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.S tearoyl-CoA desaturase (SCD) is the rate-limiting enzyme in the biosynthesis of monounsaturated fatty acids. It catalyzes the introduction of the cis double bond in the ⌬9 position of fatty acyl-CoA substrates. The preferred desaturation substrates are palmitoyl-CoA and stearoyl-CoA, which are converted to palmitoleoyl-CoA (16:1) and oleoyl-CoA (18:1), respectively (1-4). These fatty acids are requisite components of membrane phospholipids, triglycerides, cholesterol esters, and wax esters (5-7). Effects on composition of phospholipids ultimately determine membrane fluidity, and the effects on the composition of cholesterol esters and triglycerides can affect lipoprotein metabolism and adiposity. SCD expression is sensitive to dietary factors including polyunsaturated fatty acids, cholesterol and vitamin A, hormonal changes (i.e., insulin and glucagon), developmental processes, temperature changes, thiazolinediones, metals, alcohol, peroxisomal proliferators, and phenolic compounds (3). High SCD activity has been implicated in a wide range of disorders including diabetes, atherosclerosis, cancer, obesity, and viral infection (3,(8)(9)(10)(11)(12)(13).The existence of multiple SCD isoforms in mice (6, 14-18) and rats makes it difficult to determine the role of each isoform in lipid metabolism. New insights into the physiological role of the SCD1 gene and its endogenous products came from recent studies of the asebia mouse strains (ab j and ab 2j ) that have naturally occurring mutations in SCD1 (17-19) as well as a laboratory mouse model with a targeted disruption (SCD1Ϫ͞Ϫ) (6). We used these animal models to show that SCD1Ϫ͞Ϫ mice are deficient in hepatic triglycerides and cholesterol esters (7,20). The levels of palmitoleate (16:1) and oleate (18:1) are reduced, whereas palmitate and stearate are increased in the lipid fractions of SCD1Ϫ͞Ϫ mice. On a high carbohydrate diet supplemented with triolein, the cholesterol ester levels are corrected but the triglyceride levels are not reversed to the ...

DNA microarrays provide for unprecedented large-scale views of gene expression and, as a result, have emerged as a fundamental measurement tool in the study of diverse biological systems. Statistical questions abound, but many traditional data analytic approaches do not apply, in large part because thousands of individual genes are measured with relatively little replication. Empirical Bayes methods provide a natural approach to microarray data analysis because they can significantly reduce the dimensionality of an inference problem while compensating for relatively few replicates by using information across the array. We propose a general empirical Bayes modelling approach which allows for replicate expression profiles in multiple conditions. The hierarchical mixture model accounts for differences among genes in their average expression levels, differential expression for a given gene among cell types, and measurement fluctuations. Two distinct parameterizations are considered: a model based on Gamma distributed measurements and one based on log-normally distributed measurements. False discovery rate and related operating characteristics of the methodology are assessed in a simulation study. We also show how the posterior odds of differential expression in one version of the model is related to the ratio of the arithmetic mean to the geometric mean of the two sample means. The methodology is used in a study of mammary cancer in the rat, where four distinct patterns of expression are possible.

In a microarray experiment, messenger RNA samples are oftentimes pooled across subjects out of necessity, or in an effort to reduce the effect of biological variation. A basic problem in such experiments is to estimate the nominal expression levels of a large number of genes. Pooling samples will affect expression estimation, but the exact effects are not yet known as the approach has not been systematically studied in this context. We consider how mRNA pooling affects expression estimates by assessing the finite-sample performance of different estimators for designs with and without pooling. Conditions under which it is advantageous to pool mRNA are defined; and general properties of estimates from both pooled and non-pooled designs are derived under these conditions. A formula is given for the total number of subjects and arrays required in a pooled experiment to obtain gene expression estimates and confidence intervals comparable to those obtained from the no-pooling case. The formula demonstrates that by pooling a perhaps increased number of subjects, one can decrease the number of arrays required in an experiment without a loss of precision. The assumptions that facilitate derivation of this formula are considered using data from a quantitative real-time PCR experiment. The calculations are not specific to one particular method of quantifying gene expression as they assume only that a single, normalized, estimate of expression is obtained for each gene. As such, the results should be generally applicable to a number of technologies provided sufficient pre-processing and normalization methods are available and applied.