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While capillary electrophoresis (CE) based sequencers are ubiquitous at most institutions, their application to quantitative nucleic acid structural characterization requires special expertise. We therefore set out to harness the potential of CE for the structural characterization of nucleic acids by quantitative chemical mapping. A major limitation to their adoption for nucleic acid structural analysis is the absence of software that can quantitate the elution trace. The base calling algorithms necessary for sequencing are not suitable for quantification of the chemical and enzymatic mapping data necessary for structural analysis. Rather, an algorithm capable of deconvoluting overlapping signal is necessary along with software that transforms and manipulates the mapping data. To take advantage of high throughput CE sequencers, we have developed the experimental protocols and the Capillary Automated Footprinting Analysis (CAFA) software described available here that builds upon tested GE analysis tools. The structural analyses derived from CAFA based analysis will be a valuable addition to genome analyses.
Keywords: RNA folding
Local probes of macromolecular structure are measurements that are sensitive to the environment of a relatively small region within a macromolecule. These include, but are not limited to, NMR deuterium exchange and shift perturbation analysis, Fluorescence Resonance Energy Transfer (FRET), and RNA/DNA protein footprinting. The separate transitions reported by individual probes yield unique insight into folding intermediates. While simultaneous acquisition of many unique local transitions provides a cornucopia of information, creating an accurate global description of folding that remains faithful to local details is very challenging. This software package can be used to analyze such data. Initially, the data is clustered to identify major common transitions. Then, all possible kinetic model topologies are generated and tested to identify the best fitting kinetic model. The software creates a number of graphs and figures to explain the data.
This project is a data analysis package to analyze and normalize SHAPE data. Traditionally, SHAPE requires the addition of a 3' hairpin to the RNA for normalization. noRNAlize elminates the need for this experimental step by performing a global analysis of the SHAPE data, and establishing mean protection values. This is particularly important when SHAPE analysis is used to map crystal contacts in crystal structures as illustrated here.
Keywords: chemical probing, footprinting, molecular biology, RNA folding
This project is a python module that manages the processing of RNA PDB files by RNAVIEW, and which organizes the results into a database and provides for basic querying against that database. A primary purpose is to be able to generate basepair and helix descriptors that are written in terms of the PDB chain ID and PDB resseq numbers, rather than (generally somewhat different) indices than is used in the RNAVIEW rnaml output.
Quantitative analysis of gels from hydroxyl radical footprinting and other structure mapping techniques can provide a great deal of insight into the structural details of RNA molecules. We have developed and implemented a software package (SAFA v1.1) that allows rapid quantification of a footprinting gel. By automating many of the steps involved in gel analysis, we estimate that an entire gel with thousands of bands can be quantified in less than 10 minutes. In general all the automated features have amanual override, such that even difficult or exceptional gels can be analyzed with the package.