RNA characterization software tools | Mass spectrometry-based untargeted proteomics
Ribosomal ribonucleic acid (RNA), transfer RNA and other biological or synthetic RNA polymers can contain nucleotides that have been modified by the addition of chemical groups. Traditional Sanger sequencing methods cannot establish the chemical nature and sequence of these modified-nucleotide containing oligomers. Mass spectrometry (MS) has become the conventional approach for determining the nucleotide composition, modification status and sequence of modified RNAs.
An interactive software program for the robust analysis of data generated by CID MS/MS of RNA oligomers. There are three main functions of RoboOligo: (i) automated de novo sequencing via the local search paradigm. (ii) Manual sequencing with real-time spectrum labeling and cumulative intensity scoring. (iii) A hybrid approach, coined ‘variable sequencing’, which combines the user intuition of manual sequencing with the high-throughput sampling of automated de novo sequencing.
Permits users to utilize mass spectral data to detect miRNA by sequence, name, mass, accession number, and RNA modification. MicroRNA MultiTool contains features for eliminating the need of performing tandem mass spectrometry on a miRNA for the sole purpose of its identification. In summary, it has three main functionalities: (1) miRNA search and mass calculator; (2) modified miRNA mass calculator; and (3) miRNA fragment search.
Offers a database search engine for RNA with a focus on high-resolution mass spectrometry (MS) data. NASE is an open-source software that reports oligonucleotide-spectrum matches with statistically meaningful false discovery rate (FDR) scores. It can support arbitrary modifications as well as salt adducts. This tool can also be downloaded as part of the OpenMS software.
Searches whole prokaryotic genomes or RNA FASTA sequence databases to identify the origin of a given RNA based on a mass spectrum of RNA fragments. As input, the program uses the masses of specific RNase cleavage of the RNA under investigation. RNase T1 digestion is used here as a demonstration of the usability of the method for RNA identification. The concept for identification is that the masses of the digestion products constitute a specific fingerprint, which characterize the given RNA. The search algorithm is based on the same principles as those used in peptide mass fingerprinting, but has here been extended to work for both RNA sequence databases and for genome searches. A simple and powerful probability model for ranking RNA matches is proposed.