Evaluating gene expression dynamics using pairwise RNA fish data

Matthieu Wyart, David Botstein, Ned S. Wingreen

    Research output: Contribution to journalArticle

    Abstract

    Recently, a novel approach has been developed to study gene expression in single cells with high time resolution using RNA Fluorescent In Situ Hybridization (FISH). The technique allows individual mRNAs to be counted with high accuracy in wildtype cells, but requires cells to be fixed; thus, each cell provides only a ''snapshot'' of gene expression. Here we show how and when RNA FISH data on pairs of genes can be used to reconstruct real-time dynamics from a collection of such snapshots. Using maximum-likelihood parameter estimation on synthetically generated, noisy FISH data, we show that dynamical programs of gene expression, such as cycles (e.g., the cell cycle) or switches between discrete states, can be accurately reconstructed. In the limit that mRNAs are produced in short-lived bursts, binary thresholding of the FISH data provides a robust way of reconstructing dynamics. In this regime, prior knowledge of the type of dynamics - cycle versus switch - is generally required and additional constraints, e.g., from triplet FISH measurements, may also be needed to fully constrain all parameters. As a demonstration, we apply the thresholding method to RNA FISH data obtained from single, unsynchronized cells of Saccharomyces cerevisiae. Our results support the existence of metabolic cycles and provide an estimate of global gene-expression noise. The approach to FISH data presented here can be applied in general to reconstruct dynamics from snapshots of pairs of correlated quantities including, for example, protein concentrations obtained from immunofluorescence assays.

    Original languageEnglish (US)
    Article numbere1000979
    JournalPLoS Computational Biology
    Volume6
    Issue number11
    DOIs
    StatePublished - Nov 2010

    Fingerprint

    In Situ Hybridization
    Fish
    RNA
    Fluorescence In Situ Hybridization
    Gene expression
    in situ hybridization
    Gene Expression
    gene expression
    Pairwise
    Fishes
    fish
    Snapshot
    Cell
    Switches
    Thresholding
    Cycle
    Messenger RNA
    cells
    Switch
    Yeast

    ASJC Scopus subject areas

    • Cellular and Molecular Neuroscience
    • Ecology
    • Molecular Biology
    • Genetics
    • Ecology, Evolution, Behavior and Systematics
    • Modeling and Simulation
    • Computational Theory and Mathematics

    Cite this

    Evaluating gene expression dynamics using pairwise RNA fish data. / Wyart, Matthieu; Botstein, David; Wingreen, Ned S.

    In: PLoS Computational Biology, Vol. 6, No. 11, e1000979, 11.2010.

    Research output: Contribution to journalArticle

    Wyart, Matthieu ; Botstein, David ; Wingreen, Ned S. / Evaluating gene expression dynamics using pairwise RNA fish data. In: PLoS Computational Biology. 2010 ; Vol. 6, No. 11.
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