The application of predictive modelling for determining bio-environmental factors affecting the distribution of blackflies (Diptera: Simuliidae) in the Gilgel Gibe watershed in Southwest Ethiopia

Blackflies are important macroinvertebrate groups from a public health as well as ecological point of view. Determining the biological and environmental factors favouring or inhibiting the existence of blackflies could facilitate biomonitoring of rivers as well as control of disease vectors. The combined use of different predictive modelling techniques is known to improve identification of presence/absence and abundance of taxa in a given habitat. This approach enables better identification of the suitable habitat conditions or environmental constraints of a given taxon. Simuliidae larvae are important biological indicators as they are abundant in tropical aquatic ecosystems. Some of the blackfly groups are also important disease vectors in poor tropical countries. Our investigations aim to establish a combination of models able to identify the environmental factors and macroinvertebrate organisms that are favourable or inhibiting blackfly larvae existence in aquatic ecosystems. The models developed using macroinvertebrate predictors showed better performance than those based on environmental predictors. The identified environmental and macroinvertebrate parameters can be used to determine the distribution of blackflies, which in turn can help control river blindness in endemic tropical places. Through a combination of modelling techniques, a reliable method has been developed that explains environmental and biological relationships with the target organism, and, thus, can serve as a decision support tool for ecological management strategies

Family composition and age at menarche: findings from the international Health Behaviour in School-Aged Children Study

This research was funded by The University of St Andrews and NHS Health Scotland.Background Early menarche has been associated with father absence, stepfather presence and adverse health consequences in later life. This article assesses the association of different family compositions with the age at menarche. Pathways are explored which may explain any association between family characteristics and pubertal timing. Methods Cross-sectional, international data on the age at menarche, family structure and covariates (age, psychosomatic complaints, media consumption, physical activity) were collected from the 2009–2010 Health Behaviour in School-aged Children (HBSC) survey. The sample focuses on 15-year old girls comprising 36,175 individuals across 40 countries in Europe and North America (N = 21,075 for age at menarche). The study examined the association of different family characteristics with age at menarche. Regression and path analyses were applied incorporating multilevel techniques to adjust for the nested nature of data within countries. Results Living with mother (Cohen’s d = .12), father (d = .08), brothers (d = .04) and sisters (d = .06) are independently associated with later age at menarche. Living in a foster home (d = −.16), with ‘someone else’ (d = −.11), stepmother (d = −.10) or stepfather (d = −.06) was associated with earlier menarche. Path models show that up to 89% of these effects can be explained through lifestyle and psychological variables. Conclusions Earlier menarche is reported amongst those with living conditions other than a family consisting of two biological parents. This can partly be explained by girls’ higher Body Mass Index in these families which is a biological determinant of early menarche. Lower physical activity and elevated psychosomatic complaints were also more often found in girls in these family environments.Publisher PDFPeer reviewe

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease

Lifted graphical models: a survey

Lifted graphical models provide a language for expressing dependencies between different types of entities, their attributes, and their diverse relations, as well as techniques for probabilistic reasoning in such multi-relational domains. In this survey, we review a general form for a lifted graphical model, a par-factor graph, and show how a number of existing statistical relational representations map to this formalism. We discuss inference algorithms, including lifted inference algorithms, that efficiently compute the answers to probabilistic queries over such models. We also review work in learning lifted graphical models from data. There is a growing need for statistical relational models (whether they go by that name or another), as we are inundated with data which is a mix of structured and unstructured, with entities and relations extracted in a noisy manner from text, and with the need to reason effectively with this data. We hope that this synthesis of ideas from many different research groups will provide an accessible starting point for new researchers in this expanding field

Histone H3 globular domain acetylation identifies a new class of enhancers

Histone acetylation is generally associated with active chromatin, but most studies have focused on the acetylation of histone tails. Various histone H3 and H4 tail acetylations mark the promoters of active genes. These modifications include acetylation of histone H3 at lysine 27 (H3K27ac), which blocks Polycomb-mediated trimethylation of H3K27 (H3K27me3). H3K27ac is also widely used to identify active enhancers, and the assumption has been that profiling H3K27ac is a comprehensive way of cataloguing the set of active enhancers in mammalian cell types. Here we show that acetylation of lysine residues in the globular domain of histone H3 (lysine 64 (H3K64ac) and lysine 122 (H3K122ac)) marks active gene promoters and also a subset of active enhancers. Moreover, we find a new class of active functional enhancers that is marked by H3K122ac but lacks H3K27ac. This work suggests that, to identify enhancers, a more comprehensive analysis of histone acetylation is required than has previously been considered

An improved microRNA annotation of the canine genome

The domestic dog, Canis familiaris, is a valuable model for studying human diseases. The publication of the latest Canine genome build and annotation, CanFam3.1 provides an opportunity to enhance our understanding of gene regulation across tissues in the dog model system. In this study, we used the latest dog genome assembly and small RNA sequencing data from 9 different dog tissues to predict novel miRNAs in the dog genome, as well as to annotate conserved miRNAs from the miRBase database that were missing from the current dog annotation. We used both miRCat and miRDeep2 algorithms to computationally predict miRNA loci. The resulting, putative hairpin sequences were analysed in order to discard false positives, based on predicted secondary structures and patterns of small RNA read alignments. Results were further divided into high and low confidence miRNAs, using the same criteria. We generated tissue specific expression profiles for the resulting set of 811 loci: 720 conserved miRNAs, (207 of which had not been previously annotated in the dog genome) and 91 novel miRNA loci. Comparative analyses revealed 8 putative homologues of some novel miRNA in ferret, and one in microbat. All miRNAs were also classified into the genic and intergenic categories, based on the Ensembl RefSeq gene annotation for CanFam3.1. This additionally allowed us to identify four previously undescribed MiRtrons among our total set of miRNAs. We additionally annotated piRNAs, using proTRAC on the same input data. We thus identified 263 putative clusters, most of which (211 clusters) were found to be expressed in testis. Our results represent an important improvement of the dog genome annotation, paving the way to further research on the evolution of gene regulation, as well as on the contribution of post-transcriptional regulation to pathological conditions

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

Transmembrane protein PERP is a component of tessellate junctions and of other junctional and non-junctional plasma membrane regions in diverse epithelial and epithelium-derived cells

Protein PERP (p53 apoptosis effector related to PMP-22) is a small (21.4 kDa) transmembrane polypeptide with an amino acid sequence indicative of a tetraspanin character. It is enriched in the plasma membrane and apparently contributes to cell-cell contacts. Hitherto, it has been reported to be exclusively a component of desmosomes of some stratified epithelia. However, by using a series of newly generated mono- and polyclonal antibodies, we show that protein PERP is not only present in all kinds of stratified epithelia but also occurs in simple, columnar, complex and transitional epithelia, in various types of squamous metaplasia and epithelium-derived tumors, in diverse epithelium-derived cell cultures and in myocardial tissue. Immunofluorescence and immunoelectron microscopy allow us to localize PERP predominantly in small intradesmosomal locations and in variously sized, junction-like peri- and interdesmosomal regions (“tessellate junctions”), mostly in mosaic or amalgamated combinations with other molecules believed, to date, to be exclusive components of tight and adherens junctions. In the heart, PERP is a major component of the composite junctions of the intercalated disks connecting cardiomyocytes. Finally, protein PERP is a cobblestone-like general component of special plasma membrane regions such as the bile canaliculi of liver and subapical-to-lateral zones of diverse columnar epithelia and upper urothelial cell layers. We discuss possible organizational and architectonic functions of protein PERP and its potential value as an immunohistochemical diagnostic marker

Genetic variation and exercise-induced muscle damage: implications for athletic performance, injury and ageing.

Prolonged unaccustomed exercise involving muscle lengthening (eccentric) actions can result in ultrastructural muscle disruption, impaired excitation-contraction coupling, inflammation and muscle protein degradation. This process is associated with delayed onset muscle soreness and is referred to as exercise-induced muscle damage. Although a certain amount of muscle damage may be necessary for adaptation to occur, excessive damage or inadequate recovery from exercise-induced muscle damage can increase injury risk, particularly in older individuals, who experience more damage and require longer to recover from muscle damaging exercise than younger adults. Furthermore, it is apparent that inter-individual variation exists in the response to exercise-induced muscle damage, and there is evidence that genetic variability may play a key role. Although this area of research is in its infancy, certain gene variations, or polymorphisms have been associated with exercise-induced muscle damage (i.e. individuals with certain genotypes experience greater muscle damage, and require longer recovery, following strenuous exercise). These polymorphisms include ACTN3 (R577X, rs1815739), TNF (-308 G>A, rs1800629), IL6 (-174 G>C, rs1800795), and IGF2 (ApaI, 17200 G>A, rs680). Knowing how someone is likely to respond to a particular type of exercise could help coaches/practitioners individualise the exercise training of their athletes/patients, thus maximising recovery and adaptation, while reducing overload-associated injury risk. The purpose of this review is to provide a critical analysis of the literature concerning gene polymorphisms associated with exercise-induced muscle damage, both in young and older individuals, and to highlight the potential mechanisms underpinning these associations, thus providing a better understanding of exercise-induced muscle damage

Direct Repeat 6 from Human Herpesvirus-6B Encodes a Nuclear Protein that Forms a Complex with the Viral DNA Processivity Factor p41

The SalI-L fragment from human herpesvirus 6A (HHV-6A) encodes a protein DR7 that has been reported to produce fibrosarcomas when injected into nude mice, to transform NIH3T3 cells, and to interact with and inhibit the function of p53. The homologous gene in HHV-6B is dr6. Since p53 is deregulated in both HHV-6A and -6B, we characterized the expression of dr6 mRNA and the localization of the translated protein during HHV-6B infection of HCT116 cells. Expression of mRNA from dr6 was inhibited by cycloheximide and partly by phosphonoacetic acid, a known characteristic of herpesvirus early/late genes. DR6 could be detected as a nuclear protein at 24 hpi and accumulated to high levels at 48 and 72 hpi. DR6 located in dots resembling viral replication compartments. Furthermore, a novel interaction between DR6 and the viral DNA processivity factor, p41, could be detected by confocal microscopy and by co-immunoprecipitation analysis. In contrast, DR6 and p53 were found at distinct subcellular locations. Together, our data imply a novel function of DR6 during HHV-6B replication