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Origins of extrinsic variability in eukaryotic gene expression

Author

Listed:
  • Dmitri Volfson

    (University of California San Diego
    University of California San Diego)

  • Jennifer Marciniak

    (University of California San Diego)

  • William J. Blake

    (Boston University)

  • Natalie Ostroff

    (University of California San Diego)

  • Lev S. Tsimring

    (University of California San Diego)

  • Jeff Hasty

    (University of California San Diego)

Abstract

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution1,2, determination of cell fates3,4 and the development of genetic disease5,6. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously7,8,9,10, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling11,12,13,14,15,16,17,18 with fluorescence data generated from multiple promoter–gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene9. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Suggested Citation

  • Dmitri Volfson & Jennifer Marciniak & William J. Blake & Natalie Ostroff & Lev S. Tsimring & Jeff Hasty, 2006. "Origins of extrinsic variability in eukaryotic gene expression," Nature, Nature, vol. 439(7078), pages 861-864, February.
  • Handle: RePEc:nat:nature:v:439:y:2006:i:7078:d:10.1038_nature04281
    DOI: 10.1038/nature04281
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    Citations

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    Cited by:

    1. Fu Audrey Qiuyan & Pachter Lior, 2016. "Estimating intrinsic and extrinsic noise from single-cell gene expression measurements," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(6), pages 447-471, December.
    2. Christoph Zechner & Heinz Koeppl, 2014. "Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-9, December.
    3. Arjun Raj & Charles S Peskin & Daniel Tranchina & Diana Y Vargas & Sanjay Tyagi, 2006. "Stochastic mRNA Synthesis in Mammalian Cells," PLOS Biology, Public Library of Science, vol. 4(10), pages 1-13, September.
    4. Mayu Sugiyama & Takashi Saitou & Hiroshi Kurokawa & Asako Sakaue-Sawano & Takeshi Imamura & Atsushi Miyawaki & Tadahiro Iimura, 2014. "Live Imaging-Based Model Selection Reveals Periodic Regulation of the Stochastic G1/S Phase Transition in Vertebrate Axial Development," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-16, December.
    5. Alan Veliz-Cuba & Andrew J Hirning & Adam A Atanas & Faiza Hussain & Flavia Vancia & Krešimir Josić & Matthew R Bennett, 2015. "Sources of Variability in a Synthetic Gene Oscillator," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-23, December.
    6. Marc S Sherman & Barak A Cohen, 2014. "A Computational Framework for Analyzing Stochasticity in Gene Expression," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-13, May.
    7. Stuart Aitken & Marie-Cécile Robert & Ross D Alexander & Igor Goryanin & Edouard Bertrand & Jean D Beggs, 2010. "Processivity and Coupling in Messenger RNA Transcription," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-12, January.
    8. Benjamin B Kaufmann & Qiong Yang & Jerome T Mettetal & Alexander van Oudenaarden, 2007. "Heritable Stochastic Switching Revealed by Single-Cell Genealogy," PLOS Biology, Public Library of Science, vol. 5(9), pages 1-8, September.

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