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Developmental nonlinearity drives phenotypic robustness.

Rebecca M GreenJennifer L FishNathan M YoungFrancis J SmithBenjamin S RobertsKatie DolanIrene ChoiCourtney L LeachPaul GordonJames M CheverudCharles C RosemanTrevor J WilliamsRalph S MarcucioBenedikt Hallgrimsson
Published in: Nature communications (2017)
Robustness to perturbation is a fundamental feature of complex organisms. Mutations are the raw material for evolution, yet robustness to their effects is required for species survival. The mechanisms that produce robustness are poorly understood. Nonlinearities are a ubiquitous feature of development that may link variation in development to phenotypic robustness. Here, we manipulate the gene dosage of a signaling molecule, Fgf8, a critical regulator of vertebrate development. We demonstrate that variation in Fgf8 expression has a nonlinear relationship to phenotypic variation, predicting levels of robustness among genotypes. Differences in robustness are not due to gene expression variance or dysregulation, but emerge from the nonlinearity of the genotype-phenotype curve. In this instance, embedded features of development explain robustness differences. How such features vary in natural populations and relate to genetic variation are key questions for unraveling the origin and evolvability of this feature of organismal development.
Keyphrases
  • gene expression
  • machine learning
  • deep learning
  • poor prognosis
  • transcription factor
  • dna methylation
  • multidrug resistant