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Natural genetic variation impacts expression levels of coding, non-coding, and antisense transcripts in fission yeast

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Authors:
  • Clément-Ziza, Mathieu ;
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    Dresden University of Technology
  • Marsellach, Francesc X. ;
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    University College London
  • Codlin, Sandra ;
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    University College London
  • Papadakis, Manos A. ;
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    Technical University of Denmark
  • Reinhardt, Susanne ;
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    Dresden University of Technology
  • Rodríguez-López, María ;
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    University College London
  • Martin, Stuart ;
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    University College London
  • Marguerat, Samuel ;
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    University College London
  • Schmidt, Alexander ;
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    University of Basel
  • Lee, Eunhye ;
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    University College London
  • Workman, Christopher ;
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    Orcid logo0000-0002-2210-3743
    Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark
  • Bähler, Jürg ;
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    University College London
  • Beyer, Andreas
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    Dresden University of Technology
DOI:
10.15252/msb.20145123
Abstract:
Our current understanding of how natural genetic variation affects gene expression beyond well-annotated coding genes is still limited. The use of deep sequencing technologies for the study of expression quantitative trait loci (eQTLs) has the potential to close this gap. Here, we generated the first recombinant strain library for fission yeast and conducted an RNA-seq-based QTL study of the coding, non-coding, and antisense transcriptomes. We show that the frequency of distal effects (trans-eQTLs) greatly exceeds the number of local effects (cis-eQTLs) and that non-coding RNAs are as likely to be affected by eQTLs as protein-coding RNAs. We identified a genetic variation of swc5 that modifies the levels of 871 RNAs, with effects on both sense and antisense transcription, and show that this effect most likely goes through a compromised deposition of the histone variant H2A.Z. The strains, methods, and datasets generated here provide a rich resource for future studies.
Type:
Journal article
Language:
English
Published in:
Molecular Systems Biology, 2014, Vol 10, Issue 764
Main Research Area:
Science/technology
Publication Status:
Published
Review type:
Peer Review
Submission year:
2015
Scientific Level:
Scientific
ID:
272935487

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