Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria
Por:
Leifer, Ian, Sanchez-Perez, Mishael, Ishida, Cecilia, Makse, Hernan A.
Publicada:
8 jul 2021
Resumen:
Background: Gene regulatory networks coordinate the expression of genes
across physiological states and ensure a synchronized expression of
genes in cellular subsystems, critical for the coherent functioning of
cells. Here we address the question whether it is possible to predict
gene synchronization from network structure alone. We have recently
shown that synchronized gene expression can be predicted from symmetries
in the gene regulatory networks described by the concept of symmetry
fibrations. We showed that symmetry fibrations partition the genes into
groups called fibers based on the symmetries of their `input trees', the
set of paths in the network through which signals can reach a gene. In
idealized dynamic gene expression models, all genes in a fiber are
perfectly synchronized, while less idealized models-with gene input
functions differencing between genes-predict symmetry breaking and
desynchronization.
Results: To study the functional role of gene fibers and to test whether
some of the fiber-induced coexpression remains in reality, we analyze
gene fibrations for the gene regulatory networks of E. coli and B.
subtilis and confront them with expression data. We find approximate
gene coexpression patterns consistent with symmetry fibrations with
idealized gene expression dynamics. This shows that network structure
alone provides useful information about gene synchronization, and
suggest that gene input functions within fibers may be further
streamlined by evolutionary pressures to realize a coexpression of
genes.
Conclusions: Thus, gene fibrations provide a sound conceptual tool to
describe tunable coexpression induced by network topology and shaped by
mechanistic details of gene expression.
Filiaciones:
CUNY City Coll, Dept Phys, Levich Inst, New York, NY 10031 USA
Univ Nacl Autonoma Mexico, Programa Genom Computac, Ctr Ciencias Genom, Cuernavaca, Morelos, Mexico
Autonomous Univ Chihuahua, Fac Med & Biomed Sci, Chihuahua 31125, Chihuahua, Mexico
Green Published, Green Submitted, gold
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