Relating multivariate shapes to genescapes using 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 = 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.

Association of novelty-related behaviors and intravenous cocaine self-administration in Diversity Outbred mice

RATIONALE

The preference for and reaction to novelty are strongly associated with addiction to cocaine and other drugs. However, the genetic variants and molecular mechanisms underlying these phenomena remain largely unknown. Although the relationship between novelty- and addiction-related traits has been observed in rats, studies in mice have failed to demonstrate this association. New, genetically diverse, high-precision mouse populations including Diversity Outbred (DO) mice provide an opportunity to assess an expanded range of behavioral variation enabling detection of associations of novelty- and addiction-related traits in mice.

METHODS

To examine the relationship between novelty- and addiction-related traits, male (n = 51) and female (n = 47) DO mice were tested on open field exploration, hole board exploration, and novelty preference followed by intravenous cocaine self-administration (IVSA; ten 2-h sessions of fixed ratio 1 and one 6-h session of progressive ratio).

RESULTS

We observed high variation of cocaine IVSA in DO mice with 43 % reaching and 57 % not reaching conventional acquisition criteria. As a group, mice that did not reach these criteria still demonstrated significant lever discrimination. Mice experiencing catheter occlusion or other technical issues (n = 17) were excluded from the analysis. Novelty-related behaviors were positively associated with cocaine IVSA. Multivariate analysis of associations among novelty- and addiction-related traits revealed a large degree of shared variance (45 %).

CONCLUSIONS

Covariation among cocaine IVSA and novelty-related phenotypes in DO mice indicates that this relationship is amenable to genetic dissection. The high genetic precision and phenotypic diversity in the DO may facilitate discovery of previously undetectable mechanisms underlying predisposition to develop addiction disorders.

Impact of the environment on the skeleton: is it modulated by genetic factors?

The etiology of skeletal disease is driven by genetic and environmental factors. Genome-wide association studies (GWAS) of osteoporotic phenotypes have identified novel candidate genes, but have only uncovered a small proportion of the trait variance explained. This "missing heritability" is caused by several factors, including the failure to consider gene-by-environmental (G*E) interactions. Some G*E interactions have been investigated, but new approaches to integrate environmental data into genomic studies are needed. Advances in genotyping and meta-analysis techniques now allow combining genotype data from multiple studies, but the measurement of key environmental factors in large human cohorts still lags behind, as do the statistical tools needed to incorporate these measures in genome-wide association meta-studies. This review focuses on discussing ways to enhance G*E interaction studies in humans and how the use of rodent models can inform genetic studies. Understanding G*E interactions will provide opportunities to effectively target intervention strategies for individualized therapy.

Haplotype probabilities in advanced intercross populations

Advanced intercross populations, in which multiple inbred strains are mated at random for many generations, have the advantage of greater precision of genetic mapping because of the accumulation of recombination events across the multiple generations. Related designs include heterogeneous stock and the diversity outcross population. In this article, I derive the two-locus haplotype probabilities on the autosome and X chromosome with these designs. These haplotype probabilities provide the key quantities for developing hidden Markov models for the treatment of missing genotype information. I further derive the map expansion in these populations, which is the frequency of recombination breakpoints on a random chromosome.