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    Augmented annotation of the Schizosaccharomyces pombe genome reveals additional genes required for growth and viability.

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    Authors
    Bitton, Danny A
    Wood, V
    Scutt, Paul J
    Grallert, Agnes
    Yates, Tim
    Smith, Duncan L
    Hagan, Iain M
    Miller, Crispin J
    Affiliation
    Cancer Research UK Applied Computational Biology and Bioinformatics Group, University of Manchester, Christie Hospital Site, Manchester M20 4BX, United Kingdom.
    Issue Date
    2011-04
    
    Metadata
    Show full item record
    Abstract
    Genome annotation is a synthesis of computational prediction and experimental evidence. Small genes are notoriously difficult to detect because the patterns used to identify them are often indistinguishable from chance occurrences, leading to an arbitrary cutoff threshold for the length of a protein-coding gene identified solely by in silico analysis. We report a systematic reappraisal of the Schizosaccharomyces pombe genome that ignores thresholds. A complete six-frame translation was compared to a proteome data set, the Pfam domain database, and the genomes of six other fungi. Thirty-nine novel loci were identified. RT-PCR and RNA-Seq confirmed transcription at 38 loci; 33 novel gene structures were delineated by 5' and 3' RACE. Expression levels of 14 transcripts fluctuated during meiosis. Translational evidence for 10 genes, evolutionary conservation data supporting 35 predictions, and distinct phenotypes upon ORF deletion (one essential, four slow-growth, two delayed-division phenotypes) suggest that all 39 predictions encode functional proteins. The popularity of S. pombe as a model organism suggests that this augmented annotation will be of interest in diverse areas of molecular and cellular biology, while the generality of the approach suggests widespread applicability to other genomes.
    Citation
    Augmented annotation of the Schizosaccharomyces pombe genome reveals additional genes required for growth and viability. 2011, 187 (4):1207-17 Genetics
    Journal
    Genetics
    URI
    http://hdl.handle.net/10541/201529
    DOI
    10.1534/genetics.110.123497
    PubMed ID
    21270388
    Type
    Article
    Language
    en
    ISSN
    1943-2631
    ae974a485f413a2113503eed53cd6c53
    10.1534/genetics.110.123497
    Scopus Count
    Collections
    All Paterson Institute for Cancer Research

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