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Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

Knowledge of bone structure-function relationships in mice has been based on relatively small sample sets that limit generalizability. We sought to investigate structure-function relationships of long bones from a large population of genetically diverse mice. Therefore, we analyzed previously published data from the femur and radius of male and female mice from the F34 generation of the Large-by-Small advanced intercross line (LGXSM AI), which have over a two-fold continuous spread of bone and body sizes (Silva et al. 2019 JBMR).Morphological traits, mechanical properties, and estimated material properties were collected from the femur and radius from 1113 LGXSM AI adult mice (avg. age 25 wks). Males and females fed a low-fat or high-fat diet were evaluated to increase population variation. The data were analyzed using principal component analysis (PCA), Pearson's correlation, and multivariate linear regression.Using PCA groupings and hierarchical clustering, we identified a reduced set of traits that span the population variation and are relatively independent of each other. These include three morphometry parameters (cortical area, medullary area, and length), two mechanical properties (ultimate force and post-yield displacement), and one material property (ultimate stress). When comparing traits of the femur to the radius, morphological traits are moderately well correlated (rOur results indicate that variation in cortical bone phenotype in the F34 LGXSM AI mouse population can be adequately described by a reduced set of bone traits. These traits include cortical area, medullary area, bone length, ultimate force, post-yield displacement, and ultimate stress. The weak correlation of mechanical and material properties between the femur and radius indicates that the results from routine three-point bending tests of one long bone (e.g., femur) may not be generalizable to another long bone (e.g., radius). Additionally, these properties could not be fully predicted from bone morphology alone, confirming the importance of mechanical testing. Finally, material properties of the femur estimated based on beam theory equations showed a strong dependence on geometry that was not seen in the radius, suggesting that differences in femur size within a study may confound interpretation of estimated material properties.

Summary Objective To investigate the transcriptomic differences in chondrocytes obtained from LG/J (large, healer) and SM/J (small, non-healer) murine strains in an attempt to discern the molecular pathways implicated in cartilage regeneration and susceptibility to osteoarthritis (OA). Design We performed RNA-sequencing on chondrocytes derived from LG/J (n = 16) and SM/J (n = 16) mice. We validated the expression of candidate genes and compared single nucleotide polymorphisms (SNPs) between the two mouse strains. We also examined gene expression of positional candidates for ear pinna regeneration and long bone length quantitative trait loci (QTLs) that display differences in cartilaginous expression. Results We observed a distinct genetic heterogeneity between cells derived from LG/J and SM/J mouse strains. We found that gene ontologies representing cell development, cartilage condensation, and regulation of cell differentiation were enriched in LG/J chondrocytes. In contrast, gene ontologies enriched in the SM/J chondrocytes were mainly related to inflammation and degeneration. Moreover, SNP analysis revealed that multiple validated genes vary in sequence between LG/J and SM/J in coding and highly conserved noncoding regions. Finally, we showed that most QTLs have 20–30% of their positional candidates displaying differential expression between the two mouse strains. Conclusions While the enrichment of pathways related to cell differentiation, cartilage development and cartilage condensation infers superior healing potential of LG/J strain, the enrichment of pathways related to cytokine production, immune cell activation and inflammation entails greater susceptibility of SM/J strain to OA. These data provide novel insights into chondrocyte transcriptome and aid in identification of the quantitative trait genes and molecular differences underlying the phenotypic differences associated with individual QTLs.

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 = 1145 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 (process 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 that 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.

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N=10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

Parent-of-origin effects are unexpectedly common in complex traits, including metabolic and neurological diseases. Parent-of-origin effects can be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific parent-of-origin effects on metabolic traits were mapped in the F16generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these parent-of-origin effects phenomena. We propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. Here, we employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse lines to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, we leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. We identify a network comprised of 3 imprinted and 6 non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. We focus on 2 genes,NnatandF2r, whose interaction associates with serum glucose levels across generations in high fat-fed females. Single-cell RNAseq reveals thatNnatandF2rare negatively correlated in pre-adipocytes along an adipogenic trajectory, a result that is consistent with our observations in bulk white adipose tissue.

Objective Recombinant inbred mouse strains generated from an LG/J and SM/J intercross offer a unique resource to study complex genetic traits such as osteoarthritis (OA). We undertook this study to determine the susceptibility of 14 strains to various phenotypes characteristic of posttraumatic OA. We hypothesized that phenotypic variability is associated with genetic variability. Methods Ten-week-old male mice underwent surgical destabilization of the medial meniscus (DMM) to induce posttraumatic OA. Mice were killed 8 weeks after surgery, and knee joints were processed for histology to score cartilage degeneration and synovitis. Micro-computed tomography was used to analyze trabecular bone parameters including subchondral bone plate thickness and synovial ectopic calcifications. Gene expression in the knees was assessed using a QuantiGene Plex assay. Results Broad-sense heritability ranged from 0.18 to 0.58, which suggested that the responses to surgery were moderately heritable. The LGXSM-33, LGXSM-5, LGXSM-46, and SM/J strains were highly susceptible to OA, while the LGXSM-131b, LGXSM-163, LGXSM-35, LGXSM-128a, LGXSM-6, and LG/J strains were relatively OA resistant. This study was the first to accomplish measurement of genetic correlations of phenotypes that are characteristic of posttraumatic OA. Cartilage degeneration was significantly positively associated with synovitis (r = 0.83-0.92), and subchondral bone plate thickness was negatively correlated with ectopic calcifications (r = -0.59). Moreover, we showed that 40 of the 78 genes tested were significantly correlated with various OA phenotypes. However, unlike the OA phenotypes, there was no evidence for genetic variation in differences in gene expression levels between DMM-operated and sham-operated knees. Conclusion For these mouse strains, various characteristics of posttraumatic OA varied with genetic composition, which demonstrated a genetic basis for susceptibility to posttraumatic OA. The heritability of posttraumatic OA was established. Phenotypes exhibited various degrees of correlations; cartilage degeneration was positively correlated with synovitis, but not with the formation of ectopic calcifications. Further investigation of the genome regions that contain genes implicated in OA, as well as further investigation of gene expression data, will be useful for studying mechanisms of OA and identifying therapeutic targets.

Obesity is generally protective against osteoporosis and bone fracture. However, recent studies indicate that the influence of obesity on the skeleton is complex and can be detrimental. We evaluated the effects of a high-fat, obesogenic diet on the femur and radius of 1100 mice (males and females) from the Large-by-Small advanced intercross line (F34 generation). At age 5 months, bone morphology was assessed by microCT and mechanical properties by three-point bending. Mice raised on a high-fat diet had modestly greater cortical area, bending stiffness, and strength. Size-independent material properties were unaffected by a high-fat diet, indicating that diet influenced bone quantity but not quality. Bone size and mechanical properties were strongly correlated with body mass. However, the increases in many bone traits per unit increase in body mass were less in high-fat diet mice than low-fat diet mice. Thus, although mice raised on a high-fat diet have, on average, bigger and stronger bones than low-fat-fed mice, a high-fat diet diminished the positive relationship between body mass and bone size and whole-bone strength. The findings support the concept that there are diminishing benefits to skeletal health with increasing obesity. © 2019 American Society for Bone and Mineral Research.

Intervertebral disc degeneration (IDD) causes back pain and sciatica, affecting quality of life and resulting in high economic/social burden. The etiology of IDD is not well understood. Along with aging and environmental factors, genetic factors also influence the onset, progression and severity of IDD. Genetic studies of risk factors for IDD using human cohorts are limited by small sample size and low statistical power. Animal models amenable to genetic and functional studies of IDD provide desirable alternatives. Despite differences in size and cellular content as compared to human intervertebral discs (IVDs), the mouse is a powerful model for genetics and assessment of cellular changes relevant to human biology. Here, we provide evidence for early onset disc degeneration in SM/J relative to LG/J mice with poor and good tissue healing capacity respectively. In the first few months of life, LG/J mice maintain a relatively constant pool of notochordal-like cells in the nucleus pulposus (NP) of the IVD. In contrast, chondrogenic events are observed in SM/J mice beginning as early as one-week-old, with progressive fibrotic changes. Further, the extracellular matrix changes in the NP are consistent with IVD degeneration. Leveraging on the genomic data of two parental and two recombinant inbred lines, we assessed the genetic contribution to the NP changes and identified processes linked to the regulation of ion transport systems. Significantly, "transport" system is also in the top three gene ontology (GO) terms from a comparative proteomic analysis of the mouse NP. These findings support the potential of the SM/J, LG/J and their recombinant inbred lines for future genetic and biological analysis in mice and validation of candidate genes and biological relevance in human cohort studies. The proteomic data has been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD008784.

Background Cleft lip and palate is one of the most common human birth defects, but the underlying etiology is poorly understood. The A/WySn mouse is a spontaneously occurring model of multigenic clefting in which 20% to 30% of individuals develop an orofacial cleft. Recent work has shown altered methylation at a specific retrotransposon insertion downstream of the Wnt9b locus in clefting animals, which results in decreased Wnt9b expression. Results Using a newly developed protocol that allows us to measure morphology, gene expression, and DNA methylation in the same embryo, we relate gene expression in an individual embryo directly to its three-dimensional morphology for the first time. We find that methylation at the retrotransposon relates to Wnt9b expression and morphology. IAP methylation relates to shape of the nasal process in a manner consistent with clefting. Embryos with low IAP methylation exhibit increased among-individual variance in facial shape. Conclusions Methylation and gene expression relate nonlinearly to nasal process morphology. Individuals at one end of a continuum of phenotypic states display a clinical phenotype and increased phenotypic variation. Variable penetrance and expressivity in this model is likely determined both by among-individual variation in methylation and changes in phenotypic robustness along the underlying liability distribution for orofacial clefting.

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 QTL’s 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.Author 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.

Summary Objective The etiology of osteoarthritis (OA) is unknown, however, there appears to be a significant contribution from genetics. We have identified recombinant inbred strains of mice derived from LG/J (large) and SM/J (small) strains that vary significantly in their ability to repair articular cartilage and susceptibility to post-traumatic OA due to their genetic composition. Here, we report cartilage repair phenotypes in the same strains of mice in which OA susceptibility was analyzed previously, and determine the genetic correlations between phenotypes. Design We used 12 recombinant inbred strains, including the parental strains, to test three phenotypes: ear-wound healing (n = 263), knee articular cartilage repair (n = 131), and post-traumatic OA (n = 53) induced by the surgical destabilization of the medial meniscus (DMM). Genetic correlations between various traits were calculated as Pearson's correlation coefficients of strain means. Results We found a significant positive correlation between ear-wound healing and articular cartilage regeneration (r = 0.71; P = 0.005). We observed a strong inverse correlation between articular cartilage regeneration and susceptibility to OA based on maximum (r = −0.54; P = 0.036) and summed Osteoarthritis Research Society International (OARSI) scores (r = −0.56; P = 0.028). Synovitis was not significantly correlated with articular cartilage regeneration but was significantly positively correlated with maximum (r = 0.63; P = 0.014) and summed (r = 0.70; P = 0.005) OARSI scores. Ectopic calcification was significantly positively correlated with articular cartilage regeneration (r = 0.59; P = 0.021). Conclusions Using recombinant inbred strains, our study allows, for the first time, the measurement of genetic correlations of regeneration phenotypes with degeneration phenotypes, characteristic of OA (cartilage degeneration, synovitis). We demonstrate that OA is positively correlated with synovitis and inversely correlated with the ability to repair cartilage. These results suggest an addition to the risk paradigm for OA from a focus on degeneration to regeneration.

Variation in pelvic morphology has a complex genetic basis and its patterning and specification is governed by conserved developmental pathways. Whether the mechanisms underlying the differentiation and specification of the pelvis also produce the morphological covariation on which natural selection may act, is still an open question in evolutionary developmental biology. We use high‐resolution quantitative trait locus (QTL) mapping in the F34 generation of an advanced intercross experiment (LG,SM‐G34) to characterize the genetic architecture of the mouse pelvis. We test the prediction that genomic features linked to developmental patterning and differentiation of the hind limb and pelvis and the regulation of chondrogenesis are overrepresented in QTL. We find 31 single QTL trait associations at the genome‐ or chromosome‐wise significance level coalescing to 27 pleiotropic loci. We recover further QTL at a more relaxed significance threshold replicating locations found in a previous experiment in an earlier generation of the same population. QTL were more likely than chance to harbor Pitx1 and Sox9 Class II chromatin immunoprecipitation‐seq features active during development of skeletal features. There was weak or no support for the enrichment of seven more categories of developmental features drawn from the literature. Our results suggest that genotypic variation is channeled through a subset of developmental processes involved in the generation of phenotypic variation in the pelvis. This finding indicates that the evolvability of complex traits may be subject to biases not evident from patterns of covariance among morphological features or developmental patterning when either is considered in isolation.

Parent-of-origin effects (POE) are unexpectedly common in complex traits, including metabolic and neurological diseases. POE can also be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific POE on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these POE phenomena. Here, we use a simple yet powerful F1 reciprocal cross model to test the hypothesis that non-imprinted genes can generate complex POE on metabolic traits through genetic interactions with imprinted genes. Male and female mice from a F1 reciprocal cross of LG/J and SM/J strains were fed either high or low fat diets. We generated expression profiles from three metabolically-relevant tissues: hypothalamus, white adipose, and liver. We identified two classes of parent-of-origin expression biases: genes showing parent-of-origin-dependent allele-specific expression and biallelic genes that are differentially expressed by reciprocal cross. POE patterns of both gene classes are highly tissue-and context-specific, sometimes occurring only in one sex and/or diet cohort in a particular tissue. We then constructed tissue-specific interaction networks among genes from these two classes of POE. A key subset of gene pairs show significant epistasis in the F16 LG/J x SM/J advanced intercross data in cases where the biallelic gene fell within a previously-identified metabolic POE QTL interval. We highlight one such interaction in adipose, between Nnat and Mogat1, which associates with POE on multiple adiposity traits. Both genes localize to the endoplasmic reticulum of adipocytes and play a role in adipogenesis. Additionally, expression of both genes is significantly correlated in human visceral adipose tissue. The genes and networks we present here represent a set of actionable interacting candidates that can be probed to further identify the machinery driving POE on complex traits.

BackgroundIn newborns, severe congenital heart defects are rarer than mild ones. The reason why is unknown, but presumably related to a liability threshold that rises with the severity of a defect. Because the same genetic mutation can cause different defects, other variables may contribute to pushing an individual past a defect-specific liability threshold. We consider here how variables in the genetic architecture of a heart defect depend upon its fitness cost, as defined by the likelihood of survival to reproductive age in natural history studies.MethodsWe phenotyped ~10,000Nkx2-5+/-newborn mice, a model of human congenital heart disease, from two inbred strain crosses. Genome-wide association analyses detected loci that modify the risk of an atrial septal defect, membranous or muscular ventricular septal defect, or atrioventricular septal defect. The number of loci, heritability and quantitative effects on risk of pairwise (G×GNkx) and higher-order (G×G×GNkx) epistasis between the loci andNkx2-5mutation were examined as a function of the fitness cost of a defect.ResultsNkx2-5+/-mice have pleiotropic heart defects; about 70% have normal hearts. The model recapitulates the epidemiological relationship between the severity and incidence of a heart defect. Neither the number of modifier loci nor heritability depends upon the severity of a defect, but G×GNkxand G×G×GNkxeffects on risk do. Interestingly, G×G×GNkxeffects are three times more likely to suppress risk when the genotypes at the first two loci are homozygous and from the same, rather than opposite strains in a cross. Syn- and anti-homozygous genotypes at G×G×GNkxinteractions can have an especially large impact on the risk of an atrioventricular septal defect.ConclusionsGiven a modestly penetrant mutation, epistasis contributes more to the risk of severe than mild congenital heart defect. Conversely, genetic compatibility between interacting genes, as indicated by the protective effects of syn-homozygosity at G×G×GNkxinteractions, plays a newfound role in the robustness of cardiac development. The experimental model offers practical insights into the nature of genetic risk in congenital heart disease. The results more fundamentally address a longstanding question regarding how mutational robustness could arise from natural selection.

Evolutionary studies have long emphasized that the genetic architecture of traits holds important microevolutionary consequences. Yet, studies comparing the genetic architecture of traits across species are rare, and discussions of the evolution of genetic systems are made on theoretical arguments rather than on empirical evidence. Here, we compared the genetic architecture of cranial traits in two different mammalian model organisms: the gray short-tailed opossum, Monodelphis domestica, and the laboratory mouse, Mus musculus. We show that both organisms share a highly polygenic genetic architecture for craniofacial traits, with many loci of small effect. However, these two model species differ significantly in the overall degree of pleiotropy, N, of the genotype-to-phenotype map, with opossums presenting a higher average N. They also diverge in their degree of genetic modularity, with opossums presenting less modular patterns of genetic association among traits. We argue that such differences highlight the context dependency of gene effects, with developmental systems shaping the variational properties of genetic systems. Finally, we also demonstrate based on the opossum data that current measurements for the relationship between the mutational effect size and N need to be re-evaluated in relation to the importance of the cost of pleiotropy for mammals.

Modularity has emerged as a central concept for evolutionary biology, thereby providing the field with a theory of organismal structure and variation. This theory has reframed long-standing questions and serves as a unified conceptual framework for genetics, developmental biology, and multivariate evolution. Research programs in systems biology and quantitative genetics are bridging the gap between these fields. Although this synthesis is ongoing, some major themes have emerged, and empirical evidence for modularity has become abundant. In this review, we look at modularity from a historical perspective, highlighting its meaning at different levels of biological organization and the different methods that can be used to detect it. We then explore the relationship between quantitative genetic approaches to modularity and developmental genetic studies. We conclude by investigating the dynamic relationship between modularity and the adaptive landscape and how this relationship potentially shapes evolution and can help bridge the gap between micro- and macroevolution.

Despite decades of progress, congenital heart disease remains a major cause of mortality and suffering in children and young adults. Prevention would be ideal, but formidable biological and technical hurdles face any intervention that seeks to target the main causes, genetic mutations in the embryo. Other factors, however, significantly modify the total risk in individuals who carry mutations. Investigation of these factors could lead to an alternative approach to prevention. To define the risk modifiers, our group has taken an "experimental epidemiologic" approach via inbred mouse strain crosses. The original intent was to map genes that modify an individual's risk of heart defects caused by an Nkx2-5 mutation. During the analysis of >2000 Nkx2-5(+/-) offspring from one cross we serendipitously discovered a maternal-age associated risk, which also exists in humans. Reciprocal ovarian transplants between young and old mothers indicate that the incidence of heart defects correlates with the age of the mother and not the oocyte, which implicates a maternal pathway as the basis of the risk. The quantitative risk varies between strain backgrounds, so maternal genetic polymorphisms determine the activity of a factor or factors in the pathway. Most strikingly, voluntary exercise by the mother mitigates the risk. Therefore, congenital heart disease can in principle be prevented by targeting a maternal pathway even if the embryo carries a causative mutation. Further mechanistic insight is necessary to develop an intervention that could be implemented on a broad scale, but the physiology of maternal-fetal interactions, aging, and exercise are notoriously complex and undefined. This suggests that an unbiased genetic approach would most efficiently lead to the relevant pathway. A genetic foundation would lay the groundwork for human studies and clinical trials.

The rapid divergence of male genitalia is a preeminent evolutionary pattern. This rapid divergence is especially striking in the baculum, a bone that occurs in the penis of many mammalian species. Closely related species often display diverse baculum morphology where no other morphological differences can be discerned. While this fundamental pattern of evolution has been appreciated at the level of gross morphology, nearly nothing is known about the genetic basis of size and shape divergence. Quantifying the genetic basis of baculum size and shape variation has been difficult because these structures generally lack obvious landmarks, so comparing them in three dimensions is not straightforward. Here, we develop a novel morphometric approach to quantify size and shape variation from three-dimensional micro-CT scans taken from 369 bacula, representing 75 distinct strains of the BXD family of mice. We identify two quantitative trait loci (QTL) that explain ∼50% of the variance in baculum size, and a third QTL that explains more than 20% of the variance in shape. Together, our study demonstrates that baculum morphology may diverge relatively easily, with mutations at a few loci of large effect that independently modulate size and shape. Based on a combination of bioinformatic investigations and new data on RNA expression, we prioritized these QTL to 16 candidate genes, which have hypothesized roles in bone morphogenesis and may enable future genetic manipulation of baculum morphology.

With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated—in terms of effect size—with patterns of phenotypic variation (phenotypic latent variables). This multivariate genotype–phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype–phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype–phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for >70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype–phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3—the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype–phenotype map has important consequences for gene identification and may shed light on the evolvability of organisms.

Bilateral symmetry is a fundamental property of the vertebrate central nervous system. Local deviations from symmetry provide various types of information about the development, evolution, and function of elements within the CNS, especially the cerebral hemispheres. Here, we quantify the pattern and extent of asymmetry in cortical folding within the cerebrum of Papio baboons and assess the evolutionary and developmental implications of the findings. Analyses of directional asymmetry show a population-level trend in length measurements indicating that baboons are genetically predisposed to be asymmetrical, with the right side longer than the left in the anterior cerebrum while the left side is longer than the right posteriorly. We also find a corresponding bias to display a right frontal petalia (overgrowth of the anterior pole of the cerebral cortex on the right side). By quantifying fluctuating asymmetry, we assess canalization of brain features and the susceptibility of the baboon brain to developmental perturbations. We find that features are differentially canalized depending on their ontogenetic timing. We further deduce that development of the two hemispheres is to some degree independent. This independence has important implications for the evolution of cerebral hemispheres and their separate specialization. Asymmetry is a major feature of primate brains and is characteristic of both brain structure and function.

Analysis of wing variation within and between fly species reveals an unexpectedly slow evolutionary rate. Variations due to mutation and interspecific differences are similar, perhaps as a result of complex genetic interactions. See Letter p.447 Genetic mutation is the engine room of evolution. Without genetic mutation, genes would not vary, and natural selection would be powerless to act. But if genetic mutation provides the raw material for adaption, the extent to which mutation further constrains evolution over geological time is a matter of debate. Mutation rates are typically very small and are thought to be swamped by the amount of genetic divergence seen over evolutionary timescales. David Houle and colleagues present results that could be a fly in the ointment. Several thousand flies in fact. They examined the wings of more than 50,000 Drosophila and its close relatives to reveal an unexpected and strong positive relationship between mutation, genetic variation and evolutionary rate over the past 40 million years. This challenges several models of the role of mutation in evolution.

Background While the genetics of obesity has been well defined, the epigenetics of obesity is poorly understood. Here, we used a genome-wide approach to identify genes with differences in both DNA methylation and expression associated with a high-fat diet in mice. Results We weaned genetically identical Small (SM/J) mice onto a high-fat or low-fat diet and measured their weights weekly, tested their glucose and insulin tolerance, assessed serum biomarkers, and weighed their organs at necropsy. We measured liver gene expression with RNA-seq (using 21 total libraries, each pooled with 2 mice of the same sex and diet) and DNA methylation with MRE-seq and MeDIP-seq (using 8 total libraries, each pooled with 4 mice of the same sex and diet). There were 4356 genes with expression differences associated with diet, with 184 genes exhibiting a sex-by-diet interaction. Dietary fat dysregulated several pathways, including those involved in cytokine-cytokine receptor interaction, chemokine signaling, and oxidative phosphorylation. Over 7000 genes had differentially methylated regions associated with diet, which occurred in regulatory regions more often than expected by chance. Only 5–10% of differentially methylated regions occurred in differentially expressed genes, however this was more often than expected by chance (p = 2.2 × 10− 8). Conclusions Discovering the gene expression and methylation changes associated with a high-fat diet can help to identify new targets for epigenetic therapies and inform about the physiological changes in obesity. Here, we identified numerous genes with altered expression and methylation that are promising candidates for further study. Electronic supplementary material The online version of this article (10.1186/s12864-018-5327-0) contains supplementary material, which is available to authorized users.

Obesity is generally protective against osteoporosis and bone fracture. However, recent studies indicate that the influence of obesity on the skeleton is complex and can be detrimental. We evaluated the effects of a high-fat, obesogenic diet on the femur and radius of 1100 mice (males and females) from the Large-by-Small advanced intercross line (F(34) generation). At 5 months age, bone morphology was assessed by microCT and mechanical properties by three-point bending. Mice raised on a high-fat diet had modestly greater cortical area, bending stiffness and strength. Size-independent material properties were unaffected by a high-fat diet, indicating that diet influenced bone quantity but not quality. Bone size and mechanical properties were strongly correlated with body mass. However, the increases in many bone traits per unit increase in body mass were less in high-fat diet mice than low-fat diet mice. Thus, although mice raised on a high-fat diet have, on average, bigger and stronger bones than low-fat fed mice, a high-fat diet diminished the positive relationship between body mass and bone size and whole-bone strength. The findings support the concept that there are diminishing benefits to skeletal health with increasing obesity.

PURPOSE: Obesity is linked to cognitive dysfunction in humans and rodents, and its effects can be passed on to the next generation. However, the extent of these effects is not well understood. The purpose of this study was to determine the effect of a prenatal maternal high-fat diet and an individual high-fat diet in inbred mice. METHODS: We varied maternal diet and offspring diet to test the hypothesis that a high-fat diet would increase anxiety, reduce activity levels, and impair nest-building. First, we fed a high-fat (HF) or low-fat (LF) diet to genetically identical female Small (SM/J) mice and mated them with LF males. We cross-fostered all offspring to LF-fed SM/J nurses and weaned them onto an HF or LF diet. We weighed the mice weekly and we tested anxiety with the Open Field Test, activity levels with instantaneous scan sampling, and nest building using the Deacon Scale. RESULTS: Diet significantly affected weight, with HF females weighing 28.2 g (± 1.4 g SE) and LF females weighing 15.1 g (± 1.6 g SE) at 17 weeks old. The offspring’s own diet had major behavioral effects. HF mice produced more fecal boli and urinations in the Open Field Test, built lower-quality nests, and had lower activity in adulthood than LF mice. The only trait that a prenatal maternal diet significantly affected was whether the offspring built their nests inside or outside of a hut. CONCLUSIONS: Offspring diet, but not prenatal maternal diet, affected a wide range of behaviors in these mice.

Quantitative genetical theory suggests that characters existing in developmentally or functionally integrated groups are expected to be genetically correlated because they share a common inheritance. The genetic independence model for the cause of this genetic integration predicts that pleiotropic effects of single genes are mostly restricted to the characters in these integrated groups. We tested this model by estimating the additive and dominance effects of quantitative trait loci (QTLs) affecting early‐ (cranial vault) and late‐developing (face) skeletal characters in F2 house mice originally derived from a cross of the Large and Small inbred strains. Interval mapping procedures were used that resulted in the identification of 26 QTLs on 17 of the 19 autosomes that significantly affected these characters. Additive, but not dominance, genotypic effects of many of these QTLs predominantly affected either the cranial vault or face characters, which supports the genetic independence model. Only t...

Canalization, or robustness to genetic or environmental perturbations, is fundamental to complex organisms. While there is strong evidence for canalization as an evolved property that varies among genotypes, the developmental and genetic mechanisms that produce this phenomenon are very poorly understood. For evolutionary biology, understanding how canalization arises is important because, by modulating the phenotypic variation that arises in response to genetic differences, canalization is a determinant of evolvability. For genetics of disease in humans and for economically important traits in agriculture, this question is important because canalization is a potentially significant cause of missing heritability that confounds genomic prediction of phenotypes. We review the major lines of thought on the developmental-genetic basis for canalization. These fall into two groups. One proposes specific evolved molecular mechanisms while the other deals with robustness or canalization as a more general feature of development. These explanations for canalization are not mutually exclusive and they overlap in several ways. General explanations for canalization are more likely to involve emergent features of development than specific molecular mechanisms. Disentangling these explanations is also complicated by differences in perspectives between genetics and developmental biology. Understanding canalization at a mechanistic level will depend on conceptual and methodological approaches that integrate quantitative genetics and developmental biology.

Evolutionary constraint due to pleiotropy refers to a situation in which mutations in genes shared among traits generate trait covariance; therefore, traits that are not directly exposed to selective challenge show a correlated response. When such a correlated response is deleterious, it may constrain the trait from evolving. Here, we argue that the idea of absolute constraints draws from the perception that gene effects are inherent to alleles and thus invariant across genetic and environmental backgrounds. However, evidence from studies involving genetic effects on multiple traits, observed across different genetic backgrounds and environments, supports the notion that genes' effects on traits change. Consequently, pleiotropy also varies across backgrounds. We argue for a stronger emphasis on interaction effects when describing a trait's genetic basis and its evolutionary potential. By discussing different cases of trait individuation, we demonstrate how this approach can lead to new insights.

This study reports on genetic susceptibility to ectopic calcification in the LG/J and SM/J advanced intercross mice. Using 347 mice in 98 full-sibships, destabilization of medial meniscus (DMM) was performed to induce joint injury. We found that joint destabilization instigated ectopic calcifications as detected and quantified by micro-CT. We performed quantitative trait locus (QTL) analysis to map ectopic calcification phenotypes to discrete genomic locations. To validate the functional significance of the selected QTL candidate genes, we compared mRNA expression between parental LG/J and SM/J inbred strains. Overall, we detected 20 QTLs affecting synovial and meniscus calcification phenotypes with 11 QTLs linked to synovial calcification. Functional and bioinformatic analyses of single nucleotide polymorphism (SNP) identified functional classifications relevant to angiogenesis (Myo1e, Kif26b, Nprl3, Stab2, Fam105b), bone metabolism/calcification (Tle3, Tgfb2, Lipc, Nfe2l1, Ank, Fam105b), arthritis (Stab2, Tbx21, Map4k4, Hoxb9, Larp6, Col1a2, Adam10, Timp3, Nfe2l1, Trpm3), and ankylosing-spondylitis (Ank, Pon1, Il1r2, Tbkbp1) indicating that ectopic calcification involves multiple mechanisms. Furthermore, the expression of 11 out of 78 candidate genes was significantly different between LG/J and SM/J. Correlation analysis showed that Aff3, Fam81a, Syn3, and Ank were correlated with synovial calcification. Taken together, our findings of multiple genetic loci suggest the involvement of multiple genes contributing to ectopic calcification.

Folding of the primate brain cortex allows for improved neural processing power by increasing cortical surface area for the allocation of neurons. The arrangement of folds (sulci) and ridges (gyri) across the cerebral cortex is thought to reflect the underlying neural network. Gyrification, an adaptive trait with a unique evolutionary history, is affected by genetic factors different from those affecting brain volume. Using a large pedigreed population of ∼1000 Papio baboons, we address critical questions about the genetic architecture of primate brain folding, the interplay between genetics, brain anatomy, development, patterns of cortical–cortical connectivity, and gyrification’s potential for future evolution. Through Mantel testing and cluster analyses, we find that the baboon cortex is quite evolvable, with high integration between the genotype and phenotype. We further find significantly similar partitioning of variation between cortical development, anatomy, and connectivity, supporting the predictions of tension-based models for sulcal development. We identify a significant, moderate degree of genetic control over variation in sulcal length, with gyrus-shape features being more susceptible to environmental effects. Finally, through QTL mapping, we identify novel chromosomal regions affecting variation in brain folding. The most significant QTL contain compelling candidate genes, including gene clusters associated with Williams and Down syndromes. The QTL distribution suggests a complex genetic architecture for gyrification with both polygeny and pleiotropy. Our results provide a solid preliminary characterization of the genetic basis of primate brain folding, a unique and biomedically relevant phenotype with significant implications in primate brain evolution.

We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation.

Robustness to perturbation is a fundamental feature of complex organisms. Mutations are the raw material for evolution, yet robustness to their effects is required for species survival. The mechanisms that produce robustness are poorly understood. Nonlinearities are a ubiquitous feature of development that may link variation in development to phenotypic robustness. Here, we manipulate the gene dosage of a signaling molecule, Fgf8, a critical regulator of vertebrate development. We demonstrate that variation in Fgf8 expression has a nonlinear relationship to phenotypic variation, predicting levels of robustness among genotypes. Differences in robustness are not due to gene expression variance or dysregulation, but emerge from the nonlinearity of the genotype–phenotype curve. In this instance, embedded features of development explain robustness differences. How such features vary in natural populations and relate to genetic variation are key questions for unraveling the origin and evolvability of this feature of organismal development., Developmental processes often involve nonlinearities, but the consequences for translating genotype to phenotype are not well characterized. Here, Green et al. vary Fgf8 signaling across allelic series of mice and show that phenotypic robustness in craniofacial shape is explained by a nonlinear effect of Fgf8 expression.

Objectives: Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (VP) and additive genetic (VA) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution? Materials and Methods: We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone. Results: Covariates account for 1.2-91% of craniofacial VP. EID VA decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males. Discussion: Because a relatively large proportion of EID VA is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual VP patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes.

Relationship loci (rQTL) exist when the correlation between multiple traits varies by genotype. rQTL often occur due to gene-by-gene (G × G) or gene-by-environmental interactions, making them a powerful tool for detecting G × G. Here we present an empirical analysis of apolipoprotein E (APOE) with respect to lipid traits and incident CHD leading to the discovery of loci that interact with APOE to affect these traits. We found that the relationship between total cholesterol (TC) and triglycerides (ln TG) varies by APOE isoform genotype in African-American (AA) and European-American (EA) populations. The e2 allele is associated with strong correlation between ln TG and TC while the e4 allele leads to little or no correlation. This led to a priori hypotheses that APOE genotypes affect the relationship of TC and/or ln TG with incident CHD. We found that APOE*TC was significant (P = 0.016) for AA but not EA while APOE*ln TG was significant for EA (P = 0.027) but not AA. In both cases, e2e2 and e2e3 had strong relationships between TC and ln TG with CHD while e2e4 and e4e4 results in little or no relationship between TC and ln TG with CHD. Using ARIC GWAS data, scans for loci that significantly interact with APOE produced four loci for African Americans (one CHD, one TC, and two HDL). These interactions contribute to the rQTL pattern. rQTL are a powerful tool to identify loci that modify the relationship between risk factors and disease and substantially increase statistical power for detecting G × G.

Ontogenetic and static allometries describe how a character changes in size when the size of the organism changes during ontogeny and among individuals measured at the same developmental stage, respectively. Understanding the relationship between these two types of allometry is crucial to understanding the evolution of allometry and, more generally, the evolution of shape. However, the effects of ontogenetic allometry on static allometry remain largely unexplored. Here, we first show analytically how individual variation in ontogenetic allometry and body size affect static allometry. Using two longitudinal data sets on ontogenetic and static allometry, we then estimate variances and covariances for the different parameters of the ontogenetic allometry defined in our model and assess their relative contribution to the static allometric slope. The mean ontogenetic allometry is the main parameter that determines the static allometric slope, while the covariance between the ontogenetic allometric slope and body size generates most of the discrepancies between ontogenetic and static allometry. These results suggest that the apparent evolutionary stasis of the static allometric slope is not generated by internal (developmental) constraints but more likely results from external constraints imposed by selection. © 2013 by The University of Chicago. All rights reserved.