Fibroblast growth factor 21 (FGF21) mitigates many of the pathogenic features of type 2 diabetes, despite a short circulating half-life. PEGylation is a proven approach to prolonging the duration of action while enhancing biophysical solubility and stability. However, in the absence of a specific protein PEGylation site, chemical conjugation is inherently heterogeneous and commonly leads to dramatic loss in bioactivity. This work illustrates a novel means of specific PEGylation, producing FGF21 analogs with high specific activity and salutary biological activities. Using homology modeling and structure-based design, specific sites were chosen in human FGF21 for site-specific PEGylation to ensure that receptor binding regions were preserved. The in vitro activity of the PEGylated FGF21 ana-logs corresponded with the site of PEG placement within the binding model. Site-specific PEGylated analogs demonstrated dramatically increased circulating half-life and enhanced efficacy in db/db mice. Twice-weekly dosing of an optimal FGF21 analog reduced blood glucose, plasma lipids, liver triglycerides, and plasma glucagon and enhanced pancreatic insulin content, islet number, and glucose-dependent insulin secretion. Restoration of insulin sensitivity was demonstrated by the enhanced ability of insulin to induce Akt/protein kinase B phosphorylation in liver, muscle, and adipose tissues. PEGylation of human FGF21 at a specific and preferred site confers superior metabolic pharmacology.

Hyperglucagonemia is implicated in the pathophysiology of hyperglycemia. Antagonism of the glucagon receptor (GCGR) thus represents a potential approach to diabetes treatment. Herein we report the characterization of GRA1, a novel small-molecule GCGR antagonist that blocks glucagon binding to the human GCGR (hGCGR) and antagonizes glucagon-induced intracellular accumulation of cAMP with nanomolar potency. GRA1 inhibited glycogenolysis dose-dependently in primary human hepatocytes and in perfused liver from hGCGR mice, a transgenic line of mouse that expresses the hGCGR instead of the murine GCGR. When administered orally to hGCGR mice and rhesus monkeys, GRA1 blocked hyperglycemic responses to exogenous glucagon. In several murine models of diabetes, acute and chronic dosing with GRA1 significantly reduced blood glucose concentrations and moderately increased plasma glucagon and glucagon-like peptide-1. Combination of GRA1 with a dipeptidyl peptidase-4 inhibitor had an additive antihyperglycemic effect in diabetic mice. Hepatic gene-expression profiling in monkeys treated with GRA1 revealed down-regulation of numerous genes involved in amino acid catabolism, an effect that was paralleled by increased amino acid levels in the circulation. In summary, GRA1 is a potent glucagon receptor antagonist with strong antihyperglycemic efficacy in preclinical models and prominent effects on hepatic gene-expression related to amino acid metabolism.

We present a comprehensive map of over 1 million polyadenylation sites and quantify their usage in major cancers and tumor cell lines using direct RNA sequencing. We built the Expression and Polyadenylation Database to enable the visualization of the polyadenylation maps in various cancers and to facilitate the discovery of novel genes and gene isoforms that are potentially important to tumorigenesis. Analyses of polyadenylation sites indicate that a large fraction (∼30%) of mRNAs contain alternative polyadenylation sites in their 3′ untranslated regions, independent of the cell type. The shortest 3′ untranslated region isoforms are preferentially upregulated in cancer tissues, genome-wide. Candidate targets of alternative polyadenylation-mediated upregulation of short isoforms include POLR2K, and signaling cascades of cell–cell and cell–extracellular matrix contact, particularly involving regulators of Rho GTPases. Polyadenylation maps also helped to improve 3′ untranslated region annotations and identify candidate regulatory marks such as sequence motifs, H3K36Me3 and Pabpc1 that are isoform dependent and occur in a position-specific manner. In summary, these results highlight the need to go beyond monitoring only the cumulative transcript levels for a gene, to separately analysing the expression of its RNA isoforms.

Deep sequencing studies frequently identify small RNA fragments of abundant RNAs. These fragments are thought to represent degradation products of their precursors. Using sequencing, computational analysis, and sensitive northern blot assays, we show that constitutively expressed non-coding RNAs such as tRNAs, snoRNAs, rRNAs and snRNAs preferentially produce small 5′ and 3′ end fragments. Similar to that of microRNA processing, these terminal fragments are generated in an asymmetric manner that predominantly favors either the 5′ or 3′ end. Terminal-specific and asymmetric processing of these small RNAs occurs in both mouse and human cells. In addition to the known processing of some 3′ terminal tRNA-derived fragments (tRFs) by the RNase III endonuclease Dicer, we show that several RNase family members can produce tRFs, including Angiogenin that cleaves the TψC loop to generate 3′ tRFs. The 3′ terminal tRFs but not the 5′ tRFs are highly complementary to human endogenous retroviral sequences in the genome. Despite their independence from Dicer processing, these tRFs associate with Ago2 and are capable of down regulating target genes by transcript cleavage in vitro. We suggest that endogenous 3′ tRFs have a role in regulating the unwarranted expression of endogenous viruses through the RNA interference pathway.

Background

Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions.

Results

The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels.

Conclusions

This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.

In eukaryotic cells the final maturation of ribosomes occurs in the cytoplasm, where trans-acting factors are removed and critical ribosomal proteins are added for functionality. Here, we have carried out a comprehensive analysis of cytoplasmic maturation, ordering the known steps into a coherent pathway. Maturation is initiated by the ATPase Drg1. Downstream, assembly of the ribosome stalk is essential for the release of Tif6. The stalk recruits GTPases during translation. Because the GTPase Efl1, which is required for the release of Tif6, resembles the translation elongation factor eEF2, we suggest that assembly of the stalk recruits Efl1, triggering a step in 60S biogenesis that mimics aspects of translocation. Efl1 could thereby provide a mechanism to functionally check the nascent subunit. Finally, the release of Tif6 is a prerequisite for the release of the nuclear export adapter Nmd3. Establishing this pathway provides an important conceptual framework for understanding ribosome maturation.

Recently identified small (20 to 40 bases) RNAs, such as microRNAs (miRNAs) and endogenous small interfering RNAs (siRNAs) participate in important cellular pathways. In this report, we systematically characterized several novel features of human and viral RNA products smaller than miRNAs. We found that Kaposi sarcoma-associated herpesvirus K12-1 miRNA (23 bases) associates with a distinct, unusually small (17-base) RNA (usRNA) that can effectively downregulate a K12-1 miRNA target, human RAD21, suggesting that stable degradation-like products may also contribute to gene regulation. High-throughput sequencing reveals a diverse set of human miRNA-derived usRNAs and other non-miRNA-derived usRNAs. Human miRNA-derived usRNAs preferentially match to 5′ ends of miRNAs and are also more likely to associate with the siRNA effector protein Ago2 than with Ago1. Many non-miRNA-derived usRNAs associate with Ago proteins and also frequently contain C-rich 3′-specific motifs that are overrepresented in comparison to Piwi-interacting RNAs and transcription start site-associated RNAs. We postulate that approximately 30% of usRNAs could have evolved to participate in biological processes, including gene silencing.

In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper.

The step by step assembly process from preribosome in the nucleus to translation-competent 60S ribosome subunit in the cytoplasm is revealed (also see Kemmler et al. in this issue).

The ribosome stalk is essential for recruitment of translation factors. In yeast, P0 and Rpl12 correspond to bacterial L10 and L11 and form the stalk base of mature ribosomes, whereas Mrt4 is a nuclear paralogue of P0. In this study, we show that the dual-specificity phosphatase Yvh1 is required for the release of Mrt4 from the pre-60S subunits. Deletion of YVH1 leads to the persistence of Mrt4 on pre-60S subunits in the cytoplasm. A mutation in Mrt4 at the protein–RNA interface bypasses the requirement for Yvh1. Pre-60S subunits associated with Yvh1 contain Rpl12 but lack both Mrt4 and P0. These results suggest a linear series of events in which Yvh1 binds to the pre-60S subunit to displace Mrt4. Subsequently, P0 loads onto the subunit to assemble the mature stalk, and Yvh1 is released. The initial assembly of the ribosome with Mrt4 may provide functional compartmentalization of ribosome assembly in addition to the spatial separation afforded by the nuclear envelope.

The continuing discoveries of potentially active small RNAs at an unprecedented rate using high-throughput sequencing have raised the need for methods that can reliably detect and quantitate the expression levels of small RNAs. Currently, northern blot is the most widely used method for validating small RNAs that are identified by methods such as high-throughput sequencing. We describe a new northern blot-based protocol (LED) for small RNA (∼15–40 bases) detection using digoxigenin (DIG)-labeled oligonucleotide probes containing locked nucleic acids (LNA) and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide for cross-linking the RNA to the membrane. LED generates clearly visible signals for RNA amounts as low as 0.05 fmol. This method requires as little as a few seconds of membrane exposure to outperform the signal intensity using overnight exposure of isotope-based methods, corresponding to ∼1000-fold improvement in exposure-time. In contrast to commonly used radioisotope-based methods, which require freshly prepared and hazardous probes, LED probes can be stored for at least 6 months, facilitate faster and more cost-effective experiments, and are more environmentally friendly. A detailed protocol of LED is provided in the Supplementary Data.

Gene networks are an efficient route for associating candidate genes with biological processes. Here, networks are used to discover more than 15 new genes for ribosomal subunit maturation, rRNA processing, and ribosomal export from the nucleus.

Biogenesis of ribosomes is an essential cellular process conserved across all eukaryotes and is known to require >170 genes for the assembly, modification, and trafficking of ribosome components through multiple cellular compartments. Despite intensive study, this pathway likely involves many additional genes. Here, we employ network-guided genetics—an approach for associating candidate genes with biological processes that capitalizes on recent advances in functional genomic and proteomic studies—to computationally identify additional ribosomal biogenesis genes. We experimentally evaluated >100 candidate yeast genes in a battery of assays, confirming involvement of at least 15 new genes, including previously uncharacterized genes (YDL063C, YIL091C, YOR287C, YOR006C/TSR3, YOL022C/TSR4). We associate the new genes with specific aspects of ribosomal subunit maturation, ribosomal particle association, and ribosomal subunit nuclear export, and we identify genes specifically required for the processing of 5S, 7S, 20S, 27S, and 35S rRNAs. These results reveal new connections between ribosome biogenesis and mRNA splicing and add >10% new genes—most with human orthologs—to the biogenesis pathway, significantly extending our understanding of a universally conserved eukaryotic process.

Author Summary

Ribosomes are the extremely complex cellular machines responsible for constructing new proteins. In eukaryotic cells, such as yeast, each ribosome contains more than 80 protein or RNA components. These complex machines must themselves be assembled by an even more complex machinery spanning multiple cellular compartments and involving perhaps 200 components in an ordered series of processing events, resulting in delivery of the two halves of the mature ribosome, the 40S and 60S components, to the cytoplasm. The ribosome biogenesis machinery has been only partially characterized, and many lines of evidence suggest that there are additional components that are still unknown. We employed an emerging computational technique called network-guided genetics to identify new candidate genes for this pathway. We then tested the candidates in a battery of experimental assays to determine what roles the genes might play in the biogenesis of ribosomes. This approach proved an efficient route to the discovery of new genes involved in ribosome biogenesis, significantly extending our understanding of a universally conserved eukaryotic process.

Motivation: Tandem mass spectrometry (MS/MS) offers fast and reliable characterization of complex protein mixtures, but suffers from low sensitivity in protein identification. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other information available, e.g. the probability of a protein's presence is likely to correlate with its mRNA concentration.

Results: We develop a Bayesian score that estimates the posterior probability of a protein's presence in the sample given its identification in an MS/MS experiment and its mRNA concentration measured under similar experimental conditions. Our method, MSpresso, substantially increases the number of proteins identified in an MS/MS experiment at the same error rate, e.g. in yeast, MSpresso increases the number of proteins identified by ∼40%. We apply MSpresso to data from different MS/MS instruments, experimental conditions and organisms (Escherichia coli, human), and predict 19–63% more proteins across the different datasets. MSpresso demonstrates that incorporating prior knowledge of protein presence into shotgun proteomics experiments can substantially improve protein identification scores.

Availability and Implementation: Software is available upon request from the authors. Mass spectrometry datasets and supplementary information are available from http://www.marcottelab.org/MSpresso/.

Contact: marcotte@icmb.utexas.edu; miranker@cs.utexas.edu

Supplementary Information: Supplementary data website: http://www.marcottelab.org/MSpresso/.

BUD23 was identified from a bioinformatics analysis of Saccharomyces cerevisiae genes involved in ribosome biogenesis. Deletion of BUD23 leads to severely impaired growth, reduced levels of the small (40S) ribosomal subunit, and a block in processing 20S rRNA to 18S rRNA, a late step in 40S maturation. Bud23 belongs to the S-adenosylmethionine-dependent Rossmann-fold methyltransferase superfamily and is related to small-molecule methyltransferases. Nevertheless, we considered that Bud23 methylates rRNA. Methylation of G1575 is the only mapped modification for which the methylase has not been assigned. Here, we show that this modification is lost in bud23 mutants. The nuclear accumulation of the small-subunit reporters Rps2-green fluorescent protein (GFP) and Rps3-GFP, as well as the rRNA processing intermediate, the 5′ internal transcribed spacer 1, indicate that bud23 mutants are defective for small-subunit export. Mutations in Bud23 that inactivated its methyltransferase activity complemented a bud23Δ mutant. In addition, mutant ribosomes in which G1575 was changed to adenosine supported growth comparable to that of cells with wild-type ribosomes. Thus, Bud23 protein, but not its methyltransferase activity, is important for biogenesis and export of the 40S subunit in yeast.

Regulation of cell cycle progression is fundamental to cell health and reproduction, and failures in this process are associated with many human diseases. Much of our knowledge of cell cycle regulators derives from loss-of-function studies. To reveal new cell cycle regulatory genes that are difficult to identify in loss-of-function studies, we performed a near-genome-wide flow cytometry assay of yeast gene overexpression-induced cell cycle delay phenotypes. We identified 108 genes whose overexpression significantly delayed the progression of the yeast cell cycle at a specific stage. Many of the genes are newly implicated in cell cycle progression, for example SKO1, RFA1, and YPR015C. The overexpression of RFA1 or YPR015C delayed the cell cycle at G2/M phases by disrupting spindle attachment to chromosomes and activating the DNA damage checkpoint, respectively. In contrast, overexpression of the transcription factor SKO1 arrests cells at G1 phase by activating the pheromone response pathway, revealing new cross-talk between osmotic sensing and mating. More generally, 92%–94% of the genes exhibit distinct phenotypes when overexpressed as compared to their corresponding deletion mutants, supporting the notion that many genes may gain functions upon overexpression. This work thus implicates new genes in cell cycle progression, complements previous screens, and lays the foundation for future experiments to define more precisely roles for these genes in cell cycle progression.

Author Summary

All cells require proper cell cycle regulation; failure leads to numerous human diseases. Cell cycle mechanisms are broadly conserved across eukaryotes, with many key regulatory genes known. Nonetheless, our knowledge of regulators is incomplete. Many classic studies have analyzed yeast loss-of-function mutants to identify cell cycle genes. Studies have also implicated genes based upon their overexpression phenotypes, but the effects of gene overexpression on the cell cycle have not been quantified for all yeast genes. We individually quantified the effect of overexpression on cell cycle progression for nearly all (91%) of yeast genes, and we report the 108 genes causing the most significant and reproducible cell cycle defects, most of which have not been previously observed. We characterize three genes in more detail, implicating one in chromosomal segregation and mitotic spindle formation. A second affects mitotic stability and the DNA damage checkpoint. Curiously, overexpression of a third gene, SKO1, arrests the cell cycle by activating the pheromone response pathway, with cells mistakenly behaving as if mating pheromone is present. These results establish a basis for future experiments elucidating precise cell cycle roles for these genes. Similar assays in human cells could help further clarify the many connections between cell cycle control and cancers.

The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. We report a set of 7000 physical associations among human proteins inferred from indirect evidence: the comparison of human mRNA co-expression patterns with those of orthologous genes in five other eukaryotes, which we demonstrate identifies proteins in the same physical complexes. To evaluate the accuracy of the predicted physical associations, we apply quantitative mass spectrometry shotgun proteomics to measure elution profiles of 3013 human proteins during native biochemical fractionation, demonstrating systematically that putative interaction partners tend to co-sediment. We further validate uncharacterized proteins implicated by the associations in ribosome biogenesis, including WBSCR20C, associated with Williams–Beuren syndrome. This meta-analysis therefore exploits non-protein-based data, but successfully predicts associations, including 5589 novel human physical protein associations, with measured accuracies of 54±10%, comparable to direct large-scale interaction assays. The new associations' derivation from conserved in vivo phenomena argues strongly for their biological relevance.

Background

Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations.

Methodology/Principal Findings

We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis.

Conclusions/Significance

YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.

miRNAs (microRNAs) are a class of endogenous small RNAs that are thought to negatively regulate protein production. Aberrant expression of many miRNAs is linked to cancer and other diseases. Little is known about the factors that regulate the expression of miRNAs. We have identified numerous regulatory elements upstream of miRNA genes that are likely to be essential to the transcriptional and posttranscriptional regulation of miRNAs. Newly identified regulatory motifs occur frequently and in multiple copies upstream of miRNAs. The motifs are highly enriched in G and C nucleotides, in comparison with the nucleotide composition of miRNA upstream sequences. Although the motifs were predicted using sequences that are upstream of miRNAs, we find that 99% of the top-predicted motifs preferentially occur within the first 500 nucleotides upstream of the transcription start sites of protein-coding genes; the observed preference in location underscores the validity and importance of the motifs identified in this study. Our study also raises the possibility that a considerable number of well-characterized, disease-associated transcription factors (TFs) of protein-coding genes contribute to the abnormal miRNA expression in diseases such as cancer. Further analysis of predicted miRNA–protein interactions lead us to hypothesize that TFs that include c-Myb, NF-Y, Sp-1, MTF-1, and AP-2α are master-regulators of miRNA expression. Our predictions are a solid starting point for the systematic elucidation of the causative basis for aberrant expression patterns of disease-related (e.g., cancer) miRNAs. Thus, we point out that focused studies of the TFs that regulate miRNAs will be paramount in developing cures for miRNA-related diseases. The identification of the miRNA regulatory motifs was facilitated by a new computational method, K-Factor. K-Factor predicts regulatory motifs in a set of functionally related sequences, without relying on evolutionary conservation.

Author Summary

microRNAs (miRNAs) are unusually small RNAs that are thought to control the production of proteins in the cell. Recent studies have linked miRNAs to several types of cancers. Several studies strongly suggest that miRNAs could be useful as diagnostic and prognostic markers of various cancers. Thus, although miRNAs appear to have opened up a new chapter in cancer biology, the fundamental question regarding why miRNAs are strongly associated with diseases such as cancer remain unclear. Here, we endeavored to systematically identify the factors that regulate miRNA biogenesis. We first identified a large number of DNA sequence elements that are characteristic of miRNA genes, using a new computational method named K-Factor. The sequence elements were then used to match known protein binding sites to identify specific proteins (transcription factors (TF)) that regulate miRNA biogenesis. Based on our observations, we put forward the hypothesis that a number of known TFs are primarily responsible for the aberrant regulation of miRNAs in cancer and other diseases.

The enzyme 11β–hydroxysteroid dehydrogenase (HSD) type 1 converts inactive cortisone into active cortisol in cells, thereby raising the effective glucocorticoid (GC) tone above serum levels. We report that pharmacologic inhibition of 11β-HSD1 has a therapeutic effect in mouse models of metabolic syndrome. Administration of a selective, potent 11β-HSD1 inhibitor lowered body weight, insulin, fasting glucose, triglycerides, and cholesterol in diet-induced obese mice and lowered fasting glucose, insulin, glucagon, triglycerides, and free fatty acids, as well as improved glucose tolerance, in a mouse model of type 2 diabetes. Most importantly, inhibition of 11β-HSD1 slowed plaque progression in a murine model of atherosclerosis, the key clinical sequela of metabolic syndrome. Mice with a targeted deletion of apolipoprotein E exhibited 84% less accumulation of aortic total cholesterol, as well as lower serum cholesterol and triglycerides, when treated with an 11β-HSD1 inhibitor. These data provide the first evidence that pharmacologic inhibition of intracellular GC activation can effectively treat atherosclerosis, the key clinical consequence of metabolic syndrome, in addition to its salutary effect on multiple aspects of the metabolic syndrome itself.

Effective therapies for the treatment of obesity, a key element of metabolic syndrome, are urgently needed but currently lacking. Stearoyl-CoA desaturase–1 (SCD1) is the rate-limiting enzyme catalyzing the conversion of saturated long-chain fatty acids into monounsaturated fatty acids, which are major components of triglycerides. In the current study, we tested the efficacy of pharmacological inhibition of SCD1 in controlling lipogenesis and body weight in mice. SCD1-specific antisense oligonucleotide inhibitors (ASOs) reduced SCD1 expression, reduced fatty acid synthesis and secretion, and increased fatty acid oxidization in primary mouse hepatocytes. Treatment of mice with SCD1 ASOs resulted in prevention of diet-induced obesity with concomitant reductions in SCD1 expression and the ratio of oleate to stearoyl-CoA in tissues and plasma. These changes correlated with reduced body adiposity, hepatomegaly and steatosis, and postprandial plasma insulin and glucose levels. Furthermore, SCD1 ASOs reduced de novo fatty acid synthesis, decreased expression of lipogenic genes, and increased expression of genes promoting energy expenditure in liver and adipose tissues. Thus, SCD1 inhibition represents a new target for the treatment of obesity and related metabolic disorders.