Secondary Structure Model Research Articles

The Complete Mitochondrial Genome of the Stalk-Eyed Bug Chauliops fallax Scott, and the Monophyly of Malcidae (Hemiptera: Heteroptera)

Chauliops fallax Scott, 1874 (Hemiptera: Heteroptera: Malcidae: Chauliopinae) is one of the most destructive insect pests of soybean and rice fields in Asia. Here we sequenced the complete mitochondrial genome of this pest. This genome is 15,739 bp long, with an A+T content of 73.7%, containing 37 typical animal mitochondrial genes and a control region. All genes were arranged in the same order as most of other Heteroptera. A remarkable strand bias was found for all nine protein coding genes (PCGs) encoded by the majority strand were positive AT-skew and negative GC-skew, whereas the reverse were found in the remaining four PCGs encoded by the minority strand and two rRNA genes. The models of secondary structures for the two rRNA genes of sequenced true bugs and Lygaeoidea were predicted. 16S rRNA consisted of six domains (domain III is absent as in other known arthropod mitochondrial genomes) and 45 helices, while three domains and 27 helices for 12S rRNA. The control region consists of five subregions: a microsatellite-like region, a tandem repeats region and other three motifs. The unusual intergenic spacer between tRNA-H and ND4 only found in the species of Lygaeoidea, not in other heteropteran species, may be the synapomorphy of this superfamily. Phylogenetic analyses were carried out based on all the 13 PCGs showed that Chauliopinae was the sister group of Malcinae and the monophyly of Lygaeoidea.

The A-nucleotide preference of HIV-1 in the context of its structured RNA genome

A bipartition of HIV-1 RNA genome sequences into single- and double-stranded nucleotides is possible based on the secondary structure model of a complete 9 kb genome. Subsequent analysis revealed that the well-known lentiviral property of A-accumulation is profoundly present in single-stranded domains, yet absent in double-stranded domains. Mutational rate analysis by means of an unrestricted model of nucleotide substitution suggests the presence of an evolutionary equilibrium to preserve this biased nucleotide distribution.

Statistical Analysis of SHAPE-Directed RNA Secondary Structure Modeling

The ability to predict RNA secondary structure is fundamental for understanding and manipulating RNA function. The information obtained from selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) experiments greatly improves the accuracy of RNA secondary structure prediction. Recently, Das and colleagues [Kladwang, W., et al. (2011) Biochemistry 50, 8049-8056] proposed a "bootstrapping" approach for estimating the variance and helix-by-helix confidence levels of predicted secondary structures based on resampling (randomizing and summing) the measured SHAPE data. We show that the specific resampling approach described by Kladwang et al. introduces systematic errors and underestimates confidence in secondary structure prediction using SHAPE data. Instead, a leave-data-out jackknife approach better estimates the influence of a given experimental data set on SHAPE-directed secondary structure modeling. Even when 35% of the data were left out in the jackknife approach, the confidence levels of SHAPE-directed secondary structure prediction were significantly higher than those calculated by Das and colleagues using bootstrapping. Helix confidence levels were thus underestimated in the recent study, and the resampling approach implemented by Kladwang et al. is not an appropriate metric for evaluating SHAPE-directed secondary structure modeling.

Principles for understanding the accuracy of SHAPE-directed RNA structure modeling.

Accurate RNA structure modeling is an important, incompletely solved, challenge. Single-nucleotide resolution SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) yields an experimental measurement of local nucleotide flexibility that can be incorporated as pseudo-free energy change constraints to direct secondary structure predictions. Prior work from our laboratory has emphasized both the overall accuracy of this approach and the need for nuanced interpretation of modeled structures. Recent studies by Das and colleagues [Kladwang, W., et al. (2011) Biochemistry 50, 8049; Nat. Chem. 3, 954], focused on analyzing six small RNAs, yielded poorer RNA secondary structure predictions than expected on the basis of prior benchmarking efforts. To understand the features that led to these divergent results, we re-examined four RNAs yielding the poorest results in this recent work: tRNA(Phe), the adenine and cyclic-di-GMP riboswitches, and 5S rRNA. Most of the errors reported by Das and colleagues reflected nonstandard experiment and data processing choices, and selective scoring rules. For two RNAs, tRNA(Phe) and the adenine riboswitch, secondary structure predictions are nearly perfect if no experimental information is included but were rendered inaccurate by the SHAPE data of Das and colleagues. When best practices were used, single-sequence SHAPE-directed secondary structure modeling recovered ~93% of individual base pairs and >90% of helices in the four RNAs, essentially indistinguishable from the results of the mutate-and-map approach with the exception of a single helix in the 5S rRNA. The field of experimentally directed RNA secondary structure prediction is entering a phase focused on the most difficult prediction challenges. We outline five constructive principles for guiding this field forward.

Specificity between Lactobacilli and Hymenopteran Hosts Is the Exception Rather than the Rule

Lactobacilli (Lactobacillales: Lactobacillaceae) are well known for their roles in food fermentation, as probiotics, and in human health, but they can also be dominant members of the microbiota of some species of Hymenoptera (ants, bees, and wasps). Honey bees and bumble bees associate with host-specific lactobacilli, and some evidence suggests that these lactobacilli are important for bee health. Social transmission helps maintain associations between these bees and their respective microbiota. To determine whether lactobacilli associated with social hymenopteran hosts are generally host specific, we gathered publicly available Lactobacillus 16S rRNA gene sequences, along with Lactobacillus sequences from 454 pyrosequencing surveys of six other hymenopteran species (three sweat bees and three ants). We determined the comparative secondary structural models of 16S rRNA, which allowed us to accurately align the entire 16S rRNA gene, including fast-evolving regions. BLAST searches and maximum-likelihood phylogenetic reconstructions confirmed that honey and bumble bees have host-specific Lactobacillus associates. Regardless of colony size or within-colony oral sharing of food (trophallaxis), sweat bees and ants associate with lactobacilli that are closely related to those found in vertebrate hosts or in diverse environments. Why honey and bumble bees associate with host-specific lactobacilli while other social Hymenoptera do not remains an open question. Lactobacilli are known to inhibit the growth of other microbes and can be beneficial whether they are coevolved with their host or are recruited by the host from environmental sources through mechanisms of partner choice.

A unique box in 28S rRNA is shared by the enigmatic insect order Zoraptera and Dictyoptera.

The position of the Zoraptera remains one of the most challenging and uncertain concerns in ordinal-level phylogenies of the insects. Zoraptera have been viewed as having a close relationship with five different groups of Polyneoptera, or as being allied to the Paraneoptera or even Holometabola. Although rDNAs have been widely used in phylogenetic studies of insects, the application of the complete 28S rDNA are still scattered in only a few orders. In this study, a secondary structure model of the complete 28S rRNAs of insects was reconstructed based on all orders of Insecta. It was found that one length-variable region, D3-4, is particularly distinctive. The length and/or sequence of D3-4 is conservative within each order of Polyneoptera, but it can be divided into two types between the different orders of the supercohort, of which the enigmatic order Zoraptera and Dictyoptera share one type, while the remaining orders of Polyneoptera share the other. Additionally, independent evidence from phylogenetic results support the clade (Zoraptera+Dictyoptera) as well. Thus, the similarity of D3-4 between Zoraptera and Dictyoptera can serve as potentially valuable autapomorphy or synapomorphy in phylogeny reconstruction. The clades of (Plecoptera+Dermaptera) and ((Grylloblattodea+Mantophasmatodea)+(Embiodea+Phasmatodea)) were also recovered in the phylogenetic study. In addition, considering the other studies based on rDNAs, this study reached the highest congruence with previous phylogenetic studies of Holometabola based on nuclear protein coding genes or morphology characters. Future comparative studies of secondary structures across deep divergences and additional taxa are likely to reveal conserved patterns, structures and motifs that can provide support for major phylogenetic lineages.

Genome-wide analyses of Epstein-Barr virus reveal conserved RNA structures and a novel stable intronic sequence RNA.

BackgroundEpstein-Barr virus (EBV) is a human herpesvirus implicated in cancer and autoimmune disorders. Little is known concerning the roles of RNA structure in this important human pathogen. This study provides the first comprehensive genome-wide survey of RNA and RNA structure in EBV.ResultsNovel EBV RNAs and RNA structures were identified by computational modeling and RNA-Seq analyses of EBV. Scans of the genomic sequences of four EBV strains (EBV-1, EBV-2, GD1, and GD2) and of the closely related Macacine herpesvirus 4 using the RNAz program discovered 265 regions with high probability of forming conserved RNA structures. Secondary structure models are proposed for these regions based on a combination of free energy minimization and comparative sequence analysis. The analysis of RNA-Seq data uncovered the first observation of a stable intronic sequence RNA (sisRNA) in EBV. The abundance of this sisRNA rivals that of the well-known and highly expressed EBV-encoded non-coding RNAs (EBERs).ConclusionThis work identifies regions of the EBV genome likely to generate functional RNAs and RNA structures, provides structural models for these regions, and discusses potential functions suggested by the modeled structures. Enhanced understanding of the EBV transcriptome will guide future experimental analyses of the discovered RNAs and RNA structures.

Statistical Analysis of SHAPE-Directed RNA Secondary Structure Modeling

Statistical Analysis of SHAPE-Directed RNA Secondary Structure Modeling

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots

Phylogenetic Position Of The Monogenean Malayanodiscoides Bihamuli Lim Et Furtado, 1986 Inferred From Sequence And Secondary Structure Of 28S Rdna

Abstract The present study is a brief description of the morphology and molecular phylogeny of Malayanodiscoides bihamuli Lim and Furtado, 1986 infecting gill filaments of fish Notopterus chitala (Hamilton). The phylogenetic study was made of M. bihamuli and closely related taxa using DNA sequence data obtained from 28S rDNA region. Morphology as well as molecular phylogeny strongly supports the establishment of genus Malayanodiscoides and also demonstrates its close relationship with other genera of class Monogenea. In addition, the 28S secondary structure model was predicted and found to serve as a useful tool for reconstruction of optimal alignment and can be used as an additional source of data incorporating structural parameters of molecules for the study of phylogeny. Application of the secondary 28S structure data allows a more resolved and realistic picture of relationships. Results also demonstrate the phylogenetic utility of the 28S sequence secondary structure data for inferences at higher taxonomic levels.

Japanese development and testing of the Network Establishment Practices Scale for Community and Public Health Nurses

The practices required by community and public health nurses to establish community networks mainly involve communicative competencies. Assessment through development and testing of such competencies is necessary for community and public health nurse educators and practitioners around the world to create and maintain a mutual support network. The purpose of this study was to develop and test a scale for community and public health nurse practices to establish and maintain community networks, and to then determine construct validity in a factorial structure model. The participants were 3970 community and public health nurses in Japan. A 43-item list was developed from a literature review, individual interviews, and repeated examinations. The secondary structural model consisted of four factors with 21 items. The internal consistency of the 21 items was highly reliable (Cronbach's α = 0.915). Confirmatory factor analysis by structural equation modeling showed the fit criteria to be statistically significant. Attributes of the community and public health nurses (age, years of experience, work municipalities, work positions, and educational institutions) showed significant relationships with the scale scores. The findings validated the efficacy of the Network Establishment Practices Scale to assess community and public health nurse practices to establish community networks.

Direct Updating of an RNA Base-Pairing Probability Matrix with Marginal Probability Constraints

A base-pairing probability matrix (BPPM) stores the probabilities for every possible base pair in an RNA sequence and has been used in many algorithms in RNA informatics (e.g., RNA secondary structure prediction and motif search). In this study, we propose a novel algorithm to perform iterative updates of a given BPPM, satisfying marginal probability constraints that are (approximately) given by recently developed biochemical experiments, such as SHAPE, PAR, and FragSeq. The method is easily implemented and is applicable to common models for RNA secondary structures, such as energy-based or machine-learning-based models. In this article, we focus mainly on the details of the algorithms, although preliminary computational experiments will also be presented.

Systematics and biogeography of the non-viny grape relativeLeea(Vitaceae)

Leea, sometimes treated as the monogeneric family Leeaceae, is sister to the rest of the grape family, Vitaceae, but its systematics is poorly known. Phylogenetic relationships in Leea were reconstructed with parsimony and Bayesian methods using nuclear ribosomal sequences to assess species circumscriptions, morphological evolution and biogeography. The internal transcribed spacer secondary structure model for Leea facilitated homology assessments during sequence alignment. Nine morphological characters were mapped onto the phylogenetic tree. Four major clades in Leea were supported, with L. asiatica s.l. (=clade I) as the earliest diverging clade and having plesiomorphic free stamens. Clade II, which includes the prickle-bearing species, is sister to clade III, which includes species with comparatively large flowers. Clade IV, sister to clade II + III, was resolved into four subclades. Each subclade included accessions of L. indica and L. guineensis intermixed with six other morphologically distinct species, showing the polyphyly of these two species as currently circumscribed. Flower colour, previously used to characterize species, was shown to be unreliable for species identification. Dating analyses estimated that Leea originated in Indochina in the Late Cretaceous (65–86.19 Mya, 95% highest posterior density). The members of the major clades later spread to India, Africa, Madagascar, South-East (SE) Asia and tropical Australasia. Major species diversification occurred in the Neogene, when dynamic environmental and geological changes in SE Asia presented new ecological niches.

Classifying multigraph models of secondary RNA structure using graph-theoretic descriptors.

The prediction of secondary RNA folds from primary sequences continues to be an important area of research given the significance of RNA molecules in biological processes such as gene regulation. To facilitate this effort, graph models of secondary structure have been developed to quantify and thereby characterize the topological properties of the secondary folds. In this work we utilize a multigraph representation of a secondary RNA structure to examine the ability of the existing graph-theoretic descriptors to classify all possible topologies as either RNA-like or not RNA-like. We use more than one hundred descriptors and several different machine learning approaches, including nearest neighbor algorithms, one-class classifiers, and several clustering techniques. We predict that many more topologies will be identified as those representing RNA secondary structures than currently predicted in the RAG (RNA-As-Graphs) database. The results also suggest which descriptors and which algorithms are more informative in classifying and exploring secondary RNA structures.

Rfam 11.0: 10 years of RNA families

The Rfam database (available via the website at http://rfam.sanger.ac.uk and through our mirror at http://rfam.janelia.org) is a collection of non-coding RNA families, primarily RNAs with a conserved RNA secondary structure, including both RNA genes and mRNA cis-regulatory elements. Each family is represented by a multiple sequence alignment, predicted secondary structure and covariance model. Here we discuss updates to the database in the latest release, Rfam 11.0, including the introduction of genome-based alignments for large families, the introduction of the Rfam Biomart as well as other user interface improvements. Rfam is available under the Creative Commons Zero license.

Secondary structure improves OTU assignments of 16S rRNA gene sequences

In contrast to the commentary of Wang et al. (2011), I contend that the inclusion of secondary structure information provides a faster and more robust analysis when assigning sequences to operational taxonomic units (OTUs). The authors ignored the long history of molecular phylogenetics, where multiple sequence alignments are preferred to pairwise sequence alignments because multiple sequence alignments preserve positional homology across all sequences, not just pairs of sequences (Durbin et al., 1998). Furthermore, profile-based alignments that incorporate the secondary structure of the 16S rRNA molecule are preferred because they provide additional biological information that strengthens the confidence that positional homology is being conserved (Keller et al., 2010). The degree to which these theoretical points are important is contested. I contend that profile-based alignments using curated secondary structure models combined with hierarchical clustering algorithms should be the standard method of assigning 16S rRNA gene sequences to OTUs. I will justify my position by re-emphasizing my previous work, which the Wang commentary ignored, and illustrate several incorrect conclusions that they reached in supporting their thesis (Schloss 2009, 2010, 2011; Schloss and Westcott, 2011).

PCR-based molecular characterization, phylogenetic analysis and secondary structure of the 28S rDNA of Thaparocleidus wallagonius (Monogenea: Dactylogyridae) - the most primitive species of this genus from India.

Species of the monogenean genus Thaparocleidus are specific to freshwater siluriform fish. The infection caused by these gill parasites are a major health problem to fish. But, to focus the control strategies of these parasites, first it is important to establish an accurate discrimination by molecular methods. In the present study, phylogenetic and structural analysis of 28S region of ribosomal DNA of T. wallagonius species collected from fish Wallago attu from Meerut (U.P.), India, was carried out. In the first step, we amplified, sequenced 28S region of ribosomal DNA of T. wallagonius to establish the phylogenetic relationship with other species of this genus. T. wallagonius found on gill filaments of fish W. attu, is the most primitive parasite of this genus from India, was unequivocally discriminate from other species of the same genus in this study. A secondary-structure model of the large subunit rDNA was also predicted using a combined comparative and thermodynamic approach. Molecular morphometric and phylogenetic relationship of T. wallagonius are discussed in detailed that based on molecular analysis using bioinformatic tools.

NMR Studies of HAR1 RNA Secondary Structures Reveal Conformational Dynamics in the Human RNA

Comparative genomics has shown that noncoding RNAs can display substantial differences between humans and chimpanzees. The human accelerated region 1 (HAR1) is a section in the human genome that exhibits the most strongly accelerated rate of nucleotide substitution in relation to the chimpanzee genome. It is associated with higher cognitive functions in human brains. The HAR1 region of the HAR1F gene is transcribed into a 118 nt noncoding RNA. We provide experimental data to validate available secondary structure models of chimpanzee and human HAR1 RNA by utilizing CD and NMR spectroscopy and applying a "divide-and-conquer" strategy. The mutations lead to more dynamic secondary and tertiary structure in the human HAR1 RNA, presumably as part of its function. We have also determined NMR solution structures of helix H1 as the most conserved part of the chimpanzee and human HAR1 RNAs. Helix H1 contains a GAA asymmetric internal loop, the structure of which had not been solved previously. 37 nt chimpanzee and human RNA fragments (c37 and h37 RNAs) differ in a single base pair. h37 RNA folds into a slightly more stable and rigid structure than c37 RNA. Both NMR structures show structural heterogeneity of the residues corresponding to the GAA loop.

Quantitative Dimethyl Sulfate Mapping for Automated RNA Secondary Structure Inference

For decades, dimethyl sulfate (DMS) mapping has informed manual modeling of RNA structure in vitro and in vivo. Here, we incorporate DMS data into automated secondary structure inference using an energy minimization framework developed for 2'-OH acylation (SHAPE) mapping. On six noncoding RNAs with crystallographic models, DMS-guided modeling achieves overall false negative and false discovery rates of 9.5% and 11.6%, respectively, comparable to or better than those of SHAPE-guided modeling, and bootstrapping provides straightforward confidence estimates. Integrating DMS-SHAPE data and including 1-cyclohexyl(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate (CMCT) reactivities provide small additional improvements. These results establish DMS mapping, an already routine technique, as a quantitative tool for unbiased RNA secondary structure modeling.

SAVoR: a server for sequencing annotation and visualization of RNA structures

RNA secondary structure is required for the proper regulation of the cellular transcriptome. This is because the functionality, processing, localization and stability of RNAs are all dependent on the folding of these molecules into intricate structures through specific base pairing interactions encoded in their primary nucleotide sequences. Thus, as the number of RNA sequencing (RNA-seq) data sets and the variety of protocols for this technology grow rapidly, it is becoming increasingly pertinent to develop tools that can analyze and visualize this sequence data in the context of RNA secondary structure. Here, we present Sequencing Annotation and Visualization of RNA structures (SAVoR), a web server, which seamlessly links RNA structure predictions with sequencing data and genomic annotations to produce highly informative and annotated models of RNA secondary structure. SAVoR accepts read alignment data from RNA-seq experiments and computes a series of per-base values such as read abundance and sequence variant frequency. These values can then be visualized on a customizable secondary structure model. SAVoR is freely available at http://tesla.pcbi.upenn.edu/savor.