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Central dogma rates and the trade-off between precision and economy in gene expression

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  • Jean Hausser

    (Weizmann Institute of Science)

  • Avi Mayo

    (Weizmann Institute of Science)

  • Leeat Keren

    (Weizmann Institute of Science)

  • Uri Alon

    (Weizmann Institute of Science)

Abstract

Steady-state protein abundance is set by four rates: transcription, translation, mRNA decay and protein decay. A given protein abundance can be obtained from infinitely many combinations of these rates. This raises the question of whether the natural rates for each gene result from historical accidents, or are there rules that give certain combinations a selective advantage? We address this question using high-throughput measurements in rapidly growing cells from diverse organisms to find that about half of the rate combinations do not exist: genes that combine high transcription with low translation are strongly depleted. This depletion is due to a trade-off between precision and economy: high transcription decreases stochastic fluctuations but increases transcription costs. Our theory quantitatively explains which rate combinations are missing, and predicts the curvature of the fitness function for each gene. It may guide the design of gene circuits with desired expression levels and noise.

Suggested Citation

  • Jean Hausser & Avi Mayo & Leeat Keren & Uri Alon, 2019. "Central dogma rates and the trade-off between precision and economy in gene expression," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-07391-8
    DOI: 10.1038/s41467-018-07391-8
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    Cited by:

    1. Claire S. Chung & Yi Kou & Sarah J. Shemtov & Bert M. Verheijen & Ilse Flores & Kayla Love & Ashley Dosso & Max A. Thorwald & Yuchen Liu & Daniel Hicks & Yingwo Sun & Renaldo G. Toney & Lucy Carrillo , 2024. "Transcript errors generate amyloid-like proteins in human cells," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Niklas Korsbo & Henrik Jönsson, 2020. "It’s about time: Analysing simplifying assumptions for modelling multi-step pathways in systems biology," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-29, June.
    3. Isabelle Rose Leo & Luay Aswad & Matthias Stahl & Elena Kunold & Frederik Post & Tom Erkers & Nona Struyf & Georgios Mermelekas & Rubin Narayan Joshi & Eva Gracia-Villacampa & Päivi Östling & Olli P. , 2022. "Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines," Nature Communications, Nature, vol. 13(1), pages 1-19, December.

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