Variations in DNA elucidate molecular networks that cause disease

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.     

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?相似文献   

Regulation of circadian behaviour and metabolism by synthetic REV-ERB agonists

Synchronizing rhythms of behaviour and metabolic processes is important for cardiovascular health and preventing metabolic diseases. The nuclear receptors REV-ERB-α and REV-ERB-β have an integral role in regulating the expression of core clock proteins driving rhythms in activity and metabolism. Here we describe the identification of potent synthetic REV-ERB agonists with in vivo activity. Administration of synthetic REV-ERB ligands alters circadian behaviour and the circadian pattern of core clock gene expression in the hypothalami of mice. The circadian pattern of expression of an array of metabolic genes in the liver, skeletal muscle and adipose tissue was also altered, resulting in increased energy expenditure. Treatment of diet-induced obese mice with a REV-ERB agonist decreased obesity by reducing fat mass and markedly improving dyslipidaemia and hyperglycaemia. These results indicate that synthetic REV-ERB ligands that pharmacologically target the circadian rhythm may be beneficial in the treatment of sleep disorders as well as metabolic diseases.     

Ecology drives a global network of gene exchange connecting the human microbiome

Horizontal gene transfer (HGT), the acquisition of genetic material from non-parental lineages, is known to be important in bacterial evolution. In particular, HGT provides rapid access to genetic innovations, allowing traits such as virulence, antibiotic resistance and xenobiotic metabolism to spread through the human microbiome. Recent anecdotal studies providing snapshots of active gene flow on the human body have highlighted the need to determine the frequency of such recent transfers and the forces that govern these events. Here we report the discovery and characterization of a vast, human-associated network of gene exchange, large enough to directly compare the principal forces shaping HGT. We show that this network of 10,770 unique, recently transferred (more than 99% nucleotide identity) genes found in 2,235 full bacterial genomes, is shaped principally by ecology rather than geography or phylogeny, with most gene exchange occurring between isolates from ecologically similar, but geographically separated, environments. For example, we observe 25-fold more HGT between human-associated bacteria than among ecologically diverse non-human isolates (P = 3.0 × 10(-270)). We show that within the human microbiome this ecological architecture continues across multiple spatial scales, functional classes and ecological niches with transfer further enriched among bacteria that inhabit the same body site, have the same oxygen tolerance or have the same ability to cause disease. This structure offers a window into the molecular traits that define ecological niches, insight that we use to uncover sources of antibiotic resistance and identify genes associated with the pathology of meningitis and other diseases.     

Dissecting the architecture of a quantitative trait locus in yeast

Most phenotypic diversity in natural populations is characterized by differences in degree rather than in kind. Identification of the actual genes underlying these quantitative traits has proved difficult. As a result, little is known about their genetic architecture. The failures are thought to be due to the different contributions of many underlying genes to the phenotype and the ability of different combinations of genes and environmental factors to produce similar phenotypes. This study combined genome-wide mapping and a new genetic technique named reciprocal-hemizygosity analysis to achieve the complete dissection of a quantitative trait locus (QTL) in Saccharomyces cerevisiae. A QTL architecture was uncovered that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient in isolation. This arrangement of alleles explains heterosis (hybrid vigour), the increased fitness of the heterozygote compared with homozygotes. It also demonstrates a deficiency in current approaches to QTL dissection with implications extending to traits in other organisms, including human genetic diseases.     

Differential expression analysis and regulatory network reconstruction for genes associated with muscle growth and adipose deposition in obese and lean pigs

During the growth and development of skeletal muscle cells and adipose cells, the regulatory mechanism of micro-effect polygenes determines porcine meat quality, carcass characteristics and other relative quantitative traits. Obese and lean type pig breeds show obvious differences in muscle growth and adipose deposition; however, the molecular mechanism underlying this phenotypic variation remains unknown. We used pathway-focused oligo microarray studies to examine the expression changes of 140 genes associated with muscle growth and adipose deposition in longissimus dorsi muscle at six growth stages （birth, 1, 2, 3, 4 and 5 months） of Landrace （a leaner, Western breed） and Taihu pigs （a fatty, indigenous, Chinese breed）. Variance analysis （ANOVA） revealed that differences in the expression of 18 genes in Landrace pigs and three genes in Taihu pigs were very significant （FDR-adjusted permutation, P 〈 0.01） and differences for 22 genes in Landrace pigs and seven genes in Taihu pigs were significant （FDR-adjusted permutation, P 〈 0.05） among six growth stages. Clustering analysis revealed a high level of significance （FDR-adjusted, P 〈 0.01） for four gene expression patterns, in which genes that strongly up-regulated were mainly associated with the positive regulation of myofiber formation and fatty acid biogenesis and genes that strongly down-regulated were mainly associated with the inhibition of cell proliferation and positive regulation of fatty acid β-oxidation. Based on a dynamic Bayesian network （DBN） model, gene regulatory networks （GRNs） were reconstructed from time-series data for each pig breed. These two GRNs initially revealed the distinct differences in physiological and biochemical aspects of muscle growth and adipose deposition between the two pig breeds; from these results, some potential key genes could be identified. Quantitative real-time RT-PCR （QRT-PCR） was used to verify the microarray data for five modulated genes, and a good correlation between     

Identifying Micro RNA and Gene Expression Networks Using Graph Communities

Integrative network analysis is powerful in helping understand the underlying mechanisms of genetic and epigenetic perturbations for disease studies.Although it becomes clear that micro RNAs,one type of epigenetic factors,have direct effect on target genes,it is unclear how micro RNAs perturb downstream genetic neighborhood.Hence,we propose a network community approach to integrate micro RNA and gene expression profiles,to construct an integrative genetic network perturbed by micro RNAs.We apply this approach to an ovarian cancer dataset from The Cancer Genome Atlas project to identify the fluctuation of micro RNA expression and its effects on gene expression.First,we perform expression quantitative loci analysis between micro RNA and gene expression profiles via both a classical regression framework and a sparse learning model.Then,we apply the spin glass community detection algorithm to find genetic neighborhoods of the micro RNAs and their associated genes.Finally,we construct an integrated network between micro RNA and gene expression based on their community structure.Various disease related micro RNAs and genes,particularly related to ovarian cancer,are identified in this network.Such an integrative network allows us to investigate the genetic neighborhood affected by micro RNA expression that may lead to disease manifestation and progression.     

Dysfunction of lipid sensor GPR120 leads to obesity in both mouse and human

Free fatty acids provide an important energy source as nutrients, and act as signalling molecules in various cellular processes. Several G-protein-coupled receptors have been identified as free-fatty-acid receptors important in physiology as well as in several diseases. GPR120 (also known as O3FAR1) functions as a receptor for unsaturated long-chain free fatty acids and has a critical role in various physiological homeostasis mechanisms such as adipogenesis, regulation of appetite and food preference. Here we show that GPR120-deficient mice fed a high-fat diet develop obesity, glucose intolerance and fatty liver with decreased adipocyte differentiation and lipogenesis and enhanced hepatic lipogenesis. Insulin resistance in such mice is associated with reduced insulin signalling and enhanced inflammation in adipose tissue. In human, we show that GPR120 expression in adipose tissue is significantly higher in obese individuals than in lean controls. GPR120 exon sequencing in obese subjects reveals a deleterious non-synonymous mutation (p.R270H) that inhibits GPR120 signalling activity. Furthermore, the p.R270H variant increases the risk of obesity in European populations. Overall, this study demonstrates that the lipid sensor GPR120 has a key role in sensing dietary fat and, therefore, in the control of energy balance in both humans and rodents.     

Macrophage-specific PPARgamma controls alternative activation and improves insulin resistance

Obesity and insulin resistance, the cardinal features of metabolic syndrome, are closely associated with a state of low-grade inflammation. In adipose tissue chronic overnutrition leads to macrophage infiltration, resulting in local inflammation that potentiates insulin resistance. For instance, transgenic expression of Mcp1 (also known as chemokine ligand 2, Ccl2) in adipose tissue increases macrophage infiltration, inflammation and insulin resistance. Conversely, disruption of Mcp1 or its receptor Ccr2 impairs migration of macrophages into adipose tissue, thereby lowering adipose tissue inflammation and improving insulin sensitivity. These findings together suggest a correlation between macrophage content in adipose tissue and insulin resistance. However, resident macrophages in tissues display tremendous heterogeneity in their activities and functions, primarily reflecting their local metabolic and immune microenvironment. While Mcp1 directs recruitment of pro-inflammatory classically activated macrophages to sites of tissue damage, resident macrophages, such as those present in the adipose tissue of lean mice, display the alternatively activated phenotype. Despite their higher capacity to repair tissue, the precise role of alternatively activated macrophages in obesity-induced insulin resistance remains unknown. Using mice with macrophage-specific deletion of the peroxisome proliferator activated receptor-gamma (PPARgamma), we show here that PPARgamma is required for maturation of alternatively activated macrophages. Disruption of PPARgamma in myeloid cells impairs alternative macrophage activation, and predisposes these animals to development of diet-induced obesity, insulin resistance, and glucose intolerance. Furthermore, gene expression profiling revealed that downregulation of oxidative phosphorylation gene expression in skeletal muscle and liver leads to decreased insulin sensitivity in these tissues. Together, our findings suggest that resident alternatively activated macrophages have a beneficial role in regulating nutrient homeostasis and suggest that macrophage polarization towards the alternative state might be a useful strategy for treating type 2 diabetes.     

Epistasis and balanced polymorphism influencing complex trait variation

Complex traits such as human disease, growth rate, or crop yield are polygenic, or determined by the contributions from numerous genes in a quantitative manner. Although progress has been made in identifying major quantitative trait loci (QTL), experimental constraints have limited our knowledge of small-effect QTL, which may be responsible for a large proportion of trait variation. Here, we identified and dissected a one-centimorgan chromosome interval in Arabidopsis thaliana without regard to its effect on growth rate, and examined the signature of historical sequence polymorphism among Arabidopsis accessions. We found that the interval contained two growth rate QTL within 210 kilobases. Both QTL showed epistasis; that is, their phenotypic effects depended on the genetic background. This amount of complexity in such a small area suggests a highly polygenic architecture of quantitative variation, much more than previously documented. One QTL was limited to a single gene. The gene in question displayed a nucleotide signature indicative of balancing selection, and its phenotypic effects are reversed depending on genetic background. If this region typifies many complex trait loci, then non-neutral epistatic polymorphism may be an important contributor to genetic variation in complex traits.     

Alternatively activated macrophages produce catecholamines to sustain adaptive thermogenesis

All homeotherms use thermogenesis to maintain their core body temperature, ensuring that cellular functions and physiological processes can continue in cold environments. In the prevailing model of thermogenesis, when the hypothalamus senses cold temperatures it triggers sympathetic discharge, resulting in the release of noradrenaline in brown adipose tissue and white adipose tissue. Acting via the β(3)-adrenergic receptors, noradrenaline induces lipolysis in white adipocytes, whereas it stimulates the expression of thermogenic genes, such as PPAR-γ coactivator 1a (Ppargc1a), uncoupling protein 1 (Ucp1) and acyl-CoA synthetase long-chain family member 1 (Acsl1), in brown adipocytes. However, the precise nature of all the cell types involved in this efferent loop is not well established. Here we report in mice an unexpected requirement for the interleukin-4 (IL-4)-stimulated program of alternative macrophage activation in adaptive thermogenesis. Exposure to cold temperature rapidly promoted alternative activation of adipose tissue macrophages, which secrete catecholamines to induce thermogenic gene expression in brown adipose tissue and lipolysis in white adipose tissue. Absence of alternatively activated macrophages impaired metabolic adaptations to cold, whereas administration of IL-4 increased thermogenic gene expression, fatty acid mobilization and energy expenditure, all in a macrophage-dependent manner. Thus, we have discovered a role for alternatively activated macrophages in the orchestration of an important mammalian stress response, the response to cold.     

基于熵互信息理论的基因调控网络的研究

将熵互信息理论应用到布尔基因调控网络中,并推导出了多个基因决定某个或多个基因的表达值的逻辑规则,根据得到的逻辑规则建立了基因逻辑电路网络,根据该网络和逻辑电路网络分析方法又建立了基因调控网络动态转换图,从而揭示了基因之问的调控关系。     

New gene functions in megakaryopoiesis and platelet formation

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.     

一种改进的多元回归估计基因调控网络的方法

针对用多元回归分析估计基因调控网络时遇到的计算量过大的问题,提出了先用线性模型构建基因类间的调控网络,再用多元回归模型构建基因间调控网络的改进方案,利用类间网络提供的参考信息可以大大减少多元回归分析的计算量.将该方案应用到人类基因调控网络的估计中,并通过现有文献验证了部分调控关系,从而初步证明了该方法的有效性.