David G. Ashbrook

Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease

BackgroundVariation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders.ResultsWe combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis.ConclusionsWe find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer’s.

Genetic variation in offspring indirectly influences the quality of maternal behaviour in mice

Conflict over parental investment between parent and offspring is predicted to lead to selection on genes expressed in offspring for traits influencing maternal investment, and on parentally expressed genes affecting offspring behaviour. However, the specific genetic variants that indirectly modify maternal or offspring behaviour remain largely unknown. Using a cross-fostered population of mice, we map maternal behaviour in genetically uniform mothers as a function of genetic variation in offspring and identify loci on offspring chromosomes 5 and 7 that modify maternal behaviour. Conversely, we found that genetic variation among mothers influences offspring development, independent of offspring genotype. Offspring solicitation and maternal behaviour show signs of coadaptation as they are negatively correlated between mothers and their biological offspring, which may be linked to costs of increased solicitation on growth found in our study. Overall, our results show levels of parental provisioning and offspring solicitation are unique to specific genotypes. DOI: http://dx.doi.org/10.7554/eLife.11814.001

Empirical testing of hypotheses about the evolution of genomic imprinting in mammals.

The close interaction between mother and offspring in mammals is thought to contribute to the evolution of genomic imprinting or parent-of-origin dependent gene expression. Empirical tests of theories about the evolution of imprinting have been scant for several reasons. Models make different assumptions about the traits affected by imprinted genes and the scenarios in which imprinting is predicted to have been selected for. Thus, competing hypotheses cannot readily be tested against each other. Further, it is far from clear how predictions about expression patterns of genes with specific phenotypic effects can be tested given current methodology of assaying gene expression levels, be it in the brain or in other tissues. We first set out a scenario for testing competing hypotheses and delineate the different assumptions and predictions of models. We then outline how predictions may be tested using mouse models such as intercrosses or recombinant inbred (RI) systems that can be phenotyped for traits relevant to imprinting theories. Further, we briefly discuss different molecular approaches that may be used in conjunction with experiments to ascertain expression patterns of imprinted genes and thus the testing of predictions.

Transcript co-variance with Nestin in two mouse genetic reference populations identifies Lef1 as a novel candidate regulator of neural precursor cell proliferation in the adult hippocampus.

Adult neurogenesis, the lifelong production of new neurons in the adult brain, is under complex genetic control but many of the genes involved remain to be identified. In this study, we have integrated publicly available gene expression data from the BXD and CXB recombinant inbred mouse lines to discover genes co-expressed in the adult hippocampus with Nestin, a common marker of the neural precursor cell population. In addition, we incorporated spatial expression information to restrict candidates to genes with high differential gene expression in the hippocampal dentate gyrus. Incorporating data from curated protein-protein interaction databases revealed interactions between our candidate genes and those already known to be involved in adult neurogenesis. Enrichment analysis suggested a link to the Wnt/β-catenin pathway, known to be involved in adult neurogenesis. In particular, our candidates were enriched in targets of Lef1, a modulator of the Wnt pathway. In conclusion, our combination of bioinformatics approaches identified six novel candidate genes involved in adult neurogenesis; Amer3, Eya3, Mtdh, Nr4a3, Polr2a, and Tbkbp1. Further, we propose a role for Lef1 transcriptional control in the regulation of adult hippocampal precursor cell proliferation.

A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder

Bipolar disorder (BD) is a significant neuropsychiatric disorder with a lifetime prevalence of ~1%. To identify genetic variants underlying BD genome-wide association studies (GWAS) have been carried out. While many variants of small effect associated with BD have been identified few have yet been confirmed, partly because of the low power of GWAS due to multiple comparisons being made. Complementary mapping studies using murine models have identified genetic variants for behavioral traits linked to BD, often with high power, but these identified regions often contain too many genes for clear identification of candidate genes. In the current study we have aligned human BD GWAS results and mouse linkage studies to help define and evaluate candidate genes linked to BD, seeking to use the power of the mouse mapping with the precision of GWAS. We use quantitative trait mapping for open field test and elevated zero maze data in the largest mammalian model system, the BXD recombinant inbred mouse population, to identify genomic regions associated with these BD-like phenotypes. We then investigate these regions in whole genome data from the Psychiatric Genomics Consortiums bipolar disorder GWAS to identify candidate genes associated with BD. Finally we establish the biological relevance and pathways of these genes in a comprehensive systems genetics analysis. We identify four genes associated with both mouse anxiety and human BD. While TNR is a novel candidate for BD, we can confirm previously suggested associations with CMYA5, MCTP1, and RXRG. A cross-species, systems genetics analysis shows that MCTP1, RXRG, and TNR coexpress with genes linked to psychiatric disorders and identify the striatum as a potential site of action. CMYA5, MCTP1, RXRG, and TNR are associated with mouse anxiety and human BD. We hypothesize that MCTP1, RXRG, and TNR influence intercellular signaling in the striatum.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary—full‐genome sequence—is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Womens Health Initiative (www.whi.org), the Million Veterans Program (www.research.va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro‐ and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene‐by‐environment interactions. Researchers are already doing the hard part—the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Genome-Epigenome Interactions Associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is an example of a complex disease of unknown etiology. Multiple studies point to disruptions in immune functioning in ME/CFS patients as well as with specific genetic polymorphisms and alterations of the DNA methylome in lymphocytes. However, the association between DNA methylation and genetic background in relation to the ME/CFS is currently unknown. In this study we explored this association by characterizing the genomic (~4.3 million SNPs) and epigenomic (~480 thousand CpG loci) variability between populations of ME/CFS patients and healthy controls. We found significant associations of methylation states in T-lymphocytes at several CpG loci and regions with ME/CFS phenotype. These methylation anomalies are in close proximity to genes involved with immune function and cellular metabolism. Finally, we found significant correlations of genotypes with methylation phenotypes associated with ME/CFS. The findings from this study highlight the role of epigenetic and genetic interactions in complex diseases, and suggest several genetic and epigenetic elements potentially involved in the mechanisms of disease in ME/CFS.

Social Interactions and Indirect Genetic Effects on Complex Juvenile and Adult Traits

Most animal species are social in one form or another, yet many studies in rodent model systems use either individually housed animals or ignore potential confounds caused by group housing. While such social interaction effects on developmental and behavioral traits are well established, the genetic basis of social interactions has not been researched in as much detail. Specifically, the effects of genetic variation in social partners on the phenotype of a focal individual have mostly been studied at the phenotypic level. Such indirect genetic effects (IGEs), where the genotype of one individual influences the phenotype of a second individual, can have important evolutionary and medically relevant consequences. In this chapter, we give a brief outline of social interaction effects, and how systems genetics approaches using recombinant inbred populations can be used to investigate indirect genetic effects specifically, including maternal genetic effects. We discuss experimental designs for the study of IGEs and show how indirect genetic loci can be identified that underlie social interaction effects, their mechanisms, and consequences for trait variation in focal individuals.