The genomic signature of trait-associated variants

BACKGROUND: Genome-wide association studies have identified thousands of SNP variants associated with hundreds of phenotypes. For most associations the causal variants and the molecular mechanisms underlying pathogenesis remain unknown. Exploration of the underlying functional annotations of trait-associated loci has thrown some light on their potential roles in pathogenesis. However, there are some shortcomings of the methods used to date, which may undermine efforts to prioritize variants for further analyses. Here, we introduce and apply novel methods to rigorously identify annotation classes showing enrichment or depletion of trait-associated variants taking into account the underlying associations due to co-location of different functional annotations and linkage disequilibrium. RESULTS: We assessed enrichment and depletion of variants in publicly available annotation classes such as genic regions, regulatory features, measures of conservation, and patterns of histone modifications. We used logistic regression to build a multivariate model that identified the most influential functional annotations for trait-association status of genome-wide significant variants. SNPs associated with all of the enriched annotations were 8 times more likely to be trait-associated variants than SNPs annotated with none of them. Annotations associated with chromatin state together with prior knowledge of the existence of a local expression QTL (eQTL) were the most important factors in the final logistic regression model. Surprisingly, despite the widespread use of evolutionary conservation to prioritize variants for study we find only modest enrichment of trait-associated SNPs in conserved regions. CONCLUSION: We established odds ratios of functional annotations that are more likely to contain significantly trait-associated SNPs, for the purpose of prioritizing GWAS hits for further studies. Additionally, we estimated the relative and combined influence of the different genomic annotations, which may facilitate future prioritization methods by adding substantial information

Thermodynamics and structure of self-assembled networks

We study a generic model of self-assembling chains which can branch and form networks with branching points (junctions) of arbitrary functionality. The physical realizations include physical gels, wormlike micells, dipolar fluids and microemulsions. The model maps the partition function of a solution of branched, self-assembling, mutually avoiding clusters onto that of a Heisenberg magnet in the mathematical limit of zero spin components. The model is solved in the mean field approximation. It is found that despite the absence of any specific interaction between the chains, the entropy of the junctions induces an effective attraction between the monomers, which in the case of three-fold junctions leads to a first order reentrant phase separation between a dilute phase consisting mainly of single chains, and a dense network, or two network phases. Independent of the phase separation, we predict the percolation (connectivity) transition at which an infinite network is formed that partially overlaps with the first-order transition. The percolation transition is a continuous, non thermodynamic transition that describes a change in the topology of the system. Our treatment which predicts both the thermodynamic phase equilibria as well as the spatial correlations in the system allows us to treat both the phase separation and the percolation threshold within the same framework. The density-density correlation correlation has a usual Ornstein-Zernicke form at low monomer densities. At higher densities, a peak emerges in the structure factor, signifying an onset of medium-range order in the system. Implications of the results for different physical systems are discussed.Comment: Submitted to Phys. Rev.

Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals

Artificial immune systems

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self or nonself substances. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years

Midgut microbiota of the malaria mosquito vector Anopheles gambiae and Interactions with plasmodium falciparum Infection

The susceptibility of Anopheles mosquitoes to Plasmodium infections relies on complex interactions between the insect vector and the malaria parasite. A number of studies have shown that the mosquito innate immune responses play an important role in controlling the malaria infection and that the strength of parasite clearance is under genetic control, but little is known about the influence of environmental factors on the transmission success. We present here evidence that the composition of the vector gut microbiota is one of the major components that determine the outcome of mosquito infections. A. gambiae mosquitoes collected in natural breeding sites from Cameroon were experimentally challenged with a wild P. falciparum isolate, and their gut bacterial content was submitted for pyrosequencing analysis. The meta-taxogenomic approach revealed a broader richness of the midgut bacterial flora than previously described. Unexpectedly, the majority of bacterial species were found in only a small proportion of mosquitoes, and only 20 genera were shared by 80% of individuals. We show that observed differences in gut bacterial flora of adult mosquitoes is a result of breeding in distinct sites, suggesting that the native aquatic source where larvae were grown determines the composition of the midgut microbiota. Importantly, the abundance of Enterobacteriaceae in the mosquito midgut correlates significantly with the Plasmodium infection status. This striking relationship highlights the role of natural gut environment in parasite transmission. Deciphering microbe-pathogen interactions offers new perspectives to control disease transmission.Institut de Recherche pour le Developpement (IRD); French Agence Nationale pour la Recherche [ANR-11-BSV7-009-01]; European Community [242095, 223601]info:eu-repo/semantics/publishedVersio

Investigating the balance between goal-directed and habitual control in experimental and real-life settings

Do people differ in their propensity to form habits? The current study related individual differences in habitual performance on the slips-of-action task to habit formation in real life. To this end, we developed a novel key-cover procedure that controls for the amount of repetition and motivation within a naturalistic setting. Participants received a key cover for the key to their home, which after several weeks was switched with a key cover that was previously attached to a dummy key. Participants recorded effort, time, attention, and mistakes in the key-selection process. Results were in line with established properties of habits, as attention decreased in the learning phase, yet effort, time, and mistakes increased after the key-cover switch. Performance on the slips-of-action task correlated negatively with changes in attention in the real-life key-cover task. This negative correlation may reflect that flexible behavioral adjustment requires more attention in people with a relatively weak goal-directed system

Ising Universality in Three Dimensions: A Monte Carlo Study

We investigate three Ising models on the simple cubic lattice by means of Monte Carlo methods and finite-size scaling. These models are the spin-1/2 Ising model with nearest-neighbor interactions, a spin-1/2 model with nearest-neighbor and third-neighbor interactions, and a spin-1 model with nearest-neighbor interactions. The results are in accurate agreement with the hypothesis of universality. Analysis of the finite-size scaling behavior reveals corrections beyond those caused by the leading irrelevant scaling field. We find that the correction-to-scaling amplitudes are strongly dependent on the introduction of further-neighbor interactions or a third spin state. In a spin-1 Ising model, these corrections appear to be very small. This is very helpful for the determination of the universal constants of the Ising model. The renormalization exponents of the Ising model are determined as y_t = 1.587 (2), y_h = 2.4815 (15) and y_i = -0.82 (6). The universal ratio Q = ^2/ is equal to 0.6233 (4) for periodic systems with cubic symmetry. The critical point of the nearest-neighbor spin-1/2 model is K_c=0.2216546 (10).Comment: 25 pages, uuencoded compressed PostScript file (to appear in Journal of Physics A

Helping your partner with chronic pain: the importance of helping motivation, received social support, and its timeliness

Objective Like all intentional acts, social support provision varies with respect to its underlying motives. Greater autonomous or volitional motives (e.g., enjoyment, full commitment) to help individuals with chronic pain (ICPs) are associated with greater well-being benefits for the latter, as indexed by improved satisfaction of their psychological needs for autonomy, competence, and relatedness. The present study investigates the processes explaining why partners’ autonomous or volitional helping motivation yields these benefits. Methods A total of 134 couples, where at least one partner had chronic pain, completed a 14-day diary. Partners reported on their daily helping motives, whereas ICPs reported on their daily received support, timing of help, need-based experiences, and pain. Results On days when partners provided help for volitional motives, ICPs indicated receiving more help, which partially accounted for the effect of autonomous helping motivation on ICP need-based experiences. Timing of help moderated the effects of daily received support on ICP need-based experiences. Conclusions Findings highlight the importance of ICPs of receiving support in general and the role of timing in particular, which especially matters when there is little support being received.info:eu-repo/semantics/acceptedVersio