Genetic control of obesity, glucose homeostasis, dyslipidemia and fatty liver in a mouse model of diet-induced metabolic syndrome

BACKGROUND/OBJECTIVES

Both genetic and dietary factors contribute to the metabolic syndrome (MetS) in humans and animal models. Characterizing their individual roles as well as relationships among these factors is critical for understanding MetS pathogenesis and developing effective therapies. By studying phenotypic responsiveness to high-risk versus control diet in two inbred mouse strains and their derivatives, we estimated the relative contributions of diet and genetic background to MetS, characterized strain-specific combinations of MetS conditions, and tested genetic and phenotypic complexity on a single substituted chromosome.

METHODS

Ten measures of metabolic health were assessed in susceptible C57BL/6 J and resistant A/J male mice fed either a control or a high-fat, high-sucrose (HFHS) diet, permitting estimates of the relative influences of strain, diet and strain-diet interactions for each trait. The same traits were measured in a panel of C57BL/6 J (B6)-Chr(A/J) chromosome substitution strains (CSSs) fed the HFHS diet, followed by characterization of interstrain relationships, covariation among metabolic traits and quantitative trait loci (QTLs) on Chromosome 10.

RESULTS

We identified significant genetic contributions to nine of ten metabolic traits and significant dietary influence on eight. Significant strain-diet interaction effects were detected for four traits. Although a range of HFHS-induced phenotypes were observed among the CSSs, significant associations were detected among all traits but one. Strains were grouped into three clusters based on overall phenotype and specific CSSs were identified with distinct and reproducible trait combinations. Finally, several Chr10 regions were shown to control the severity of MetS conditions.

CONCLUSIONS

Generally strong genetic and dietary effects validate these CSSs as a multifactorial model of MetS. Although traits tended to segregate together, considerable phenotypic heterogeneity suggests that underlying genetic factors influence their co-occurrence and severity. Identification of multiple QTLs within and among strains highlights both the complexity of genetically regulated, diet-induced MetS and the ability of CSSs to prioritize candidate loci for mechanistic studies.

Relationship of bull fertility to sperm nuclear shape

The relationship between sperm nuclear shape and bull fertility was determined. Two groups of bulls, 3 per group, were selected. Bulls differed in fertility based on lifetime nonreturn rates. Digital images of propidium iodide-stained sperm from each bull were collected and shape-evaluated by Fourier harmonic amplitudes 0 to 5. A discriminant function (P < .05) was constructed based on harmonic amplitudes and the 2 fertility groups. When individual sperm were classified as being of high or lower fertility, the percentage of each bull's sperm placed in the high-fertility group had a linear relationship (r = .89, P < .05) with fertility. To construct a plot of mean sperm shapes, a novel technique to automatically orient and identify the anterior tip of the sperm head was developed. The mean nuclear shape of high-fertility sperm was more elongated and tapered than those of lower fertility. A discriminant function (P < .05) was also constructed that separated the 6 bulls into 2 groups based only on the harmonic amplitudes or sperm nuclear shape. The bulls were correctly classified into the 2 fertility groups. A comparison of sperm chromatin structure analysis (SCSA) and harmonic amplitudes found that overall size variance, anterior roundness, and posterior taperedness of sperm nuclei were related to chromatin stability (P < .05). Some of the differences observed in sperm nuclear shape between the high- and lower-fertility bulls may be explained by varying levels of chromatin stability. However, sperm nuclear shape appears to contain additional information from chromatin stability alone. In this particular study, with 6 bulls, all with good chromatin quality, sperm nuclear shape was a better predictor of bull fertility.

Statistical issues in the analysis of quantitative traits in combined crosses

We consider some practical statistical issues in QTL analysis where several crosses originate in multiple inbred parents. Our results show that ignoring background polygenic variation in different crosses may lead to biased interval mapping estimates of QTL effects or loss of efficiency. Threshold and power approximations are derived by extending earlier results based on the Ornstein-Uhlenbeck diffusion process. The results are useful in the design and analysis of genome screen experiments. Several common designs are evaluated in terms of their power to detect QTL.

Genetic obesity unmasks nonlinear interactions between murine type 2 diabetes susceptibility loci

Nonlinear interactions between obesity and genetic risk factors are thought to determine susceptibility to type 2 diabetes. We used genetic obesity as a tool to uncover latent differences in diabetes susceptibility between two mouse strains, C57BL/6J (B6) and BTBR. Although both BTBR and B6 lean mice are euglycemic and glucose tolerant, lean BTBR x B6 F1 male mice are profoundly insulin resistant. We hypothesized that the genetic determinants of the insulin resistance syndrome might also predispose genetically obese mice to severe diabetes. Introgressing the ob allele into BTBR revealed large differences in diabetes susceptibility between the strain backgrounds. In a population of F2-ob/ob mice segregating for BTBR and B6 alleles, we observed large variation in pancreatic compensation for the underlying insulin resistance. We also detected two loci that substantially modify diabetes severity, and a third locus that strongly links to fasting plasma insulin levels. Amplification of the genetic signal from these latent diabetes susceptibility alleles in F2-ob/ob mice permitted discovery of an interaction between the two loci that substantially increased the risk of severe type 2 diabetes.

The expression of adipogenic genes is decreased in obesity and diabetes mellitus

Obesity is strongly correlated with type 2 diabetes mellitus, a common disorder of glucose and lipid metabolism. Although adipocytes are critical in obesity, their role in diabetes has only recently been appreciated. We conducted studies by using DNA microarrays to identify differences in gene expression in adipose tissue from lean, obese, and obese-diabetic mice. The expression level of over 11,000 transcripts was analyzed, and 214 transcripts showed significant differences between lean and obese mice. Surprisingly, the expression of genes normally associated with adipocyte differentiation were down-regulated in obesity. Not all obese individuals will become diabetic; many remain normoglycemic despite profound obesity. Understanding the transition to obesity with concomitant diabetes will provide important clues to the pathogenesis of type 2 diabetes. Therefore, we examined the levels of gene expression in adipose tissue from five groups of obese mice with varying degrees of hyperglycemia, and we identified 88 genes whose expression strongly correlated with diabetes severity. This group included many genes that are known to be involved in signal transduction and energy metabolism as well as genes not previously examined in the context of diabetes. Our data show that a decrease in expression of genes normally involved in adipogenesis is associated with obesity, and we further identify genes important for subsequent development of type 2 diabetes mellitus.

Magnetic resonance imaging procedures to study the concurrent anatomic development of vocal tract structures: preliminary results

The vocal tract structures undergo drastic anatomic restructuring during the course of development from infancy to adulthood. This study demonstrates the feasibility of using MRI to examine the growth processes of the vocal tract. This method affords precise and detailed visualization of the soft tissues in the oro-pharyngeal region, while also providing images of related bony and cartilaginous structures. Information on anatomic restructuring contributes to the understanding of how speech emerges and develops, and it also establishes normative information that can be used in the assessment of developmental anomalies. This paper describes the method used to measure and examine the concurrent anatomic development of the various vocal tract structures during early childhood. Preliminary results from two pediatric subjects indicate that there is synchrony of growth in the different structures-both soft and hard tissues-, and that such synchronous growth appears to persist during periods of growth spurts.

An estimation method for the semiparametric mixed effects model

A semiparametric mixed effects regression model is proposed for the analysis of clustered or longitudinal data with continuous, ordinal, or binary outcome. The common assumption of Gaussian random effects is relaxed by using a predictive recursion method (Newton and Zhang, 1999) to provide a nonparametric smooth density estimate. A new strategy is introduced to accelerate the algorithm. Parameter estimates are obtained by maximizing the marginal profile likelihood by Powell's conjugate direction search method. Monte Carlo results are presented to show that the method can improve the mean squared error of the fixed effects estimators when the random effects distribution is not Gaussian. The usefulness of visualizing the random effects density itself is illustrated in the analysis of data from the Wisconsin Sleep Survey. The proposed estimation procedure is computationally feasible for quite large data sets.

Half tetrad analysis in alfalfa using multiple restriction fragment length polymorphism markers

A maximum likelihood approach of half tetrad analysis (HTA) based on multiple restriction fragment length polymorphism (RFLP) markers was developed. This procedure estimates the relative frequencies of 2n gametes produced by mechanisms genetically equivalent to first division restitution (FDR) or second division restitution and simultaneously locates the centromere within a linkage group of RFLP marker loci. The method was applied to the diploid alfalfa clone PG-F9 (2n = 2x = 16) previously selected because of its high frequency of 2n egg production. HTA was based on four RFLP loci for which PG-F9 was heterozygous with codominant alleles that were absent in the tetraploid tester. Models including three linked and one unlinked RFLP loci were developed and tested. Results of the HTA showed that PG-F9 produced 6% FDR and 94% second division restitution 2n eggs. Information from a marker locus belonging to one linkage group was used to more precisely locate the centromere on a different linkage group. HTA, together with previous cytological analysis, indicated that in PG-F9, FDR 2n eggs are likely produced by diplospory, a mechanism common among apomictic species. The occurrence of FDR 2n eggs in plant species and their importance for crop evolution and breeding is discussed together with the potential applicability of multilocus HTA in the study of reproductive mutants.

A bayesian approach to detect quantitative trait loci using Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) techniques are applied to simultaneously identify multiple quantitative trait loci (QTL) and the magnitude of their effects. Using a Bayesian approach a multi-locus model is fit to quantitative trait and molecular marker data, instead of fitting one locus at a time. The phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. Inference summaries for the locations of the QTL and their effects are derived from the corresponding marginal posterior densities obtained by integrating the likelihood, rather than by optimizing the joint likelihood surface. This is done using MCMC by treating the unknown QTL, genotypes, and any missing marker genotypes, as augmented data and then by including these unknowns in the Markov chain cycle alone with the unknown parameters. Parameter estimates are obtained as means of the corresponding marginal posterior densities. High posterior density regions of the marginal densities are obtained as confidence regions. We examine flowering time data from double haploid progeny of Brassica napus to illustrate the proposed method.

Mapping loci controlling vernalization requirement and flowering time in Brassica napus

Rapeseed cultivars (Brassica napus L.) can be classified into annual and biennial groups according to their requirement for vernalization in order to induce flowering. The genetic control of these phenotypic differences is not well understood, but this information could be valuable for the design of breeding approaches to accelerate rapeseed improvement. In order to map loci controlling this variation, a doubled haploid population, derived from a cross between annual and biennial cultivars, was evaluated for vernalization requirement and days-to-flowering in a replicated field experiment using three treatments: no vernalization, 4 weeks of vernalization and 8 weeks of vernalization. A linkage map of 132 RFLP loci was used to locate loci controlling these traits. Marker segregation in one region of linkage group 9 was strongly associated with the annual/biennial growth habit in the unvernalized treatment and with days-to-flowering in all three treatments. Two other regions with smaller effects on days-to-flowering were also identified.

The dilemma of negative analysis of variance estimators of intraclass correlation

At least two common practices exist when a negative variance component estimate is obtained, either setting it to zero or not reporting the estimate. The consequences of these practices are investigated in the context of the intraclass correlation estimation in terms of bias, variance and mean squared error (MSE). For the one-way analysis of variance random effects model and its extension to the common correlation model, we compare five estimators: analysis of variance (ANOVA), concentrated ANOVA, truncated ANOVA and two maximum likelihood-like (ML) estimators. For the balanced case, the exact bias and MSE are calculated via numerical integration of the exact sample distributions, while a Monte Carlo simulation study is conducted for the unbalanced case. The results indicate that the ANOVA estimator performs well except for designs with family size n = 2. The two ML estimators are generally poor, and the concentrated and truncated ANOVA estimators have some advantages over the ANOVA in terms of MSE. However, the large biases may make the concentrated and truncated ANOVA estimators objectionable when intraclass correlation (ϱ) is small. Bias should be a concern when a pooled estimate is obtained from the literature since ϱ<0.05 in many genetic studies.

Bias of maximum likelihood estimator of intraclass correlation

A bias correction was derived for the maximum likelihood estimator (MLE) of the intraclass correlation. The bias consisted of two parts: a correction from MLE to the analysis of variance estimator (ANOVA) and the bias of ANOVA. The total possible bias was always negative and depended upon both the degree of correlation and the design size and balance. The first part of the bias was an exact algebraic expression from MLE to ANOVA, and the corrected estimator by this part was ANOVA. It was also shown that the first correction term was equivalent to Fisher's reciprocal bias correction on hisZ scores. The total possible bias of MLE was large for small and moderate samples. Relative biases were larger for small parametric values and vice versa. To ensure a relative bias less than 10% assuming an intraclass correlation of 0.025, which is not unusual in most of the animal genetic studies, the total number of observations (N) should be not less than 500. From a design point of view, minimum bias occurred atn = 2, the minimum family size possible, underN fixed.

Modeling the effects of light, carbon dioxide, and temperature on the growth of potato

This study examined the effects of light, temperature and carbon dioxide on the growth of potato (Solanum tuberosum L.) in a controlled environment in order to ascertain the best growing conditions for potato in life support systems in space. 'Norland' and 'Russet Burbank' were grown in 6-L pots of peat-vermiculite for 56 d in growth chambers at the University of Wisconsin Biotron. Environmental factor levels included continuous light (24-h photoperiod) at 250, 400, and 550 micromoles m-2 s-1 PPF; constant temperature at 16, 20, and 24 degrees C; and CO2 at approximately 400, 1000, and 1600 microliters L-1. Separate effects analysis and ridge analysis provided a means to examine the effects of individual environmental factors and to determine combinations of factors that are expected to give the best increases in yields over the central design point. The response surface of Norland indicated that tuber yields were highest with moderately low temperature (18.7 degrees C), low CO2 (400 microliters L-1) and high light (550 micromoles m-2 s-1 PPF). These conditions also favored shorter stem growth. Russet Burbank tuber yields were highest at moderately low temperature (17.5 degrees C), high CO2 (1600 microliters L-1) and medium analyses will be used to project the most efficient conditions for growth of potatoes in closed ecological life support systems (CELSS) in space colonies.

Bean arcelin : 1. Inheritance of a novel seed protein of Phaseolus vulgaris L. and its effect on seed composition

SDS-PAGE of seed proteins from the seeds of a nondomesticated bean of Mexican origin (Phaseolus vulgaris L., PI 325690) revealed the presence of a novel 38 kd protein which appeared to be neither an altered phaseolin nor a lectin fraction. The protein was named arcelin, after Arcelia, the town in the state of Guerrero near which PI 325690 had been collected. The pure line, UW 325, was derived by self fertilization of the plant from a single arcelin-containing seed of PI 325690. Despite a low percentage seed phaseolin (14.6%), seed phenotype, seed germination, plant growth, pollen fertility, and percentage seed protein of UW 325 were normal. Analyses of F2 and F3 seeds from a single F1 plant of the cross 'Sanilac'XPI 325690-3 revealed that arcelin expression was inherited as a single gene and that presence was dominant to absence of arcelin. The mean percentage phaseolin in the seeds of homozygous dominant Arc/Arc F3 families (14.0%) was significantly lower than that of the homozygous recessive arc/arc seeds (44.7%). The distribution of percentage phaseolin values for seeds within segregating families was bimodal and nonoverlapping. Without exception, seeds containing arcelin (Arc+phenotype) contained a lower percentage phaseolin than seeds lacking arcelin (Arc-phenotype). Although arcelin presence was associated with low percentage phaseolin, the Arc/Arc and Arc/arc genotypes were similar for seed weight and percentage total seed protein.

Effect of stage of lactation on transport of colloidal carbon or Staphylococcus aureus from the mammary gland lumen to lymph nodes in guinea pigs

Guinea pig mammary glands which were either lactating, involuting or dry were infused with colloidal carbon or killed staphylococci. At different time intervals following infusion, animals were killed and the superficial inguinal lymph nodes examined for the presence of carbon. Sides which had nodes with visible carbon were designated 'positive'. The time intervals from infusion to positive for the three groups were compared using logistic regression. The times required for 50% of the sides to be positive were estimated to be approximately 4 h for lactating glands, 32 h for those in involution, and 13 min for dry glands. Histological differences in distribution of carbon in the mammary tissue suggest that differences in transit time may have been due to different mechanisms of transport through the glands in the three different physiological states. The distribution of bacteria was similar to that of the carbon in the corresponding tissues.