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RNA dot plots: an image representation for RNA secondary structure analysis and manipulations

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Abstract Dot plots were originally introduced in bioinformatics as dot‐containing images used to compare biological sequences and identify regions of close similarity between them. In addition to similarity, dot plots were extended to possibly represent interactions between building blocks of biological sequences, where the dots can vary in size or color according to desired features. In this survey, we first review their use in representing an RNA secondary structure, which has mostly been applied for displaying the output secondary structures as a result of running RNA folding prediction algorithms. Such a result may often contain suboptimal solutions in addition to the optimal one, which can be easily incorporated in the dot plot. We then proceed from their passive use of providing RNA secondary structure snapshots to their active use of illustrating RNA secondary structure manipulations in beneficial ways. While comparison between RNA secondary structures can mostly be done efficiently using a string representation, there are notable advantages in using dot plots for analyzing the suboptimal solutions that convey important information about the structure of the RNA molecule. In addition, structure‐based alignment of dot plots has been advanced considerably and the filtering of dot plots that considers chemical and enzymatic data from structure determination experiments has been suggested. We discuss these procedures and how they can be enhanced in the future by using an image representation to analyze RNA secondary structures and examine their manipulations. WIREs RNA 2013, 4:205–216. doi: 10.1002/wrna.1154 This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA

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Dot plot of a bistable RNA. A dot plot example using UNAFold68 of a bistable RNA from leptomonas collosoma spliced leader67 that assumes two different stable conformations. Optimal structure is depicted in red dots and suboptimal structure in green dots, respectively.

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An illustration of stem alignment using dot plots. The folding prediction result of an RNA segment taken from the small nuclear RNA SNORD73,55 using a dot plot representation (top left) that includes suboptimal solutions and a secondary structure drawing of the optimal solution (bottom). Panel on the right depicts a dot plot containing artificially drawn stems of interest, with arrows indicating a desired alignment of these stems with the structure contained in the dot plot of panel on the left.

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An example of suboptimal manipulations using dot plots. The folding predicted solution of an artificial RNA is drawn using a dot plot representation (top left), which contains both the optimal solution labeled ‘o’ and a suboptimal solution labeled ‘s’. The mutation at position (4,18) is circled and pointed to with a line because it can potentially enhance a suboptimal solution. The RNA secondary structure drawing of the optimal solution is shown (top right). The folding predicted solution of the mutated artificial RNA is drawn using a dot plot (bottom left), showing that the suboptimal solution of the wild‐type became the optimal solution of the mutated sequence. The RNA secondary structure drawing of the new optimal solution is shown (bottom right).

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