Compact and ordered collapse of randomly generated RNA sequences

Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Observation of coordinated RNA folding events by systematic cotranscriptional RNA structure probing

RNA begins to fold as it is transcribed by an RNA polymerase. Consequently, RNA folding is constrained by the direction and rate of transcription. Understanding how RNA folds into secondary and tertiary structures therefore requires methods for determining the structure of cotranscriptional folding intermediates. Cotranscriptional RNA chemical probing methods accomplish this by systematically probing the structure of nascent RNA that is displayed from an RNA polymerase. Here, we describe a concise, high-resolution cotranscriptional RNA chemical probing procedure called variable length Transcription Elongation Complex RNA structure probing (TECprobe-VL). We demonstrate the accuracy and resolution of TECprobe-VL by replicating and extending previous analyses of ZTP and fluoride riboswitch folding and mapping the folding pathway of a ppGpp-sensing riboswitch. In each system, we show that TECprobe-VL identifies coordinated cotranscriptional folding events that mediate transcription antitermination. Our findings establish TECprobe-VL as an accessible method for mapping cotranscriptional RNA folding pathways.

Modeling the 3D structure and conformational dynamics of very large RNAs using coarse-grained molecular simulations

We describe a computational approach to building and simulating realistic 3D models of very large RNA molecules (>1000 nucleotides) at a resolution of one "bead" per nucleotide. The method starts with a predicted secondary structure and uses several stages of energy minimization and Brownian dynamics (BD) simulation to build 3D models. A key step in the protocol is the temporary addition of a 4 ^th spatial dimension that allows all predicted helical elements to become disentangled from each other in an effectively automated way. We then use the resulting 3D models as input to Brownian dynamics simulations that include hydrodynamic interactions (HIs) that allow the diffusive properties of the RNA to be modelled as well as enabling its conformational dynamics to be simulated. To validate the dynamics part of the method, we first show that when applied to small RNAs with known 3D structures the BD-HI simulation models accurately reproduce their experimental hydrodynamic radii (Rh). We then apply the modelling and simulation protocol to a variety of RNAs for which experimental Rh values have been reported ranging in size from 85 to 3569 nucleotides. We show that the 3D models, when used in BD-HI simulations, produce hydrodynamic radii that are usually in good agreement with experimental estimates for RNAs that do not contain tertiary contacts that persist even under very low salt conditions. Finally, we show that sampling of the conformational dynamics of large RNAs on timescales of 100 µs is computationally feasible with BD-HI simulations.

Predicting phenotype transition probabilities via conditional algorithmic probability approximations

Unravelling the structure of genotype-phenotype (GP) maps is an important problem in biology. Recently, arguments inspired by algorithmic information theory (AIT) and Kolmogorov complexity have been invoked to uncover simplicity bias in GP maps, an exponentially decaying upper bound in phenotype probability with the increasing phenotype descriptional complexity. This means that phenotypes with many genotypes assigned via the GP map must be simple, while complex phenotypes must have few genotypes assigned. Here, we use similar arguments to bound the probability P(x → y) that phenotype x, upon random genetic mutation, transitions to phenotype y. The bound is [Formula: see text], where [Formula: see text] is the estimated conditional complexity of y given x, quantifying how much extra information is required to make y given access to x. This upper bound is related to the conditional form of algorithmic probability from AIT. We demonstrate the practical applicability of our derived bound by predicting phenotype transition probabilities (and other related quantities) in simulations of RNA and protein secondary structures. Our work contributes to a general mathematical understanding of GP maps and may facilitate the prediction of transition probabilities directly from examining phenotype themselves, without utilizing detailed knowledge of the GP map.

Discovering functional motifs in long noncoding RNAs

Long noncoding RNAs (lncRNAs) are products of pervasive transcription that closely resemble messenger RNAs on the molecular level, yet function through largely unknown modes of action. The current model is that the function of lncRNAs often relies on specific, typically short, conserved elements, connected by linkers in which specific sequences and/or structures are less important. This notion has fueled the development of both computational and experimental methods focused on the discovery of functional elements within lncRNA genes, based on diverse signals such as evolutionary conservation, predicted structural elements, or the ability to rescue loss-of-function phenotypes. In this review, we outline the main challenges that the different methods need to overcome, describe the recently developed approaches, and discuss their respective limitations. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Thoughts on how to think (and talk) about RNA structure

Recent events have pushed RNA research into the spotlight. Continued discoveries of RNA with unexpected diverse functions in healthy and diseased cells, such as the role of RNA as both the source and countermeasure to a severe acute respiratory syndrome coronavirus 2 infection, are igniting a new passion for understanding this functionally and structurally versatile molecule. Although RNA structure is key to function, many foundational characteristics of RNA structure are misunderstood, and the default state of RNA is often thought of and depicted as a single floppy strand. The purpose of this perspective is to help adjust mental models, equipping the community to better use the fundamental aspects of RNA structural information in new mechanistic models, enhance experimental design to test these models, and refine data interpretation. We discuss six core observations focused on the inherent nature of RNA structure and how to incorporate these characteristics to better understand RNA structure. We also offer some ideas for future efforts to make validated RNA structural information available and readily used by all researchers.

A roadmap for rRNA folding and assembly during transcription

Ribonucleoprotein (RNP) assembly typically begins during transcription when folding of the newly synthesized RNA is coupled with the recruitment of RNA-binding proteins (RBPs). Upon binding, the proteins induce structural rearrangements in the RNA that are crucial for the next steps of assembly. Focusing primarily on bacterial ribosome assembly, we discuss recent work showing that early RNA-protein interactions are more dynamic than previously supposed, and remain so, until sufficient proteins are recruited to each transcript to consolidate an entire domain of the RNP. We also review studies showing that stable assembly of an RNP competes against modification and processing of the RNA. Finally, we discuss how transcription sets the timeline for competing and cooperative RNA-RBP interactions that determine the fate of the nascent RNA. How this dance is coordinated is the focus of this review.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Large Phenotypic Enhancement of Structured Random RNA Pools

Laboratory evolution of functional RNAs has applications in many areas of chemical and synthetic biology. In vitro selections critically depend on the presence of functional molecules, such as aptamers and ribozymes, in the starting sequence pools. For selection of novel functions the pools are typically transcribed from random-sequence DNA templates, yielding a highly diverse set of RNAs that contain a multitude of folds and biochemical activities. The phenotypic potential, the frequency of functional RNAs, is very low, requiring large complexity of starting pools, surpassing 10¹⁵ different sequences, to identify highly active isolates. Furthermore, the majority of random sequences is not structured and has a high propensity for aggregation; the in vitro selection process thus involves not just enrichment of functional RNAs, but also their purification from aggregation-prone "free-riders". We reasoned that purification of the nonaggregating, monomeric subpopulation of a random-sequence RNA pool will yield pools of folded, functional RNAs. We performed six rounds of selection for monomeric sequences and show that the enriched population is compactly folded. In vitro selections originating from various mixtures of the compact pool and a fully random pool showed that sequences from the compact pool always dominate the population once a biochemical activity is detectable. A head-to-head competition of the two pools starting from a low (5 × 10¹²) sequence diversity revealed that the phenotypic potential of the compact pool is about 1000-times higher than the fully random pool. A selection for folded and monomeric RNA pools thus greatly increases the frequency of functional RNAs from that seen in random-sequence pools, providing a facile experimental approach to isolation of highly active functional RNAs from low-diversity populations.

On the emergence of structural complexity in RNA replicators

The RNA world hypothesis relies on the ability of ribonucleic acids to spontaneously acquire complex structures capable of supporting essential biological functions. Multiple sophisticated evolutionary models have been proposed for their emergence, but they often assume specific conditions. In this work, we explore a simple and parsimonious scenario describing the emergence of complex molecular structures at the early stages of life. We show that at specific GC content regimes, an undirected replication model is sufficient to explain the apparition of multibranched RNA secondary structures-a structural signature of many essential ribozymes. We ran a large-scale computational study to map energetically stable structures on complete mutational networks of 50-nt-long RNA sequences. Our results reveal that the sequence landscape with stable structures is enriched with multibranched structures at a length scale coinciding with the appearance of complex structures in RNA databases. A random replication mechanism preserving a 50% GC content may suffice to explain a natural enrichment of stable complex structures in populations of functional RNAs. In contrast, an evolutionary mechanism eliciting the most stable folds at each generation appears to help reaching multibranched structures at highest GC content.

Identification and characterization of novel conserved RNA structures in Drosophila

BACKGROUND

Comparative genomics approaches have facilitated the discovery of many novel non-coding and structured RNAs (ncRNAs). The increasing availability of related genomes now makes it possible to systematically search for compensatory base changes - and thus for conserved secondary structures - even in genomic regions that are poorly alignable in the primary sequence. The wealth of available transcriptome data can add valuable insight into expression and possible function for new ncRNA candidates. Earlier work identifying ncRNAs in Drosophila melanogaster made use of sequence-based alignments and employed a sliding window approach, inevitably biasing identification toward RNAs encoded in the more conserved parts of the genome.

RESULTS

To search for conserved RNA structures (CRSs) that may not be highly conserved in sequence and to assess the expression of CRSs, we conducted a genome-wide structural alignment screen of 27 insect genomes including D. melanogaster and integrated this with an extensive set of tiling array data. The structural alignment screen revealed ∼30,000 novel candidate CRSs at an estimated false discovery rate of less than 10%. With more than one quarter of all individual CRS motifs showing sequence identities below 60%, the predicted CRSs largely complement the findings of sliding window approaches applied previously. While a sixth of the CRSs were ubiquitously expressed, we found that most were expressed in specific developmental stages or cell lines. Notably, most statistically significant enrichment of CRSs were observed in pupae, mainly in exons of untranslated regions, promotors, enhancers, and long ncRNAs. Interestingly, cell lines were found to express a different set of CRSs than were found in vivo. Only a small fraction of intergenic CRSs were co-expressed with the adjacent protein coding genes, which suggests that most intergenic CRSs are independent genetic units.

CONCLUSIONS

This study provides a more comprehensive view of the ncRNA transcriptome in fly as well as evidence for differential expression of CRSs during development and in cell lines.

Regulation by 3'-Untranslated Regions

3'-untranslated regions (3'-UTRs) are the noncoding parts of mRNAs. Compared to yeast, in humans, median 3'-UTR length has expanded approximately tenfold alongside an increased generation of alternative 3'-UTR isoforms. In contrast, the number of coding genes, as well as coding region length, has remained similar. This suggests an important role for 3'-UTRs in the biology of higher organisms. 3'-UTRs are best known to regulate diverse fates of mRNAs, including degradation, translation, and localization, but they can also function like long noncoding or small RNAs, as has been shown for whole 3'-UTRs as well as for cleaved fragments. Furthermore, 3'-UTRs determine the fate of proteins through the regulation of protein-protein interactions. They facilitate cotranslational protein complex formation, which establishes a role for 3'-UTRs as evolved eukaryotic operons. Whereas bacterial operons promote the interaction of two subunits, 3'-UTRs enable the formation of protein complexes with diverse compositions. All of these 3'-UTR functions are accomplished by effector proteins that are recruited by RNA-binding proteins that bind to 3'-UTR cis-elements. In summary, 3'-UTRs seem to be major players in gene regulation that enable local functions, compartmentalization, and cooperativity, which makes them important tools for the regulation of phenotypic diversity of higher organisms.

Intrinsic Base-Pair Rearrangement in the Hairpin Ribozyme Directs RNA Conformational Sampling and Tertiary Interface Formation

Dynamic fluctuations in RNA structure enable conformational changes that are required for catalysis and recognition. In the hairpin ribozyme, the catalytically active structure is formed as an intricate tertiary interface between two RNA internal loops. Substantial alterations in the structure of each loop are observed upon interface formation, or docking. The very slow on-rate for this relatively tight interaction has led us to hypothesize a double conformational capture mechanism for RNA-RNA recognition. We used extensive molecular dynamics simulations to assess conformational sampling in the undocked form of the loop domain containing the scissile phosphate (loop A). We observed several major accessible conformations with distinctive patterns of hydrogen bonding and base stacking interactions in the active-site internal loop. Several important conformational features characteristic of the docked state were observed in well-populated substates, consistent with the kinetic sampling of docking-competent states by isolated loop A. Our observations suggest a hybrid or multistage binding mechanism, in which initial conformational selection of a docking-competent state is followed by induced-fit adjustment to an in-line, chemically reactive state only after formation of the initial complex with loop B.

Long non-coding RNAs in human early embryonic development and their potential in ART

BACKGROUND

Human long non-coding RNAs (lncRNAs) are an emerging category of transcripts with increasingly documented functional roles during development. LncRNAs and roles during human early embryo development have recently begun to be unravelled.

OBJECTIVE AND RATIONALE

This review summarizes the most recent knowledge on lncRNAs and focuses on their expression patterns and role during early human embryo development and in pluripotent stem cells (PSCs). Public mRNA sequencing (mRNA-seq) data were used to illustrate these expression signatures.

SEARCH METHODS

The PubMed and EMBASE databases were first interrogated using specific terms, such as 'lncRNAs', to get an extensive overview on lncRNAs up to February 2016, and then using 'human lncRNAs' and 'embryo', 'development', or 'PSCs' to focus on lncRNAs involved in human embryo development or in PSC.Recently published RNA-seq data from human oocytes and pre-implantation embryos (including single-cell data), PSC and a panel of normal and malignant adult tissues were used to describe the specific expression patterns of some lncRNAs in early human embryos.

OUTCOMES

The existence and the crucial role of lncRNAs in many important biological phenomena in each branch of the life tree are now well documented. The number of identified lncRNAs is rapidly increasing and has already outnumbered that of protein-coding genes. Unlike small non-coding RNAs, a variety of mechanisms of action have been proposed for lncRNAs. The functional role of lncRNAs has been demonstrated in many biological and developmental processes, including cell pluripotency induction, X-inactivation or gene imprinting. Analysis of RNA-seq data highlights that lncRNA abundance changes significantly during human early embryonic development. This suggests that lncRNAs could represent candidate biomarkers for developing non-invasive tests for oocyte or embryo quality. Finally, some of these lncRNAs are also expressed in human cancer tissues, suggesting that reactivation of an embryonic lncRNA program may contribute to human malignancies.

WIDER IMPLICATIONS

LncRNAs are emerging potential key players in gene expression regulation. Analysis of RNA-seq data from human pre-implantation embryos identified lncRNA signatures that are specific to this critical step. We anticipate that further studies will show that these new transcripts are major regulators of embryo development. These findings might also be used to develop new tests/treatments for improving the pregnancy success rate in IVF procedures or for regenerative medicine applications involving PSC.

Evolutionary clues in lncRNAs

The diversity of long non-coding RNAs (lncRNAs) in the human transcriptome is in stark contrast to the sparse exploration of their functions concomitant with their conservation and evolution. The pervasive transcription of the largely non-coding human genome makes the evolutionary age and conservation patterns of lncRNAs to a topic of interest. Yet it is a fairly unexplored field and not that easy to determine as for protein-coding genes. Although there are a few experimentally studied cases, which are conserved at the sequence level, most lncRNAs exhibit weak or untraceable primary sequence conservation. Recent studies shed light on the interspecies conservation of secondary structures among lncRNA homologs by using diverse computational methods. This highlights the importance of structure on functionality of lncRNAs as opposed to the poor impact of primary sequence changes. Further clues in the evolution of lncRNAs are given by selective constraints on non-coding gene structures (e.g., promoters or splice sites) as well as the conservation of prevalent spatio-temporal expression patterns. However, a rapid evolutionary turnover is observable throughout the heterogeneous group of lncRNAs. This still gives rise to questions about its functional meaning. WIREs RNA 2017, 8:e1376. doi: 10.1002/wrna.1376 For further resources related to this article, please visit the WIREs website.

The structure of the genotype-phenotype map strongly constrains the evolution of non-coding RNA

The prevalence of neutral mutations implies that biological systems typically have many more genotypes than phenotypes. But, can the way that genotypes are distributed over phenotypes determine evolutionary outcomes? Answering such questions is difficult, in part because the number of genotypes can be hyper-astronomically large. By solving the genotype-phenotype (GP) map for RNA secondary structure (SS) for systems up to length L = 126 nucleotides (where the set of all possible RNA strands would weigh more than the mass of the visible universe), we show that the GP map strongly constrains the evolution of non-coding RNA (ncRNA). Simple random sampling over genotypes predicts the distribution of properties such as the mutational robustness or the number of stems per SS found in naturally occurring ncRNA with surprising accuracy. Because we ignore natural selection, this strikingly close correspondence with the mapping suggests that structures allowing for functionality are easily discovered, despite the enormous size of the genetic spaces. The mapping is extremely biased: the majority of genotypes map to an exponentially small portion of the morphospace of all biophysically possible structures. Such strong constraints provide a non-adaptive explanation for the convergent evolution of structures such as the hammerhead ribozyme. These results present a particularly clear example of bias in the arrival of variation strongly shaping evolutionary outcomes and may be relevant to Mayr's distinction between proximate and ultimate causes in evolutionary biology.

Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis

Landscapes exhibiting multiple secondary structures arise in natural RNA molecules that modulate gene expression, protein synthesis, and viral infection [corrected]. We report herein that high-throughput chemical experiments can isolate an RNA's multiple alternative secondary structures as they are stabilized by systematic mutagenesis (mutate-and-map, M2) and that a computational algorithm, REEFFIT, enables unbiased reconstruction of these states' structures and populations. In an in silico benchmark on non-coding RNAs with complex landscapes, M2-REEFFIT recovers 95% of RNA helices present with at least 25% population while maintaining a low false discovery rate (10%) and conservative error estimates. In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments. With this validation, M2-REEFFIT enabled tests of whether artificial RNA sequences might exhibit complex landscapes in the absence of explicit design. An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations. These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

Analysis of non-coding transcriptome in rice and maize uncovers roles of conserved lncRNAs associated with agriculture traits

Long non-coding RNAs (lncRNAs) have recently been found to widely exist in eukaryotes and play important roles in key biological processes. To extend our knowledge of lncRNAs in crop plants we performed both non-directional and strand-specific RNA-sequencing experiments to profile non-coding transcriptomes of various rice and maize organs at different developmental stages. Analysis of more than 3 billion reads identified 22 334 long intergenic non-coding RNAs (lincRNAs) and 6673 pairs of sense and natural antisense transcript (NAT). Many lincRNA genes were associated with epigenetic marks. Expression of rice lincRNA genes was significantly correlated with that of nearby protein-coding genes. A set of NAT genes also showed expression correlation with their sense genes. More than 200 rice lincRNA genes had homologous non-coding sequences in the maize genome. Much more lincRNA and NAT genes were derived from conserved genomic regions between the two cereals presenting positional conservation. Protein-coding genes flanking or having a sense-antisense relationship to these conserved lncRNA genes were mainly involved in development and stress responses, suggesting that the associated lncRNAs might have similar functions. Integrating previous genome-wide association studies (GWAS), we found that hundreds of lincRNAs contain trait-associated SNPs (single nucleotide polymorphisms [SNPs]) suggesting their putative contributions to developmental and agriculture traits.

Viral RNAs are unusually compact

A majority of viruses are composed of long single-stranded genomic RNA molecules encapsulated by protein shells with diameters of just a few tens of nanometers. We examine the extent to which these viral RNAs have evolved to be physically compact molecules to facilitate encapsulation. Measurements of equal-length viral, non-viral, coding and non-coding RNAs show viral RNAs to have among the smallest sizes in solution, i.e., the highest gel-electrophoretic mobilities and the smallest hydrodynamic radii. Using graph-theoretical analyses we demonstrate that their sizes correlate with the compactness of branching patterns in predicted secondary structure ensembles. The density of branching is determined by the number and relative positions of 3-helix junctions, and is highly sensitive to the presence of rare higher-order junctions with 4 or more helices. Compact branching arises from a preponderance of base pairing between nucleotides close to each other in the primary sequence. The density of branching represents a degree of freedom optimized by viral RNA genomes in response to the evolutionary pressure to be packaged reliably. Several families of viruses are analyzed to delineate the effects of capsid geometry, size and charge stabilization on the selective pressure for RNA compactness. Compact branching has important implications for RNA folding and viral assembly.

Evidence of pervasive biologically functional secondary structures within the genomes of eukaryotic single-stranded DNA viruses

Single-stranded DNA (ssDNA) viruses have genomes that are potentially capable of forming complex secondary structures through Watson-Crick base pairing between their constituent nucleotides. A few of the structural elements formed by such base pairings are, in fact, known to have important functions during the replication of many ssDNA viruses. Unknown, however, are (i) whether numerous additional ssDNA virus genomic structural elements predicted to exist by computational DNA folding methods actually exist and (ii) whether those structures that do exist have any biological relevance. We therefore computationally inferred lists of the most evolutionarily conserved structures within a diverse selection of animal- and plant-infecting ssDNA viruses drawn from the families Circoviridae, Anelloviridae, Parvoviridae, Nanoviridae, and Geminiviridae and analyzed these for evidence of natural selection favoring the maintenance of these structures. While we find evidence that is consistent with purifying selection being stronger at nucleotide sites that are predicted to be base paired than at sites predicted to be unpaired, we also find strong associations between sites that are predicted to pair with one another and site pairs that are apparently coevolving in a complementary fashion. Collectively, these results indicate that natural selection actively preserves much of the pervasive secondary structure that is evident within eukaryote-infecting ssDNA virus genomes and, therefore, that much of this structure is biologically functional. Lastly, we provide examples of various highly conserved but completely uncharacterized structural elements that likely have important functions within some of the ssDNA virus genomes analyzed here.

Kinetic Monte Carlo approach to RNA folding dynamics using structure-based models

RNA molecules form three-dimensional structures via base pairing that determine the function and biochemical activity of the molecule. Here we introduce a structure-based method for studying the folding dynamics of RNA secondary structures. The approach focuses on native contacts that are parametrized with standard empirical free energies. Kinetic Monte Carlo simulations for free folding of simple hairpins and complex structures such as a tRNA as well as for folding in the presence of an external force show good agreement with experimental data. A systematic comparison of simulated and experimental folding rates for various structures shows a strong correlation, indicating that the approach can predict folding rates within about an order of magnitude.

lincRNAs: genomics, evolution, and mechanisms

Long intervening noncoding RNAs (lincRNAs) are transcribed from thousands of loci in mammalian genomes and might play widespread roles in gene regulation and other cellular processes. This Review outlines the emerging understanding of lincRNAs in vertebrate animals, with emphases on how they are being identified and current conclusions and questions regarding their genomics, evolution and mechanisms of action.

Prediction of hammerhead ribozyme intracellular activity with the catalytic core fingerprint

Hammerhead ribozyme is a versatile tool for down-regulation of gene expression in vivo. Owing to its small size and high activity, it is used as a model for RNA structure–function relationship studies. In the present paper we describe a new extended hammerhead ribozyme HH-2 with a tertiary stabilizing motif constructed on the basis of the tetraloop receptor sequence. This ribozyme is very active in living cells, but shows low activity in vitro. To understand it, we analysed tertiary structure models of substrate–ribozyme complexes. We calculated six unique catalytic core geometry parameters as distances and angles between particular atoms that we call the ribozyme fingerprint. A flanking sequence and tertiary motif change the geometry of the general base, general acid, nucleophile and leaving group. We found almost complete correlation between these parameters and the decrease of target gene expression in the cells. The tertiary structure model calculations allow us to predict ribozyme intracellular activity. Our approach could be widely adapted to characterize catalytic properties of other RNAs.

The DNA Habitat and its RNA Inhabitants: At the Dawn of RNA Sociology

Most molecular biological concepts derive from physical chemical assumptions about the genetic code that are basically more than 40 years old. Additionally, systems biology, another quantitative approach, investigates the sum of interrelations to obtain a more holistic picture of nucleotide sequence order. Recent empirical data on genetic code compositions and rearrangements by mobile genetic elements and noncoding RNAs, together with results of virus research and their role in evolution, does not really fit into these concepts and compel a reexamination. In this review, we try to find an alternate hypothesis. It seems plausible now that if we look at the abundance of regulatory RNAs and persistent viruses in host genomes, we will find more and more evidence that the key players that edit the genetic codes of host genomes are consortia of RNA agents and viruses that drive evolutionary novelty and regulation of cellular processes in all steps of development. This agent-based approach may lead to a qualitative RNA sociology that investigates and identifies relevant behavioral motifs of cooperative RNA consortia. In addition to molecular biological perspectives, this may lead to a better understanding of genetic code evolution and dynamics.

Cation-dependent folding of 3' cap-independent translation elements facilitates interaction of a 17-nucleotide conserved sequence with eIF4G

The 3′-untranslated regions of many plant viral RNAs contain cap-independent translation elements (CITEs) that drive translation initiation at the 5′-end of the mRNA. The barley yellow dwarf virus-like CITE (BTE) stimulates translation by binding the eIF4G subunit of translation initiation factor eIF4F with high affinity. To understand this interaction, we characterized the dynamic structural properties of the BTE, mapped the eIF4G-binding sites on the BTE and identified a region of eIF4G that is crucial for BTE binding. BTE folding involves cooperative uptake of magnesium ions and is driven primarily by charge neutralization. Footprinting experiments revealed that functional eIF4G fragments protect the highly conserved stem–loop I and a downstream bulge. The BTE forms a functional structure in the absence of protein, and the loop that base pairs the 5′-untranslated region (5′-UTR) remains solvent-accessible at high eIF4G concentrations. The region in eIF4G between the eIF4E-binding site and the MIF4G region is required for BTE binding and translation. The data support the model in which the eIF4F complex binds directly to the BTE which base pairs simultaneously to the 5′-UTR, allowing eIF4F to recruit the 40S ribosomal subunit to the 5′-end.

A comparison of genotype-phenotype maps for RNA and proteins

The relationship between the genotype (sequence) and the phenotype (structure) of macromolecules affects their ability to evolve new structures and functions. We here compare the genotype space organization of proteins and RNA molecules to identify differences that may affect this ability. To this end, we computationally study the genotype-phenotype relationship for short RNA and lattice proteins of a reduced monomer alphabet size, to make exhaustive analysis and direct comparison of their genotype spaces feasible. We find that many fewer protein molecules than RNA molecules fold, but they fold into many more structures than RNA. In consequence, protein phenotypes have smaller genotype networks whose member genotypes tend to be more similar than for RNA phenotypes. Neighborhoods in sequence space of a given radius around an RNA molecule contain more novel structures than for protein molecules. We compare this property to evidence from natural RNA and protein molecules, and conclude that RNA genotype space may be more conducive to the evolution of new structure phenotypes.

Genome-wide measurement of RNA folding energies

RNA structural transitions are important in the function and regulation of RNAs. Here, we reveal a layer of transcriptome organization in the form of RNA folding energies. By probing yeast RNA structures at different temperatures, we obtained relative melting temperatures (Tm) for RNA structures in over 4000 transcripts. Specific signatures of RNA Tm demarcated the polarity of mRNA open reading frames and highlighted numerous candidate regulatory RNA motifs in 3' untranslated regions. RNA Tm distinguished noncoding versus coding RNAs and identified mRNAs with distinct cellular functions. We identified thousands of putative RNA thermometers, and their presence is predictive of the pattern of RNA decay in vivo during heat shock. The exosome complex recognizes unpaired bases during heat shock to degrade these RNAs, coupling intrinsic structural stabilities to gene regulation. Thus, genome-wide structural dynamics of RNA can parse functional elements of the transcriptome and reveal diverse biological insights.

Combinatorial action of miRNAs regulates transcriptional and post-transcriptional gene silencing following in vivo PNS injury

Injury response in the peripheral nervous system (PNS) is characterized by rapid alterations in the genetic program of Schwann cells. However, the epigenetic mechanisms modulating these changes remain elusive. Here we show that sciatic nerve injury in mice induces a cohort of 22 miRNAs, which coordinate Schwann cell differentiation and dedifferentiation through a combinatorial modulation of their positive and negative gene regulators. These miRNAs and their targeted mRNAs form functional complexes with the Argonaute-2 protein to mediate post-transcriptional gene silencing. MiR-138 and miR-709 show the highest affinity amongst the cohort, for binding and regulation of Egr2, Sox-2 and c-Jun expression following injury. Moreover, miR-709 participates in the formation of epigenetic silencing complexes with H3K27me3 and Argonaute-1 to induce transcriptional gene silencing of the Egr2 promoter. Collectively, we identified a discrete cohort of miRNAs as the central epigenetic regulators of the transition between differentiation and dedifferentiation during the acute phase of PNS injury.

Cooperative tertiary interaction network guides RNA folding

Noncoding RNAs form unique 3D structures, which perform many regulatory functions. To understand how RNAs fold uniquely despite a small number of tertiary interaction motifs, we mutated the major tertiary interactions in a group I ribozyme by single-base substitutions. The resulting perturbations to the folding energy landscape were measured using SAXS, ribozyme activity, hydroxyl radical footprinting, and native PAGE. Double- and triple-mutant cycles show that most tertiary interactions have a small effect on the stability of the native state. Instead, the formation of core and peripheral structural motifs is cooperatively linked in near-native folding intermediates, and this cooperativity depends on the native helix orientation. The emergence of a cooperative interaction network at an early stage of folding suppresses nonnative structures and guides the search for the native state. We suggest that cooperativity in noncoding RNAs arose from natural selection of architectures conducive to forming a unique, stable fold.

Do natural proteins differ from random sequences polypeptides? Natural vs. random proteins classification using an evolutionary neural network

Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random.

Ribosomal history reveals origins of modern protein synthesis

The origin and evolution of the ribosome is central to our understanding of the cellular world. Most hypotheses posit that the ribosome originated in the peptidyl transferase center of the large ribosomal subunit. However, these proposals do not link protein synthesis to RNA recognition and do not use a phylogenetic comparative framework to study ribosomal evolution. Here we infer evolution of the structural components of the ribosome. Phylogenetic methods widely used in morphometrics are applied directly to RNA structures of thousands of molecules and to a census of protein structures in hundreds of genomes. We find that components of the small subunit involved in ribosomal processivity evolved earlier than the catalytic peptidyl transferase center responsible for protein synthesis. Remarkably, subunit RNA and proteins coevolved, starting with interactions between the oldest proteins (S12 and S17) and the oldest substructure (the ribosomal ratchet) in the small subunit and ending with the rise of a modern multi-subunit ribosome. Ancestral ribonucleoprotein components show similarities to in vitro evolved RNA replicase ribozymes and protein structures in extant replication machinery. Our study therefore provides important clues about the chicken-or-egg dilemma associated with the central dogma of molecular biology by showing that ribosomal history is driven by the gradual structural accretion of protein and RNA structures. Most importantly, results suggest that functionally important and conserved regions of the ribosome were recruited and could be relics of an ancient ribonucleoprotein world.

Functional complexity and regulation through RNA dynamics

Changes to the conformation of coding and non-coding RNAs form the basis of elements of genetic regulation and provide an important source of complexity, which drives many of the fundamental processes of life. Although the structure of RNA is highly flexible, the underlying dynamics of RNA are robust and are limited to transitions between the few conformations that preserve favourable base-pairing and stacking interactions. The mechanisms by which cellular processes harness the intrinsic dynamic behaviour of RNA and use it within functionally productive pathways are complex. The versatile functions and ease by which it is integrated into a wide variety of genetic circuits and biochemical pathways suggests there is a general and fundamental role for RNA dynamics in cellular processes.

Protein folding absent selection

Biological proteins are known to fold into specific 3D conformations. However, the fundamental question has remained: Do they fold because they are biological, and evolution has selected sequences which fold? Or is folding a common trait, widespread throughout sequence space? To address this question arbitrary, unevolved, random-sequence proteins were examined for structural features found in folded, biological proteins. Libraries of long (71 residue), random-sequence polypeptides, with ensemble amino acid composition near the mean for natural globular proteins, were expressed as cleavable fusions with ubiquitin. The structural properties of both the purified pools and individual isolates were then probed using circular dichroism, fluorescence emission, and fluorescence quenching techniques. Despite this necessarily sparse "sampling" of sequence space, structural properties that define globular biological proteins, namely collapsed conformations, secondary structure, and cooperative unfolding, were found to be prevalent among unevolved sequences. Thus, for polypeptides the size of small proteins, natural selection is not necessary to account for the compact and cooperative folded states observed in nature.

Role of large thermal fluctuations and magnesium ions in t-RNA selectivity of the ribosome

The fidelity of translation selection begins with the base pairing of codon-anticodon complex between the m-RNA and tRNAs. Binding of cognate and near-cognate tRNAs induces 30S subunit of the ribosome to wrap around the ternary complex, EF-Tu(GTP)aa-tRNA. We have proposed that large thermal fluctuations play a crucial role in the selection process. To test this conjecture, we have developed a theoretical technique to determine the probability that the ternary complex, as a result of large thermal fluctuations, forms contacts leading to stabilization of the GTPase activated state. We argue that the configurational searches for such processes are in the tail end of the probability distribution and show that the probability for this event is localized around the most likely configuration. Small variations in the repositioning of cognate relative to near-cognate complexes lead to rate enhancement of the cognate complex. The binding energies of over a dozen unique site-bound magnesium structural motifs are investigated and provide insights into the nature of interaction of divalent metal ions with the ribosome.

Ribozymes and riboswitches: modulation of RNA function by small molecules

Diverse small molecules interact with catalytic RNAs (ribozymes) as substrates and cofactors, and their intracellular concentrations are sensed by gene-regulatory mRNA domains (riboswitches) that modulate transcription, splicing, translation, or RNA stability. Although recognition mechanisms vary from RNA to RNA, structural analyses reveal recurring strategies that arise from the intrinsic properties of RNA such as base pairing and stacking with conjugated heterocycles, and cation-dependent recognition of anionic functional groups. These studies also suggest that, to a first approximation, the magnitude of ligand-induced reorganization of an RNA is inversely proportional to the complexity of the riboswitch or ribozyme. How these small molecule binding-induced changes in RNA lead to alteration in gene expression is less well understood. While different riboswitches have been proposed to be under either kinetic or thermodynamic control, the biochemical and structural mechanisms that give rise to regulatory consequences downstream of small molecule recognition by RNAs mostly remain to be elucidated.

Predicting translational diffusion of evolutionary conserved RNA structures by the nucleotide number

Ribonucleic acids are highly conserved essential parts of cellular life. RNA function is determined to a large extent by its hydrodynamic behaviour. The presented study proposes a strategy to predict the hydrodynamic behaviour of RNA single strands on the basis of the polymer size. By atom-level shell-modelling of high-resolution structures, hydrodynamic radius and diffusion coefficient of evolutionary conserved RNA single strands (ssRNA) were calculated. The diffusion coefficients D of 17–174 nucleotides (nt) containing ssRNA depended on the number of nucleotides N with D = 4.56 × 10⁻¹⁰ N^−0.39 m² s⁻¹. The hydrodynamic radius R_H depended on N with R_H = 5.00 × 10⁻¹⁰N^0.38 m. An average ratio of the radius of gyration and the hydrodynamic radius of 0.98 ± 0.08 was calculated in solution. The empirical law was tested by in solution measured hydrodynamic radii and radii of gyration and was found to be highly consistent with experimental data of evolutionary conserved ssRNA. Furthermore, the hydrodynamic behaviour of several evolutionary unevolved ribonucleic acids could be predicted. Based on atom-level shell-modelling of high-resolution structures and experimental hydrodynamic data, empirical models are proposed, which enable to predict the translational diffusion coefficient and molecular size of short RNA single strands solely on the basis of the polymer size.

Taming free energy landscapes with RNA chaperones

Many non-coding RNAs fold into complex three-dimensional structures, yet the self-assembly of RNA structure is hampered by mispairing, weak tertiary interactions, electrostatic barriers, and the frequent requirement that the 5' and 3' ends of the transcript interact. This rugged free energy landscape for RNA folding means that some RNA molecules in a population rapidly form their native structure, while many others become kinetically trapped in misfolded conformations. Transient binding of RNA chaperone proteins destabilize misfolded intermediates and lower the transition states between conformations, producing a smoother landscape that increases the rate of folding and the probability that a molecule will find the native structure. DEAD-box proteins couple the chemical potential of ATP hydrolysis with repetitive cycles of RNA binding and release, expanding the range of conditions under which they can refold RNA structures.

The ancient history of the structure of ribonuclease P and the early origins of Archaea

BACKGROUND

Ribonuclease P is an ancient endonuclease that cleaves precursor tRNA and generally consists of a catalytic RNA subunit (RPR) and one or more proteins (RPPs). It represents an important macromolecular complex and model system that is universally distributed in life. Its putative origins have inspired fundamental hypotheses, including the proposal of an ancient RNA world.

RESULTS

To study the evolution of this complex, we constructed rooted phylogenetic trees of RPR molecules and substructures and estimated RPP age using a cladistic method that embeds structure directly into phylogenetic analysis. The general approach was used previously to study the evolution of tRNA, SINE RNA and 5S rRNA, the origins of metabolism, and the evolution and complexity of the protein world, and revealed here remarkable evolutionary patterns. Trees of molecules uncovered the tripartite nature of life and the early origin of archaeal RPRs. Trees of substructures showed molecules originated in stem P12 and were accessorized with a catalytic P1-P4 core structure before the first substructure was lost in Archaea. This core currently interacts with RPPs and ancient segments of the tRNA molecule. Finally, a census of protein domain structure in hundreds of genomes established RPPs appeared after the rise of metabolic enzymes at the onset of the protein world.

CONCLUSIONS

The study provides a detailed account of the history and early diversification of a fundamental ribonucleoprotein and offers further evidence in support of the existence of a tripartite organismal world that originated by the segregation of archaeal lineages from an ancient community of primordial organisms.

Evolution of ribozymes in an RNA world

Ribozymes (catalytic RNAs) were the center of a presumed RNA world in the early origin of life. In this issue, Lau and Unrau show evidence that an RNA world could have used a similar evolutionary pathway as most proteins do.

The dawn of the RNA World: toward functional complexity through ligation of random RNA oligomers

A main unsolved problem in the RNA World scenario for the origin of life is how a template-dependent RNA polymerase ribozyme emerged from short RNA oligomers obtained by random polymerization on mineral surfaces. A number of computational studies have shown that the structural repertoire yielded by that process is dominated by topologically simple structures, notably hairpin-like ones. A fraction of these could display RNA ligase activity and catalyze the assembly of larger, eventually functional RNA molecules retaining their previous modular structure: molecular complexity increases but template replication is absent. This allows us to build up a stepwise model of ligation-based, modular evolution that could pave the way to the emergence of a ribozyme with RNA replicase activity, step at which information-driven Darwinian evolution would be triggered.

A rugged free energy landscape separates multiple functional RNA folds throughout denaturation

The dynamic mechanisms by which RNAs acquire biologically functional structures are of increasing importance to the rapidly expanding fields of RNA therapeutics and biotechnology. Large energy barriers separating misfolded and functional states arising from alternate base pairing are a well-appreciated characteristic of RNA. In contrast, it is typically assumed that functionally folded RNA occupies a single native basin of attraction that is free of deeply dividing energy barriers (ergodic hypothesis). This assumption is widely used as an implicit basis to interpret experimental ensemble-averaged data. Here, we develop an experimental approach to isolate persistent sub-populations of a small RNA enzyme and show by single molecule fluorescence resonance energy transfer (smFRET), biochemical probing and high-resolution mass spectrometry that commitment to one of several catalytically active folds occurs unexpectedly high on the RNA folding energy landscape, resulting in partially irreversible folding. Our experiments reveal the retention of molecular heterogeneity following the complete loss of all native secondary and tertiary structure. Our results demonstrate a surprising longevity of molecular heterogeneity and advance our current understanding beyond that of non-functional misfolds of RNA kinetically trapped on a rugged folding-free energy landscape.

Predicting the sizes of large RNA molecules

We present a theory of the dependence on sequence of the three-dimensional size of large single-stranded (ss) RNA molecules. The work is motivated by the fact that the genomes of many viruses are large ssRNA molecules-often several thousand nucleotides long-and that these RNAs are spontaneously packaged into small rigid protein shells. We argue that there has been evolutionary pressure for the genome to have overall spatial properties-including an appropriate radius of gyration, R(g)-that facilitate this assembly process. For an arbitrary RNA sequence, we introduce the (thermal) average maximum ladder distance (MLD) and use it as a measure of the "extendedness" of the RNA secondary structure. The MLD values of viral ssRNAs that package into capsids of fixed size are shown to be consistently smaller than those for randomly permuted sequences of the same length and base composition, and also smaller than those of natural ssRNAs that are not under evolutionary pressure to have a compact native form. By mapping these secondary structures onto a linear polymer model and by using MLD as a measure of effective contour length, we predict the R(g) values of viral ssRNAs are smaller than those of nonviral sequences. More generally, we predict the average MLD values of large nonviral ssRNAs scale as N(0.67+/-0.01), where N is the number of nucleotides, and that their R(g) values vary as MLD(0.5) in an ideal solvent, and hence as N(0.34). An alternative analysis, which explicitly includes all branches, is introduced and shown to yield consistent results.

Evolutionary patterns in the sequence and structure of transfer RNA: a window into early translation and the genetic code

Transfer RNA (tRNA) molecules play vital roles during protein synthesis. Their acceptor arms are aminoacylated with specific amino acid residues while their anticodons delimit codon specificity. The history of these two functions has been generally linked in evolutionary studies of the genetic code. However, these functions could have been differentially recruited as evolutionary signatures were left embedded in tRNA molecules. Here we built phylogenies derived from the sequence and structure of tRNA, we forced taxa into monophyletic groups using constraint analyses, tested competing evolutionary hypotheses, and generated timelines of amino acid charging and codon discovery. Charging of Sec, Tyr, Ser and Leu appeared ancient, while specificities related to Asn, Met, and Arg were derived. The timelines also uncovered an early role of the second and then first codon bases, identified codons for Ala and Pro as the most ancient, and revealed important evolutionary take-overs related to the loss of the long variable arm in tRNA. The lack of correlation between ancestries of amino acid charging and encoding indicated that the separate discoveries of these functions reflected independent histories of recruitment. These histories were probably curbed by co-options and important take-overs during early diversification of the living world.

Prediction of RNA pseudoknots using heuristic modeling with mapping and sequential folding

Predicting RNA secondary structure is often the first step to determining the structure of RNA. Prediction approaches have historically avoided searching for pseudoknots because of the extreme combinatorial and time complexity of the problem. Yet neglecting pseudoknots limits the utility of such approaches. Here, an algorithm utilizing structure mapping and thermodynamics is introduced for RNA pseudoknot prediction that finds the minimum free energy and identifies information about the flexibility of the RNA. The heuristic approach takes advantage of the 5′ to 3′ folding direction of many biological RNA molecules and is consistent with the hierarchical folding hypothesis and the contact order model. Mapping methods are used to build and analyze the folded structure for pseudoknots and to add important 3D structural considerations. The program can predict some well known pseudoknot structures correctly. The results of this study suggest that many functional RNA sequences are optimized for proper folding. They also suggest directions we can proceed in the future to achieve even better results.

MicroRNA targeting specificity in mammals: determinants beyond seed pairing

Mammalian microRNAs (miRNAs) pair to 3'UTRs of mRNAs to direct their posttranscriptional repression. Important for target recognition are approximately 7 nt sites that match the seed region of the miRNA. However, these seed matches are not always sufficient for repression, indicating that other characteristics help specify targeting. By combining computational and experimental approaches, we uncovered five general features of site context that boost site efficacy: AU-rich nucleotide composition near the site, proximity to sites for coexpressed miRNAs (which leads to cooperative action), proximity to residues pairing to miRNA nucleotides 13-16, positioning within the 3'UTR at least 15 nt from the stop codon, and positioning away from the center of long UTRs. A model combining these context determinants quantitatively predicts site performance both for exogenously added miRNAs and for endogenous miRNA-message interactions. Because it predicts site efficacy without recourse to evolutionary conservation, the model also identifies effective nonconserved sites and siRNA off-targets.

Analysis of tRNA abstract shapes of precursor/derivative amino acids in Archaea

Wong's theory of the genetic code's origin states that because of historical constraints, codon assignment depends on the relation between precursor and derivative amino acids, a result of the coevolutionary process between amino acids' biosynthetic pathways and tRNAs. Based on arguments supporting the assumption that natural selection favors more stable and thus functionally constrained structures, we tested whether precursor and derivative tRNAs are equally evolved by measuring their structural parameters, thermostability and molecular plasticity. We also estimated the extent to which precursor and derivative tRNAs differ within Archaea. We used Archaea sequences of both precursor and derivative tRNAs in order to examine the plastic repertoires or sets of suboptimal structures at a defined free energy interval. We grouped secondary structures according to their helix nesting and adjacency using abstract shapes analysis. This clustering enabled us to infer a consensus sequence for all shapes that fit the clover leaf secondary structure [Giegerich, R., et al., Nucleic Acids Res 2004; 32 (16): 4843-51.]. This consensus sequence was then folded in order to retrieve a set of suboptimal structures. For each pair of precursor and derivative tRNAs, we compared these plastic repertoires based on the number of secondary structures, the thermostability of the minimum free energy structure and two structural parameters (base pair propensity (P) and mean length of helical stem structures (S)), which were measured for every representative secondary structure [Schultes, E.A., et al., J Mol Evol 1999; 49 (1): 76-83.]. We found that derivative tRNAs have fewer numbers of shapes, higher thermostability and more stable parameters than precursor tRNAs, a fact in full agreement with Wong's coevolution theory of the genetic code.

Using prior knowledge in the determination of macromolecular size-distributions by analytical ultracentrifugation

Analytical ultracentrifugation has reemerged as a widely used tool for the study of ensembles of biological macromolecules to understand, for example, their size-distribution and interactions in free solution. Such information can be obtained from the mathematical analysis of the concentration and signal gradients across the solution column and their evolution in time generated as a result of the gravitational force. In sedimentation velocity analytical ultracentrifugation, this analysis is frequently conducted using high resolution, diffusion-deconvoluted sedimentation coefficient distributions. They are based on Fredholm integral equations, which are ill-posed unless stabilized by regularization. In many fields, maximum entropy and Tikhonov-Phillips regularization are well-established and powerful approaches that calculate the most parsimonious distribution consistent with the data and prior knowledge, in accordance with Occam's razor. In the implementations available in analytical ultracentrifugation, to date, the basic assumption implied is that all sedimentation coefficients are equally likely and that the information retrieved should be condensed to the least amount possible. Frequently, however, more detailed distributions would be warranted by specific detailed prior knowledge on the macromolecular ensemble under study, such as the expectation of the sample to be monodisperse or paucidisperse or the expectation for the migration to establish a bimodal sedimentation pattern based on Gilbert-Jenkins' theory for the migration of chemically reacting systems. So far, such prior knowledge has remained largely unused in the calculation of the sedimentation coefficient or molecular weight distributions or was only applied as constraints. In the present paper, we examine how prior expectations can be built directly into the computational data analysis, conservatively in a way that honors the complete information of the experimental data, whether or not consistent with the prior expectation. Consistent with analogous results in other fields, we find that the use of available prior knowledge can have a dramatic effect on the resulting molecular weight, sedimentation coefficient, and size-and-shape distributions and can significantly increase both their sensitivity and their resolution. Further, the use of multiple alternative prior information allows us to probe the range of possible interpretations consistent with the data.

Charge density of divalent metal cations determines RNA stability

RNA molecules are exquisitely sensitive to the properties of counterions. The folding equilibrium of the Tetrahymena ribozyme is measured by nondenaturing gel electrophoresis in the presence of divalent group IIA metal cations. The stability of the folded ribozyme increases with the charge density (zeta) of the cation. Similar scaling is found when the free energy of the RNA folded in small and large metal cations is measured by urea denaturation. Brownian dynamics simulations of a polyelectrolyte show that the experimental observations can be explained by nonspecific ion-RNA interactions in the absence of site-specific metal chelation. The experimental and simulation results establish that RNA stability is largely determined by a combination of counterion charge and the packing efficiency of condensed cations that depends on the excluded volume of the cations.

A counterintuitive Mg2+-dependent and modification-assisted functional folding of mitochondrial tRNAs

Mitochondrial tRNAs (mtRNAs) often lack domains and posttranscriptional modifications that are found in cytoplasmic tRNAs. These structural and chemical elements normally stabilize the folding of cytoplasmic tRNAs into canonical structures that are competent for aminoacylation and translation. For example, the dihydrouridine (D) stem and loop domain is involved in the tertiary structure of cytoplasmic tRNAs through hydrogen bonds and a Mg2+ bridge to the ribothymidine (T) stem and loop domain. These interactions are often absent in mtRNA because the D-domain is truncated or missing. Using gel mobility shift analyses, UV, circular dichroism and NMR spectroscopies and aminoacylation assays, we have investigated the functional folding interactions of chemically synthesized and site-specifically modified mitochondrial and cytoplasmic tRNAs. We found that Mg2+ is critical for folding of the truncated D-domain of bovine mtRNAMet with the tRNA's T-domain. Contrary to the expectation that Mg2+ stabilizes RNA folding, the mtRNAMet D-domain structure was unfolded and relaxed, rather than stabilized in the presence of Mg2+. Because the D-domain is transcribed prior to the T-domain, we conclude that Mg2+ prevents misfolding of the 5'-half of bovine mtRNAMet facilitating its correct interaction with the T-domain. The interaction of the mtRNAMet D-domain with the T-domain was enhanced by a pseudouridine located in either the D or T-domains compared to that of the unmodified RNAs (Kd=25.3, 24.6 and 44.4 microM, respectively). Mg2+ also affected the folding interaction of a yeast mtRNALeu1, but had minimal effect on the folding of an Escherichia coli cytoplasmic tRNALeu. The D-domain modification, dihydrouridine, facilitated mtRNALeu folding. These data indicate that conserved modifications assist and stabilize the formation of the functional mtRNA tertiary structure.