Biology subjects

Cheverud, J.

Publications and source records attributed to Cheverud, J..

3 recordsLinked to original sources

bioRxiv2021

Morphological integration during postnatal ontogeny: implications for evolutionary biology

How covariance patterns of phenotypes change during development is fundamental for a broader understanding of evolution. There is compelling evidence that mammalian skull covariance patterns change during ontogeny. However, it is unclear to what extent variation in covariance patterns during ontogeny can impact the response to selection. To tackle this question we explored: i) the extent to which covariance patterns change during postnatal ontogeny; ii) in which ontogenetic stages covariance patterns differ the most, and iii) the extent to which the phenotypic covariance pattern at different ontogenetic stages can be explained by the same processes determining additive genetic covariance. We sampled postnatal ontogenetic series for both marsupials, and placentals. Within each ontogenetic series, we compared covariance matrices (P-matrices) at different ontogenetic stages. Furthermore, we compared these P-matrices to two target matrices [adult P-matrix and an additive genetic covariance matrix (G-matrix)]. Our results show that for all ontogenetic series, covariance patterns from weaning onward are conserved and probably shaped by the same processes determining the G-matrix. We conclude that irrespective of eventual differences in how selection operates during most of postnatal ontogeny, the net response to such pressures will probably not be affected by ontogenetic differences in the covariance pattern.

developmental biology↗

bioRxiv2020

Shapes and Genescapes: Mapping Multivariate Phenotype-Biological Process Associations for Craniofacial Shape

Realistic mappings of genes to morphology are inherently multivariate on both sides of the equation. The importance of coordinated gene effects on morphological phenotypes is clear from the intertwining of gene actions in signaling pathways, gene regulatory networks, and developmental processes underlying the development of shape and size. Yet, current approaches tend to focus on identifying and localizing the effects of individual genes and rarely leverage the information content of high dimensional phenotypes. Here, we explicitly model the joint effects of biologically coherent collections of genes on a multivariate trait--craniofacial shape -- in a sample of n = 1,145 mice from the Diversity Outbred (DO) experimental line. We use biological process gene ontology (GO) annotations to select skeletal and facial development gene sets and solve for the axis of shape variation that maximally covaries with gene set marker variation. We use our process-centered, multivariate genotype-phenotype (MGP) approach to determine the overall contributions to craniofacial variation of genes involved in relevant processes and how variation in different processes corresponds to multivariate axes of shape variation. Further, we compare the directions of effect in phenotype space of mutations to the primary axis of shape variation associated with broader pathways within which they are thought to function. Finally, we leverage the relationship between mutational and pathway-level effects to predict phenotypic effects beyond craniofacial shape in specific mutants. We also introduce an online application which provides users the means to customize their own process-centered craniofacial shape analyses in the DO. The process-centered approach is generally applicable to any continuously varying phenotype and thus has wide-reaching implications for complex-trait genetics.

genomics↗

bioRxiv2019

Facial shape and allometry quantitative trait locus intervals in the Diversity Outbred mouse are enriched for known skeletal and facial development genes

The biology of how faces are built and come to differ from one another is complex. Discovering the genes that contribute to differences in facial morphology is one key to untangling this complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTLs peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.\n\nAuthor SummaryThe mammalian face is a complex structure serving many functions. We studied the genetic basis for facial skeletal diversity in a large sample of mice from an experimental population designed for the study of complex traits. We quantified the contribution of genetic variation to variation in three-dimensional facial shape across more than 55,000 genetic markers spread throughout the mouse genome. We found 37 genetic regions which are very likely to contribute to differences in facial shape. We then conducted a more detailed analysis of the genetic regions associated with the most variable aspects of facial shape. For these regions, a disproportionately large number of genes are known to be important to growth and to skeletal and facial development. The magnitude of these genetic contributions to differences in facial shape are consistently small. Our results therefore support the notion that facial skeletal diversity is influenced by many genes of small effect, but that some of these small effects may be related to genes that are fundamental to skeletal and facial development.

genetics↗