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Heart size is an important factor in cardiac health and disease. In particular, increased heart weight is predictive of adverse cardiovascular outcomes in multiple large community-based studies. We use two cohorts of Diversity Outbred (DO) mice to investigate the role of genetics, sex, age, and diet on heart size. DO mice (n = 289) of both sexes from generation 10 were fed a standard chow diet, and analyzed at 12–15 weeks of age. Another cohort of female DO mice (n = 258) from generation 11 were fed either a high-fat, cholesterol-containing (HFC) diet or a low-fat, high-protein diet, and analyzed at 24–25 weeks. We did not observe an effect of diet on body or heart weight in generation 11 mice, although we previously reported an effect on other cardiovascular risk factors, including cholesterol, triglycerides, and insulin. We do observe a significant genetic effect on heart weight in this population. We identified two quantitative trait loci for heart weight, one (Hwtf1) at a genome-wide significance level of p ≤ 0.05 on MMU15 and one (Hwtf2) at a genome-wide suggestive level of p ≤ 0.1 on MMU10, that together explain 13.3% of the phenotypic variance. Hwtf1 contained collagen type XXII alpha 1 chain (Col22a1), and the NZO/HlLtJ and WSB/EiJ haplotypes were associated with larger hearts. This is consistent with heart tissue Col22a1 expression in DO founders and SNP patterns within Hwtf1 for Col22a1. Col22a1 has been previously associated with cardiac fibrosis in mice, suggesting that Col22a1 may be involved in pathological cardiac hypertrophy.

High dietary fat intake and obesity may increase the risk of susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F2 mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F2 mice either a very high-fat or a matched-control-fat diet, and we measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL × diet interaction effects. Here we describe effects of diet on mammary tumor and metastases phenotypes, mapping of tumor/metastasis modifier genes, and the interaction between dietary fat levels and effects of cancer modifiers. Results demonstrate that animals fed a high-fat diet are not only more likely to experience decreased mammary cancer latency but increased tumor growth and pulmonary metastases occurrence over an equivalent time. We identified 25 modifier loci for mammary cancer and pulmonary metastasis, likely representing 13 unique loci after accounting for pleiotropy, and novel QTL × diet interactions at a majority of these loci. These findings highlight the importance of accurately modeling not only the human cancer characteristics in mice but also the environmental exposures of human populations Udgivelsesdato: March High dietary fat intake and obesity may increase the risk of susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F2 mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F2 mice either a very high-fat or a matched-control-fat diet, and we measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL × diet interaction effects. Here we describe effects of diet on mammary tumor and metastases phenotypes, mapping of tumor/metastasis modifier genes, and the interaction between dietary fat levels and effects of cancer modifiers. Results demonstrate that animals fed a high-fat diet are not only more likely to experience decreased mammary cancer latency but increased tumor growth and pulmonary metastases occurrence over an equivalent time. We identified 25 modifier loci for mammary cancer and pulmonary metastasis, likely representing 13 unique loci after accounting for pleiotropy, and novel QTL × diet interactions at a majority of these loci. These findings highlight the importance of accurately modeling not only the human cancer characteristics in mice but also the environmental exposures of human populations

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n approximately to 1000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from 10-week-old F2 females (n = 439) detected 15 quantitative trait loci (QTLs) on 5 chromosomes that influence reproduction traits characterized at day 16 of gestation. These QTL are broadly categorized into two groups: those where effects on the number of live fetuses (LF) were accompanied by parallel effects on the number of dead fetuses (DF), and those free of such undesirable effects. QTL for ovulation rate (OR) did not overlap with QTL for litter size, potentially indicating the importance of uterine capacity. Large dominance effects were identified for most QTL detected, and overdominance was also present. The QTL of largest effects were detected in regions of Chromosome 2, where large QTL effects for growth and fatness have also been found and where corroborating evidence from other studies exists. Considerable overlap between locations of QTL for reproductive traits and for growth traits corresponds well with the positive correlations usually observed among these sets of phenotypes. Some support for the relevance of QTL x genetic background interactions in reproduction was detected. Traits with low heritability demand considerably larger sample sizes to achieve effective power of QTL detection. This is unfortunate as traits with low heritability are among those that could most benefit from QTL-complemented breeding and selection strategies in food animal production.

By use of long-term selection lines for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted in mice to further understand the genetic architecture of complex polygenic traits. In combination with previous work, we conclude that QTL analysis has reinforced classic polygenic paradigms put in place prior to molecular analysis. Composite interval mapping revealed large numbers of QTL for growth traits with an exponential distribution of magnitudes of effects and validated theoretical expectations regarding gene action. Of particular significance, large effects were detected on Chromosome (Chr) 2. Regions on Chrs 1, 3, 6, 10, 11, and 17 also harbor loci with significant contributions to phenotypic variation for growth. Despite the large sample size, average confidence intervals of approximately 20 cM exhibit the poor resolution for initial estimates of QTL location. Analysis with genome-wide and chromosomal polygenic models revealed that, under certain assumptions, large fractions of the genome may contribute little to phenotypic variation for growth. Only a few epistatic interactions among detected QTL, little statistical support for gender-specific QTL, and significant age effects on genetic architecture were other primary observations from this study.

Ovulation rate is a major factor determining litter size in swine and is, therefore, a trait of economic importance to the pork industry. The dynamics of follicle development, which in turn are dictated by a balance between follicle recruitment, maturation, selection, and atresia, are a major determining factor of ovulation rate. The role of several genes expressed in the ovaries during these processes has been described, but studies utilizing large-scale genomic approaches have yet to be conducted to examine gene expression in this tissue more globally. We have developed a normalized cDNA library from swine ovarian follicles in various stages of development, ranging from 2.0 to 10.0 mm in diameter, collected from gilts from divergent genetic lines selected for high and low ovulation rates, during the 7 initial days of the follicular phase of the estrous cycle. EST sequences were obtained from 5231 distinct clones derived from this library. In total, 3479 unique sequence clusters were obtained, of which 2661 singletons (76.5%) were observed. BLASTN searches with the primary sequences from the clusters obtained resulted in 1037 sequences not matching (E

and Implications Human and sheep Melatonin receptor 1a (MTNR1A) gene information was used to clone a portion of the coding region of this gene in pigs, and to identify polymorphisms of the gene for its assignment to both the genetic linkage and physical maps. MTNR1A maps to pig chromosome 17, establishing a new region of conserved synteny between this chromosome and human chromosome 4. Furthermore, we have assigned MTNR1A to bovine chromosome 27 and sheep chromosome 26. The addition of genes like MTNR1A to livestock genome maps allows questions about evolutionary events and the genetic basis for quantitative traits in livestock to be addressed.