Autoimmune hyperthyroidism, Graves' disease, can be induced by immunizing susceptible strains of mice with adenovirus encoding the human thyrotropin receptor (TSHR) or its A-subunit. Studies in two small families of recombinant inbred strains showed that susceptibility to developing TSHR antibodies (measured by TSH binding inhibition, TBI) was linked to the MHC region whereas genes on different chromosomes contributed to hyperthyroidism. We have now investigated TSHR antibody production and hyperthyroidism induced by TSHR A-subunit adenovirus immunization of a larger family of strains (26 of the AXB and BXA strains). Analysis of the combined AXB and BXA families provided unexpected insight into several aspects of Graves' disease. First, extreme thyroid hyperplasia and hyperthyroidism in one remarkable strain, BXA13, reflected an inability to generate non-functional TSHR antibodies measured by ELISA. Although neutral TSHR antibodies have been detected in Graves' sera, pathogenic, functional TSHR antibodies in Graves' patients are undetectable by ELISA. Therefore, this strain immunized with A-subunit-adenovirus that generates only functional TSHR antibodies may provide an improved model for studies of induced Graves' disease. Second, our combined analysis of linkage data from this and previous work strengthens the evidence that gene variants in the immunoglobulin heavy chain V region contribute to generating thyroid stimulating antibodies. Third, a broad region that encompasses the MHC region on mouse chromosome 17 is linked to the development of TSHR antibodies (measured by TBI). Most importantly, unlike other strains, TBI linkage in the AXB and BXA families to MHC class I and class II genes provides an explanation for the unresolved class I/class II difference in humans.

Neurons are commonly organized as regular arrays within a structure, and their patterning is achieved by minimizing the proximity between like-type cells, but molecular mechanisms regulating this process have, until recently, been unexplored. We performed a forward genetic screen using recombinant inbred (RI) strains derived from two parental A/J and C57BL/6J mouse strains to identify genomic loci controlling spacing of cholinergic amacrine cells, which is a subclass of retinal interneuron. We found conspicuous variation in mosaic regularity across these strains and mapped a sizeable proportion of that variation to a locus on chromosome 11 that was subsequently validated with a chromosome substitution strain. Using a bioinformatics approach to narrow the list of potential candidate genes, we identified pituitary tumor-transforming gene 1 (Pttg1) as the most promising. Expression of Pttg1 was significantly different between the two parental strains and correlated with mosaic regularity across the RI strains. We identified a seven-nucleotide deletion in the Pttg1 promoter in the C57BL/6J mouse strain and confirmed a direct role for this motif in modulating Pttg1 expression. Analysis of Pttg1 KO mice revealed a reduction in the mosaic regularity of cholinergic amacrine cells, as well as horizontal cells, but not in two other retinal cell types. Together, these results implicate Pttg1 in the regulation of homotypic spacing between specific types of retinal neurons. The genetic variant identified creates a binding motif for the transcriptional activator protein 1 complex, which may be instrumental in driving differential expression of downstream processes that participate in neuronal spacing.

The sizes of different neuronal populations within the CNS are precisely controlled, but whether neuronal number is coordinated between cell types is unknown. We examined the covariance structure of 12 different retinal cell types across 30 genetically distinct lines of mice, finding minimal covariation when comparing synaptically connected or developmentally related cell types. Variation mapped to one or more genomic loci for each cell type, but rarely were these shared, indicating minimal genetic coregulation of final number. Multiple genes, therefore, participate in the specification of the size of every population of retinal neuron, yet genetic variants work largely independent of one another during development to modulate those numbers, yielding substantial variability in the convergence ratios between pre- and postsynaptic populations. Density-dependent cellular interactions in the outer plexiform layer overcome this variability to ensure the formation of neuronal circuits that maintain constant retinal coverage and complete afferent sampling.

Numerous shown consequences of age-related hearing loss have been unveiled; however, the relationship of the cortical and subcortical structures of the auditory pathway with aging is not well known. Investigations into neural structure analysis remain sparse due to difficulties of doing so in animal models; however, recent technological advances have been able to achieve a resolution adequate to perform such studies even in the small mouse. We utilize 12 members of the BXD family of recombinant inbred mice and aged separate cohorts. Utilizing novel magnetic resonance histology imaging techniques, we imaged these mice and generated high spatial resolution three dimensional images which were then comprehensively labeled. We completed volumetric analysis of 12 separate regions of interest specific to the auditory pathway brainstem nuclei and cortical areas with focus on the effect of aging upon said structures. Our results showed significant interstrain variation in the age-related effect on structure volume supporting a genetic influence in this interaction. Through multivariable modeling, we observed heterogenous effects of aging between different structures. Six of the 12 regions of interests demonstrated a significant age-related effect. The auditory cortex and ventral cochlear nucleus were found to decrease in volume with age, while the medial division of the medial geniculate nucleus, lateral lemniscus and its nucleus, and the inferior colliculus increased in size with age. Additionally, no sex-based differences were noted, and we observed a negative relationship between auditory cortex volume and mouse weight. This study is one of the first to perform comprehensive magnetic resonance imaging and quantitative analysis in the mouse brain auditory pathway cytoarchitecture, offering both novel insights into the neuroanatomical basis of age-related changes in hearing as well as evidence toward a genetic influence in this interaction. High resonance magnetic resonance imaging provides a promising efficacious avenue in future mouse model hearing loss investigations.

Genetically diverse inbred strains are frequently used in quantitative trait mapping to identify sequence variants underlying trait variation. Poor locus resolution and high genetic complexity impede variant discovery. As a solution, we explore reduced complexity crosses (RCCs) between phenotypically divergent, yet genetically similar, rodent substrains. RCCs accelerate functional variant discovery via decreasing the number of segregating variants by orders of magnitude. The simplified genetic architecture of RCCs often permit immediate identification of causal variants or rapid fine-mapping of broad loci to smaller intervals. Whole-genome sequences of substrains make RCCs possible by supporting the development of array- and targeted sequencing-based genotyping platforms, coupled with rapid genome editing for variant validation. In summary, RCCs enhance discovery-based genetics of complex traits.

Dopaminergic neurons in the midbrain are of particular interest due to their role in diseases such as Parkinson's disease and schizophrenia. Genetic variation between individuals can affect the integrity and function of dopaminergic neurons but the DNA variants and molecular cascades modulating dopaminergic neurons and other cells types of ventral midbrain remain poorly defined. Three genetically diverse inbred mouse strains - C57BL/6J, A/J, and DBA/2J - differ significantly in their genomes (∼7 million variants), motor and cognitive behavior, and susceptibility to neurotoxins. To further dissect the underlying molecular networks responsible for these variable phenotypes, we generated RNA-seq and ChIP-seq data from ventral midbrains of the 3 mouse strains. We defined 1000-1200 transcripts that are differentially expressed among them. These widespread differences may be due to altered activity or expression of upstream transcription factors. Interestingly, transcription factors were significantly underrepresented among the differentially expressed genes, and only one transcription factor, Pttg1, showed significant differences between all three strains. The changes in Pttg1 expression were accompanied by consistent alterations in histone H3 lysine 4 trimethylation at Pttg1 transcription start site. The ventral midbrain transcriptome of 3-month-old C57BL/6J congenic Pttg1^-/- mutants was only modestly altered, but shifted toward that of A/J and DBA/2J in 9-month-old mice. Principle component analysis (PCA) identified the genes underlying the transcriptome shift and deconvolution of these bulk RNA-seq changes using midbrain single cell RNA-seq data suggested that the changes were occurring in several different cell types, including neurons, oligodendrocytes, and astrocytes. Taken together, our results show that Pttg1 contributes to gene regulatory variation between mouse strains and influences mouse midbrain transcriptome during aging.

Short tandem repeats (STRs) are a class of rapidly mutating genetic elements typically characterized by repeated units of 1-6 bp. We leveraged whole-genome sequencing data for 152 recombinant inbred (RI) strains from the BXD family of mice to map loci that modulate genome-wide patterns of new mutations arising during parent-to-offspring transmission at STRs. We defined quantitative phenotypes describing the numbers and types of germline STR mutations in each strain and performed quantitative trait locus (QTL) analyses for each of these phenotypes. We identified a locus on Chromosome 13 at which strains inheriting the C57BL/6J (B) haplotype have a higher rate of STR expansions than those inheriting the DBA/2J (D) haplotype. The strongest candidate gene in this locus is Msh3, a known modifier of STR stability in cancer and at pathogenic repeat expansions in mice and humans, as well as a current drug target against Huntington's disease. The D haplotype at this locus harbors a cluster of variants near the 5' end of Msh3, including multiple missense variants near the DNA mismatch recognition domain. In contrast, the B haplotype contains a unique retrotransposon insertion. The rate of expansion covaries positively with Msh3 expression-with higher expression from the B haplotype. Finally, detailed analysis of mutation patterns showed that strains carrying the B allele have higher expansion rates, but slightly lower overall total mutation rates, compared with those with the D allele, particularly at tetranucleotide repeats. Our results suggest an important role for inherited variants in Msh3 in modulating genome-wide patterns of germline mutations at STRs.

The scientific community is increasingly concerned with the proportion of published "discoveries" that are not replicated in subsequent studies. The field of rodent behavioral phenotyping was one of the first to raise this concern, and to relate it to other methodological issues: the complex interaction between genotype and environment; the definitions of behavioral constructs; and the use of laboratory mice and rats as model species for investigating human health and disease mechanisms. In January 2015, researchers from various disciplines gathered at Tel Aviv University to discuss these issues. The general consensus was that the issue is prevalent and of concern, and should be addressed at the statistical, methodological and policy levels, but is not so severe as to call into question the validity and the usefulness of model organisms as a whole. Well-organized community efforts, coupled with improved data and metadata sharing, have a key role in identifying specific problems and promoting effective solutions. Replicability is closely related to validity, may affect generalizability and translation of findings, and has important ethical implications.

Background

A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.

Description

Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them.

Conclusion

By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.