Predicting gene ontology from a global meta-analysis of 1-color microarray experiments

<p>Abstract</p> <p>Background</p> <p>Global meta-analysis (GMA) of microarray data to identify genes with highly similar co-expression profiles is emerging as an accurate method to predict gene function and phenotype, even in the absence of published data on the gene(s) being analyzed. With a third of human genes still uncharacterized, this approach is a promising way to direct experiments and rapidly understand the biological roles of genes. To predict function for genes of interest, GMA relies on a guilt-by-association approach to identify sets of genes with known functions that are consistently co-expressed with it across different experimental conditions, suggesting coordinated regulation for a specific biological purpose. Our goal here is to define how sample, dataset size and ranking parameters affect prediction performance.</p> <p>Results</p> <p>13,000 human 1-color microarrays were downloaded from GEO for GMA analysis. Prediction performance was benchmarked by calculating the distance within the Gene Ontology (GO) tree between predicted function and annotated function for sets of 100 randomly selected genes. We find the number of new predicted functions rises as more datasets are added, but begins to saturate at a sample size of approximately 2,000 experiments. For the gene set used to predict function, we find precision to be higher with smaller set sizes, yet with correspondingly poor recall and, as set size is increased, recall and F-measure also tend to increase but at the cost of precision.</p> <p>Conclusions</p> <p>Of the 20,813 genes expressed in 50 or more experiments, at least one predicted GO category was found for 72.5% of them. Of the 5,720 genes without GO annotation, 4,189 had at least one predicted ontology using top 40 co-expressed genes for prediction analysis. For the remaining 1,531 genes without GO predictions or annotations, ~17% (257 genes) had sufficient co-expression data yet no statistically significantly overrepresented ontologies, suggesting their regulation may be more complex.</p

Estimating networks of sustainable development goals

An increasing number of researchers and practitioners advocate for a systemic understanding of the Sustainable Development Goals (SDGs) through interdependency networks. Ironically, the burgeoning network-estimation literature seems neglected by this community. We provide an introduction to the most suitable estimation methods for SDG networks. Building a dataset with 87 development indicators in four countries over 20 years, we perform a comparative study of these methods. We find important differences in the estimated network structures as well as in synergies and trade-offs between SDGs. Finally, we provide some guidelines on the potentials and limitations of estimating SDG networks for policy advice

Toxicogenomics : a transcriptomics approach to assess the toxicity of 4-nitrophenol to sachharomyces cerevisiae

PhD ThesisSince the industrial revolution there has been a significant increase in the production, use and release of man-made chemicals (xenobiotics) into the environment. This is cause for concern because the toxicity of some xenobiotics are unknown, consequently there is an increased need for high throughput sensitive assays that can be used to detect and evaluate the toxicity of xenobiotics. The advent of transcriptomics has provided scientists with a sensitive, accurate high throughput method to measure gene expression in response to chemicals (toxicogenomics). The aim of this work was to investigate the effects of the widely distributed xenobiotic and model organic pollutant, 4-nitrophenol on gene expression in the model eukaryote Saccharomyces cerevisiae. This would assess if this chemical had more subtle effects on cells than previous traditional biochemistry studies revealed and to see if certain genes could be used to develop a specific microarray test to detect the presence of 4-nitrophenol in the environment. Traditional growth inhibition tests were used to ascertain the toxicity of 4-nitrophenol to S. cerevisiae. Traditional tests were used to establish EC10 & EC50 concentrations in standard defined media (SDM). Subsequently S. cerevisiae were exposed to 10 & 39 mg/l 4-nitrophenol in SDM and samples taken for expression profiling when conditions were optimal, one, two and three hours after 4-nitrophenol exposure. qRT-PCR was used to validate the gene expression results. Approximately 600 genes were increased in expression and ˜600 genes were decreased in expression at 10 & 39 4-nitrophenol. Genes associated with RNA processing, ribosome formation, mitochondrial biogenesis, and respiratory activity were differentially expressed. Time series analysis showed 4-nitrophenol caused damage to cell walls and membranes as inferred from increased expression of genes for cell wall and membrane synthesis (DCW1, GRE2). This resulted in hypo-osmotic stress (increased expression of SLN1, & AQY2) and decreased expression of genes involved in cell replication (MDY2, PAN3). At 39 mg/l 4-nitrophenol expression of additional drug resistance genes increased after one (PDR3, PDR15, PDR16), two (PDR3, PDR15) and three (PDR5) hour’s exposure. After two hours cells had respiration deficiencies shown by; increased expression of RIM2 a mitochondrial carrier protein, which rescues respiration deficient cells, and decreased production of mitochondrial oxidoreductases. Fourteen iron homeostasis genes were increased in expression and iron requiring cytochromes and oxidoreductases were decreased in expression alongside glucose transporter encoding genes. The results showed respiration was reduced and implicated an increased requirement for iron. Expression of general Environmental Stress Response (ESR) genes initially decreased (one hour of exposure to 39 mg/l 4-nitrophenol). However, three hours after the addition of 4-nitrophenol expression of ESR genes increased. ESR genes are known to be repressed for up to two hours after chemical exposure, and are known to be involved in respiration. The results in this study show reduced respiration is temporary. Increased expression of genes involved in respiration and growth after three hours show that treated cells have adapted to 4-nitrophenol presence. Only two iron homeostasis genes were increased in expression after three hours exposure to 39 mg/l 4-nitrophenol showing iron concentrations inside the cell have stabilised. Exposure to 4-nitrophenol resulted in hypo-osmotic stress, probably caused by membrane damage. This led to decreased intracellular iron concentrations and increased oxidative stress, iron availability directly controls expression of ESR genes and oxidoreductases and may explain the effects seen on mitochondrial respiratory activity and the general stress response observed. The study confirms biochemical results which have shown 4-nitrophenol damages cell membranes and reduces respiration, and implicates iron deficiency in playing a role in this process. It also shows that at sub lethal concentrations cells can adapt their respiration and growth to survive in the presence of 4-nitrophenol.Natural Environment Research Council (NERC) AstraZeneca COGEME (Manchester University