Cutting-edge technology: IV. Genomic engineering for studies of the gastrointestinal tract in mice

Advances in our understanding of the complex, dynamic interactions that exist among the gastrointestinal microflora, the epithelium of the gastrointestinal mucosae, and the immune system have been facilitated by powerful new genetic tools. Recent understanding that the gastrointestinal epithelium performs not only a barrier function but is also an active sensor of the microflora and an important intermediary in regulating and integrating cross-talk between it and cells of the innate and adaptive immune systems provides one of the most fertile and challenging areas for application of these technologies. The intestinal epithelium also represents an important model system for study of programs of cell lineage commitment and differentiation, given its continual and rapid regeneration throughout life and the regional differences in these programs that exist along the gastrocolonic and crypt-villous axes. This review will highlight current and emerging technologies that are available in the mouse model for identification and manipulation of genetic elements that regulate the normal and pathological physiology of the intestinal tissues in the post-genomic era.     

Genomic studies of uncultivated archaea

Archaea represent a considerable fraction of the prokaryotic world in marine and terrestrial ecosystems, indicating that organisms from this domain might have a large impact on global energy cycles. However, many novel archaeal lineages that have been detected by molecular phylogenetic approaches have remained elusive because no laboratory-cultivated strains are available. Environmental genomic analyses have recently provided clues about the potential metabolic strategies of several of the uncultivated and abundant archaeal species, including non-thermophilic terrestrial and marine crenarchaeota and methanotrophic euryarchaeota. These initial studies of natural archaeal populations also revealed an unexpected degree of genomic variation that indicates considerable heterogeneity among archaeal strains. Here, we review genomic studies of uncultivated archaea within a framework of the phylogenetic diversity and ecological distribution of this domain.     

Genomic control for association studies

A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with case control data and yet, like family-based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly independent; and, by using Bayesian outlier methods, it circumvents the need for Bonferroni correction for multiple tests, leading to better performance in many settings while still constraining risk for false positives. The performance of our genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.     

Genomic analysis of metabolic pathway gene expression in mice

Background  

A segregating population of (C57BL/6J × DBA/2J)F2 intercross mice was studied for obesity-related traits and for global gene expression in liver. Quantitative trait locus analyses were applied to the subcutaneous fat-mass trait and all gene-expression data. These data were then used to identify gene sets that are differentially perturbed in lean and obese mice.     

Cytogenetic studies on wild house mice from Belgium

The present status of Robertsonian karyotype variation in populations of wild mice from Belgium is presented. Two fusions, Rb(4.12)1Nam and Rb(5.10)3Nam, were identified in the central plain of this flat country. Surrounding this region only mice with the usual 2n=40 karyotype occurred. From the distribution pattern some possible relationships to other Rb populations from Europe are discussed.     

Genomic imprinting and genetic effects on muscle traits in mice

ABSTRACT: BACKGROUND: Genomic imprinting refers to parent-of-origin dependent gene expression caused by differential DNA methylation of the paternally and maternally derived alleles. Imprinting is increasingly recognized as an important source of variation in complex traits, however, its role in explaining variation in muscle and physiological traits, especially those of commercial value, is largely unknown compared with genetic effects. RESULTS: We investigated both genetic and genomic imprinting effects on key muscle traits in mice from the Berlin Muscle Mouse population, a key model system to study muscle traits. Using a genome scan, we first identified loci with either imprinting or genetic effects on phenotypic variation. Next, we established the proportion of phenotypic variation explained by additive, dominance and imprinted QTL and characterized the patterns of effects. In total, we identified nine QTL, two of which show large imprinting effects on glycogen content and potential, and body weight. Surprisingly, all imprinting patterns were of the bipolar type, in which the two heterozygotes are different from each other but the homozygotes are not. Most QTL had pleiotropic effects and explained up to 40% of phenotypic variance, with individual imprinted loci accounting for 4-5% of variation alone. CONCLUSION: Surprisingly, variation in glycogen content and potential was only modulated by imprinting effects. Further, in contrast to general assumptions, our results show that genomic imprinting can impact physiological traits measured at adult stages and that the expression does not have to follow the patterns of paternal or maternal expression commonly ascribed to imprinting effects.     

Genomic imprinting: an obsession with depilatory mice

Excessive grooming in mice has been promoted as a model of human obsessive-compulsive disorders. A recent paper adds Grb10 to the list of genes with effects on behavioral hair loss, with the added twist that this time the gene is imprinted.     

Melatonin and protection from whole-body irradiation: survival studies in mice

The radioprotective ability of melatonin was investigated in mice exposed to an acute whole-body gamma radiation dose of 815 cGy (estimated LD50/30 dose). The animals were observed for mortality over a period of 30 days following irradiation. The results indicated 100% survival for unirradiated and untreated control mice, and for mice treated with melatonin or solvent alone. Forty-five percent of mice exposed to 815 cGy radiation alone, and 50% of mice pretreated with solvent and irradiated with 815 cGy were alive at the end of 30 days. Irradiated mice which were pretreated with 125 mg/kg melatonin exhibited a slight increase in their survival (60%) (p=0.3421). In contrast, 85% of irradiated mice which were pretreated with 250 mg/kg melatonin were alive at the end of 30 days (p=0.0080). These results indicate that melatonin (at a dose as high as 250 mg/kg) is non-toxic, and that high doses of melatonin are effective in protecting mice from lethal effects of acute whole-body irradiation.     

Genomic and proteomic analysis of mammary tumors arising in transgenic mice

Transforming growth factor-beta (TGF-beta) is the prototype of a large family of signaling molecules. TGF-beta signaling profoundly influences tumor development as demonstrated in several engineered mouse models. The present study was designed to identify differences by cDNA microarray and MALDI-TOF MS analyses in mammary carcinomas with and without TGF-beta signaling. The results demonstrate a significant potential for combination of profiling technologies to further understand the molecular mechanisms of breast cancer.     

Genomic variation in the vomeronasal receptor gene repertoires of inbred mice

ABSTRACT: BACKGROUND: Vomeronasal receptors (VRs), expressed in sensory neurons of the vomeronasal organ, are thought to bind pheromones and mediate innate behaviours. The mouse reference genome has over 360 functional VRs arranged in highly homologous clusters, but the vast majority are of unknown function. Differences in these receptors within and between closely related species of mice are likely to underpin a range of behavioural responses. To investigate these differences, we interrogated the VR gene repertoire from 17 inbred strains of mice using massively parallel sequencing. RESULTS: Approximately half of the 6222 VR genes that we investigated could be successfully resolved, and those that were unambiguously mapped resulted in an extremely accurate dataset. Collectively VRs have over twice the coding sequence variation of the genome average; but we identify striking non-random distribution of these variants within and between genes, clusters, clades and functional classes of VRs. We show that functional VR gene repertoires differ considerably between different Mus subspecies and species, suggesting these receptors may play a role in mediating behavioural adaptations. Finally, we provide evidence that widely-used, highly inbred laboratory-derived strains have a greatly reduced, but not entirely redundant capacity for differential pheromone-mediated behaviours. CONCLUSIONS: Together our results suggest that the unusually variable VR repertoires of mice have a significant role in encoding differences in olfactory-mediated responses and behaviours. Our dataset has expanded over nine fold the known number of mouse VR alleles, and will enable mechanistic analyses into the genetics of innate behavioural differences in mice.     

Genomic studies on killer yeasts belonging to the genusPichia

Twenty-four species belonging to the genusPichia were investigated using restriction fragment length polymorphism (RFLP) and Southern blot hybridization of their genomic DNA.Saccharomyces cerevisiae, Kluyveromyces lactis, Williopsis mrakii andCandida albicans were also included in this study. The RFLP patterns were obtained from digestion of yeast DNA with several restriction endonuclease enzymes, and showed various bands with different mobility; in most isolates, the more deeply stained bands were species-specific. This observation was confirmed by the results obtained from Southern blot hybridization of theEcoRI andXhoI RFLP patterns withP. anomala UCSC 25F DNA, digested with the same enzymes, used as probes. These bands are likely to be ribosomal DNA as shown by hybridization of digested DNA from unrelated yeast species (S. cerevisiae, K. lactis andC. albicans). However, one hybridized band, located at 3.9–4.1 Kb, seems to be peculiar to thePichia species. Our study confirms the usefulness of molecular tools in studying genetic relatedness among yeasts.     

Genomic control for association studies under various genetic models

Case-control studies are commonly used to study whether a candidate allele and a disease are associated. However, spurious association can arise due to population substructure or cryptic relatedness, which cause the variance of the trend test to increase. Devlin and Roeder derived the appropriate variance inflation factor (VIF) for the trend test and proposed a novel genomic control (GC) approach to estimate VIF and adjust the test statistic. Their results were derived assuming an additive genetic model and the corresponding VIF is independent of the candidate allele frequency. We determine the appropriate VIFs for recessive and dominant models. Unlike the additive test, the VIFs for the optimal tests for these two models depend on the candidate allele frequency. Simulation results show that, when the null loci used to estimate the VIF have allele frequencies similar to that of the candidate gene, the GC tests derived for recessive and dominant models remain optimal. When the underlying genetic model is unknown or the null loci and candidate gene have quite different allele frequencies, the GC tests derived for the recessive or dominant models cannot be used while the GC test derived for the additive model can be.     

Inferences from Genomic Models in Stratified Populations

Unaccounted population stratification can lead to spurious associations in genome-wide association studies (GWAS) and in this context several methods have been proposed to deal with this problem. An alternative line of research uses whole-genome random regression (WGRR) models that fit all markers simultaneously. Important objectives in WGRR studies are to estimate the proportion of variance accounted for by the markers, the effect of individual markers, prediction of genetic values for complex traits, and prediction of genetic risk of diseases. Proposals to account for stratification in this context are unsatisfactory. Here we address this problem and describe a reparameterization of a WGRR model, based on an eigenvalue decomposition, for simultaneous inference of parameters and unobserved population structure. This allows estimation of genomic parameters with and without inclusion of marker-derived eigenvectors that account for stratification. The method is illustrated with grain yield in wheat typed for 1279 genetic markers, and with height, HDL cholesterol and systolic blood pressure from the British 1958 cohort study typed for 1 million SNP genotypes. Both sets of data show signs of population structure but with different consequences on inferences. The method is compared to an advocated approach consisting of including eigenvectors as fixed-effect covariates in a WGRR model. We show that this approach, used in the context of WGRR models, is ill posed and illustrate the advantages of the proposed model. In summary, our method permits a unified approach to the study of population structure and inference of parameters, is computationally efficient, and is easy to implement.