Ecomorphological studies evaluating the impact of environmental and biological factors on the brain have so far focused on morphology or size measurements, and the ecological relevance of potential multi-level variations in brain architecture remains unclear in vertebrates. Here, we exploit the extraordinary ecomorphological diversity of squamates to assess brain phenotypic diversification with respect to locomotor specialization, by integrating single-cell distribution and transcriptomic data along with geometric morphometric, phylogenetic, and volumetric analysis of high-definition 3D models. We reveal significant changes in cerebellar shape and size as well as alternative spatial layouts of cortical neurons and dynamic gene expression that all correlate with locomotor behaviours. These findings show that locomotor mode is a strong predictor of cerebellar structure and pattern, suggesting that major behavioural transitions in squamates are evolutionarily correlated with mosaic brain changes. Furthermore, our study amplifies the concept of ‘cerebrotype’, initially proposed for vertebrate brain proportions, towards additional shape characters.

While floral symmetry has traditionally been assessed qualitatively, recent advances in geometric morphometrics have opened up new avenues to specifically quantify flower shape and size using robust multivariate statistical methods. In this study, we examine, for the first time, the ability of geometric morphometrics to detect morphological differences in floral dorsoventral asymmetry following virus-induced gene silencing (VIGS). Using Fedia graciliflora Fisch. & Meyer (Valerianaceae) as a model, corolla shape of untreated flowers was compared using canonical variate analysis to knockdown phenotypes of CYCLOIDEA2A (FgCYC2A), ANTHOCYANIDIN SYNTHASE (FgANS), and empty vector controls. Untreated flowers and all VIGS treatments were morphologically distinct from each other, suggesting that VIGS may cause subtle shifts in floral shape. Knockdowns of FgCYC2A were the most dramatic, affecting the position of dorsal petals in relation to lateral petals, thereby resulting in more actinomorphic-like flowers. Additionally, FgANS knockdowns developed larger flowers with wider corolla tube openings. These results provide a method to quantify the role that specific genes play in the developmental pathway affecting the dorsoventral axis of symmetry in zygomorphic flowers. Additionally, they suggest that ANS may have an unintended effect on floral size and shape.

Symmetry is a pervasive feature of organismal shape and the focus of a large body of research in Biology. Here, we consider complex patterns of symmetry where a phenotype exhibits a hierarchically structured combination of symmetries. We extend the Procrustes ANOVA for the analysis of nested symmetries and the decomposition of the overall morphological variation into components of symmetry (among-individual variation) and asymmetry (directional and fluctuating asymmetry). We illustrate its use with the Aristotle’s lantern, the masticatory apparatus of ‘regular’ sea urchins, a complex organ displaying bilateral symmetry nested within five-fold rotational symmetry. Our results highlight the importance of characterising the full symmetry of a structure with nested symmetries. Higher order rotational symmetry appears strongly constrained and developmentally stable compared to lower level bilateral symmetry. This contrast between higher and lower levels of asymmetry is discussed in relation to the spatial pattern of the lantern morphogenesis. This extended framework is applicable to any biological object exhibiting nested symmetries, regardless of their type (e.g., bilateral, rotational, translational). Such cases are extremely widespread in animals and plants, from arthropod segmentation to angiosperm inflorescence and corolla shape. The method therefore widens the research scope on developmental instability, canalization, developmental modularity and morphological integration.

Genic copy number differences can have phenotypic consequences, but so far this has not been studied in detail in natural populations. Here, we analysed the natural variation of two families of tandemly repeated regulatory small nucleolar RNAs (SNORD115 and SNORD116) in the house mouse (Mus musculus). They are encoded within the Prader‐Willi Syndrome gene region, known to be involved in behavioural, metabolic, and osteogenic functions in mammals. We determined that the copy numbers of these SNORD RNAs show substantial natural variation, both in wild‐derived mice as well as in an inbred mouse strain (C57BL/6J). We show that copy number differences are subject to change across generations, making them highly variable and resulting in individual differences. In transcriptome data from brain samples, we found SNORD copy‐number correlated regulation of possible target genes, including Htr2c, a predicted target gene of SNORD115, as well as Ankrd11, a predicted target gene of SNORD116. Ankrd11 is a chromatin regulator, which has previously been implicated in regulating the development of the skull. Based on morphometric shape analysis of the skulls of individual mice of the inbred strain, we show that shape measures correlate with SNORD116 copy numbers in the respective individuals. Our results suggest that the variable dosage of regulatory RNAs can lead to phenotypic variation between individuals that would typically have been ascribed to environmentally induced variation, while it is actually encoded in individual differences of copy numbers of regulatory molecules.

Various advances in 3D automatic phenotyping and landmark-based geometric morphometric methods have been made. While it is generally accepted that automatic landmarking compromises the capture of the biological variation, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to extract an actual biological signal adequately. Here, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. We find that most significant SNPs and QTLs are not recovered based on the data derived from the automatic landmarking method. Our results thus confirm the notion that information is lost in the automated landmarking procedure although somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question.