Display Settings:

Format

Send to:

Choose Destination
    Nat Methods. 2008 Jul;5(7):613-9. Epub 2008 May 30.

    Stem cell transcriptome profiling via massive-scale mRNA sequencing.

    Source

    Expression Genomics Laboratory, Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, St. Lucia, Queensland, 4072, Australia.

    Abstract

    We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A)(+) transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete.

    PMID:
    18516046
    [PubMed - indexed for MEDLINE]

      Supplemental Content

      Icon for Nature Publishing Group

      Save items

      loading

      Recent activity

      Your browsing activity is empty.

      Activity recording is turned off.

      Turn recording back on

      See more...
      Write to the Help Desk