Programs for calculating the statistical powers of detecting susceptibility genes in case–control studies based on multistage designs

Motivation: A two-stage association study is the most commonly used method among multistage designs to efficiently identify disease susceptibility genes. Recently, some SNP studies have utilized more than two stages to detect disease genes. However, there are few available programs for calculating statistical powers and positive predictive values (PPVs) of arbitrary n-stage designs

Epidemiology Insights

This book represents an overview on the diverse threads of epidemiological research, brings together the expertise and enthusiasm of an international panel of leading researchers to provide a state-of-the art overview of the field. Topics include the epidemiology of dermatomycoses and Candida spp. infections, the epidemiology molecular of methicillin-resistant Staphylococcus aureus (MRSA) isolated from humans and animals, the epidemiology of varied manifestations neuro-psychiatric, virology and epidemiology, epidemiology of wildlife tuberculosis, epidemiologic approaches to the study of microbial quality of milk and milk products, Cox proportional hazards model, epidemiology of lymphoid malignancy, epidemiology of primary immunodeficiency diseases and genetic epidemiology family-based. Written by experts from around the globe, this book is reading for clinicians, researchers and students, who intend to address these issues

Evolution-based strategies to elucidate genotype-phenotype relationships in traits relevant to human health

Understanding the link between genotype and phenotype is a key question in biological research. In other words, how do changes in DNA sequence give rise to the enormous diversity of life on Earth? In this work, we address that question by focusing on the genomics of convergent phenotypes, or phenotypes that have evolved independently in unrelated species. These natural biological replicates of phenotype evolution allow us to identify genomic regions, either regulatory or protein coding, that have experienced convergent evolution in concordance with convergent evolution of phenotypes, thus linking genomic regions to phenotypes. In this work, we calculate evolutionary rates throughout the mammalian phylogeny for numerous genomic sequences to find concordance between species phenotype and evolutionary rate of sequences to link genomic regions to phenotypes. Chapter one describes three methods associated with quantifying the connection between genomic region evolution and phenotype evolution. First, RERconverge connects genomic regions to phenotypes in a linear regression-based framework. Second, permulations are a statistical extension to RERconverge that allow for rigorous calculation of confidence in associations from RERconverge. Third, proper implementation of branch-site models for convergent positive selection allows for identification of genes potentially driving convergent evolution. Chapter two describes implementation of methods from chapter one to longevity phenotypes in 61 mammal species. We found increased evolutionary constraint in cancer control genes in large, long-lived species, thus likely conferring additional protection from cancer. Species exceptionally long-lived given their size showed increased evolutionary constraint on DNA repair pathways, indicating that efficient DNA repair is important to evolution of extreme lifespan independent of body size. This work provided insight into pan-mammalian genomic mechanisms underlying lifespan. Chapter three describes further implementation of chapter one methods to the hairlessness phenotype in 61 mammal species. Although all mammals have some hair at some developmental time point, several mammals, such as cetaceans, naked mole-rats, armadillos, and humans, have relatively little hair. Many genomic elements we identified were known to be hair-related, and many more are valuable candidates for further testing into hair-related functions. This work for the first time provided insights to the natural evolution of mammalian hairlessness

The Identification of Genetic and Epigenetic Changes that Contribute to Type 1 Diabetes

Type 1 diabetes (T1D) results from an immune cell mediated destruction of insulin-producing pancreatic β cells. Currently there is no cure for T1D. The exact cause for T1D is unknown but growing evidence points to the contribution of both genetic and environmental factors, leading to a breakdown in immunological tolerance normally maintained by Regulatory T (Treg) cells. The exact environmental contributions to T1D progression are not well characterised but emerging studies suggest that they may alter the immune system via epigenetic modification. Recent data strongly link the breakdown in tolerance in T1D and other autoimmune diseases to alterations in the transcriptional program in CD4+ T cells, however, the molecular mechanisms are not well understood. This work proposes that in T1D causal genetic risk SNPs alter the gene expression patterns in CD4+ Treg and or T helper cells by either disrupting or creating new TF (transcription factor) binding sites in regulatory elements (enhancers) located in genetic susceptibility regions and this may combine with environmentally induced epigenetic change and alter chromatin accessibility. Current methods to identify the functional consequences and mechanisms of these changes are complex, time consuming and expensive as generally they can only examine one TF/binding site at a time, involve TF binding site prediction, which has a high degree of false positives/negatives and require large quantities of starting material making them challenging for application on limited clinical samples. To overcome these limitations, and to functionally annotate genetic risk of T1D, this study employs genome wide approaches including ATAC-seq and RNA-seq to compare the DNA accessibility and transcriptomes in CD4+ Treg and Th (Helper T)/Tconv (Conventional T) cells isolated from individuals with established T1D and sibling-matched healthy controls. By incorporating case-control ATAC-seq and TF footprints this study prioritises 111 and 96 T1D-associated SNPs in Treg and Tconv cells, respectively, that may play a role in mediating the disease susceptibility and subsequently contributing to the loss of tolerance in T1D. Using a bioinformatic pipeline to integrate case-control ATAC-seq differentially accessible peaks and RNA-seq differentially expressed genes with Hi-C 3D connectivity maps this study identifies 42 and 21 dysregulated gene targets in Treg and Tconv cells, respectively. Those targets include TIGIT, MAF and IL2 and the enhancers regulating those loci showed differential accessibility and are enriched for T1D SNPs and differential TF footprint signals. One theory to explain such observation is T1D SNPs and epigenetic alterations may alter or disrupt TF occupancy at these loci contributing to dysregulated target gene regulation. This study identifies changes in chromatin structure in T1D samples relative to healthy controls, enabling the identification of changes driven by both genetic and epigenetic variation that correlates with an altered transcriptional program in T1D. T1D associated SNPs at these regions can then be correlated with alterations in TF binding and putative epigenetically modified T1D regions can be validated in follow-up functional assays to demonstrate causality. This study captures chromatin and transcriptional changes between T1D and healthy individuals but it does not have the capability to distinguish if the changes are the driver or the consequence of the disease because the case cohort contains only established T1D from a single time point. In order to infer causality those changes would need to be tracked and validated over a timeline of disease progression in a longitudinal cohort. Nonetheless, this work provides a novel 3D genomic approach to functionally annotating the genetic risk and epigenetic changes that directly or indirectly result in altered gene expression, and promising preliminary data warranting further investigation on the causal functional role of the dysregulated gene targets in T1D.Thesis (Ph.D.) -- University of Adelaide, School of Medicine, 202

Systems Analytics and Integration of Big Omics Data

A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome

Quantitative Trait Loci Mapping in Merino Sheep and Effect of Accuracy of QTL Parameter Estimation on Marker Assisted Selection

The objectives of this thesis were to perform a genome scan for important production traits in Australian Merino sheep and to investigate issues related to the prediction of marker assisted selection (MAS) response in single and multiple trait selection schemes in animal breeding programs. In the first experimental chapter, a genome scan was performed for 4 growth and 7 fleece traits in Australian Merino sheep. Quantitative trait loci (QTL) parameters were estimated through single QTL interval mapping within and across four paternal half-sib families. The genome scan yielded 21 significant QTL for all traits at the 1% chromosome wise significance threshold level in within family analysis. Across family analysis supported most of the highly significant results from single family analysis but did not show any common significant QTL at the 1% chromosome wise significance threshold level across all families. Because of the relatively small progeny group sizes the power and the precision of the analysis are probably low and the QTL allele substitution effects are overestimated. In the subsequent three chapters some important issues related to the application of QTL information in MAS, including efficient prediction of MAS response and effect of the accuracy of estimated QTL effect in single and multiple trait selection, were investigated

Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Studies on sequencing analyses of genetic and epigenetics features in melanoma and breast cancer

The dissertation includes 3 projects and in each work we applied different approaches to sequencing and bioinformatics analyses to gain a better understanding of the molecular characteristics of breast cancer and melanoma. In the first project (paper I) we applied whole exome sequencing to samples from patients with metastatic melanoma. We assessed intra patient heterogeneity and we identified several general patterns of tumor evolution in this malignancy. In the second project (paper II) we used promoter methylation-specific sequencing and analysed the variation of promoter methylation of tumor suppressors in healthy individuals. As such, we also established a cost-effective method to study promoter methylation as a potential modulator of cancer risk. In the third project (paper III), we used microRNA sequencing and identified novel miRNAs that were overexpressed in breast cancer patients. Two of these were selected for further investigation focusing on their potential biological roles in breast cancer.Doktorgradsavhandlin

2013 Oklahoma Research Day Full Program

This document contains all abstracts from the 2013 Oklahoma Research Day held at the University of Central Oklahoma

Modifying effects of oxidative stress and DNA repair variants on physical activity and breast cancer risk

Purpose. The mechanisms driving the inverse association between recreational physical activity (RPA) and breast cancer risk are unclear. Exercise both increases reactive oxygen species production, which may transform normal epithelium to a malignant phenotype, and enhances antioxidant capacity, which could protect against subsequent oxidative insult. Physical activity may also improve damage repair systems, particularly those that operate on oxidative damage. Given the paradoxical and complex effects of physical activity both oxidative stress and DNA repair pathways are of interest. Polymorphisms in these pathways may modify the association between RPA and breast cancer incidence. Methods. We estimated interactions between RPA and several polymorphisms in oxidative stress-related genes (CAT, COMT, GPX, GSTP1, GSTA1, GSTM1, GSTP1, MPO, and MnSOD) as well as DNA repair genes (ERCC1, MGMT, MLH1, MSH2, MSH3, OGG1, XPA, XPC, XPD, XPF, XPG, and XRCC1). Data were from the Long Island Breast Cancer Study Project, a population-based, case-control study with interview and biomarker data available on 1053 cases and 1102 controls. Results. Six variants in antioxidant and DNA repair pathway genes (CAT rs1001179, GSTP1-Ile105Val, XPC-Ala499Val, XPF-Arg415Gln, XPG-Asp1104His and MLH1-lle219Val) interacted with postmenopausal RPA (p=0.043, 0.006, 0.048, 0.022, 0.012, and 0.010, respectively). Highly active women with genotypes related to reduced antioxidant capacity were at increased risk of breast cancer (CAT OR=1.61; 95% CI, 1.06-2.45) while risk reductions were observed among moderately active women with genotypes related to enhanced antioxidant capacity (GSTP1 OR=0.56; 95% CI, 0.38-0.84). With respect to DNA repair we found risk reductions for highly active women with common genotypes for XPC (OR=0.57; 95% CI, 0.38-0.84) and XPF (OR=0.64; 95% CI, 0.46-0.89) compared to non-active women homozygous for the major alleles. Non-significant risk reductions were observed among active women with at least one variant allele for XPG and MLH1, respectively. Conclusions. Genes involved in antioxidant and DNA repair pathways may modify the RPA-breast cancer risk association. While the functional significance of many polymorphisms with respect to breast cancer remains largely unknown, the observed associations are biologically plausible and consistent across multiple indicators of physical activity reducing the likelihood that these findings are attributable to chance. Our results merit further investigation.Doctor of Philosoph