Biomedical subjects

Brian S Yandell

Publications and source records attributed to Brian S Yandell.

16 recordsLinked to original sources

PubMed2006

Abdominal obesity in BTBR male mice is associated with peripheral but not hepatic insulin resistance.

Insulin resistance is a common feature of obesity. BTBR mice have more fat mass than most other inbred mouse strains. On a chow diet, BTBR mice have elevated insulin levels relative to the C57BL/6J (B6) strain. Male F1 progeny of a B6 x BTBR cross are insulin resistant. Previously, we reported insulin resistance in isolated muscle and in isolated adipocytes in this strain. Whereas the muscle insulin resistance was observed only in male F1 mice, adipocyte insulin resistance was also present in male BTBR mice. We examined in vivo mechanisms of insulin resistance with the hyperinsulinemic euglycemic clamp technique. At 10 wk of age, BTBR and F1 mice had a >30% reduction in whole body glucose disposal primarily due to insulin resistance in heart, soleus muscle, and adipose tissue. The increased adipose tissue mass and decreased muscle mass in BTBR and F1 mice were negatively and positively correlated with whole body glucose disposal, respectively. Genes involved in focal adhesion, actin cytoskeleton, and inflammation were more highly expressed in BTBR and F1 than in B6 adipose tissue. The BTBR and F1 mice have higher levels of testosterone, which may be related to the pathological changes in adipose tissue that lead to systemic insulin resistance. Despite profound peripheral insulin resistance, BTBR and F1 mice retained hepatic insulin sensitivity. These studies reveal a genetic difference in body composition that correlates with large differences in peripheral insulin sensitivity.

Abdominal Fat↗

PubMed2006

Impact of nonsense-mediated mRNA decay on the global expression profile of budding yeast.

Nonsense-mediated mRNA decay (NMD) is a eukaryotic mechanism of RNA surveillance that selectively eliminates aberrant transcripts coding for potentially deleterious proteins. NMD also functions in the normal repertoire of gene expression. In Saccharomyces cerevisiae, hundreds of endogenous RNA Polymerase II transcripts achieve steady-state levels that depend on NMD. For some, the decay rate is directly influenced by NMD (direct targets). For others, abundance is NMD-sensitive but without any effect on the decay rate (indirect targets). To distinguish between direct and indirect targets, total RNA from wild-type (Nmd(+)) and mutant (Nmd(-)) strains was probed with high-density arrays across a 1-h time window following transcription inhibition. Statistical models were developed to describe the kinetics of RNA decay. 45% +/- 5% of RNAs targeted by NMD were predicted to be direct targets with altered decay rates in Nmd(-) strains. Parallel experiments using conventional methods were conducted to empirically test predictions from the global experiment. The results show that the global assay reliably distinguished direct versus indirect targets. Different types of targets were investigated, including transcripts containing adjacent, disabled open reading frames, upstream open reading frames, and those prone to out-of-frame initiation of translation. Known targeting mechanisms fail to account for all of the direct targets of NMD, suggesting that additional targeting mechanisms remain to be elucidated. 30% of the protein-coding targets of NMD fell into two broadly defined functional themes: those affecting chromosome structure and behavior and those affecting cell surface dynamics. Overall, the results provide a preview for how expression profiles in multi-cellular eukaryotes might be impacted by NMD. Furthermore, the methods for analyzing decay rates on a global scale offer a blueprint for new ways to study mRNA decay pathways in any organism where cultured cell lines are available.

Codon, Initiator↗

PubMed2006

Positional cloning of Sorcs1, a type 2 diabetes quantitative trait locus.

We previously mapped the type 2 diabetes mellitus-2 locus (T2dm2), which affects fasting insulin levels, to distal chromosome 19 in a leptin-deficient obese F2 intercross derived from C57BL/6 (B6) and BTBR T+ tf/J (BTBR) mice. Introgression of a 7-Mb segment of the B6 chromosome 19 into the BTBR background (strain 1339A) replicated the reduced insulin linked to T2dm2. The 1339A mice have markedly impaired insulin secretion in vivo and disrupted islet morphology. We used subcongenic strains derived from 1339A to localize the T2dm2 quantitative trait locus (QTL) to a 242-kb segment comprising the promoter, first exon and most of the first intron of the Sorcs1 gene. This was the only gene in the 1339A strain for which we detected amino acid substitutions and expression level differences between mice carrying B6 and BTBR alleles of this insert, thereby identifying variation within the Sorcs1 gene as underlying the phenotype associated with the T2dm2 locus. SorCS1 binds platelet-derived growth factor, a growth factor crucial for pericyte recruitment to the microvasculature, and may thus have a role in expanding or maintaining the islet vasculature. Our identification of the Sorcs1 gene provides insight into the pathway underlying the pathophysiology of obesity-induced type 2 diabetes mellitus.

Animals↗

PubMed2006

Combined expression trait correlations and expression quantitative trait locus mapping.

Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. The consideration of gene expression correlation over a time or tissue dimension has proved valuable in predicting gene function. Here, we consider correlations over a genetic dimension. In addition to identifying coregulated genes, the genetic dimension also supplies us with information about the genomic locations of putative regulatory loci. We calculated correlations among approximately 45,000 expression traits derived from 60 individuals in an F2 sample segregating for obesity and diabetes. By combining the correlation results with linkage mapping information, we were able to identify regulatory networks, make functional predictions for uncharacterized genes, and characterize novel members of known pathways. We found evidence of coordinate regulation of 174 G protein-coupled receptor protein signaling pathway expression traits. Of the 174 traits, 50 had their major LOD peak within 10 cM of a locus on Chromosome 2, and 81 others had a secondary peak in this region. We also characterized a Riken cDNA clone that showed strong correlation with stearoyl-CoA desaturase 1 expression. Experimental validation confirmed that this clone is involved in the regulation of lipid metabolism. We conclude that trait correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we studied only mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping alone.

Animals↗

PubMed2005

Bayesian model selection for genome-wide epistatic quantitative trait loci analysis.

The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and Metropolis-Hastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i.

Algorithms↗

PubMed2005

Development of vocal tract length during early childhood: a magnetic resonance imaging study.

Speech development in children is predicated partly on the growth and anatomic restructuring of the vocal tract. This study examines the growth pattern of the various hard and soft tissue vocal tract structures as visualized by magnetic resonance imaging (MRI), and assesses their relational growth with vocal tract length (VTL). Measurements on lip thickness, hard- and soft-palate length, tongue length, naso-oro-pharyngeal length, mandibular length and depth, and distance of the hyoid bone and larynx from the posterior nasal spine were used from 63 pediatric cases (ages birth to 6 years and 9 months) and 12 adults. Results indicate (a) ongoing growth of all oral and pharyngeal vocal tract structures with no sexual dimorphism, and a period of accelerated growth between birth and 18 months; (b) vocal tract structure's region (oral/anterior versus pharyngeal/posterior) and orientation (horizontal versus vertical) determine its growth pattern; and (c) the relational growth of the different structures with VTL changes with development-while the increase in VTL throughout development is predominantly due to growth of pharyngeal/posterior structures, VTL is also substantially affected by the growth of oral/anterior structures during the first 18 months of life. Findings provide normative data that can be used for modeling the development of the vocal tract.

Age Factors↗

PubMed2004

Gene expression analysis suggests that 1,25-dihydroxyvitamin D3 reverses experimental autoimmune encephalomyelitis by stimulating inflammatory cell apoptosis.

Multiple sclerosis (MS) is a debilitating autoimmune disease of the central nervous system (CNS) that develops in genetically susceptible individuals who are exposed to undefined environmental risk factors. Epidemiological, genetic, and biological evidence suggests that insufficient vitamin D may be an MS risk factor. However, little is known about how vitamin D might be protective in MS. We hypothesized that 1,25-dihydroxyvitamin D3 [1,25-(OH)2D3] might regulate gene expression patterns in a manner that would resolve inflammation. To test this hypothesis, experimental autoimmune encephalomyelitis (EAE) was induced in mice, 1,25-(OH)2D3 or a placebo was administered, and 6 h later, DNA microarray hybridization was performed with spinal cord RNA to analyze the gene expression patterns. At this time, clinical, histopathological, and biological studies showed that the two groups did not differ in EAE disease, but changes in several 1,25-(OH)2D3-responsive genes indicated that the 1,25-(OH)2D3 had reached the CNS. Compared with normal mice, placebo-treated mice with EAE showed increased expression of many immune system genes, confirming the acute inflammation. When 1,25-(OH)2D3 was administered, several genes like glial fibrillary acidic protein and eukaryotic initiation factor 2alpha kinase 4, whose expression increased or decreased with EAE, returned to homeostatic levels. Also, two genes with pro-apoptotic functions, calpain-2 and caspase-8-associated protein, increased significantly. A terminal deoxynucleotidyl transferase-mediated dUTP nicked end labeling study detected increased nuclear fragmentation in the 1,25-(OH)2D3-treated samples, confirming increased apoptosis. Together, these results suggest that sensitization of inflammatory cells to apoptotic signals may be one mechanism by which the 1,25-(OH)2D3 resolved EAE.

Animals↗

PubMed2004

Nonparametric estimation of the effects of quantitative trait loci.

Interval mapping of quantitative trait loci from breeding experiments plays an important role in understanding the mechanisms of disease, both in humans and other organisms. Standard approaches to estimation involve parametric assumptions for the component distributions and may be sensitive to model misspecification. Some nonparametric tests have been studied. However, nonparametric estimation of the phenotypic distributions has not been considered in the genetics literature, even though such methods might provide essential nonparametric summaries for comparing different loci. We develop a sufficient condition for identifiability of the phenotypic distributions. Simple nonparametric estimators for the distributions are proposed for uncensored and right censored data. They have a closed form and their small and large sample properties are readily established. Their practical utility as numerical summaries which complement nonparametric tests is demonstrated on two recent genetics examples.

Animals↗

PubMed2004

Selective phenotyping for increased efficiency in genetic mapping studies.

The power of a genetic mapping study depends on the heritability of the trait, the number of individuals included in the analysis, and the genetic dissimilarity among them. In experiments that involve microarrays or other complex physiological assays, phenotyping can be expensive and time-consuming and may impose limits on the sample size. A random selection of individuals may not provide sufficient power to detect linkage until a large sample size is reached. We present an algorithm for selecting a subset of individuals solely on the basis of genotype data that can achieve substantial improvements in sensitivity compared to a random sample of the same size. The selective phenotyping method involves preferentially selecting individuals to maximize their genotypic dissimilarity. Selective phenotyping is most effective when prior knowledge of genetic architecture allows us to focus on specific genetic regions. However, it can also provide modest improvements in efficiency when applied on a whole-genome basis. Importantly, selective phenotyping does not reduce the efficiency of mapping as compared to a random sample in regions that are not considered in the selection process. In contrast to selective genotyping, inferences based solely on a selectively phenotyped population of individuals are representative of the whole population. The substantial improvement introduced by selective phenotyping is particularly useful when phenotyping is difficult or costly and thus limits the sample size in a genetic mapping study.

Animals↗

PubMed2004

Distinguishing covariation from causation in diabetes: a lesson from the protein disulfide isomerase mRNA abundance trait.

Protein disulfide isomerase (Pdi) is reported to be an insulin-regulated gene whose expression level is increased in the livers of rats with streptozotocin-induced diabetes. We found that Pdi mRNA is approximately 20-fold more abundant in the diabetes-susceptible BTBR mouse strain relative to the diabetes-resistant C56BL/6 (B6) strain. A genetic analysis was carried out to determine whether there is a causal relationship between elevated Pdi expression and diabetes phenotype in BTBR-ob/ob mice. We mapped Pdi mRNA abundance as a quantitative trait in 108 (B6 x BTBR)F(2)-ob/ob mice segregating for diabetes. We detected a single linkage at the telomeric end of chromosome 11, where the Pdi gene itself resides (logarithm of odds score >30.0). No linkage was detected for the Pdi mRNA trait in the regions where we have previously identified quantitative trait loci for diabetes traits. Sequencing of the Pdi promoter and cDNA revealed several single nucleotide polymorphisms between these two mouse strains. We conclude that in our experimental model, elevated Pdi expression is cis regulated and is not linked to diabetes susceptibility. Genetic analysis is a powerful tool for distinguishing covariation from causation in expression array studies of disease traits.

Animals↗

PubMed2004

Identification of major quantitative trait loci controlling body weight variation in ob/ob mice.

The adipocyte hormone leptin constitutes an important component of the regulation of energy homeostasis; leptin-deficient animals, such as obese mice, are strikingly overweight. The seemingly uninhibited weight gain in obese mice belies the fact that control of energy homeostasis remains under precise, heritably modifiable control. Herein, we report large, heritable differences in body weight and food intake between BTBR-ob/ob and B6-ob/ob mice. We have identified two loci, called modifier of obese (Moo1 and Moo2), that explain the majority of the heritable variance in (BTBR x B6) F(2)-ob/ob mice. Using interval-specific congenic mouse lines, we mapped Moo1 to an 8-Mb segment of chromosome 2 and demonstrated that Moo1 exerts its effects primarily by regulating total fat mass. Although null alleles of leptin are rare, the majority of overweight adults are leptin resistant, suggesting that leptin-independent pathways, such as those studied here, are important regulators of energy homeostasis. Thus, the identification of these loci may provide important new insights into the pathogenesis of human obesity.

Aging↗

PubMed2003

Dimension reduction for mapping mRNA abundance as quantitative traits.

The advent of sophisticated genomic techniques for gene mapping and microarray analysis has provided opportunities to map mRNA abundance to quantitative trait loci (QTL) throughout the genome. Unfortunately, simple mapping of each individual mRNA trait on the scale of a typical microarray experiment is computationally intensive, subject to high sample variance, and therefore underpowered. However, this problem can be addressed by capitalizing on correlation among the large number of mRNA traits. We present a method to reduce the dimensionality for mapping gene expression data as quantitative traits. We used a blind method, principal components, and a sighted method, hierarchical clustering seeded by disease relevant traits, to define new traits composed of a small collection of promising mRNAs. We validated the principle of our approach by mapping the expression levels of metabolism genes in a population of F(2)-ob/ob mice derived from the BTBR and C57BL/6J strains. We found that lipogenic and gluconeogenic mRNAs, which are known targets of insulin action, were closely associated with the insulin trait. Multiple interval mapping and Bayesian interval mapping of this new trait revealed significant linkages to chromosome regions that were contained in loci associated with type 2 diabetes in this same mouse sample. As a further statistical refinement, we show that principal component analysis also effectively reduced dimensions for mapping phenotypes composed of mRNA abundances.

Animals↗

PubMed2003

Rank-based statistical methodologies for quantitative trait locus mapping.

This article addresses the identification of genetic loci (QTL and elsewhere) that influence nonnormal quantitative traits with focus on experimental crosses. QTL mapping is typically based on the assumption that the traits follow normal distributions, which may not be true in practice. Model-free tests have been proposed. However, nonparametric estimation of genetic effects has not been studied. We propose an estimation procedure based on the linear rank test statistics. The properties of the new procedure are compared with those of traditional likelihood-based interval mapping and regression interval mapping via simulations and a real data example. The results indicate that the nonparametric method is a competitive alternative to the existing parametric methodologies.

Crosses, Genetic↗

PubMed2003

Gene expression profiles of nondiabetic and diabetic obese mice suggest a role of hepatic lipogenic capacity in diabetes susceptibility.

Obesity is a strong risk factor for the development of type 2 diabetes. We have previously reported that in adipose tissue of obese (ob/ob) mice, the expression of adipogenic genes is decreased. When made genetically obese, the BTBR mouse strain is diabetes susceptible and the C57BL/6J (B6) strain is diabetes resistant. We used DNA microarrays and RT-PCR to compare the gene expression in BTBR-ob/ob versus B6-ob/ob mice in adipose tissue, liver, skeletal muscle, and pancreatic islets. Our results show: 1) there is an increased expression of genes involved in inflammation in adipose tissue of diabetic mice; 2) lipogenic gene expression was lower in adipose tissue of diabetes-susceptible mice, and it continued to decrease with the development of diabetes, compared with diabetes-resistant obese mice; 3) hepatic expression of lipogenic enzymes was increased and the hepatic triglyceride content was greatly elevated in diabetes-resistant obese mice; 4) hepatic expression of gluconeogenic genes was suppressed at the prediabetic stage but not at the onset of diabetes; and 5) genes normally not expressed in skeletal muscle and pancreatic islets were expressed in these tissues in the diabetic mice. We propose that increased hepatic lipogenic capacity protects the B6-ob/ob mice from the development of type 2 diabetes.

Adipose Tissue↗

PubMed2002

Loss of stearoyl-CoA desaturase-1 function protects mice against adiposity.

Stearoyl-CoA desaturase (SCD) is a central lipogenic enzyme catalyzing the synthesis of monounsaturated fatty acids, mainly oleate (C18:1) and palmitoleate (C16:1), which are components of membrane phospholipids, triglycerides, wax esters, and cholesterol esters. Several SCD isoforms (SCD1-3) exist in the mouse. Here we show that mice with a targeted disruption of the SCD1 isoform have reduced body adiposity, increased insulin sensitivity, and are resistant to diet-induced weight gain. The protection from obesity involves increased energy expenditure and increased oxygen consumption. Compared with the wild-type mice the SCD1-/- mice have increased levels of plasma ketone bodies but reduced levels of plasma insulin and leptin. In the SCD1-/- mice, the expression of several genes of lipid oxidation are up-regulated, whereas lipid synthesis genes are down-regulated. These observations suggest that a consequence of SCD1 deficiency is an activation of lipid oxidation in addition to reduced triglyceride synthesis and storage.

Adipose Tissue↗

PubMedDate not supplied

A Bayesian approach for constructing genetic maps when markers are miscoded.

The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

Bayes Theorem↗