Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies

Background
Automated candidate gene prediction systems allow geneticists to hone in on disease genes more rapidly by identifying the most probable candidate genes linked to the disease phenotypes under investigation. Here we assessed the ability of eight different candidate gene prediction systems to predict disease genes in intervals previously associated with type 2 diabetes by benchmarking their performance against genes implicated by recent genome-wide association studies.

Results
Using a search space of 9556 genes, all but one of the systems pruned the genome in favour of genes associated with moderate to highly significant SNPs. Of the 11 genes associated with highly significant SNPs identified by the genome-wide association studies, eight were flagged as likely candidates by at least one of the prediction systems. A list of candidates produced by a previous consensus approach did not match any of the genes implicated by 706 moderate to highly significant SNPs flagged by the genome-wide association studies. We prioritized genes associated with medium significance SNPs.

Conclusion
The study appraises the relative success of several candidate gene prediction systems against independent genetic data. Even when confronted with challengingly large intervals, the candidate gene prediction systems can successfully select likely disease genes. Furthermore, they can be used to filter statistically less-well-supported genetic data to select more likely candidates. We suggest consensus approaches fail because they penalize novel predictions made from independent underlying databases. To realize their full potential further work needs to be done on prioritization and annotation of genes.

Decreased expression of adipogenic genes in obese subjects with type 2 diabetes

Objective: Our objective was to delineate the potential role of adipogenesis in insulin resistance and type 2 diabetes. Obesity is characterized by an increase in adipose tissue mass resulting from enlargement of existing fat cells (hypertrophy) and/or from increased number of adipocytes (hyperplasia). The inability of the adipose tissue to recruit new fat cells may cause ectopic fat deposition and insulin resistance.

Research Methods and Procedures: We examined the expression of candidate genes involved in adipocyte proliferation and/or differentiation [ CCAAT/enhancer-binding protein (C/EBP) alpha, C/EBPdelta, GATA domain-binding protein 3 (GATA3), C/EBPbeta, peroxisome proliferator-activated receptor (PPAR) gamma2, signal transducer and activator of transcription 5A (STAT5A), Wnt-10b, tumor necrosis factor alpha, sterol regulatory element-binding protein 1c (SREBP1c), 11 beta-hydroxysteroid dehydrogenase, PPARG angiopoietin-related protein (PGAR), insulin-like growth factor 1, PPARitalic gamma coactivator 1alpha, PPARitalic gamma coactivator 1beta, and PPARdelta] in subcutaneous adipose tissue from 42 obese individuals with type 2 diabetes and 25 non-diabetic subjects matched for age and obesity.

Results: Insulin sensitivity was measured by a 3-hour 80 mU/m2 per minute hyperinsulinemic glucose clamp (100 mg/dL). As expected, subjects with type 2 diabetes had lower glucose disposal (4.9 plusminus 1.9 vs. 7.5 plusminus 2.8 mg/min per kilogram fat-free mass; p < 0.001) and larger fat cells (0.90 plusminus 0.26 vs. 0.78 plusminus 0.17 mum; p = 0.04) as compared with obese control subjects. Three genes (SREBP1c, p < 0.01; STAT5A, p = 0.02; and PPARitalic gamma2, p = 0.02) had significantly lower expression in obese type 2 diabetics, whereas C/EBPbeta only tended to be lower (p = 0.07).

Discussion: This cross-sectional study supports the hypothesis that impaired expression of adipogenic genes may result in impaired adipogenesis, potentially leading to larger fat cells in subcutaneous adipose tissue and insulin resistance.

Skeletal muscle htererogeneity in fasting-induced upregulation of genes encoding UCP2, UCP3, PPARĂ and key enzymes of lipid oxidation

The uncoupling protein homologs UCP2 and UCP3 have been proposed as candidate genes for the regulation of lipid metabolism. Within the context of this hypothesis, we have compared, from fed and fasted rats, changes in gene expression of skeletal muscle UCP2 and UCP3 with those of carnitine palmitoyltransferase I and medium-chain acyl-CoA dehydrogenase, two key enzymes regulating lipid flux across the mitochondrial #-oxidation pathway. In addition, changes in gene expression of peroxisome proliferator-activated receptor gamma, a nuclear transcription factor implicated in lipid metabolism, were also investigated. The results indicate that in response to fasting, the mRNA levels of UCP2, UCP3, carnitine palmitoyltransferase I and medium-chain acyl-CoA dehydrogenase are markedly increased, by three- to sevenfold, in the gastrocnemius and tibialis anterior (fast-twitch muscles, predominantly glycolytic or oxidative-glycolytic), but only mildly increased, by less than twofold, in the soleus (slow-twitch muscle, predominantly oxidative). Furthermore, such muscle-type dependency in fasting-induced transcriptional changes in UCP2, UCP3, carnitine palmitoyltransferase and medium-chain acyl-CoA dehydrogenase persists when the increase in circulating levels of free fatty acids during fasting is abolished by the anti-lipolytic agent nicotinic acid - with blunted responses only in the slow-twitch muscle contrasting with unabated increases in fast-twitch muscles. Independently of muscle type, however, the mRNA levels of peroxisome proliferator-activated receptor gamma are not altered during fasting. Taken together, these studies indicate a close association between fasting-induced changes in UCP2 and UCP3 gene expression with those of key regulators of lipid oxidation, and are hence consistent with the hypothesis that these UCP homologs may be involved in the regulation of lipid metabolism. Furthermore, they suggest that in response to fasting, neither the surge of free fatty acids in the circulation nor induction of the peroxisome proliferator-activated receptor gamma gene may be required for the marked upregulation of genes encoding the UCP homologs and key enzymes regulating lipid oxidation in fast-twitch muscles.

Genetic variation and obesity in Australian women: A prospective study.

Objective: A number of candidate genes have been implicated in the pathogenesis of obesity in humans. This study examines associations between longitudinal changes in body mass and composition and the presence of polymorphisms in the ß-3 adrenergic receptor, tumor necrosis factor-α, leptin, and leptin receptor (Lepr) in a cohort of Australian women.

Research Methods and Procedures: Healthy white Australian women (n = 335) were randomly selected from the Barwon region of Victoria and underwent baseline anthropometry and double-energy X-ray absorptiometry for assessment of body mass and adiposity. These measurements were repeated again at 2-year follow-up. Genomic DNA was extracted and used for polymerase chain reaction-based genotyping of all polymorphisms.

Results: The Pro1019Pro Lepr polymorphism was associated with longitudinal increases in body weight (p = 0.02), fat mass (p = 0.05), and body mass index (p = 0.01) in this study, and individuals homozygous for the A allele at this locus had a greater propensity to gain body fat over time. The largest effects on body composition seemed to be in individuals already obese at baseline. Changes in body weight, fat mass, percent body fat, and body mass index over a 2-year period were not associated with genetic variation in the ß-3 adrenergic receptor (Trp64Arg), tumor necrosis factor-α promoter, or leptin genes in non-obese or obese women.

Discussion: These results suggest that a Lepr polymorphism is involved in the regulation of body mass and adiposity in obese Australian white women, which may have implications for the treatment of obesity in this population.

New approaches to gene discovery with animal models of obesity and diabetes

DNA-based approaches to the discovery of genes contributing to the development of type 2 diabetes have not been very successful despite substantial investments of time and money. The multiple gene-gene and gene-environment interactions that influence the development of type 2 diabetes mean that DNA approaches are not the ideal tool for defining the etiology of this complex disease. Gene expression-based technologies may prove to be a more rewarding strategy to identify diabetes candidate genes. There are a number of RNA-based technologies available to identify genes that are differentially expressed in various tissues in type 2 diabetes. These include differential display polymerase chain reaction (ddPCR), suppression subtractive hybridization (SSH), and cDNA microarrays. The power of new technologies to detect differential gene expression is ideally suited to studies utilizing appropriate animal models of human disease. We have shown that the gene expression approach, in combination with an excellent animal model such as the Israeli sand rat (Psammomys obesus), can provide novel genes and pathways that may be important in the disease process and provide novel therapeutic approaches. This paper will describe a new gene discovery, beacon, a novel gene linked with energy intake. As the functional characterization of novel genes discovered in our laboratory using this approach continues, it is anticipated that we will soon be able to compile a definitive list of genes that are important in the development of obesity and type 2 diabetes.

A custom-built insulin resistance gene chip

Objectives/Aim—Microarray (gene chip) technology offers a powerful new tool for analyzing the expression of large numbers of genes in many experimental samples. The aim of this study was to design, construct, and use a gene chip to measure the expression levels of key genes in metabolic pathways related to insulin resistance.
Methods—We selected genes that were implicated in the development of insulin resistance, including genes involved in insulin signaling; glucose uptake, oxidation, and storage; fat uptake, oxidation, and storage; cytoskeletal components; and transcription factors. The key regulatory genes in the pathways were identified, along with other recently identified candidate genes such as calpain-10. A total of 242 selected genes (including 32 internal control elements) were sequence-verified, purified, and arrayed on aldehyde-coated slides.
Results—Where more than 1 clone containing the gene of interest was available, we chose those containing the genes in the 5' orientation and an insert size of around 1.5 kb. Of the 262 clones purchased, 56 (21%) were found to contain sequences other than those expected. In addition, 2 (1%) did not grow under standard conditions and were assumed to be nonviable. In these cases, alternate clones containing the gene of interest were chosen as described above. The current version of the Insulin Resistance Gene Chip contains 210 genes of interest, plus 48 control elements. A full list of the genes is available at http://www.hbs.deakin.edu.au/mru/research/gene_chip_tech/genechip_three.htm/.
Conclusions—The human Insulin Resistance Gene Chip that we have constructed will be a very useful tool for investigating variation in the expression of genes relevant to insulin resistance under various experimental conditions. Initially, the gene chip will be used in studies such as exercise interventions, fasting, euglycemic-hyperinsulinemic clamps, and administration of antidiabetic agents

Heterologous microarray experiments used to identify the early gene response to heat stress in a coral reef fish

Coral reef fishes are expected to experience rising sea surface temperatures due to climate change. How well tropical reef fishes will respond to these increased temperatures and which genes are important in the response to elevated temperatures is not known. Microarray technology provides a powerful tool for gene discovery studies, but the development of microarrays for individual species can be expensive and time-consuming. In this study, we tested the suitability of a Danio rerio oligonucleotide microarray for application in a species with few genomic resources, the coral reef fish Pomacentrus moluccensis. Results from a comparative genomic hybridization experiment and direct sequence comparisons indicate that for most genes there is considerable sequence similarity between the two species, suggesting that the D. rerio array is useful for genomic studies of P. moluccensis. We employed this heterologous microarray approach to characterize the early transcriptional response to heat stress in P. moluccensis. A total of 111 gene loci, many of which are involved in protein processing, transcription, and cell growth, showed significant changes in transcript abundance following exposure to elevated temperatures. Changes in transcript abundance were validated for a selection of candidate genes using quantitative real-time polymerase chain reaction. This study demonstrates that heterologous microarrays can be successfully employed to study species for which specific microarrays have not yet been developed, and so have the potential to greatly enhance the utility of microarray technology to the field of environmental and functional genomics.

Investigation of plasmodiophora brassicae (clubroot disease) in vegetable brassica using arabidopsis thaliana as a model system

Clubroot, caused by Plasmodiophora brassicae, is the most devastating soil-borne disease of vegetable brassicas. It occurs all over the world and is responsible for crop losses of up to 10% every year. In Australia, the disease is being managed effectively with chemicals and cultural practices, but ideally control can be improved in the long term by the introduction of resistant cultivars. The life cycle ofP. brassicae and mode of action of plant resistance has not been fully elucidated because of the technical difficulties of working with an obligate, soil-borne plant pathogen. However, Arabidopsis thaliana, which is a host ofP. brassicae, has great potential as a model system for studying the life cycle, the infection process and development of resistance. We have developed a sand-liquid-culture system for growing Arabidopsis that allows easy observation of all life stages and, most importantly, the primary plasmodial stages within the root hair. The method was first optimised for observations of the lifecycle of the pathogen in a susceptible Arabidopsis ecotype (Col-3) where all stages of the lifecycle have now been observed and characterised. Further screening of Arabidopsis ecotypes for disease resistance has utilised one of the most virulent Australian pathotypes of brassica (ECD number 16/19/31). To date, Arabidopsis ecotype Ta-0 has shown a level of tolerance to the disease even though the roots get infected. It has been reported earlier that resistance toP. brassicae in Arabidopsis is due to one or a small number of genes. To examine changes in gene expression during the early, critical stages of infection, RNA was extracted from the susceptible and resistant ecotypes at two time points, 4 days and 17 days after inoculation. Microarray analysis will be used to investigate genome wide changes in gene expression during infection but also to identify candidate genes that may confer resistance to Australian isolates of the pathogen.

Identification of secreted proteins associated with obesity and type 2 diabetes in Psammomys obesus

Objective: Skeletal muscle produces a variety of secreted proteins that have important roles in intercellular communication and affects processes such as glucose homoeostasis. The objective of this study was to develop a novel Signal Sequence Trap (SST) in conjunction with cDNA microarray technology to identify proteins secreted from skeletal muscle of Psammomys obesus that were associated with obesity and type 2 diabetes (T2D).

Design: Secreted proteins that were differentially expressed between lean, normal glucose tolerant (NGT), overweight and impaired glucose tolerant (IGT) and obese, T2D P. obesus were isolated using SST in conjunction with cDNA microarray technology. Subsequent gene expression was measured in tissues from P. obesus by real-time PCR (RT-PCR).

Results: The SST yielded 1600 positive clones, which were screened for differential expression. A total of 91 (B6%) clones were identified by microarray to be differentially expressed between NGT, IGT and T2D P. obesus. These clones were sequenced to identify 51 genes, of which only 27 were previously known to encode secreted proteins. Three candidate genes not previously associated with obesity or type 2 diabetes, sushi domain containing 2, collagen and calcium-binding EGF domains 1 and periostin (Postn), as well as one gene known to be associated, complement component 1, were shown by RT-PCR to be differentially expressed in  skeletal muscle of P. obesus. Further characterization of the secreted protein Postn revealed it to be predominantly expressed in adipose tissue, with higher expression in visceral compared with subcutaneous adipose depots.

Conclusion: SST in conjunction with cDNA microarray technology is a powerful tool to identify differentially expressed secreted proteins involved in complex diseases such as obesity and type 2 diabetes. Furthermore, a number of candidate genes were identified, in particular, Postn, which may have a role in the development of obesity and type 2 diabetes.

A novel approach identified the FOLR1 gene, a putative regulator of milk protein synthesis

This study has utilised comparative functional genomics to exploit animal models with extreme adaptation to lactation to identify candidate genes that specifically regulate protein synthesis in the cow mammary gland. Increasing milk protein production is valuable to the dairy industry. The lactation strategies of both the Cape fur seal (Artocephalus pusillus pusillus) and the tammar wallaby (Macropus eugenii) include periods of high rates of milk protein synthesis during an established lactation and therefore offer unique models to target genes that specifically regulate milk protein synthesis. Global changes in mammary gene expression in the Cape fur seal, tammar wallaby, and the cow (Bos taurus) were assessed using microarray analysis. The folate receptor α (FOLR1) showed the greatest change in gene expression in all three species [cow 12.7-fold (n = 3), fur seal 15.4-fold (n = 1), tammar 2.4-fold (n = 4)] at periods of increased milk protein production. This compliments previous reports that folate is important for milk protein synthesis and suggests FOLR1 may be a key regulatory point of folate metabolism for milk protein synthesis within mammary epithelial cells (lactocytes). These data may have important implications for the dairy industry to develop strategies to increase milk protein production in cows. This study illustrates the potential of comparative genomics to target genes of interest to the scientific community.

Biomarkers in bipolar disorder : a positional paper from the International Society for Bipolar Disorders Biomarkers Task Force

Although the etiology of bipolar disorder remains uncertain, multiple studies examining neuroimaging, peripheral markers and genetics have provided important insights into the pathophysiologic processes underlying bipolar disorder. Neuroimaging studies have consistently demonstrated loss of gray matter, as well as altered activation of subcortical, anterior temporal and ventral prefrontal regions in response to emotional stimuli in bipolar disorder. Genetics studies have identified several potential candidate genes associated with increased risk for developing bipolar disorder that involve circadian rhythm, neuronal development and calcium metabolism. Notably, several groups have found decreased levels of neurotrophic factors and increased pro-inflammatory cytokines and oxidative stress markers. Together these findings provide the background for the identification of potential biomarkers for vulnerability, disease expression and to help understand the course of illness and treatment response. In other areas of medicine, validated biomarkers now inform clinical decision-making. Although the findings reviewed herein hold promise, further research involving large collaborative studies is needed to validate these potential biomarkers prior to employing them for clinical purposes. Therefore, in this positional paper from the ISBD-BIONET (biomarkers network from the International Society for Bipolar Disorders), we will discuss our view of biomarkers for these three areas: neuroimaging, peripheral measurements and genetics; and conclude the paper with our position for the next steps in the search for biomarkers for bipolar disorder.

Identification of novel therapeutics for complex diseases from genome-wide association data

Human genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials.

Transcriptomics-based analysis using RNA-Seq of the coconut (Cocos nucifera) leaf in response to yellow decline phytoplasma infection

Invasive phytoplasmas wreak havoc on coconut palms worldwide, leading to high loss of income, food insecurity and extreme poverty of farmers in producing countries. Phytoplasmas as strictly biotrophic insect-transmitted bacterial pathogens instigate distinct changes in developmental processes and defence responses of the infected plants and manipulate plants to their own advantage; however, little is known about the cellular and molecular mechanisms underlying host–phytoplasma interactions. Further, phytoplasma-mediated transcriptional alterations in coconut palm genes have not yet been identified. This study evaluated the whole transcriptome profiles of naturally infected leaves of Cocos nucifera ecotype Malayan Red Dwarf in response to yellow decline phytoplasma from group 16SrXIV, using RNA-Seq technique. Transcriptomics-based analysis reported here identified genes involved in coconut innate immunity. The number of down-regulated genes in response to phytoplasma infection exceeded the number of genes up-regulated. Of the 39,873 differentially expressed unigenes, 21,860 unigenes were suppressed and 18,013 were induced following infection. Comparative analysis revealed that genes associated with defence signalling against biotic stimuli were significantly overexpressed in phytoplasma-infected leaves versus healthy coconut leaves. Genes involving cell rescue and defence, cellular transport, oxidative stress, hormone stimulus and metabolism, photosynthesis reduction, transcription and biosynthesis of secondary metabolites were differentially represented. Our transcriptome analysis unveiled a core set of genes associated with defence of coconut in response to phytoplasma attack, although several novel defence response candidate genes with unknown function have also been identified. This study constitutes valuable sequence resource for uncovering the resistance genes and/or susceptibility genes which can be used as genetic tools in disease resistance breeding.

Novel therapeutics for cononary artery disease from genome-wide association study data

Abstract
Background: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.
Methods: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatics modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.
Results: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).
Conclusions: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.