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Related Experiment Video

Updated: May 5, 2026

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Vespucci: a system for building annotated databases of nascent transcripts.

Karmel A Allison1, Minna U Kaikkonen, Terry Gaasterland

  • 1Department of Cellular and Molecular Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, USA, Department of Bioinformatics and Systems Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, USA, San Diego Center for Systems Biology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0375, USA, A.I. Virtanen Institute, Department of Biotechnology and Molecular Medicine, University of Eastern Finland, P.O. Box 1627, 70120 Kuopio, Finland, Institute for Genomic Medicine and Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, USA and Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, USA.

Nucleic Acids Research
|December 6, 2013
PubMed
Summary
This summary is machine-generated.

A new algorithm, Vespucci, identifies novel RNA transcripts from GRO-sequencing data. This method enhances understanding of non-coding RNA and expands current gene annotations for mammalian cells.

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Area of Science:

  • Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • Global run-on sequencing (GRO-seq) offers insights into cellular transcriptional dynamics.
  • Existing analysis tools for ChIP-seq and RNA-seq are inadequate for de novo transcript identification from GRO-seq data.

Purpose of the Study:

  • To develop a novel algorithm and system for de novo transcript identification from GRO-sequencing data.
  • To analyze GRO-seq data from mouse macrophages to characterize non-coding transcription.

Main Methods:

  • A novel algorithm, Vespucci, was developed for de novo transcript identification.
  • The system determines transcript regions, stores them in a database, and links them to reference annotations.
  • GRO-sequencing data from primary mouse macrophages was analyzed.

Main Results:

  • Vespucci expands annotations for mRNAs and lincRNAs by defining primary transcripts beyond polyadenylation sites.
  • The system generates assemblies for un-annotated non-coding RNAs, including those from enhancer-like elements.
  • Novel quantitative insights into mammalian non-coding transcription were derived.

Conclusions:

  • Vespucci provides a robust system for defining, storing, and analyzing diverse primary RNA transcripts.
  • The findings highlight the extent and characteristics of non-coding transcription in mammalian cells.
  • This work advances the study of transcriptional dynamics and RNA biology.