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Patterning precision under non-linear morphogen decay and molecular noise.

Jan Andreas AdelmannRoman VetterDagmar Iber
Published in: eLife (2023)
Morphogen gradients can instruct cells about their position in a patterned tissue. Non-linear morphogen decay has been suggested to increase gradient precision by reducing the sensitivity to variability in the morphogen source. Here, we use cell-based simulations to quantitatively compare the positional error of gradients for linear and non-linear morphogen decay. While we confirm that non-linear decay reduces the positional error close to the source, the reduction is very small for physiological noise levels. Far from the source, the positional error is much larger for non-linear decay in tissues that pose a flux barrier to the morphogen at the boundary. In light of this new data, a physiological role of morphogen decay dynamics in patterning precision appears unlikely.
Keyphrases
  • gene expression
  • stem cells
  • machine learning
  • artificial intelligence
  • cell proliferation
  • signaling pathway
  • cell cycle arrest
  • endoplasmic reticulum stress
  • cell death
  • cell therapy
  • cell fate