Stability of ribonucleic acid double-stranded helices

Molecular Detection of Respiratory Tract Viruses in Chickens at the Point of Need by Loop-Mediated Isothermal Amplification (LAMP)

Accurate and timely molecular diagnosis of respiratory diseases in chickens is essential for implementing effective control measures, preventing the spread of diseases within poultry flocks, minimizing economic loss, and guarding food security. Traditional molecular diagnostic methods like polymerase chain reaction (PCR) require expensive equipment and trained personnel, limiting their use to centralized labs with a significant delay between sample collection and results. Loop-mediated isothermal amplification (LAMP) of nucleic acids offers an attractive alternative for detecting respiratory viruses in broiler chickens with sensitivity comparable to that of PCR. LAMP's main advantages over PCR are its constant incubation temperature (∼65 °C), high amplification efficiency, and contaminant tolerance, which reduce equipment complexity, cost, and power consumption and enable instrument-free tests. This review highlights effective LAMP methods and variants that have been developed for detecting respiratory viruses in chickens at the point of need.

Atomistic simulations of RNA duplex thermal denaturation: Sequence- and forcefield-dependence

Double-stranded RNA is the end-product of template-based replication, and is also the functional state of some biological RNAs. Similarly to proteins and DNA, they can be denatured by temperature, with important physiological and technological implications. Here, we use an in silico strategy to probe the thermal denaturation of RNA duplexes. Following previous results that were obtained on a few different duplexes, and which nuanced the canonical 2-state picture of nucleic acid denaturation, we here specifically address three different aspects that greatly improve our description of the temperature-induced dsRNA separation. First, we investigate the effect of the spatial distribution of weak and strong base-pairs among the duplex sequence. We show that the deviations from the two-state dehybridization mechanism are more pronounced when a strong core is flanked with weak extremities, while duplexes with a weak core but strong extremities exhibit a two-state behavior, which can be explained by the key role played by base fraying. This was later verified by generating artificial hairpin or circular states containing one or two locked duplex extremities, which results in an important reinforcement of the entire HB structure of the duplex and higher melting temperatures. Finally, we demonstrate that our results are little sensitive to the employed combination of RNA and water forcefields. The trends in thermal stability among the different sequences as well as the observed unfolding mechanisms (and the deviations from a two-state scenario) remain the same regardless of the employed atomistic models. However, our study points to possible limitations of recent reparametrizations of the Amber RNA forcefield, which sometimes results in duplexes that readily denature under ambient conditions, in contradiction with available experimental results.

Nearest-neighbour parametrization of DNA single, double and triple mismatches at low sodium concentration

DNA mismatches, that is, base pairs different from the canonical AT and CG, are involved in numerous biological processes and can be a problem for technological applications such as PCR amplification. The nearest-neighbour (NN) model is the standard approach for predicting melting temperatures and is used in methods of secondary structure predictions and modelling of hybridization kinetics. However, despite its biological and technological importance, existing NN parameters that include DNA mismatches are incomplete, and those available were obtained from a limited set of melting temperature at high sodium concentration. To our knowledge, there is currently no NN set of parameters for up to three mismatches covering all configurations at low sodium concentrations. Here, we are applying the NN model to a large set of 4096 published melting temperatures, covering all combinations of single, double and triple mismatches. Dealing with such a large set of temperature is challenging in several ways, bringing new methodological problems. Here, optimizing a large number of 252 independent parameters has required the development of a new method where we readjust the seed parameters using the definition of the Gibbs free energy. The new parameters predict the training set within 1.1 °C and the validation set to 2.7 °C.

Rational Design of DNA Hydrogels Based on Molecular Dynamics of Polymers

In recent years, DNA has emerged as a fascinating building material to engineer hydrogel due to its excellent programmability, which has gained considerable attention in biomedical applications. Understanding the structure-property relationship and underlying molecular determinants of DNA hydrogel is essential to precisely tailor its macroscopic properties at molecular level. In this review, the rational design principles of DNA molecular networks based on molecular dynamics of polymers on the temporal scale, which can be engineered via the backbone rigidity and crosslinking kinetics, are highlighted. By elucidating the underlying molecular mechanisms and theories, it is aimed to provide a comprehensive overview of how the tunable DNA backbone rigidity and the crosslinking kinetics lead to desirable macroscopic properties of DNA hydrogels, including mechanical properties, diffusive permeability, swelling behaviors, and dynamic features. Furthermore, it is also discussed how the tunable macroscopic properties make DNA hydrogels promising candidates for biomedical applications, such as cell culture, tissue engineering, bio-sensing, and drug delivery.

Competitive Influence of Alkali Metals in the Ion Atmosphere on Nucleic Acid Duplex Stability

The nonspecific atmosphere around nucleic acids, often termed the ion atmosphere, encompasses a collection of weak ion-nucleic acid interactions. Although nonspecific, the ion atmosphere has been shown to influence nucleic acid folding and structural stability. Studies investigating the composition of the ion atmosphere have shown competitive occupancy of the atmosphere between metal ions in the same solution. Many studies have investigated single ion effects on nucleic acid secondary structure stability; however, no comprehensive studies have investigated how the competitive occupancy of mixed ions in the ion atmosphere influences nucleic acid secondary structure stability. Here, six oligonucleotides were optically melted in buffers containing molar quantities, or mixtures, of either XCl (X = Li, K, Rb, or Cs) or NaCl. A correction factor was developed to better predict RNA duplex stability in solutions containing mixed XCl/NaCl. For solutions containing a 1:1 mixture of XCl/NaCl, one alkali metal chloride contributed more to duplex stability than the other. Overall, there was a 54% improvement in predictive capabilities with the correction factor compared with the standard 1.0 M NaCl nearest-neighbor models. This correction factor can be used in models to better predict RNA secondary structure in solutions containing mixed XCl/NaCl.

VarGibbs Usage in the Optimization of Nearest-Neighbor Parameters and Prediction of Melting Temperature of RNA Duplexes

The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.

A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools

RNA biology has risen to prominence after a remarkable discovery of diverse functions of noncoding RNA (ncRNA). Most untranslated transcripts often exert their regulatory functions into RNA-RNA complexes via base pairing with complementary sequences in other RNAs. An interplay between RNAs is essential, as it possesses various functional roles in human cells, including genetic translation, RNA splicing, editing, ribosomal RNA maturation, RNA degradation and the regulation of metabolic pathways/riboswitches. Moreover, the pervasive transcription of the human genome allows for the discovery of novel genomic functions via RNA interactome investigation. The advancement of experimental procedures has resulted in an explosion of documented data, necessitating the development of efficient and precise computational tools and algorithms. This review provides an extensive update on RNA-RNA interaction (RRI) analysis via thermodynamic- and comparative-based RNA secondary structure prediction (RSP) and RNA-RNA interaction prediction (RIP) tools and their general functions. We also highlighted the current knowledge of RRIs and the limitations of RNA interactome mapping via experimental data. Then, the gap between RSP and RIP, the importance of RNA homologues, the relationship between pseudoknots, and RNA folding thermodynamics are discussed. It is hoped that these emerging prediction tools will deepen the understanding of RNA-associated interactions in human diseases and hasten treatment processes.

Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery

Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life sciences, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction in recent years. Historically, thermodynamics-based methods were widely employed for the prediction of RNA secondary structures; however, machine learning-based approaches have demonstrated remarkable advancements in recent years, enabling more accurate predictions. Consequently, the precision of sequence analysis pertaining to RNA secondary structures, such as RNA-protein interactions, has also been enhanced, making a substantial contribution to the field of RNA biology. Additionally, artificial intelligence and machine learning are also introducing technical innovations in the analysis of RNA-small molecule interactions for RNA-targeted drug discovery and in the design of RNA aptamers, where RNA serves as its own ligand. This review will highlight recent trends in the prediction of RNA secondary structure, RNA aptamers and RNA drug discovery using machine learning, deep learning and related technologies, and will also discuss potential future avenues in the field of RNA informatics.

Toward a Molecular Mechanism of Complementary RNA Duplexes Denaturation

RNA duplexes are relatively rare but play very important biological roles. As an end-product of template-based RNA replication, they also have key implications for hypothetical primitive forms of life. Unless they are specifically separated by enzymes, these duplexes denature upon a temperature increase. However, mechanistic and kinetic aspects of RNA (and DNA) duplex thermal denaturation remain unclear at the microscopic level. We propose an in silico strategy that probes the thermal denaturation of RNA duplexes and allows for an extensive conformational space exploration along a wide temperature range with atomistic precision. We show that this approach first accounts for the strong sequence and length dependence of the duplexes melting temperature, reproducing the trends seen in the experiments and predicted by nearest-neighbor models. The simulations are then instrumental at providing a molecular picture of the temperature-induced strand separation. The textbook canonical "all-or-nothing" two-state model, very much inspired by the protein folding mechanism, can be nuanced. We demonstrate that a temperature increase leads to significantly distorted but stable structures with extensive base-fraying at the extremities, and that the fully formed duplexes typically do not form around melting. The duplex separation therefore appears as much more gradual than commonly thought.

Solid-phase synthesis and properties of stereocontrolled boranophosphate/phosphate and phosphorothioate/phosphate chimeric oligouridylates

This study describes the stereoselective synthesis of boranophosphate/phosphate (PB/PO) and phosphorothioate/phosphate (PS/PO) chimeric oligouridylates using the solid-phase method. Oxazaphospholidine monomer was used to construct the stereodefined PB and PS linkages. The study introduces modifications to oligouridylate derivatives in the intended positions with the intended stereochemistry of phosphorous atoms. Additionally, biophysical and biochemical properties of the synthesized oligomers were evaluated. Notably, it was found that a (Sp)-PB/PO chimeric oligouridylate had higher hybridization ability than the unmodified counterpart to an unmodified oligoadenylate. This is the first report that elucidates the effect of both stereochemistry and type of P-modification (PB and PS) on properties of oligoribonucleotides.

RNA Secondary Structure Prediction Based on Energy Models

This chapter introduces the RNA secondary structure prediction based on the nearest neighbor energy model, which is one of the most popular architectures of modeling RNA secondary structure without pseudoknots. We discuss the parameterization and the parameter determination by experimental and machine learning-based approaches as well as an integrated approach that compensates each other's shortcomings. Then, folding algorithms for the minimum free energy and the maximum expected accuracy using the dynamic programming technique are introduced. Finally, we compare the prediction accuracy of the method described so far with benchmark datasets.

Dinuclear complex-induced DNA melting

Dinuclear copper complexes have been designed for molecular recognition in order to selectively bind to two neighboring phosphate moieties in the backbone of double strand DNA. Associated biophysical, biochemical and cytotoxic effects on DNA were investigated in previous works, where atomic force microscopy (AFM) in ambient conditions turned out to be a particular valuable asset, since the complexes influence the macromechanical properties and configurations of the strands. To investigate and scrutinize these effects in more depth from a structural point of view, cutting-edge preparation methods and scanning force microscopy under ultra-high vacuum (UHV) conditions were employed to yield submolecular resolution images. DNA strand mechanics and interactions could be resolved on the single base pair level, including the amplified formation of melting bubbles. Even the interaction of singular complex molecules could be observed. To better assess the results, the appearance of treated DNA is also compared to the behavior of untreated DNA in UHV on different substrates. Finally, we present data from a statistical simulation reasoning about the nanomechanics of strand dissociation. This sort of quantitative experimental insights paralleled by statistical simulations impressively shade light on the rationale for strand dissociations of this novel DNA interaction process, that is an important nanomechanistic key and novel approach for the development of new chemotherapeutic agents.

Identification of highly variable sequence fragments in unmapped reads for rapid bacterial genotyping

BACKGROUND

Bacterial genotyping is a crucial process in outbreak investigation and epidemiological studies. Several typing methods such as pulsed-field gel electrophoresis, multilocus sequence typing (MLST) and whole genome sequencing are currently used in routine clinical practice. However, these methods are costly, time-consuming and have high computational demands. An alternative to these methods is mini-MLST, a quick, cost-effective and robust method based on high-resolution melting analysis. Nevertheless, no standardized approach to identify markers suitable for mini-MLST exists. Here, we present a pipeline for variable fragment detection in unmapped reads based on a modified hybrid assembly approach using data from one sequencing platform.

RESULTS

In routine assembly against the reference sequence, high variable reads are not aligned and remain unmapped. If de novo assembly of them is performed, variable genomic regions can be located in created scaffolds. Based on the variability rates calculation, it is possible to find a highly variable region with the same discriminatory power as seven housekeeping gene fragments used in MLST. In the work presented here, we show the capability of identifying one variable fragment in de novo assembled scaffolds of 21 Escherichia coli genomes and three variable regions in scaffolds of 31 Klebsiella pneumoniae genomes. For each identified fragment, the melting temperatures are calculated based on the nearest neighbor method to verify the mini-MLST's discriminatory power.

CONCLUSIONS

A pipeline for a modified hybrid assembly approach consisting of reference-based mapping and de novo assembly of unmapped reads is presented. This approach can be employed for the identification of highly variable genomic fragments in unmapped reads. The identified variable regions can then be used in efficient laboratory methods for bacterial typing such as mini-MLST with high discriminatory power, fully replacing expensive methods such as MLST. The results can and will be delivered in a shorter time, which allows immediate and fast infection monitoring in clinical practice.

Measuring thermodynamic preferences to form non-native conformations in nucleic acids using ultraviolet melting

Thermodynamic preferences to form non-native conformations are crucial for understanding how nucleic acids fold and function. However, they are difficult to measure experimentally because this requires accurately determining the population of minor low-abundance (<10%) conformations in a sea of other conformations. Here, we show that melting experiments enable facile measurements of thermodynamic preferences to adopt nonnative conformations in DNA and RNA. The key to this "delta-melt" approach is to use chemical modifications to render specific minor non-native conformations the major state. The validity and robustness of delta-melt is established for four different non-native conformations under various physiological conditions and sequence contexts through independent measurements of thermodynamic preferences using NMR. Delta-melt is faster relative to NMR, simple, and cost-effective and enables thermodynamic preferences to be measured for exceptionally low-populated conformations. Using delta-melt, we obtained rare insights into conformational cooperativity, obtaining evidence for significant cooperativity (1.0 to 2.5 kcal/mol) when simultaneously forming two adjacent Hoogsteen base pairs. We also measured the thermodynamic preferences to form G-C⁺ and A-T Hoogsteen and A-T base open states for nearly all 16 trinucleotide sequence contexts and found distinct sequence-specific variations on the order of 2 to 3 kcal/mol. This rich landscape of sequence-specific non-native minor conformations in the DNA double helix may help shape the sequence specificity of DNA biochemistry. Thus, melting experiments can now be used to access thermodynamic information regarding regions of the free energy landscape of biomolecules beyond the native folded and unfolded conformations.

Nearest neighbor rules for RNA helix folding thermodynamics: improved end effects

Nearest neighbor parameters for estimating the folding stability of RNA secondary structures are in widespread use. For helices, current parameters penalize terminal AU base pairs relative to terminal GC base pairs. We curated an expanded database of helix stabilities determined by optical melting experiments. Analysis of the updated database shows that terminal penalties depend on the sequence identity of the adjacent penultimate base pair. New nearest neighbor parameters that include this additional sequence dependence accurately predict the measured values of 271 helices in an updated database with a correlation coefficient of 0.982. This refined understanding of helix ends facilitates fitting terms for base pair stacks with GU pairs. Prior parameter sets treated 5′GGUC3′ paired to 3′CUGG5′ separately from other 5′GU3′/3′UG5′ stacks. The improved understanding of helix end stability, however, makes the separate treatment unnecessary. Introduction of the additional terms was tested with three optical melting experiments. The average absolute difference between measured and predicted free energy changes at 37°C for these three duplexes containing terminal adjacent AU and GU pairs improved from 1.38 to 0.27 kcal/mol. This confirms the need for the additional sequence dependence in the model.

Context-sensitivity of isosteric substitutions of non-Watson-Crick basepairs in recurrent RNA 3D motifs

Sequence variation in a widespread, recurrent, structured RNA 3D motif, the Sarcin/Ricin (S/R), was studied to address three related questions: First, how do the stabilities of structured RNA 3D motifs, composed of non-Watson–Crick (non-WC) basepairs, compare to WC-paired helices of similar length and sequence? Second, what are the effects on the stabilities of such motifs of isosteric and non-isosteric base substitutions in the non-WC pairs? And third, is there selection for particular base combinations in non-WC basepairs, depending on the temperature regime to which an organism adapts? A survey of large and small subunit rRNAs from organisms adapted to different temperatures revealed the presence of systematic sequence variations at many non-WC paired sites of S/R motifs. UV melting analysis and enzymatic digestion assays of oligonucleotides containing the motif suggest that more stable motifs tend to be more rigid. We further found that the base substitutions at non-Watson–Crick pairing sites can significantly affect the thermodynamic stabilities of S/R motifs and these effects are highly context specific indicating the importance of base-stacking and base-phosphate interactions on motif stability. This study highlights the significance of non-canonical base pairs and their contributions to modulating the stability and flexibility of RNA molecules.

Developing an Updated Strategy for Estimating the Free-Energy Parameters in RNA Duplexes

For the last 20 years, it has been common lore that the free energy of RNA duplexes formed from canonical Watson-Crick base pairs (bps) can be largely approximated with dinucleotide bp parameters and a few simple corrective constants that are duplex independent. Additionally, the standard benchmark set of duplexes used to generate the parameters were GC-rich in the shorter duplexes and AU-rich in the longer duplexes, and the length of the majority of the duplexes ranged between 6 and 8 bps. We were curious if other models would generate similar results and whether adding longer duplexes of 17 bps would affect the conclusions. We developed a gradient-descent fitting program for obtaining free-energy parameters-the changes in Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS), and the melting temperature (Tm)-directly from the experimental melting curves. Using gradient descent and a genetic algorithm, the duplex melting results were combined with the standard benchmark data to obtain bp parameters. Both the standard (Turner) model and a new model that includes length-dependent terms were tested. Both models could fit the standard benchmark data; however, the new model could handle longer sequences better. We developed an updated strategy for fitting the duplex melting data.

Nearest-neighbour transition-state analysis for nucleic acid kinetics

We used stopped-flow to monitor hypochromicity for 43 oligonucleotide duplexes to study nucleic acid kinetics and extract transition-state parameters for association and dissociation. Reactions were performed in 1.0 M NaCl (for literature comparisons) and 2.2 mM MgCl2 (PCR conditions). Dissociation kinetics depended on sequence, increased exponentially with temperature, and transition-state parameters inversely correlated to thermodynamic parameters (r = -0.99). Association had no consistent enthalpic component, varied little with temperature or sequence, and poorly correlated to thermodynamic parameters (r = 0.28). Average association rates decreased 78% in MgCl2 compared to NaCl while dissociation was relatively insensitive to ionic conditions. A nearest-neighbour kinetic model for dissociation predicted rate constants within 3-fold of literature values (n = 11). However, a nearest-neighbour model for association appeared overparameterized and inadequate for predictions. Kinetic predictions were used to simulate published high-speed (<1 min) melting analysis and extreme (<2 min) PCR experiments. Melting simulations predicted apparent melting temperatures increase on average 2.4°C when temperature ramp rates increased from 0.1 to 32°C/s, compared to 2.8°C reported in the literature. PCR simulations revealed that denaturation kinetics are dependent on the thermocycling profile. Simulations overestimated annealing efficiencies at shorter annealing times and suggested that polymerase interactions contribute to primer-template complex stability at extension temperatures.

Watson-Crick versus Hoogsteen Base Pairs: Chemical Strategy to Encode and Express Genetic Information in Life

Nucleic acids typically form a double helix structure through Watson-Crick base-pairing. In contrast, non-Watson-Crick base pairs can form other three-dimensional structures. Although it is well-known that Watson-Crick base pairs may be more unstable than non-Watson-Crick base pairs under some conditions, the importance of non-Watson-Crick base pairs has not been widely examined. Hoogsteen base pairs, the non-Watson-Crick base pairs, contain important hydrogen-bond patterns that form the helices of nucleic acids, such as in Watson-Crick base pairs, and can form non-double helix structures such as triplexes and quadruplexes. In recent years, non-double helix structures have been discovered in cells and were reported to considerably influence gene expression. The complex behavior of these nucleic acids in cells is gradually being revealed, but the underlying mechanisms remain almost unknown.Quantitatively analyzing the structural stability of nucleic acids is important for understanding their behavior. A nucleic acid is an anionic biopolymer composed of a sugar, base, and phosphoric acid. The physicochemical factors that determine the stability of nucleic acid structures include those derived from the interactions of nucleic acid structures and those derived from the environments surrounding nucleic acids. The Gibbs free energy change (ΔG) of structure formation is the most commonly used physicochemical parameter for analyzing quantitative stability. Quantitatively understanding the intracellular behavior of nucleic acids involves describing the formation of nucleic acid structures and related reactions as ΔG. Based on this concept, we quantitatively analyzed the stability of double helix and non-double helix structures and found that decreased water activity, an important factor in crowded cellular conditions, significantly destabilize the formation of Watson-Crick base pairs but stabilizes Hoogsteen base pairs.Here, we describe a physicochemical approach to understand the regulation of gene expressions based on the stability of nucleic acid structures. We developed new methods for predicting the stability of double and non-double helices in various molecular environments by mimicking intracellular environments. Furthermore, the physicochemical approach used for analyzing gene expression regulated by non-double helix structures is useful for not only determining how gene expression is controlled by cellular environments but also for developing new technologies to chemically regulate gene expression by targeting non-double helix structures. We discuss the roles of Watson-Crick and Hoogsteen base pairs in cells based on our results and why both types of base pairing are required for life. Finally, a new concept in nucleic acid science beyond that of Watson and Crick base pairing is introduced.

Statistical physics of DNA hybridization

Deoxyribonucleic acid (DNA) hybridization is at the heart of countless biological and biotechnological processes. Its theoretical modeling played a crucial role, since it has enabled extracting the relevant thermodynamic parameters from systematic measurements of DNA melting curves. In this article, we propose a framework based on statistical physics to describe DNA hybridization and melting in an arbitrary mixture of DNA strands. In particular, we are able to analytically derive closed expressions of the system partition functions for any number N of strings and explicitly calculate them in two paradigmatic situations: (i) a system made of self-complementary sequences and (ii) a system comprising two mutually complementary sequences. We derive the melting curve in the thermodynamic limit (N→∞) of our description, which provides a full justification for the extra entropic contribution that in classic hybridization modeling was required to correctly describe within the same framework the melting of sequences either self-complementary or not. We thus provide a thorough study comprising limit cases and alternative approaches showing how our framework can give a comprehensive view of hybridization and melting phenomena.

New Insights into the Functions of Nucleic Acids Controlled by Cellular Microenvironments

The right-handed double-helical B-form structure (B-form duplex) has been widely recognized as the canonical structure of nucleic acids since it was first proposed by James Watson and Francis Crick in 1953. This B-form duplex model has a monochronic and static structure and codes genetic information within a sequence. Interestingly, DNA and RNA can form various non-canonical structures, such as hairpin loops, left-handed helices, triplexes, tetraplexes of G-quadruplex and i-motif, and branched junctions, in addition to the canonical structure. The formation of non-canonical structures depends not only on sequence but also on the surrounding environment. Importantly, these non-canonical structures may exhibit a wide variety of biological roles by changing their structures and stabilities in response to the surrounding environments, which undergo vast changes at specific locations and at specific times in cells. Here, we review recent progress regarding the interesting behaviors and functions of nucleic acids controlled by molecularly crowded cellular conditions. New insights gained from recent studies suggest that nucleic acids not only code genetic information in sequences but also have unknown functions regarding their structures and stabilities through drastic structural changes in cellular environments.

Guide-target mismatch effects on dCas9-sgRNA binding activity in living bacterial cells

As an effective programmable DNA targeting tool, CRISPR-Cas9 system has been adopted in varieties of biotechnological applications. However, the off-target effects, derived from the tolerance towards guide-target mismatches, are regarded as the major problems in engineering CRISPR systems. To understand this, we constructed two sgRNA libraries carrying saturated single- and double-nucleotide mismatches in living bacteria cells, and profiled the comprehensive landscape of in vivo binding affinity of dCas9 toward DNA target guided by each individual sgRNA with particular mismatches. We observed a synergistic effect in seed, where combinatorial double mutations caused more severe activity loss compared with the two corresponding single mutations. Moreover, we found that a particular mismatch type, dDrG (D = A, T, G), only showed moderate impairment on binding. To quantitatively understand the causal relationship between mismatch and binding behaviour of dCas9, we further established a biophysical model, and found that the thermodynamic properties of base-pairing coupled with strand invasion process, to a large extent, can account for the observed mismatch-activity landscape. Finally, we repurposed this model, together with a convolutional neural network constructed based on the same mechanism, as a predictive tool to guide the rational design of sgRNA in bacterial CRISPR interference.

Thermodynamics of DNA Hybridization from Atomistic Simulations

Studying DNA hybridization equilibrium at atomistic length scales, either via molecular dynamics (MD) or through commonly used advanced sampling approaches, is notoriously difficult. In this work, we describe an order-parameter-based advanced sampling technique to calculate the free energy of hybridization, and estimate the melting temperature of DNA oligomers at atomistic resolution. The free energy landscapes are reported as a function of a native-topology-based order parameter for the Drew-Dickerson dodecamer and for a range of DNA decamer sequences of different GC content. Our estimated melting temperatures match the experimental numbers within ±15 °C. As a test of the numerical reliability of the procedures employed, it was verified that the predicted free energy surfaces and melting temperatures of the d- and l-enantiomers of the Drew-Dickerson dodecamer were indistinguishable within numerical accuracy.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

Free-Energy Calculation of Ribonucleic Inosines and Its Application to Nearest-Neighbor Parameters

Can current simulations quantitatively predict the stability of ribonucleic acids (RNAs)? In this research, we apply a free-energy perturbation simulation of RNAs containing inosine, a modified ribonucleic base, to the derivation of RNA nearest-neighbor parameters. A parameter set derived solely from 30 simulations was used to predict the free-energy difference of the RNA duplex with a mean unbiased error of 0.70 kcal/mol, which is a level of accuracy comparable to that obtained with parameters derived from 25 experiments. We further show that the error can be lowered to 0.60 kcal/mol by combining the simulation-derived free-energy differences with experimentally measured differences. This protocol can be used as a versatile method for deriving nearest-neighbor parameters of RNAs with various modified bases.

Nearest-neighbor parameters for predicting DNA duplex stability in diverse molecular crowding conditions

The intracellular environment is crowded and heterogeneous. Although the thermodynamic stability of nucleic acid duplexes is predictable in dilute solutions, methods of predicting such stability under specific intracellular conditions are not yet available. We recently showed that the nearest-neighbor model for self-complementary DNA is valid under molecular crowding condition of 40% polyethylene glycol with an average molecular weight of 200 (PEG 200) in 100 mM NaCl. Here, we determined nearest-neighbor parameters for DNA duplex formation under the same crowding condition to predict the thermodynamics of DNA duplexes in the intracellular environment. Preferential hydration of the nucleotides was found to be the key factor for nearest-neighbor parameters in the crowding condition. The determined parameters were shown to predict the thermodynamic parameters (∆H°, ∆S°, and ∆G°₃₇) and melting temperatures (T _m) of the DNA duplexes in the crowding condition with significant accuracy. Moreover, we proposed a general method for predicting the stability of short DNA duplexes in different cosolutes based on the relationship between duplex stability and the water activity of the cosolute solution. The method described herein would be valuable for investigating biological processes that occur under specific intracellular crowded conditions and for the application of DNA-based biotechnologies in crowded environments.

Forces maintaining the DNA double helix

Despite the common acceptance that the enthalpy of DNA duplex unfolding does not depend on temperature and is greater for the CG base pair held by three hydrogen bonds than for the AT base pair held by only two, direct calorimetric measurements have shown that the enthalpic and entropic contributions of both base pairs are temperature dependent and at all temperatures are greater for the AT than the CG pair. The temperature dependence results from hydration of the apolar surfaces of bases that become exposed upon duplex dissociation. The larger enthalpic and entropic contributions of the AT pair are caused by water fixed by this pair in the minor groove of DNA and released on duplex dissociation. Analysis of the experimental thermodynamic characteristics of unfolding/refolding DNA duplexes of various compositions shows that the enthalpy of base pairing is negligibly small, while the entropic contribution is considerable. Thus, DNA base pairing is entropy driven and is coupled to the enthalpy driven van der Waals base pair stacking. Each of these two processes is responsible for about half the Gibbs energy of duplex stabilization, but all the enthalpy, i.e., the total heat of melting, results from dissociation of the stacked base pairs. Both these processes tightly cooperate: while the pairing of conjugate bases is critical for recognition of complementary strands, stacking of the flat apolar surfaces of the base pairs reinforces the DNA duplex formed.

Stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells

This review provides the biophysicochemical background and recent advances in stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells.

Validation of the nearest-neighbor model for Watson-Crick self-complementary DNA duplexes in molecular crowding condition

Recent advancement in nucleic acid techniques inside cells demands the knowledge of the stability of nucleic acid structures in molecular crowding. The nearest-neighbor model has been successfully used to predict thermodynamic parameters for the formation of nucleic acid duplexes, with significant accuracy in a dilute solution. However, knowledge about the applicability of the model in molecular crowding is still limited. To determine and predict the stabilities of DNA duplexes in a cell-like crowded environment, we systematically investigated the validity of the nearest-neighbor model for Watson–Crick self-complementary DNA duplexes in molecular crowding. The thermodynamic parameters for the duplex formation were measured in the presence of 40 wt% poly(ethylene glycol)200 for different self-complementary DNA oligonucleotides consisting of identical nearest-neighbors in a physiological buffer containing 0.1 M NaCl. The thermodynamic parameters as well as the melting temperatures (T_m) obtained from the UV melting studies revealed similar values for the oligonucleotides having identical nearest-neighbors, suggesting the validity of the nearest-neighbor model in the crowding condition. Linear relationships between the measured ΔG°₃₇ and T_m in crowding condition and those predicted in dilute solutions allowed us to predict ΔG°₃₇, T_m and nearest-neighbor parameters in molecular crowding using existing parameters in the dilute condition, which provides useful information about the thermostability of the self-complementary DNA duplexes in molecular crowding.

In search of visible-light photoresponsive peptide nucleic acids (PNAs) for reversible control of DNA hybridization

Photoswitchable oligonucleotides can determine specific biological outcomes by light-induced conformational changes. In particular, artificial probes activated by visible-light irradiation are highly desired in biological applications. Here, we report two novel types of visible-light photoswitchable peptide nucleic acids (PNAs) based on the molecular transducers: hemithioindigo and tetra-ortho-fluoroazobenzene. Our study reveals that the tetra-ortho-fluoroazobenzene-PNA conjugates have promising properties (fast reversible isomerization, exceptional thermal stability, high isomer conversions and sensitivity to visible-light irradiation) as reversible modulators to control oligonucleotide hybridization in biological contexts. Furthermore, we verified that this switchable modification delivers a slightly different hybridization behavior in the PNA. Thus, both melting experiments and strand-displacement assays showed that in all the cases the trans-isomer is the one with superior binding affinities. Alternative versions, inspired by our first compounds here reported, may find applications in different fields such as chemical biology, nanotechnology and materials science.

Thermodynamic characterization and nearest neighbor parameters for RNA duplexes under molecular crowding conditions

It is essential to study RNA under molecular crowding conditions to better predict secondary structures of RNAs in vivo. No systematic study has been completed to determine the effects of molecular crowding on RNA duplexes of varying lengths and sequence composition. Here, optical melting, circular dichroism, and osmometry data were collected for RNA duplexes in a 20% polyethylene glycol (with an average molecular weight of 200 g/mol) solution (PEG 200), and nearest neighbor parameters were derived using this data. RNA duplexes are destabilized, on average, 1.02 kcal/mol in the presence of 20% PEG 200. The ΔG°₃₇ values predicted by the nearest neighbor parameters for RNA duplexes in 20% PEG 200 were ∼0.65 kcal/mol closer to experimental ΔG°₃₇ values than those predicted by the standard nearest neighbor model. For one DNA sequence in solution with small crowders, the ΔG°₃₇ values predicted by the 20% PEG 200 RNA nearest neighbor parameters were closer to the experimental values than ΔG°₃₇ values predicted by either the RNA or DNA standard nearest neighbor models. This indicates that the nearest neighbor parameters for RNA duplexes in 20% PEG 200 may be generalizable to RNA and DNA duplexes in solutions with small crowding agents.

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes

Background

General translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.

Results

Here, we show that these sequence features specify 42–81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25–60 nucleotide segments within mRNA 5′ regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5′ regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.

Conclusions

Our work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell.

Electronic supplementary material

The online version of this article (10.1186/s13059-019-1761-9) contains supplementary material, which is available to authorized users.

Improving RNA nearest neighbor parameters for helices by going beyond the two-state model

RNA folding free energy change nearest neighbor parameters are widely used to predict folding stabilities of secondary structures. They were determined by linear regression to datasets of optical melting experiments on small model systems. Traditionally, the optical melting experiments are analyzed assuming a two-state model, i.e. a structure is either complete or denatured. Experimental evidence, however, shows that structures exist in an ensemble of conformations. Partition functions calculated with existing nearest neighbor parameters predict that secondary structures can be partially denatured, which also directly conflicts with the two-state model. Here, a new approach for determining RNA nearest neighbor parameters is presented. Available optical melting data for 34 Watson–Crick helices were fit directly to a partition function model that allows an ensemble of conformations. Fitting parameters were the enthalpy and entropy changes for helix initiation, terminal AU pairs, stacks of Watson–Crick pairs and disordered internal loops. The resulting set of nearest neighbor parameters shows a 38.5% improvement in the sum of residuals in fitting the experimental melting curves compared to the current literature set.

A strongly pairing fifth base: oligonucleotides with a C-nucleoside replacing thymidine

There are five canonical bases in DNA and RNA. Each base has its particular molecular recognition properties and base pairing strength. Thymine and uracil form only two hydrogen bonds when pairing with adenine, and duplexes rich in A:T base pairs are more labile than duplexes rich in C and G, making some sequences difficult to detect via hybridization in a genomic context. Here we report the synthesis of an ethynylmethylpyridone C-nucleoside, abbreviated ‘W’, that presents a similar recognition surface as thymidine in the major groove but pairs with A about as strongly as C pairs with G. A phosphoramidite building block was synthesized that allows for incorporation of W residues via automated synthesis in high yield. Melting point increases over duplexes containing T:A pairs of up to 17.5°C, or up to 5.8°C per residue were measured for oligonucleotides containing W. Further, the new base shows excellent fidelity, with a single mismatched G opposite W causing a melting point depression of up to 20.5°C. The strongly pairing replacement for thymidine is only slightly larger than its natural counterpart and performs well in different sequence contexts. It can be used to target weakly pairing A-rich sequences in biological studies.

Translational Entropy and DNA Duplex Stability

Investigation of folding/unfolding DNA duplexes of various size and composition by superprecise calorimetry has revised several long-held beliefs concerning the forces responsible for the formation of the double helix. It was established that: 1) the enthalpy and the entropy of duplex unfolding are temperature dependent, increasing with temperature rise and having the same heat capacity increment for CG and AT pairs; 2) the enthalpy of AT melting is greater than that of the CG pair, so the stabilizing effect of the CG pair in comparison with AT results not from its larger enthalpic contribution (as expected from its extra hydrogen bond), but from the larger entropic contribution of the AT pair that results from its ability to fix ordered water in the minor groove and release it upon duplex unfolding; 3) the translation entropy, resulting from the appearance of a new kinetic unit on duplex dissociation, determines the dependence of duplex stability on its length and its concentration (it is an order-of-magnitude smaller than predicted from the statistical mechanics of gases and is fully expressed by the stoichiometric correction term); 4) changes in duplex stability on reshuffling the sequence (the "nearest-neighbor effect") result from the immobilized water molecules fixed by AT pairs in the minor groove; and 5) the evaluated thermodynamic components permit a quantitative expression of DNA duplex stability.

Minor groove binder modification of widely used TaqMan hydrolysis probe for detection of dengue virus reduces risk of false-negative real-time PCR results for serotype 4

Dengue is a vector-transmitted viral infection that is a significant cause of morbidity and mortality in humans worldwide, with over 50 million apparent cases and a fatality rate of 2.5 % of 0.5 million severe cases per annum in recent years. Four serotypes are currently co-circulating. Diagnosis of infection may be by polymerase chain reaction, serology or rapid antigen test for NS1. Both pan-serotype and serotype-specific genome detection assays have been described, however, achieving adequate sensitivity with pan-serotype assays has been challenging. Indeed, as we show here, inspection of components and cycling parameters of a pan-serotype RT-qPCR assay in use in laboratories worldwide revealed insufficient probe stability to accommodate potential nucleotide mismatches, resulting in false-negatives. A minor-groove binder (MGB)-modified version of the probe was designed and its performance compared with that of the original probe in 32 samples. Eight of the samples were undetected by the original probe but detected by the MGB modified probe and six out of seven of these that could be serotyped belonged to serotype 4. Sequencing of the region targeted by the probe in these samples revealed two mismatches which were also universally present in all other serotype 4 sequences in a public database. We therefore recommend adoption of this MGB modification in order to reduce the risk of false-negative results, especially with dengue serotype 4 infections.

Stability of RNA duplexes containing inosine·cytosine pairs

Inosine is found naturally in the anticodon loop of tRNA, is a product of adenosine deaminases that act on RNA, and can be used in oligonucleotide probes or to investigate the role of the exocyclic amino group of guanosine. Although the thermodynamics of I·U pairs in RNA have been systematically studied [Wright, D. J., Rice, J. L., Yanker, D. M., and Znosko, B. M. (2007) Biochemistry 46, 4625-4634], the thermodynamics of I·C pairs in RNA have not. Here, we have performed optical melting experiments on a series of RNA duplexes containing I·C pairs and compared their thermodynamics to the same duplexes containing A·C and G-C pairs. Nearest neighbor parameters for single I·C pairs adjacent to Watson-Crick pairs were derived. The derived nearest neighbor parameters are compared to those previously predicted blindly through a reweighting of energy-function collection with conformational ensemble sampling in Rosetta [Chou, F.-C., Kladwang, W., Kappel, K., and Das, R. (2016) Proc. Natl. Acad. Sci. U.S.A. 113, 8430-8435]. Scientists can use these nearest neighbor parameters to calculate the stability of ADAR products and to calculate the stability of an RNA duplex in which G-to-I substitution was used to determine the role of the exocyclic amino group of G.

Structure and Interaction Prediction in Prokaryotic RNA Biology

Many years of research in RNA biology have soundly established the importance of RNA-based regulation far beyond most early traditional presumptions. Importantly, the advances in "wet" laboratory techniques have produced unprecedented amounts of data that require efficient and precise computational analysis schemes and algorithms. Hence, many in silico methods that attempt topological and functional classification of novel putative RNA-based regulators are available. In this review, we technically outline thermodynamics-based standard RNA secondary structure and RNA-RNA interaction prediction approaches that have proven valuable to the RNA research community in the past and present. For these, we highlight their usability with a special focus on prokaryotic organisms and also briefly mention recent advances in whole-genome interactomics and how this may influence the field of predictive RNA research.

Modeling Structure, Stability, and Flexibility of Double-Stranded RNAs in Salt Solutions

Double-stranded (ds) RNAs play essential roles in many processes of cell metabolism. The knowledge of three-dimensional (3D) structure, stability, and flexibility of dsRNAs in salt solutions is important for understanding their biological functions. In this work, we further developed our previously proposed coarse-grained model to predict 3D structure, stability, and flexibility for dsRNAs in monovalent and divalent ion solutions through involving an implicit structure-based electrostatic potential. The model can make reliable predictions for 3D structures of extensive dsRNAs with/without bulge/internal loops from their sequences, and the involvement of the structure-based electrostatic potential and corresponding ion condition can improve the predictions for 3D structures of dsRNAs in ion solutions. Furthermore, the model can make good predictions for thermal stability for extensive dsRNAs over the wide range of monovalent/divalent ion concentrations, and our analyses show that the thermally unfolding pathway of dsRNA is generally dependent on its length as well as its sequence. In addition, the model was employed to examine the salt-dependent flexibility of a dsRNA helix, and the calculated salt-dependent persistence lengths are in good accordance with experiments.

Interactive implementations of thermodynamics-based RNA structure and RNA-RNA interaction prediction approaches for example-driven teaching

The investigation of RNA-based regulation of cellular processes is becoming an increasingly important part of biological or medical research. For the analysis of this type of data, RNA-related prediction tools are integrated into many pipelines and workflows. In order to correctly apply and tune these programs, the user has to have a precise understanding of their limitations and concepts. Within this manuscript, we provide the mathematical foundations and extract the algorithmic ideas that are core to state-of-the-art RNA structure and RNA–RNA interaction prediction algorithms. To allow the reader to change and adapt the algorithms or to play with different inputs, we provide an open-source web interface to JavaScript implementations and visualizations of each algorithm. The conceptual, teaching-focused presentation enables a high-level survey of the approaches, while providing sufficient details for understanding important concepts. This is boosted by the simple generation and study of examples using the web interface available at http://rna.informatik.uni-freiburg.de/Teaching/. In combination, we provide a valuable resource for teaching, learning, and understanding the discussed prediction tools and thus enable a more informed analysis of RNA-related effects.

RNA molecules are central players in many cellular processes. Thus, the analysis of RNA-based regulation has provided valuable insights and is often pivotal to biological and medical research. In order to correctly select appropriate algorithms and apply available RNA structure and RNA–RNA interaction prediction software, it is crucial to have a good understanding of their limitations and concepts. Such an overview is hard to achieve by end users, since most state-of-the-art tools are introduced on expert level and are not discussed in text books. Within this manuscript, we provide the mathematical means and extract the algorithmic concepts that are core to state-of-the-art RNA structure and RNA–RNA interaction prediction algorithms. The conceptual, teaching-focused presentation enables a detailed understanding of the approaches using a simplified model for didactic purposes. We support this process by providing clear examples using the web interface of our algorithm implementation. In summary, we have compiled material and web applications for teaching—and the self-study of—several state-of-the-art algorithms commonly used to investigate the role of RNA in regulatory processes.

Identification of the RNA Pseudoknot within the 3' End of the Porcine Reproductive and Respiratory Syndrome Virus Genome as a Pathogen-Associated Molecular Pattern To Activate Antiviral Signaling via RIG-I and Toll-Like Receptor 3

Once infected by viruses, cells can detect pathogen-associated molecular patterns (PAMPs) on viral nucleic acid by host pattern recognition receptors (PRRs) to initiate the antiviral response. Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of porcine reproductive and respiratory syndrome (PRRS), characterized by reproductive failure in sows and respiratory diseases in pigs of different ages. To date, the sensing mechanism of PRRSV has not been elucidated. Here, we reported that the pseudoknot region residing in the 3' untranslated regions (UTR) of the PRRSV genome, which has been proposed to regulate RNA synthesis and virus replication, was sensed as nonself by retinoic acid-inducible gene I (RIG-I) and Toll-like receptor 3 (TLR3) and strongly induced type I interferons (IFNs) and interferon-stimulated genes (ISGs) in porcine alveolar macrophages (PAMs). The interaction between the two stem-loops inside the pseudoknot structure was sufficient for IFN induction, since disruption of the pseudoknot interaction powerfully dampened the IFN induction. Furthermore, transfection of the 3' UTR pseudoknot transcripts in PAMs inhibited PRRSV replication in vitro Importantly, the predicted similar structures of other arterivirus members, including equine arteritis virus (EAV), lactate dehydrogenase-elevating virus (LDV), and simian hemorrhagic fever virus (SHFV), also displayed strong IFN induction activities. Together, in this work we identified an innate recognition mechanism by which the PRRSV 3' UTR pseudoknot region served as PAMPs of arteriviruses and activated innate immune signaling to produce IFNs that inhibit virus replication. All of these results provide novel insights into innate immune recognition during virus infection.IMPORTANCE PRRS is the most common viral disease in the pork industry. It is caused by PRRSV, a positive single-stranded RNA virus, whose infection often leads to persistent infection. To date, it is not yet clear how PRRSV is recognized by the host and what is the exact mechanism of IFN induction. Here, we investigated the nature of PAMPs on PRRSV and the associated PRRs. We found that the 3' UTR pseudoknot region of PRRSV, which has been proposed to regulate viral RNA synthesis, could act as PAMPs recognized by RIG-I and TLR3 to induce type I IFN production to suppress PRRSV infection. This report is the first detailed description of pattern recognition for PRRSV, which is important in understanding the antiviral response of arteriviruses, especially PRRSV, and extends our knowledge on virus recognition.

Predictive Model for the Sequence-Dependent Fluorogenic Response of Forced-Intercalation Peptide Nucleic Acid

The forced-intercalation peptide nucleic acid (FIT-PNA) concept, introduced by Seitz and co-workers, is based on replacing a nucleobase of the PNA sequence with a cyanine dye (such as thiazole orange). The cyanine dye is thus a surrogate base that is forced to intercalate in the duplex (e.g.

, PNA

DNA). This allows single-mismatch sensitivity as the introduction of a mismatch in the vicinity of the dye increases freedom of motion and leads to a significant depletion of its fluorescence because of the free rotation of the monomethine bond separating the two π-systems of the cyanine dye. Herein, we designed and synthesized six FIT-PNA probes, featuring bisquinoline (BisQ), a red-emitting cyanine dye recently developed in our laboratory for FIT-PNAs. By following PNA-DNA duplex fluorescence, we found new sequence-based factors governing the fluorescence response to the mismatched FIT-PNA:DNA duplex. Fluorogenic properties are correlated with the π-stacking energy of three distinctive base pair steps (BPSs) in the PNA:DNA duplex. The first two are the two BPSs opposite BisQ, whereas the third is the BPS of the mismatch position, which presumably becomes unstacked due to the mismatch. We suggest a predictive model for FIT-PNA single-mismatch detection mechanism, a model that can be used in future research to improve FIT-PNA design.

Genetic Fingerprinting Using Microsatellite Markers in a Multiplex PCR Reaction: A Compilation of Methodological Approaches from Primer Design to Detection Systems

Microsatellites are polymorphic DNA loci comprising repeated sequence motifs of two to five base pairs which are dispersed throughout the genome. Genotyping of microsatellites is a widely accepted tool for diagnostic and research purposes such as forensic investigations and parentage testing, but also in clinics (e.g. monitoring of bone marrow transplantation), as well as for the agriculture and food industries. The co-amplification of several short tandem repeat (STR) systems in a multiplex reaction with simultaneous detection helps to obtain more information from a DNA sample where its availability may be limited. Here, we introduce and describe this commonly used genotyping technique, providing an overview on available resources on STRs, multiplex design, and analysis.

RNA Secondary Structure Determination by NMR

Dynamic programming methods for predicting RNA secondary structure often use thermodynamics and experimental restraints and/or constraints to limit folding space. Chemical mapping results typically restrain certain nucleotides not to be in AU or GC pairs. Two-dimensional nuclear magnetic resonance (NMR) spectra can reveal the order of AU, GC, and GU pairs in double helixes. This chapter describes a program, NMR-assisted prediction of secondary structure and chemical shifts (NAPSS-CS), that constrains possible secondary structures on the basis of the NMR determined order and 5'-3' direction of AU, GC, and GU pairs in helixes. NAPSS-CS minimally requires input of the order of base pairs as determined from nuclear Overhauser effect spectroscopy (NOESY) of imino protons. The program deduces the 5'-3' direction of the base pairs if certain chemical shifts are also input. Secondary structures predicted by the program provide assignments of input chemical shifts to particular nucleotides in the sequence, thus facilitating an important step for determination of the three dimensional structure by NMR. The method is particularly useful for revealing pseudoknots and an example is provided. The method may also allow determination of secondary structures when a sequence folds into two structures that exchange slowly.

The loss of a hydrogen bond: Thermodynamic contributions of a non-standard nucleotide

Non-standard nucleotides are ubiquitous in RNA. Thermodynamic studies with RNA duplexes containing non-standard nucleotides, whether incorporated naturally or chemically, can provide insight into the stability of Watson–Crick pairs and the role of specific functional groups in stabilizing a Watson–Crick pair. For example, an A-U, inosine•U and pseudouridine•A pair each form two hydrogen bonds. However, an RNA duplex containing a central I•U pair or central Ψ•A pair is 2.4 kcal/mol less stable or 1.7 kcal/mol more stable, respectively, than the corresponding duplex containing an A-U pair. In the non-standard nucleotide purine, hydrogen replaces the exocyclic amino group of A. This replacement results in a P•U pair containing only one hydrogen bond. Optical melting studies were performed with RNA duplexes containing P•U pairs adjacent to different nearest neighbors. The resulting thermodynamic parameters were compared to RNA duplexes containing A-U pairs in order to determine the contribution of the hydrogen bond involving the exocyclic amino group. Results indicate a loss of 1.78 kcal/mol, on average, when an internal P•U replaces A-U in an RNA duplex. This value is compared to the thermodynamics of a hydrogen bond determined by similar methods. Nearest neighbor parameters were derived for use in free energy and secondary structure prediction software.