A computational proposal for designing structured RNA pools for in vitro selection of RNAs

Although in vitro selection technology is a versatile experimental tool for discovering novel synthetic RNA molecules, finding complex RNA molecules is difficult because most RNAs identified from random sequence pools are simple motifs, consistent with recent computational analysis of such sequence pools. Thus, enriching in vitro selection pools with complex structures could increase the probability of discovering novel RNAs. Here we develop an approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a "mixing matrix" approach combined with a graph theory analysis. We define five classes of mixing matrices motivated by covariance mutations in RNA; these constructs define nucleotide transition rates and are applied to chosen starting sequences to yield specific nonrandom pools. We examine the coverage of sequence space as a function of the mixing matrix and starting sequence via clustering analysis. We show that, in contrast to random sequences, which are associated only with a local region of sequence space, our designed pools, including a structured pool for GTP aptamers, can target specific motifs. It follows that experimental synthesis of designed pools can benefit from using optimized starting sequences, mixing matrices, and pool fractions associated with each of our constructed pools as a guide. Automation of our approach could provide practical tools for pool design applications for in vitro selection of RNAs and related problems.     

Computational approaches toward the design of pools for the in vitro selection of complex aptamers

It is well known that using random RNA/DNA sequences for SELEX experiments will generally yield low-complexity structures. Early experimental results suggest that having a structurally diverse library, which, for instance, includes high-order junctions, may prove useful in finding new functional motifs. Here, we develop two computational methods to generate sequences that exhibit higher structural complexity and can be used to increase the overall structural diversity of initial pools for in vitro selection experiments. Random Filtering selectively increases the number of five-way junctions in RNA/DNA pools, and Genetic Filtering designs RNA/DNA pools to a specified structure distribution, whether uniform or otherwise. We show that using our computationally designed DNA pool greatly improves access to highly complex sequence structures for SELEX experiments (without losing our ability to select for common one-way and two-way junction sequences).     

Computational generation and screening of RNA motifs in large nucleotide sequence pools

Although identification of active motifs in large random sequence pools is central to RNA in vitro selection, no systematic computational equivalent of this process has yet been developed. We develop a computational approach that combines target pool generation, motif scanning and motif screening using secondary structure analysis for applications to 10¹²–10¹⁴-sequence pools; large pool sizes are made possible using program redesign and supercomputing resources. We use the new protocol to search for aptamer and ribozyme motifs in pools up to experimental pool size (10¹⁴ sequences). We show that motif scanning, structure matching and flanking sequence analysis, respectively, reduce the initial sequence pool by 6–8, 1–2 and 1 orders of magnitude, consistent with the rare occurrence of active motifs in random pools. The final yields match the theoretical yields from probability theory for simple motifs and overestimate experimental yields, which constitute lower bounds, for aptamers because screening analyses beyond secondary structure information are not considered systematically. We also show that designed pools using our nucleotide transition probability matrices can produce higher yields for RNA ligase motifs than random pools. Our methods for generating, analyzing and designing large pools can help improve RNA design via simulation of aspects of in vitro selection.     

Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design

Understanding the structural repertoire of RNA is crucial for RNA genomics research. Yet current methods for finding novel RNAs are limited to small or known RNA families. To expand known RNA structural motifs, we develop a two-dimensional graphical representation approach for describing and estimating the size of RNA’s secondary structural repertoire, including naturally occurring and other possible RNA motifs. We employ tree graphs to describe RNA tree motifs and more general (dual) graphs to describe both RNA tree and pseudoknot motifs. Our estimates of RNA’s structural space are vastly smaller than the nucleotide sequence space, suggesting a new avenue for finding novel RNAs. Specifically our survey shows that known RNA trees and pseudoknots represent only a small subset of all possible motifs, implying that some of the ‘missing’ motifs may represent novel RNAs. To help pinpoint RNA-like motifs, we show that the motifs of existing functional RNAs are clustered in a narrow range of topological characteristics. We also illustrate the applications of our approach to the design of novel RNAs and automated comparison of RNA structures; we report several occurrences of RNA motifs within larger RNAs. Thus, our graph theory approach to RNA structures has implications for RNA genomics, structure analysis and design.     

RAG: RNA-As-Graphs database--concepts, analysis, and features

MOTIVATION: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire. RESULTS: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. AVAILABILITY: The database is accessible on the web at http://monod.biomath.nyu.edu/rna     

On the structural repertoire of pools of short, random RNA sequences

A detailed knowledge of the mapping between sequence and structure spaces in populations of RNA molecules is essential to better understand their present-day functional properties, to envisage a plausible early evolution of RNA in a prebiotic chemical environment and to improve the design of in vitro evolution experiments, among others. Analysis of natural RNAs, as well as in vitro and computational studies, show that certain RNA structural motifs are much more abundant than others, pointing out a complex relation between sequence and structure. Within this framework, we have investigated computationally the structural properties of a large pool (10⁸ molecules) of single-stranded, 35 nt-long, random RNA sequences. The secondary structures obtained are ranked and classified into structure families. The number of structures in main families is analytically calculated and compared with the numerical results. This permits a quantification of the fraction of structure space covered by a large pool of sequences. We further show that the number of structural motifs and their frequency is highly unbalanced with respect to the nucleotide composition: simple structures such as stem-loops and hairpins arise from sequences depleted in G, while more complex structures require an enrichment of G. In general, we observe a strong correlation between subfamilies—characterized by a fixed number of paired nucleotides—and nucleotide composition. Our results are compared to the structural repertoire obtained in a second pool where isolated base pairs are prohibited.     

An algorithm for searching RNA motifs in genomic sequences

RNA molecules, which are found in all living cells, fold into characteristic structures that account for their diverse functional activities. Many of these RNA structures consist of a collection of fundamental RNA motifs. The various combinations of RNA basic components form different RNA classes and define their unique structural and functional properties. The availability of many genome sequences makes it possible to search computationally for functional RNAs. Biological experiments indicate that functional RNAs have characteristic RNA structural motifs represented by specific combinations of base pairings and conserved nucleotides in the loop regions. The searching for those well-ordered RNA structures and their homologues in genomic sequences is very helpful for the understanding of RNA-based gene regulation. In this paper, we consider the following problem: given an RNA sequence with a known secondary structure, efficiently determine candidate segments in genomic sequences that can potentially form RNA secondary structures similar to the given RNA secondary structure. Our new bottom-up approach searches all potential stem-loops similar to ones of the given RNA secondary structure first, and then based on located stem-loops, detects potential homologous structural RNAs in genomic sequences.     

RNA structural motifs: building blocks of a modular biomolecule

RNAs are modular biomolecules, composed largely of conserved structural subunits, or motifs. These structural motifs comprise the secondary structure of RNA and are knit together via tertiary interactions into a compact, functional, three-dimensional structure and are to be distinguished from motifs defined by sequence or function. A relatively small number of structural motifs are found repeatedly in RNA hairpin and internal loops, and are observed to be composed of a limited number of common 'structural elements'. In addition to secondary and tertiary structure motifs, there are functional motifs specific for certain biological roles and binding motifs that serve to complex metals or other ligands. Research is continuing into the identification and classification of RNA structural motifs and is being initiated to predict motifs from sequence, to trace their phylogenetic relationships and to use them as building blocks in RNA engineering.     

Ribonucleopeptides: functional RNA-peptide complexes

Selection of functional RNAs from randomized pool of RNA molecules successfully affords RNA aptamers that specifically bind to small molecules, and that have catalytic activities. Recent structural analyses of the ribosomal RNA complex suggest that the RNA-protein complex would be a new structural candidate for the design of tailor-made receptors and enzymes. We have designed an ATP binding domain that consists of an RNA subunit and a peptide subunit by means of structure-based design approach and successive in vitro selection method. The RNA subunit is designed to consist of two functional domains; an ATP binding domain with 20 randomized nucleotides and an adjacent stem region that serves as a binding site for the RNA-binding peptide. The randomized nucleotide region was placed next to the HIV-1 Rev response element to enable the formation of "ribonucleopeptide" pools in the presence of the Rev peptide. In vitro selection of RNA oligonucleotides from the randomized pool afforded a ribonucleopeptide receptor specific for ATP. The ATP-binding ribonucleopeptide did not share the known consensus nucleotide sequence for ATP aptamers, and completely lost its ATP-binding ability in the absence of the Rev peptide. The ATP-binding activity of the ribonucleopeptide was increased by a substitution of the N-terminal amino acid of the Rev peptide. These results demonstrate that the peptide stabilizes the functional structure of RNA and suggest that amino acids outside the RNA binding region of the peptide participate in the ATP binding. Our approach would provide a new strategy for the design of tailor-made ribonucleopeptide receptors.     

In vitro genetic selection analysis of alfalfa mosaic virus coat protein binding to 3'-terminal AUGC repeats in the viral RNAs.

The coat proteins of alfalfa mosaic virus (AMV) and the related ilarviruses bind specifically to the 3' untranslated regions of the viral RNAs, which contain conserved repeats of the tetranucleotide sequence AUGC. The purpose of this study was to develop a more detailed understanding of RNA sequence and/or structural determinants required for coat protein binding by characterizing the role of the AUGC repeats. Starting with a complex pool of 39-nucleotide RNA molecules containing random substitutions in the AUGC repeats, in vitro genetic selection was used to identify RNAs that bound coat protein. After six iterative rounds of selection, amplification, and reselection, 25% of the RNAs selected from the randomized pool were wild type; that is, they contained all four AUGC sequences. Among the 31 clones analyzed, AUGC was clearly the preferred selected sequence at the four repeats, but some nucleotide sequence variability was observed at AUGC(865-868) if the other three AUGC repeats were present. Variant RNAs that bound coat protein with affinities equal to or greater than that of the wild-type molecule were not selected. To extend the in vitro selection results, RNAs containing specific nucleotide substitutions were transcribed in vitro and tested in coat protein and peptide binding assays. The data strongly suggest that the AUGC repeats provide sequence-specific determinants and contribute to a structural platform for specific coat protein binding. Coat protein may function in maintaining the 3' ends of the genomic RNAs during replication by stabilizing an RNA structure that defines the 3' terminus as the initiation site for minus-strand synthesis.     

Characterization of RNA binding specificity of the Drosophila sex-lethal protein by in vitro ligand selection.

The Drosophila sex-lethal (Sxl) protein, a regulator of somatic sexual differentiation, is an RNA binding protein with two potential RNA recognition motifs (RRMs). It is thought to exert its function on splicing by binding to specific RNA sequences within Sxl and transformer (tra) pre-mRNAs. To examine the Sxl RNA binding specificity in detail, we performed in vitro selection and amplification of ligand RNAs from a random sequence pool on the basis of affinity with Sxl protein. After three cycles of selection and amplification, we cloned and sequenced 17 cDNAs corresponding to the RNAs selected in vitro. Sequencing showed that most of the RNAs selected contain polyuridine stretches surrounded by purine residues. In vitro binding analysis revealed that the sequences of the in vitro selected RNAs with relatively high affinity for Sxl show similarity to that of the Sxl- and tra-regulated acceptor regions, including the invariant AG sequence for splicing. These results suggest that Sxl recognizes and preferentially binds to a polyuridine stretch with a downstream AG sequence.     

In vitro selection of RNAs with increased tertiary structure stability.

An in vitro selection system was devised to select RNAs based on their tertiary structural stability, independent of RNA activity. Selection studies were conducted on the P4-P6 domain from the Tetrahymena thermophila group I intron, an autonomous self-folding unit that contains several important tertiary folding motifs including the tetraloop receptor and the A-rich bulge. Partially randomized P4-P6 molecules were selected based on their ability to fold into compact structures using native gel electrophoresis in the presence of decreasing concentrations of MgCl2. After 10 rounds of the selection process, a number of sequence alterations were identified that stabilized the P4-P6 RNA. One of these, a single base deletion of C209 within the P4 helix, significantly stabilized the P4-P6 molecule and would not have been identified by an activity-based selection because of its essential role for ribozyme function. Additionally, the sequence analysis provided evidence that stabilization of secondary structure may contribute to overall tertiary stability for RNAs. This system for probing RNA structure irrespective of RNA activity allows analysis of RNA structure/function relationships by identifying nucleotides or motifs important for folding and then comparing them with RNA sequences required for function.     

Structural bias in T4 RNA ligase-mediated 3'-adapter ligation

T4 RNA ligases are commonly used to attach adapters to RNAs, but large differences in ligation efficiency make detection and quantitation problematic. We developed a ligation selection strategy using random RNAs in combination with high-throughput sequencing to gain insight into the differences in efficiency of ligating pre-adenylated DNA adapters to RNA 3'-ends. After analyzing biases in RNA sequence, secondary structure and RNA-adapter cofold structure, we conclude that T4 RNA ligases do not show significant primary sequence preference in RNA substrates, but are biased against structural features within RNAs and adapters. Specifically, RNAs with less than three unstructured nucleotides at the 3'-end and RNAs that are predicted to cofold with an adapter in unfavorable structures are likely to be poorly ligated. The effect of RNA-adapter cofold structures on ligation is supported by experiments where the ligation efficiency of specific miRNAs was changed by designing adapters to alter cofold structure. In addition, we show that using adapters with randomized regions results in higher ligation efficiency and reduced ligation bias. We propose that using randomized adapters may improve RNA representation in experiments that include a 3'-adapter ligation step.     

Compact and ordered collapse of randomly generated RNA sequences

As the raw material for evolution, arbitrary RNA sequences represent the baseline for RNA structure formation and a standard to which evolved structures can be compared. Here, we set out to probe, using physical and chemical methods, the structural properties of RNAs having randomly generated oligonucleotide sequences that were of sufficient length and information content to encode complex, functional folds, yet were unbiased by either genealogical or functional constraints. Typically, these unevolved, nonfunctional RNAs had sequence-specific secondary structure configurations and compact magnesium-dependent conformational states comparable to those of evolved RNA isolates. But unlike evolved sequences, arbitrary sequences were prone to having multiple competing conformations. Thus, for RNAs the size of small ribozymes, natural selection seems necessary to achieve uniquely folding sequences, but not to account for the well-ordered secondary structures and overall compactness observed in nature.     

RNA aptamers that bind L-arginine with sub-micromolar dissociation constants and high enantioselectivity.

A completely randomized RNA pool as well as a degenerate pool comprised of an RNA sequence which binds citrulline with a dissociation constant of 0 muM were used to select for tight binding arginine specific RNA aptamers. A modified in vitro selection scheme, based on affinity chromatography was applied to allow the enrichment of high affinity solution binders. The selection scheme included a negative selection with the non-cognate ligand citrulline, and a heat denaturation step prior to affinity elution with an excess of the cognate ligand arginine. After 20 cycles the majority of the pools bound specifically to the arginine matrix even after denaturation/renaturation in the presence of 20 mM of a non-cognate amino acid. When denatured and eluted in the presence of 20 mM arginine, the selected RNAs quantitatively washed off the column. These RNA aptamers were cloned and sequenced. Equilibrium dialysis performed with the most abundant clone among the selected sequence revealed Kd values of 330 nM for the RNA/arginine affinity, which is nearly a 200-fold improvement over the tightest binding arginine binding RNAs known to date. Arginine recognition by this RNA is highly enantioselectice: L- arginine is bound 12 000-fold better than D-arginine. Chemical modification analysis revealed that the secondary structure of the aptamer might contain a pseudoknot motif. Our tight binding arginine aptamers join a number of natural and in vitro selected RNAs which recognize arginine. The RNAs described here compare in their binding affinity with the tightest binding RNA aptamers for low molecular weight molecules isolated in other in vitro selection experiments.     

The secondary structure and sequence optimization of an RNA ligase ribozyme.

In vitro selection can generate functional sequence variants of an RNA structural motif that are useful for comparative analysis. The technique is particularly valuable in cases where natural variation is unavailable or non-existent. We report the extension of this approach to a new extreme--the identification of a 112 nt ribozyme secondary structure imbedded within a 186 nt RNA. A pool of 10(14) variants of an RNA ligase ribozyme was generated using combinatorial chemical synthesis coupled with combinatorial enzymatic ligation such that 172 of the 186 relevant positions were partially mutagenized. Active variants of this pool were enriched using an in vitro selection scheme that retains the sequence variability at positions very close to the ligation junction. Ligases isolated after four rounds of selection catalyzed self-ligation up to 700 times faster than the starting sequence. Comparative analysis of the isolates indicated that when complexed with substrate RNAs the ligase forms a nested, double pseudo-knot secondary structure with seven stems and several important joining segments. Comparative analysis also suggested the identity of mutations that account for the increased activity of the selected ligase variants; designed constructs incorporating combinations of these changes were more active than any of the individual ligase isolates.     

A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications

Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.     

Functional Analysis of the Core Human Immunodeficiency Virus Type 1 Packaging Signal in a Permissive Cell Line

Packaging of type C retrovirus genomic RNAs into budding virions requires a highly specific interaction between the viral Gag precursor and unique cis-acting packaging signals on the full-length RNA genome, allowing the selection of this RNA species from among a pool of spliced viral RNAs and similar cellular RNAs. This process is thought to involve RNA secondary and tertiary structural motifs since there is little conservation of the primary sequence of this region between retroviruses. To confirm RNA secondary structures, which we and others have predicted for this region, disruptive, compensatory, and deletion mutations were introduced into proviral constructs, which were then assayed in a permissive cell line. Disruption of either of two predicted stem-loops was found to greatly reduce RNA encapsidation and replication, whereas compensatory mutations restoring base pairing to these stem-loops had a wild-type phenotype. A GGNGR motif was identified in the loops of three hairpins in this region. Results were consistent with the hypothesis that the process of efficient RNA encapsidation is linked to dimerization. Replication and encapsidation were shown to occur at a reduced rate in the absence of the previously described kissing hairpin motif.     

SERF: in vitro election of random RNA fragments to identify protein binding sites within large RNAs

In vitro selection experiments have various goals depending on the composition of the initial pool and the selection method applied. We developed an in vitro selection variant (SERF, selection of random RNA fragments) that is useful for the identification of short RNA fragments originating from large RNAs that bind specifically to a protein. A pool of randomly fragmented RNA is constructed from a large RNA, which is the natural binding partner for a protein. Such a pool contains all the potential binding sites and is therefore used as starting material for affinity selection with the purified protein to find its natural target. Here we provide a detailed experimental protocol of the method. SERF has been developed for ribosomal systems and is a general approach providing a basis for functional and structural characterization of RNA-protein interactions in large ribonucleoprotein particles.