RoboOligo: software for mass spectrometry data to support manual and de novo sequencing of post-transcriptionally modified ribonucleic acids

نویسندگان

  • Paul J. Sample
  • Kirk W. Gaston
  • Juan D. Alfonzo
  • Patrick A. Limbach
چکیده

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. Modified RNAs are analyzed by MS using collision-induced dissociation tandem mass spectrometry (CID MS/MS), which produces a complex dataset of oligomeric fragments that must be interpreted to identify and place modified nucleosides within the RNA sequence. Here we report the development of RoboOligo, 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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Mapping Post-Transcriptional Modifications onto Transfer Ribonucleic Acid Sequences by Liquid Chromatography Tandem Mass Spectrometry

Liquid chromatography, coupled with tandem mass spectrometry, has become one of the most popular methods for the analysis of post-transcriptionally modified transfer ribonucleic acids (tRNAs). Given that the information collected using this platform is entirely determined by the mass of the analyte, it has proven to be the gold standard for accurately assigning nucleobases to the sequence. For ...

متن کامل

PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry.

A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing softwa...

متن کامل

An Information Theoretic Approach to Rescoring Peptides Produced by De Novo Peptide Sequencing

Tandem mass spectrometry (MS/MS) is the engine driving high-throughput protein identification. Protein mixtures possibly representing thousands of proteins from multiple species are treated with proteolytic enzymes, cutting the proteins into smaller peptides that are then analyzed generating MS/MS spectra. The task of determining the identity of the peptide from its spectrum is currently the we...

متن کامل

PEAKS: Powerful Software for Peptide De Novo Sequencing by MS/MS

A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing softwa...

متن کامل

Optimization algorithm for de novo analysis of tandem

Protein identification is usually achieved by tandem mass spectrometry (MS/MS). Because of the difficulty in measuring complete proteins using MS/MS, typically a protein is enzymatically digested into peptides and the MS/MS spectrum of each peptide is measured. The database searching methods are predominant in the task of peptide identification. Their aim is to find the best match between model...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 43  شماره 

صفحات  -

تاریخ انتشار 2015