Developmental nonlinearity drives phenotypic robustness

Abstract

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.

Nonlinear gene expression‐phenotype relationships contribute to variation and clefting in the A/WySn mouse

“…This relationship may be a general attribute of signaling pathways and that changes in levels of signaling molecules along the nonlinear curve are likely to result in differences in phenotypic variance. We have shown similar types of nonlinear gene expression‐phenotype maps for FGF signaling, SHH signaling and now WNT signaling. The results imply that this mechanism may be involved in, not just dramatic phenotypes, but also smaller phenotypic changes which can result in birth defects such as CL/P.…”

“…Embryos were fixed and set in the PAXgene tissue system as outlined in Green et al The embryos were microCT scanned using a Scanco UCT 35 desktop scanner also according to the protocol outlined in Reference , briefly, embryos contrasted in 1% iodine metal in PAX tissue stabilizer for 1 hour and were scanned in air in a sealed microfuge tube with a small amount of clean PAX tissue stabilizer. They were scanned at 11 μm resolution at 55 kpv.…”

“…Data were modeled using a von Bertalanffy growth curve based on the relationship suggested by nonparametric curve fits . We used a nonlinear least‐squares regression approach to identify the coefficients of the curve.…”

“…Such gene expression to phenotype maps are known in only a few cases for a genetically complex morphological trait like facial shape. We have previously shown that for Fgf8 expression or SHH signaling, this map is highly nonlinear with loss of up to 50% of Fgf8 expression producing no effect on morphology while changes below 50% produce large changes . Such gene expression to phenotype maps are distinct from genotype‐phenotype maps.…”

Novel approach to quantitative spatial gene expression uncovers genetic stochasticity in the developing Drosophila eye

“…Indeed, the genetic basis of adaptation is often inferred to be due to differences in gene expression (Chan et al, ; Gompel, Prud'homme, Wittkopp, Kassner, & Carroll, ; Hoekstra & Coyne, ; Jeong et al, ; Pai & Gilad, ; Signor, Liu, Rebeiz, & Kopp, ; Wray, ; Yassin et al, ). This balance between stability and lability is a question that has been addressed philosophically, but little experimental evidence exists to suggest the mechanisms underlying these phenomena (Casci, ; Gibson, ; Green et al, ; Heranz & Cohen, ; Hermisson & Wagner, ; Nijhout et al, ; Rutherford et al, ; Stern, ; True & Haag, ).…”