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. 2023 Jan;25(1):85-102.
doi: 10.1111/ede.12421. Epub 2022 Nov 14.

Covariation of brain and skull shapes as a model to understand the role of crosstalk in development and evolution

Andrew J Conith  1 , Sylvie A Hope  1 , R Craig Albertson  1
Affiliations

Covariation of brain and skull shapes as a model to understand the role of crosstalk in development and evolution

Andrew J Conith et al. Evol Dev. 2023 Jan.

Abstract

Covariation among discrete phenotypes can arise due to selection for shared functions, and/or shared genetic and developmental underpinnings. The consequences of such phenotypic integration are far-reaching and can act to either facilitate or limit morphological variation. The vertebrate brain is known to act as an "organizer" of craniofacial development, secreting morphogens that can affect the shape of the growing neurocranium, consistent with roles for pleiotropy in brain-neurocranium covariation. Here, we test this hypothesis in cichlid fishes by first examining the degree of shape integration between the brain and the neurocranium using three-dimensional geometric morphometrics in an F5 hybrid population, and then genetically mapping trait covariation using quantitative trait loci (QTL) analysis. We observe shape associations between the brain and the neurocranium, a pattern that holds even when we assess associations between the brain and constituent parts of the neurocranium: the rostrum and braincase. We also recover robust genetic signals for both hard- and soft-tissue traits and identify a genomic region where QTL for the brain and braincase overlap, implicating a role for pleiotropy in patterning trait covariation. Fine mapping of the overlapping genomic region identifies a candidate gene, notch1a, which is known to be involved in patterning skeletal and neural tissues during development. Taken together, these data offer a genetic hypothesis for brain-neurocranium covariation, as well as a potential mechanism by which behavioral shifts may simultaneously drive rapid change in neuroanatomy and craniofacial morphology.

Keywords: bone; brain; development; geometric morphometrics; phenotypic integration.

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Figures

Figure 1
Figure 1
Cichlid brain–neurocranium anatomy and the implications for covariation. (a) Line drawing demonstrating the relative positions of the brain (gray) positioned within the braincase region of the neurocranium (blue). (b) The two major subregions of the neurocranium are the rostrum (anterior) and braincase (posterior). These regions were developmentally and statistically defined based on tissue origin and modularity analyses (see Materials and methods/Results section), respectively. (c) Hypotheses for the phenotypic association between the brain and neurocranium, alongside its subregions. Given the brain likely acts as an “organizer” of craniofacial shape, each neurocranial subregion will receive a different concentration of morphogens diffusing from the brain (braincase, high; rostrum, low), suggesting proximity of the brain to a given tissue should manifest in the strength of covariation between structures. (d) Hypotheses for the genetic association between the brain and neurocranium. Top, the genetic map depicts substantial overlap between brain and neurocranium traits, suggesting similar genomic regions may regulate both structures, consistent with pleiotropy. Bottom, the genetic map depicts little overlap between brain and neurocranium traits, suggesting different genomic regions may regulate each structure, consistent with processes above the level of genome regulating covariation. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 2
Figure 2
Brain and neurocranium anatomical outlines and landmark placement. (a) Left, cichlid neurocranium depicting the major subregions, the braincase and rostrum. Right, cichlid brain depicting the major subregions discussed in this study. (b–d) CAD templates used for automated mapping of surface semilandmarks onto brain models. (e–g) Fixed (black) and sliding semilandmarks (red) placed on the template match those placed on all hybrid brain models to assist in directing automated surface sliding semilandmark locations (blue). (h–j) Neurocranium fixed landmark placement positions across all hybrid cichlid individuals. Landmark color scheme reflects module partitions: green, rostrum module; red, shared rostrum/braincase module; purple, braincase module. (b–j) From left to right: left ¾ view, lateral view, dorsal view. Detailed information on landmark placement can be found in Table 1. Anatomical naming conventions taken from Liem and Osse (1975). Neurocranium: Orb, orbit; PS, parasphenoid; PT, posttemporal SOC, supraoccipital crest; Vo, vomer. Brain: Ce, cerebellum; Hyp, hypothalamus; Me, medulla; OB, olfactory bulbs; OC, optic chiasm; Pa, pallium; Spa, subpallium; TeO, optic tectum. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 3
Figure 3
Neurocranium and brain principal component morphospaces for all F5 hybrid individuals. Primary and secondary axes of variation with representative individuals illustrate morphological differences among the hybrid population. Representative neurocranium and brain images are presented in the right lateral (top) and dorsal (bottom) views for all structures. (a) Neurocranium morphospace and representative individuals at the terminal ends of each axis. (b) brain morphospace and representative individuals at the terminal ends of each axis. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 4
Figure 4
Two‐block partial least‐squares analysis to assess the association between the brain and the constituent parts of the neurocranium: the rostrum and braincase. Representative hybrid individuals are included to illustrate the morphological differences across the primary axes of covariation. (a) Brain and rostrum. (b) Brain and braincase. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 5
Figure 5
Statistical genetic analyses to uncover regions of the genome responsible covariation between brain and neurocranium. (a) Quantitative trait loci analysis to identify regions in the genome associated with each covarying trait. (b) Fine‐mapping brain–braincase covariation and (c) braincase–brain covariation across LG 7. The trait in square brackets in the figure legend represents the covarying trait. Values far from 0 denote large differences in trait values between hybrids with either a Labeotropheus fuelleborni (LF) or Tropheops sp. “red cheek” (TRC) genotype at a given marker. We observe peak genotype‐phenotype association at ~50 Mb that coincides with our Bayes credible interval (gray bar). Solid line represents the mean phenotypic effect and lighter polygon represents the standard error. (d) Fine mapping the brain–braincase covarying traits across the Bayes credible interval on LG 7. Population level genetic diversity (F ST) data are included on the map (black points) with their opacity dependent on the degree of marker segregation between LF and TRC. Within the credible interval (gray bar), there are three F ST values of 1.0 (indicating alternate fixation) that reside close to a genotype–phenotype peak for both traits (purple circle). (e) Pleiotropy analysis across LG 7 to assess evidence of shared genetic control of brain and braincase trait covariation. The pleiotropy peak between traits occurs at approximately 20 centimorgans (cM) along LG 7. [Color figure can be viewed at wileyonlinelibrary.com]
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