Evolutionary dimension reduction in phenotypic space
Takuya U. Sato, Kunihiko Kaneko

TL;DR
This study reveals that phenotypic changes in evolving cells are predominantly confined to a low-dimensional subspace, which simplifies understanding biological adaptation and evolution by linking it to the dominant singular value of the inverse Jacobian matrix.
Contribution
The paper introduces a dynamical systems framework to explain phenotypic dimension reduction and demonstrates its occurrence through numerical evolution of cellular models.
Findings
Phenotypic changes are mainly restricted to a one-dimensional subspace.
A single large singular value dominates the inverse Jacobian matrix at fixed points.
Phenotypic evolution exploits this constrained direction, leading to convergent pathways.
Abstract
In general, cellular phenotypes, as measured by concentrations of cellular components, involve large degrees of freedom. However, recent measurement has demonstrated that phenotypic changes resulting from adaptation and evolution in response to environmental changes are effectively restricted to a low-dimensional subspace. Thus, uncovering the origin and nature of such a drastic dimension reduction is crucial to understanding the general characteristics of biological adaptation and evolution. Herein, we first formulated the dimension reduction in terms of dynamical systems theory: considering the steady growth state of cells, the reduction is represented by the separation of a few large singular values of the inverse Jacobian matrix around a fixed point. We then examined this dimension reduction by numerical evolution of cells consisting of thousands of chemicals whose concentrations…
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