Molecular insight into the association between cartilage regeneration and ear wound healing in genetic mouse models: Targeting new genes in regeneration

Tissue regeneration is a complex trait with few genetic models available. Mouse strains LG/J and MRL are exceptional healers. Using recombinant inbred strains from a large (LG/J, healer) and small (SM/J, nonhealer) intercross, we have previously shown a positive genetic correlation between ear wound healing, knee cartilage regeneration, and protection from osteoarthritis. We hypothesize that a common set of genes operates in tissue healing and articular cartilage regeneration. Taking advantage of archived histological sections from recombinant inbred strains, we analyzed expression of candidate genes through branched-chain DNA technology directly from tissue lysates. We determined broad-sense heritability of candidates, Pearson correlation of candidates with healing phenotypes, and Ward minimum variance cluster analysis for strains. A bioinformatic assessment of allelic polymorphisms within and near candidate genes was also performed. The expression of several candidates was significantly heritable among strains. Although several genes correlated with both ear wound healing and cartilage healing at a marginal level, the expression of four genes representing DNA repair (Xrcc2, Pcna) and Wnt signaling (Axin2, Wnt16) pathways was significantly positively correlated with both phenotypes. Cluster analysis accurately classified healers and nonhealers for seven out of eight strains based on gene expression. Specific sequence differences between LG/J and SM/J were identified as potential causal polymorphisms. Our study suggests a common genetic basis between tissue healing and osteoarthritis susceptibility. Mapping genetic variations causing differences in diverse healing responses in multiple tissues may reveal generic healing processes in pursuit of new therapeutic targets designed to induce or enhance regeneration and, potentially, protection from osteoarthritis

Cortical bone relationships are maintained regardless of sex and diet in a large population of LGXSM advanced intercross mice

Introduction: 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). Methods: 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\u27s correlation, and multivariate linear regression. Results: 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 (r2: 0.18–0.44) and independent of sex and diet. However, mechanical and material properties are weakly correlated or uncorrelated between the long bones. Ultimate force can be predicted from morphology with moderate accuracy for both long bones independent of variations due to genetics, sex, or diet; however, predictions miss up to 50 % of the variation in the population. Estimated material properties in the femur are moderately to strongly correlated with bone size parameters, while these correlations are very weak in the radius. Discussion: Our 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

Genetic variation in the pleiotropic association between physical activity and body weight in mice

<p>Abstract</p> <p>Background</p> <p>A sedentary lifestyle is often assumed to lead to increases in body weight and potentially obesity and related diseases but in fact little is known about the genetic association between physical activity and body weight. We tested for such an association between body weight and the distance, duration, and speed voluntarily run by 310 mice from the F₂generation produced from an intercross of two inbred lines that differed dramatically in their physical activity levels.</p> <p>Methods</p> <p>We used a conventional interval mapping approach with SNP markers to search for QTLs that affected both body weight and activity traits. We also conducted a genome scan to search for relationship QTLs (<it>rel</it>QTLs), or chromosomal regions that affected an activity trait variably depending on the phenotypic value of body weight.</p> <p>Results</p> <p>We uncovered seven quantitative trait loci (QTLs) affecting body weight, but only one co-localized with another QTL previously found for activity traits. We discovered 19 <it>rel</it>QTLs that provided evidence for a genetic (pleiotropic) association of physical activity and body weight. The three genotypes at each of these loci typically exhibited a combination of negative, zero, and positive regressions of the activity traits on body weight, the net effect of which was to produce overall independence of body weight from physical activity. We also demonstrated that the <it>rel</it>QTLs produced these varying associations through differential epistatic interactions with a number of other epistatic QTLs throughout the genome.</p> <p>Conclusion</p> <p>It was concluded that individuals with specific combinations of genotypes at the <it>rel</it>QTLs and <it>epi</it>QTLs might account for some of the variation typically seen in plots of the association of physical activity with body weight.</p

Sex dependent imprinting effects on complex traits in mice

BACKGROUND: Genomic imprinting is an epigenetic source of variation in quantitative traits that results from monoallelic gene expression, where commonly either only the paternally- or the maternally-derived allele is expressed. Imprinting has been shown to affect a diversity of complex traits in a variety of species. For several such quantitative traits sex-dependent genetic effects have been discovered, but whether imprinting effects also show such sex-dependence has yet to be explored. Moreover, theoretical work on the evolution of sex-dependent genomic imprinting effects makes specific predictions about the phenotypic patterns of such effects, which, however, have not been assessed empirically to date. RESULTS: Using a genome-scan for loci affecting a set of complex growth and body composition traits from an intercross between two divergent mouse strains, we investigated possible sex-dependent imprinting effects. Our results demonstrate for the first time the existence of genomic imprinting effects that depend on sex and are not related to sex-chromosome effects. We detected a total of 13 loci on 11 chromosomes that showed significant differences between the sexes in imprinting effects. Most loci showed imprinting effects in only one sex, with eight imprinted effects found in males and six in females. One locus showed sex-dependent imprinting effects in both sexes for different traits. The absence of an imprinting effect in one sex was not necessarily indicative of the overall inactivity of the locus in that sex, as for several loci a significant additive or dominance effect was detected. Moreover, three loci exhibited significant additive effects in both sexes but their imprinting effect was restricted to one sex. CONCLUSION: Our results clearly show that imprinting effects can be sex-dependent and also suggest that new candidate imprinted loci can be detected when taking account of sex-specific imprinting effects. However, predictions made about the evolution of sex-dependent imprinting effects and associated phenotypic patterns cannot be unequivocally supported at present and further research into the selection pressures applied to the strains of mice used in our study is required

Genome-Wide Analysis Reveals a Complex Pattern of Genomic Imprinting in Mice

Parent-of-origin–dependent gene expression resulting from genomic imprinting plays an important role in modulating complex traits ranging from developmental processes to cognitive abilities and associated disorders. However, while gene-targeting techniques have allowed for the identification of imprinted loci, very little is known about the contribution of imprinting to quantitative variation in complex traits. Most studies, furthermore, assume a simple pattern of imprinting, resulting in either paternal or maternal gene expression; yet, more complex patterns of effects also exist. As a result, the distribution and number of different imprinting patterns across the genome remain largely unexplored. We address these unresolved issues using a genome-wide scan for imprinted quantitative trait loci (iQTL) affecting body weight and growth in mice using a novel three-generation design. We identified ten iQTL that display much more complex and diverse effect patterns than previously assumed, including four loci with effects similar to the callipyge mutation found in sheep. Three loci display a new phenotypic pattern that we refer to as bipolar dominance, where the two heterozygotes are different from each other while the two homozygotes are identical to each other. Our study furthermore detected a paternally expressed iQTL on Chromosome 7 in a region containing a known imprinting cluster with many paternally expressed genes. Surprisingly, the effects of the iQTL were mostly restricted to traits expressed after weaning. Our results imply that the quantitative effects of an imprinted allele at a locus depend both on its parent of origin and the allele it is paired with. Our findings also show that the imprinting pattern of a locus can be variable over ontogenetic time and, in contrast to current views, may often be stronger at later stages in life

Quantitative Genetics, Pleiotropy, and Morphological Integration in the Dentition of Papio hamadryas

Variation in the mammalian dentition is highly informative of adaptations and evolutionary relationships, and consequently has been the focus of considerable research. Much of the current research exploring the genetic underpinnings of dental variation can trace its roots to Olson and Miller's 1958 book Morphological Integration. These authors explored patterns of correlation in the post-canine dentitions of the owl monkey and Hyopsodus, an extinct condylarth from the Eocene. Their results were difficult to interpret, as was even noted by the authors, due to a lack of genetic information through which to view the patterns of correlation. Following in the spirit of Olson and Miller's research, we present a quantitative genetic analysis of dental variation in a pedigreed population of baboons. We identify patterns of genetic correlations that provide insight to the genetic architecture of the baboon dentition. This genetic architecture indicates the presence of at least three modules: an incisor module that is genetically independent of the post-canine dentition, and a premolar module that demonstrates incomplete pleiotropy with the molar module. We then compare this matrix of genetic correlations to matrices of phenotypic correlations between the same measurements made on museum specimens of another baboon subspecies and the Southeast Asian colobine Presbytis. We observe moderate significant correlations between the matrices from these three primate taxa. From these observations we infer similarity in modularity and hypothesize a common pattern of genetic integration across the dental arcade in the Cercopithecoidea

A complete classification of epistatic two-locus models

Background: The study of epistasis is of great importance in statistical genetics in fields such as linkage and association analysis and QTL mapping. In an effort to classify the types of epistasis in the case of two biallelic loci Li and Reich listed and described all models in the simplest case of 0/ 1 penetrance values. However, they left open the problem of finding a classification of two-locus models with continuous penetrance values. Results: We provide a complete classification of biallelic two-locus models. In addition to solving the classification problem for dichotomous trait disease models, our results apply to any instance where real numbers are assigned to genotypes, and provide a complete framework for studying epistasis in QTL data. Our approach is geometric and we show that there are 387 distinct types of two-locus models, which can be reduced to 69 when symmetry between loci and alleles is accounted for. The model types are defined by 86 circuits, which are linear combinations of genotype values, each of which measures a fundamental unit of interaction. Conclusion: The circuits provide information on epistasis beyond that contained in the additive × additive, additive × dominance, and dominance × dominance interaction terms. We discuss th

A High-Resolution Map of Segmental DNA Copy Number Variation in the Mouse Genome

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits

A wild derived quantitative trait locus on mouse chromosome 2 prevents obesity

<p>Abstract</p> <p>Background</p> <p>The genetic architecture of multifactorial traits such as obesity has been poorly understood. Quantitative trait locus (QTL) analysis is widely used to localize loci affecting multifactorial traits on chromosomal regions. However, large confidence intervals and small phenotypic effects of identified QTLs and closely linked loci are impeding the identification of causative genes that underlie the QTLs. Here we developed five subcongenic mouse strains with overlapping and non-overlapping wild-derived genomic regions from an F2 intercross of a previously developed congenic strain, B6.Cg-<it>Pbwg1</it>, and its genetic background strain, C57BL/6J (B6). The subcongenic strains developed were phenotyped on low-fat standard chow and a high-fat diet to fine-map a previously identified obesity QTL. Microarray analysis was performed with Affymetrix GeneChips to search for candidate genes of the QTL.</p> <p>Results</p> <p>The obesity QTL was physically mapped to an 8.8-Mb region of mouse chromosome 2. The wild-derived allele significantly decreased white fat pad weight, body weight and serum levels of glucose and triglyceride. It was also resistant to the high-fat diet. Among 29 genes residing within the 8.8-Mb region, <it>Gpd2, Upp2, Acvr1c, March7 </it>and <it>Rbms1 </it>showed great differential expression in livers and/or gonadal fat pads between B6.Cg-<it>Pbwg1 </it>and B6 mice.</p> <p>Conclusions</p> <p>The wild-derived QTL allele prevented obesity in both mice fed a low-fat standard diet and mice fed a high-fat diet. This finding will pave the way for identification of causative genes for obesity. A further understanding of this unique QTL effect at genetic and molecular levels may lead to the discovery of new biological and pathologic pathways associated with obesity.</p