RNAstructure: software for RNA secondary structure prediction and analysis

<p>Abstract</p> <p>Background</p> <p>To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence.</p> <p>Results</p> <p>RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained.</p> <p>Conclusion</p> <p>The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at <url>http://rna.urmc.rochester.edu/RNAstructure.html</url>.</p

Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

BACKGROUND: We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm. RESULTS: We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. CONCLUSION: Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding. Constraining on alignment is a straightforward method of reducing the runtime and memory requirements of the algorithm. Five practical implementations of the pairwise Sankoff algorithm – this work (Consan), David Mathews' Dynalign, Ian Holmes' Stemloc, Ivo Hofacker's PMcomp, and Jan Gorodkin's FOLDALIGN – have comparable overall performance with different strengths and weaknesses

Metabolic adaptation drives arsenic trioxide resistance in acute promyelocytic leukemia.

Acquired genetic mutations can confer resistance to arsenic trioxide (ATO) in the treatment of acute promyelocytic leukemia (APL). However, such resistance-conferring mutations are rare and do not explain most disease recurrence seen in the clinic. We have generated stable ATO-resistant promyelocytic cell lines that are also less sensitive to ATRA and the combination of ATO and ATRA compared to the sensitive cell line. Characterization of these in-house generated resistant cell lines showed significant differences in immunophenotype, drug transporter expression, anti-apoptotic protein dependence, and PML-RARA mutation. Gene expression profiling revealed prominent dysregulation of the cellular metabolic pathways in these ATO resistant APL cell lines. Glycolytic inhibition by 2-DG was sufficient and comparable to the standard of care (ATO) in targeting the sensitive APL cell line. 2-DG was also effective in the in vivo transplantable APL mouse model; however, it did not affect the ATO resistant cell lines. In contrast, the resistant cell lines were significantly affected by compounds targeting the mitochondrial respiration when combined with ATO, irrespective of the ATO resistance-conferring genetic mutations or the pattern of their anti-apoptotic protein dependency. Our data demonstrate that the addition of mitocans in combination with ATO can overcome ATO resistance. We further show that this combination has the potential in the treatment of non-M3 AML and relapsed APL. The translation of this approach in the clinic needs to be explored further

Lost & Found Dark Matter in Elliptical Galaxies

There is strong evidence that the mass in the Universe is dominated by dark matter, which exerts gravitational attraction but whose exact nature is unknown. In particular, all galaxies are believed to be embedded in massive haloes of dark matter. This view has recently been challenged by surprisingly low random stellar velocities in the outskirts of ordinary elliptical galaxies, which were interpreted as indicating a lack of dark matter (Mendez et al. 2001; Romanowsky et al. 2003). Here we show that the low velocities are in fact compatible with galaxy formation in dark-matter haloes. Using numerical simulations of disc-galaxy mergers, we find that the stellar orbits in the outer regions of the resulting ellipticals are very elongated. These stars were torn by tidal forces from their original galaxies during the first close passage and put on outgoing trajectories. The elongated orbits, combined with the steeply falling density profile of the observed tracers, explain the observed low velocities even in the presence of large amounts of dark matter. Projection effects when viewing a triaxial elliptical can lead to even lower observed velocities along certain lines of sight.Comment: Letter to Nature, 13+15 pages, 2+11 figures, improved text, extended Supplementary Information adde

Maximum expected accuracy structural neighbors of an RNA secondary structure

International audienceBACKGROUND: Since RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches; nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure. RESULTS: Given an arbitrary RNA secondary structure S₀ for an RNA nucleotide sequence a = a₁,..., a(n), we say that another secondary structure S of a is a k-neighbor of S₀, if the base pair distance between S₀ and S is k. In this paper, we prove that the Boltzmann probability of all k-neighbors of the minimum free energy structure S₀ can be approximated with accuracy ε and confidence 1 - p, simultaneously for all 0 ≤ k N(ε,p,K)=Φ⁻¹(p/2K)²/4ε², where Φ(z) is the cumulative distribution function (CDF) for the standard normal distribution. We go on to describe the algorithm RNAborMEA, which for an arbitrary initial structure S₀ and for all values 0 ≤ k < K, computes the secondary structure MEA(k), having maximum expected accuracy over all k-neighbors of S₀. Computation time is O(n³ * K²), and memory requirements are O(n² * K). We analyze a sample TPP riboswitch, and apply our algorithm to the class of purine riboswitches. CONCLUSIONS: The approximation of RNAbor by sampling, with rigorous bound on accuracy, together with the computation of maximum expected accuracy k-neighbors by RNAborMEA, provide additional tools toward conformational switch detection. Results from RNAborMEA are quite distinct from other tools, such as RNAbor, RNAshapes and paRNAss, hence may provide orthogonal information when looking for suboptimal structures or conformational switches. Source code for RNAborMEA can be downloaded from http://sourceforge.net/projects/rnabormea/ or http://bioinformatics.bc.edu/clotelab/RNAborMEA/

Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions

Racial/Ethnic Disparities in Exercise and Dietary Behaviors of Middle-Aged and Older Adults

BackgroundDifferences in health behaviors may be important contributors to racial/ethnic disparities in the health status of adults. Studies to date have not compared whether there are health behavior differences in exercise and dietary behaviors among middle-age and older adults in the four largest racial/ethnic categories.ObjectiveTo investigate racial/ethnic differences in exercise and dietary behaviors of middle-aged and older adults.DesignWe used data from the 2007 California Health Interview Survey. Multivariable logistic regression was used to examine interactions between age and race/ethnicity in predicting two categories of health behaviors. Analyses were conducted adjusting for sociodemographic characteristics, health insurance status, and healthcare utilization.ParticipantsA population-based sample of 33,189 California adults 45 years old and older: 26,522 non-Hispanic whites, 1,686 African American/blacks, 2,565 Asian/Pacific Islanders (1,741 English-proficient; 824 limited English-proficient), and 2,416 Latinos (1,538 English-proficient; 878 limited English-proficient).Main measuresSelf-report leisure-time physical activity (moderate and vigorous) and daily consumption of fruits and vegetables.Key resultsRacial/ethnic minorities generally engaged in less healthy exercise and dietary behaviors than whites, with differences more pronounced in middle adulthood. The disparities were the greatest among English-proficient minorities. Specifically, among middle-aged respondents, all racial/ethnic minorities engaged in less vigorous physical activity than whites (ORs range = 0.28 to 0.73; 95% CI range = 0.16-1.00). Additionally, middle-aged, English-proficient minorities engaged in less moderate physical activity compared to whites (ORs range =0.57 to 0.67; 95% CI range = 0.45-0.79). Furthermore, middle-aged, English-proficient Latinos had a poorer diet than whites (OR = 0.54; 0.39-0.75). Few significant racial/ethnic differences emerged in the exercise and dietary behaviors of older adults.ConclusionsRacial/ethnic disparities in exercise and dietary behaviors are most notable among middle-aged, acculturated minorities. Results highlight the need to promote positive exercise and dietary behaviors during critical preventive ages, when racial/ethnic disparities are large and the potential to prevent chronic disease is great

Analysis of pmpD Expression and PmpD Post-Translational Processing during the Life Cycle of Chlamydia trachomatis Serovars A, D, and L2

BACKGROUND: The polymorphic membrane protein D (PmpD) in Chlamydia is structurally similar to autotransporter proteins described in other bacteria and may be involved in cellular and humoral protective immunity against Chlamydia. The mechanism of PmpD post-translational processing and the role of its protein products in the pathogenesis of chlamydial infection have not been very well elucidated to date. METHODOLOGY/PRINCIPAL FINDINGS: Here we examined the expression and post-translational processing of the protein product of the pmpD gene during the life cycle of C. trachomatis serovars A, D, and L2. Each of these three serovars targets different human organs and tissues and encodes a different pmpD gene nucleotide sequence. Our quantitative real-time reverse transcription polymerase chain reaction results demonstrate that the pmpD gene is up-regulated at 12-24 hours after infection regardless of the Chlamydia serovar. This up-regulation is coincidental with the period of exponential growth and replication of reticulate bodies (RB) of Chlamydia and indicates a probable similarity in function of pmpD in serovars A, D, and L2 of Chlamydia. Using mass spectrometry analysis, we identified the protein products of post-translational processing of PmpD of C. trachomatis serovar L2 and propose a double pathway model for PmpD processing, with one cleavage site between the passenger and autotransporter domains and the other site in the middle of the passenger domain. Notably, when Chlamydia infected culture cells were subjected to low (28 degrees C) temperature, PmpD post-translational processing and secretion was found to be uninhibited in the resulting persistent infection. In addition, confocal microscopy of cells infected with Chlamydia confirms our earlier hypothesis that PmpD is secreted outside Chlamydia and its secretion increases with growth of the chlamydial inclusion. CONCLUSION/SIGNIFICANCE: The results of this current study involving multiple Chlamydia serovars support the general consensus that the pmpD gene is maximally expressed at mid infection and provide new information about PmpD as an autotransporter protein which is post-translationally processed and secreted outside Chlamydia during normal and low temperature induced persistent chlamydial infection

Hybridization thermodynamics of NimbleGen Microarrays

Background While microarrays are the predominant method for gene expression profiling, probe signal variation is still an area of active research. Probe signal is sequence dependent and affected by probe-target binding strength and the competing formation of probe-probe dimers and secondary structures in probes and targets. Results We demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and the different competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the melting temperature Tm was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that fully considered competing structures was twice as powerful a predictor of probe signal variation. We show that this was largely due to the effects of secondary structures in the probe and target molecules. The predictive power of the strength of these intramolecular structures was already comparable to that of the melting temperature or the free energy of the probe-target duplex. Conclusions This analysis illustrates the importance of considering both the effects of probe-target binding strength and the different competing structures. For specific hybridization, the secondary structures of probe and target molecules turn out to be at least as important as the probe-target binding strength for an understanding of the observed microarray signal intensities. Besides their relevance for the design of new arrays, our results demonstrate the value of improving thermodynamic models for the read-out and interpretation of microarray signals

Diversity of 23S rRNA Genes within Individual Prokaryotic Genomes

The concept of ribosomal constraints on rRNA genes is deduced primarily based on the comparison of consensus rRNA sequences between closely related species, but recent advances in whole-genome sequencing allow evaluation of this concept within organisms with multiple rRNA operons. was the only species in which intragenomic diversity >3% was observed among 4 paralogous 23S rRNA genes.These findings indicate tight ribosomal constraints on individual 23S rRNA genes within a genome. Although classification using primary 23S rRNA sequences could be erroneous, significant diversity among paralogous 23S rRNA genes was observed only once in the 184 species analyzed, indicating little overall impact on the mainstream of 23S rRNA gene-based prokaryotic taxonomy