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Biophysical ambiguities prevent accurate genetic prediction

Author

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  • Xianghua Li

    (Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology)

  • Ben Lehner

    (Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology
    Universitat Pompeu Fabra (UPF)
    ICREA)

Abstract

A goal of biology is to predict how mutations combine to alter phenotypes, fitness and disease. It is often assumed that mutations combine additively or with interactions that can be predicted. Here, we show using simulations that, even for the simple example of the lambda phage transcription factor CI repressing a gene, this assumption is incorrect and that perfect measurements of the effects of mutations on a trait and mechanistic understanding can be insufficient to predict what happens when two mutations are combined. This apparent paradox arises because mutations can have different biophysical effects to cause the same change in a phenotype and the outcome in a double mutant depends upon what these hidden biophysical changes actually are. Pleiotropy and non-monotonic functions further confound prediction of how mutations interact. Accurate prediction of phenotypes and disease will sometimes not be possible unless these biophysical ambiguities can be resolved using additional measurements.

Suggested Citation

  • Xianghua Li & Ben Lehner, 2020. "Biophysical ambiguities prevent accurate genetic prediction," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18694-0
    DOI: 10.1038/s41467-020-18694-0
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    Cited by:

    1. Xuan Xie & Xia Sun & Yuheng Wang & Ben Lehner & Xianghua Li, 2023. "Dominance vs epistasis: the biophysical origins and plasticity of genetic interactions within and between alleles," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Matteo Cagiada & Sandro Bottaro & Søren Lindemose & Signe M. Schenstrøm & Amelie Stein & Rasmus Hartmann-Petersen & Kresten Lindorff-Larsen, 2023. "Discovering functionally important sites in proteins," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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