Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants

Background: One of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age-standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are affecting the number of adults with diabetes.Methods: We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence—defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs—in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue.Findings: We used data from 751 studies including 4?372?000 adults from 146 of the 200 countries we make estimates for. Global age-standardised diabetes prevalence increased from 4·3% (95% credible interval 2·4–7·0) in 1980 to 9·0% (7·2–11·1) in 2014 in men, and from 5·0% (2·9–7·9) to 7·9% (6·4–9·7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28·5% due to the rise in prevalence, 39·7% due to population growth and ageing, and 31·8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalence rose because of ageing of the population. By contrast, age-standardised adult prevalence rose by 15 percentage points in men and women in Polynesia and Micronesia. In 2014, American Samoa had the highest national prevalence of diabetes (>30% in both sexes), with age-standardised adult prevalence also higher than 25% in some other islands in Polynesia and Micronesia. If post-2000 trends continue, the probability of meeting the global target of halting the rise in the prevalence of diabetes by 2025 at the 2010 level worldwide is lower than 1% for men and is 1% for women. Only nine countries for men and 29 countries for women, mostly in western Europe, have a 50% or higher probability of meeting the global target.Interpretation: Since 1980, age-standardised diabetes prevalence in adults has increased, or at best remained unchanged, in every country. Together with population growth and ageing, this rise has led to a near quadrupling of the number of adults with diabetes worldwide. The burden of diabetes, both in terms of prevalence and number of adults affected, has increased faster in low-income and middle-income countries than in high-income countries

Increased Expression of the Δ133p53β Isoform Enhances Brain Metastasis

The Δ133p53β isoform is increased in many primary tumors and has many tumor-promoting properties that contribute to increased proliferation, migration and inflammation. Here we investigated whether Δ133p53β contributed to some of the most aggressive tumors that had metastasized to the brain. Δ133p53β mRNA expression was measured in lung, breast, melanoma, colorectal metastases and, where available, the matched primary tumor. The presence of Δ133p53β expression was associated with the time for the primary tumor to metastasize and overall survival once the tumor was detected in the brain. Δ133p53β was present in over 50% of lung, breast, melanoma and colorectal metastases to the brain. It was also increased in the brain metastases compared with the matched primary tumor. Brain metastases with Δ133p53β expressed were associated with a reduced time for the primary tumor to metastasize to the brain compared with tumors with no Δ133p53β expression. In-vitro-based analyses in Δ133p53β-expressing cells showed increased cancer-promoting proteins on the cell surface and increased downstream p-AKT and p-MAPK signaling. Δ133p53β-expressing cells also invaded more readily across a mock blood–brain barrier. Together these data suggested that Δ133p53β contributes to brain metastases by making cells more likely to invade the brain

GRIP1-associated SET-domain methyltransferase in glucocorticoid receptor target gene expression

Transcriptional regulators such as the glucocorticoid receptor (GR) recruit multiple cofactors to activate or repress transcription. Although most cofactors are intrinsically bifunctional, little is known about the molecular mechanisms dictating the specific polarity of regulation. Furthermore, chromatin modifications thought to be confined to silent loci appear in actively transcribed genes suggesting that similar enzymatic activities may mediate constitutive and transient chromatin states. GRIP1, a GR ligand-dependent coregulator of the p160 family can potentiate or inhibit transcription but the molecular contexts and mechanisms that enable GRIP1 corepressor activity are poorly understood. In a yeast 2-hybrid screen with GRIP1 repression domain (RD)-containing fragment, we repeatedly isolated the C-terminal region of a SET domain-containing protein subsequently identified as histone H4 lysine 20 trimethyltransferase, Suv4-20h1. We cloned a full-length Suv4-20h1 and dissected its interaction with GRIP1 in yeast, in vitro, and in mammalian cells. Strict nuclear localization and high salt concentration required for Suv4-20h1 extraction were consistent with its tight association with chromatin. Overexpression of Suv4-20h1 in human U2OS and A549 cells expressing integrated and endogenous GR, respectively, antagonized ligand-dependent induction of a subset of GR target genes, whereas Suv4-20h1 siRNA-mediated depletion had a reciprocal effect. Inhibition of GR transactivation required both the GRIP1 interacting region of Suv4-20h1 and its catalytic activity. Thus, Suv4-20h1 known exclusively as a factor involved in constitutive heterochromatin maintenance, actively participates in hormone-dependent transcriptional regulation affecting GR target gene expression in a promoter- and cell type-specific manner