A Statistical Analysis of RNA Folding Algorithms Through Thermodynamic Parameter Perturbation

Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We find that already for changes corresponding to the actual experimental error to which these parameters have been determined 30% of the structure are falsly predicted and the ground state structure is preserved under parameter perturbation in only 5% of all cases. We establish that base pairing probabilities calculated in a thermal ensemble are a viable though not perfect measure for the reliability of the prediction of individual structure elements. A new measure of stability using parameter perturbation is proposed, and its limitations discussed.Comment: 6 pages, 3 figures, 1 table submitted to Nucleic Acids Researc

Nature of the glassy phase of RNA secondary structure

We characterize the low temperature phase of a simple model for RNA secondary structures by determining the typical energy scale E(l) of excitations involving l bases. At zero temperature, we find a scaling law E(l) \sim l^\theta with \theta \approx 0.23, and this same scaling holds at low enough temperatures. Above a critical temperature, there is a different phase characterized by a relatively flat free energy landscape resembling that of a homopolymer with a scaling exponent \theta=1. These results strengthen the evidence in favour of the existence of a glass phase at low temperatures.Comment: 7 pages, 1 figur

Retaining Residents Is Important to New Hampshire\u27s Future: Why Do People Stay?

A key factor impacting New Hampshire’s demographic and economic success is retaining and growing its population. What motivates people to move to New Hampshire is important to the state’s future and garners considerable policy attention. Much less consideration is given to retaining current residents. Yet on average, nearly 1.3 million New Hampshire residents do not migrate into or out of the state in a given year. Understanding why those residents stay in New Hampshire can be an important element of the state’s comprehensive development strategy. In this brief, authors Kristine Bundschuh and Kenneth Johnson discuss the results of NH Granite State Polls conducted from 2010–2012 and 2018–2019 that asked a representative sample of over 3,300 established residents to share, in their own words, their top three reasons for staying in New Hampshire rather than moving to another state. They report that most long-term residents stay in New Hampshire for multiple reasons, rather than just one. People are most likely to stay for economic reasons, the physical environment, family, and the social atmosphere. Reasons to stay are interconnected, with people appreciating the overall experience of living in New Hampshire because of a combination of local benefits. Given these findings, simple development strategies based on any one factor, like low taxes or stronger environmental laws, are unlikely to trigger substantial population retention alone. Rather, the multidimensional and interconnected reasons identified in the brief provide a roadmap for crafting programs and policies to maintain and enhance the state’s economic, social, and natural environment, both to retain more current residents and to attract new ones

Why People Move to and Stay in New Hampshire

Migration is important to New Hampshire’s demographic future. Traditionally, the state has grown both because of migration into it and because of the surplus of births over deaths. However, recently all of New Hampshire’s population growth has been due to migration. In this brief, authors Kenneth Johnson and Kristine Bundschuh analyze data from the University of New Hampshire Survey Center’s Granite State Poll to examine the characteristics of two groups of current New Hampshire residents—recent migrants and established residents—to understand why people move to and choose to stay in the state. Their findings illustrate that migration decisions are influenced by an interrelated set of factors that encompass elements of the state’s social, economic, and natural environment

Model for Folding and Aggregation in RNA Secondary Structures

We study the statistical mechanics of RNA secondary structures designed to have an attraction between two different types of structures as a model system for heteropolymer aggregation. The competition between the branching entropy of the secondary structure and the energy gained by pairing drives the RNA to undergo a `temperature independent' second order phase transition from a molten to an aggregated phase'. The aggregated phase thus obtained has a macroscopically large number of contacts between different RNAs. The partition function scaling exponent for this phase is \theta ~ 1/2 and the crossover exponent of the phase transition is \nu ~ 5/3. The relevance of these calculations to the aggregation of biological molecules is discussed.Comment: Revtex, 4 pages; 3 Figures; Final published versio

Discovery of new genes and deletion editing in Physarum mitochondria enabled by a novel algorithm for finding edited mRNAs

Gene finding is complicated in organisms that exhibit insertional RNA editing. Here, we demonstrate how our new algorithm Predictor of Insertional Editing (PIE) can be used to locate genes whose mRNAs are subjected to multiple frameshifting events, and extend the algorithm to include probabilistic predictions for sites of nucleotide insertion; this feature is particularly useful when designing primers for sequencing edited RNAs. Applying this algorithm, we successfully identified the nad2, nad4L, nad6 and atp8 genes within the mitochondrial genome of Physarum polycephalum, which had gone undetected by existing programs. Characterization of their mRNA products led to the unanticipated discovery of nucleotide deletion editing in Physarum. The deletion event, which results in the removal of three adjacent A residues, was confirmed by primer extension sequencing of total RNA. This finding is remarkable in that it comprises the first known instance of nucleotide deletion in this organelle, to be contrasted with nearly 500 sites of single and dinucleotide addition in characterized mitochondrial RNAs. Statistical analysis of this larger pool of editing sites indicates that there are significant biases in the 2 nt immediately upstream of editing sites, including a reduced incidence of nucleotide repeats, in addition to the previously identified purine-U bias

Analytical description of finite size effects for RNA secondary structures

The ensemble of RNA secondary structures of uniform sequences is studied analytically. We calculate the partition function for very long sequences and discuss how the cross-over length, beyond which asymptotic scaling laws apply, depends on thermodynamic parameters. For realistic choices of parameters this length can be much longer than natural RNA molecules. This has to be taken into account when applying asymptotic theory to interpret experiments or numerical results.Comment: 10 pages, 13 figures, published in Phys. Rev.

Quantification of the differences between quenched and annealed averaging for RNA secondary structures

The analytical study of disordered system is usually difficult due to the necessity to perform a quenched average over the disorder. Thus, one may resort to the easier annealed ensemble as an approximation to the quenched system. In the study of RNA secondary structures, we explicitly quantify the deviation of this approximation from the quenched ensemble by looking at the correlations between neighboring bases. This quantified deviation then allows us to propose a constrained annealed ensemble which predicts physical quantities much closer to the results of the quenched ensemble without becoming technically intractable.Comment: 9 pages, 14 figures, submitted to Phys. Rev.

Statistical mechanics of RNA folding: a lattice approach

We propose a lattice model for RNA based on a self-interacting two-tolerant trail. Self-avoidance and elements of tertiary structure are taken into account. We investigate a simple version of the model in which the native state of RNA consists of just one hairpin. Using exact arguments and Monte Carlo simulations we determine the phase diagram for this case. We show that the denaturation transition is first order and can either occur directly or through an intermediate molten phase.Comment: 8 pages, 9 figure