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An evaluation of detection methods for large lariat RNAs.

ABSTRACT: Ty1 elements are long terminal repeat (LTR) retrotransposons that reside within the genome of Saccharomyces cerevisiae. It has been known for many years that the 2'-5' phosphodiesterase Dbr1p, which debranches intron lariats, is required for efficient Ty1 transposition. A recent report suggested the intriguing possibility that Ty1 RNA forms a lariat as a transposition intermediate. We set out to further investigate the nature of the proposed Ty1 lariat branchpoint. However, using a wide range of techniques we were unable to find any evidence for the proposed lariat structure. Furthermore, we demonstrate that some of the techniques used in the initial study describing the lariat are capable of incorrectly reporting a lariat structure. Thus, the role of the Dbr1 protein in Ty1 retrotransposition remains elusive.

SUBMITTER: Coombes CE

PROVIDER: S-EPMC1370721 | biostudies-literature | 2005 Mar

REPOSITORIES: biostudies-literature

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An evaluation of detection methods for large lariat RNAs.

Coombes Candice E CE Boeke Jef D JD

RNA (New York, N.Y.) 20050120 3

Ty1 elements are long terminal repeat (LTR) retrotransposons that reside within the genome of Saccharomyces cerevisiae. It has been known for many years that the 2'-5' phosphodiesterase Dbr1p, which debranches intron lariats, is required for efficient Ty1 transposition. A recent report suggested the intriguing possibility that Ty1 RNA forms a lariat as a transposition intermediate. We set out to further investigate the nature of the proposed Ty1 lariat branchpoint. However, using a wide range of ...[more]

PMID: 15661842

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Project description:Large-scale identification of metabolites is key to elucidating and modeling metabolism at the systems level. Advances in metabolomics technologies, particularly ultra-high resolution mass spectrometry (MS) enable comprehensive and rapid analysis of metabolites. However, a significant barrier to meaningful data interpretation is the identification of a wide range of metabolites including unknowns and the determination of their role(s) in various metabolic networks. Chemoselective (CS) probes to tag metabolite functional groups combined with high mass accuracy provide additional structural constraints for metabolite identification and quantification. We have developed a novel algorithm, Chemically Aware Substructure Search (CASS) that efficiently detects functional groups within existing metabolite databases, allowing for combined molecular formula and functional group (from CS tagging) queries to aid in metabolite identification without a priori knowledge. Analysis of the isomeric compounds in both Human Metabolome Database (HMDB) and KEGG Ligand demonstrated a high percentage of isomeric molecular formulae (43 and 28%, respectively), indicating the necessity for techniques such as CS-tagging. Furthermore, these two databases have only moderate overlap in molecular formulae. Thus, it is prudent to use multiple databases in metabolite assignment, since each major metabolite database represents different portions of metabolism within the biosphere. In silico analysis of various CS-tagging strategies under different conditions for adduct formation demonstrate that combined FT-MS derived molecular formulae and CS-tagging can uniquely identify up to 71% of KEGG and 37% of the combined KEGG/HMDB database vs. 41 and 17%, respectively without adduct formation. This difference between database isomer disambiguation highlights the strength of CS-tagging for non-lipid metabolite identification. However, unique identification of complex lipids still needs additional information.

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An evaluation of detection methods for large lariat RNAs.

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An evaluation of detection methods for large lariat RNAs.

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