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Questions and answers => RNA structures (DSSR) => DSSR-NAR paper => Topic started by: xiangjun on July 03, 2015, 11:37:23 am

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Title: Reproducing results published in the DSSR-NAR paper
Post by: xiangjun on July 03, 2015, 11:37:23 am
I am pleased to announce that a paper on DSSR, an integrated software tool for dissecting the spatial structure of RNA (https://nar.oxfordjournals.org/content/43/21/e142.full), has recently been published in Nucleic Acids Research (NAR). Co-authored by Harmen Bussemaker, Wilma Olson and me (a team with a unique combination of complementary expertise), this DSSR paper represents another solid piece of work that I can be proud of. Moreover, in contrast to our previous GpU dinucleotide platform (http://nar.oxfordjournals.org/content/38/14/4868.full) paper focusing on results, and the two major 3DNA papers (http://goo.gl/SZyNn) concentrating on methods, the current NAR article describes significant scientific findings that are enabled by the novel analysis algorithms implemented in the DSSR software program. The abstract of the paper is quoted below:

Insight into the three-dimensional architecture of RNA is essential for understanding its cellular functions. However, even the classic transfer RNA structure contains features that are overlooked by existing bioinformatics tools. Here we present DSSR (Dissecting the Spatial Structure of RNA), an integrated and automated tool for analyzing and annotating RNA tertiary structures. The software identifies canonical and noncanonical base pairs, including those with modified nucleotides, in any tautomeric or protonation state. DSSR detects higher-order coplanar base associations, termed multiplets. It finds arrays of stacked pairs, classifies them by base-pair identity and backbone connectivity, and distinguishes a stem of covalently connected canonical pairs from a helix of stacked pairs of arbitrary type/linkage. DSSR identifies coaxial stacking of multiple stems within a single helix and lists isolated canonical pairs that lie outside of a stem. The program characterizes ‘closed’ loops of various types (hairpin, bulge, internal, and junction loops) and pseudoknots of arbitrary complexity. Notably, DSSR employs isolated pairs and the ends of stems, whether pseudoknotted or not, to define junction loops. This new, inclusive definition provides a novel perspective on the spatial organization of RNA. Tests on all nucleic acid structures in the Protein Data Bank confirm the efficiency and robustness of the software, and applications to representative RNA molecules illustrate its unique features. DSSR and related materials are freely available at http://x3dna.org/.

This section on the 3DNA Forum is dedicated to topics on reproducing the results reported in the DSSR article. In the following series of posts, I will provide the scripts and related data files where necessary so that any interested parties can rigorously reproduce our results, as presented (mostly) in the table and figures (including supplementary ones). I welcome any questions and comments you may have. Please post them here instead of (or in addition to) sending me emails.

Table 1: summary of structural features identified by DSSR (in default settings) for ten representative RNA molecules (http://forum.x3dna.org/dssr-nar-paper/summary-table/).

Six main figures

Supplementary data: nine figures and the main output of a sample DSSR run, combined into one PDF file (Lu-DSSR-supp.pdf (http://x3dna.bio.columbia.edu/dssr-nar/Lu-DSSR-supp.pdf))

Cartoon-block representations: four more sample schematic images (http://forum.x3dna.org/dssr-nar-paper/rna-cartoon-block-representations-with-pymol-and-dssr/) created with PyMOL and DSSR (cartoon-block.tar.gz (http://x3dna.bio.columbia.edu/dssr-nar/cartoon-block.tar.gz)). Thomas Holder, the Principal Developer of PyMOL, has written a PyMOL plugin that implements the dssr_block (https://pymolwiki.org/index.php/Dssr_block) command. Now users can create "block" shaped cartoons for nucleic acid bases and base pairs interactively in PyMOL.

Best regards,


Created and maintained by Dr. Xiang-Jun Lu[律祥俊]· Supported by the NIH grant R01GM096889 · Dr. Lu is currently a member of the Bussemaker Laboratory at the Department of Biological Sciences, Columbia University. The project is in collabration with the Olson Laborarory at Rutgers where 3DNA got started.