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Genome Network and FANTOM3: Assessing the Complexity of the Transcriptome

PLoS Genetics
Public Library of Science
Publication Date
DOI: 10.1371/journal.pgen.0020063
  • Editorial
  • Bioinformatics - Computational Biology
  • Biotechnology
  • Evolution
  • Genetics/Gene Expression
  • Homo (Human)
  • Mus (Mouse)
  • Biology


plge-02-04-23 492..497 Editorial Genome Network and FANTOM3: Assessing the Complexity of the Transcriptome Yoshihide Hayashizaki*, Piero Carninci The findings of the FANTOM3/Genome Network project haveredefined the landscape of the mammalian transcriptome by introducing an extensive collection of novel cDNAs and millions of sequenced tags corresponding to 59- and 39-ends of mRNAs. This issue of PLoS Genetics includes a special collection of articles that explore the transcriptome complexity being revealed by work on the FANTOM3 dataset. Besides revealing staggering complexity, analysis of this collection is providing an increasing number of novel mRNA classes, expressed pseudogenes, and bona fide noncoding variants of protein-coding genes. In addition, new types of regulatory logic have emerged, including sense–antisense mechanisms of RNA regulation. This high- resolution cDNA collection and its analysis represent an important world resource for discovery, and demonstrate the value of large-scale transcriptome approaches towards understanding genome function. The Era of Transcriptome Technology: From RNA to Function After the completion of several genome sequences [1,2] the scientific community has been pondering what type of technologies are necessary for understanding the underlying biology of genomes. Two classes of novel technologies, one based on the hybridization of nucleic acids and the other on sequencing products from mRNA libraries, are already affecting the way we understand biological systems. Hybridization-based methods, such as genome tiling arrays [3–5], have some specific advantages: in a single experiment they can give a draft description of the transcriptome, or of genome elements selected by chromatin immunoprecipitation (ChIP) [6]. Although a general picture of the transcriptome can be produced quickly, important details such as transcriptional start sites (TSSs) cannot be accurately identified at single-base resolution, nor can such methods determine the exact

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