Doctor of Philosophy (Ph.D.), Bowling Green State University, 2012, Biological Sciences

Many hairpin and internal RNA 3D motif structures are recurrent, occurring in various types of RNA molecules, not necessarily homologs. Although usually drawn as single-strand “loops” in RNA 2D diagrams, recurrent motifs share a common 3D structure, but can vary in sequence. It is essential to understand the sequence variability of RNA 3D motifs in order to advance the RNA 2D and 3D structure prediction and ncRNA discovery methods, to interpret mutations that affect ncRNAs, and to guide experimental functional studies. The dissertation is organized into two parts as follows. First, the development of a new online resource called RNA 3D Hub is described, which is intended to provide a useful resource for structure modeling and prediction. It houses non-redundant sets of RNA-containing 3D structures, RNA 3D motifs extracted from all RNA 3D structures, and the RNA 3D Motif Atlas, a representative collection of RNA 3D motifs. Unique and stable ids are assigned to all non-redundant equivalence classes of structure files, to all motifs, and to all motif instances. RNA 3D Hub is updated automatically on a regular schedule and is available at http://rna.bgsu.edu/rna3dhub. In the second part of the dissertation, the development of WebFR3D (http://rna.bgsu.edu/webfr3d), a new webserver for finding and aligning RNA 3D motifs, is described and its use in a biologically relevant context is then illustrated using two RNA 3D motifs. The first motif was predicted in Potato Spindle Tuber Viroid (PSTVd), and the prediction was supported by functional evidence. The second motif had previously been undescribed, although it is found in multiple 3D structures. RNA 3D Hub, RNA 3D Motif Atlas, and the bioinformatic techniques discussed in this dissertation lay the groundwork for further research into RNA 3D motif prediction starting from sequence and provide useful online resources for the scientific community worldwide.

Committee: Neocles Leontis PhD (Advisor); Craig Zirbel PhD (Committee Member); Paul Morris PhD (Committee Member); Scott Rogers PhD (Committee Member); Raymond Larsen PhD (Committee Member) Subjects: Bioinformatics; Biology

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2016, Biological Sciences

This dissertation contains two types of work. The first is the creation and maintenance of our data pipeline. This chapter focuses on the technical work behind the extension of our pipeline. In general, this work extends our previous pipeline to import more data as well as standardizing several parts of the pipeline. As a result, this work provides a framework for future modifications of the pipeline. This work was driven both by the move from RNA 3D structures being provided in mmCIF format instead of the more limited PDB format, as well as the need to clean up the previous version of the pipeline. The second type of work is scientific including my work on creating equivalence classes for all RNA 3D structures, using these sets to build representative sets and then how to use these representative sets along with new quality data to select a set of high quality loops for future analysis. The new work on equivalence classes and representative sets was driven by the move from PDB to mmCIF formats. This move forced the redesign of the previous method, as it would only use the largest chain in each PDB file. This change allowed me to reconsider the approach and allowed several improvements. The work on loop quality was prompted by the release of new structure quality data, Real Space R Z-Score (RSRZ). This data allows the examination of how well a proposed structure fits the data it is built from. By using this we can limit our studies of RNA loops to only those that are from high quality, well modeled structures.

Committee: Neocles Leontis (Advisor); Raymond Larsen (Committee Member); George Bullerjahn (Committee Member); Hans Wildschutte (Committee Member); Howard Cromwell (Other) Subjects: Bioinformatics; Biology