TY - JOUR
T1 - A tractable physical model for the yeast polarity predicts epistasis and fitness
AU - Daalman, Werner Karl Gustav
AU - Sweep, Els
AU - Laan, Liedewij
PY - 2023
Y1 - 2023
N2 - Accurate phenotype prediction based on genetic information has numerous societal applications, such as crop design or cellular factories. Epistasis, when biological components interact, complicates modelling phenotypes from genotypes. Here we show an approach to mitigate this complication for polarity establishment in budding yeast, where mechanistic information is abundant. We coarse-grain molecular interactions into a so-called mesotype, which we combine with gene expression noise into a physical cell cycle model. First, we show with computer simulations that the mesotype allows validation of the most current biochemical polarity models by quantitatively matching doubling times. Second, the mesotype elucidates epistasis emergence as exemplified by evaluating the predicted mutational effect of key polarity protein Bem1p when combined with known interactors or under different growth conditions. This example also illustrates how unlikely evolutionary trajectories can become more accessible. The tractability of our biophysically justifiable approach inspires a road-map towards bottom-up modelling complementary to statistical inferences. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
AB - Accurate phenotype prediction based on genetic information has numerous societal applications, such as crop design or cellular factories. Epistasis, when biological components interact, complicates modelling phenotypes from genotypes. Here we show an approach to mitigate this complication for polarity establishment in budding yeast, where mechanistic information is abundant. We coarse-grain molecular interactions into a so-called mesotype, which we combine with gene expression noise into a physical cell cycle model. First, we show with computer simulations that the mesotype allows validation of the most current biochemical polarity models by quantitatively matching doubling times. Second, the mesotype elucidates epistasis emergence as exemplified by evaluating the predicted mutational effect of key polarity protein Bem1p when combined with known interactors or under different growth conditions. This example also illustrates how unlikely evolutionary trajectories can become more accessible. The tractability of our biophysically justifiable approach inspires a road-map towards bottom-up modelling complementary to statistical inferences. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
KW - bottom-up modelling
KW - budding yeast
KW - epistasis
KW - genotype–phenotype map
KW - polarity
UR - http://www.scopus.com/inward/record.url?scp=85151346813&partnerID=8YFLogxK
U2 - 10.1098/rstb.2022.0044
DO - 10.1098/rstb.2022.0044
M3 - Article
C2 - 37004720
AN - SCOPUS:85151346813
SN - 1471-2970
VL - 378
SP - 20220044
JO - Philosophical transactions of the Royal Society of London. Series B, Biological sciences
JF - Philosophical transactions of the Royal Society of London. Series B, Biological sciences
IS - 1877
M1 - 20220044
ER -