IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0176228.html
   My bibliography  Save this article

Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression

Author

Listed:
  • David M Holloway
  • Alexander V Spirov

Abstract

Anterior-posterior (AP) body segmentation of the fruit fly (Drosophila) is first seen in the 7-stripe spatial expression patterns of the pair-rule genes, which regulate downstream genes determining specific segment identities. Regulation of pair-rule expression has been extensively studied for the even-skipped (eve) gene. Recent live imaging, of a reporter for the 2nd eve stripe, has demonstrated the stochastic nature of this process, with ‘bursts’ in the number of RNA transcripts being made over time. We developed a stochastic model of the spatial and temporal expression of eve stripe 2 (binding by transcriptional activators (Bicoid and Hunchback proteins) and repressors (Giant and Krüppel proteins), transcriptional initiation and termination; with all rate parameters constrained by features of the experimental data) in order to analyze the noisy experimental time series and test hypotheses for how eve transcription is regulated. These include whether eve transcription is simply OFF or ON, with a single ON rate, or whether it proceeds by a more complex mechanism, with multiple ON rates. We find that both mechanisms can produce long (multi-minute) RNA bursts, but that the short-time (minute-to-minute) statistics of the data is indicative of eve being transcribed with at least two distinct ON rates, consistent with data on the joint activation of eve by Bicoid and Hunchback. We also predict distinct statistical signatures for cases in which eve is repressed (e.g. along the edges of the stripe) vs. cases in which activation is reduced (e.g. by mutagenesis of transcription factor binding sites). Fundamental developmental processes such as gene transcription are intrinsically noisy; our approach presents a new way to quantify and analyze time series data during developmental patterning in order to understand regulatory mechanisms and how they propagate noise and impact embryonic robustness.

Suggested Citation

  • David M Holloway & Alexander V Spirov, 2017. "Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-24, April.
  • Handle: RePEc:plo:pone00:0176228
    DOI: 10.1371/journal.pone.0176228
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176228
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0176228&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0176228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. William J. Blake & Mads KÆrn & Charles R. Cantor & J. J. Collins, 2003. "Noise in eukaryotic gene expression," Nature, Nature, vol. 422(6932), pages 633-637, April.
    2. David M Holloway & Francisco J P Lopes & Luciano da Fontoura Costa & Bruno A N Travençolo & Nina Golyandina & Konstantin Usevich & Alexander V Spirov, 2011. "Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-18, February.
    3. Johannes Jaeger & Svetlana Surkova & Maxim Blagov & Hilde Janssens & David Kosman & Konstantin N. Kozlov & Manu & Ekaterina Myasnikova & Carlos E. Vanario-Alonso & Maria Samsonova & David H. Sharp & J, 2004. "Dynamic control of positional information in the early Drosophila embryo," Nature, Nature, vol. 430(6997), pages 368-371, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Xiaoli & Wu, Fengyan & Duan, Jinqiao & Kurths, Jürgen & Li, Xiaofan, 2019. "Most probable dynamics of a genetic regulatory network under stable Lévy noise," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 425-436.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefano Ciliberti & Olivier C Martin & Andreas Wagner, 2007. "Robustness Can Evolve Gradually in Complex Regulatory Gene Networks with Varying Topology," PLOS Computational Biology, Public Library of Science, vol. 3(2), pages 1-10, February.
    2. Li, Hongying & Yao, Chengli, 2017. "The influence of internal noise on the detection of hormonal signal with the existence of external noise in a cell system," Applied Mathematics and Computation, Elsevier, vol. 314(C), pages 1-6.
    3. Mohammad Soltani & Cesar A Vargas-Garcia & Duarte Antunes & Abhyudai Singh, 2016. "Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-23, August.
    4. Chih-Yuan Hsu & Bor-Sen Chen, 2016. "Systematic Design of a Metal Ion Biosensor: A Multi-Objective Optimization Approach," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    5. Kolja Becker & Eva Balsa-Canto & Damjan Cicin-Sain & Astrid Hoermann & Hilde Janssens & Julio R Banga & Johannes Jaeger, 2013. "Reverse-Engineering Post-Transcriptional Regulation of Gap Genes in Drosophila melanogaster," PLOS Computational Biology, Public Library of Science, vol. 9(10), pages 1-16, October.
    6. Blasi, Monica Francesca & Casorelli, Ida & Colosimo, Alfredo & Blasi, Francesco Simone & Bignami, Margherita & Giuliani, Alessandro, 2005. "A recursive network approach can identify constitutive regulatory circuits in gene expression data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 349-370.
    7. Chunjuan Zhu & Zibo Chen & Qiwen Sun, 2022. "Stochastic Transcription with Alterable Synthesis Rates," Mathematics, MDPI, vol. 10(13), pages 1-20, June.
    8. Ronald Thenius & Michael Bodi & Thomas Schmickl & Karl Crailsheim, 2013. "Novel method of virtual embryogenesis for structuring Artificial Neural Network controllers," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 19(4), pages 375-387.
    9. Valenti, D. & Tranchina, L. & Brai, M. & Caruso, A. & Cosentino, C. & Spagnolo, B., 2008. "Environmental metal pollution considered as noise: Effects on the spatial distribution of benthic foraminifera in two coastal marine areas of Sicily (Southern Italy)," Ecological Modelling, Elsevier, vol. 213(3), pages 449-462.
    10. Tobias May & Lee Eccleston & Sabrina Herrmann & Hansjörg Hauser & Jorge Goncalves & Dagmar Wirth, 2008. "Bimodal and Hysteretic Expression in Mammalian Cells from a Synthetic Gene Circuit," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-7, June.
    11. Seyed Yahya Anvar & Allan Tucker & Veronica Vinciotti & Andrea Venema & Gert-Jan B van Ommen & Silvere M van der Maarel & Vered Raz & Peter A C ‘t Hoen, 2011. "Interspecies Translation of Disease Networks Increases Robustness and Predictive Accuracy," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-14, November.
    12. Michael W Klymkowsky & Kathy Garvin-Doxas, 2008. "Recognizing Student Misconceptions through Ed's Tools and the Biology Concept Inventory," PLOS Biology, Public Library of Science, vol. 6(1), pages 1-4, January.
    13. Diana Monteoliva & Christina B McCarthy & Luis Diambra, 2013. "Noise Minimisation in Gene Expression Switches," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-9, December.
    14. Burton W Andrews & Pablo A Iglesias, 2007. "An Information-Theoretic Characterization of the Optimal Gradient Sensing Response of Cells," PLOS Computational Biology, Public Library of Science, vol. 3(8), pages 1-9, August.
    15. Elijah Roberts & Andrew Magis & Julio O Ortiz & Wolfgang Baumeister & Zaida Luthey-Schulten, 2011. "Noise Contributions in an Inducible Genetic Switch: A Whole-Cell Simulation Study," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-21, March.
    16. Maksat Ashyraliyev & Ken Siggens & Hilde Janssens & Joke Blom & Michael Akam & Johannes Jaeger, 2009. "Gene Circuit Analysis of the Terminal Gap Gene huckebein," PLOS Computational Biology, Public Library of Science, vol. 5(10), pages 1-16, October.
    17. G.-W. Weber & P. Taylan & S. Alparslan-Gök & S. Özöğür-Akyüz & B. Akteke-Öztürk, 2008. "Optimization of gene-environment networks in the presence of errors and uncertainty with Chebychev approximation," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 284-318, December.
    18. 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.
    19. Chen, Aimin & Tian, Tianhai & Chen, Yiren & Zhou, Tianshou, 2022. "Stochastic analysis of a complex gene-expression model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    20. Arantxa Urchueguía & Luca Galbusera & Dany Chauvin & Gwendoline Bellement & Thomas Julou & Erik van Nimwegen, 2021. "Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network," PLOS Biology, Public Library of Science, vol. 19(12), pages 1-22, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0176228. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.