The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

Background: To better understand the genetic determination of udder health, we performed a genome-wide association study (GWAS) on a population of 2354 German Holstein bulls for which daughter yield deviations (DYD) for somatic cell score (SCS) were available. For this study, we used genetic information of 44 576 informative single nucleotide polymorphisms (SNPs) and 11 725 inferred haplotype blocks. Results: When accounting for the sub-structure of the analyzed population, 16 SNPs and 10 haplotypes in six genomic regions were significant at the Bonferroni threshold of P ≤ 1.14 × 10 ^-6 . The size of the identified regions ranged from 0.05 to 5.62 Mb. Genomic regions on chromosomes 5, 6, 18 and 19 coincided with known QTL affecting SCS, while additional genomic regions were found on chromosomes 13 and X. Of particular interest is the region on chromosome 6 between 85 and 88 Mb, where QTL for mastitis traits and significant SNPs for SCS in different Holstein populations coincide with our results. In all identified regions, except for the region on chromosome X, significant SNPs were present in significant haplotypes. The minor alleles of identified SNPs on chromosomes 18 and 19, and the major alleles of SNPs on chromosomes 6 and X were favorable for a lower SCS. Differences in somatic cell count (SCC) between alternative SNP alleles reached 14 000 cells/mL. Conclusions: The results support the polygenic nature of the genetic determination of SCS, confirm the importance of previously reported QTL, and provide evidence for the segregation of additional QTL for SCS in Holstein cattle. The small size of the regions identified here will facilitate the search for causal genetic variations that affect gene functions.

Effects of probiotic bacteria on viral infections have been described previously. Here, two groups of sows and their piglets were fed with or without feed supplementation of the probiotic bacterium Enterococcus faecium NCIMB 10415. Shedding of enteric viruses naturally occurring in these pigs was analyzed by quantitative real-time RT-PCR. No differences between the groups were recorded for hepatitis E virus, encephalomyocarditis virus and norovirus. In contrast, astrovirus was exclusively detected in the non-supplemented control group. Rotavirus was shedded later and with lower amounts in the probiotic piglet group (p < 0.05); rotavirus-shedding piglets gained less weight than non-infected animals (p < 0.05). Serum titres of anti-rotavirus IgA and IgG antibodies were higher in piglets from the control group, whereas no difference was detected between sow groups. Phenotype analysis of immune cell antigens revealed significant differences of the CD4 and CD8β (p < 0.05) as well as CD8α and CD25 (p < 0.1) T cell populations of the probiotic supplemented group compared to the non-supplemented control group. In addition, differences were evident for CD21/MHCII-positive (p < 0.05) and IgM-positive (p < 0.1) B cell populations. The results indicate that probiotic bacteria could have effects on virus shedding in naturally infected pigs, which depend on the virus type. These effects seem to be caused by immunological changes; however, the distinct mechanism of action remains to be elucidated.

Background: Obesity-associated organ-specific pathological states can be ensued from the dysregulation of the functions of the adipose tissues, liver and muscle. However, the influence of genetic differences underlying gross-compositional differences in these tissues is largely unknown. In the present study, the analytical method of ATR-FTIR spectroscopy has been combined with a genetic approach to identify genetic differences responsible for phenotypic alterations in adipose, liver and muscle tissues. Results: Mice from 29 BXD recombinant inbred mouse strains were put on high fat diet and gross-compositional changes in adipose, liver and muscle tissues were measured by ATR-FTIR spectroscopy. The analysis of genotype-phenotype correlations revealed significant quantitative trait loci (QTL) on chromosome 12 for the content of fat and collagen, collagen integrity, and the lipid to protein ratio in adipose tissue and on chromosome 17 for lipid to protein ratio in liver. Using gene expression and sequence information, we suggest Rsad2 (viperin) and Colec11 (collectin-11) on chromosome 12 as potential quantitative trait candidate genes. Rsad2 may act as a modulator of lipid droplet contents and lipid biosynthesis; Colec11 might play a role in apoptopic cell clearance and maintenance of adipose tissue. An increased level of Rsad2 transcripts in adipose tissue of DBA/2J compared to C57BL/6J mice suggests a cis-acting genetic variant leading to differential gene activation. Conclusion: The results demonstrate that the analytical method of ATR-FTIR spectroscopy effectively contributed to decompose the macromolecular composition of tissues that accumulate fat and to link this information with genetic determinants. The candidate genes in the QTL regions may contribute to obesity-related diseases in humans, in particular if the results can be verified in a bigger BXD cohort.

The aim of this study was to characterize the responses of individual tissues to high-fat feeding as a function of mass, fat composition, and transcript abundance. We examined a panel of eight tissues [5 white adipose tissues (WAT), brown adipose tissue (BAT), liver, muscle] obtained from DBA/2J mice on either a standard breeding diet (SBD) or a high-fat diet (HFD). HFD led to weight gain, decreased insulin sensitivity, and tissue-specific responses, including inflammation, in these mice. The dietary fatty acids were partially metabolized and converted in both liver and fat tissues. Saturated fatty acids (SFA) were converted in the liver to monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA), and oleic acid (C18:1) was the preferred MUFA for storage of excess energy in all tissues of HFD-fed mice. Transcriptional changes largely reflected the tissue-specific fat deposition. SFA were negatively correlated with genes in the collagen family and processes involving the extracellular matrix. We propose a novel role of the tryptophan hydroxylase 2 (Tph2) gene in adipose tissues of diet-induced obesity. Tissue-specific responses to HFD were identified. Liver steatosis was evident in HFD-fed mice. Gonadal, retroperitoneal and subcutaneous adipose tissue and BAT exhibited severe inflammatory and immune responses. Mesenteric adipose tissue was the most metabolically active adipose tissue. Gluteal adipose tissue had the highest mass gain but was sluggish in its metabolism. In HFD conditions, BAT functioned largely like WAT in its role as a depot for excess energy, whereas WAT played a role in thermogenesis.