Phenotypic plasticity, the ability of a single genotype to produce multiple phenotypes under different environmental conditions, is critical for the origins and maintenance of biodiversity; however, the genetic mechanisms underlying plasticity as well as how variation in those mechanisms can drive evolutionary change remain poorly understood. Here, we examine the cichlid feeding apparatus, an icon of both prodigious evolutionary divergence and adaptive phenotypic plasticity. We first provide a tissue-level mechanism for plasticity in craniofacial shape by measuring rates of bone deposition within functionally salient elements of the feeding apparatus in fishes forced to employ alternate foraging modes. We show that levels and patterns of phenotypic plasticity are distinct among closely related cichlid species, underscoring the evolutionary potential of this trait. Next, we demonstrate that hedgehog (Hh) signaling, which has been implicated in the evolutionary divergence of cichlid feeding architecture, is associated with environmentally induced rates of bone deposition. Finally, to demonstrate that Hh levels are the cause of the plastic response and not simply the consequence of producing more bone, we use transgenic zebrafish in which Hh levels could be experimentally manipulated under different foraging conditions. Notably, we find that the ability to modulate bone deposition rates in different environments is dampened when Hh levels are reduced, whereas the sensitivity of bone deposition to different mechanical demands increases with elevated Hh levels. These data advance a mechanistic understanding of phenotypic plasticity in the teleost feeding apparatus and in doing so contribute key insights into the origins of adaptive morphological radiations.

Bone deposition rate data were collected via dual fluorochrome labeling, followed by fluorescence microscopy. All bone deposition data were analyzed in R. See methods section in the associated article for additional details.

Gene expression data were collected via RT-qPCR and quantified in R. See methods section in the associated article for additional details, including primer sequences. 

Missing values are denoted as NA in the datasets.