Brain anatomy is highly variable and it is widely accepted that anatomical variation impacts brain function and ultimately behavior. The structural complexity of the brain, including differences in volume and shape, presents an enormous barrier to define how variability underlies differences in function. In this study, we sought to investigate the evolution of brain anatomy in relation to brain region volume and shape across the brain of a single species with variable genetic and anatomical morphs. We generated a high-resolution brain atlas for the blind Mexican cavefish and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface to cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted in cavefish, while ventral regions have expanded. This trend is true for both volume and shape, suggesting that these two parameters share developmental mechanisms necessary for remodeling the entire brain. Given the high conservation of brain anatomy and function among vertebrate species, we expect these data to reveal generalized principles of brain evolution and show that Astyanax provides a system for functionally determining basic principles of brain evolution by utilizing the independent genetic diversity of different morphs, to test how genes influence early patterning events to drive brain-wide anatomical evolution.  

Brains were stained with p44/42 MAP Kinase (L34F12) Mouse mAb, which detects endogenous levels of total p44/42 MAP kinase (Erk1/Erk2) protein. This antibody provides a brain-wide immunolabeling stain that was then used to register all surface fish, Pachon cavefish and surface to Pachon hybrid (F1 and F2) to a common Astyanax Mexicanus atlas. This atlas was then inverse registered to each indivdual brain (see paper for technical details), providing automated segmentation of upto 180 unique brain regions. These segmented brains were then run through the morphometric analysis program CobraZ (Gupta et al. 2018), providing brain region volume in percentage of total brain volume. Populations were then compared statistically using a hom's corrected t-test in CobraZ for wildtype surface and Pachon populations, and a holm's corrected ANOVA in graphpad Prism for wildtype and hybrid populations. After extracting 3D models of the preoptic region of the hypothalamus and pineal body of the diencephalon, we characterized shape variation using 3D geometric morphometrics (LandmarkEditor (v3.0) (47). To assess differences we performed a procrustes superimposition on our shape data to remove the effects of translation, rotation, and scaling from all individuals using the gpagen function from the geomorph (v4.0) package in R. We then assessed differences in shape among populations and performed a multivariate regression of shape on centroid size and population (i.e., surface, cave, hybrid) using the procD.lm r function from geomorph.

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