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Transcriptome annotation using tandem SAGE tags.

Eric Rivals1, Anthony Boureux, Mireille Lejeune

  • 1Laboratoire d'Informatique, de Robotique et de Microélectronique, UMR 5506 CNRS-Université de Montpellier II, 161 rue Ada, 34392 Montpellier 05, France.

Nucleic Acids Research
|August 22, 2007
PubMed
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This study introduces a novel Serial Analysis of Gene Expression (SAGE) strategy using dual tags to identify new RNA transcripts. This method enhances transcriptome annotation by revealing previously unrecognized genomic sequences.

Area of Science:

  • Genomics and Transcriptomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Millions of expressed gene signatures (tags) reveal more unique sequences than annotated genes in mammalian genomes.
  • Serial Analysis of Gene Expression (SAGE) identifies novel Poly(A) RNAs from previously unrecognized chromosomal regions.
  • Conventional SAGE tags are too short for unambiguous identification in large genomes.

Purpose of the Study:

  • To design a novel SAGE strategy for improved transcriptome annotation.
  • To develop and validate an algorithm for locating tag-delimited genomic sequences (TDGS).
  • To predict unknown transcripts using human SAGE tag data.

Main Methods:

  • A novel SAGE strategy using two distinct restriction sites on cDNAs.

Related Experiment Videos

  • Development of a new algorithm to locate tag-delimited genomic sequences (TDGS).
  • Processing of complete human SAGE tag sets and cross-validation with tiling array data.

    • Main Results:

    • The novel strategy and algorithm successfully identified known genes and revealed new transcripts.
    • The algorithm is efficient for large-scale analysis.
    • Cross-validation showed that 47% of predicted TDGS overlap with actively transcribed regions.

    Conclusions:

    • The developed dual-tag SAGE strategy and TDGS algorithm offer a novel approach for transcriptome annotation.
    • This method complements existing techniques for discovering previously unrecognized transcripts.
    • The findings contribute to a more comprehensive understanding of complex mammalian transcriptomes.