Efficiency and accuracy validation for incremental changes of a large-scale protein structure database [abstract]

Abstract only availableProteins, the essential building blocks of organisms, have many important roles, from providing structure to aiding movement and digestion. The construction of proteins involves one or more polypeptide chains that fold into complicated 3D structures. Each protein has a unique shape and some specific functions, which are intricately and irrevocably connected. In order to aid the study of structure-function relationships, ProteinDBS developed at the University of Missouri-Columbia presents a fast structure retrieval system to find proteins with such structural similarities. To present the most accurate results, ProteinDBS features automatic weekly updates of its system from the Protein Data Bank (PDB) which has over 76,000 protein chains and continuously grows the database size at least linearly. This research focuses on the efficiency and accuracy of protein structure retrieval using the ProteinDBS system as the size of the dataset grows. The investigation examines changes in results arising from the addition of new proteins to the system and illuminates the reasons for differences among search results. First, the system automatically checks protein domains and folds after insertion of new proteins. Testing proteins collected from various plants, such as maize and soybean, are validated against both the original dataset and the new, larger dataset. The systems compares the results from both sets of data to determine the changes in the composition of the result set, including the proliferation of newly inserted proteins, and the relative ordering of proteins in the ranked results. The analysis provides a thorough investigation of the effect the dataset has on protein structure retrieval and suggests areas for future improvement of the algorithmic designs of ProteinDBS in feature extraction, database indexing, and result ranking.National Science Foundation, University of Missouri-Columbia Research Counci

Genealogy browser: A framework for the management and analysis of genotypic and phenotypic plant data [abstract]

Abstract only availableResearchers who study plants need an efficient way to manage data that provides insight into genealogy and its effect on genotypic and phenotypic expressions. Traditional pencil and paper methods, arising from the need to collect data from the field, prove time consuming and error prone when tracking plant lineage. Genealogy Browser presents an effective method for plant management. By providing a web interface that collects information about plant families and relationships, the application provides the framework for data analysis. This setting allows researchers to collaborate about common plants and to become aware of the traits seen in other research groups. Furthermore, the application analyzes current gene and phenotype information to demonstrate where plants deviate from the expected, which will be of great importance to researchers especially as they study crops in varying climate settings. Genealogy Browser proves extremely vital for researchers needing to manage thousands of plants while obtaining useful information that sheds light on genotypic and phenotypic trends.National Science Foundation; Shumaker Endowment for Bioinformatic

A Human Cytomegalovirus-Encoded microRNA Regulates Expression of Multiple Viral Genes Involved in Replication

Although multiple studies have documented the expression of over 70 novel virus-encoded microRNAs (miRNAs), the targets and functions of most of these regulatory RNA species are unknown. In this study a comparative bioinformatics approach was employed to identify potential human cytomegalovirus (HCMV) mRNA targets of the virus-encoded miRNA miR-UL112-1. Bioinformatics analysis of the known HCMV mRNA 3′ untranslated regions (UTRs) revealed 14 potential viral transcripts that were predicted to contain functional target sites for miR-UL112-1. The potential target sites were screened using luciferase reporters that contain the HCMV 3′UTRs in co-transfection assays with miR-UL112-1. Three of the 14 HCMV miRNA targets were validated, including the major immediate early gene encoding IE72 (UL123, IE1), UL112/113, and UL120/121. Further analysis of IE72 regulation by miR-UL112-1 with clones encoding the complete major immediate early region revealed that the IE72 3′UTR target site is necessary and sufficient to direct miR-UL112-1-specific inhibition of expression in transfected cells. In addition, miR-UL112-1 regulation is mediated through translational inhibition rather than RNA degradation. Premature expression of miR-UL112-1 during HCMV infection resulted in a significant decrease in genomic viral DNA levels, suggesting a functional role for miR-UL112-1 in regulating the expression of genes involved in viral replication. This study demonstrates the ability of a viral miRNA to regulate multiple viral genes

Genetic Determinants of UV-Susceptibility in Non-Melanoma Skin Cancer

A milieu of cytokines and signaling molecules are involved in the induction of UV-induced immune suppression and thus the etiology of non-melanoma skin cancer (NMSC). Targeting the UV-induced immunosuppression pathway, and using a large population based study of NMSC, we have investigated the risk associated with functional variants in 10 genes (IL10, IL4, IL4R, TNF, TNFR2, HTR2A, HRH2, IL12B, PTGS2, and HAL). The most prominent single genetic effect was observed for IL10. There was increasing risk for both basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) with increasing number of variant IL10 haplotypes (BCC: ptrend = 0.0048; SCC: ptrend = 0.031). Having two IL10 GC haplotypes was associated with increased odds ratios of BCC and SCC (ORBCC = 1.5, 95% CI 1.1–1.9; ORSCC = 1.4, 95% CI 1.0–1.9), and these associations were largely confined to women (ORBCC = 2.2, 95% CI 1.4–3.4; SCC: ORSCC = 1.8, 95% CI 1.1–3.0). To examine how combinations of these variants contribute to risk of BCC and SCC, we used multifactor dimensionality reduction (MDR) and classification and regression trees (CART). Results from both of these methods found that in men, a combination of skin type, burns, IL10, IL4R, and possibly TNFR2 were important in both BCC and SCC. In women, skin type, burns, and IL10 were the most critical risk factors in SCC, with risk of BCC involving these same factors plus genetic variants in HTR2A, IL12B and IL4R. These data suggest differential genetic susceptibility to UV-induced immune suppression and skin cancer risk by gender

RNASEL and MIR146A SNP-SNP Interaction as a Susceptibility Factor for Non-Melanoma Skin Cancer

Immunity and inflammatory pathways are important in the genesis of non-melanoma skin cancers (NMSC). Functional genetic variation in immune modulators has the potential to affect disease etiology. We investigated associations between common variants in two key regulators, MIR146A and RNASEL, and their relation to NMSCs. Using a large population-based case-control study of basal cell (BCC) and squamous cell carcinoma (SCC), we investigated the impact of MIR146A SNP rs2910164 on cancer risk, and interaction with a SNP in one of its putative targets (RNASEL, rs486907). To examine associations between genotype and BCC and SCC, occurrence odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using unconditional logistic regression, accounting for multiple confounding factors. We did not observe an overall change in the odds ratios for SCC or BCC among individuals carrying either of the RNASEL or MIR146A variants compared with those who were wild type at these loci. However, there was a sex-specific association between BCC and MIR146A in women (ORGC = 0.73, [95%CI = 0.52–1.03]; ORCC = 0.29, [95% CI = 0.14–0.61], p-trend\u3c0.001), and a reduction in risk, albeit not statistically significant, associated with RNASEL and SCC in men (ORAG = 0.88, [95%CI = 0.65–1.19]; ORAA = 0.68, [95%CI = 0.43–1.08], p-trend = 0.10). Most striking was the strong interaction between the two genes. Among individuals carrying variant alleles of both rs2910164 and rs486907, we observed inverse relationships with SCC (ORSCC = 0.56, [95%CI = 0.38–0.81], p-interaction = 0.012) and BCC (ORBCC = 0.57, [95%CI = 0.40–0.80], p-interaction = 0.005). Our results suggest that genetic variation in immune and inflammatory regulators may influence susceptibility to NMSC, and novel SNP-SNP interaction for a microRNA and its target. These data suggest that RNASEL, an enzyme involved in RNA turnover, is controlled by miR-146a and may be important in NMSC etiology

Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context

Epigenetic control of gene transcription is critical for normal human development and cellular differentiation. While alterations of epigenetic marks such as DNA methylation have been linked to cancers and many other human diseases, interindividual epigenetic variations in normal tissues due to aging, environmental factors, or innate susceptibility are poorly characterized. The plasticity, tissue-specific nature, and variability of gene expression are related to epigenomic states that vary across individuals. Thus, population-based investigations are needed to further our understanding of the fundamental dynamics of normal individual epigenomes. We analyzed 217 non-pathologic human tissues from 10 anatomic sites at 1,413 autosomal CpG loci associated with 773 genes to investigate tissue-specific differences in DNA methylation and to discern how aging and exposures contribute to normal variation in methylation. Methylation profile classes derived from unsupervised modeling were significantly associated with age (P,0.0001) and were significant predictors of tissue origin (P,0.0001). In solid tissues (n = 119) we found striking, highly significant CpG island–dependent correlations between age and methylation; loci in CpG islands gained methylation with age, loci not in CpG islands lost methylation with age (P,0.001), and this pattern was consistent across tissues and in an analysis of blood-derived DNA. Our data clearly demonstrate age- and exposure-related differences in tissue-specific methylation and significant age-associated methylation patterns which are CpG island context-dependent. This work provides novel insight into the role of aging and the environment in susceptibility to diseases such as cancer and critically informs the field of epigenomics by providing evidence of epigenetic dysregulation by age-related methylation alterations. Collectively we reveal key issues to consider both in the construction of reference and disease-related epigenomes and in the interpretation of potentially pathologically important alterations

Smoking-gun signatures of little Higgs models

Little Higgs models predict new gauge bosons, fermions and scalars at the TeV scale that stabilize the Higgs mass against quadratically divergent one-loop radiative corrections. We categorize the many little Higgs models into two classes based on the structure of the extended electroweak gauge group and examine the experimental signatures that identify the little Higgs mechanism in addition to those that identify the particular little Higgs model. We find that by examining the properties of the new heavy fermion(s) at the LHC, one can distinguish the structure of the top quark mass generation mechanism and test the little Higgs mechanism in the top sector. Similarly, by studying the couplings of the new gauge bosons to the light Higgs boson and to the Standard Model fermions, one can confirm the little Higgs mechanism and determine the structure of the extended electroweak gauge group.Comment: 59 pages, 10 figures. v2: refs added, typos fixed, JHEP versio

Global Methylation in Exposure Biology and Translational Medical Science

Background: Many groups are actively investigating how the epigenetic state relates to environmental exposures and development of disease, including cancer. There are myriad choices for capturing and measuring the epigenetic state of a tissue, ranging from assessing the total methyl-CpG content to array-based platforms that simultaneously probe hundreds of thousands of CpG loci. There is an emerging literature that uses CpG methylation at repetitive sequences, including LINE-1 (long interspersed nuclear element-1) elements, to capture the epigenomic state

Breast Cancer DNA Methylation Profiles Are Associated with Tumor Size and Alcohol and Folate Intake

Although tumor size and lymph node involvement are the current cornerstones of breast cancer prognosis, they have not been extensively explored in relation to tumor methylation attributes in conjunction with other tumor and patient dietary and hormonal characteristics. Using primary breast tumors from 162 (AJCC stage I-IV) women from the Kaiser Division of Research Pathways Study and the Illumina GoldenGate methylation bead-array platform, we measured 1,413 autosomal CpG loci associated with 773 cancer-related genes and validated select CpG loci with Sequenom EpiTYPER. Tumor grade, size, estrogen and progesterone receptor status, and triple negative status were significantly (Q-values \u3c0.05) associated with altered methylation of 209, 74, 183, 69, and 130 loci, respectively. Unsupervised clustering, using a recursively partitioned mixture model (RPMM), of all autosomal CpG loci revealed eight distinct methylation classes. Methylation class membership was significantly associated with patient race (P\u3c0.02) and tumor size (P\u3c0.001) in univariate tests. Using multinomial logistic regression to adjust for potential confounders, patient age and tumor size, as well as known disease risk factors of alcohol intake and total dietary folate, were all significantly (P\u3c0.0001) associated with methylation class membership. Breast cancer prognostic characteristics and risk-related exposures appear to be associated with gene-specific tumor methylation, as well as overall methylation patterns