E-RNAi: a web application for the multi-species design of RNAi reagents—2010 update

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files

OligoWalk: an online siRNA design tool utilizing hybridization thermodynamics

Given an mRNA sequence as input, the OligoWalk web server generates a list of small interfering RNA (siRNA) candidate sequences, ranked by the probability of being efficient siRNA (silencing efficacy greater than 70%). To accomplish this, the server predicts the free energy changes of the hybridization of an siRNA to a target mRNA, considering both siRNA and mRNA self-structure. The free energy changes of the structures are rigorously calculated using a partition function calculation. By changing advanced options, the free energy changes can also be calculated using less rigorous lowest free energy structure or suboptimal structure prediction methods for the purpose of comparison. Considering the predicted free energy changes and local siRNA sequence features, the server selects efficient siRNA with high accuracy using a support vector machine. On average, the fraction of efficient siRNAs selected by the server that will be efficient at silencing is 78.6%. The OligoWalk web server is freely accessible through internet at http://rna.urmc.rochester.edu/servers/oligowalk

Whole genome functional analysis identifies novel components required for mitotic spindle integrity in human cells

A loss-of-function screen for siRNAs that arrest human cells in metaphase reveals genes involved in mitotic spindle integrity

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Exogenous short interfering RNAs (siRNAs) induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs), General Linear Models (GLMs) and Support Vector Machines (SVMs). Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are not consistent across learning techniques, suggesting care should be taken in the interpretation of feature relevance. In the models developed here, there are statistically differentiable combinations of learning techniques and feature mapping methods where the SVM technique under a specific combination of features significantly outperforms all the best combinations of features within the ANN and GLM techniques

Search for eta-mesic 4He in the dd->3He n pi0 and dd->3He p pi- reactions with the WASA-at-COSY facility

The search for 4He-eta bound states was performed with the WASA-at-COSY facility via the measurement of the excitation function for the dd->3He n pi0 and dd->3He p pi- processes. The beam momentum was varied continuously between 2.127 GeV/c and 2.422 GeV/c, corresponding to the excess energy for the dd->4He eta reaction ranging from Q=-70 MeV to Q=30 MeV. The luminosity was determined based on the dd->3He n reaction and quasi-free proton-proton scattering via dd->pp n_spectator n_spectator reactions. The excitation functions determined independently for the measured reactions do not reveal a structure which could be interpreted as a narrow mesic nucleus. Therefore, the upper limits of the total cross sections for the bound state production and decay in dd->(4He-eta)_bound->3He n pi0 and dd->(4He-eta)_bound->3He p pi- processes were determined taking into account the isospin relation between both the channels considered. The results of the analysis depend on the assumptions of the N* momentum distribution in the anticipated mesic-4He. Assuming as in the previous works, that this is identical with the distribution of nucleons bound with 20 MeV in 4He, we determined that (for the mesic bound state width in the range from 5 MeV to 50 MeV) the upper limits at 90% confidence level are about 3 nb and about 6 nb for npi0 and ppi- channels, respectively. However, based on the recent theoretical findings of the N*(1535) momentum distribution in the N*-3He nucleus bound by 3.6 MeV, we find that the WASA-at-COSY detector acceptance decreases and hence the corresponding upper limits are 5 nb and 10 nb for npi0 and ppi- channels respectively.Comment: This article will be submitted to JHE

Selection of hyperfunctional siRNAs with improved potency and specificity

One critical step in RNA interference (RNAi) experiments is to design small interfering RNAs (siRNAs) that can greatly reduce the expression of the target transcripts, but not of other unintended targets. Although various statistical and computational approaches have been attempted, this remains a challenge facing RNAi researchers. Here, we present a new experimentally validated method for siRNA design. By analyzing public siRNA data and focusing on hyperfunctional siRNAs, we identified a set of sequence features as potency selection criteria to build an siRNA design algorithm with support vector machines. Additional bioinformatics filters were also included in the algorithm to increase RNAi specificity by reducing potential sequence cross-hybridization or microRNA-like effects. Independent validation experiments were performed, which indicated that the newly designed siRNAs have significantly improved performance, and worked effectively even at low concentrations. Furthermore, our cell-based studies demonstrated that the siRNA off-target effects were significantly reduced when the siRNAs were delivered into cells at the 3 nM concentration compared to 30 nM. Thus, the capability of our new design program to select highly potent siRNAs also renders increased RNAi specificity because these siRNAs can be used at a much lower concentration. The siRNA design web server is available at http://www5.appliedbiosystems.com/tools/siDesign/

Fundamental differences in the equilibrium considerations for siRNA and antisense oligodeoxynucleotide design

Both siRNA and antisense oligodeoxynucleotides (ODNs) inhibit the expression of a complementary gene. In this study, fundamental differences in the considerations for RNA interference and antisense ODNs are reported. In siRNA and antisense ODN databases, positive correlations are observed between the cost to open the mRNA target self-structure and the stability of the duplex to be formed, meaning the sites along the mRNA target with highest potential to form strong duplexes with antisense strands also have the greatest tendency to be involved in pre-existing structure. Efficient siRNA have less stable siRNA–target duplex stability than inefficient siRNA, but the opposite is true for antisense ODNs. It is, therefore, more difficult to avoid target self-structure in antisense ODN design. Self-structure stabilities of oligonucleotide and target correlate to the silencing efficacy of siRNA. Oligonucleotide self-structure correlations to efficacy of antisense ODNs, conversely, are insignificant. Furthermore, self-structure in the target appears to correlate with antisense ODN efficacy, but such that more effective antisense ODNs appear to target mRNA regions with greater self-structure. Therefore, different criteria are suggested for the design of efficient siRNA and antisense ODNs and the design of antisense ODNs is more challenging

Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency

Motivation: Short interfering RNA (siRNA)-induced RNA interference is an endogenous pathway in sequence-specific gene silencing. The potency of different siRNAs to inhibit a common target varies greatly and features affecting inhibition are of high current interest. The limited success in predicting siRNA potency being reported so far could originate in the small number and the heterogeneity of available datasets in addition to the knowledge-driven, empirical basis on which features thought to be affecting siRNA potency are often chosen. We attempt to overcome these problems by first constructing a meta-dataset of 6483 publicly available siRNAs (targeting mammalian mRNA), the largest to date, and then applying a Bayesian analysis which accommodates feature set uncertainty. A stochastic logistic regression-based algorithm is designed to explore a vast model space of 497 compositional, structural and thermodynamic features, identifying associations with siRNA potency

Search for the decay J/ψ→γ+invisibleJ/\psi\to\gamma + \rm {invisible}

We search for $J/\psi$ radiative decays into a weakly interacting neutral particle, namely an invisible particle, using the $J/\psi$ produced through the process $\psi(3686)\to\pi^+\pi^-J/\psi$ in a data sample of $(448.1\pm2.9)\times 10^6$ $\psi(3686)$ decays collected by the BESIII detector at BEPCII. No significant signal is observed. Using a modified frequentist method, upper limits on the branching fractions are set under different assumptions of invisible particle masses up to 1.2 $\mathrm{\ Ge\kern -0.1em V}/c^2$. The upper limit corresponding to an invisible particle with zero mass is 7.0$\times 10^{-7}$ at the 90\% confidence level

Measurement of proton electromagnetic form factors in e+e−→ppˉe^+e^- \to p\bar{p} in the energy region 2.00-3.08 GeV

The process of $e^+e^- \rightarrow p\bar{p}$ is studied at 22 center-of-mass energy points ($\sqrt{s}$) from 2.00 to 3.08 GeV, exploiting 688.5~pb$^{-1}$ of data collected with the BESIII detector operating at the BEPCII collider. The Born cross section~($\sigma_{p\bar{p}}$) of $e^+e^- \rightarrow p\bar{p}$ is measured with the energy-scan technique and it is found to be consistent with previously published data, but with much improved accuracy. In addition, the electromagnetic form-factor ratio ($|G_{E}/G_{M}|$) and the value of the effective ($|G_{\rm{eff}}|$), electric ($|G_E|$) and magnetic ($|G_M|$) form factors are measured by studying the helicity angle of the proton at 16 center-of-mass energy points. $|G_{E}/G_{M}|$ and $|G_M|$ are determined with high accuracy, providing uncertainties comparable to data in the space-like region, and $|G_E|$ is measured for the first time. We reach unprecedented accuracy, and precision results in the time-like region provide information to improve our understanding of the proton inner structure and to test theoretical models which depend on non-perturbative Quantum Chromodynamics