Thermodynamic contributions of single internal rA·dA, rC·dC, rG·dG and rU·dT mismatches in RNA/DNA duplexes

Cas12a domain flexibility guides R-loop formation and forces RuvC resetting

The specific nature of CRISPR-Cas12a makes it a desirable RNA-guided endonuclease for biotechnology and therapeutic applications. To understand how R-loop formation within the compact Cas12a enables target recognition and nuclease activation, we used cryo-electron microscopy to capture wild-type Acidaminococcus sp. Cas12a R-loop intermediates and DNA delivery into the RuvC active site. Stages of Cas12a R-loop formation-starting from a 5-bp seed-are marked by distinct REC domain arrangements. Dramatic domain flexibility limits contacts until nearly complete R-loop formation, when the non-target strand is pulled across the RuvC nuclease and coordinated domain docking promotes efficient cleavage. Next, substantial domain movements enable target strand repositioning into the RuvC active site. Between cleavage events, the RuvC lid conformationally resets to occlude the active site, requiring re-activation. These snapshots build a structural model depicting Cas12a DNA targeting that rationalizes observed specificity and highlights mechanistic comparisons to other class 2 effectors.

Nucleic Acid Structure Prediction Including Pseudoknots Through Direct Enumeration of States: A User's Guide to the LandscapeFold Algorithm

Here we detail the LandscapeFold secondary structure prediction algorithm and how it is used. The algorithm was previously described and tested in (Kimchi O et al., Biophys J 117(3):520-532, 2019), though it was not named there. The algorithm directly enumerates all possible secondary structures into which up to two RNA or single-stranded DNA sequences can fold. It uses a polymer physics model to estimate the configurational entropy of structures including complex pseudoknots. We detail each of these steps and ways in which the user can adjust the algorithm as desired. The code is available on the GitHub repository https://github.com/ofer-kimchi/LandscapeFold .

CRISPR/Cas9 gRNA activity depends on free energy changes and on the target PAM context

A major challenge of CRISPR/Cas9-mediated genome engineering is that not all guide RNAs (gRNAs) cleave the DNA efficiently. Although the heterogeneity of gRNA activity is well recognized, the current understanding of how CRISPR/Cas9 activity is regulated remains incomplete. Here, we identify a sweet spot range of binding free energy change for optimal efficiency which largely explains why gRNAs display changes in efficiency at on- and off-target sites, including why gRNAs can cleave an off-target with higher efficiency than the on-target. Using an energy-based model, we show that local gRNA-DNA interactions resulting from Cas9 "sliding" on overlapping protospacer adjacent motifs (PAMs) profoundly impact gRNA activities. Combining the effects of local sliding for a given PAM context with global off-targets allows us to better identify highly specific, and thus efficient, gRNAs. We validate the effects of local sliding on gRNA efficiency using both public data and in-house data generated by measuring SpCas9 cleavage efficiency at 1024 sites designed to cover all possible combinations of 4-nt PAM and context sequences of 4 gRNAs. Our results provide insights into the mechanisms of Cas9-PAM compatibility and cleavage activation, underlining the importance of accounting for local sliding in gRNA design.

Complex dependence of CRISPR-Cas9 binding strength on guide RNA spacer lengths

It is established that for CRISPR-Cas9 applications guide RNAs with 17-20 bp long spacer sequences are optimal for accurate target binding and cleavage. In this work we perform cell-free CRISPRa (CRISPR activation) and CRISPRi (CRISPR inhibition) experiments to demonstrate the existence of a complex dependence of CRISPR-Cas9 binding as a function of the spacer length and complementarity. Our results show that significantly truncated or mismatched spacer sequences can form stronger guide-target bonds than the conventional 17-20 bp long spacers. To explain this phenomenon, we take into consideration previous structural and single-molecule CRISPR-Cas9 experiments and develop a novel thermodynamic model of CRISPR-Cas9 target recognition.

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.

Optical and theoretical study of strand recognition by nucleic acid probes

Detection of nucleic acids is crucial to the study of their basic properties and consequently to applying this knowledge to the determination of pathologies such as cancer. In this work, our goal is to determine new trends for creating diagnostic tools for cancer driver mutations. Herein, we study a library of natural and modified oligonucleotide duplexes by a combination of optical and theoretical methods. We report a profound effect of additives on the duplexes, including nucleic acids as an active crowder. Unpredictably and inconsistent with DNA+LNA/RNA duplexes, locked nucleic acids contribute poorly to mismatch discrimination in the DNA+LNA/DNA duplexes. We develop a theoretical framework that explains poor mismatch discrimination in KRAS oncogene. We implement our findings in a bead-bait genotyping assay to detect mutated human cancer RNA. The performance of rationally designed probes in this assay is superior to the LNA-primer polymerase chain reaction, and it agrees with sequencing data.

A Polymer Physics Framework for the Entropy of Arbitrary Pseudoknots

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past 40 years. Although many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges arising from two main factors: 1) no physical model exists to estimate the loop entropies of complex intramolecular pseudoknots, and 2) their NP-complete enumeration has impeded their study. Here, we address both challenges. First, we develop a polymer physics model that can address arbitrarily complex pseudoknots using only two parameters corresponding to concrete physical quantities-over an order of magnitude fewer than the sparsest state-of-the-art phenomenological methods. Second, by coupling this model to exhaustive enumeration of the set of possible structures, we compute the entire free energy landscape of secondary structures resulting from a primary RNA sequence. We demonstrate that for RNA structures of ∼80 nucleotides, with minimal heuristics, the complete enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem. We further show that despite our loop entropy model's parametric sparsity, it performs better than or on par with previously published methods in predicting both pseudoknotted and non-pseudoknotted structures on a benchmark data set of RNA structures of ≤80 nucleotides. We suggest ways in which the accuracy of the model can be further improved.

Role of nucleotide identity in effective CRISPR target escape mutations

Prokaryotes use primed CRISPR adaptation to update their memory bank of spacers against invading genetic elements that have escaped CRISPR interference through mutations in their protospacer target site. We previously observed a trend that nucleotide-dependent mismatches between crRNA and the protospacer strongly influence the efficiency of primed CRISPR adaptation. Here we show that guanine-substitutions in the target strand of the protospacer are highly detrimental to CRISPR interference and interference-dependent priming, while cytosine-substitutions are more readily tolerated. Furthermore, we show that this effect is based on strongly decreased binding affinity of the effector complex Cascade for guanine-mismatched targets, while cytosine-mismatched targets only minimally affect target DNA binding. Structural modeling of Cascade-bound targets with mismatches shows that steric clashes of mismatched guanines lead to unfavorable conformations of the RNA-DNA duplex. This effect has strong implications for the natural selection of target site mutations that lead to effective escape from type I CRISPR-Cas systems.

CRISPR-Cas9 off-targeting assessment with nucleic acid duplex energy parameters

BACKGROUND

Recent experimental efforts of CRISPR-Cas9 systems have shown that off-target binding and cleavage are a concern for the system and that this is highly dependent on the selected guide RNA (gRNA) design. Computational predictions of off-targets have been proposed as an attractive and more feasible alternative to tedious experimental efforts. However, accurate scoring of the high number of putative off-targets plays a key role for the success of computational off-targeting assessment.

RESULTS

We present an approximate binding energy model for the Cas9-gRNA-DNA complex, which systematically combines the energy parameters obtained for RNA-RNA, DNA-DNA, and RNA-DNA duplexes. Based on this model, two novel off-target assessment methods for gRNA selection in CRISPR-Cas9 applications are introduced: CRISPRoff to assign confidence scores to predicted off-targets and CRISPRspec to measure the specificity of the gRNA. We benchmark the methods against current state-of-the-art methods and show that both are in better agreement with experimental results. Furthermore, we show significant evidence supporting the inverse relationship between the on-target cleavage efficiency and specificity of the system, in which introduced binding energies are key components.

CONCLUSIONS

The impact of the binding energies provides a direction for further studies of off-targeting mechanisms. The performance of CRISPRoff and CRISPRspec enables more accurate off-target evaluation for gRNA selections, prior to any CRISPR-Cas9 genome-editing application. For given gRNA sequences or all potential gRNAs in a given target region, CRISPRoff-based off-target predictions and CRISPRspec-based specificity evaluations can be carried out through our webserver at https://rth.dk/resources/crispr/ .

Kinetic Basis for DNA Target Specificity of CRISPR-Cas12a

Class 2 CRISPR-Cas nucleases are programmable genome editing tools with promising applications in human health and disease. However, DNA cleavage at off-target sites that resemble the target sequence is a pervasive problem that remains poorly understood mechanistically. Here, we use quantitative kinetics to dissect the reaction steps of DNA targeting by Acidaminococcus sp Cas12a (also known as Cpf1). We show that Cas12a binds DNA tightly in two kinetically separable steps. Protospacer-adjacent motif (PAM) recognition is followed by rate-limiting R-loop propagation, leading to inevitable DNA cleavage of both strands. Despite functionally irreversible binding, Cas12a discriminates strongly against mismatches along most of the DNA target sequence. This result implies substantial reversibility during R-loop formation-a late transition state-and defies common descriptions of a "seed" region. Our results provide a quantitative basis for the DNA cleavage patterns measured in vivo and observations of greater reported target specificity for Cas12a than for the Cas9 nuclease.

Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models

Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.

Transcriptional accuracy modeling suggests two-step proofreading by RNA polymerase

We suggest a novel two-step proofreading mechanism with two sequential rounds of proofreading selection in mRNA transcription. It is based on the previous experimental observations that the proofreading RNA polymerase cleaves off transcript fragments of at least 2 nt and that transcript elongation after a nucleotide misincorporation is anomalously slow. Taking these results into account, we extend the description of the accuracy of template guided nucleotide selection beyond previous models of RNA polymerase-dependent DNA transcription. The model derives the accuracy of initial and proofreading base selection from experimentally estimated nearest-neighbor parameters. It is also used to estimate the small accuracy enhancement of polymerase revisiting of previous positions following transcript cleavage.

Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast

RNA Polymerase II pauses and backtracks during transcription, with many consequences for gene expression and cellular physiology. Here, we show that the energy required to melt double-stranded nucleic acids in the transcription bubble predicts pausing in Saccharomyces cerevisiae far more accurately than nucleosome roadblocks do. In addition, the same energy difference also determines when the RNA polymerase backtracks instead of continuing to move forward. This data-driven model corroborates—in a genome wide and quantitative manner—previous evidence that sequence-dependent thermodynamic features of nucleic acids influence both transcriptional pausing and backtracking.

Revealing Nucleic Acid Mutations Using Förster Resonance Energy Transfer-Based Probes

Nucleic acid mutations are of tremendous importance in modern clinical work, biotechnology and in fundamental studies of nucleic acids. Therefore, rapid, cost-effective and reliable detection of mutations is an object of extensive research. Today, Förster resonance energy transfer (FRET) probes are among the most often used tools for the detection of nucleic acids and in particular, for the detection of mutations. However, multiple parameters must be taken into account in order to create efficient FRET probes that are sensitive to nucleic acid mutations. In this review; we focus on the design principles for such probes and available computational methods that allow for their rational design. Applications of advanced, rationally designed FRET probes range from new insights into cellular heterogeneity to gaining new knowledge of nucleic acid structures directly in living cells.

Rapid generation of CRISPR/dCas9-regulated, orthogonally repressible hybrid T7-lac promoters for modular, tuneable control of metabolic pathway fluxes in Escherichia coli

Robust gene circuit construction requires use of promoters exhibiting low crosstalk. Orthogonal promoters have been engineered utilizing an assortment of natural and synthetic transcription factors, but design of large orthogonal promoter-repressor sets is complicated, labor-intensive, and often results in unanticipated crosstalk. The specificity and ease of targeting the RNA-guided DNA-binding protein dCas9 to any 20 bp user-defined DNA sequence makes it a promising candidate for orthogonal promoter regulation. Here, we rapidly construct orthogonal variants of the classic T7-lac promoter using site-directed mutagenesis, generating a panel of inducible hybrid promoters regulated by both LacI and dCas9. Remarkably, orthogonality is mediated by only two to three nucleotide mismatches in a narrow window of the RNA:DNA hybrid, neighboring the protospacer adjacent motif. We demonstrate that, contrary to many reports, one PAM-proximal mismatch is insufficient to abolish dCas9-mediated repression, and we show for the first time that mismatch tolerance is a function of target copy number. Finally, these promoters were incorporated into the branched violacein biosynthetic pathway as dCas9-dependent switches capable of throttling and selectively redirecting carbon flux in Escherichia coli. We anticipate this strategy is relevant for any promoter and will be adopted for many applications at the interface of synthetic biology and metabolic engineering.

A Biophysical Model of CRISPR/Cas9 Activity for Rational Design of Genome Editing and Gene Regulation

The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II) system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9's off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits.

A Tandem Oligonucleotide Approach for SNP-Selective RNA Degradation Using Modified Antisense Oligonucleotides

Antisense oligonucleotides have been studied for many years as a tool for gene silencing. One of the most difficult cases of selective RNA silencing involves the alleles of single nucleotide polymorphisms, in which the allele sequence is differentiated by a single nucleotide. A new approach to improve the performance of allele selectivity for antisense oligonucleotides is proposed. It is based on the simultaneous application of two oligonucleotides. One is complementary to the mutated form of the targeted RNA and is able to activate RNase H to cleave the RNA. The other oligonucleotide, which is complementary to the wild type allele of the targeted RNA, is able to inhibit RNase H cleavage. Five types of SNPs, C/G, G/C, G/A, A/G, and C/U, were analyzed within the sequence context of genes associated with neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, ALS (Amyotrophic Lateral Sclerosis), and Machado-Joseph disease. For most analyzed cases, the application of the tandem approach increased allele-selective RNA degradation 1.5–15 fold relative to the use of a single antisense oligonucleotide. The presented study proves that differentiation between single substitution is highly dependent on the nature of the SNP and surrounding nucleotides. These variables are crucial for determining the proper length of the inhibitor antisense oligonucleotide. In the tandem approach, the comparison of thermodynamic stability of the favorable duplexes WT RNA-inhibitor and Mut RNA-gapmer with the other possible duplexes allows for the evaluation of chances for the allele-selective degradation of RNA. A larger difference in thermodynamic stability between favorable duplexes and those that could possibly form, usually results in the better allele selectivity of RNA degradation.

Structure and specificity of the RNA-guided endonuclease Cas9 during DNA interrogation, target binding and cleavage

CRISPR-associated endonuclease Cas9 cuts DNA at variable target sites designated by a Cas9-bound RNA molecule. Cas9's ability to be directed by single 'guide RNA' molecules to target nearly any sequence has been recently exploited for a number of emerging biological and medical applications. Therefore, understanding the nature of Cas9's off-target activity is of paramount importance for its practical use. Using atomic force microscopy (AFM), we directly resolve individual Cas9 and nuclease-inactive dCas9 proteins as they bind along engineered DNA substrates. High-resolution imaging allows us to determine their relative propensities to bind with different guide RNA variants to targeted or off-target sequences. Mapping the structural properties of Cas9 and dCas9 to their respective binding sites reveals a progressive conformational transformation at DNA sites with increasing sequence similarity to its target. With kinetic Monte Carlo (KMC) simulations, these results provide evidence of a 'conformational gating' mechanism driven by the interactions between the guide RNA and the 14th-17th nucleotide region of the targeted DNA, the stabilities of which we find correlate significantly with reported off-target cleavage rates. KMC simulations also reveal potential methodologies to engineer guide RNA sequences with improved specificity by considering the invasion of guide RNAs into targeted DNA duplex.

Simulation-guided DNA probe design for consistently ultraspecific hybridization

Hybridization of complementary sequences is one of the central tenets of nucleic acid chemistry; however, the unintended binding of closely related sequences limits the accuracy of hybridization-based approaches for analyzing nucleic acids. Thermodynamics-guided probe design and empirical optimization of reaction conditions have been used to enable discrimination of single nucleotide variants, but typically these approaches provide only an approximate 25-fold difference in binding affinity. Here we show that simulations of the binding kinetics are both necessary and sufficient to design nucleic acid probe systems with consistently high specificity as they enable the discovery of an optimal combination of thermodynamic parameters. Simulation-guided probe systems designed against 44 different target single nucleotide variants sequences showed between 200- and 3000-fold (median 890) higher binding affinity than their corresponding wildtype sequences. As a demonstration of the usefulness of this simulation-guided design approach we developed probes which, in combination with PCR amplification, we use to detect low concentrations of variant alleles (1%) in human genomic DNA.

DNA template dependent accuracy variation of nucleotide selection in transcription

It has been commonly assumed that the effect of erroneous transcription of DNA genes into messenger RNAs on peptide sequence errors are masked by much more frequent errors of mRNA translation to protein. We present a theoretical model of transcriptional accuracy. It uses experimentally estimated standard free energies of double-stranded DNA and RNA/DNA hybrids and predicts a DNA template dependent transcriptional accuracy variation spanning several orders of magnitude. The model also identifies high-error as well a high-accuracy transcription motifs. The source of the large accuracy span is the context dependent variation of the stacking free energy of pairs of correct and incorrect base pairs in the ever moving transcription bubble. Our model predictions have direct experimental support from recent single molecule based identifications of transcriptional errors in the C. elegans transcriptome. Our conclusions challenge the general view that amino acid substitution errors in proteins are mainly caused by translational errors. It suggests instead that transcriptional error hotspots are the dominating source of peptide sequence errors in some DNA template contexts, while mRNA translation is the major cause of protein errors in other contexts.

Mathematical tools to optimize the design of oligonucleotide probes and primers

The identification and quantification of specific organisms in mixed microbial communities often relies on the ability to design oligonucleotide probes and primers with high specificity and sensitivity. The design of these oligonucleotides (or "oligos" for short) shares many of the same principles in spite of their widely divergent applications. Three common molecular biology technologies that require oligonucleotide design are polymerase chain reaction (PCR), fluorescence in situ hybridization (FISH), and DNA microarrays. This article reviews techniques and software available for the design and optimization of oligos with the goal of targeting a specific group of organisms within mixed microbial communities. Strategies for enhancing specificity without compromising sensitivity are described, as well as design tools well suited for this purpose.

Noncanonical structures and their thermodynamics of DNA and RNA under molecular crowding: beyond the Watson-Crick double helix

How does molecular crowding affect the stability of nucleic acid structures inside cells? Water is the major solvent component in living cells, and the properties of water in the highly crowded media inside cells differ from that in buffered solution. As it is difficult to measure the thermodynamic behavior of nucleic acids in cells directly and quantitatively, we recently developed a cell-mimicking system using cosolutes as crowding reagents. The influences of molecular crowding on the structures and thermodynamics of various nucleic acid sequences have been reported. In this chapter, we discuss how the structures and thermodynamic properties of nucleic acids differ under various conditions such as highly crowded environments, compartment environments, and in the presence of ionic liquids, and the major determinants of the crowding effects on nucleic acids are discussed. The effects of molecular crowding on the activities of ribozymes and riboswitches on noncanonical structures of DNA- and RNA-like quadruplexes that play important roles in transcription and translation are also described.

Reconsideration of in silico siRNA design from a perspective of heterogeneous data integration: problems and solutions

The success of RNA interference (RNAi) depends on the interaction between short interference RNAs (siRNAs) and mRNAs. Design of highly efficient and specific siRNAs has become a challenging issue in applications of RNAi. Here, we present a detailed survey on the state-of-the-art siRNAs design, focusing on several key issues with the current in silico RNAi studies, including: (i) inconsistencies among the proposed guidelines for siRNAs design and the incomplete list of siRNAs features, (ii) improper integration of the heterogeneous cross-platform siRNAs data, (iii) inadequate consideration of the binding specificity of the target mRNAs and (iv) reduction in the 'off-target' effect in siRNAs design. With these considerations, the popular in silico siRNAs design rules are reexamined and several inconsistent viewpoints toward siRNAs feature identifications are clarified. In addition, novel computational models for siRNAs design using state-of-art machine learning techniques are discussed, which focus on heterogeneous data integration, joint feature selection and customized siRNAs screening toward highly specific targets. We believe that addressing such issues in siRNA study will provide new clues for further improved design of more efficient and specific siRNAs in RNAi.

Stability and mismatch discrimination of locked nucleic acid-DNA duplexes

Locked nucleic acids (LNA; symbols of bases, +A, +C, +G, and +T) are introduced into chemically synthesized oligonucleotides to increase duplex stability and specificity. To understand these effects, we have determined thermodynamic parameters of consecutive LNA nucleotides. We present guidelines for the design of LNA oligonucleotides and introduce free online software that predicts the stability of any LNA duplex oligomer. Thermodynamic analysis shows that the single strand–duplex transition is characterized by a favorable enthalpic change and by an unfavorable loss of entropy. A single LNA modification confines the local conformation of nucleotides, causing a smaller, less unfavorable entropic loss when the single strand is restricted to the rigid duplex structure. Additional LNAs adjacent to the initial modification appear to enhance stacking and H-bonding interactions because they increase the enthalpic contributions to duplex stabilization. New nearest-neighbor parameters correctly forecast the positive and negative effects of LNAs on mismatch discrimination. Specificity is enhanced in a majority of sequences and is dependent on mismatch type and adjacent base pairs; the largest discriminatory boost occurs for the central +C·C mismatch within the +T+C+C sequence and the +A·G mismatch within the +T+A+G sequence. LNAs do not affect specificity in some sequences and even impair it for many +G·T and +C·A mismatches. The level of mismatch discrimination decreases the most for the central +G·T mismatch within the +G+G+C sequence and the +C·A mismatch within the +G+C+G sequence. We hypothesize that these discrimination changes are not unique features of LNAs but originate from the shift of the duplex conformation from B-form to A-form.