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Related Experiment Videos

Gene discovery and annotation using LCM-454 transcriptome sequencing.

Scott J Emrich1, W Brad Barbazuk, Li Li

  • 1Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50010, USA.

Genome Research
|November 11, 2006
PubMed
Summary
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Laser capture microdissection combined with 454 sequencing identified novel maize shoot apical meristem transcripts. This approach discovered rare, cell-type-specific genes previously undetected in maize EST collections.

Area of Science:

  • Plant Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • The shoot apical meristem (SAM) is crucial for plant development.
  • Previous maize EST projects using hand-dissected tissue missed many SAM-specific transcripts.
  • Deep sequencing technologies offer potential for discovering rare transcripts.

Purpose of the Study:

  • To identify novel transcripts from maize shoot apical meristem (SAM) using advanced sequencing.
  • To compare transcript discovery efficiency between laser capture microdissection (LCM) and traditional methods.
  • To validate and characterize novel SAM-expressed genes.

Main Methods:

  • Isolation of cDNA from maize SAM using laser capture microdissection (LCM).
  • High-throughput sequencing of cDNA using 454 Life Sciences technology.

Related Experiment Videos

  • Bioinformatic analysis of expressed sequence tags (ESTs) and alignment to existing databases.
  • Validation of novel gene expression using RT-PCR.

    • Main Results:

    • Generated over 261,000 maize ESTs, annotating >25,000 genomic sequences.
    • Discovered approximately 400 novel transcripts lacking homologous sequences in other species.
    • Identified over 70% new ESTs compared to a previous project, with 30% unaligned to existing maize ESTs.
    • Validated 27 novel SAM-expressed genes, finding 74% were not detected in immature ears.

    Conclusions:

    • The combination of LCM and 454 sequencing effectively enriches for rare and cell-type-specific SAM transcripts.
    • This integrated approach significantly expands the maize transcriptomic dataset.
    • Facilitates the discovery of novel genes potentially involved in maize development and function.