20,895 research outputs found
Encoding folding paths of RNA switches
RNA co-transcriptional folding has long been suspected to play an active role
in helping proper native folding of ribozymes and structured regulatory motifs
in mRNA untranslated regions. Yet, the underlying mechanisms and coding
requirements for efficient co-transcriptional folding remain unclear.
Traditional approaches have intrinsic limitations to dissect RNA folding paths,
as they rely on sequence mutations or circular permutations that typically
perturb both RNA folding paths and equilibrium structures. Here, we show that
exploiting sequence symmetries instead of mutations can circumvent this problem
by essentially decoupling folding paths from equilibrium structures of designed
RNA sequences. Using bistable RNA switches with symmetrical helices conserved
under sequence reversal, we demonstrate experimentally that native and
transiently formed helices can guide efficient co-transcriptional folding into
either long-lived structure of these RNA switches. Their folding path is
controlled by the order of helix nucleations and subsequent exchanges during
transcription, and may also be redirected by transient antisense interactions.
Hence, transient intra- and intermolecular base pair interactions can
effectively regulate the folding of nascent RNA molecules into different native
structures, provided limited coding requirements, as discussed from an
information theory perspective. This constitutive coupling between RNA
synthesis and RNA folding regulation may have enabled the early emergence of
autonomous RNA-based regulation networks.Comment: 9 pages, 6 figure
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
A mutate-and-map protocol for inferring base pairs in structured RNA
Chemical mapping is a widespread technique for structural analysis of nucleic
acids in which a molecule's reactivity to different probes is quantified at
single-nucleotide resolution and used to constrain structural modeling. This
experimental framework has been extensively revisited in the past decade with
new strategies for high-throughput read-outs, chemical modification, and rapid
data analysis. Recently, we have coupled the technique to high-throughput
mutagenesis. Point mutations of a base-paired nucleotide can lead to exposure
of not only that nucleotide but also its interaction partner. Carrying out the
mutation and mapping for the entire system gives an experimental approximation
of the molecules contact map. Here, we give our in-house protocol for this
mutate-and-map strategy, based on 96-well capillary electrophoresis, and we
provide practical tips on interpreting the data to infer nucleic acid
structure.Comment: 22 pages, 5 figure
Paradigms for computational nucleic acid design
The design of DNA and RNA sequences is critical for many endeavors, from DNA nanotechnology, to PCR‐based applications, to DNA hybridization arrays. Results in the literature rely on a wide variety of design criteria adapted to the particular requirements of each application. Using an extensively studied thermodynamic model, we perform a detailed study of several criteria for designing sequences intended to adopt a target secondary structure. We conclude that superior design methods should explicitly implement both a positive design paradigm (optimize affinity for the target structure) and a negative design paradigm (optimize specificity for the target structure). The commonly used approaches of sequence symmetry minimization and minimum free‐energy satisfaction primarily implement negative design and can be strengthened by introducing a positive design component. Surprisingly, our findings hold for a wide range of secondary structures and are robust to modest perturbation of the thermodynamic parameters used for evaluating sequence quality, suggesting the feasibility and ongoing utility of a unified approach to nucleic acid design as parameter sets are refined further. Finally, we observe that designing for thermodynamic stability does not determine folding kinetics, emphasizing the opportunity for extending design criteria to target kinetic features of the energy landscape
Understanding the errors of SHAPE-directed RNA structure modeling
Single-nucleotide-resolution chemical mapping for structured RNA is being
rapidly advanced by new chemistries, faster readouts, and coupling to
computational algorithms. Recent tests have shown that selective 2'-hydroxyl
acylation by primer extension (SHAPE) can give near-zero error rates (0-2%) in
modeling the helices of RNA secondary structure. Here, we benchmark the method
using six molecules for which crystallographic data are available: tRNA(phe)
and 5S rRNA from Escherichia coli, the P4-P6 domain of the Tetrahymena group I
ribozyme, and ligand-bound domains from riboswitches for adenine, cyclic
di-GMP, and glycine. SHAPE-directed modeling of these highly structured RNAs
gave an overall false negative rate (FNR) of 17% and a false discovery rate
(FDR) of 21%, with at least one helix prediction error in five of the six
cases. Extensive variations of data processing, normalization, and modeling
parameters did not significantly mitigate modeling errors. Only one varation,
filtering out data collected with deoxyinosine triphosphate during primer
extension, gave a modest improvement (FNR = 12%, and FDR = 14%). The residual
structure modeling errors are explained by the insufficient information content
of these RNAs' SHAPE data, as evaluated by a nonparametric bootstrapping
analysis. Beyond these benchmark cases, bootstrapping suggests a low level of
confidence (<50%) in the majority of helices in a previously proposed
SHAPE-directed model for the HIV-1 RNA genome. Thus, SHAPE-directed RNA
modeling is not always unambiguous, and helix-by-helix confidence estimates, as
described herein, may be critical for interpreting results from this powerful
methodology.Comment: Biochemistry, Article ASAP (Aug. 15, 2011
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The how and why of lncRNA function: An innate immune perspective.
Next-generation sequencing has provided a more complete picture of the composition of the human transcriptome indicating that much of the "blueprint" is a vastness of poorly understood non-protein-coding transcripts. This includes a newly identified class of genes called long noncoding RNAs (lncRNAs). The lack of sequence conservation for lncRNAs across species meant that their biological importance was initially met with some skepticism. LncRNAs mediate their functions through interactions with proteins, RNA, DNA, or a combination of these. Their functions can often be dictated by their localization, sequence, and/or secondary structure. Here we provide a review of the approaches typically adopted to study the complexity of these genes with an emphasis on recent discoveries within the innate immune field. Finally, we discuss the challenges, as well as the emergence of new technologies that will continue to move this field forward and provide greater insight into the biological importance of this class of genes. This article is part of a Special Issue entitled: ncRNA in control of gene expression edited by Kotb Abdelmohsen
Noncoder : a web interface for exon array-based detection of long non-coding RNAs
Due to recent technical developments, a high number of long non-coding RNAs (lncRNAs) have been discovered in mammals. Although it has been shown that lncRNAs are regulated differently among tissues and disease statuses, functions of these transcripts are still unknown in most cases. GeneChip Exon 1.0 ST Arrays (exon arrays) from Affymetrix, Inc. have been used widely to profile genome-wide expression changes and alternative splicing of protein-coding genes. Here, we demonstrate that re-annotation of exon array probes can be used to profile expressions of tens of thousands of lncRNAs. With this annotation, a detailed inspection of lncRNAs and their isoforms is possible. To allow for a general usage to the research community, we developed a user-friendly web interface called 'noncoder'. By uploading CEL files from exon arrays and with a few mouse clicks and parameter settings, exon array data will be normalized and analysed to identify differentially expressed lncRNAs. Noncoder provides the detailed annotation information of lncRNAs and is equipped with unique features to allow for an efficient search for interesting lncRNAs to be studied further. The web interface is available at http://noncoder.mpi-bn.mpg.de
Genomics and proteomics: a signal processor's tour
The theory and methods of signal processing are becoming increasingly important in molecular biology. Digital filtering techniques, transform domain methods, and Markov models have played important roles in gene identification, biological sequence analysis, and alignment. This paper contains a brief review of molecular biology, followed by a review of the applications of signal processing theory. This includes the problem of gene finding using digital filtering, and the use of transform domain methods in the study of protein binding spots. The relatively new topic of noncoding genes, and the associated problem of identifying ncRNA buried in DNA sequences are also described. This includes a discussion of hidden Markov models and context free grammars. Several new directions in genomic signal processing are briefly outlined in the end
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