10.5061/DRYAD.BF597
Sellis, Diamantis
Stanford University
Longo, Mark D.
Stanford University
Data from: Patterns of variation during adaptation in functionally linked loci
Dryad
dataset
2014
metabolic pathway
fine-tuning
2014-09-08T17:43:37Z
2014-09-08T17:43:37Z
en
https://doi.org/10.1111/evo.12548
14145 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
An understanding of the distribution of natural patterns of genetic
variation is relevant to such fundamental biological fields as evolution
and development. One recent approach to understanding such patterns has
been to focus on the constraints which may arise as a function of the
network or pathway context in which genes are embedded. Despite
theoretical expectations of higher evolutionary constraint for genes
encoding upstream versus downstream enzymes in metabolic pathways,
empirical results have varied. Here we combine two complementary models
from population genetics and enzyme kinetics to explore genetic variation
as a function of pathway position when selection acts on whole-pathway
flux. We are able to qualitatively reproduce empirically observed patterns
of polymorphism and divergence and suggest that expectations should vary
depending on the evolutionary trajectory of a population. Upstream genes
are initially more polymorphic and diverge faster after an environmental
change, while we see the opposite trend as the population approaches its
fitness optimum.
simulation of pathway evolutionmg.140313.tar.gz