Towards automating structural analysis of complex RNA molecules and some applications in nanotechnology
Year: 2015
Type: article
Abstract: Neocles B. Leontis, Advisor RNA has emerged as a versatile and multi-faceted player in gene expression and the informational metabolism of living cells.RNA molecules can function by virtue of their sequences, storing or transmitting genetic information, as well as by forming complex threedimensional (3D) structures that can bind specifically to proteins, small molecules or other RNA or DNA molecules to carry out diverse recognition functions, including chemical catalysis.As a result of revolutions in RNA 3D structure determination and high-throughput DNA and RNA sequencing, on-line databases are brimming with new structure and sequence data.The large amounts of new data are creating new challenges in data management, curation, search, visualization, and access.For example, ribosomes have been solved in many different functional states, with tRNAs variously bound to the A-, P-, or E-sites, or associated with different translation factors (i.e.initiation, elongation, termination or recycling factors) or antibiotics.Detailed and accurate functional annotations are needed to enable focused database searches for specific states and bound ligands and to uncover new relationships regarding structure, function, and evolution of RNA molecules and their complexes.As large numbers of new structures are accumulating in databases faster than they can be manually annotated, automated annotation procedures need to be developed and deployed by databases such as the Nucleic Acid Database (NDB).In addition to annotation of individual structures, related structures must be identified, compared and clustered, and representative structures chosen for detailed analysis.To facilitate research, clustering should be dynamic and user driven.iv The unifying theme of this dissertation is to develop new conceptual frameworks and analytical approaches to assess and improve the automated annotation and analysis of RNA 3D structures, and to connect these data to structural changes in functional state and evolutionary changes.More specifically, the dissertation focuses on analysis of 3D structures of ribosomal RNA (rRNA) from the large (LSU) and small (SSU) subunits of ribosomes, and the hairpin and internal loop motifs extracted from them.A manual analysis was carried out of all atomicresolution, 3D structures of the SSU of the bacterium T. thermophilus found in the NDB as of April, 2014, structure equivalence class NR_4.0_81883.24,release 1.56 of ribosome structures posted in the NDB (see http://rna.bgsu.edu/rna3dhub/nrlist).Each structure was manually examined to determine the functional annotations for the state of the ribosome with all bound tRNAs, mRNAs and other factors.These data were combined in a single spreadsheet found at this link: http://tinyurl.com/16S-T-Thermophilus-summary.NDB maintains a Non-redundant (NR) set of structures that is updated each week and used to construct the 3D Motif Atlas of RNA hairpin and internal loop motifs (http://rna.bgsu.edu/rna3dhub/motifs).To assess the quality of motif clustering in the Motif Atlas, links and meta-data were downloaded and analyzed for all motif instances in release 1.14 (http://rna.bgsu.edu/rna3dhub/motifs/release/IL/1.14).Overall, motifs found in conserved regions of the rRNAs were placed in the same motif groups by the automated clustering.Information must flow between different parts of the ribosome to report on the state of one part that is relevant to another part.One hypothesis is that networks of RNA tertiary and quaternary interactions play a central role in the ribosome.As a first step to automatically detecting and comparing networks of RNA-RNA interactions in the ribosome, a new module was created for the FR3D ("Find RNA 3D") suite of RNA analysis tools.This module can perform the analysis of large structures automatically.v To my Mother: "Multumesc ca esti mama mea." vi
Author: Lorena Parlea
Institution: Bowling Green State University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2519270825