammalian ncRNAs. Improved algorithms used to search whole genomes have thus helped to discover large numbers of candidate ncRNAs. A good example of this trend is the exponential growth of the microRNA (miRNA) class since their first discovery [18,19]. Many new miRNA predictions, found by sophisticated algorithms such as the ‘‘pyknon’’ pattern recognition system, await validation [20]. When used to search for miRNAs in the human genome, pyknons predict over 55,000 miRNAs, with stringent criteria [21]. A range of useful databases have documented the growth in

614

Opinion

TRENDS in Neurosciences

ncRNA numbers and functions. For miRNAs, they include miRbase [22] and Argonaute [23] among others. RNAdb [24], RFAM [25], and NONCODE [26] cover all classes of ncRNAs. snoRNAbase treats snoRNAs [26,27], and RegRNA is dedicated to RNA regulatory motifs [28]. Table 1 and Box 1 summarize and briefly describe different categories of RNAs, illustrating a previously unexpected diversity. Nonconservation and evolutionary plasticity of ncRNA Whereas conserved ncRNAs have been the first to be identified by bioinformatics approaches, the non-conserved ncRNA families could be larger, and still relatively overlooked [29]. Discoveries of important ncRNAs such as XIST, H-19, and the brain-specific Human Accelerated RNA (HAR) [30] have demonstrated that interspecies sequence conservation is not a requirement for physiological function. Indeed, recently, 447 new miRNAs with relatively little interspecies conservation have been discovered in human and chimpanzee brain [31]. Instead of the relatively strict structure-function constraints that exist for proteins, the constraints on miRNAs, for example, largely depend on the number of functional targets of each different miRNA, with a greater number of targets implying greater constraint and more conservation [32]. As their relative nonconservation suggests, metazoan ncRNAs are a relatively recent evolutionary macroevent, not vestiges of the old RNA world. Mattick has presented an analysis indicating that protein-based networks reached a functional limit before the Cambrian Explosion [33–35]. The ncRNAs we now see in the mammalian genome are arguably a consequence of a special necessity—the evolutionary pressure to find a more efficient and computationally powerful toolset for the control of gene expression. Thus, modern ncRNA computational machinery would have allowed for the subsequent geometric growth in metazoan, mammalian, and especially primate complexity. Such evolutionary plasticity, combined with superior functionality as an information-processing system, might explain the cumulative fixation of greater numbers of ncRNAs with increasing organismal complexity [32,36]. Unlike coding or directly regulatory RNA, with established sequence-crucial functions, ncRNA holds more evolutionary plasticity [37], as further elucidated below. Notably, because much of that higher organism complexity is concentrated in the brain, the theory predicts broad involvement of many classes of ncRNA in information processing associated with higher brain function, where inherent evolvability and plasticity would be highly useful features [38]. ncRNAs play crucial roles at many levels in the control of gene expression ncRNAs probably play roles at almost every level in the gene expression machinery, with few signaling pathways spared of their influence. Accumulating evidence suggests that ncRNA elements maintain the molecular computation and information flow required to deliver the right transcripts, to the right location, at the right time. Their impact can be felt from the moment of RNA Polymerase II (Pol II) transcription initiation, through www.sciencedirect.com

Vol.30 No.12

the entire life cycle of coding transcripts until their degradation by elements of nonsense-mediated decay (NMD) and exosomal pathways (see Figure 1 for details and examples.) ncRNAs can function to repress transcription, as in the ncRNAs transcribed upstream of the human dihydrofolate reductase major promoter [39], or enhance transcription, as in the case of the EVF-2 ncRNA expressed in mouse forebrain [40]. A variety of molecular mechanisms exist, including the formation of DNA-RNA triplexes, sense–antisense pairing, binding of ncRNAs to transcriptional enhancers or inhibitors, or modulation of epigenetic machinery [41]. At least some 40% of conventional protein-coding genes in mouse and human have antisense transcript partners, most of which are noncoding [42]. Functionally, antisense transcripts have the capacity to regulate the expression of their sense partners, either concordantly (antisense transcript abrogation results in concomitant sense transcript reduction), as shown for svPINK1 in human neuroblastoma cells [43], or discordantly (antisense transcript abrogation results in sense transcript elevation) [41]. Several ncRNAs, including 7SK RNA [44,45], B2 RNA [46,47] NRON, U1 RNA (a possible information link between transcription and splicing), and others, target RNA Pol II itself [48]. Notably, neuronal-specific RNA element (NSRE), a 20 bp dsRNA, has been found to activate gene expression in neuronal stem cells, causing them to differentiate [49]. Once a new transcript has been created, there are many more opportunities for ncRNAs to influence the temporal and spatial patterns of its expression. Splicing, subcellular localization, ADAR (adenosine deaminase that acts on RNA) editing, and polyadenylation are activities probably modulated by ncRNAs (see also Figure 1). ncRNAs are strong candidates for participatation in the complex computational machinery of neural alternative splicing. The brain is the most complex environment for alternative splicing of any tissue, with tens of millions of possibilities that need to be recomputed frequently during the lifetime of each neuron. An interesting example is provided by the Drosophila Dscam gene, in which splicing errors that disrupt choices between the more than 34,000 different potential alternative isoforms cause subtle, but highly specific, defects in fine arborization of mechanosensory neurons [50]. The HBII-52 snoRNA functions to modulate alternative splicing of the serotonin receptor 2C (5HT2C) gene [51,52] and to repress ADAR editing. The recent discovery of NEAT1 and NEAT2, as components of the SC35 splicing domains (nuclear speckles), adds to the growing list of ncRNAs involved in splicing. For example, recent studies of presynaptic genes found hundreds of highly conserved, secondary-structure-forming, intronic sequences, suggestive of ncRNAs involved in controlling presynaptic gene expression [53]. The recent discovery of intronic riboswitch-controlled alternative splicing provides another potential mechanism for ncRNA involvement in alternative splicing [54]. After splicing, the resulting mature transcript is then subjected to the controls and modulations of the wellstudied RISC complex of proteins and miRNAs (for reviews

Opinion

TRENDS in Neurosciences

Vol.30 No.12

615

Figure 1. An illustration of the path followed by a protein-coding transcript, during its creation and maturation, illustrates the large cumulative effect of ncRNAs on the expression of its corresponding protein. Each number in the diagram identifies a separate mechanism by which an ncRNA can affect a transcript during different phases of mRNA biogenesis. See the text for additional information. P body, mRNA processing body; RISC, RNA-induced silencing complex; NFAT, nuclear factor of activated T cell. 1. Epigenetic guidance (imprinting, methylation, demethylation) (e.g. IGF2r, KvLQT [95,96]). 2. RNA-DNA triplex inhibition of promoter region (e.g. DHFR locus, upstream transcripts [39]). 3. RNA-based enhancement of transcription (e.g. Air, EVF-2 [97]). 4. RNA-induced transcriptional gene silencing (TGS) (e.g. RITS [98]). 5. Modifications to functional RNAs (e.g. snoRNAs [51]). 6. X inactivation (e.g. XIST, Tsix [99]). 7. ncRNAs targeting activators and repressors of transcription (e.g. NRSE, SRA, HSR1 [65,100,101]). 8. Stimulation of initiation (e.g. U1 to TFIIH [48]). 9. Transcription elongation (e.g. 7SK to PtefB [44]). 10. ncRNA targeting Pol II (e.g. B2 RNA [46,47]). 11. Splicing (e.g. HBII-52, SC35 complex, TTP riboswitch [52–54]). 12. Transcript editing (e.g. HBII-52, TS [51]). 13 Nuclear sequestration (e.g. CTN—paraspeckles [102]). 14. Polyadenylation (e.g. IDE [103]). 15. Transport to the cytoplasm (e.g. NF90—tau mRNA [88]). 16. mRNA stabilization/destabilization (Bri-2, HIF-a1 [104]). 17. Sequestration to P body by RISC complex (e.g. miRNA [83,84,89–92]). 18. Transcript cleavage by RISC (e.g. siRNA [41]). 19. Translation initiation arrest (e.g. B1, B200, BCMA [105]). 20. Release of translation inhibition (e.g. CAT mRNA in response to stress [81]). 21. Nuclear localization of TFs (e.g. NRON [106]).

see [55,56]). Moreover, transcription of ncRNA might also demarcate chromosomal domains of gene silencing at a distance, as recently shown for human HOX loci [57]. Figure 1 summarizes the multitude of mechanisms through which ncRNAs have recently been implicated in the control of mammalian gene expression. The analog-digital language of ncRNAs Whereas the discovery of mammalian ncRNA species has grown geometrically, a unifying conceptual understanding of their function remains elusive. This ncRNA molecular language probably has its foundations in the unique set of information-coding and computational features of these molecules. www.sciencedirect.com

ncRNAs contain unique and rapidly evolvable [38,58] information signatures, coupling analog to digital within in the same molecule, facilitating computationally complex interaction pathways between RNA, DNA, and protein. The analog-digital distinction is a conceptually simple, but powerful technique to better understand the subtleties of RNA information signaling and processing (see Box 2 for our definitions of the terms, analog and digital). Analog information coded into RNA can produce dramatic results. Owing to the degeneracy of the genetic code for amino acids, close to 30% of the total Shannon entropy (information-coding potential) remains digitally unused. Shabalina and colleagues showed that these degenerate codons often contain analog information specifying

616

Opinion

TRENDS in Neurosciences

Box 2. Definition of the ‘‘analog and digital’’ terminology Information flows from a source to a destination (using common semantic grammar). Information theory identifies the discrete, ON/ OFF, existence/nonexistence distinction as the most basic, indivisible unit of information. The Shannon Entropy measures information content in exactly these units of discrete ON/OFF distinctions, called ‘‘bits.’’ Digital information flows encode information directly as multiples of such discrete ON/OFF units. In biological systems, digital information and analog information flow between coupled source-destination pairs. At the level of RNA in the eukaryotic cell, digital information refers to the established grammar of Watson Crick base pairing, in which the degrees of freedom of nucleotide hybridization in shape space are restricted by the ribose backbones and the double-helix conformation energetically favored by these molecules. Analog information, by contrast, is represented by RNA secondary and tertiary structure, determined by the equations of Boltzmann statistical thermodynamics. These equations can be considered ‘‘boundary value equations’’ integrating many other elements of analog information, such as temperature, salt concentration, and hydrophobicity to ‘‘compute’’ a solution—the shape and charge landscape of the RNA shape. In theory, the shape of an RNA can cover a continuous range over a subspace of RNA shape space. RNA analog information has several consequences: it allows an RNA molecule to ‘‘understand’’ or ‘‘communicate’’ with the complex analog grammar of protein shape space; it allows an RNA molecule to adopt a range of shapes in response to changes in the cellular environment (boundary conditions); and it allows RNA to be molded into a functional complex, as well as an informational molecule. Neither analog information nor digital information can communicate with each other without carefully crafted coupling machinery. Any system that does couple analog and digital information has a qualitatively better design and functional capabilities. The better the coupling, the better the design. A useful approach to distinguish between digital and analog information is to look quantitatively at the content of an RNA molecule that contains some of both: according to Shannon’s Entropy Equation for information content of a message, the total information content of an exon that is 300 nucleotides long is: IT = log2 (4300) = 600 bits. By contrast, the digital information content of the polypeptide translated from this exon is only: ID = log2 (20100) = 432 bits. The remaining 168 bits can be used to specify analog information, thereby generating secondary and tertiary structure in the mRNA. The analog nature of this information makes it recognizable and perhaps crucial to the protein machineries of the cell involved in translation, trafficking, and other aspects of gene expression.

precise mRNA secondary structures [59,60]. Such changes in secondary structure can have dramatic functional outcomes. For example, haplotypes (transcripts from human genetic variants) of Catechol-O-methyltransferase, divergent only in synonymous codon changes, exhibit large differences in translated protein levels [61]. In other transcripts, these digitally silent analog signals [62] can change splicing patterns [63]. ncRNAs can adopt almost any required analog shape in multidimensional conformational space [64]. Because millions of affinity binding interactions based on shape and charge distributions together define the analog world of the cell, molecular adaptors that can connect this analog world directly to the digital language of nucleic acids represent a unique potential for higher-order integration and control of gene expression. Several ncRNAs now appear to form duplexes or triplexes with important DNA regions, whereas other sequences in the same ncRNA www.sciencedirect.com

Vol.30 No.12

form secondary structures that bind to proteins important for transcription or epigenetic modifications (see Figure 1 and references therein). Thus, the addressing and localization mechanisms for epigenetic machinery, currently under intensive study, could make use of ncRNA digital and analog information coupling to improve system dynamics and signal-to-noise ratios. Figure 2 provides a schematic illustration of the proposed digital to analog coupling through reversible modulation of an ncRNA. Reversibility and sensitivity features of ncRNAs We thus argue that ncRNAs could be able to integrate diverse information elements in the cell to achieve a coordinated control of gene expression. In fact, thermodynamics and Information Theory arguments favor an extensive role for ncRNAs in cellular control and homeostasis. What used to be simply considered ‘‘dsRNA’’ has now become a multitude of differentiable structures with highly varied information content and signaling potential [32,41], a veritable computing system using shapes and charge distributions as the encoding medium. ncRNAs can convey crucial information to cellular signaling systems through small changes in RNA secondary structure. For example, in the Catechol-O-methyltransferase example described above, a variance in the mRNA folding energy of only 8 kcal/mol can produce large changes in translational efficiency [61]; coding a similar information signal through ATP-dependent phosphorylation would cost 32 kcal/mol. Thus, analog information coding in RNA can provide a large information-processing advantage, by improving the information-energy ratio, a key objective of neural tissues. Whereas the evolutionary design constraints require proteins to resist most microenvironment-induced changes in secondary structure, ncRNAs are relatively free to change their secondary structure in response to finegrained changes in cellular conditions. The recently discovered Heat Shock Response (HSR) RNA [65] provides an excellent example, establishing ncRNA as environmental sensors in mammals. A 600 nt constitutively expressed ncRNA, HSR1, is required for HSF activation. The ncRNA itself is not induced by heat shock, strongly suggesting that this ncRNA functions as a thermosensor, sensing the analog temperature information in the cellular environment and responding with a change in its own analog shape, which is recognized in turn by proteins in the HSF1 activation complex [65]. ncRNAs respond to subtle environmental changes with changes in their secondary structure (analog information), which can result in the presentation of different digital information, with dramatic computational effects. In the recently discovered eukaryotic riboswitch [54], located in the NMT1 gene of Neurospora crassa, binding to thiamine causes a change in secondary structure, followed by the presentation of 12 previously sequestered nucleotides that are strongly complementary to the 50 splice site of the gene, creating an immediate change in splicing [54]. Neuronal tissues are probably subject to relatively extreme conditions as a result of spike activity, synaptic function, and the long distances involved in axonal and

Opinion

TRENDS in Neurosciences

Vol.30 No.12

617

Figure 2. Proposed model for digital to analog coupling through reversible modulation of a noncoding RNA (ncRNA). Combining ncRNA ability and function as a sensor, with its many modes of secondary-structure alteration, interaction, processing, and interaction with heterogeneous partners, can produce intelligent informationprocessing circuits, resulting in ‘‘cellular intelligence.’’ The ncRNA at the upper left of the diagram is about to undergo a change in secondary structure as a result of some cellular stress (e.g., heat shock affecting Heat Shock RNA). This secondary shape change triggers a series of combinatorial decisions, each of which is affected by concentration levels and availability of various transiently interacting macromolecular partners, as well as the inherent computational nature of the substrate ncRNA itself. As the events progress, the ncRNA can be trafficked to the nucleus for further signaling, cleaved, edited, or finally returned to its original state when the stress is eliminated from the microenvironment. The potential exists to form reticular networks of ncRNAs within different cellular microenvironments for the sensing and computational processing of stress signals. See the text for further explanation of the model. TF, transcription factor.

dendritic transport. This would create a fertile environment for microregion-specific changes in the ncRNA conformational landscape, in a fashion similar to that described above for HSR1 and eukaryotic riboswitches [54]. The sensory and computational features of ncRNA potentially use the degrees of freedom in RNA conformational space to respond to stress and changing conditions in their microenvironment. When the information-processing event is finished, the feature of ncRNA thermodynamic near-reversibility allows the neuron to erase the no-longer-useful information by returning the ncRNA to its original conformation (see Figure 2). ncRNAs accelerate evolution As suggested in the Introduction, a most valuable advantage would come from evolving a tool set that was itself able to increase its own ability to evolve. Evidence is accumulating that, especially in primates, such a system operates through RNA, by using machinery that includes ADARs, long interspersed repeated elements (LINEs), and Alu-repeat sequences (ALUs). www.sciencedirect.com

Brain-expressed ADAR enzymes can widely edit ncRNAs with secondary structure, including crucial signaling transcripts such as those encoding the 5HT2C, KCNA1, and gluR receptors [66]. ADAR editing occurs in both mRNAs and ncRNAs and can be modulated by ncRNA interactions with editing sites. The highest levels of editing appear to be primate specific [67]. ADAR editing sites contain information accumulated over evolutionary time in the form of secondary structures and, in humans, might especially target ALU sequences [67]. There is increasing evidence that the ADAR machinery also responds to sensory information and stress. In Drosophila, modest temperature changes produce specific changes in editing profiles: editing at some sites increases, whereas editing at other sites decreases. ADAR2 activity might be modulated in response to changes in neurotransmitter levels [68]. An instructive example of how ADAR could participate in determining complex behavior and reproductive fitness is provided from studies of Drosophila ADAR / mutants. In ADAR mutant male flies, the mating song changes,

618

Opinion

TRENDS in Neurosciences

becoming less attractive to females, which, in turn, reduces the reproductive fitness of the male ADAR / fly. Combining the precise recognition of accumulated evolutionary information with rapid sensory and stress-response inputs could result in a sophisticated computational system that influences complex neurological behavior in model organisms as well as in mammals [69]. Capturing such RNA information, both edited and nonedited, back into the genome would offer interesting evolutionary advantages. The elements necessary to accomplish this appear to exist as a result of the expression of protein products of LINEs (Orf1, an RNA-binding and shuttling protein, and Orf2, a reverse transcriptase that exhibits DNA-nicking activity). These proteins provide the elements necessary for writing RNA information, both edited and nonedited, back into the genome [70]. On an evolutionary timescale, at least, evidence already exists for this mechanism. Evidence implicates LINE mechanisms in the creation of pseudogenes (relatives of known genes, usually nonfunctional), including such important examples as functional Nanog pseudogenes [71], presumably by copying RNA back into the genome. ADAR might have participated in the creation of the HAR1 and HAR-2 sequences, because the sequential A ! G substitutions within these ‘‘human accelerated regions’’ are notable. ncRNAs facilitate molecular mechanisms of complex functions in the nervous system Their functional diversity, large numbers, and widespread expression in neural tissues argue for ncRNA involvement in the most complex nervous system activities. Techniques/ tools such as in situ hybridization (ISH), locked nucleic acids (LNAs), and customized microarrays have begun to reveal a fascinating ncRNA expression landscape in the mammalian central nervous system [63–65]. For example, by using the FANTOM ‘‘tour de force’’ murine cDNA library collection, the Allen Brain Institute ISH project has revealed many brain-specific RNA expression patterns. Many of these will turn out to be ncRNAs, because the majority of the FANTOM cDNA library is based on ncRNAs. The discovery of the HARs, and the expression of HAR-1 in Cajal Retzius cells [30] indicates that human neurons express nonconserved ncRNAs in highly cell-specific patterns. ncRNAs’ unique, flexible computational features could thus provide adaptable, information-dense building blocks for implementing the ambitious genetic blueprints of neural tissues. Their participation in one such complex is discussed below. Spatial, temporal, and activity-dependent maps of mRNAs in neural microregions A neuron’s ability to articulate heterogeneous landscapes of mRNAs across different microregions, and then to modulate them in an activity-dependant manner, provides a potentially powerful tool for use in higher brain functions. Below, we define the concept of a ‘‘digital reservoir’’ and suggest how regions of ncRNA sequence could provide the computational mechanisms necessary for its function. Dendritic spines, synaptic boutons, and surrounding regions contain hundreds of mRNA transcripts ready for www.sciencedirect.com

Vol.30 No.12

activity-dependent translation [72]. These transcripts exist in the form of combinatorially defined RNPs [73], which accumulate within a system of associated organelles including P bodies and stress granules. Functionally diverse proteins such as Fragile X mental retardation protein (FMRP), cytoplasmic polyadenylation elementbinding protein (CPEB), and members of the Argonaute (Ago) family dynamically associate with these organelles. CPEB [73–77], for example, localizes to the postsynaptic density (PSD) and functions in conjunction with miRNAs and the RISC complex [78–80] to regulate the translation of synapse-specific mRNAs, A variety of different stresses appear to trigger specific responses from these RNP organelles, such as the sequestration and translational inhibition of specific transcripts, or their release from within these organelles for immediate translation. For example, Battacharya and colleagues [81] have shown that stress signals quickly release CAT mRNA from P Body storage for immediate active translation. Likewise, exposure of neurons to BDNF releases Limk1 mRNA from P-body-localized translation inhibition [82]. Synaptic activity itself plays a role, including the induction of proteosomal degradation of RISC component Armitage, resulting in derepression of a subset of transcripts required for the formation of long-term memory [83]. Because these organelles and their associated RNPs are enriched in neuronally important digital information (mRNA-coding regions), subject to dynamic two way regulation, we call them digital information reservoirs. Digital reservoirs might be controlled by analog information in regions of ncRNA sequence. A growing list of ncRNAs, including the miRNA-RISC complex [84] and members of the dendritically localized BC1/BC200 family [85], interact with digital reservoirs. BC1 RNA was shown to negatively regulate dopamine D2 receptor-mediated synaptic transmission in the striatum, probably by derepressing the translation of an mRNA specifying a membrane protein that interacts with and downregulates the D2 receptor [86]. Interestingly, this work establishes the potential for feedback loops between synaptic activity and translational regulation by digital reservoirs. Another example is provided by the recent discovery of a ‘‘rapidly evolving’’ (hominid specific) family of small ncRNAs that bind an RNA-shuttling protein called Nuclear Factor 90 (NF90) in vivo [87]. NF90 is required for the correct axonal localization of tau mRNA [88], and whereas the physiological function of these ncRNAs remains unknown, their knockdown might interfere with the dynamics of tau mRNA localization to neuronal digital reservoirs. The noncoding untranslated regions (UTRs) of neuronally expressed mRNA transcripts also play a crucial role in digital information reservoirs [55,89–92]. Different classes of mRNAs cluster into subgroups according to common motifs in their secondary structure, thus defining their recognition under different conditions and stresses by the digital-reservoirbased machinery. In the proposed model, the digital reservoir surveys the analog information content of its associated RNPs, as well as its immediate microregion, then processes that information content to output a range of complex logistics for subsets of its associated mRNA species. The associated

Opinion

TRENDS in Neurosciences

RNPs might contain heterogeneous interaction topologies as a result of temporal, spatial, and activity variation during their formation [93]. Such accumulated conformational complexity of RNA-protein interactions [73] could constitute a kind of molecular information ‘‘memory state’’ that would be recognized later by neuronal machinery. Furthermore, as shown above in the BC1 RNA–DR2 example, digital reservoirs can participate in complex feedback loops, which could facilitate higher neuronal functions. Coupling the analog information flows of the neuronal environment to precise transcript recruitment from digital reservoirs enables an advantageous analog-digital interplay. Intriguing features of the resulting computational system include feedback loops, high-resolution control of local translation, and macromolecular memory states. In effect, digital reservoirs are computationally sophisticated clearing houses [94] that probably participate in neuronal processes such as long-term potentiation (LTP), and longterm depression (LTD). ncRNA could thus conceivably contribute to functional heterogeneity in LTP and/or LTD. Conclusions The computational language of ncRNA requires a new conceptual paradigm: multiple layers of well-ordered integration between environmental inputs and the analog and digital components of RNA-protein interactions. The computational complexity of ncRNAs, including their secondary structure, their varied and flexible protein-binding characteristics, and their participation in tunable feedback mechanisms such as ADAR editing and digital reservoirs, increase the information capacity of protein interaction networks, possibly well beyond current estimates. In a neuroscience context, spatial, temporal, and activity-dependent signaling rely on analog mechanisms. ncRNAs are uniquely suited to couple these information flows to the digital information reservoirs that drive localized gene expression. In sum, we propose that ncRNAs contribute to the success of the organism’s information processing in several ways. First, they allow a more efficient coupling of energy to information, wherein less energy is required to represent and process more information. Condensed in analog and digital form, and into smaller spatial and temporal domains, such an information medium is ideal for the environments found in neural tissues because of their flexibility and information density. Second, they permit the rapid acquisition of information from the environment, along with the processing and elimination of that information when it is no longer necessary. Third, they appear to facilitate accelerated evolution of an organism’s information content and functional computational systems. The molecular computing system of RNA-protein interactions is a result of fine-grained information encoded and accumulated over evolutionary time. This emerging panorama potentially opens entirely new dimensions of information processing in the brain. Acknowledgements The authors would like to thank Ajit Kumar, Siva Balasubramanian, and Mohammad Ali Faghihi for helpful comments on the text, and Mark Mazaitis for assistance with the graphics work. www.sciencedirect.com

Vol.30 No.12

619

References 1 Venter, J.C. et al. (2001) The sequence of the human genome. Science 291, 1304–1351 2 Lander, E.S. et al. (2001) Initial sequencing and analysis of the human genome. Nature 409, 860–921 3 Taft, R.J. et al. (2007) The relationship between non-protein-coding DNA and eukaryotic complexity. Bioessays 29, 288–299 4 Mehler, M.F. and Mattick, J.S. (2006) Non-coding RNAs in the nervous system. J. Physiol. 575, 333–341 5 Mattick, J.S. (2001) Non-coding RNAs: the architects of eukaryotic complexity. EMBO Rep. 2, 986–991 6 Herbert, A. and Rich, A. (1999) RNA processing in evolution. The logic of soft-wired genomes. Ann. N. Y. Acad. Sci. 870, 119–132 7 Herbert, A. and Rich, A. (1999) RNA processing and the evolution of eukaryotes. Nat. Genet. 21, 265–269 8 Frith, M.C. et al. (2006) Discrimination of non-protein-coding transcripts from protein-coding mRNA. RNA Biol. 3, 40–48 9 Hayashizaki, Y. and Carninci, P. (2006) Genome Network and FANTOM3: assessing the complexity of the transcriptome. PLoS Genet. 2, e63 10 Katayama, S. et al. (2005) Antisense transcription in the mammalian transcriptome. Science 309, 1564–1566 11 Carninci, P. et al. (2005) The transcriptional landscape of the mammalian genome. Science 309, 1559–1563 12 Carninci, P. and Hayashizaki, Y. (2007) Noncoding RNA transcription beyond annotated genes. Curr. Opin. Genet. Dev. 17, 139–144 13 Cheng, J. et al. (2005) Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 308, 1149–1154 14 Manak, J.R. et al. (2006) Biological function of unannotated transcription during the early development of Drosophila melanogaster. Nat. Genet. 38, 1151–1158 15 Willingham, A.T. and Gingeras, T.R. (2006) TUF love for ‘‘junk’’ DNA. Cell 125, 1215–1220 16 Kapranov, P. et al. (2007) RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science 316, 1484–1488 17 ENCODE Project Consortium et al. (2007) Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447, 799–816 18 Grishok, A. et al. (2001) Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C. elegans developmental timing. Cell 106, 23–34 19 Lee, R.C. et al. (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75, 843– 854 20 Rigoutsos, I. et al. (2006) Short blocks from the noncoding parts of the human genome have instances within nearly all known genes and relate to biological processes. Proc. Natl. Acad. Sci. U. S. A. 103, 6605– 6610 21 Miranda, K.C. et al. (2006) A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes. Cell 126, 1203–1217 22 Griffiths-Jones, S. et al. (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 34, D140–D144 23 Shahi, P. et al. (2006) Argonaute–a database for gene regulation by mammalian microRNAs. Nucleic Acids Res. 34, D115–D118 24 Pang, K.C. et al. (2007) RNAdb 2.0–an expanded database of mammalian non-coding RNAs. Nucleic Acids Res. 35, D178–D182 25 Griffiths-Jones, S. et al. (2005) Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 33, D121–D124 26 Liu, C. et al. (2005) NONCODE: an integrated knowledge database of non-coding RNAs. Nucleic Acids Res. 33, D112–D115 27 Xie, J. et al. (2007) Sno/scaRNAbase: a curated database for small nucleolar RNAs and cajal body-specific RNAs. Nucleic Acids Res. 35, D183–D187 28 Huang, H.Y. et al. (2006) RegRNA: an integrated web server for identifying regulatory RNA motifs and elements. Nucleic Acids Res. 34, W429–W434 29 Pang, K.C. et al. (2006) Rapid evolution of noncoding RNAs: lack of conservation does not mean lack of function. Trends Genet. 22, 1–5 30 Pollard, K.S. et al. (2006) An RNA gene expressed during cortical development evolved rapidly in humans. Nature 443, 167–172 31 Berezikov, E. et al. (2006) Diversity of microRNAs in human and chimpanzee brain. Nat. Genet. 38, 1375–1377

620

Opinion

TRENDS in Neurosciences

32 Mattick, J.S. (2007) A new paradigm for developmental biology. J. Exp. Biol. 210, 1526–1547 33 Gagen, M.J. and Mattick, J.S. (2005) Accelerating, hyperaccelerating, and decelerating networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 72, 016123 34 Mattick, J.S. and Gagen, M.J. (2001) The evolution of controlled multitasked gene networks: the role of introns and other noncoding RNAs in the development of complex organisms. Mol. Biol. Evol. 18, 1611–1630 35 Mattick, J.S. (2004) RNA regulation: a new genetics? Nat. Rev. Genet. 5, 316–323 36 Sempere, L.F. et al. (2006) The phylogenetic distribution of metazoan microRNAs: insights into evolutionary complexity and constraint. J. Exp. Zoolog. B Mol. Dev. Evol. 306, 575–588 37 Salehi-Ashtiani, K. et al. (2006) A genomewide search for ribozymes reveals an HDV-like sequence in the human CPEB3 gene. Science 313, 1788–1792 38 Iwazaki, T. et al. (2005) Evolvability of the mode of peptide binding by an RNA. RNA 11, 1364–1373 39 Martianov, I. et al. (2007) Repression of the human dihydrofolate reductase gene by a non-coding interfering transcript. Nature 445, 666–670 40 Feng, J. et al. (2006) The Evf-2 noncoding RNA is transcribed from the Dlx-5/6 ultraconserved region and functions as a Dlx-2 transcriptional coactivator. Genes Dev. 20, 1470–1484 41 Wahlestedt, C. (2006) Natural antisense and noncoding RNA transcripts as potential drug targets. Drug Discov. Today 11, 503–508 42 Engstrom, P.G. et al. (2006) Complex loci in human and mouse genomes. PLoS Genet 2, e47 43 Scheele, C. et al. (2007) The human PINK1 locus is regulated in vivo by a non-coding natural antisense RNA during modulation of mitochondrial function. BMC Genomics 8, 74 44 Nguyen, V.T. et al. (2001) 7SK small nuclear RNA binds to and inhibits the activity of CDK9/cyclin T complexes. Nature 414, 322–325 45 Yik, J.H. et al. (2003) Inhibition of P-TEFb (CDK9/Cyclin T) kinase and RNA polymerase II transcription by the coordinated actions of HEXIM1 and 7SK snRNA. Mol. Cell 12, 971–982 46 Espinoza, C.A. et al. (2004) B2 RNA binds directly to RNA polymerase II to repress transcript synthesis. Nat. Struct. Mol. Biol. 11, 822–829 47 Espinoza, C.A. et al. (2007) Characterization of the structure, function, and mechanism of B2 RNA, an ncRNA repressor of RNA polymerase II transcription. RNA 13, 583–596 48 Goodrich, J.A. and Kugel, J.F. (2006) Non-coding-RNA regulators of RNA polymerase II transcription. Nat. Rev. Mol. Cell Biol. 7, 612–616 49 Kuwabara, T. et al. (2004) A small modulatory dsRNA specifies the fate of adult neural stem cells. Cell 116, 779–793 50 Chen, B.E. et al. (2006) The molecular diversity of Dscam is functionally required for neuronal wiring specificity in Drosophila. Cell 125, 607–620 51 Cavaille, J. et al. (2000) Identification of brain-specific and imprinted small nucleolar RNA genes exhibiting an unusual genomic organization. Proc. Natl. Acad. Sci. U. S. A. 97, 14311–14316 52 Kishore, S. and Stamm, S. (2006) The snoRNA HBII-52 regulates alternative splicing of the serotonin receptor 2C. Science 311, 230–232 53 Hadley, D. et al. (2006) Patterns of sequence conservation in presynaptic neural genes. Genome Biol. 7, R105 54 Cheah, M.T. et al. (2007) Control of alternative RNA splicing and gene expression by eukaryotic riboswitches. Nature 447, 497–500 55 Kosik, K.S. (2006) The neuronal microRNA system. Nat. Rev. Neurosci. 7, 911–920 56 Nilsen, T.W. (2007) Mechanisms of microRNA-mediated gene regulation in animal cells. Trends Genet. 23, 243–249 57 Rinn, J.L. et al. (2007) Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129, 1311–1323 58 Harada, K. et al. (2003) The variability of the peptide-binding specificity of RNA. Nucleic Acids Res. (Suppl), 201–202 59 Shabalina, S.A. et al. (2006) A periodic pattern of mRNA secondary structure created by the genetic code. Nucleic Acids Res. 34, 2428– 2437 60 Shabalina, S.A. et al. (2004) Comparative analysis of orthologous eukaryotic mRNAs: potential hidden functional signals. Nucleic Acids Res. 32, 1774–1782 www.sciencedirect.com

Vol.30 No.12

61 Nackley, A.G. et al. (2006) Human catechol-O-methyltransferase haplotypes modulate protein expression by altering mRNA secondary structure. Science 314, 1930–1933 62 Chen, H. and Blanchette, M. (2007) Detecting non-coding selective pressure in coding regions. BMC Evol. Biol. 7 (Suppl 1), S9 63 Meyer, I.M. and Miklos, I. (2005) Statistical evidence for conserved, local secondary structure in the coding regions of eukaryotic mRNAs and pre-mRNAs. Nucleic Acids Res. 33, 6338–6348 64 Leulliot, N. and Varani, G. (2001) Current topics in RNA-protein recognition: control of specificity and biological function through induced fit and conformational capture. Biochemistry 40, 7947–7956 65 Shamovsky, I. et al. (2006) RNA-mediated response to heat shock in mammalian cells. Nature 440, 556–560 66 Seeburg, P.H. (2002) A-to-I editing: new and old sites, functions and speculations. Neuron 35, 17–20 67 Eisenberg, E. et al. (2005) Is abundant A-to-I RNA editing primatespecific? Trends Genet. 21, 77–81 68 Gurevich, I. et al. (2002) Altered editing of serotonin 2C receptor premRNA in the prefrontal cortex of depressed suicide victims. Neuron 34, 349–356 69 Hoopengardner, B. et al. (2003) Nervous system targets of RNA editing identified by comparative genomics. Science 301, 832–836 70 Cao, X. et al. (2006) Noncoding RNAs in the mammalian central nervous system. Annu. Rev. Neurosci. 29, 77–103 71 Fairbanks, D.J. and Maughan, P.J. (2006) Evolution of the NANOG pseudogene family in the human and chimpanzee genomes. BMC Evol. Biol. 6, 12 72 Poon, M.M. et al. (2006) Identification of process-localized mRNAs from cultured rodent hippocampal neurons. J. Neurosci. 26, 13390– 13399 73 Hieronymus, H. and Silver, P.A. (2004) A systems view of mRNP biology. Genes Dev. 18, 2845–2860 74 Cao, Q. et al. (2005) Amyloid precursor proteins anchor CPEB to membranes and promote polyadenylation-induced translation. Mol. Cell. Biol. 25, 10930–10939 75 Hake, L.E. et al. (1998) Specificity of RNA binding by CPEB: requirement for RNA recognition motifs and a novel zinc finger. Mol. Cell. Biol. 18, 685–693 76 Huang, Y.S. et al. (2003) Facilitation of dendritic mRNA transport by CPEB. Genes Dev. 17, 638–653 77 Huang, Y.S. et al. (2006) CPEB3 and CPEB4 in neurons: analysis of RNA-binding specificity and translational control of AMPA receptor GluR2 mRNA. EMBO J. 25, 4865–4876 78 Richter, J.D. (2007) CPEB: a life in translation. Trends Biochem. Sci. 32, 279–285 79 Wilczynska, A. et al. (2005) The translational regulator CPEB1 provides a link between dcp1 bodies and stress granules. J. Cell Sci. 118, 981–992 80 Huang, Y.S. and Richter, J.D. (2004) Regulation of local mRNA translation. Curr. Opin. Cell Biol. 16, 308–313 81 Bhattacharyya, S.N. et al. (2006) Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell 125, 1111–1124 82 Schratt, G.M. et al. (2006) A brain-specific microRNA regulates dendritic spine development. Nature 439, 283–289 83 Ashraf, S.I. et al. (2006) Synaptic protein synthesis associated with memory is regulated by the RISC pathway in Drosophila. Cell 124, 191–205 84 Ashraf, S.I. and Kunes, S. (2006) A trace of silence: memory and microRNA at the synapse. Curr. Opin. Neurobiol. 16, 535–539 85 Zalfa, F. et al. (2003) The fragile X syndrome protein FMRP associates with BC1 RNA and regulates the translation of specific mRNAs at synapses. Cell 112, 317–327 86 Centonze, D. et al. (2007) The brain cytoplasmic RNA BC1 regulates dopamine D2 receptor-mediated transmission in the striatum. J. Neurosci. 27, 8885–8892 87 Parrott, A.M. and Mathews, M.B. (2007) Novel rapidly evolving hominid RNAs bind nuclear factor 90 and display tissue-restricted distribution. Nucleic Acids Res. DOI: 10.1093/nar/gkm668 88 Larcher, J.C. et al. (2004) Ilf3 and NF90 associate with the axonal targeting element of Tau mRNA. FASEB J. 18, 1761–1763 89 Pillai, R.S. (2005) MicroRNA function: multiple mechanisms for a tiny RNA? RNA 11, 1753–1761

Opinion

TRENDS in Neurosciences

90 Liu, J. et al. (2005) A role for the P-body component GW182 in microRNA function. Nat. Cell Biol. 7, 1261–1266 91 Kosik, K.S. and Krichevsky, A.M. (2005) The elegance of the microRNAs: a neuronal perspective. Neuron 47, 779–782 92 Chu, C.Y. and Rana, T.M. (2006) Translation repression in human cells by microRNA-induced gene silencing requires RCK/p54. PLoS Biol. 4, e210 93 Barbee, S.A. et al. (2006) Staufen- and FMRP-containing neuronal RNPs are structurally and functionally related to somatic P bodies. Neuron 52, 997–1009 94 Parker, R. and Sheth, U. (2007) P bodies and the control of mRNA translation and degradation. Mol. Cell 25, 635–646 95 Vu, T.H. et al. (2006) Cross-species clues of an epigenetic imprinting regulatory code for the IGF2R gene. Cytogenet. Genome Res. 113, 202– 208 96 Mitsuya, K. et al. (1999) LIT1, an imprinted antisense RNA in the human KvLQT1 locus identified by screening for differentially expressed transcripts using monochromosomal hybrids. Hum. Mol. Genet. 8, 1209–1211 97 Seidl, C.I. et al. (2006) The imprinted Air ncRNA is an atypical RNAPII transcript that evades splicing and escapes nuclear export. EMBO J. 25, 3565–3575 98 Buhler, M. et al. (2006) Tethering RITS to a nascent transcript initiates RNAi- and heterochromatin-dependent gene silencing. Cell 125, 873–886

Vol.30 No.12

621

99 de Napoles, M. et al. (2007) Early loss of xist RNA expression and inactive x chromosome associated chromatin modification in developing primordial germ cells. PLoS ONE 2, e860 100 Kuwabara, T. et al. (2005) The NRSE smRNA specifies the fate of adult hippocampal neural stem cells. Nucleic Acids Symp. Ser. (Oxf) 87–88 101 Leygue, E. (2007) Steroid receptor RNA activator (SRA1): unusual bifaceted gene products with suspected relevance to breast cancer. Nucl. Recept. Signal 5, e006 102 Prasanth, K.V. et al. (2005) Regulating gene expression through RNA nuclear retention. Cell 123, 249–263 103 Farris, V. et al. (2005) Alternative splicing of human insulindegrading enzyme yields a novel isoform with a decreased ability to degrade insulin and amyloid beta-protein. Biochemistry 44, 6513– 6525 104 Dang, D.T. et al. (2006) Hypoxia-inducible factor-1a promotes nonhypoxia-mediated proliferation in colon cancer cells and xenografts. Cancer Res. 66, 1684–1936 105 Hatzoglou, A. et al. (2002) Natural antisense RNA inhibits the expression of BCMA, a tumour necrosis factor receptor homologue. BMC Mol. Biol. 3, 4 106 Willingham, A.T. et al. (2005) A strategy for probing the function of noncoding RNAs finds a repressor of NFAT. Science 309, 1570– 1573

Endeavour The quarterly magazine for the history and philosophy of science. You can access Endeavour online on ScienceDirect, where you’ll find book reviews, editorial comment and a collection of beautifully illustrated articles on the history of science. Featuring: Information revolution: William Chambers, the publishing pioneer by A. Fyfe Does history count? by K. Anderson Waking up to shell shock: psychiatry in the US military during World War II by H. Pols Deserts on the sea floor: Edward Forbes and his azoic hypothesis for a lifeless deep ocean by T.R. Anderson and T. Rice ‘Higher, always higher’: technology, the military and aviation medicine during the age of the two world wars by C. Kehrt Bully for Apatosaurus by P. Brinkman Coming soon: Environmentalism out of the Industrial Revolution by C. Macleod Pandemic in print: the spread of influenza in the Fin de Sie`cle by J. Mussell Earthquake theories in the early modern period by F. Willmoth Science in fiction - attempts to make a science out of literary criticism by J. Adams The birth of botanical Drosophila by S. Leonelli And much, much more. . .

Endeavour is available on ScienceDirect, www.sciencedirect.com www.sciencedirect.com