Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant’s sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes use of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. The resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance

Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome

<p>Abstract</p> <p>Background</p> <p>Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although <it>in utero </it>alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach.</p> <p>Results</p> <p>10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes.</p> <p>Conclusion</p> <p>This analysis highlighted a list of strong candidate genes from the TGF-β, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.</p

MeInfoText: associated gene methylation and cancer information from text mining

<p>Abstract</p> <p>Background</p> <p>DNA methylation is an important epigenetic modification of the genome. Abnormal DNA methylation may result in silencing of tumor suppressor genes and is common in a variety of human cancer cells. As more epigenetics research is published electronically, it is desirable to extract relevant information from biological literature. To facilitate epigenetics research, we have developed a database called MeInfoText to provide gene methylation information from text mining.</p> <p>Description</p> <p>MeInfoText presents comprehensive association information about gene methylation and cancer, the profile of gene methylation among human cancer types and the gene methylation profile of a specific cancer type, based on association mining from large amounts of literature. In addition, MeInfoText offers integrated protein-protein interaction and biological pathway information collected from the Internet. MeInfoText also provides pathway cluster information regarding to a set of genes which may contribute the development of cancer due to aberrant methylation. The extracted evidence with highlighted keywords and the gene names identified from each methylation-related abstract is also retrieved. The database is now available at <url>http://mit.lifescience.ntu.edu.tw/</url>.</p> <p>Conclusion</p> <p>MeInfoText is a unique database that provides comprehensive gene methylation and cancer association information. It will complement existing DNA methylation information and will be useful in epigenetics research and the prevention of cancer.</p

Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology.

High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types

Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BACKGROUND: Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease. METHODS: We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium(R) HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes. RESULTS: Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy. CONCLUSION: This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy

Summaries of plenary, symposia, and oral sessions at the XXII World Congress of Psychiatric Genetics, Copenhagen, Denmark, 12-16 October 2014

The XXII World Congress of Psychiatric Genetics, sponsored by the International Society of Psychiatric Genetics, took place in Copenhagen, Denmark, on 12-16 October 2014. A total of 883 participants gathered to discuss the latest findings in the field. The following report was written by student and postdoctoral attendees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the oral presentations during the conference, and contains some of the major notable new findings reported

Ecogenetics of mercury: From genetic polymorphisms and epigenetics to risk assessment and decision‐making

The risk assessment of mercury (Hg), in both humans and wildlife, is made challenging by great variability in exposure and health effects. Although disease risk arises following complex interactions between genetic (“nature”) and environmental (“nurture”) factors, most Hg studies thus far have focused solely on environmental factors. In recent years, ecogenetic‐based studies have emerged and have started to document genetic and epigenetic factors that may indeed influence the toxicokinetics or toxicodynamics of Hg. The present study reviews these studies and discusses their utility in terms of Hg risk assessment, management, and policy and offers perspectives on fruitful areas for future research. In brief, epidemiological studies on populations exposed to inorganic Hg (e.g., dentists and miners) or methylmercury (e.g., fish consumers) are showing that polymorphisms in a number of environmentally responsive genes can explain variations in Hg biomarker values and health outcomes. Studies on mammals (wildlife, humans, rodents) are showing Hg exposures to be related to epigenetic marks such as DNA methylation. Such findings are beginning to increase understanding of the mechanisms of action of Hg, and in doing so they may help identify candidate biomarkers and pinpoint susceptible groups or life stages. Furthermore, they may help refine uncertainty factors and thus lead to more accurate risk assessments and improved decision‐making. Environ Toxicol Chem 2014;33:1248–1258. © 2013 SETACPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106903/1/etc2375.pd

Arsenic exposure and early biomarkers of cardiovascular disease and cancer

AbstractInorganic arsenic exposure through drinking water is a serious public health concern because of its association to cancer and non-cancer diseases. More than one hundred million people world-wide are exposed to elevated levels of arsenic on a regular basis. Arsenic is classified as class I carcinogen by International Agency for Research on Cancer (IARC). Recent report shows that arsenic exposure via drinking water is associated with increased risk of cardiovascular disease and diabetes. Several mechanisms of arsenic-related toxicity have been suggested, among those are genotoxicity and epigenetic modifications affecting gene expression. The aim of this thesis was to identify early biomarkers for arsenic-related cancer and cardiovascular disease, as well as, to analyse changes in gene expression and DNA methylation related to chronic arsenic exposure. The study participants were from the Salta Province of northern Argentina, a region known to have areas with arsenic in drinking water. Two groups of study subjects, one residing in Puna area of Andes mountains (~4000 meters above the sea level) here called as Andes, and another residing in Salta plains (~300 meters above sea level) called Chaco, were studied. Arsenic exposure was assessed as the sum of inorganic arsenic and its metabolites, inorganic arsenic (iAs), methylarsonic acid (MMA) and dimethylarsinic acid (DMA) in urine, measured by high performance liquid-chromatography hydride-generation inductively-coupled-plasma-mass-spectrometry (HPLC-HG-ICPMS). The arsenic metabolism efficiency was assessed by the urinary fractions (%) of individual metabolites. To evaluate cardiovascular health, blood pressure was measured and homocysteine concentration and lipid profile were analysed in the plasma as early cardiovascular biomarkers in Andean women. To evaluate arenic realted DNA damage, telomere length and mitochondrial DNA copy number (mtDNAcn) were measured in peripheral blood in both Andes and Chaco study groups. Gene expression and DNA methylation were measured in peripheral blood in the Andes study group. The arsenic concentrations in water had large ranges in both Andes and Chaco, and the median urinary arsenic concentrations for Andes and Chaco were 196 µg/L and 80 µg/L, respectively. The urinary arsenic metabolites differed significantly between the study groups, the median %iAs and %MMA were higher and the median %DMA was lower in Chaco population compared to the Andes, reflecting a less efficient arsenic metabolism in the Chaco study group. In women from Andes, increased urinary arsenic concentration was associated with decreased diastolic blood pressure and apoB/A, but there were no associations between urinary arsenic and homocysteine, triglycerides or cytokines, suggesting no evident cardiovascular toxicity. In men and women in Andes and Chaco, urinary arsenic was associated with longer telomere length and in Chaco with increased mtDNAcn. When the study groups were stratified according to fraction of inorganic arsenic in urine (%iAs), the associations remained significant in the above %iAs group, i.e. with less efficient arsenic metabolism capacity, for both Andes and Chaco. This suggests that individuals with less efficient arsenic metabolism are more prone to arsenic-related DNA damage and may be at high risk for arsenic-related future diseases. In Andes women, urinary arsenic was associated with decreased gene expression and increased DNA methylation in peripheral blood, indicating that arsenic exposure may have silenced gene expression by increasing DNA methylation. This thesis showed genotoxic and epigenetic, but no adverse cardiovascular, effects of arsenic exposure via drinking water. Future studies are needed to follow-up the study groups for future arsenic-related disease